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facelessuser/soupsieve | soupsieve/util.py | lower | def lower(string):
"""Lower."""
new_string = []
for c in string:
o = ord(c)
new_string.append(chr(o + 32) if UC_A <= o <= UC_Z else c)
return ''.join(new_string) | python | def lower(string):
"""Lower."""
new_string = []
for c in string:
o = ord(c)
new_string.append(chr(o + 32) if UC_A <= o <= UC_Z else c)
return ''.join(new_string) | Lower. | https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/util.py#L45-L52 |
facelessuser/soupsieve | soupsieve/util.py | upper | def upper(string): # pragma: no cover
"""Lower."""
new_string = []
for c in string:
o = ord(c)
new_string.append(chr(o - 32) if LC_A <= o <= LC_Z else c)
return ''.join(new_string) | python | def upper(string): # pragma: no cover
"""Lower."""
new_string = []
for c in string:
o = ord(c)
new_string.append(chr(o - 32) if LC_A <= o <= LC_Z else c)
return ''.join(new_string) | Lower. | https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/util.py#L55-L62 |
facelessuser/soupsieve | soupsieve/util.py | uord | def uord(c):
"""Get Unicode ordinal."""
if len(c) == 2: # pragma: no cover
high, low = [ord(p) for p in c]
ordinal = (high - 0xD800) * 0x400 + low - 0xDC00 + 0x10000
else:
ordinal = ord(c)
return ordinal | python | def uord(c):
"""Get Unicode ordinal."""
if len(c) == 2: # pragma: no cover
high, low = [ord(p) for p in c]
ordinal = (high - 0xD800) * 0x400 + low - 0xDC00 + 0x10000
else:
ordinal = ord(c)
return ordinal | Get Unicode ordinal. | https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/util.py#L74-L83 |
facelessuser/soupsieve | soupsieve/util.py | deprecated | def deprecated(message, stacklevel=2): # pragma: no cover
"""
Raise a `DeprecationWarning` when wrapped function/method is called.
Borrowed from https://stackoverflow.com/a/48632082/866026
"""
def _decorator(func):
@wraps(func)
def _func(*args, **kwargs):
warnings.warn(
"'{}' is deprecated. {}".format(func.__name__, message),
category=DeprecationWarning,
stacklevel=stacklevel
)
return func(*args, **kwargs)
return _func
return _decorator | python | def deprecated(message, stacklevel=2): # pragma: no cover
"""
Raise a `DeprecationWarning` when wrapped function/method is called.
Borrowed from https://stackoverflow.com/a/48632082/866026
"""
def _decorator(func):
@wraps(func)
def _func(*args, **kwargs):
warnings.warn(
"'{}' is deprecated. {}".format(func.__name__, message),
category=DeprecationWarning,
stacklevel=stacklevel
)
return func(*args, **kwargs)
return _func
return _decorator | Raise a `DeprecationWarning` when wrapped function/method is called.
Borrowed from https://stackoverflow.com/a/48632082/866026 | https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/util.py#L104-L121 |
facelessuser/soupsieve | soupsieve/util.py | warn_deprecated | def warn_deprecated(message, stacklevel=2): # pragma: no cover
"""Warn deprecated."""
warnings.warn(
message,
category=DeprecationWarning,
stacklevel=stacklevel
) | python | def warn_deprecated(message, stacklevel=2): # pragma: no cover
"""Warn deprecated."""
warnings.warn(
message,
category=DeprecationWarning,
stacklevel=stacklevel
) | Warn deprecated. | https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/util.py#L124-L131 |
facelessuser/soupsieve | soupsieve/util.py | get_pattern_context | def get_pattern_context(pattern, index):
"""Get the pattern context."""
last = 0
current_line = 1
col = 1
text = []
line = 1
# Split pattern by newline and handle the text before the newline
for m in RE_PATTERN_LINE_SPLIT.finditer(pattern):
linetext = pattern[last:m.start(0)]
if not len(m.group(0)) and not len(text):
indent = ''
offset = -1
col = index - last + 1
elif last <= index < m.end(0):
indent = '--> '
offset = (-1 if index > m.start(0) else 0) + 3
col = index - last + 1
else:
indent = ' '
offset = None
if len(text):
# Regardless of whether we are presented with `\r\n`, `\r`, or `\n`,
# we will render the output with just `\n`. We will still log the column
# correctly though.
text.append('\n')
text.append('{}{}'.format(indent, linetext))
if offset is not None:
text.append('\n')
text.append(' ' * (col + offset) + '^')
line = current_line
current_line += 1
last = m.end(0)
return ''.join(text), line, col | python | def get_pattern_context(pattern, index):
"""Get the pattern context."""
last = 0
current_line = 1
col = 1
text = []
line = 1
# Split pattern by newline and handle the text before the newline
for m in RE_PATTERN_LINE_SPLIT.finditer(pattern):
linetext = pattern[last:m.start(0)]
if not len(m.group(0)) and not len(text):
indent = ''
offset = -1
col = index - last + 1
elif last <= index < m.end(0):
indent = '--> '
offset = (-1 if index > m.start(0) else 0) + 3
col = index - last + 1
else:
indent = ' '
offset = None
if len(text):
# Regardless of whether we are presented with `\r\n`, `\r`, or `\n`,
# we will render the output with just `\n`. We will still log the column
# correctly though.
text.append('\n')
text.append('{}{}'.format(indent, linetext))
if offset is not None:
text.append('\n')
text.append(' ' * (col + offset) + '^')
line = current_line
current_line += 1
last = m.end(0)
return ''.join(text), line, col | Get the pattern context. | https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/util.py#L134-L171 |
facelessuser/soupsieve | soupsieve/util.py | warn_quirks | def warn_quirks(message, recommend, pattern, index):
"""Warn quirks."""
import traceback
import bs4 # noqa: F401
# Acquire source code line context
paths = (MODULE, sys.modules['bs4'].__path__[0])
tb = traceback.extract_stack()
previous = None
filename = None
lineno = None
for entry in tb:
if (PY35 and entry.filename.startswith(paths)) or (not PY35 and entry[0].startswith(paths)):
break
previous = entry
if previous:
filename = previous.filename if PY35 else previous[0]
lineno = previous.lineno if PY35 else previous[1]
# Format pattern to show line and column position
context, line = get_pattern_context(pattern, index)[0:2]
# Display warning
warnings.warn_explicit(
"\nCSS selector pattern:\n" +
" {}\n".format(message) +
" This behavior is only allowed temporarily for Beautiful Soup's transition to Soup Sieve.\n" +
" In order to confrom to the CSS spec, {}\n".format(recommend) +
" It is strongly recommended the selector be altered to conform to the CSS spec " +
"as an exception will be raised for this case in the future.\n" +
"pattern line {}:\n{}".format(line, context),
QuirksWarning,
filename,
lineno
) | python | def warn_quirks(message, recommend, pattern, index):
"""Warn quirks."""
import traceback
import bs4 # noqa: F401
# Acquire source code line context
paths = (MODULE, sys.modules['bs4'].__path__[0])
tb = traceback.extract_stack()
previous = None
filename = None
lineno = None
for entry in tb:
if (PY35 and entry.filename.startswith(paths)) or (not PY35 and entry[0].startswith(paths)):
break
previous = entry
if previous:
filename = previous.filename if PY35 else previous[0]
lineno = previous.lineno if PY35 else previous[1]
# Format pattern to show line and column position
context, line = get_pattern_context(pattern, index)[0:2]
# Display warning
warnings.warn_explicit(
"\nCSS selector pattern:\n" +
" {}\n".format(message) +
" This behavior is only allowed temporarily for Beautiful Soup's transition to Soup Sieve.\n" +
" In order to confrom to the CSS spec, {}\n".format(recommend) +
" It is strongly recommended the selector be altered to conform to the CSS spec " +
"as an exception will be raised for this case in the future.\n" +
"pattern line {}:\n{}".format(line, context),
QuirksWarning,
filename,
lineno
) | Warn quirks. | https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/util.py#L178-L213 |
facelessuser/soupsieve | soupsieve/__init__.py | compile | def compile(pattern, namespaces=None, flags=0, **kwargs): # noqa: A001
"""Compile CSS pattern."""
if namespaces is not None:
namespaces = ct.Namespaces(**namespaces)
custom = kwargs.get('custom')
if custom is not None:
custom = ct.CustomSelectors(**custom)
if isinstance(pattern, SoupSieve):
if flags:
raise ValueError("Cannot process 'flags' argument on a compiled selector list")
elif namespaces is not None:
raise ValueError("Cannot process 'namespaces' argument on a compiled selector list")
elif custom is not None:
raise ValueError("Cannot process 'custom' argument on a compiled selector list")
return pattern
return cp._cached_css_compile(pattern, namespaces, custom, flags) | python | def compile(pattern, namespaces=None, flags=0, **kwargs): # noqa: A001
"""Compile CSS pattern."""
if namespaces is not None:
namespaces = ct.Namespaces(**namespaces)
custom = kwargs.get('custom')
if custom is not None:
custom = ct.CustomSelectors(**custom)
if isinstance(pattern, SoupSieve):
if flags:
raise ValueError("Cannot process 'flags' argument on a compiled selector list")
elif namespaces is not None:
raise ValueError("Cannot process 'namespaces' argument on a compiled selector list")
elif custom is not None:
raise ValueError("Cannot process 'custom' argument on a compiled selector list")
return pattern
return cp._cached_css_compile(pattern, namespaces, custom, flags) | Compile CSS pattern. | https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/__init__.py#L44-L63 |
facelessuser/soupsieve | soupsieve/__init__.py | closest | def closest(select, tag, namespaces=None, flags=0, **kwargs):
"""Match closest ancestor."""
return compile(select, namespaces, flags, **kwargs).closest(tag) | python | def closest(select, tag, namespaces=None, flags=0, **kwargs):
"""Match closest ancestor."""
return compile(select, namespaces, flags, **kwargs).closest(tag) | Match closest ancestor. | https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/__init__.py#L72-L75 |
facelessuser/soupsieve | soupsieve/__init__.py | match | def match(select, tag, namespaces=None, flags=0, **kwargs):
"""Match node."""
return compile(select, namespaces, flags, **kwargs).match(tag) | python | def match(select, tag, namespaces=None, flags=0, **kwargs):
"""Match node."""
return compile(select, namespaces, flags, **kwargs).match(tag) | Match node. | https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/__init__.py#L78-L81 |
facelessuser/soupsieve | soupsieve/__init__.py | filter | def filter(select, iterable, namespaces=None, flags=0, **kwargs): # noqa: A001
"""Filter list of nodes."""
return compile(select, namespaces, flags, **kwargs).filter(iterable) | python | def filter(select, iterable, namespaces=None, flags=0, **kwargs): # noqa: A001
"""Filter list of nodes."""
return compile(select, namespaces, flags, **kwargs).filter(iterable) | Filter list of nodes. | https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/__init__.py#L84-L87 |
facelessuser/soupsieve | soupsieve/__init__.py | comments | def comments(tag, limit=0, flags=0, **kwargs):
"""Get comments only."""
return [comment for comment in cm.CommentsMatch(tag).get_comments(limit)] | python | def comments(tag, limit=0, flags=0, **kwargs):
"""Get comments only."""
return [comment for comment in cm.CommentsMatch(tag).get_comments(limit)] | Get comments only. | https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/__init__.py#L91-L94 |
facelessuser/soupsieve | soupsieve/__init__.py | select_one | def select_one(select, tag, namespaces=None, flags=0, **kwargs):
"""Select a single tag."""
return compile(select, namespaces, flags, **kwargs).select_one(tag) | python | def select_one(select, tag, namespaces=None, flags=0, **kwargs):
"""Select a single tag."""
return compile(select, namespaces, flags, **kwargs).select_one(tag) | Select a single tag. | https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/__init__.py#L105-L108 |
facelessuser/soupsieve | soupsieve/__init__.py | select | def select(select, tag, namespaces=None, limit=0, flags=0, **kwargs):
"""Select the specified tags."""
return compile(select, namespaces, flags, **kwargs).select(tag, limit) | python | def select(select, tag, namespaces=None, limit=0, flags=0, **kwargs):
"""Select the specified tags."""
return compile(select, namespaces, flags, **kwargs).select(tag, limit) | Select the specified tags. | https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/__init__.py#L111-L114 |
facelessuser/soupsieve | soupsieve/__init__.py | iselect | def iselect(select, tag, namespaces=None, limit=0, flags=0, **kwargs):
"""Iterate the specified tags."""
for el in compile(select, namespaces, flags, **kwargs).iselect(tag, limit):
yield el | python | def iselect(select, tag, namespaces=None, limit=0, flags=0, **kwargs):
"""Iterate the specified tags."""
for el in compile(select, namespaces, flags, **kwargs).iselect(tag, limit):
yield el | Iterate the specified tags. | https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/__init__.py#L117-L121 |
bigcommerce/bigcommerce-api-python | bigcommerce/resources/base.py | ListableApiResource.all | def all(cls, connection=None, **params):
"""
Returns first page if no params passed in as a list.
"""
request = cls._make_request('GET', cls._get_all_path(), connection, params=params)
return cls._create_object(request, connection=connection) | python | def all(cls, connection=None, **params):
"""
Returns first page if no params passed in as a list.
"""
request = cls._make_request('GET', cls._get_all_path(), connection, params=params)
return cls._create_object(request, connection=connection) | Returns first page if no params passed in as a list. | https://github.com/bigcommerce/bigcommerce-api-python/blob/76a8f5d59fd44a4365f14a5959102e118cf35dee/bigcommerce/resources/base.py#L102-L108 |
bigcommerce/bigcommerce-api-python | bigcommerce/resources/base.py | ListableApiResource.iterall | def iterall(cls, connection=None, **kwargs):
"""
Returns a autopaging generator that yields each object returned one by one.
"""
try:
limit = kwargs['limit']
except KeyError:
limit = None
try:
page = kwargs['page']
except KeyError:
page = None
def _all_responses():
page = 1 # one based
params = kwargs.copy()
while True:
params.update(page=page, limit=250)
rsp = cls._make_request('GET', cls._get_all_path(), connection, params=params)
if rsp:
yield rsp
page += 1
else:
yield [] # needed for case where there is no objects
break
if not (limit or page):
for rsp in _all_responses():
for obj in rsp:
yield cls._create_object(obj, connection=connection)
else:
response = cls._make_request('GET', cls._get_all_path(), connection, params=kwargs)
for obj in cls._create_object(response, connection=connection):
yield obj | python | def iterall(cls, connection=None, **kwargs):
"""
Returns a autopaging generator that yields each object returned one by one.
"""
try:
limit = kwargs['limit']
except KeyError:
limit = None
try:
page = kwargs['page']
except KeyError:
page = None
def _all_responses():
page = 1 # one based
params = kwargs.copy()
while True:
params.update(page=page, limit=250)
rsp = cls._make_request('GET', cls._get_all_path(), connection, params=params)
if rsp:
yield rsp
page += 1
else:
yield [] # needed for case where there is no objects
break
if not (limit or page):
for rsp in _all_responses():
for obj in rsp:
yield cls._create_object(obj, connection=connection)
else:
response = cls._make_request('GET', cls._get_all_path(), connection, params=kwargs)
for obj in cls._create_object(response, connection=connection):
yield obj | Returns a autopaging generator that yields each object returned one by one. | https://github.com/bigcommerce/bigcommerce-api-python/blob/76a8f5d59fd44a4365f14a5959102e118cf35dee/bigcommerce/resources/base.py#L111-L148 |
bigcommerce/bigcommerce-api-python | bigcommerce/connection.py | Connection.get | def get(self, resource="", rid=None, **query):
"""
Retrieves the resource with given id 'rid', or all resources of given type.
Keep in mind that the API returns a list for any query that doesn't specify an ID, even when applying
a limit=1 filter.
Also be aware that float values tend to come back as strings ("2.0000" instead of 2.0)
Keyword arguments can be parsed for filtering the query, for example:
connection.get('products', limit=3, min_price=10.5)
(see Bigcommerce resource documentation).
"""
if rid:
if resource[-1] != '/':
resource += '/'
resource += str(rid)
response = self._run_method('GET', resource, query=query)
return self._handle_response(resource, response) | python | def get(self, resource="", rid=None, **query):
"""
Retrieves the resource with given id 'rid', or all resources of given type.
Keep in mind that the API returns a list for any query that doesn't specify an ID, even when applying
a limit=1 filter.
Also be aware that float values tend to come back as strings ("2.0000" instead of 2.0)
Keyword arguments can be parsed for filtering the query, for example:
connection.get('products', limit=3, min_price=10.5)
(see Bigcommerce resource documentation).
"""
if rid:
if resource[-1] != '/':
resource += '/'
resource += str(rid)
response = self._run_method('GET', resource, query=query)
return self._handle_response(resource, response) | Retrieves the resource with given id 'rid', or all resources of given type.
Keep in mind that the API returns a list for any query that doesn't specify an ID, even when applying
a limit=1 filter.
Also be aware that float values tend to come back as strings ("2.0000" instead of 2.0)
Keyword arguments can be parsed for filtering the query, for example:
connection.get('products', limit=3, min_price=10.5)
(see Bigcommerce resource documentation). | https://github.com/bigcommerce/bigcommerce-api-python/blob/76a8f5d59fd44a4365f14a5959102e118cf35dee/bigcommerce/connection.py#L83-L99 |
bigcommerce/bigcommerce-api-python | bigcommerce/connection.py | Connection.update | def update(self, resource, rid, updates):
"""
Updates the resource with id 'rid' with the given updates dictionary.
"""
if resource[-1] != '/':
resource += '/'
resource += str(rid)
return self.put(resource, data=updates) | python | def update(self, resource, rid, updates):
"""
Updates the resource with id 'rid' with the given updates dictionary.
"""
if resource[-1] != '/':
resource += '/'
resource += str(rid)
return self.put(resource, data=updates) | Updates the resource with id 'rid' with the given updates dictionary. | https://github.com/bigcommerce/bigcommerce-api-python/blob/76a8f5d59fd44a4365f14a5959102e118cf35dee/bigcommerce/connection.py#L101-L108 |
bigcommerce/bigcommerce-api-python | bigcommerce/connection.py | Connection.delete | def delete(self, resource, rid=None): # note that rid can't be 0 - problem?
"""
Deletes the resource with given id 'rid', or all resources of given type if rid is not supplied.
"""
if rid:
if resource[-1] != '/':
resource += '/'
resource += str(rid)
response = self._run_method('DELETE', resource)
return self._handle_response(resource, response, suppress_empty=True) | python | def delete(self, resource, rid=None): # note that rid can't be 0 - problem?
"""
Deletes the resource with given id 'rid', or all resources of given type if rid is not supplied.
"""
if rid:
if resource[-1] != '/':
resource += '/'
resource += str(rid)
response = self._run_method('DELETE', resource)
return self._handle_response(resource, response, suppress_empty=True) | Deletes the resource with given id 'rid', or all resources of given type if rid is not supplied. | https://github.com/bigcommerce/bigcommerce-api-python/blob/76a8f5d59fd44a4365f14a5959102e118cf35dee/bigcommerce/connection.py#L116-L125 |
bigcommerce/bigcommerce-api-python | bigcommerce/connection.py | Connection.put | def put(self, url, data):
"""
Make a PUT request to save data.
data should be a dictionary.
"""
response = self._run_method('PUT', url, data=data)
log.debug("OUTPUT: %s" % response.content)
return self._handle_response(url, response) | python | def put(self, url, data):
"""
Make a PUT request to save data.
data should be a dictionary.
"""
response = self._run_method('PUT', url, data=data)
log.debug("OUTPUT: %s" % response.content)
return self._handle_response(url, response) | Make a PUT request to save data.
data should be a dictionary. | https://github.com/bigcommerce/bigcommerce-api-python/blob/76a8f5d59fd44a4365f14a5959102e118cf35dee/bigcommerce/connection.py#L133-L140 |
bigcommerce/bigcommerce-api-python | bigcommerce/connection.py | Connection.post | def post(self, url, data, headers={}):
"""
POST request for creating new objects.
data should be a dictionary.
"""
response = self._run_method('POST', url, data=data, headers=headers)
return self._handle_response(url, response) | python | def post(self, url, data, headers={}):
"""
POST request for creating new objects.
data should be a dictionary.
"""
response = self._run_method('POST', url, data=data, headers=headers)
return self._handle_response(url, response) | POST request for creating new objects.
data should be a dictionary. | https://github.com/bigcommerce/bigcommerce-api-python/blob/76a8f5d59fd44a4365f14a5959102e118cf35dee/bigcommerce/connection.py#L142-L148 |
bigcommerce/bigcommerce-api-python | bigcommerce/connection.py | Connection._handle_response | def _handle_response(self, url, res, suppress_empty=True):
"""
Returns parsed JSON or raises an exception appropriately.
"""
self._last_response = res
result = {}
if res.status_code in (200, 201, 202):
try:
result = res.json()
except Exception as e: # json might be invalid, or store might be down
e.message += " (_handle_response failed to decode JSON: " + str(res.content) + ")"
raise # TODO better exception
elif res.status_code == 204 and not suppress_empty:
raise EmptyResponseWarning("%d %s @ %s: %s" % (res.status_code, res.reason, url, res.content), res)
elif res.status_code >= 500:
raise ServerException("%d %s @ %s: %s" % (res.status_code, res.reason, url, res.content), res)
elif res.status_code == 429:
raise RateLimitingException("%d %s @ %s: %s" % (res.status_code, res.reason, url, res.content), res)
elif res.status_code >= 400:
raise ClientRequestException("%d %s @ %s: %s" % (res.status_code, res.reason, url, res.content), res)
elif res.status_code >= 300:
raise RedirectionException("%d %s @ %s: %s" % (res.status_code, res.reason, url, res.content), res)
return result | python | def _handle_response(self, url, res, suppress_empty=True):
"""
Returns parsed JSON or raises an exception appropriately.
"""
self._last_response = res
result = {}
if res.status_code in (200, 201, 202):
try:
result = res.json()
except Exception as e: # json might be invalid, or store might be down
e.message += " (_handle_response failed to decode JSON: " + str(res.content) + ")"
raise # TODO better exception
elif res.status_code == 204 and not suppress_empty:
raise EmptyResponseWarning("%d %s @ %s: %s" % (res.status_code, res.reason, url, res.content), res)
elif res.status_code >= 500:
raise ServerException("%d %s @ %s: %s" % (res.status_code, res.reason, url, res.content), res)
elif res.status_code == 429:
raise RateLimitingException("%d %s @ %s: %s" % (res.status_code, res.reason, url, res.content), res)
elif res.status_code >= 400:
raise ClientRequestException("%d %s @ %s: %s" % (res.status_code, res.reason, url, res.content), res)
elif res.status_code >= 300:
raise RedirectionException("%d %s @ %s: %s" % (res.status_code, res.reason, url, res.content), res)
return result | Returns parsed JSON or raises an exception appropriately. | https://github.com/bigcommerce/bigcommerce-api-python/blob/76a8f5d59fd44a4365f14a5959102e118cf35dee/bigcommerce/connection.py#L150-L172 |
bigcommerce/bigcommerce-api-python | bigcommerce/connection.py | OAuthConnection.verify_payload | def verify_payload(signed_payload, client_secret):
"""
Given a signed payload (usually passed as parameter in a GET request to the app's load URL) and a client secret,
authenticates the payload and returns the user's data, or False on fail.
Uses constant-time str comparison to prevent vulnerability to timing attacks.
"""
encoded_json, encoded_hmac = signed_payload.split('.')
dc_json = base64.b64decode(encoded_json)
signature = base64.b64decode(encoded_hmac)
expected_sig = hmac.new(client_secret.encode(), base64.b64decode(encoded_json), hashlib.sha256).hexdigest()
authorised = hmac.compare_digest(signature, expected_sig.encode())
return json.loads(dc_json.decode()) if authorised else False | python | def verify_payload(signed_payload, client_secret):
"""
Given a signed payload (usually passed as parameter in a GET request to the app's load URL) and a client secret,
authenticates the payload and returns the user's data, or False on fail.
Uses constant-time str comparison to prevent vulnerability to timing attacks.
"""
encoded_json, encoded_hmac = signed_payload.split('.')
dc_json = base64.b64decode(encoded_json)
signature = base64.b64decode(encoded_hmac)
expected_sig = hmac.new(client_secret.encode(), base64.b64decode(encoded_json), hashlib.sha256).hexdigest()
authorised = hmac.compare_digest(signature, expected_sig.encode())
return json.loads(dc_json.decode()) if authorised else False | Given a signed payload (usually passed as parameter in a GET request to the app's load URL) and a client secret,
authenticates the payload and returns the user's data, or False on fail.
Uses constant-time str comparison to prevent vulnerability to timing attacks. | https://github.com/bigcommerce/bigcommerce-api-python/blob/76a8f5d59fd44a4365f14a5959102e118cf35dee/bigcommerce/connection.py#L217-L229 |
bigcommerce/bigcommerce-api-python | bigcommerce/connection.py | OAuthConnection.fetch_token | def fetch_token(self, client_secret, code, context, scope, redirect_uri,
token_url='https://login.bigcommerce.com/oauth2/token'):
"""
Fetches a token from given token_url, using given parameters, and sets up session headers for
future requests.
redirect_uri should be the same as your callback URL.
code, context, and scope should be passed as parameters to your callback URL on app installation.
Raises HttpException on failure (same as Connection methods).
"""
res = self.post(token_url, {'client_id': self.client_id,
'client_secret': client_secret,
'code': code,
'context': context,
'scope': scope,
'grant_type': 'authorization_code',
'redirect_uri': redirect_uri},
headers={'Content-Type': 'application/x-www-form-urlencoded'})
self._session.headers.update(self._oauth_headers(self.client_id, res['access_token']))
return res | python | def fetch_token(self, client_secret, code, context, scope, redirect_uri,
token_url='https://login.bigcommerce.com/oauth2/token'):
"""
Fetches a token from given token_url, using given parameters, and sets up session headers for
future requests.
redirect_uri should be the same as your callback URL.
code, context, and scope should be passed as parameters to your callback URL on app installation.
Raises HttpException on failure (same as Connection methods).
"""
res = self.post(token_url, {'client_id': self.client_id,
'client_secret': client_secret,
'code': code,
'context': context,
'scope': scope,
'grant_type': 'authorization_code',
'redirect_uri': redirect_uri},
headers={'Content-Type': 'application/x-www-form-urlencoded'})
self._session.headers.update(self._oauth_headers(self.client_id, res['access_token']))
return res | Fetches a token from given token_url, using given parameters, and sets up session headers for
future requests.
redirect_uri should be the same as your callback URL.
code, context, and scope should be passed as parameters to your callback URL on app installation.
Raises HttpException on failure (same as Connection methods). | https://github.com/bigcommerce/bigcommerce-api-python/blob/76a8f5d59fd44a4365f14a5959102e118cf35dee/bigcommerce/connection.py#L231-L250 |
bigcommerce/bigcommerce-api-python | bigcommerce/connection.py | OAuthConnection._handle_response | def _handle_response(self, url, res, suppress_empty=True):
"""
Adds rate limiting information on to the response object
"""
result = Connection._handle_response(self, url, res, suppress_empty)
if 'X-Rate-Limit-Time-Reset-Ms' in res.headers:
self.rate_limit = dict(ms_until_reset=int(res.headers['X-Rate-Limit-Time-Reset-Ms']),
window_size_ms=int(res.headers['X-Rate-Limit-Time-Window-Ms']),
requests_remaining=int(res.headers['X-Rate-Limit-Requests-Left']),
requests_quota=int(res.headers['X-Rate-Limit-Requests-Quota']))
if self.rate_limiting_management:
if self.rate_limiting_management['min_requests_remaining'] >= self.rate_limit['requests_remaining']:
if self.rate_limiting_management['wait']:
sleep(ceil(float(self.rate_limit['ms_until_reset']) / 1000))
if self.rate_limiting_management.get('callback_function'):
callback = self.rate_limiting_management['callback_function']
args_dict = self.rate_limiting_management.get('callback_args')
if args_dict:
callback(args_dict)
else:
callback()
return result | python | def _handle_response(self, url, res, suppress_empty=True):
"""
Adds rate limiting information on to the response object
"""
result = Connection._handle_response(self, url, res, suppress_empty)
if 'X-Rate-Limit-Time-Reset-Ms' in res.headers:
self.rate_limit = dict(ms_until_reset=int(res.headers['X-Rate-Limit-Time-Reset-Ms']),
window_size_ms=int(res.headers['X-Rate-Limit-Time-Window-Ms']),
requests_remaining=int(res.headers['X-Rate-Limit-Requests-Left']),
requests_quota=int(res.headers['X-Rate-Limit-Requests-Quota']))
if self.rate_limiting_management:
if self.rate_limiting_management['min_requests_remaining'] >= self.rate_limit['requests_remaining']:
if self.rate_limiting_management['wait']:
sleep(ceil(float(self.rate_limit['ms_until_reset']) / 1000))
if self.rate_limiting_management.get('callback_function'):
callback = self.rate_limiting_management['callback_function']
args_dict = self.rate_limiting_management.get('callback_args')
if args_dict:
callback(args_dict)
else:
callback()
return result | Adds rate limiting information on to the response object | https://github.com/bigcommerce/bigcommerce-api-python/blob/76a8f5d59fd44a4365f14a5959102e118cf35dee/bigcommerce/connection.py#L252-L274 |
FSX/misaka | misaka/api.py | escape_html | def escape_html(text, escape_slash=False):
"""
Binding for Hoedown's HTML escaping function.
The implementation is inspired by the OWASP XSS Prevention recommendations:
.. code-block:: none
& --> &
< --> <
> --> >
" --> "
' --> '
/ --> / when escape_slash is set to True
.. versionadded:: 2.1.0
"""
byte_str = text.encode('utf-8')
ob = lib.hoedown_buffer_new(OUNIT)
lib.hoedown_escape_html(ob, byte_str, len(byte_str), int(escape_slash))
try:
return to_string(ob)
finally:
lib.hoedown_buffer_free(ob) | python | def escape_html(text, escape_slash=False):
"""
Binding for Hoedown's HTML escaping function.
The implementation is inspired by the OWASP XSS Prevention recommendations:
.. code-block:: none
& --> &
< --> <
> --> >
" --> "
' --> '
/ --> / when escape_slash is set to True
.. versionadded:: 2.1.0
"""
byte_str = text.encode('utf-8')
ob = lib.hoedown_buffer_new(OUNIT)
lib.hoedown_escape_html(ob, byte_str, len(byte_str), int(escape_slash))
try:
return to_string(ob)
finally:
lib.hoedown_buffer_free(ob) | Binding for Hoedown's HTML escaping function.
The implementation is inspired by the OWASP XSS Prevention recommendations:
.. code-block:: none
& --> &
< --> <
> --> >
" --> "
' --> '
/ --> / when escape_slash is set to True
.. versionadded:: 2.1.0 | https://github.com/FSX/misaka/blob/c13aff82d370d606ff61361db79c166a897641cf/misaka/api.py#L69-L93 |
FSX/misaka | misaka/api.py | html | def html(text, extensions=0, render_flags=0):
"""
Convert markdown text to HTML.
``extensions`` can be a list or tuple of extensions (e.g.
``('fenced-code', 'footnotes', 'strikethrough')``) or an integer
(e.g. ``EXT_FENCED_CODE | EXT_FOOTNOTES | EXT_STRIKETHROUGH``).
``render_flags`` can be a list or tuple of flags (e.g.
``('skip-html', 'hard-wrap')``) or an integer
(e.g. ``HTML_SKIP_HTML | HTML_HARD_WRAP``).
"""
extensions = args_to_int(extension_map, extensions)
render_flags = args_to_int(html_flag_map, render_flags)
ib = lib.hoedown_buffer_new(IUNIT)
ob = lib.hoedown_buffer_new(OUNIT)
renderer = lib.hoedown_html_renderer_new(render_flags, 0)
document = lib.hoedown_document_new(renderer, extensions, 16);
lib.hoedown_buffer_puts(ib, text.encode('utf-8'))
lib.hoedown_document_render(document, ob, ib.data, ib.size);
lib.hoedown_buffer_free(ib);
lib.hoedown_document_free(document);
lib.hoedown_html_renderer_free(renderer);
try:
return to_string(ob)
finally:
lib.hoedown_buffer_free(ob); | python | def html(text, extensions=0, render_flags=0):
"""
Convert markdown text to HTML.
``extensions`` can be a list or tuple of extensions (e.g.
``('fenced-code', 'footnotes', 'strikethrough')``) or an integer
(e.g. ``EXT_FENCED_CODE | EXT_FOOTNOTES | EXT_STRIKETHROUGH``).
``render_flags`` can be a list or tuple of flags (e.g.
``('skip-html', 'hard-wrap')``) or an integer
(e.g. ``HTML_SKIP_HTML | HTML_HARD_WRAP``).
"""
extensions = args_to_int(extension_map, extensions)
render_flags = args_to_int(html_flag_map, render_flags)
ib = lib.hoedown_buffer_new(IUNIT)
ob = lib.hoedown_buffer_new(OUNIT)
renderer = lib.hoedown_html_renderer_new(render_flags, 0)
document = lib.hoedown_document_new(renderer, extensions, 16);
lib.hoedown_buffer_puts(ib, text.encode('utf-8'))
lib.hoedown_document_render(document, ob, ib.data, ib.size);
lib.hoedown_buffer_free(ib);
lib.hoedown_document_free(document);
lib.hoedown_html_renderer_free(renderer);
try:
return to_string(ob)
finally:
lib.hoedown_buffer_free(ob); | Convert markdown text to HTML.
``extensions`` can be a list or tuple of extensions (e.g.
``('fenced-code', 'footnotes', 'strikethrough')``) or an integer
(e.g. ``EXT_FENCED_CODE | EXT_FOOTNOTES | EXT_STRIKETHROUGH``).
``render_flags`` can be a list or tuple of flags (e.g.
``('skip-html', 'hard-wrap')``) or an integer
(e.g. ``HTML_SKIP_HTML | HTML_HARD_WRAP``). | https://github.com/FSX/misaka/blob/c13aff82d370d606ff61361db79c166a897641cf/misaka/api.py#L96-L125 |
FSX/misaka | misaka/api.py | smartypants | def smartypants(text):
"""
Transforms sequences of characters into HTML entities.
=================================== ===================== =========
Markdown HTML Result
=================================== ===================== =========
``'s`` (s, t, m, d, re, ll, ve) ’s ’s
``"Quotes"`` “Quotes” “Quotes”
``---`` — —
``--`` – –
``...`` … …
``. . .`` … …
``(c)`` © ©
``(r)`` ® ®
``(tm)`` ™ ™
``3/4`` ¾ ¾
``1/2`` ½ ½
``1/4`` ¼ ¼
=================================== ===================== =========
"""
byte_str = text.encode('utf-8')
ob = lib.hoedown_buffer_new(OUNIT)
lib.hoedown_html_smartypants(ob, byte_str, len(byte_str))
try:
return to_string(ob)
finally:
lib.hoedown_buffer_free(ob); | python | def smartypants(text):
"""
Transforms sequences of characters into HTML entities.
=================================== ===================== =========
Markdown HTML Result
=================================== ===================== =========
``'s`` (s, t, m, d, re, ll, ve) ’s ’s
``"Quotes"`` “Quotes” “Quotes”
``---`` — —
``--`` – –
``...`` … …
``. . .`` … …
``(c)`` © ©
``(r)`` ® ®
``(tm)`` ™ ™
``3/4`` ¾ ¾
``1/2`` ½ ½
``1/4`` ¼ ¼
=================================== ===================== =========
"""
byte_str = text.encode('utf-8')
ob = lib.hoedown_buffer_new(OUNIT)
lib.hoedown_html_smartypants(ob, byte_str, len(byte_str))
try:
return to_string(ob)
finally:
lib.hoedown_buffer_free(ob); | Transforms sequences of characters into HTML entities.
=================================== ===================== =========
Markdown HTML Result
=================================== ===================== =========
``'s`` (s, t, m, d, re, ll, ve) ’s ’s
``"Quotes"`` “Quotes” “Quotes”
``---`` — —
``--`` – –
``...`` … …
``. . .`` … …
``(c)`` © ©
``(r)`` ® ®
``(tm)`` ™ ™
``3/4`` ¾ ¾
``1/2`` ½ ½
``1/4`` ¼ ¼
=================================== ===================== ========= | https://github.com/FSX/misaka/blob/c13aff82d370d606ff61361db79c166a897641cf/misaka/api.py#L128-L156 |
FSX/misaka | misaka/api.py | SaferHtmlRenderer.autolink | def autolink(self, raw_url, is_email):
"""
Filters links generated by the ``autolink`` extension.
"""
if self.check_url(raw_url):
url = self.rewrite_url(('mailto:' if is_email else '') + raw_url)
url = escape_html(url)
return '<a href="%s">%s</a>' % (url, escape_html(raw_url))
else:
return escape_html('<%s>' % raw_url) | python | def autolink(self, raw_url, is_email):
"""
Filters links generated by the ``autolink`` extension.
"""
if self.check_url(raw_url):
url = self.rewrite_url(('mailto:' if is_email else '') + raw_url)
url = escape_html(url)
return '<a href="%s">%s</a>' % (url, escape_html(raw_url))
else:
return escape_html('<%s>' % raw_url) | Filters links generated by the ``autolink`` extension. | https://github.com/FSX/misaka/blob/c13aff82d370d606ff61361db79c166a897641cf/misaka/api.py#L304-L313 |
FSX/misaka | misaka/api.py | SaferHtmlRenderer.image | def image(self, raw_url, title='', alt=''):
"""
Filters the ``src`` attribute of an image.
Note that filtering the source URL of an ``<img>`` tag is only a very
basic protection, and it's mostly useless in modern browsers (they block
JavaScript in there by default). An example of attack that filtering
does not thwart is phishing based on HTTP Auth, see `this issue
<https://github.com/liberapay/liberapay.com/issues/504>`_ for details.
To mitigate this issue you should only allow images from trusted services,
for example your own image store, or a proxy (see :meth:`rewrite_url`).
"""
if self.check_url(raw_url, is_image_src=True):
url = self.rewrite_url(raw_url, is_image_src=True)
maybe_alt = ' alt="%s"' % escape_html(alt) if alt else ''
maybe_title = ' title="%s"' % escape_html(title) if title else ''
url = escape_html(url)
return '<img src="%s"%s%s />' % (url, maybe_alt, maybe_title)
else:
return escape_html("" % (alt, raw_url)) | python | def image(self, raw_url, title='', alt=''):
"""
Filters the ``src`` attribute of an image.
Note that filtering the source URL of an ``<img>`` tag is only a very
basic protection, and it's mostly useless in modern browsers (they block
JavaScript in there by default). An example of attack that filtering
does not thwart is phishing based on HTTP Auth, see `this issue
<https://github.com/liberapay/liberapay.com/issues/504>`_ for details.
To mitigate this issue you should only allow images from trusted services,
for example your own image store, or a proxy (see :meth:`rewrite_url`).
"""
if self.check_url(raw_url, is_image_src=True):
url = self.rewrite_url(raw_url, is_image_src=True)
maybe_alt = ' alt="%s"' % escape_html(alt) if alt else ''
maybe_title = ' title="%s"' % escape_html(title) if title else ''
url = escape_html(url)
return '<img src="%s"%s%s />' % (url, maybe_alt, maybe_title)
else:
return escape_html("" % (alt, raw_url)) | Filters the ``src`` attribute of an image.
Note that filtering the source URL of an ``<img>`` tag is only a very
basic protection, and it's mostly useless in modern browsers (they block
JavaScript in there by default). An example of attack that filtering
does not thwart is phishing based on HTTP Auth, see `this issue
<https://github.com/liberapay/liberapay.com/issues/504>`_ for details.
To mitigate this issue you should only allow images from trusted services,
for example your own image store, or a proxy (see :meth:`rewrite_url`). | https://github.com/FSX/misaka/blob/c13aff82d370d606ff61361db79c166a897641cf/misaka/api.py#L315-L335 |
FSX/misaka | misaka/api.py | SaferHtmlRenderer.link | def link(self, content, raw_url, title=''):
"""
Filters links.
"""
if self.check_url(raw_url):
url = self.rewrite_url(raw_url)
maybe_title = ' title="%s"' % escape_html(title) if title else ''
url = escape_html(url)
return ('<a href="%s"%s>' % (url, maybe_title)) + content + '</a>'
else:
return escape_html("[%s](%s)" % (content, raw_url)) | python | def link(self, content, raw_url, title=''):
"""
Filters links.
"""
if self.check_url(raw_url):
url = self.rewrite_url(raw_url)
maybe_title = ' title="%s"' % escape_html(title) if title else ''
url = escape_html(url)
return ('<a href="%s"%s>' % (url, maybe_title)) + content + '</a>'
else:
return escape_html("[%s](%s)" % (content, raw_url)) | Filters links. | https://github.com/FSX/misaka/blob/c13aff82d370d606ff61361db79c166a897641cf/misaka/api.py#L337-L347 |
FSX/misaka | misaka/api.py | SaferHtmlRenderer.check_url | def check_url(self, url, is_image_src=False):
"""
This method is used to check a URL.
Returns :obj:`True` if the URL is "safe", :obj:`False` otherwise.
The default implementation only allows HTTP and HTTPS links. That means
no ``mailto:``, no ``xmpp:``, no ``ftp:``, etc.
This method exists specifically to allow easy customization of link
filtering through subclassing, so don't hesitate to write your own.
If you're thinking of implementing a blacklist approach, see
"`Which URL schemes are dangerous (XSS exploitable)?
<http://security.stackexchange.com/q/148428/37409>`_".
"""
return bool(self._allowed_url_re.match(url)) | python | def check_url(self, url, is_image_src=False):
"""
This method is used to check a URL.
Returns :obj:`True` if the URL is "safe", :obj:`False` otherwise.
The default implementation only allows HTTP and HTTPS links. That means
no ``mailto:``, no ``xmpp:``, no ``ftp:``, etc.
This method exists specifically to allow easy customization of link
filtering through subclassing, so don't hesitate to write your own.
If you're thinking of implementing a blacklist approach, see
"`Which URL schemes are dangerous (XSS exploitable)?
<http://security.stackexchange.com/q/148428/37409>`_".
"""
return bool(self._allowed_url_re.match(url)) | This method is used to check a URL.
Returns :obj:`True` if the URL is "safe", :obj:`False` otherwise.
The default implementation only allows HTTP and HTTPS links. That means
no ``mailto:``, no ``xmpp:``, no ``ftp:``, etc.
This method exists specifically to allow easy customization of link
filtering through subclassing, so don't hesitate to write your own.
If you're thinking of implementing a blacklist approach, see
"`Which URL schemes are dangerous (XSS exploitable)?
<http://security.stackexchange.com/q/148428/37409>`_". | https://github.com/FSX/misaka/blob/c13aff82d370d606ff61361db79c166a897641cf/misaka/api.py#L349-L365 |
FSX/misaka | misaka/api.py | SaferHtmlRenderer.rewrite_url | def rewrite_url(self, url, is_image_src=False):
"""
This method is called to rewrite URLs.
It uses either ``self.link_rewrite`` or ``self.img_src_rewrite``
depending on the value of ``is_image_src``. The URL is returned
unchanged if the corresponding attribute is :obj:`None`.
"""
rewrite = self.img_src_rewrite if is_image_src else self.link_rewrite
if rewrite:
return rewrite.format(url=urlquote(url))
return url | python | def rewrite_url(self, url, is_image_src=False):
"""
This method is called to rewrite URLs.
It uses either ``self.link_rewrite`` or ``self.img_src_rewrite``
depending on the value of ``is_image_src``. The URL is returned
unchanged if the corresponding attribute is :obj:`None`.
"""
rewrite = self.img_src_rewrite if is_image_src else self.link_rewrite
if rewrite:
return rewrite.format(url=urlquote(url))
return url | This method is called to rewrite URLs.
It uses either ``self.link_rewrite`` or ``self.img_src_rewrite``
depending on the value of ``is_image_src``. The URL is returned
unchanged if the corresponding attribute is :obj:`None`. | https://github.com/FSX/misaka/blob/c13aff82d370d606ff61361db79c166a897641cf/misaka/api.py#L367-L378 |
FSX/misaka | misaka/utils.py | args_to_int | def args_to_int(mapping, argument):
"""
Convert list of strings to an int using a mapping.
"""
if isinstance(argument, int):
if argument == 0:
return 0
deprecation('passing extensions and flags as constants is deprecated')
return argument
elif isinstance(argument, (tuple, list)):
return reduce(op.or_, [mapping[n] for n in set(argument) if n in mapping], 0)
raise TypeError('argument must be a list of strings or an int') | python | def args_to_int(mapping, argument):
"""
Convert list of strings to an int using a mapping.
"""
if isinstance(argument, int):
if argument == 0:
return 0
deprecation('passing extensions and flags as constants is deprecated')
return argument
elif isinstance(argument, (tuple, list)):
return reduce(op.or_, [mapping[n] for n in set(argument) if n in mapping], 0)
raise TypeError('argument must be a list of strings or an int') | Convert list of strings to an int using a mapping. | https://github.com/FSX/misaka/blob/c13aff82d370d606ff61361db79c166a897641cf/misaka/utils.py#L40-L51 |
vsergeev/u-msgpack-python | umsgpack.py | _pack3 | def _pack3(obj, fp, **options):
"""
Serialize a Python object into MessagePack bytes.
Args:
obj: a Python object
fp: a .write()-supporting file-like object
Kwargs:
ext_handlers (dict): dictionary of Ext handlers, mapping a custom type
to a callable that packs an instance of the type
into an Ext object
force_float_precision (str): "single" to force packing floats as
IEEE-754 single-precision floats,
"double" to force packing floats as
IEEE-754 double-precision floats.
Returns:
None.
Raises:
UnsupportedType(PackException):
Object type not supported for packing.
Example:
>>> f = open('test.bin', 'wb')
>>> umsgpack.pack({u"compact": True, u"schema": 0}, f)
>>>
"""
global compatibility
ext_handlers = options.get("ext_handlers")
if obj is None:
_pack_nil(obj, fp, options)
elif ext_handlers and obj.__class__ in ext_handlers:
_pack_ext(ext_handlers[obj.__class__](obj), fp, options)
elif isinstance(obj, bool):
_pack_boolean(obj, fp, options)
elif isinstance(obj, int):
_pack_integer(obj, fp, options)
elif isinstance(obj, float):
_pack_float(obj, fp, options)
elif compatibility and isinstance(obj, str):
_pack_oldspec_raw(obj.encode('utf-8'), fp, options)
elif compatibility and isinstance(obj, bytes):
_pack_oldspec_raw(obj, fp, options)
elif isinstance(obj, str):
_pack_string(obj, fp, options)
elif isinstance(obj, bytes):
_pack_binary(obj, fp, options)
elif isinstance(obj, (list, tuple)):
_pack_array(obj, fp, options)
elif isinstance(obj, dict):
_pack_map(obj, fp, options)
elif isinstance(obj, datetime.datetime):
_pack_ext_timestamp(obj, fp, options)
elif isinstance(obj, Ext):
_pack_ext(obj, fp, options)
elif ext_handlers:
# Linear search for superclass
t = next((t for t in ext_handlers.keys() if isinstance(obj, t)), None)
if t:
_pack_ext(ext_handlers[t](obj), fp, options)
else:
raise UnsupportedTypeException(
"unsupported type: %s" % str(type(obj)))
else:
raise UnsupportedTypeException(
"unsupported type: %s" % str(type(obj))) | python | def _pack3(obj, fp, **options):
"""
Serialize a Python object into MessagePack bytes.
Args:
obj: a Python object
fp: a .write()-supporting file-like object
Kwargs:
ext_handlers (dict): dictionary of Ext handlers, mapping a custom type
to a callable that packs an instance of the type
into an Ext object
force_float_precision (str): "single" to force packing floats as
IEEE-754 single-precision floats,
"double" to force packing floats as
IEEE-754 double-precision floats.
Returns:
None.
Raises:
UnsupportedType(PackException):
Object type not supported for packing.
Example:
>>> f = open('test.bin', 'wb')
>>> umsgpack.pack({u"compact": True, u"schema": 0}, f)
>>>
"""
global compatibility
ext_handlers = options.get("ext_handlers")
if obj is None:
_pack_nil(obj, fp, options)
elif ext_handlers and obj.__class__ in ext_handlers:
_pack_ext(ext_handlers[obj.__class__](obj), fp, options)
elif isinstance(obj, bool):
_pack_boolean(obj, fp, options)
elif isinstance(obj, int):
_pack_integer(obj, fp, options)
elif isinstance(obj, float):
_pack_float(obj, fp, options)
elif compatibility and isinstance(obj, str):
_pack_oldspec_raw(obj.encode('utf-8'), fp, options)
elif compatibility and isinstance(obj, bytes):
_pack_oldspec_raw(obj, fp, options)
elif isinstance(obj, str):
_pack_string(obj, fp, options)
elif isinstance(obj, bytes):
_pack_binary(obj, fp, options)
elif isinstance(obj, (list, tuple)):
_pack_array(obj, fp, options)
elif isinstance(obj, dict):
_pack_map(obj, fp, options)
elif isinstance(obj, datetime.datetime):
_pack_ext_timestamp(obj, fp, options)
elif isinstance(obj, Ext):
_pack_ext(obj, fp, options)
elif ext_handlers:
# Linear search for superclass
t = next((t for t in ext_handlers.keys() if isinstance(obj, t)), None)
if t:
_pack_ext(ext_handlers[t](obj), fp, options)
else:
raise UnsupportedTypeException(
"unsupported type: %s" % str(type(obj)))
else:
raise UnsupportedTypeException(
"unsupported type: %s" % str(type(obj))) | Serialize a Python object into MessagePack bytes.
Args:
obj: a Python object
fp: a .write()-supporting file-like object
Kwargs:
ext_handlers (dict): dictionary of Ext handlers, mapping a custom type
to a callable that packs an instance of the type
into an Ext object
force_float_precision (str): "single" to force packing floats as
IEEE-754 single-precision floats,
"double" to force packing floats as
IEEE-754 double-precision floats.
Returns:
None.
Raises:
UnsupportedType(PackException):
Object type not supported for packing.
Example:
>>> f = open('test.bin', 'wb')
>>> umsgpack.pack({u"compact": True, u"schema": 0}, f)
>>> | https://github.com/vsergeev/u-msgpack-python/blob/e290b768ce63177ae04ed96402915b75a9741f38/umsgpack.py#L486-L555 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/util.py | _get_task_target | def _get_task_target():
"""Get the default target for a pipeline task.
Current version id format is: user_defined_version.minor_version_number
Current module id is just the module's name. It could be "default"
Returns:
A complete target name is of format version.module. If module is the
default module, just version. None if target can not be determined.
"""
# Break circular dependency.
# pylint: disable=g-import-not-at-top
import pipeline
if pipeline._TEST_MODE:
return None
# Further protect against test cases that doesn't set env vars
# propertly.
if ("CURRENT_VERSION_ID" not in os.environ or
"CURRENT_MODULE_ID" not in os.environ):
logging.warning("Running Pipeline in non TEST_MODE but important "
"env vars are not set.")
return None
version = os.environ["CURRENT_VERSION_ID"].split(".")[0]
module = os.environ["CURRENT_MODULE_ID"]
return "%s.%s" % (version, module) | python | def _get_task_target():
"""Get the default target for a pipeline task.
Current version id format is: user_defined_version.minor_version_number
Current module id is just the module's name. It could be "default"
Returns:
A complete target name is of format version.module. If module is the
default module, just version. None if target can not be determined.
"""
# Break circular dependency.
# pylint: disable=g-import-not-at-top
import pipeline
if pipeline._TEST_MODE:
return None
# Further protect against test cases that doesn't set env vars
# propertly.
if ("CURRENT_VERSION_ID" not in os.environ or
"CURRENT_MODULE_ID" not in os.environ):
logging.warning("Running Pipeline in non TEST_MODE but important "
"env vars are not set.")
return None
version = os.environ["CURRENT_VERSION_ID"].split(".")[0]
module = os.environ["CURRENT_MODULE_ID"]
return "%s.%s" % (version, module) | Get the default target for a pipeline task.
Current version id format is: user_defined_version.minor_version_number
Current module id is just the module's name. It could be "default"
Returns:
A complete target name is of format version.module. If module is the
default module, just version. None if target can not be determined. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/util.py#L40-L66 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/util.py | for_name | def for_name(fq_name, recursive=False):
"""Find class/function/method specified by its fully qualified name.
Fully qualified can be specified as:
* <module_name>.<class_name>
* <module_name>.<function_name>
* <module_name>.<class_name>.<method_name> (an unbound method will be
returned in this case).
for_name works by doing __import__ for <module_name>, and looks for
<class_name>/<function_name> in module's __dict__/attrs. If fully qualified
name doesn't contain '.', the current module will be used.
Args:
fq_name: fully qualified name of something to find
Returns:
class object.
Raises:
ImportError: when specified module could not be loaded or the class
was not found in the module.
"""
fq_name = str(fq_name)
module_name = __name__
short_name = fq_name
if fq_name.rfind(".") >= 0:
(module_name, short_name) = (fq_name[:fq_name.rfind(".")],
fq_name[fq_name.rfind(".") + 1:])
try:
result = __import__(module_name, None, None, [short_name])
return result.__dict__[short_name]
except KeyError:
# If we're recursively inside a for_name() chain, then we want to raise
# this error as a key error so we can report the actual source of the
# problem. If we're *not* recursively being called, that means the
# module was found and the specific item could not be loaded, and thus
# we want to raise an ImportError directly.
if recursive:
raise
else:
raise ImportError("Could not find '%s' on path '%s'" % (
short_name, module_name))
except ImportError, e:
# module_name is not actually a module. Try for_name for it to figure
# out what's this.
try:
module = for_name(module_name, recursive=True)
if hasattr(module, short_name):
return getattr(module, short_name)
else:
# The module was found, but the function component is missing.
raise KeyError()
except KeyError:
raise ImportError("Could not find '%s' on path '%s'" % (
short_name, module_name))
except ImportError:
# This means recursive import attempts failed, thus we will raise the
# first ImportError we encountered, since it's likely the most accurate.
pass
# Raise the original import error that caused all of this, since it is
# likely the real cause of the overall problem.
raise | python | def for_name(fq_name, recursive=False):
"""Find class/function/method specified by its fully qualified name.
Fully qualified can be specified as:
* <module_name>.<class_name>
* <module_name>.<function_name>
* <module_name>.<class_name>.<method_name> (an unbound method will be
returned in this case).
for_name works by doing __import__ for <module_name>, and looks for
<class_name>/<function_name> in module's __dict__/attrs. If fully qualified
name doesn't contain '.', the current module will be used.
Args:
fq_name: fully qualified name of something to find
Returns:
class object.
Raises:
ImportError: when specified module could not be loaded or the class
was not found in the module.
"""
fq_name = str(fq_name)
module_name = __name__
short_name = fq_name
if fq_name.rfind(".") >= 0:
(module_name, short_name) = (fq_name[:fq_name.rfind(".")],
fq_name[fq_name.rfind(".") + 1:])
try:
result = __import__(module_name, None, None, [short_name])
return result.__dict__[short_name]
except KeyError:
# If we're recursively inside a for_name() chain, then we want to raise
# this error as a key error so we can report the actual source of the
# problem. If we're *not* recursively being called, that means the
# module was found and the specific item could not be loaded, and thus
# we want to raise an ImportError directly.
if recursive:
raise
else:
raise ImportError("Could not find '%s' on path '%s'" % (
short_name, module_name))
except ImportError, e:
# module_name is not actually a module. Try for_name for it to figure
# out what's this.
try:
module = for_name(module_name, recursive=True)
if hasattr(module, short_name):
return getattr(module, short_name)
else:
# The module was found, but the function component is missing.
raise KeyError()
except KeyError:
raise ImportError("Could not find '%s' on path '%s'" % (
short_name, module_name))
except ImportError:
# This means recursive import attempts failed, thus we will raise the
# first ImportError we encountered, since it's likely the most accurate.
pass
# Raise the original import error that caused all of this, since it is
# likely the real cause of the overall problem.
raise | Find class/function/method specified by its fully qualified name.
Fully qualified can be specified as:
* <module_name>.<class_name>
* <module_name>.<function_name>
* <module_name>.<class_name>.<method_name> (an unbound method will be
returned in this case).
for_name works by doing __import__ for <module_name>, and looks for
<class_name>/<function_name> in module's __dict__/attrs. If fully qualified
name doesn't contain '.', the current module will be used.
Args:
fq_name: fully qualified name of something to find
Returns:
class object.
Raises:
ImportError: when specified module could not be loaded or the class
was not found in the module. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/util.py#L69-L133 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/util.py | is_generator_function | def is_generator_function(obj):
"""Return true if the object is a user-defined generator function.
Generator function objects provides same attributes as functions.
See isfunction.__doc__ for attributes listing.
Adapted from Python 2.6.
Args:
obj: an object to test.
Returns:
true if the object is generator function.
"""
CO_GENERATOR = 0x20
return bool(((inspect.isfunction(obj) or inspect.ismethod(obj)) and
obj.func_code.co_flags & CO_GENERATOR)) | python | def is_generator_function(obj):
"""Return true if the object is a user-defined generator function.
Generator function objects provides same attributes as functions.
See isfunction.__doc__ for attributes listing.
Adapted from Python 2.6.
Args:
obj: an object to test.
Returns:
true if the object is generator function.
"""
CO_GENERATOR = 0x20
return bool(((inspect.isfunction(obj) or inspect.ismethod(obj)) and
obj.func_code.co_flags & CO_GENERATOR)) | Return true if the object is a user-defined generator function.
Generator function objects provides same attributes as functions.
See isfunction.__doc__ for attributes listing.
Adapted from Python 2.6.
Args:
obj: an object to test.
Returns:
true if the object is generator function. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/util.py#L136-L152 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/util.py | _register_json_primitive | def _register_json_primitive(object_type, encoder, decoder):
"""Extend what Pipeline can serialize.
Args:
object_type: type of the object.
encoder: a function that takes in an object and returns
a dict of json primitives.
decoder: inverse function of encoder.
"""
global _TYPE_TO_ENCODER
global _TYPE_NAME_TO_DECODER
if object_type not in _TYPE_TO_ENCODER:
_TYPE_TO_ENCODER[object_type] = encoder
_TYPE_NAME_TO_DECODER[object_type.__name__] = decoder | python | def _register_json_primitive(object_type, encoder, decoder):
"""Extend what Pipeline can serialize.
Args:
object_type: type of the object.
encoder: a function that takes in an object and returns
a dict of json primitives.
decoder: inverse function of encoder.
"""
global _TYPE_TO_ENCODER
global _TYPE_NAME_TO_DECODER
if object_type not in _TYPE_TO_ENCODER:
_TYPE_TO_ENCODER[object_type] = encoder
_TYPE_NAME_TO_DECODER[object_type.__name__] = decoder | Extend what Pipeline can serialize.
Args:
object_type: type of the object.
encoder: a function that takes in an object and returns
a dict of json primitives.
decoder: inverse function of encoder. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/util.py#L211-L224 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/util.py | _JsonDecodeKey | def _JsonDecodeKey(d):
"""Json decode a ndb.Key object."""
k_c = d['key_string']
if isinstance(k_c, (list, tuple)):
return ndb.Key(flat=k_c)
return ndb.Key(urlsafe=d['key_string']) | python | def _JsonDecodeKey(d):
"""Json decode a ndb.Key object."""
k_c = d['key_string']
if isinstance(k_c, (list, tuple)):
return ndb.Key(flat=k_c)
return ndb.Key(urlsafe=d['key_string']) | Json decode a ndb.Key object. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/util.py#L238-L243 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/util.py | JsonEncoder.default | def default(self, o):
"""Inherit docs."""
if type(o) in _TYPE_TO_ENCODER:
encoder = _TYPE_TO_ENCODER[type(o)]
json_struct = encoder(o)
json_struct[self.TYPE_ID] = type(o).__name__
return json_struct
return super(JsonEncoder, self).default(o) | python | def default(self, o):
"""Inherit docs."""
if type(o) in _TYPE_TO_ENCODER:
encoder = _TYPE_TO_ENCODER[type(o)]
json_struct = encoder(o)
json_struct[self.TYPE_ID] = type(o).__name__
return json_struct
return super(JsonEncoder, self).default(o) | Inherit docs. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/util.py#L160-L167 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/util.py | JsonDecoder._dict_to_obj | def _dict_to_obj(self, d):
"""Converts a dictionary of json object to a Python object."""
if JsonEncoder.TYPE_ID not in d:
return d
type_name = d.pop(JsonEncoder.TYPE_ID)
if type_name in _TYPE_NAME_TO_DECODER:
decoder = _TYPE_NAME_TO_DECODER[type_name]
return decoder(d)
else:
raise TypeError("Invalid type %s.", type_name) | python | def _dict_to_obj(self, d):
"""Converts a dictionary of json object to a Python object."""
if JsonEncoder.TYPE_ID not in d:
return d
type_name = d.pop(JsonEncoder.TYPE_ID)
if type_name in _TYPE_NAME_TO_DECODER:
decoder = _TYPE_NAME_TO_DECODER[type_name]
return decoder(d)
else:
raise TypeError("Invalid type %s.", type_name) | Converts a dictionary of json object to a Python object. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/util.py#L178-L188 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _short_repr | def _short_repr(obj):
"""Helper function returns a truncated repr() of an object."""
stringified = pprint.saferepr(obj)
if len(stringified) > 200:
return '%s... (%d bytes)' % (stringified[:200], len(stringified))
return stringified | python | def _short_repr(obj):
"""Helper function returns a truncated repr() of an object."""
stringified = pprint.saferepr(obj)
if len(stringified) > 200:
return '%s... (%d bytes)' % (stringified[:200], len(stringified))
return stringified | Helper function returns a truncated repr() of an object. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1233-L1238 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _write_json_blob | def _write_json_blob(encoded_value, pipeline_id=None):
"""Writes a JSON encoded value to a Cloud Storage File.
This function will store the blob in a GCS file in the default bucket under
the appengine_pipeline directory. Optionally using another directory level
specified by pipeline_id
Args:
encoded_value: The encoded JSON string.
pipeline_id: A pipeline id to segment files in Cloud Storage, if none,
the file will be created under appengine_pipeline
Returns:
The blobstore.BlobKey for the file that was created.
"""
default_bucket = app_identity.get_default_gcs_bucket_name()
if default_bucket is None:
raise Exception(
"No default cloud storage bucket has been set for this application. "
"This app was likely created before v1.9.0, please see: "
"https://cloud.google.com/appengine/docs/php/googlestorage/setup")
path_components = ['/', default_bucket, "appengine_pipeline"]
if pipeline_id:
path_components.append(pipeline_id)
path_components.append(uuid.uuid4().hex)
# Use posixpath to get a / even if we're running on windows somehow
file_name = posixpath.join(*path_components)
with cloudstorage.open(file_name, 'w', content_type='application/json') as f:
for start_index in xrange(0, len(encoded_value), _MAX_JSON_SIZE):
end_index = start_index + _MAX_JSON_SIZE
f.write(encoded_value[start_index:end_index])
key_str = blobstore.create_gs_key("/gs" + file_name)
logging.debug("Created blob for filename = %s gs_key = %s", file_name, key_str)
return blobstore.BlobKey(key_str) | python | def _write_json_blob(encoded_value, pipeline_id=None):
"""Writes a JSON encoded value to a Cloud Storage File.
This function will store the blob in a GCS file in the default bucket under
the appengine_pipeline directory. Optionally using another directory level
specified by pipeline_id
Args:
encoded_value: The encoded JSON string.
pipeline_id: A pipeline id to segment files in Cloud Storage, if none,
the file will be created under appengine_pipeline
Returns:
The blobstore.BlobKey for the file that was created.
"""
default_bucket = app_identity.get_default_gcs_bucket_name()
if default_bucket is None:
raise Exception(
"No default cloud storage bucket has been set for this application. "
"This app was likely created before v1.9.0, please see: "
"https://cloud.google.com/appengine/docs/php/googlestorage/setup")
path_components = ['/', default_bucket, "appengine_pipeline"]
if pipeline_id:
path_components.append(pipeline_id)
path_components.append(uuid.uuid4().hex)
# Use posixpath to get a / even if we're running on windows somehow
file_name = posixpath.join(*path_components)
with cloudstorage.open(file_name, 'w', content_type='application/json') as f:
for start_index in xrange(0, len(encoded_value), _MAX_JSON_SIZE):
end_index = start_index + _MAX_JSON_SIZE
f.write(encoded_value[start_index:end_index])
key_str = blobstore.create_gs_key("/gs" + file_name)
logging.debug("Created blob for filename = %s gs_key = %s", file_name, key_str)
return blobstore.BlobKey(key_str) | Writes a JSON encoded value to a Cloud Storage File.
This function will store the blob in a GCS file in the default bucket under
the appengine_pipeline directory. Optionally using another directory level
specified by pipeline_id
Args:
encoded_value: The encoded JSON string.
pipeline_id: A pipeline id to segment files in Cloud Storage, if none,
the file will be created under appengine_pipeline
Returns:
The blobstore.BlobKey for the file that was created. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1241-L1276 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _dereference_args | def _dereference_args(pipeline_name, args, kwargs):
"""Dereference a Pipeline's arguments that are slots, validating them.
Each argument value passed in is assumed to be a dictionary with the format:
{'type': 'value', 'value': 'serializable'} # A resolved value.
{'type': 'slot', 'slot_key': 'str() on a db.Key'} # A pending Slot.
Args:
pipeline_name: The name of the pipeline class; used for debugging.
args: Iterable of positional arguments.
kwargs: Dictionary of keyword arguments.
Returns:
Tuple (args, kwargs) where:
Args: A list of positional arguments values that are all dereferenced.
Kwargs: A list of keyword arguments values that are all dereferenced.
Raises:
SlotNotFilledError if any of the supplied 'slot_key' records are not
present in the Datastore or have not yet been filled.
UnexpectedPipelineError if an unknown parameter type was passed.
"""
lookup_slots = set()
for arg in itertools.chain(args, kwargs.itervalues()):
if arg['type'] == 'slot':
lookup_slots.add(db.Key(arg['slot_key']))
slot_dict = {}
for key, slot_record in zip(lookup_slots, db.get(lookup_slots)):
if slot_record is None or slot_record.status != _SlotRecord.FILLED:
raise SlotNotFilledError(
'Slot "%s" missing its value. From %s(*args=%s, **kwargs=%s)' %
(key, pipeline_name, _short_repr(args), _short_repr(kwargs)))
slot_dict[key] = slot_record.value
arg_list = []
for current_arg in args:
if current_arg['type'] == 'slot':
arg_list.append(slot_dict[db.Key(current_arg['slot_key'])])
elif current_arg['type'] == 'value':
arg_list.append(current_arg['value'])
else:
raise UnexpectedPipelineError('Unknown parameter type: %r' % current_arg)
kwarg_dict = {}
for key, current_arg in kwargs.iteritems():
if current_arg['type'] == 'slot':
kwarg_dict[key] = slot_dict[db.Key(current_arg['slot_key'])]
elif current_arg['type'] == 'value':
kwarg_dict[key] = current_arg['value']
else:
raise UnexpectedPipelineError('Unknown parameter type: %r' % current_arg)
return (arg_list, kwarg_dict) | python | def _dereference_args(pipeline_name, args, kwargs):
"""Dereference a Pipeline's arguments that are slots, validating them.
Each argument value passed in is assumed to be a dictionary with the format:
{'type': 'value', 'value': 'serializable'} # A resolved value.
{'type': 'slot', 'slot_key': 'str() on a db.Key'} # A pending Slot.
Args:
pipeline_name: The name of the pipeline class; used for debugging.
args: Iterable of positional arguments.
kwargs: Dictionary of keyword arguments.
Returns:
Tuple (args, kwargs) where:
Args: A list of positional arguments values that are all dereferenced.
Kwargs: A list of keyword arguments values that are all dereferenced.
Raises:
SlotNotFilledError if any of the supplied 'slot_key' records are not
present in the Datastore or have not yet been filled.
UnexpectedPipelineError if an unknown parameter type was passed.
"""
lookup_slots = set()
for arg in itertools.chain(args, kwargs.itervalues()):
if arg['type'] == 'slot':
lookup_slots.add(db.Key(arg['slot_key']))
slot_dict = {}
for key, slot_record in zip(lookup_slots, db.get(lookup_slots)):
if slot_record is None or slot_record.status != _SlotRecord.FILLED:
raise SlotNotFilledError(
'Slot "%s" missing its value. From %s(*args=%s, **kwargs=%s)' %
(key, pipeline_name, _short_repr(args), _short_repr(kwargs)))
slot_dict[key] = slot_record.value
arg_list = []
for current_arg in args:
if current_arg['type'] == 'slot':
arg_list.append(slot_dict[db.Key(current_arg['slot_key'])])
elif current_arg['type'] == 'value':
arg_list.append(current_arg['value'])
else:
raise UnexpectedPipelineError('Unknown parameter type: %r' % current_arg)
kwarg_dict = {}
for key, current_arg in kwargs.iteritems():
if current_arg['type'] == 'slot':
kwarg_dict[key] = slot_dict[db.Key(current_arg['slot_key'])]
elif current_arg['type'] == 'value':
kwarg_dict[key] = current_arg['value']
else:
raise UnexpectedPipelineError('Unknown parameter type: %r' % current_arg)
return (arg_list, kwarg_dict) | Dereference a Pipeline's arguments that are slots, validating them.
Each argument value passed in is assumed to be a dictionary with the format:
{'type': 'value', 'value': 'serializable'} # A resolved value.
{'type': 'slot', 'slot_key': 'str() on a db.Key'} # A pending Slot.
Args:
pipeline_name: The name of the pipeline class; used for debugging.
args: Iterable of positional arguments.
kwargs: Dictionary of keyword arguments.
Returns:
Tuple (args, kwargs) where:
Args: A list of positional arguments values that are all dereferenced.
Kwargs: A list of keyword arguments values that are all dereferenced.
Raises:
SlotNotFilledError if any of the supplied 'slot_key' records are not
present in the Datastore or have not yet been filled.
UnexpectedPipelineError if an unknown parameter type was passed. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1279-L1332 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _generate_args | def _generate_args(pipeline, future, queue_name, base_path):
"""Generate the params used to describe a Pipeline's depedencies.
The arguments passed to this method may be normal values, Slot instances
(for named outputs), or PipelineFuture instances (for referring to the
default output slot).
Args:
pipeline: The Pipeline instance to generate args for.
future: The PipelineFuture for the Pipeline these arguments correspond to.
queue_name: The queue to run the pipeline on.
base_path: Relative URL for pipeline URL handlers.
Returns:
Tuple (dependent_slots, output_slot_keys, params_text, params_blob) where:
dependent_slots: List of db.Key instances of _SlotRecords on which
this pipeline will need to block before execution (passed to
create a _BarrierRecord for running the pipeline).
output_slot_keys: List of db.Key instances of _SlotRecords that will
be filled by this pipeline during its execution (passed to create
a _BarrierRecord for finalizing the pipeline).
params_text: JSON dictionary of pipeline parameters to be serialized and
saved in a corresponding _PipelineRecord. Will be None if the params are
too big and must be saved in a blob instead.
params_blob: JSON dictionary of pipeline parameters to be serialized and
saved in a Blob file, and then attached to a _PipelineRecord. Will be
None if the params data size was small enough to fit in the entity.
"""
params = {
'args': [],
'kwargs': {},
'after_all': [],
'output_slots': {},
'class_path': pipeline._class_path,
'queue_name': queue_name,
'base_path': base_path,
'backoff_seconds': pipeline.backoff_seconds,
'backoff_factor': pipeline.backoff_factor,
'max_attempts': pipeline.max_attempts,
'task_retry': pipeline.task_retry,
'target': pipeline.target,
}
dependent_slots = set()
arg_list = params['args']
for current_arg in pipeline.args:
if isinstance(current_arg, PipelineFuture):
current_arg = current_arg.default
if isinstance(current_arg, Slot):
arg_list.append({'type': 'slot', 'slot_key': str(current_arg.key)})
dependent_slots.add(current_arg.key)
else:
arg_list.append({'type': 'value', 'value': current_arg})
kwarg_dict = params['kwargs']
for name, current_arg in pipeline.kwargs.iteritems():
if isinstance(current_arg, PipelineFuture):
current_arg = current_arg.default
if isinstance(current_arg, Slot):
kwarg_dict[name] = {'type': 'slot', 'slot_key': str(current_arg.key)}
dependent_slots.add(current_arg.key)
else:
kwarg_dict[name] = {'type': 'value', 'value': current_arg}
after_all = params['after_all']
for other_future in future._after_all_pipelines:
slot_key = other_future._output_dict['default'].key
after_all.append(str(slot_key))
dependent_slots.add(slot_key)
output_slots = params['output_slots']
output_slot_keys = set()
for name, slot in future._output_dict.iteritems():
output_slot_keys.add(slot.key)
output_slots[name] = str(slot.key)
params_encoded = json.dumps(params, cls=mr_util.JsonEncoder)
params_text = None
params_blob = None
if len(params_encoded) > _MAX_JSON_SIZE:
params_blob = _write_json_blob(params_encoded, pipeline.pipeline_id)
else:
params_text = params_encoded
return dependent_slots, output_slot_keys, params_text, params_blob | python | def _generate_args(pipeline, future, queue_name, base_path):
"""Generate the params used to describe a Pipeline's depedencies.
The arguments passed to this method may be normal values, Slot instances
(for named outputs), or PipelineFuture instances (for referring to the
default output slot).
Args:
pipeline: The Pipeline instance to generate args for.
future: The PipelineFuture for the Pipeline these arguments correspond to.
queue_name: The queue to run the pipeline on.
base_path: Relative URL for pipeline URL handlers.
Returns:
Tuple (dependent_slots, output_slot_keys, params_text, params_blob) where:
dependent_slots: List of db.Key instances of _SlotRecords on which
this pipeline will need to block before execution (passed to
create a _BarrierRecord for running the pipeline).
output_slot_keys: List of db.Key instances of _SlotRecords that will
be filled by this pipeline during its execution (passed to create
a _BarrierRecord for finalizing the pipeline).
params_text: JSON dictionary of pipeline parameters to be serialized and
saved in a corresponding _PipelineRecord. Will be None if the params are
too big and must be saved in a blob instead.
params_blob: JSON dictionary of pipeline parameters to be serialized and
saved in a Blob file, and then attached to a _PipelineRecord. Will be
None if the params data size was small enough to fit in the entity.
"""
params = {
'args': [],
'kwargs': {},
'after_all': [],
'output_slots': {},
'class_path': pipeline._class_path,
'queue_name': queue_name,
'base_path': base_path,
'backoff_seconds': pipeline.backoff_seconds,
'backoff_factor': pipeline.backoff_factor,
'max_attempts': pipeline.max_attempts,
'task_retry': pipeline.task_retry,
'target': pipeline.target,
}
dependent_slots = set()
arg_list = params['args']
for current_arg in pipeline.args:
if isinstance(current_arg, PipelineFuture):
current_arg = current_arg.default
if isinstance(current_arg, Slot):
arg_list.append({'type': 'slot', 'slot_key': str(current_arg.key)})
dependent_slots.add(current_arg.key)
else:
arg_list.append({'type': 'value', 'value': current_arg})
kwarg_dict = params['kwargs']
for name, current_arg in pipeline.kwargs.iteritems():
if isinstance(current_arg, PipelineFuture):
current_arg = current_arg.default
if isinstance(current_arg, Slot):
kwarg_dict[name] = {'type': 'slot', 'slot_key': str(current_arg.key)}
dependent_slots.add(current_arg.key)
else:
kwarg_dict[name] = {'type': 'value', 'value': current_arg}
after_all = params['after_all']
for other_future in future._after_all_pipelines:
slot_key = other_future._output_dict['default'].key
after_all.append(str(slot_key))
dependent_slots.add(slot_key)
output_slots = params['output_slots']
output_slot_keys = set()
for name, slot in future._output_dict.iteritems():
output_slot_keys.add(slot.key)
output_slots[name] = str(slot.key)
params_encoded = json.dumps(params, cls=mr_util.JsonEncoder)
params_text = None
params_blob = None
if len(params_encoded) > _MAX_JSON_SIZE:
params_blob = _write_json_blob(params_encoded, pipeline.pipeline_id)
else:
params_text = params_encoded
return dependent_slots, output_slot_keys, params_text, params_blob | Generate the params used to describe a Pipeline's depedencies.
The arguments passed to this method may be normal values, Slot instances
(for named outputs), or PipelineFuture instances (for referring to the
default output slot).
Args:
pipeline: The Pipeline instance to generate args for.
future: The PipelineFuture for the Pipeline these arguments correspond to.
queue_name: The queue to run the pipeline on.
base_path: Relative URL for pipeline URL handlers.
Returns:
Tuple (dependent_slots, output_slot_keys, params_text, params_blob) where:
dependent_slots: List of db.Key instances of _SlotRecords on which
this pipeline will need to block before execution (passed to
create a _BarrierRecord for running the pipeline).
output_slot_keys: List of db.Key instances of _SlotRecords that will
be filled by this pipeline during its execution (passed to create
a _BarrierRecord for finalizing the pipeline).
params_text: JSON dictionary of pipeline parameters to be serialized and
saved in a corresponding _PipelineRecord. Will be None if the params are
too big and must be saved in a blob instead.
params_blob: JSON dictionary of pipeline parameters to be serialized and
saved in a Blob file, and then attached to a _PipelineRecord. Will be
None if the params data size was small enough to fit in the entity. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1335-L1419 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _get_timestamp_ms | def _get_timestamp_ms(when):
"""Converts a datetime.datetime to integer milliseconds since the epoch.
Requires special handling to preserve microseconds.
Args:
when: A datetime.datetime instance.
Returns:
Integer time since the epoch in milliseconds. If the supplied 'when' is
None, the return value will be None.
"""
if when is None:
return None
ms_since_epoch = float(time.mktime(when.utctimetuple()) * 1000.0)
ms_since_epoch += when.microsecond / 1000.0
return int(ms_since_epoch) | python | def _get_timestamp_ms(when):
"""Converts a datetime.datetime to integer milliseconds since the epoch.
Requires special handling to preserve microseconds.
Args:
when: A datetime.datetime instance.
Returns:
Integer time since the epoch in milliseconds. If the supplied 'when' is
None, the return value will be None.
"""
if when is None:
return None
ms_since_epoch = float(time.mktime(when.utctimetuple()) * 1000.0)
ms_since_epoch += when.microsecond / 1000.0
return int(ms_since_epoch) | Converts a datetime.datetime to integer milliseconds since the epoch.
Requires special handling to preserve microseconds.
Args:
when: A datetime.datetime instance.
Returns:
Integer time since the epoch in milliseconds. If the supplied 'when' is
None, the return value will be None. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L2872-L2888 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _get_internal_status | def _get_internal_status(pipeline_key=None,
pipeline_dict=None,
slot_dict=None,
barrier_dict=None,
status_dict=None):
"""Gets the UI dictionary of a pipeline from a set of status dictionaries.
Args:
pipeline_key: The key of the pipeline to lookup.
pipeline_dict: Dictionary mapping pipeline db.Key to _PipelineRecord.
Default is an empty dictionary.
slot_dict: Dictionary mapping slot db.Key to _SlotRecord.
Default is an empty dictionary.
barrier_dict: Dictionary mapping barrier db.Key to _BarrierRecord.
Default is an empty dictionary.
status_dict: Dictionary mapping status record db.Key to _StatusRecord.
Default is an empty dictionary.
Returns:
Dictionary with the keys:
classPath: The pipeline function being run.
args: List of positional argument slot dictionaries.
kwargs: Dictionary of keyword argument slot dictionaries.
outputs: Dictionary of output slot dictionaries.
children: List of child pipeline IDs.
queueName: Queue on which this pipeline is running.
afterSlotKeys: List of Slot Ids after which this pipeline runs.
currentAttempt: Number of the current attempt, starting at 1.
maxAttempts: Maximum number of attempts before aborting.
backoffSeconds: Constant factor for backoff before retrying.
backoffFactor: Exponential factor for backoff before retrying.
status: Current status of the pipeline.
startTimeMs: When this pipeline ran or will run due to retries, if present.
endTimeMs: When this pipeline finalized, if present.
lastRetryMessage: Why the pipeline failed during the last retry, if there
was a failure; may be empty.
abortMessage: For root pipelines, why the pipeline was aborted if it was
aborted; may be empty.
Dictionary will contain these keys if explicit status is set:
statusTimeMs: When the status was set as milliseconds since the epoch.
statusMessage: Status message, if present.
statusConsoleUrl: The relative URL for the console of this pipeline.
statusLinks: Dictionary mapping human-readable names to relative URLs
for related URLs to this pipeline.
Raises:
PipelineStatusError if any input is bad.
"""
if pipeline_dict is None:
pipeline_dict = {}
if slot_dict is None:
slot_dict = {}
if barrier_dict is None:
barrier_dict = {}
if status_dict is None:
status_dict = {}
pipeline_record = pipeline_dict.get(pipeline_key)
if pipeline_record is None:
raise PipelineStatusError(
'Could not find pipeline ID "%s"' % pipeline_key.name())
params = pipeline_record.params
root_pipeline_key = \
_PipelineRecord.root_pipeline.get_value_for_datastore(pipeline_record)
default_slot_key = db.Key(params['output_slots']['default'])
start_barrier_key = db.Key.from_path(
_BarrierRecord.kind(), _BarrierRecord.START, parent=pipeline_key)
finalize_barrier_key = db.Key.from_path(
_BarrierRecord.kind(), _BarrierRecord.FINALIZE, parent=pipeline_key)
status_record_key = db.Key.from_path(
_StatusRecord.kind(), pipeline_key.name())
start_barrier = barrier_dict.get(start_barrier_key)
finalize_barrier = barrier_dict.get(finalize_barrier_key)
default_slot = slot_dict.get(default_slot_key)
status_record = status_dict.get(status_record_key)
if finalize_barrier is None:
raise PipelineStatusError(
'Finalization barrier missing for pipeline ID "%s"' %
pipeline_key.name())
if default_slot is None:
raise PipelineStatusError(
'Default output slot with key=%s missing for pipeline ID "%s"' % (
default_slot_key, pipeline_key.name()))
output = {
'classPath': pipeline_record.class_path,
'args': list(params['args']),
'kwargs': params['kwargs'].copy(),
'outputs': params['output_slots'].copy(),
'children': [key.name() for key in pipeline_record.fanned_out],
'queueName': params['queue_name'],
'afterSlotKeys': [str(key) for key in params['after_all']],
'currentAttempt': pipeline_record.current_attempt + 1,
'maxAttempts': pipeline_record.max_attempts,
'backoffSeconds': pipeline_record.params['backoff_seconds'],
'backoffFactor': pipeline_record.params['backoff_factor'],
}
# TODO(user): Truncate args, kwargs, and outputs to < 1MB each so we
# can reasonably return the whole tree of pipelines and their outputs.
# Coerce each value to a string to truncate if necessary. For now if the
# params are too big it will just cause the whole status page to break.
# Fix the key names in parameters to match JavaScript style.
for value_dict in itertools.chain(
output['args'], output['kwargs'].itervalues()):
if 'slot_key' in value_dict:
value_dict['slotKey'] = value_dict.pop('slot_key')
# Figure out the pipeline's status.
if pipeline_record.status in (_PipelineRecord.WAITING, _PipelineRecord.RUN):
if default_slot.status == _SlotRecord.FILLED:
status = 'finalizing'
elif (pipeline_record.status == _PipelineRecord.WAITING and
pipeline_record.next_retry_time is not None):
status = 'retry'
elif start_barrier and start_barrier.status == _BarrierRecord.WAITING:
# start_barrier will be missing for root pipelines
status = 'waiting'
else:
status = 'run'
elif pipeline_record.status == _PipelineRecord.DONE:
status = 'done'
elif pipeline_record.status == _PipelineRecord.ABORTED:
status = 'aborted'
output['status'] = status
if status_record:
output['statusTimeMs'] = _get_timestamp_ms(status_record.status_time)
if status_record.message:
output['statusMessage'] = status_record.message
if status_record.console_url:
output['statusConsoleUrl'] = status_record.console_url
if status_record.link_names:
output['statusLinks'] = dict(
zip(status_record.link_names, status_record.link_urls))
# Populate status-depenedent fields.
if status in ('run', 'finalizing', 'done', 'retry'):
if pipeline_record.next_retry_time is not None:
output['startTimeMs'] = _get_timestamp_ms(pipeline_record.next_retry_time)
elif start_barrier:
# start_barrier will be missing for root pipelines
output['startTimeMs'] = _get_timestamp_ms(start_barrier.trigger_time)
elif pipeline_record.start_time:
# Assume this pipeline ran immediately upon spawning with no
# start barrier or it's the root pipeline.
output['startTimeMs'] = _get_timestamp_ms(pipeline_record.start_time)
if status in ('finalizing',):
output['endTimeMs'] = _get_timestamp_ms(default_slot.fill_time)
if status in ('done',):
output['endTimeMs'] = _get_timestamp_ms(pipeline_record.finalized_time)
if pipeline_record.next_retry_time is not None:
output['lastRetryMessage'] = pipeline_record.retry_message
if pipeline_record.abort_message:
output['abortMessage'] = pipeline_record.abort_message
return output | python | def _get_internal_status(pipeline_key=None,
pipeline_dict=None,
slot_dict=None,
barrier_dict=None,
status_dict=None):
"""Gets the UI dictionary of a pipeline from a set of status dictionaries.
Args:
pipeline_key: The key of the pipeline to lookup.
pipeline_dict: Dictionary mapping pipeline db.Key to _PipelineRecord.
Default is an empty dictionary.
slot_dict: Dictionary mapping slot db.Key to _SlotRecord.
Default is an empty dictionary.
barrier_dict: Dictionary mapping barrier db.Key to _BarrierRecord.
Default is an empty dictionary.
status_dict: Dictionary mapping status record db.Key to _StatusRecord.
Default is an empty dictionary.
Returns:
Dictionary with the keys:
classPath: The pipeline function being run.
args: List of positional argument slot dictionaries.
kwargs: Dictionary of keyword argument slot dictionaries.
outputs: Dictionary of output slot dictionaries.
children: List of child pipeline IDs.
queueName: Queue on which this pipeline is running.
afterSlotKeys: List of Slot Ids after which this pipeline runs.
currentAttempt: Number of the current attempt, starting at 1.
maxAttempts: Maximum number of attempts before aborting.
backoffSeconds: Constant factor for backoff before retrying.
backoffFactor: Exponential factor for backoff before retrying.
status: Current status of the pipeline.
startTimeMs: When this pipeline ran or will run due to retries, if present.
endTimeMs: When this pipeline finalized, if present.
lastRetryMessage: Why the pipeline failed during the last retry, if there
was a failure; may be empty.
abortMessage: For root pipelines, why the pipeline was aborted if it was
aborted; may be empty.
Dictionary will contain these keys if explicit status is set:
statusTimeMs: When the status was set as milliseconds since the epoch.
statusMessage: Status message, if present.
statusConsoleUrl: The relative URL for the console of this pipeline.
statusLinks: Dictionary mapping human-readable names to relative URLs
for related URLs to this pipeline.
Raises:
PipelineStatusError if any input is bad.
"""
if pipeline_dict is None:
pipeline_dict = {}
if slot_dict is None:
slot_dict = {}
if barrier_dict is None:
barrier_dict = {}
if status_dict is None:
status_dict = {}
pipeline_record = pipeline_dict.get(pipeline_key)
if pipeline_record is None:
raise PipelineStatusError(
'Could not find pipeline ID "%s"' % pipeline_key.name())
params = pipeline_record.params
root_pipeline_key = \
_PipelineRecord.root_pipeline.get_value_for_datastore(pipeline_record)
default_slot_key = db.Key(params['output_slots']['default'])
start_barrier_key = db.Key.from_path(
_BarrierRecord.kind(), _BarrierRecord.START, parent=pipeline_key)
finalize_barrier_key = db.Key.from_path(
_BarrierRecord.kind(), _BarrierRecord.FINALIZE, parent=pipeline_key)
status_record_key = db.Key.from_path(
_StatusRecord.kind(), pipeline_key.name())
start_barrier = barrier_dict.get(start_barrier_key)
finalize_barrier = barrier_dict.get(finalize_barrier_key)
default_slot = slot_dict.get(default_slot_key)
status_record = status_dict.get(status_record_key)
if finalize_barrier is None:
raise PipelineStatusError(
'Finalization barrier missing for pipeline ID "%s"' %
pipeline_key.name())
if default_slot is None:
raise PipelineStatusError(
'Default output slot with key=%s missing for pipeline ID "%s"' % (
default_slot_key, pipeline_key.name()))
output = {
'classPath': pipeline_record.class_path,
'args': list(params['args']),
'kwargs': params['kwargs'].copy(),
'outputs': params['output_slots'].copy(),
'children': [key.name() for key in pipeline_record.fanned_out],
'queueName': params['queue_name'],
'afterSlotKeys': [str(key) for key in params['after_all']],
'currentAttempt': pipeline_record.current_attempt + 1,
'maxAttempts': pipeline_record.max_attempts,
'backoffSeconds': pipeline_record.params['backoff_seconds'],
'backoffFactor': pipeline_record.params['backoff_factor'],
}
# TODO(user): Truncate args, kwargs, and outputs to < 1MB each so we
# can reasonably return the whole tree of pipelines and their outputs.
# Coerce each value to a string to truncate if necessary. For now if the
# params are too big it will just cause the whole status page to break.
# Fix the key names in parameters to match JavaScript style.
for value_dict in itertools.chain(
output['args'], output['kwargs'].itervalues()):
if 'slot_key' in value_dict:
value_dict['slotKey'] = value_dict.pop('slot_key')
# Figure out the pipeline's status.
if pipeline_record.status in (_PipelineRecord.WAITING, _PipelineRecord.RUN):
if default_slot.status == _SlotRecord.FILLED:
status = 'finalizing'
elif (pipeline_record.status == _PipelineRecord.WAITING and
pipeline_record.next_retry_time is not None):
status = 'retry'
elif start_barrier and start_barrier.status == _BarrierRecord.WAITING:
# start_barrier will be missing for root pipelines
status = 'waiting'
else:
status = 'run'
elif pipeline_record.status == _PipelineRecord.DONE:
status = 'done'
elif pipeline_record.status == _PipelineRecord.ABORTED:
status = 'aborted'
output['status'] = status
if status_record:
output['statusTimeMs'] = _get_timestamp_ms(status_record.status_time)
if status_record.message:
output['statusMessage'] = status_record.message
if status_record.console_url:
output['statusConsoleUrl'] = status_record.console_url
if status_record.link_names:
output['statusLinks'] = dict(
zip(status_record.link_names, status_record.link_urls))
# Populate status-depenedent fields.
if status in ('run', 'finalizing', 'done', 'retry'):
if pipeline_record.next_retry_time is not None:
output['startTimeMs'] = _get_timestamp_ms(pipeline_record.next_retry_time)
elif start_barrier:
# start_barrier will be missing for root pipelines
output['startTimeMs'] = _get_timestamp_ms(start_barrier.trigger_time)
elif pipeline_record.start_time:
# Assume this pipeline ran immediately upon spawning with no
# start barrier or it's the root pipeline.
output['startTimeMs'] = _get_timestamp_ms(pipeline_record.start_time)
if status in ('finalizing',):
output['endTimeMs'] = _get_timestamp_ms(default_slot.fill_time)
if status in ('done',):
output['endTimeMs'] = _get_timestamp_ms(pipeline_record.finalized_time)
if pipeline_record.next_retry_time is not None:
output['lastRetryMessage'] = pipeline_record.retry_message
if pipeline_record.abort_message:
output['abortMessage'] = pipeline_record.abort_message
return output | Gets the UI dictionary of a pipeline from a set of status dictionaries.
Args:
pipeline_key: The key of the pipeline to lookup.
pipeline_dict: Dictionary mapping pipeline db.Key to _PipelineRecord.
Default is an empty dictionary.
slot_dict: Dictionary mapping slot db.Key to _SlotRecord.
Default is an empty dictionary.
barrier_dict: Dictionary mapping barrier db.Key to _BarrierRecord.
Default is an empty dictionary.
status_dict: Dictionary mapping status record db.Key to _StatusRecord.
Default is an empty dictionary.
Returns:
Dictionary with the keys:
classPath: The pipeline function being run.
args: List of positional argument slot dictionaries.
kwargs: Dictionary of keyword argument slot dictionaries.
outputs: Dictionary of output slot dictionaries.
children: List of child pipeline IDs.
queueName: Queue on which this pipeline is running.
afterSlotKeys: List of Slot Ids after which this pipeline runs.
currentAttempt: Number of the current attempt, starting at 1.
maxAttempts: Maximum number of attempts before aborting.
backoffSeconds: Constant factor for backoff before retrying.
backoffFactor: Exponential factor for backoff before retrying.
status: Current status of the pipeline.
startTimeMs: When this pipeline ran or will run due to retries, if present.
endTimeMs: When this pipeline finalized, if present.
lastRetryMessage: Why the pipeline failed during the last retry, if there
was a failure; may be empty.
abortMessage: For root pipelines, why the pipeline was aborted if it was
aborted; may be empty.
Dictionary will contain these keys if explicit status is set:
statusTimeMs: When the status was set as milliseconds since the epoch.
statusMessage: Status message, if present.
statusConsoleUrl: The relative URL for the console of this pipeline.
statusLinks: Dictionary mapping human-readable names to relative URLs
for related URLs to this pipeline.
Raises:
PipelineStatusError if any input is bad. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L2891-L3056 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _get_internal_slot | def _get_internal_slot(slot_key=None,
filler_pipeline_key=None,
slot_dict=None):
"""Gets information about a _SlotRecord for display in UI.
Args:
slot_key: The db.Key of the slot to fetch.
filler_pipeline_key: In the case the slot has not yet been filled, assume
that the given db.Key (for a _PipelineRecord) will be the filler of
the slot in the future.
slot_dict: The slot JSON dictionary.
Returns:
Dictionary with the keys:
status: Slot status: 'filled' or 'waiting'
fillTimeMs: Time in milliseconds since the epoch of when it was filled.
value: The current value of the slot, which is a slot's JSON dictionary.
fillerPipelineId: The pipeline ID of what stage has or should fill
this slot.
Raises:
PipelineStatusError if any input is bad.
"""
if slot_dict is None:
slot_dict = {}
slot_record = slot_dict.get(slot_key)
if slot_record is None:
raise PipelineStatusError(
'Could not find data for output slot key "%s".' % slot_key)
output = {}
if slot_record.status == _SlotRecord.FILLED:
output['status'] = 'filled'
output['fillTimeMs'] = _get_timestamp_ms(slot_record.fill_time)
output['value'] = slot_record.value
filler_pipeline_key = (
_SlotRecord.filler.get_value_for_datastore(slot_record))
else:
output['status'] = 'waiting'
if filler_pipeline_key:
output['fillerPipelineId'] = filler_pipeline_key.name()
return output | python | def _get_internal_slot(slot_key=None,
filler_pipeline_key=None,
slot_dict=None):
"""Gets information about a _SlotRecord for display in UI.
Args:
slot_key: The db.Key of the slot to fetch.
filler_pipeline_key: In the case the slot has not yet been filled, assume
that the given db.Key (for a _PipelineRecord) will be the filler of
the slot in the future.
slot_dict: The slot JSON dictionary.
Returns:
Dictionary with the keys:
status: Slot status: 'filled' or 'waiting'
fillTimeMs: Time in milliseconds since the epoch of when it was filled.
value: The current value of the slot, which is a slot's JSON dictionary.
fillerPipelineId: The pipeline ID of what stage has or should fill
this slot.
Raises:
PipelineStatusError if any input is bad.
"""
if slot_dict is None:
slot_dict = {}
slot_record = slot_dict.get(slot_key)
if slot_record is None:
raise PipelineStatusError(
'Could not find data for output slot key "%s".' % slot_key)
output = {}
if slot_record.status == _SlotRecord.FILLED:
output['status'] = 'filled'
output['fillTimeMs'] = _get_timestamp_ms(slot_record.fill_time)
output['value'] = slot_record.value
filler_pipeline_key = (
_SlotRecord.filler.get_value_for_datastore(slot_record))
else:
output['status'] = 'waiting'
if filler_pipeline_key:
output['fillerPipelineId'] = filler_pipeline_key.name()
return output | Gets information about a _SlotRecord for display in UI.
Args:
slot_key: The db.Key of the slot to fetch.
filler_pipeline_key: In the case the slot has not yet been filled, assume
that the given db.Key (for a _PipelineRecord) will be the filler of
the slot in the future.
slot_dict: The slot JSON dictionary.
Returns:
Dictionary with the keys:
status: Slot status: 'filled' or 'waiting'
fillTimeMs: Time in milliseconds since the epoch of when it was filled.
value: The current value of the slot, which is a slot's JSON dictionary.
fillerPipelineId: The pipeline ID of what stage has or should fill
this slot.
Raises:
PipelineStatusError if any input is bad. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L3059-L3103 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | get_status_tree | def get_status_tree(root_pipeline_id):
"""Gets the full status tree of a pipeline.
Args:
root_pipeline_id: The pipeline ID to get status for.
Returns:
Dictionary with the keys:
rootPipelineId: The ID of the root pipeline.
slots: Mapping of slot IDs to result of from _get_internal_slot.
pipelines: Mapping of pipeline IDs to result of _get_internal_status.
Raises:
PipelineStatusError if any input is bad.
"""
root_pipeline_key = db.Key.from_path(_PipelineRecord.kind(), root_pipeline_id)
root_pipeline_record = db.get(root_pipeline_key)
if root_pipeline_record is None:
raise PipelineStatusError(
'Could not find pipeline ID "%s"' % root_pipeline_id)
# If the supplied root_pipeline_id is not actually the root pipeline that's
# okay. We'll find the real root and override the value they passed in.
actual_root_key = _PipelineRecord.root_pipeline.get_value_for_datastore(
root_pipeline_record)
if actual_root_key != root_pipeline_key:
root_pipeline_key = actual_root_key
root_pipeline_id = root_pipeline_key.id_or_name()
root_pipeline_record = db.get(root_pipeline_key)
if not root_pipeline_record:
raise PipelineStatusError(
'Could not find pipeline ID "%s"' % root_pipeline_id)
# Run all queries asynchronously.
queries = {}
for model in (_PipelineRecord, _SlotRecord, _BarrierRecord, _StatusRecord):
queries[model] = model.all().filter(
'root_pipeline =', root_pipeline_key).run(batch_size=1000)
found_pipeline_dict = dict(
(stage.key(), stage) for stage in queries[_PipelineRecord])
found_slot_dict = dict(
(slot.key(), slot) for slot in queries[_SlotRecord])
found_barrier_dict = dict(
(barrier.key(), barrier) for barrier in queries[_BarrierRecord])
found_status_dict = dict(
(status.key(), status) for status in queries[_StatusRecord])
# Breadth-first traversal of _PipelineRecord instances by following
# _PipelineRecord.fanned_out property values.
valid_pipeline_keys = set([root_pipeline_key])
slot_filler_dict = {} # slot_key to pipeline_key
expand_stack = [root_pipeline_record]
while expand_stack:
old_stack = expand_stack
expand_stack = []
for pipeline_record in old_stack:
for child_pipeline_key in pipeline_record.fanned_out:
# This will let us prune off those pipelines which were allocated in
# the Datastore but were never run due to mid-flight task failures.
child_pipeline_record = found_pipeline_dict.get(child_pipeline_key)
if child_pipeline_record is None:
raise PipelineStatusError(
'Pipeline ID "%s" points to child ID "%s" which does not exist.'
% (pipeline_record.key().name(), child_pipeline_key.name()))
expand_stack.append(child_pipeline_record)
valid_pipeline_keys.add(child_pipeline_key)
# Figure out the deepest pipeline that's responsible for outputting to
# a particular _SlotRecord, so we can report which pipeline *should*
# be the filler.
child_outputs = child_pipeline_record.params['output_slots']
for output_slot_key in child_outputs.itervalues():
slot_filler_dict[db.Key(output_slot_key)] = child_pipeline_key
output = {
'rootPipelineId': root_pipeline_id,
'slots': {},
'pipelines': {},
}
for pipeline_key in found_pipeline_dict.keys():
if pipeline_key not in valid_pipeline_keys:
continue
output['pipelines'][pipeline_key.name()] = _get_internal_status(
pipeline_key=pipeline_key,
pipeline_dict=found_pipeline_dict,
slot_dict=found_slot_dict,
barrier_dict=found_barrier_dict,
status_dict=found_status_dict)
for slot_key, filler_pipeline_key in slot_filler_dict.iteritems():
output['slots'][str(slot_key)] = _get_internal_slot(
slot_key=slot_key,
filler_pipeline_key=filler_pipeline_key,
slot_dict=found_slot_dict)
return output | python | def get_status_tree(root_pipeline_id):
"""Gets the full status tree of a pipeline.
Args:
root_pipeline_id: The pipeline ID to get status for.
Returns:
Dictionary with the keys:
rootPipelineId: The ID of the root pipeline.
slots: Mapping of slot IDs to result of from _get_internal_slot.
pipelines: Mapping of pipeline IDs to result of _get_internal_status.
Raises:
PipelineStatusError if any input is bad.
"""
root_pipeline_key = db.Key.from_path(_PipelineRecord.kind(), root_pipeline_id)
root_pipeline_record = db.get(root_pipeline_key)
if root_pipeline_record is None:
raise PipelineStatusError(
'Could not find pipeline ID "%s"' % root_pipeline_id)
# If the supplied root_pipeline_id is not actually the root pipeline that's
# okay. We'll find the real root and override the value they passed in.
actual_root_key = _PipelineRecord.root_pipeline.get_value_for_datastore(
root_pipeline_record)
if actual_root_key != root_pipeline_key:
root_pipeline_key = actual_root_key
root_pipeline_id = root_pipeline_key.id_or_name()
root_pipeline_record = db.get(root_pipeline_key)
if not root_pipeline_record:
raise PipelineStatusError(
'Could not find pipeline ID "%s"' % root_pipeline_id)
# Run all queries asynchronously.
queries = {}
for model in (_PipelineRecord, _SlotRecord, _BarrierRecord, _StatusRecord):
queries[model] = model.all().filter(
'root_pipeline =', root_pipeline_key).run(batch_size=1000)
found_pipeline_dict = dict(
(stage.key(), stage) for stage in queries[_PipelineRecord])
found_slot_dict = dict(
(slot.key(), slot) for slot in queries[_SlotRecord])
found_barrier_dict = dict(
(barrier.key(), barrier) for barrier in queries[_BarrierRecord])
found_status_dict = dict(
(status.key(), status) for status in queries[_StatusRecord])
# Breadth-first traversal of _PipelineRecord instances by following
# _PipelineRecord.fanned_out property values.
valid_pipeline_keys = set([root_pipeline_key])
slot_filler_dict = {} # slot_key to pipeline_key
expand_stack = [root_pipeline_record]
while expand_stack:
old_stack = expand_stack
expand_stack = []
for pipeline_record in old_stack:
for child_pipeline_key in pipeline_record.fanned_out:
# This will let us prune off those pipelines which were allocated in
# the Datastore but were never run due to mid-flight task failures.
child_pipeline_record = found_pipeline_dict.get(child_pipeline_key)
if child_pipeline_record is None:
raise PipelineStatusError(
'Pipeline ID "%s" points to child ID "%s" which does not exist.'
% (pipeline_record.key().name(), child_pipeline_key.name()))
expand_stack.append(child_pipeline_record)
valid_pipeline_keys.add(child_pipeline_key)
# Figure out the deepest pipeline that's responsible for outputting to
# a particular _SlotRecord, so we can report which pipeline *should*
# be the filler.
child_outputs = child_pipeline_record.params['output_slots']
for output_slot_key in child_outputs.itervalues():
slot_filler_dict[db.Key(output_slot_key)] = child_pipeline_key
output = {
'rootPipelineId': root_pipeline_id,
'slots': {},
'pipelines': {},
}
for pipeline_key in found_pipeline_dict.keys():
if pipeline_key not in valid_pipeline_keys:
continue
output['pipelines'][pipeline_key.name()] = _get_internal_status(
pipeline_key=pipeline_key,
pipeline_dict=found_pipeline_dict,
slot_dict=found_slot_dict,
barrier_dict=found_barrier_dict,
status_dict=found_status_dict)
for slot_key, filler_pipeline_key in slot_filler_dict.iteritems():
output['slots'][str(slot_key)] = _get_internal_slot(
slot_key=slot_key,
filler_pipeline_key=filler_pipeline_key,
slot_dict=found_slot_dict)
return output | Gets the full status tree of a pipeline.
Args:
root_pipeline_id: The pipeline ID to get status for.
Returns:
Dictionary with the keys:
rootPipelineId: The ID of the root pipeline.
slots: Mapping of slot IDs to result of from _get_internal_slot.
pipelines: Mapping of pipeline IDs to result of _get_internal_status.
Raises:
PipelineStatusError if any input is bad. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L3106-L3203 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | get_pipeline_names | def get_pipeline_names():
"""Returns the class paths of all Pipelines defined in alphabetical order."""
class_path_set = set()
for cls in _PipelineMeta._all_classes:
if cls.class_path is not None:
class_path_set.add(cls.class_path)
return sorted(class_path_set) | python | def get_pipeline_names():
"""Returns the class paths of all Pipelines defined in alphabetical order."""
class_path_set = set()
for cls in _PipelineMeta._all_classes:
if cls.class_path is not None:
class_path_set.add(cls.class_path)
return sorted(class_path_set) | Returns the class paths of all Pipelines defined in alphabetical order. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L3206-L3212 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | get_root_list | def get_root_list(class_path=None, cursor=None, count=50):
"""Gets a list root Pipelines.
Args:
class_path: Optional. If supplied, only return root Pipelines with the
given class_path. By default all root pipelines are returned.
cursor: Optional. When supplied, the cursor returned from the last call to
get_root_list which indicates where to pick up.
count: How many pipeline returns to return.
Returns:
Dictionary with the keys:
pipelines: The list of Pipeline records in the same format as
returned by get_status_tree, but with only the roots listed.
cursor: Cursor to pass back to this function to resume the query. Will
only be present if there is another page of results.
Raises:
PipelineStatusError if any input is bad.
"""
query = _PipelineRecord.all(cursor=cursor)
if class_path:
query.filter('class_path =', class_path)
query.filter('is_root_pipeline =', True)
query.order('-start_time')
root_list = query.fetch(count)
fetch_list = []
for pipeline_record in root_list:
fetch_list.append(db.Key(pipeline_record.params['output_slots']['default']))
fetch_list.append(db.Key.from_path(
_BarrierRecord.kind(), _BarrierRecord.FINALIZE,
parent=pipeline_record.key()))
fetch_list.append(db.Key.from_path(
_StatusRecord.kind(), pipeline_record.key().name()))
pipeline_dict = dict((stage.key(), stage) for stage in root_list)
slot_dict = {}
barrier_dict = {}
status_dict = {}
for entity in db.get(fetch_list):
if isinstance(entity, _BarrierRecord):
barrier_dict[entity.key()] = entity
elif isinstance(entity, _SlotRecord):
slot_dict[entity.key()] = entity
elif isinstance(entity, _StatusRecord):
status_dict[entity.key()] = entity
results = []
for pipeline_record in root_list:
try:
output = _get_internal_status(
pipeline_record.key(),
pipeline_dict=pipeline_dict,
slot_dict=slot_dict,
barrier_dict=barrier_dict,
status_dict=status_dict)
output['pipelineId'] = pipeline_record.key().name()
results.append(output)
except PipelineStatusError, e:
output = {'status': e.message}
output['classPath'] = ''
output['pipelineId'] = pipeline_record.key().name()
results.append(output)
result_dict = {}
cursor = query.cursor()
query.with_cursor(cursor)
if query.get(keys_only=True):
result_dict.update(cursor=cursor)
result_dict.update(pipelines=results)
return result_dict | python | def get_root_list(class_path=None, cursor=None, count=50):
"""Gets a list root Pipelines.
Args:
class_path: Optional. If supplied, only return root Pipelines with the
given class_path. By default all root pipelines are returned.
cursor: Optional. When supplied, the cursor returned from the last call to
get_root_list which indicates where to pick up.
count: How many pipeline returns to return.
Returns:
Dictionary with the keys:
pipelines: The list of Pipeline records in the same format as
returned by get_status_tree, but with only the roots listed.
cursor: Cursor to pass back to this function to resume the query. Will
only be present if there is another page of results.
Raises:
PipelineStatusError if any input is bad.
"""
query = _PipelineRecord.all(cursor=cursor)
if class_path:
query.filter('class_path =', class_path)
query.filter('is_root_pipeline =', True)
query.order('-start_time')
root_list = query.fetch(count)
fetch_list = []
for pipeline_record in root_list:
fetch_list.append(db.Key(pipeline_record.params['output_slots']['default']))
fetch_list.append(db.Key.from_path(
_BarrierRecord.kind(), _BarrierRecord.FINALIZE,
parent=pipeline_record.key()))
fetch_list.append(db.Key.from_path(
_StatusRecord.kind(), pipeline_record.key().name()))
pipeline_dict = dict((stage.key(), stage) for stage in root_list)
slot_dict = {}
barrier_dict = {}
status_dict = {}
for entity in db.get(fetch_list):
if isinstance(entity, _BarrierRecord):
barrier_dict[entity.key()] = entity
elif isinstance(entity, _SlotRecord):
slot_dict[entity.key()] = entity
elif isinstance(entity, _StatusRecord):
status_dict[entity.key()] = entity
results = []
for pipeline_record in root_list:
try:
output = _get_internal_status(
pipeline_record.key(),
pipeline_dict=pipeline_dict,
slot_dict=slot_dict,
barrier_dict=barrier_dict,
status_dict=status_dict)
output['pipelineId'] = pipeline_record.key().name()
results.append(output)
except PipelineStatusError, e:
output = {'status': e.message}
output['classPath'] = ''
output['pipelineId'] = pipeline_record.key().name()
results.append(output)
result_dict = {}
cursor = query.cursor()
query.with_cursor(cursor)
if query.get(keys_only=True):
result_dict.update(cursor=cursor)
result_dict.update(pipelines=results)
return result_dict | Gets a list root Pipelines.
Args:
class_path: Optional. If supplied, only return root Pipelines with the
given class_path. By default all root pipelines are returned.
cursor: Optional. When supplied, the cursor returned from the last call to
get_root_list which indicates where to pick up.
count: How many pipeline returns to return.
Returns:
Dictionary with the keys:
pipelines: The list of Pipeline records in the same format as
returned by get_status_tree, but with only the roots listed.
cursor: Cursor to pass back to this function to resume the query. Will
only be present if there is another page of results.
Raises:
PipelineStatusError if any input is bad. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L3215-L3287 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | create_handlers_map | def create_handlers_map(prefix='.*'):
"""Create new handlers map.
Args:
prefix: url prefix to use.
Returns:
list of (regexp, handler) pairs for WSGIApplication constructor.
"""
return [
(prefix + '/output', _BarrierHandler),
(prefix + '/run', _PipelineHandler),
(prefix + '/finalized', _PipelineHandler),
(prefix + '/cleanup', _CleanupHandler),
(prefix + '/abort', _PipelineHandler),
(prefix + '/fanout', _FanoutHandler),
(prefix + '/fanout_abort', _FanoutAbortHandler),
(prefix + '/callback', _CallbackHandler),
(prefix + '/rpc/tree', status_ui._TreeStatusHandler),
(prefix + '/rpc/class_paths', status_ui._ClassPathListHandler),
(prefix + '/rpc/list', status_ui._RootListHandler),
(prefix + '(/.+)', status_ui._StatusUiHandler),
] | python | def create_handlers_map(prefix='.*'):
"""Create new handlers map.
Args:
prefix: url prefix to use.
Returns:
list of (regexp, handler) pairs for WSGIApplication constructor.
"""
return [
(prefix + '/output', _BarrierHandler),
(prefix + '/run', _PipelineHandler),
(prefix + '/finalized', _PipelineHandler),
(prefix + '/cleanup', _CleanupHandler),
(prefix + '/abort', _PipelineHandler),
(prefix + '/fanout', _FanoutHandler),
(prefix + '/fanout_abort', _FanoutAbortHandler),
(prefix + '/callback', _CallbackHandler),
(prefix + '/rpc/tree', status_ui._TreeStatusHandler),
(prefix + '/rpc/class_paths', status_ui._ClassPathListHandler),
(prefix + '/rpc/list', status_ui._RootListHandler),
(prefix + '(/.+)', status_ui._StatusUiHandler),
] | Create new handlers map.
Args:
prefix: url prefix to use.
Returns:
list of (regexp, handler) pairs for WSGIApplication constructor. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L3303-L3325 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Slot.value | def value(self):
"""Returns the current value of this slot.
Returns:
The value of the slot (a serializable Python type).
Raises:
SlotNotFilledError if the value hasn't been filled yet.
"""
if not self.filled:
raise SlotNotFilledError('Slot with name "%s", key "%s" not yet filled.'
% (self.name, self.key))
return self._value | python | def value(self):
"""Returns the current value of this slot.
Returns:
The value of the slot (a serializable Python type).
Raises:
SlotNotFilledError if the value hasn't been filled yet.
"""
if not self.filled:
raise SlotNotFilledError('Slot with name "%s", key "%s" not yet filled.'
% (self.name, self.key))
return self._value | Returns the current value of this slot.
Returns:
The value of the slot (a serializable Python type).
Raises:
SlotNotFilledError if the value hasn't been filled yet. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L203-L215 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Slot.filler | def filler(self):
"""Returns the pipeline ID that filled this slot's value.
Returns:
A string that is the pipeline ID.
Raises:
SlotNotFilledError if the value hasn't been filled yet.
"""
if not self.filled:
raise SlotNotFilledError('Slot with name "%s", key "%s" not yet filled.'
% (self.name, self.key))
return self._filler_pipeline_key.name() | python | def filler(self):
"""Returns the pipeline ID that filled this slot's value.
Returns:
A string that is the pipeline ID.
Raises:
SlotNotFilledError if the value hasn't been filled yet.
"""
if not self.filled:
raise SlotNotFilledError('Slot with name "%s", key "%s" not yet filled.'
% (self.name, self.key))
return self._filler_pipeline_key.name() | Returns the pipeline ID that filled this slot's value.
Returns:
A string that is the pipeline ID.
Raises:
SlotNotFilledError if the value hasn't been filled yet. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L218-L230 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Slot.fill_datetime | def fill_datetime(self):
"""Returns when the slot was filled.
Returns:
A datetime.datetime.
Raises:
SlotNotFilledError if the value hasn't been filled yet.
"""
if not self.filled:
raise SlotNotFilledError('Slot with name "%s", key "%s" not yet filled.'
% (self.name, self.key))
return self._fill_datetime | python | def fill_datetime(self):
"""Returns when the slot was filled.
Returns:
A datetime.datetime.
Raises:
SlotNotFilledError if the value hasn't been filled yet.
"""
if not self.filled:
raise SlotNotFilledError('Slot with name "%s", key "%s" not yet filled.'
% (self.name, self.key))
return self._fill_datetime | Returns when the slot was filled.
Returns:
A datetime.datetime.
Raises:
SlotNotFilledError if the value hasn't been filled yet. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L233-L245 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Slot._set_value | def _set_value(self, slot_record):
"""Sets the value of this slot based on its corresponding _SlotRecord.
Does nothing if the slot has not yet been filled.
Args:
slot_record: The _SlotRecord containing this Slot's value.
"""
if slot_record.status == _SlotRecord.FILLED:
self.filled = True
self._filler_pipeline_key = _SlotRecord.filler.get_value_for_datastore(
slot_record)
self._fill_datetime = slot_record.fill_time
self._value = slot_record.value | python | def _set_value(self, slot_record):
"""Sets the value of this slot based on its corresponding _SlotRecord.
Does nothing if the slot has not yet been filled.
Args:
slot_record: The _SlotRecord containing this Slot's value.
"""
if slot_record.status == _SlotRecord.FILLED:
self.filled = True
self._filler_pipeline_key = _SlotRecord.filler.get_value_for_datastore(
slot_record)
self._fill_datetime = slot_record.fill_time
self._value = slot_record.value | Sets the value of this slot based on its corresponding _SlotRecord.
Does nothing if the slot has not yet been filled.
Args:
slot_record: The _SlotRecord containing this Slot's value. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L247-L260 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | PipelineFuture._inherit_outputs | def _inherit_outputs(self,
pipeline_name,
already_defined,
resolve_outputs=False):
"""Inherits outputs from a calling Pipeline.
Args:
pipeline_name: The Pipeline class name (used for debugging).
already_defined: Maps output name to stringified db.Key (of _SlotRecords)
of any exiting output slots to be inherited by this future.
resolve_outputs: When True, this method will dereference all output slots
before returning back to the caller, making those output slots' values
available.
Raises:
UnexpectedPipelineError when resolve_outputs is True and any of the output
slots could not be retrived from the Datastore.
"""
for name, slot_key in already_defined.iteritems():
if not isinstance(slot_key, db.Key):
slot_key = db.Key(slot_key)
slot = self._output_dict.get(name)
if slot is None:
if self._strict:
raise UnexpectedPipelineError(
'Inherited output named "%s" must be filled but '
'not declared for pipeline class "%s"' % (name, pipeline_name))
else:
self._output_dict[name] = Slot(name=name, slot_key=slot_key)
else:
slot.key = slot_key
slot._exists = True
if resolve_outputs:
slot_key_dict = dict((s.key, s) for s in self._output_dict.itervalues())
all_slots = db.get(slot_key_dict.keys())
for slot, slot_record in zip(slot_key_dict.itervalues(), all_slots):
if slot_record is None:
raise UnexpectedPipelineError(
'Inherited output named "%s" for pipeline class "%s" is '
'missing its Slot in the datastore: "%s"' %
(slot.name, pipeline_name, slot.key))
slot = slot_key_dict[slot_record.key()]
slot._set_value(slot_record) | python | def _inherit_outputs(self,
pipeline_name,
already_defined,
resolve_outputs=False):
"""Inherits outputs from a calling Pipeline.
Args:
pipeline_name: The Pipeline class name (used for debugging).
already_defined: Maps output name to stringified db.Key (of _SlotRecords)
of any exiting output slots to be inherited by this future.
resolve_outputs: When True, this method will dereference all output slots
before returning back to the caller, making those output slots' values
available.
Raises:
UnexpectedPipelineError when resolve_outputs is True and any of the output
slots could not be retrived from the Datastore.
"""
for name, slot_key in already_defined.iteritems():
if not isinstance(slot_key, db.Key):
slot_key = db.Key(slot_key)
slot = self._output_dict.get(name)
if slot is None:
if self._strict:
raise UnexpectedPipelineError(
'Inherited output named "%s" must be filled but '
'not declared for pipeline class "%s"' % (name, pipeline_name))
else:
self._output_dict[name] = Slot(name=name, slot_key=slot_key)
else:
slot.key = slot_key
slot._exists = True
if resolve_outputs:
slot_key_dict = dict((s.key, s) for s in self._output_dict.itervalues())
all_slots = db.get(slot_key_dict.keys())
for slot, slot_record in zip(slot_key_dict.itervalues(), all_slots):
if slot_record is None:
raise UnexpectedPipelineError(
'Inherited output named "%s" for pipeline class "%s" is '
'missing its Slot in the datastore: "%s"' %
(slot.name, pipeline_name, slot.key))
slot = slot_key_dict[slot_record.key()]
slot._set_value(slot_record) | Inherits outputs from a calling Pipeline.
Args:
pipeline_name: The Pipeline class name (used for debugging).
already_defined: Maps output name to stringified db.Key (of _SlotRecords)
of any exiting output slots to be inherited by this future.
resolve_outputs: When True, this method will dereference all output slots
before returning back to the caller, making those output slots' values
available.
Raises:
UnexpectedPipelineError when resolve_outputs is True and any of the output
slots could not be retrived from the Datastore. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L314-L358 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline.from_id | def from_id(cls, pipeline_id, resolve_outputs=True, _pipeline_record=None):
"""Returns an instance corresponding to an existing Pipeline.
The returned object will have the same properties a Pipeline does while
it's running synchronously (e.g., like what it's first allocated), allowing
callers to inspect caller arguments, outputs, fill slots, complete the
pipeline, abort, retry, etc.
Args:
pipeline_id: The ID of this pipeline (a string).
resolve_outputs: When True, dereference the outputs of this Pipeline
so their values can be accessed by the caller.
_pipeline_record: Internal-only. The _PipelineRecord instance to use
to instantiate this instance instead of fetching it from
the datastore.
Returns:
Pipeline sub-class instances or None if it could not be found.
"""
pipeline_record = _pipeline_record
# Support pipeline IDs and idempotence_keys that are not unicode.
if not isinstance(pipeline_id, unicode):
try:
pipeline_id = pipeline_id.encode('utf-8')
except UnicodeDecodeError:
pipeline_id = hashlib.sha1(pipeline_id).hexdigest()
pipeline_key = db.Key.from_path(_PipelineRecord.kind(), pipeline_id)
if pipeline_record is None:
pipeline_record = db.get(pipeline_key)
if pipeline_record is None:
return None
try:
pipeline_func_class = mr_util.for_name(pipeline_record.class_path)
except ImportError, e:
logging.warning('Tried to find Pipeline %s#%s, but class could '
'not be found. Using default Pipeline class instead.',
pipeline_record.class_path, pipeline_id)
pipeline_func_class = cls
params = pipeline_record.params
arg_list, kwarg_dict = _dereference_args(
pipeline_record.class_path, params['args'], params['kwargs'])
outputs = PipelineFuture(pipeline_func_class.output_names)
outputs._inherit_outputs(
pipeline_record.class_path,
params['output_slots'],
resolve_outputs=resolve_outputs)
stage = pipeline_func_class(*arg_list, **kwarg_dict)
stage.backoff_seconds = params['backoff_seconds']
stage.backoff_factor = params['backoff_factor']
stage.max_attempts = params['max_attempts']
stage.task_retry = params['task_retry']
stage.target = params.get('target') # May not be defined for old Pipelines
stage._current_attempt = pipeline_record.current_attempt
stage._set_values_internal(
_PipelineContext('', params['queue_name'], params['base_path']),
pipeline_key,
_PipelineRecord.root_pipeline.get_value_for_datastore(pipeline_record),
outputs,
pipeline_record.status)
return stage | python | def from_id(cls, pipeline_id, resolve_outputs=True, _pipeline_record=None):
"""Returns an instance corresponding to an existing Pipeline.
The returned object will have the same properties a Pipeline does while
it's running synchronously (e.g., like what it's first allocated), allowing
callers to inspect caller arguments, outputs, fill slots, complete the
pipeline, abort, retry, etc.
Args:
pipeline_id: The ID of this pipeline (a string).
resolve_outputs: When True, dereference the outputs of this Pipeline
so their values can be accessed by the caller.
_pipeline_record: Internal-only. The _PipelineRecord instance to use
to instantiate this instance instead of fetching it from
the datastore.
Returns:
Pipeline sub-class instances or None if it could not be found.
"""
pipeline_record = _pipeline_record
# Support pipeline IDs and idempotence_keys that are not unicode.
if not isinstance(pipeline_id, unicode):
try:
pipeline_id = pipeline_id.encode('utf-8')
except UnicodeDecodeError:
pipeline_id = hashlib.sha1(pipeline_id).hexdigest()
pipeline_key = db.Key.from_path(_PipelineRecord.kind(), pipeline_id)
if pipeline_record is None:
pipeline_record = db.get(pipeline_key)
if pipeline_record is None:
return None
try:
pipeline_func_class = mr_util.for_name(pipeline_record.class_path)
except ImportError, e:
logging.warning('Tried to find Pipeline %s#%s, but class could '
'not be found. Using default Pipeline class instead.',
pipeline_record.class_path, pipeline_id)
pipeline_func_class = cls
params = pipeline_record.params
arg_list, kwarg_dict = _dereference_args(
pipeline_record.class_path, params['args'], params['kwargs'])
outputs = PipelineFuture(pipeline_func_class.output_names)
outputs._inherit_outputs(
pipeline_record.class_path,
params['output_slots'],
resolve_outputs=resolve_outputs)
stage = pipeline_func_class(*arg_list, **kwarg_dict)
stage.backoff_seconds = params['backoff_seconds']
stage.backoff_factor = params['backoff_factor']
stage.max_attempts = params['max_attempts']
stage.task_retry = params['task_retry']
stage.target = params.get('target') # May not be defined for old Pipelines
stage._current_attempt = pipeline_record.current_attempt
stage._set_values_internal(
_PipelineContext('', params['queue_name'], params['base_path']),
pipeline_key,
_PipelineRecord.root_pipeline.get_value_for_datastore(pipeline_record),
outputs,
pipeline_record.status)
return stage | Returns an instance corresponding to an existing Pipeline.
The returned object will have the same properties a Pipeline does while
it's running synchronously (e.g., like what it's first allocated), allowing
callers to inspect caller arguments, outputs, fill slots, complete the
pipeline, abort, retry, etc.
Args:
pipeline_id: The ID of this pipeline (a string).
resolve_outputs: When True, dereference the outputs of this Pipeline
so their values can be accessed by the caller.
_pipeline_record: Internal-only. The _PipelineRecord instance to use
to instantiate this instance instead of fetching it from
the datastore.
Returns:
Pipeline sub-class instances or None if it could not be found. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L544-L609 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline.start | def start(self,
idempotence_key='',
queue_name='default',
base_path='/_ah/pipeline',
return_task=False,
countdown=None,
eta=None):
"""Starts a new instance of this pipeline.
Args:
idempotence_key: The ID to use for this Pipeline and throughout its
asynchronous workflow to ensure the operations are idempotent. If
empty a starting key will be automatically assigned.
queue_name: What queue this Pipeline's workflow should execute on.
base_path: The relative URL path to where the Pipeline API is
mounted for access by the taskqueue API or external requests.
return_task: When True, a task to start this pipeline will be returned
instead of submitted, allowing the caller to start off this pipeline
as part of a separate transaction (potentially leaving this newly
allocated pipeline's datastore entities in place if that separate
transaction fails for any reason).
countdown: Time in seconds into the future that this Task should execute.
Defaults to zero.
eta: A datetime.datetime specifying the absolute time at which the task
should be executed. Must not be specified if 'countdown' is specified.
This may be timezone-aware or timezone-naive. If None, defaults to now.
For pull tasks, no worker will be able to lease this task before the
time indicated by eta.
Returns:
A taskqueue.Task instance if return_task was True. This task will *not*
have a name, thus to ensure reliable execution of your pipeline you
should add() this task as part of a separate Datastore transaction.
Raises:
PipelineExistsError if the pipeline with the given idempotence key exists.
PipelineSetupError if the pipeline could not start for any other reason.
"""
if not idempotence_key:
idempotence_key = uuid.uuid4().hex
elif not isinstance(idempotence_key, unicode):
try:
idempotence_key.encode('utf-8')
except UnicodeDecodeError:
idempotence_key = hashlib.sha1(idempotence_key).hexdigest()
pipeline_key = db.Key.from_path(_PipelineRecord.kind(), idempotence_key)
context = _PipelineContext('', queue_name, base_path)
future = PipelineFuture(self.output_names, force_strict=True)
try:
self._set_values_internal(
context, pipeline_key, pipeline_key, future, _PipelineRecord.WAITING)
return context.start(
self, return_task=return_task, countdown=countdown, eta=eta)
except Error:
# Pass through exceptions that originate in this module.
raise
except Exception, e:
# Re-type any exceptions that were raised in dependent methods.
raise PipelineSetupError('Error starting %s#%s: %s' % (
self, idempotence_key, str(e))) | python | def start(self,
idempotence_key='',
queue_name='default',
base_path='/_ah/pipeline',
return_task=False,
countdown=None,
eta=None):
"""Starts a new instance of this pipeline.
Args:
idempotence_key: The ID to use for this Pipeline and throughout its
asynchronous workflow to ensure the operations are idempotent. If
empty a starting key will be automatically assigned.
queue_name: What queue this Pipeline's workflow should execute on.
base_path: The relative URL path to where the Pipeline API is
mounted for access by the taskqueue API or external requests.
return_task: When True, a task to start this pipeline will be returned
instead of submitted, allowing the caller to start off this pipeline
as part of a separate transaction (potentially leaving this newly
allocated pipeline's datastore entities in place if that separate
transaction fails for any reason).
countdown: Time in seconds into the future that this Task should execute.
Defaults to zero.
eta: A datetime.datetime specifying the absolute time at which the task
should be executed. Must not be specified if 'countdown' is specified.
This may be timezone-aware or timezone-naive. If None, defaults to now.
For pull tasks, no worker will be able to lease this task before the
time indicated by eta.
Returns:
A taskqueue.Task instance if return_task was True. This task will *not*
have a name, thus to ensure reliable execution of your pipeline you
should add() this task as part of a separate Datastore transaction.
Raises:
PipelineExistsError if the pipeline with the given idempotence key exists.
PipelineSetupError if the pipeline could not start for any other reason.
"""
if not idempotence_key:
idempotence_key = uuid.uuid4().hex
elif not isinstance(idempotence_key, unicode):
try:
idempotence_key.encode('utf-8')
except UnicodeDecodeError:
idempotence_key = hashlib.sha1(idempotence_key).hexdigest()
pipeline_key = db.Key.from_path(_PipelineRecord.kind(), idempotence_key)
context = _PipelineContext('', queue_name, base_path)
future = PipelineFuture(self.output_names, force_strict=True)
try:
self._set_values_internal(
context, pipeline_key, pipeline_key, future, _PipelineRecord.WAITING)
return context.start(
self, return_task=return_task, countdown=countdown, eta=eta)
except Error:
# Pass through exceptions that originate in this module.
raise
except Exception, e:
# Re-type any exceptions that were raised in dependent methods.
raise PipelineSetupError('Error starting %s#%s: %s' % (
self, idempotence_key, str(e))) | Starts a new instance of this pipeline.
Args:
idempotence_key: The ID to use for this Pipeline and throughout its
asynchronous workflow to ensure the operations are idempotent. If
empty a starting key will be automatically assigned.
queue_name: What queue this Pipeline's workflow should execute on.
base_path: The relative URL path to where the Pipeline API is
mounted for access by the taskqueue API or external requests.
return_task: When True, a task to start this pipeline will be returned
instead of submitted, allowing the caller to start off this pipeline
as part of a separate transaction (potentially leaving this newly
allocated pipeline's datastore entities in place if that separate
transaction fails for any reason).
countdown: Time in seconds into the future that this Task should execute.
Defaults to zero.
eta: A datetime.datetime specifying the absolute time at which the task
should be executed. Must not be specified if 'countdown' is specified.
This may be timezone-aware or timezone-naive. If None, defaults to now.
For pull tasks, no worker will be able to lease this task before the
time indicated by eta.
Returns:
A taskqueue.Task instance if return_task was True. This task will *not*
have a name, thus to ensure reliable execution of your pipeline you
should add() this task as part of a separate Datastore transaction.
Raises:
PipelineExistsError if the pipeline with the given idempotence key exists.
PipelineSetupError if the pipeline could not start for any other reason. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L613-L673 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline.retry | def retry(self, retry_message=''):
"""Forces a currently running asynchronous pipeline to retry.
Note this may not be called by synchronous or generator pipelines. Those
must instead raise the 'Retry' exception during execution.
Args:
retry_message: Optional message explaining why the retry happened.
Returns:
True if the Pipeline should be retried, False if it cannot be cancelled
mid-flight for some reason.
"""
if not self.async:
raise UnexpectedPipelineError(
'May only call retry() method for asynchronous pipelines.')
if self.try_cancel():
self._context.transition_retry(self._pipeline_key, retry_message)
return True
else:
return False | python | def retry(self, retry_message=''):
"""Forces a currently running asynchronous pipeline to retry.
Note this may not be called by synchronous or generator pipelines. Those
must instead raise the 'Retry' exception during execution.
Args:
retry_message: Optional message explaining why the retry happened.
Returns:
True if the Pipeline should be retried, False if it cannot be cancelled
mid-flight for some reason.
"""
if not self.async:
raise UnexpectedPipelineError(
'May only call retry() method for asynchronous pipelines.')
if self.try_cancel():
self._context.transition_retry(self._pipeline_key, retry_message)
return True
else:
return False | Forces a currently running asynchronous pipeline to retry.
Note this may not be called by synchronous or generator pipelines. Those
must instead raise the 'Retry' exception during execution.
Args:
retry_message: Optional message explaining why the retry happened.
Returns:
True if the Pipeline should be retried, False if it cannot be cancelled
mid-flight for some reason. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L693-L713 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline.abort | def abort(self, abort_message=''):
"""Mark the entire pipeline up to the root as aborted.
Note this should only be called from *outside* the context of a running
pipeline. Synchronous and generator pipelines should raise the 'Abort'
exception to cause this behavior during execution.
Args:
abort_message: Optional message explaining why the abort happened.
Returns:
True if the abort signal was sent successfully; False if the pipeline
could not be aborted for any reason.
"""
# TODO: Use thread-local variable to enforce that this is not called
# while a pipeline is executing in the current thread.
if (self.async and self._root_pipeline_key == self._pipeline_key and
not self.try_cancel()):
# Handle the special case where the root pipeline is async and thus
# cannot be aborted outright.
return False
else:
return self._context.begin_abort(
self._root_pipeline_key, abort_message=abort_message) | python | def abort(self, abort_message=''):
"""Mark the entire pipeline up to the root as aborted.
Note this should only be called from *outside* the context of a running
pipeline. Synchronous and generator pipelines should raise the 'Abort'
exception to cause this behavior during execution.
Args:
abort_message: Optional message explaining why the abort happened.
Returns:
True if the abort signal was sent successfully; False if the pipeline
could not be aborted for any reason.
"""
# TODO: Use thread-local variable to enforce that this is not called
# while a pipeline is executing in the current thread.
if (self.async and self._root_pipeline_key == self._pipeline_key and
not self.try_cancel()):
# Handle the special case where the root pipeline is async and thus
# cannot be aborted outright.
return False
else:
return self._context.begin_abort(
self._root_pipeline_key, abort_message=abort_message) | Mark the entire pipeline up to the root as aborted.
Note this should only be called from *outside* the context of a running
pipeline. Synchronous and generator pipelines should raise the 'Abort'
exception to cause this behavior during execution.
Args:
abort_message: Optional message explaining why the abort happened.
Returns:
True if the abort signal was sent successfully; False if the pipeline
could not be aborted for any reason. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L715-L738 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline.fill | def fill(self, name_or_slot, value):
"""Fills an output slot required by this Pipeline.
Args:
name_or_slot: The name of the slot (a string) or Slot record to fill.
value: The serializable value to assign to this slot.
Raises:
UnexpectedPipelineError if the Slot no longer exists. SlotNotDeclaredError
if trying to output to a slot that was not declared ahead of time.
"""
if isinstance(name_or_slot, basestring):
slot = getattr(self.outputs, name_or_slot)
elif isinstance(name_or_slot, Slot):
slot = name_or_slot
else:
raise UnexpectedPipelineError(
'Could not fill invalid output name: %r' % name_or_slot)
if not slot._exists:
raise SlotNotDeclaredError(
'Cannot fill output with name "%s" that was just '
'declared within the Pipeline context.' % slot.name)
self._context.fill_slot(self._pipeline_key, slot, value) | python | def fill(self, name_or_slot, value):
"""Fills an output slot required by this Pipeline.
Args:
name_or_slot: The name of the slot (a string) or Slot record to fill.
value: The serializable value to assign to this slot.
Raises:
UnexpectedPipelineError if the Slot no longer exists. SlotNotDeclaredError
if trying to output to a slot that was not declared ahead of time.
"""
if isinstance(name_or_slot, basestring):
slot = getattr(self.outputs, name_or_slot)
elif isinstance(name_or_slot, Slot):
slot = name_or_slot
else:
raise UnexpectedPipelineError(
'Could not fill invalid output name: %r' % name_or_slot)
if not slot._exists:
raise SlotNotDeclaredError(
'Cannot fill output with name "%s" that was just '
'declared within the Pipeline context.' % slot.name)
self._context.fill_slot(self._pipeline_key, slot, value) | Fills an output slot required by this Pipeline.
Args:
name_or_slot: The name of the slot (a string) or Slot record to fill.
value: The serializable value to assign to this slot.
Raises:
UnexpectedPipelineError if the Slot no longer exists. SlotNotDeclaredError
if trying to output to a slot that was not declared ahead of time. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L741-L765 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline.set_status | def set_status(self, message=None, console_url=None, status_links=None):
"""Sets the current status of this pipeline.
This method is purposefully non-transactional. Updates are written to the
datastore immediately and overwrite all existing statuses.
Args:
message: (optional) Overall status message.
console_url: (optional) Relative URL to use for the "console" of this
pipeline that displays current progress. When None, no console will
be displayed.
status_links: (optional) Dictionary of readable link names to relative
URLs that should be associated with this pipeline as it runs. These links
provide convenient access to other dashboards, consoles, etc associated
with the pipeline.
Raises:
PipelineRuntimeError if the status could not be set for any reason.
"""
if _TEST_MODE:
logging.info(
'New status for %s#%s: message=%r, console_url=%r, status_links=%r',
self, self.pipeline_id, message, console_url, status_links)
return
status_key = db.Key.from_path(_StatusRecord.kind(), self.pipeline_id)
root_pipeline_key = db.Key.from_path(
_PipelineRecord.kind(), self.root_pipeline_id)
status_record = _StatusRecord(
key=status_key, root_pipeline=root_pipeline_key)
try:
if message:
status_record.message = message
if console_url:
status_record.console_url = console_url
if status_links:
# Alphabeticalize the list.
status_record.link_names = sorted(
db.Text(s) for s in status_links.iterkeys())
status_record.link_urls = [
db.Text(status_links[name]) for name in status_record.link_names]
status_record.status_time = datetime.datetime.utcnow()
status_record.put()
except Exception, e:
raise PipelineRuntimeError('Could not set status for %s#%s: %s' %
(self, self.pipeline_id, str(e))) | python | def set_status(self, message=None, console_url=None, status_links=None):
"""Sets the current status of this pipeline.
This method is purposefully non-transactional. Updates are written to the
datastore immediately and overwrite all existing statuses.
Args:
message: (optional) Overall status message.
console_url: (optional) Relative URL to use for the "console" of this
pipeline that displays current progress. When None, no console will
be displayed.
status_links: (optional) Dictionary of readable link names to relative
URLs that should be associated with this pipeline as it runs. These links
provide convenient access to other dashboards, consoles, etc associated
with the pipeline.
Raises:
PipelineRuntimeError if the status could not be set for any reason.
"""
if _TEST_MODE:
logging.info(
'New status for %s#%s: message=%r, console_url=%r, status_links=%r',
self, self.pipeline_id, message, console_url, status_links)
return
status_key = db.Key.from_path(_StatusRecord.kind(), self.pipeline_id)
root_pipeline_key = db.Key.from_path(
_PipelineRecord.kind(), self.root_pipeline_id)
status_record = _StatusRecord(
key=status_key, root_pipeline=root_pipeline_key)
try:
if message:
status_record.message = message
if console_url:
status_record.console_url = console_url
if status_links:
# Alphabeticalize the list.
status_record.link_names = sorted(
db.Text(s) for s in status_links.iterkeys())
status_record.link_urls = [
db.Text(status_links[name]) for name in status_record.link_names]
status_record.status_time = datetime.datetime.utcnow()
status_record.put()
except Exception, e:
raise PipelineRuntimeError('Could not set status for %s#%s: %s' %
(self, self.pipeline_id, str(e))) | Sets the current status of this pipeline.
This method is purposefully non-transactional. Updates are written to the
datastore immediately and overwrite all existing statuses.
Args:
message: (optional) Overall status message.
console_url: (optional) Relative URL to use for the "console" of this
pipeline that displays current progress. When None, no console will
be displayed.
status_links: (optional) Dictionary of readable link names to relative
URLs that should be associated with this pipeline as it runs. These links
provide convenient access to other dashboards, consoles, etc associated
with the pipeline.
Raises:
PipelineRuntimeError if the status could not be set for any reason. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L767-L815 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline.complete | def complete(self, default_output=None):
"""Marks this asynchronous Pipeline as complete.
Args:
default_output: What value the 'default' output slot should be assigned.
Raises:
UnexpectedPipelineError if the slot no longer exists or this method was
called for a pipeline that is not async.
"""
# TODO: Enforce that all outputs expected by this async pipeline were
# filled before this complete() function was called. May required all
# async functions to declare their outputs upfront.
if not self.async:
raise UnexpectedPipelineError(
'May only call complete() method for asynchronous pipelines.')
self._context.fill_slot(
self._pipeline_key, self.outputs.default, default_output) | python | def complete(self, default_output=None):
"""Marks this asynchronous Pipeline as complete.
Args:
default_output: What value the 'default' output slot should be assigned.
Raises:
UnexpectedPipelineError if the slot no longer exists or this method was
called for a pipeline that is not async.
"""
# TODO: Enforce that all outputs expected by this async pipeline were
# filled before this complete() function was called. May required all
# async functions to declare their outputs upfront.
if not self.async:
raise UnexpectedPipelineError(
'May only call complete() method for asynchronous pipelines.')
self._context.fill_slot(
self._pipeline_key, self.outputs.default, default_output) | Marks this asynchronous Pipeline as complete.
Args:
default_output: What value the 'default' output slot should be assigned.
Raises:
UnexpectedPipelineError if the slot no longer exists or this method was
called for a pipeline that is not async. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L817-L834 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline.get_callback_url | def get_callback_url(self, **kwargs):
"""Returns a relative URL for invoking this Pipeline's callback method.
Args:
kwargs: Dictionary mapping keyword argument names to single values that
should be passed to the callback when it is invoked.
Raises:
UnexpectedPipelineError if this is invoked on pipeline that is not async.
"""
# TODO: Support positional parameters.
if not self.async:
raise UnexpectedPipelineError(
'May only call get_callback_url() method for asynchronous pipelines.')
kwargs['pipeline_id'] = self._pipeline_key.name()
params = urllib.urlencode(sorted(kwargs.items()))
return '%s/callback?%s' % (self.base_path, params) | python | def get_callback_url(self, **kwargs):
"""Returns a relative URL for invoking this Pipeline's callback method.
Args:
kwargs: Dictionary mapping keyword argument names to single values that
should be passed to the callback when it is invoked.
Raises:
UnexpectedPipelineError if this is invoked on pipeline that is not async.
"""
# TODO: Support positional parameters.
if not self.async:
raise UnexpectedPipelineError(
'May only call get_callback_url() method for asynchronous pipelines.')
kwargs['pipeline_id'] = self._pipeline_key.name()
params = urllib.urlencode(sorted(kwargs.items()))
return '%s/callback?%s' % (self.base_path, params) | Returns a relative URL for invoking this Pipeline's callback method.
Args:
kwargs: Dictionary mapping keyword argument names to single values that
should be passed to the callback when it is invoked.
Raises:
UnexpectedPipelineError if this is invoked on pipeline that is not async. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L836-L852 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline.get_callback_task | def get_callback_task(self, *args, **kwargs):
"""Returns a task for calling back this Pipeline.
Args:
params: Keyword argument containing a dictionary of key/value pairs
that will be passed to the callback when it is executed.
args, kwargs: Passed to the taskqueue.Task constructor. Use these
arguments to set the task name (for idempotence), etc.
Returns:
A taskqueue.Task instance that must be enqueued by the caller.
"""
if not self.async:
raise UnexpectedPipelineError(
'May only call get_callback_task() method for asynchronous pipelines.')
params = kwargs.get('params', {})
kwargs['params'] = params
params['pipeline_id'] = self._pipeline_key.name()
kwargs['url'] = self.base_path + '/callback'
kwargs['method'] = 'POST'
return taskqueue.Task(*args, **kwargs) | python | def get_callback_task(self, *args, **kwargs):
"""Returns a task for calling back this Pipeline.
Args:
params: Keyword argument containing a dictionary of key/value pairs
that will be passed to the callback when it is executed.
args, kwargs: Passed to the taskqueue.Task constructor. Use these
arguments to set the task name (for idempotence), etc.
Returns:
A taskqueue.Task instance that must be enqueued by the caller.
"""
if not self.async:
raise UnexpectedPipelineError(
'May only call get_callback_task() method for asynchronous pipelines.')
params = kwargs.get('params', {})
kwargs['params'] = params
params['pipeline_id'] = self._pipeline_key.name()
kwargs['url'] = self.base_path + '/callback'
kwargs['method'] = 'POST'
return taskqueue.Task(*args, **kwargs) | Returns a task for calling back this Pipeline.
Args:
params: Keyword argument containing a dictionary of key/value pairs
that will be passed to the callback when it is executed.
args, kwargs: Passed to the taskqueue.Task constructor. Use these
arguments to set the task name (for idempotence), etc.
Returns:
A taskqueue.Task instance that must be enqueued by the caller. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L854-L875 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline.send_result_email | def send_result_email(self, sender=None):
"""Sends an email to admins indicating this Pipeline has completed.
For developer convenience. Automatically called from finalized for root
Pipelines that do not override the default action.
Args:
sender: (optional) Override the sender's email address.
"""
status = 'successful'
if self.was_aborted:
status = 'aborted'
app_id = os.environ['APPLICATION_ID']
shard_index = app_id.find('~')
if shard_index != -1:
app_id = app_id[shard_index+1:]
param_dict = {
'status': status,
'app_id': app_id,
'class_path': self._class_path,
'pipeline_id': self.root_pipeline_id,
'base_path': '%s.appspot.com%s' % (app_id, self.base_path),
}
subject = (
'Pipeline %(status)s: App "%(app_id)s", %(class_path)s'
'#%(pipeline_id)s' % param_dict)
body = """View the pipeline results here:
http://%(base_path)s/status?root=%(pipeline_id)s
Thanks,
The Pipeline API
""" % param_dict
html = """<html><body>
<p>View the pipeline results here:</p>
<p><a href="http://%(base_path)s/status?root=%(pipeline_id)s"
>http://%(base_path)s/status?root=%(pipeline_id)s</a></p>
<p>
Thanks,
<br>
The Pipeline API
</p>
</body></html>
""" % param_dict
if sender is None:
sender = '%s@%s.appspotmail.com' % (app_id, app_id)
try:
self._send_mail(sender, subject, body, html=html)
except (mail.InvalidSenderError, mail.InvalidEmailError):
logging.warning('Could not send result email for '
'root pipeline ID "%s" from sender "%s"',
self.root_pipeline_id, sender) | python | def send_result_email(self, sender=None):
"""Sends an email to admins indicating this Pipeline has completed.
For developer convenience. Automatically called from finalized for root
Pipelines that do not override the default action.
Args:
sender: (optional) Override the sender's email address.
"""
status = 'successful'
if self.was_aborted:
status = 'aborted'
app_id = os.environ['APPLICATION_ID']
shard_index = app_id.find('~')
if shard_index != -1:
app_id = app_id[shard_index+1:]
param_dict = {
'status': status,
'app_id': app_id,
'class_path': self._class_path,
'pipeline_id': self.root_pipeline_id,
'base_path': '%s.appspot.com%s' % (app_id, self.base_path),
}
subject = (
'Pipeline %(status)s: App "%(app_id)s", %(class_path)s'
'#%(pipeline_id)s' % param_dict)
body = """View the pipeline results here:
http://%(base_path)s/status?root=%(pipeline_id)s
Thanks,
The Pipeline API
""" % param_dict
html = """<html><body>
<p>View the pipeline results here:</p>
<p><a href="http://%(base_path)s/status?root=%(pipeline_id)s"
>http://%(base_path)s/status?root=%(pipeline_id)s</a></p>
<p>
Thanks,
<br>
The Pipeline API
</p>
</body></html>
""" % param_dict
if sender is None:
sender = '%s@%s.appspotmail.com' % (app_id, app_id)
try:
self._send_mail(sender, subject, body, html=html)
except (mail.InvalidSenderError, mail.InvalidEmailError):
logging.warning('Could not send result email for '
'root pipeline ID "%s" from sender "%s"',
self.root_pipeline_id, sender) | Sends an email to admins indicating this Pipeline has completed.
For developer convenience. Automatically called from finalized for root
Pipelines that do not override the default action.
Args:
sender: (optional) Override the sender's email address. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L877-L935 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline.cleanup | def cleanup(self):
"""Clean up this Pipeline and all Datastore records used for coordination.
Only works when called on a root pipeline. Child pipelines will ignore
calls to this method.
After this method is called, Pipeline.from_id() and related status
methods will return inconsistent or missing results. This method is
fire-and-forget and asynchronous.
"""
if self._root_pipeline_key is None:
raise UnexpectedPipelineError(
'Could not cleanup Pipeline with unknown root pipeline ID.')
if not self.is_root:
return
task = taskqueue.Task(
params=dict(root_pipeline_key=self._root_pipeline_key),
url=self.base_path + '/cleanup',
headers={'X-Ae-Pipeline-Key': self._root_pipeline_key})
taskqueue.Queue(self.queue_name).add(task) | python | def cleanup(self):
"""Clean up this Pipeline and all Datastore records used for coordination.
Only works when called on a root pipeline. Child pipelines will ignore
calls to this method.
After this method is called, Pipeline.from_id() and related status
methods will return inconsistent or missing results. This method is
fire-and-forget and asynchronous.
"""
if self._root_pipeline_key is None:
raise UnexpectedPipelineError(
'Could not cleanup Pipeline with unknown root pipeline ID.')
if not self.is_root:
return
task = taskqueue.Task(
params=dict(root_pipeline_key=self._root_pipeline_key),
url=self.base_path + '/cleanup',
headers={'X-Ae-Pipeline-Key': self._root_pipeline_key})
taskqueue.Queue(self.queue_name).add(task) | Clean up this Pipeline and all Datastore records used for coordination.
Only works when called on a root pipeline. Child pipelines will ignore
calls to this method.
After this method is called, Pipeline.from_id() and related status
methods will return inconsistent or missing results. This method is
fire-and-forget and asynchronous. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L937-L956 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline.with_params | def with_params(self, **kwargs):
"""Modify various execution parameters of a Pipeline before it runs.
This method has no effect in test mode.
Args:
kwargs: Attributes to modify on this Pipeline instance before it has
been executed.
Returns:
This Pipeline instance, for easy chaining.
"""
if _TEST_MODE:
logging.info(
'Setting runtime parameters for %s#%s: %r',
self, self.pipeline_id, kwargs)
return self
if self.pipeline_id is not None:
raise UnexpectedPipelineError(
'May only call with_params() on a Pipeline that has not yet '
'been scheduled for execution.')
ALLOWED = ('backoff_seconds', 'backoff_factor', 'max_attempts', 'target')
for name, value in kwargs.iteritems():
if name not in ALLOWED:
raise TypeError('Unexpected keyword: %s=%r' % (name, value))
setattr(self, name, value)
return self | python | def with_params(self, **kwargs):
"""Modify various execution parameters of a Pipeline before it runs.
This method has no effect in test mode.
Args:
kwargs: Attributes to modify on this Pipeline instance before it has
been executed.
Returns:
This Pipeline instance, for easy chaining.
"""
if _TEST_MODE:
logging.info(
'Setting runtime parameters for %s#%s: %r',
self, self.pipeline_id, kwargs)
return self
if self.pipeline_id is not None:
raise UnexpectedPipelineError(
'May only call with_params() on a Pipeline that has not yet '
'been scheduled for execution.')
ALLOWED = ('backoff_seconds', 'backoff_factor', 'max_attempts', 'target')
for name, value in kwargs.iteritems():
if name not in ALLOWED:
raise TypeError('Unexpected keyword: %s=%r' % (name, value))
setattr(self, name, value)
return self | Modify various execution parameters of a Pipeline before it runs.
This method has no effect in test mode.
Args:
kwargs: Attributes to modify on this Pipeline instance before it has
been executed.
Returns:
This Pipeline instance, for easy chaining. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L958-L986 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline._set_class_path | def _set_class_path(cls, module_dict=sys.modules):
"""Sets the absolute path to this class as a string.
Used by the Pipeline API to reconstruct the Pipeline sub-class object
at execution time instead of passing around a serialized function.
Args:
module_dict: Used for testing.
"""
# Do not traverse the class hierarchy fetching the class path attribute.
found = cls.__dict__.get('_class_path')
if found is not None:
return
# Do not set the _class_path for the base-class, otherwise all children's
# lookups for _class_path will fall through and return 'Pipeline' above.
# This situation can happen if users call the generic Pipeline.from_id
# to get the result of a Pipeline without knowing its specific class.
if cls is Pipeline:
return
class_path = '%s.%s' % (cls.__module__, cls.__name__)
# When a WSGI handler is invoked as an entry point, any Pipeline class
# defined in the same file as the handler will get __module__ set to
# __main__. Thus we need to find out its real fully qualified path.
if cls.__module__ == '__main__':
for name, module in module_dict.items():
if name == '__main__':
continue
found = getattr(module, cls.__name__, None)
if found is cls:
class_path = '%s.%s' % (name, cls.__name__)
break
cls._class_path = class_path | python | def _set_class_path(cls, module_dict=sys.modules):
"""Sets the absolute path to this class as a string.
Used by the Pipeline API to reconstruct the Pipeline sub-class object
at execution time instead of passing around a serialized function.
Args:
module_dict: Used for testing.
"""
# Do not traverse the class hierarchy fetching the class path attribute.
found = cls.__dict__.get('_class_path')
if found is not None:
return
# Do not set the _class_path for the base-class, otherwise all children's
# lookups for _class_path will fall through and return 'Pipeline' above.
# This situation can happen if users call the generic Pipeline.from_id
# to get the result of a Pipeline without knowing its specific class.
if cls is Pipeline:
return
class_path = '%s.%s' % (cls.__module__, cls.__name__)
# When a WSGI handler is invoked as an entry point, any Pipeline class
# defined in the same file as the handler will get __module__ set to
# __main__. Thus we need to find out its real fully qualified path.
if cls.__module__ == '__main__':
for name, module in module_dict.items():
if name == '__main__':
continue
found = getattr(module, cls.__name__, None)
if found is cls:
class_path = '%s.%s' % (name, cls.__name__)
break
cls._class_path = class_path | Sets the absolute path to this class as a string.
Used by the Pipeline API to reconstruct the Pipeline sub-class object
at execution time instead of passing around a serialized function.
Args:
module_dict: Used for testing. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1035-L1068 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline._set_values_internal | def _set_values_internal(self,
context,
pipeline_key,
root_pipeline_key,
outputs,
result_status):
"""Sets the user-visible values provided as an API by this class.
Args:
context: The _PipelineContext used for this Pipeline.
pipeline_key: The db.Key of this pipeline.
root_pipeline_key: The db.Key of the root pipeline.
outputs: The PipelineFuture for this pipeline.
result_status: The result status of this pipeline.
"""
self._context = context
self._pipeline_key = pipeline_key
self._root_pipeline_key = root_pipeline_key
self._result_status = result_status
self.outputs = outputs | python | def _set_values_internal(self,
context,
pipeline_key,
root_pipeline_key,
outputs,
result_status):
"""Sets the user-visible values provided as an API by this class.
Args:
context: The _PipelineContext used for this Pipeline.
pipeline_key: The db.Key of this pipeline.
root_pipeline_key: The db.Key of the root pipeline.
outputs: The PipelineFuture for this pipeline.
result_status: The result status of this pipeline.
"""
self._context = context
self._pipeline_key = pipeline_key
self._root_pipeline_key = root_pipeline_key
self._result_status = result_status
self.outputs = outputs | Sets the user-visible values provided as an API by this class.
Args:
context: The _PipelineContext used for this Pipeline.
pipeline_key: The db.Key of this pipeline.
root_pipeline_key: The db.Key of the root pipeline.
outputs: The PipelineFuture for this pipeline.
result_status: The result status of this pipeline. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1070-L1089 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline._callback_internal | def _callback_internal(self, kwargs):
"""Used to execute callbacks on asynchronous pipelines."""
logging.debug('Callback %s(*%s, **%s)#%s with params: %r',
self._class_path, _short_repr(self.args),
_short_repr(self.kwargs), self._pipeline_key.name(), kwargs)
return self.callback(**kwargs) | python | def _callback_internal(self, kwargs):
"""Used to execute callbacks on asynchronous pipelines."""
logging.debug('Callback %s(*%s, **%s)#%s with params: %r',
self._class_path, _short_repr(self.args),
_short_repr(self.kwargs), self._pipeline_key.name(), kwargs)
return self.callback(**kwargs) | Used to execute callbacks on asynchronous pipelines. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1091-L1096 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline._run_internal | def _run_internal(self,
context,
pipeline_key,
root_pipeline_key,
caller_output):
"""Used by the Pipeline evaluator to execute this Pipeline."""
self._set_values_internal(
context, pipeline_key, root_pipeline_key, caller_output,
_PipelineRecord.RUN)
logging.debug('Running %s(*%s, **%s)#%s',
self._class_path, _short_repr(self.args),
_short_repr(self.kwargs), self._pipeline_key.name())
return self.run(*self.args, **self.kwargs) | python | def _run_internal(self,
context,
pipeline_key,
root_pipeline_key,
caller_output):
"""Used by the Pipeline evaluator to execute this Pipeline."""
self._set_values_internal(
context, pipeline_key, root_pipeline_key, caller_output,
_PipelineRecord.RUN)
logging.debug('Running %s(*%s, **%s)#%s',
self._class_path, _short_repr(self.args),
_short_repr(self.kwargs), self._pipeline_key.name())
return self.run(*self.args, **self.kwargs) | Used by the Pipeline evaluator to execute this Pipeline. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1098-L1110 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | Pipeline._finalized_internal | def _finalized_internal(self,
context,
pipeline_key,
root_pipeline_key,
caller_output,
aborted):
"""Used by the Pipeline evaluator to finalize this Pipeline."""
result_status = _PipelineRecord.RUN
if aborted:
result_status = _PipelineRecord.ABORTED
self._set_values_internal(
context, pipeline_key, root_pipeline_key, caller_output, result_status)
logging.debug('Finalizing %s(*%r, **%r)#%s',
self._class_path, _short_repr(self.args),
_short_repr(self.kwargs), self._pipeline_key.name())
try:
self.finalized()
except NotImplementedError:
pass | python | def _finalized_internal(self,
context,
pipeline_key,
root_pipeline_key,
caller_output,
aborted):
"""Used by the Pipeline evaluator to finalize this Pipeline."""
result_status = _PipelineRecord.RUN
if aborted:
result_status = _PipelineRecord.ABORTED
self._set_values_internal(
context, pipeline_key, root_pipeline_key, caller_output, result_status)
logging.debug('Finalizing %s(*%r, **%r)#%s',
self._class_path, _short_repr(self.args),
_short_repr(self.kwargs), self._pipeline_key.name())
try:
self.finalized()
except NotImplementedError:
pass | Used by the Pipeline evaluator to finalize this Pipeline. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1112-L1131 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | InOrder._add_future | def _add_future(cls, future):
"""Adds a future to the list of in-order futures thus far.
Args:
future: The future to add to the list.
"""
if cls._local._activated:
cls._local._in_order_futures.add(future) | python | def _add_future(cls, future):
"""Adds a future to the list of in-order futures thus far.
Args:
future: The future to add to the list.
"""
if cls._local._activated:
cls._local._in_order_futures.add(future) | Adds a future to the list of in-order futures thus far.
Args:
future: The future to add to the list. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1190-L1197 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | InOrder._thread_init | def _thread_init(cls):
"""Ensure thread local is initialized."""
if not hasattr(cls._local, '_in_order_futures'):
cls._local._in_order_futures = set()
cls._local._activated = False | python | def _thread_init(cls):
"""Ensure thread local is initialized."""
if not hasattr(cls._local, '_in_order_futures'):
cls._local._in_order_futures = set()
cls._local._activated = False | Ensure thread local is initialized. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1224-L1228 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _PipelineContext.from_environ | def from_environ(cls, environ=os.environ):
"""Constructs a _PipelineContext from the task queue environment."""
base_path, unused = (environ['PATH_INFO'].rsplit('/', 1) + [''])[:2]
return cls(
environ['HTTP_X_APPENGINE_TASKNAME'],
environ['HTTP_X_APPENGINE_QUEUENAME'],
base_path) | python | def from_environ(cls, environ=os.environ):
"""Constructs a _PipelineContext from the task queue environment."""
base_path, unused = (environ['PATH_INFO'].rsplit('/', 1) + [''])[:2]
return cls(
environ['HTTP_X_APPENGINE_TASKNAME'],
environ['HTTP_X_APPENGINE_QUEUENAME'],
base_path) | Constructs a _PipelineContext from the task queue environment. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1452-L1458 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _PipelineContext.fill_slot | def fill_slot(self, filler_pipeline_key, slot, value):
"""Fills a slot, enqueueing a task to trigger pending barriers.
Args:
filler_pipeline_key: db.Key or stringified key of the _PipelineRecord
that filled this slot.
slot: The Slot instance to fill.
value: The serializable value to assign.
Raises:
UnexpectedPipelineError if the _SlotRecord for the 'slot' could not
be found in the Datastore.
"""
if not isinstance(filler_pipeline_key, db.Key):
filler_pipeline_key = db.Key(filler_pipeline_key)
if _TEST_MODE:
slot._set_value_test(filler_pipeline_key, value)
else:
encoded_value = json.dumps(value,
sort_keys=True,
cls=mr_util.JsonEncoder)
value_text = None
value_blob = None
if len(encoded_value) <= _MAX_JSON_SIZE:
value_text = db.Text(encoded_value)
else:
# The encoded value is too big. Save it as a blob.
value_blob = _write_json_blob(encoded_value, filler_pipeline_key.name())
def txn():
slot_record = db.get(slot.key)
if slot_record is None:
raise UnexpectedPipelineError(
'Tried to fill missing slot "%s" '
'by pipeline ID "%s" with value: %r'
% (slot.key, filler_pipeline_key.name(), value))
# NOTE: Always take the override value here. If down-stream pipelines
# need a consitent view of all up-stream outputs (meaning, all of the
# outputs came from the same retry attempt of the upstream pipeline),
# the down-stream pipeline must also wait for the 'default' output
# of these up-stream pipelines.
slot_record.filler = filler_pipeline_key
slot_record.value_text = value_text
slot_record.value_blob = value_blob
slot_record.status = _SlotRecord.FILLED
slot_record.fill_time = self._gettime()
slot_record.put()
task = taskqueue.Task(
url=self.barrier_handler_path,
params=dict(
slot_key=slot.key,
use_barrier_indexes=True),
headers={'X-Ae-Slot-Key': slot.key,
'X-Ae-Filler-Pipeline-Key': filler_pipeline_key})
task.add(queue_name=self.queue_name, transactional=True)
db.run_in_transaction_options(
db.create_transaction_options(propagation=db.ALLOWED), txn)
self.session_filled_output_names.add(slot.name) | python | def fill_slot(self, filler_pipeline_key, slot, value):
"""Fills a slot, enqueueing a task to trigger pending barriers.
Args:
filler_pipeline_key: db.Key or stringified key of the _PipelineRecord
that filled this slot.
slot: The Slot instance to fill.
value: The serializable value to assign.
Raises:
UnexpectedPipelineError if the _SlotRecord for the 'slot' could not
be found in the Datastore.
"""
if not isinstance(filler_pipeline_key, db.Key):
filler_pipeline_key = db.Key(filler_pipeline_key)
if _TEST_MODE:
slot._set_value_test(filler_pipeline_key, value)
else:
encoded_value = json.dumps(value,
sort_keys=True,
cls=mr_util.JsonEncoder)
value_text = None
value_blob = None
if len(encoded_value) <= _MAX_JSON_SIZE:
value_text = db.Text(encoded_value)
else:
# The encoded value is too big. Save it as a blob.
value_blob = _write_json_blob(encoded_value, filler_pipeline_key.name())
def txn():
slot_record = db.get(slot.key)
if slot_record is None:
raise UnexpectedPipelineError(
'Tried to fill missing slot "%s" '
'by pipeline ID "%s" with value: %r'
% (slot.key, filler_pipeline_key.name(), value))
# NOTE: Always take the override value here. If down-stream pipelines
# need a consitent view of all up-stream outputs (meaning, all of the
# outputs came from the same retry attempt of the upstream pipeline),
# the down-stream pipeline must also wait for the 'default' output
# of these up-stream pipelines.
slot_record.filler = filler_pipeline_key
slot_record.value_text = value_text
slot_record.value_blob = value_blob
slot_record.status = _SlotRecord.FILLED
slot_record.fill_time = self._gettime()
slot_record.put()
task = taskqueue.Task(
url=self.barrier_handler_path,
params=dict(
slot_key=slot.key,
use_barrier_indexes=True),
headers={'X-Ae-Slot-Key': slot.key,
'X-Ae-Filler-Pipeline-Key': filler_pipeline_key})
task.add(queue_name=self.queue_name, transactional=True)
db.run_in_transaction_options(
db.create_transaction_options(propagation=db.ALLOWED), txn)
self.session_filled_output_names.add(slot.name) | Fills a slot, enqueueing a task to trigger pending barriers.
Args:
filler_pipeline_key: db.Key or stringified key of the _PipelineRecord
that filled this slot.
slot: The Slot instance to fill.
value: The serializable value to assign.
Raises:
UnexpectedPipelineError if the _SlotRecord for the 'slot' could not
be found in the Datastore. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1460-L1519 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _PipelineContext.notify_barriers | def notify_barriers(self,
slot_key,
cursor,
use_barrier_indexes,
max_to_notify=_MAX_BARRIERS_TO_NOTIFY):
"""Searches for barriers affected by a slot and triggers completed ones.
Args:
slot_key: db.Key or stringified key of the _SlotRecord that was filled.
cursor: Stringified Datastore cursor where the notification query
should pick up.
use_barrier_indexes: When True, use _BarrierIndex records to determine
which _Barriers to trigger by having this _SlotRecord filled. When
False, use the old method that queries for _BarrierRecords by
the blocking_slots parameter.
max_to_notify: Used for testing.
Raises:
PipelineStatusError: If any of the barriers are in a bad state.
"""
if not isinstance(slot_key, db.Key):
slot_key = db.Key(slot_key)
logging.debug('Notifying slot %r', slot_key)
if use_barrier_indexes:
# Please see models.py:_BarrierIndex to understand how _BarrierIndex
# entities relate to _BarrierRecord entities.
query = (
_BarrierIndex.all(cursor=cursor, keys_only=True)
.ancestor(slot_key))
barrier_index_list = query.fetch(max_to_notify)
barrier_key_list = [
_BarrierIndex.to_barrier_key(key) for key in barrier_index_list]
# If there are task and pipeline kickoff retries it's possible for a
# _BarrierIndex to exist for a _BarrierRecord that was not successfully
# written. It's safe to ignore this because the original task that wrote
# the _BarrierIndex and _BarrierRecord would not have made progress to
# kick off a real pipeline or child pipeline unless all of the writes for
# these dependent entities went through. We assume that the instigator
# retried from scratch and somehwere there exists a good _BarrierIndex and
# corresponding _BarrierRecord that tries to accomplish the same thing.
barriers = db.get(barrier_key_list)
results = []
for barrier_key, barrier in zip(barrier_key_list, barriers):
if barrier is None:
logging.debug('Ignoring that Barrier "%r" is missing, '
'relies on Slot "%r"', barrier_key, slot_key)
else:
results.append(barrier)
else:
# TODO(user): Delete this backwards compatible codepath and
# make use_barrier_indexes the assumed default in all cases.
query = (
_BarrierRecord.all(cursor=cursor)
.filter('blocking_slots =', slot_key))
results = query.fetch(max_to_notify)
# Fetch all blocking _SlotRecords for any potentially triggered barriers.
blocking_slot_keys = []
for barrier in results:
blocking_slot_keys.extend(barrier.blocking_slots)
blocking_slot_dict = {}
for slot_record in db.get(blocking_slot_keys):
if slot_record is None:
continue
blocking_slot_dict[slot_record.key()] = slot_record
task_list = []
updated_barriers = []
for barrier in results:
ready_slots = []
for blocking_slot_key in barrier.blocking_slots:
slot_record = blocking_slot_dict.get(blocking_slot_key)
if slot_record is None:
raise UnexpectedPipelineError(
'Barrier "%r" relies on Slot "%r" which is missing.' %
(barrier.key(), blocking_slot_key))
if slot_record.status == _SlotRecord.FILLED:
ready_slots.append(blocking_slot_key)
# When all of the blocking_slots have been filled, consider the barrier
# ready to trigger. We'll trigger it regardless of the current
# _BarrierRecord status, since there could be task queue failures at any
# point in this flow; this rolls forward the state and de-dupes using
# the task name tombstones.
pending_slots = set(barrier.blocking_slots) - set(ready_slots)
if not pending_slots:
if barrier.status != _BarrierRecord.FIRED:
barrier.status = _BarrierRecord.FIRED
barrier.trigger_time = self._gettime()
updated_barriers.append(barrier)
purpose = barrier.key().name()
if purpose == _BarrierRecord.START:
path = self.pipeline_handler_path
countdown = None
else:
path = self.finalized_handler_path
# NOTE: Wait one second before finalization to prevent
# contention on the _PipelineRecord entity.
countdown = 1
pipeline_key = _BarrierRecord.target.get_value_for_datastore(barrier)
pipeline_record = db.get(pipeline_key)
logging.debug('Firing barrier %r', barrier.key())
task_list.append(taskqueue.Task(
url=path,
countdown=countdown,
name='ae-barrier-fire-%s-%s' % (pipeline_key.name(), purpose),
params=dict(pipeline_key=pipeline_key, purpose=purpose),
headers={'X-Ae-Pipeline-Key': pipeline_key},
target=pipeline_record.params['target']))
else:
logging.debug('Not firing barrier %r, Waiting for slots: %r',
barrier.key(), pending_slots)
# Blindly overwrite _BarrierRecords that have an updated status. This is
# acceptable because by this point all finalization barriers for
# generator children should have already had their final outputs assigned.
if updated_barriers:
db.put(updated_barriers)
# Task continuation with sequence number to prevent fork-bombs.
if len(results) == max_to_notify:
the_match = re.match('(.*)-ae-barrier-notify-([0-9]+)', self.task_name)
if the_match:
prefix = the_match.group(1)
end = int(the_match.group(2)) + 1
else:
prefix = self.task_name
end = 0
task_list.append(taskqueue.Task(
name='%s-ae-barrier-notify-%d' % (prefix, end),
url=self.barrier_handler_path,
params=dict(
slot_key=slot_key,
cursor=query.cursor(),
use_barrier_indexes=use_barrier_indexes)))
if task_list:
try:
taskqueue.Queue(self.queue_name).add(task_list)
except (taskqueue.TombstonedTaskError, taskqueue.TaskAlreadyExistsError):
pass | python | def notify_barriers(self,
slot_key,
cursor,
use_barrier_indexes,
max_to_notify=_MAX_BARRIERS_TO_NOTIFY):
"""Searches for barriers affected by a slot and triggers completed ones.
Args:
slot_key: db.Key or stringified key of the _SlotRecord that was filled.
cursor: Stringified Datastore cursor where the notification query
should pick up.
use_barrier_indexes: When True, use _BarrierIndex records to determine
which _Barriers to trigger by having this _SlotRecord filled. When
False, use the old method that queries for _BarrierRecords by
the blocking_slots parameter.
max_to_notify: Used for testing.
Raises:
PipelineStatusError: If any of the barriers are in a bad state.
"""
if not isinstance(slot_key, db.Key):
slot_key = db.Key(slot_key)
logging.debug('Notifying slot %r', slot_key)
if use_barrier_indexes:
# Please see models.py:_BarrierIndex to understand how _BarrierIndex
# entities relate to _BarrierRecord entities.
query = (
_BarrierIndex.all(cursor=cursor, keys_only=True)
.ancestor(slot_key))
barrier_index_list = query.fetch(max_to_notify)
barrier_key_list = [
_BarrierIndex.to_barrier_key(key) for key in barrier_index_list]
# If there are task and pipeline kickoff retries it's possible for a
# _BarrierIndex to exist for a _BarrierRecord that was not successfully
# written. It's safe to ignore this because the original task that wrote
# the _BarrierIndex and _BarrierRecord would not have made progress to
# kick off a real pipeline or child pipeline unless all of the writes for
# these dependent entities went through. We assume that the instigator
# retried from scratch and somehwere there exists a good _BarrierIndex and
# corresponding _BarrierRecord that tries to accomplish the same thing.
barriers = db.get(barrier_key_list)
results = []
for barrier_key, barrier in zip(barrier_key_list, barriers):
if barrier is None:
logging.debug('Ignoring that Barrier "%r" is missing, '
'relies on Slot "%r"', barrier_key, slot_key)
else:
results.append(barrier)
else:
# TODO(user): Delete this backwards compatible codepath and
# make use_barrier_indexes the assumed default in all cases.
query = (
_BarrierRecord.all(cursor=cursor)
.filter('blocking_slots =', slot_key))
results = query.fetch(max_to_notify)
# Fetch all blocking _SlotRecords for any potentially triggered barriers.
blocking_slot_keys = []
for barrier in results:
blocking_slot_keys.extend(barrier.blocking_slots)
blocking_slot_dict = {}
for slot_record in db.get(blocking_slot_keys):
if slot_record is None:
continue
blocking_slot_dict[slot_record.key()] = slot_record
task_list = []
updated_barriers = []
for barrier in results:
ready_slots = []
for blocking_slot_key in barrier.blocking_slots:
slot_record = blocking_slot_dict.get(blocking_slot_key)
if slot_record is None:
raise UnexpectedPipelineError(
'Barrier "%r" relies on Slot "%r" which is missing.' %
(barrier.key(), blocking_slot_key))
if slot_record.status == _SlotRecord.FILLED:
ready_slots.append(blocking_slot_key)
# When all of the blocking_slots have been filled, consider the barrier
# ready to trigger. We'll trigger it regardless of the current
# _BarrierRecord status, since there could be task queue failures at any
# point in this flow; this rolls forward the state and de-dupes using
# the task name tombstones.
pending_slots = set(barrier.blocking_slots) - set(ready_slots)
if not pending_slots:
if barrier.status != _BarrierRecord.FIRED:
barrier.status = _BarrierRecord.FIRED
barrier.trigger_time = self._gettime()
updated_barriers.append(barrier)
purpose = barrier.key().name()
if purpose == _BarrierRecord.START:
path = self.pipeline_handler_path
countdown = None
else:
path = self.finalized_handler_path
# NOTE: Wait one second before finalization to prevent
# contention on the _PipelineRecord entity.
countdown = 1
pipeline_key = _BarrierRecord.target.get_value_for_datastore(barrier)
pipeline_record = db.get(pipeline_key)
logging.debug('Firing barrier %r', barrier.key())
task_list.append(taskqueue.Task(
url=path,
countdown=countdown,
name='ae-barrier-fire-%s-%s' % (pipeline_key.name(), purpose),
params=dict(pipeline_key=pipeline_key, purpose=purpose),
headers={'X-Ae-Pipeline-Key': pipeline_key},
target=pipeline_record.params['target']))
else:
logging.debug('Not firing barrier %r, Waiting for slots: %r',
barrier.key(), pending_slots)
# Blindly overwrite _BarrierRecords that have an updated status. This is
# acceptable because by this point all finalization barriers for
# generator children should have already had their final outputs assigned.
if updated_barriers:
db.put(updated_barriers)
# Task continuation with sequence number to prevent fork-bombs.
if len(results) == max_to_notify:
the_match = re.match('(.*)-ae-barrier-notify-([0-9]+)', self.task_name)
if the_match:
prefix = the_match.group(1)
end = int(the_match.group(2)) + 1
else:
prefix = self.task_name
end = 0
task_list.append(taskqueue.Task(
name='%s-ae-barrier-notify-%d' % (prefix, end),
url=self.barrier_handler_path,
params=dict(
slot_key=slot_key,
cursor=query.cursor(),
use_barrier_indexes=use_barrier_indexes)))
if task_list:
try:
taskqueue.Queue(self.queue_name).add(task_list)
except (taskqueue.TombstonedTaskError, taskqueue.TaskAlreadyExistsError):
pass | Searches for barriers affected by a slot and triggers completed ones.
Args:
slot_key: db.Key or stringified key of the _SlotRecord that was filled.
cursor: Stringified Datastore cursor where the notification query
should pick up.
use_barrier_indexes: When True, use _BarrierIndex records to determine
which _Barriers to trigger by having this _SlotRecord filled. When
False, use the old method that queries for _BarrierRecords by
the blocking_slots parameter.
max_to_notify: Used for testing.
Raises:
PipelineStatusError: If any of the barriers are in a bad state. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1521-L1665 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _PipelineContext.begin_abort | def begin_abort(self, root_pipeline_key, abort_message):
"""Kicks off the abort process for a root pipeline and all its children.
Args:
root_pipeline_key: db.Key of the root pipeline to abort.
abort_message: Message explaining why the abort happened, only saved
into the root pipeline.
Returns:
True if the abort signal was sent successfully; False otherwise.
"""
def txn():
pipeline_record = db.get(root_pipeline_key)
if pipeline_record is None:
logging.warning(
'Tried to abort root pipeline ID "%s" but it does not exist.',
root_pipeline_key.name())
raise db.Rollback()
if pipeline_record.status == _PipelineRecord.ABORTED:
logging.warning(
'Tried to abort root pipeline ID "%s"; already in state: %s',
root_pipeline_key.name(), pipeline_record.status)
raise db.Rollback()
if pipeline_record.abort_requested:
logging.warning(
'Tried to abort root pipeline ID "%s"; abort signal already sent.',
root_pipeline_key.name())
raise db.Rollback()
pipeline_record.abort_requested = True
pipeline_record.abort_message = abort_message
pipeline_record.put()
task = taskqueue.Task(
url=self.fanout_abort_handler_path,
params=dict(root_pipeline_key=root_pipeline_key))
task.add(queue_name=self.queue_name, transactional=True)
return True
return db.run_in_transaction(txn) | python | def begin_abort(self, root_pipeline_key, abort_message):
"""Kicks off the abort process for a root pipeline and all its children.
Args:
root_pipeline_key: db.Key of the root pipeline to abort.
abort_message: Message explaining why the abort happened, only saved
into the root pipeline.
Returns:
True if the abort signal was sent successfully; False otherwise.
"""
def txn():
pipeline_record = db.get(root_pipeline_key)
if pipeline_record is None:
logging.warning(
'Tried to abort root pipeline ID "%s" but it does not exist.',
root_pipeline_key.name())
raise db.Rollback()
if pipeline_record.status == _PipelineRecord.ABORTED:
logging.warning(
'Tried to abort root pipeline ID "%s"; already in state: %s',
root_pipeline_key.name(), pipeline_record.status)
raise db.Rollback()
if pipeline_record.abort_requested:
logging.warning(
'Tried to abort root pipeline ID "%s"; abort signal already sent.',
root_pipeline_key.name())
raise db.Rollback()
pipeline_record.abort_requested = True
pipeline_record.abort_message = abort_message
pipeline_record.put()
task = taskqueue.Task(
url=self.fanout_abort_handler_path,
params=dict(root_pipeline_key=root_pipeline_key))
task.add(queue_name=self.queue_name, transactional=True)
return True
return db.run_in_transaction(txn) | Kicks off the abort process for a root pipeline and all its children.
Args:
root_pipeline_key: db.Key of the root pipeline to abort.
abort_message: Message explaining why the abort happened, only saved
into the root pipeline.
Returns:
True if the abort signal was sent successfully; False otherwise. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1667-L1706 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _PipelineContext.continue_abort | def continue_abort(self,
root_pipeline_key,
cursor=None,
max_to_notify=_MAX_ABORTS_TO_BEGIN):
"""Sends the abort signal to all children for a root pipeline.
Args:
root_pipeline_key: db.Key of the root pipeline to abort.
cursor: The query cursor for enumerating _PipelineRecords when inserting
tasks to cause child pipelines to terminate.
max_to_notify: Used for testing.
"""
if not isinstance(root_pipeline_key, db.Key):
root_pipeline_key = db.Key(root_pipeline_key)
# NOTE: The results of this query may include _PipelineRecord instances
# that are not actually "reachable", meaning you cannot get to them by
# starting at the root pipeline and following "fanned_out" onward. This
# is acceptable because even these defunct _PipelineRecords will properly
# set their status to ABORTED when the signal comes, regardless of any
# other status they may have had.
#
# The only gotcha here is if a Pipeline's finalize method somehow modifies
# its inputs (like deleting an input file). In the case there are
# unreachable child pipelines, it will appear as if two finalize methods
# have been called instead of just one. The saving grace here is that
# finalize must be idempotent, so this *should* be harmless.
query = (
_PipelineRecord.all(cursor=cursor)
.filter('root_pipeline =', root_pipeline_key))
results = query.fetch(max_to_notify)
task_list = []
for pipeline_record in results:
if pipeline_record.status not in (
_PipelineRecord.RUN, _PipelineRecord.WAITING):
continue
pipeline_key = pipeline_record.key()
task_list.append(taskqueue.Task(
name='%s-%s-abort' % (self.task_name, pipeline_key.name()),
url=self.abort_handler_path,
params=dict(pipeline_key=pipeline_key, purpose=_BarrierRecord.ABORT),
headers={'X-Ae-Pipeline-Key': pipeline_key}))
# Task continuation with sequence number to prevent fork-bombs.
if len(results) == max_to_notify:
the_match = re.match('(.*)-([0-9]+)', self.task_name)
if the_match:
prefix = the_match.group(1)
end = int(the_match.group(2)) + 1
else:
prefix = self.task_name
end = 0
task_list.append(taskqueue.Task(
name='%s-%d' % (prefix, end),
url=self.fanout_abort_handler_path,
params=dict(root_pipeline_key=root_pipeline_key,
cursor=query.cursor())))
if task_list:
try:
taskqueue.Queue(self.queue_name).add(task_list)
except (taskqueue.TombstonedTaskError, taskqueue.TaskAlreadyExistsError):
pass | python | def continue_abort(self,
root_pipeline_key,
cursor=None,
max_to_notify=_MAX_ABORTS_TO_BEGIN):
"""Sends the abort signal to all children for a root pipeline.
Args:
root_pipeline_key: db.Key of the root pipeline to abort.
cursor: The query cursor for enumerating _PipelineRecords when inserting
tasks to cause child pipelines to terminate.
max_to_notify: Used for testing.
"""
if not isinstance(root_pipeline_key, db.Key):
root_pipeline_key = db.Key(root_pipeline_key)
# NOTE: The results of this query may include _PipelineRecord instances
# that are not actually "reachable", meaning you cannot get to them by
# starting at the root pipeline and following "fanned_out" onward. This
# is acceptable because even these defunct _PipelineRecords will properly
# set their status to ABORTED when the signal comes, regardless of any
# other status they may have had.
#
# The only gotcha here is if a Pipeline's finalize method somehow modifies
# its inputs (like deleting an input file). In the case there are
# unreachable child pipelines, it will appear as if two finalize methods
# have been called instead of just one. The saving grace here is that
# finalize must be idempotent, so this *should* be harmless.
query = (
_PipelineRecord.all(cursor=cursor)
.filter('root_pipeline =', root_pipeline_key))
results = query.fetch(max_to_notify)
task_list = []
for pipeline_record in results:
if pipeline_record.status not in (
_PipelineRecord.RUN, _PipelineRecord.WAITING):
continue
pipeline_key = pipeline_record.key()
task_list.append(taskqueue.Task(
name='%s-%s-abort' % (self.task_name, pipeline_key.name()),
url=self.abort_handler_path,
params=dict(pipeline_key=pipeline_key, purpose=_BarrierRecord.ABORT),
headers={'X-Ae-Pipeline-Key': pipeline_key}))
# Task continuation with sequence number to prevent fork-bombs.
if len(results) == max_to_notify:
the_match = re.match('(.*)-([0-9]+)', self.task_name)
if the_match:
prefix = the_match.group(1)
end = int(the_match.group(2)) + 1
else:
prefix = self.task_name
end = 0
task_list.append(taskqueue.Task(
name='%s-%d' % (prefix, end),
url=self.fanout_abort_handler_path,
params=dict(root_pipeline_key=root_pipeline_key,
cursor=query.cursor())))
if task_list:
try:
taskqueue.Queue(self.queue_name).add(task_list)
except (taskqueue.TombstonedTaskError, taskqueue.TaskAlreadyExistsError):
pass | Sends the abort signal to all children for a root pipeline.
Args:
root_pipeline_key: db.Key of the root pipeline to abort.
cursor: The query cursor for enumerating _PipelineRecords when inserting
tasks to cause child pipelines to terminate.
max_to_notify: Used for testing. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1708-L1771 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _PipelineContext.start | def start(self, pipeline, return_task=True, countdown=None, eta=None):
"""Starts a pipeline.
Args:
pipeline: Pipeline instance to run.
return_task: When True, do not submit the task to start the pipeline
but instead return it for someone else to enqueue.
countdown: Time in seconds into the future that this Task should execute.
Defaults to zero.
eta: A datetime.datetime specifying the absolute time at which the task
should be executed. Must not be specified if 'countdown' is specified.
This may be timezone-aware or timezone-naive. If None, defaults to now.
For pull tasks, no worker will be able to lease this task before the
time indicated by eta.
Returns:
The task to start this pipeline if return_task was True.
Raises:
PipelineExistsError if the pipeline with the given ID already exists.
"""
# Adjust all pipeline output keys for this Pipeline to be children of
# the _PipelineRecord, that way we can write them all and submit in a
# single transaction.
for name, slot in pipeline.outputs._output_dict.iteritems():
slot.key = db.Key.from_path(
*slot.key.to_path(), **dict(parent=pipeline._pipeline_key))
_, output_slots, params_text, params_blob = _generate_args(
pipeline, pipeline.outputs, self.queue_name, self.base_path)
@db.transactional(propagation=db.INDEPENDENT)
def txn():
pipeline_record = db.get(pipeline._pipeline_key)
if pipeline_record is not None:
raise PipelineExistsError(
'Pipeline with idempotence key "%s" already exists; params=%s' %
(pipeline._pipeline_key.name(),
_short_repr(pipeline_record.params)))
entities_to_put = []
for name, slot in pipeline.outputs._output_dict.iteritems():
entities_to_put.append(_SlotRecord(
key=slot.key,
root_pipeline=pipeline._pipeline_key))
entities_to_put.append(_PipelineRecord(
key=pipeline._pipeline_key,
root_pipeline=pipeline._pipeline_key,
is_root_pipeline=True,
# Bug in DB means we need to use the storage name here,
# not the local property name.
params=params_text,
params_blob=params_blob,
start_time=self._gettime(),
class_path=pipeline._class_path,
max_attempts=pipeline.max_attempts))
entities_to_put.extend(_PipelineContext._create_barrier_entities(
pipeline._pipeline_key,
pipeline._pipeline_key,
_BarrierRecord.FINALIZE,
output_slots))
db.put(entities_to_put)
task = taskqueue.Task(
url=self.pipeline_handler_path,
params=dict(pipeline_key=pipeline._pipeline_key),
headers={'X-Ae-Pipeline-Key': pipeline._pipeline_key},
target=pipeline.target,
countdown=countdown,
eta=eta)
if return_task:
return task
task.add(queue_name=self.queue_name, transactional=True)
task = txn()
# Immediately mark the output slots as existing so they can be filled
# by asynchronous pipelines or used in test mode.
for output_slot in pipeline.outputs._output_dict.itervalues():
output_slot._exists = True
return task | python | def start(self, pipeline, return_task=True, countdown=None, eta=None):
"""Starts a pipeline.
Args:
pipeline: Pipeline instance to run.
return_task: When True, do not submit the task to start the pipeline
but instead return it for someone else to enqueue.
countdown: Time in seconds into the future that this Task should execute.
Defaults to zero.
eta: A datetime.datetime specifying the absolute time at which the task
should be executed. Must not be specified if 'countdown' is specified.
This may be timezone-aware or timezone-naive. If None, defaults to now.
For pull tasks, no worker will be able to lease this task before the
time indicated by eta.
Returns:
The task to start this pipeline if return_task was True.
Raises:
PipelineExistsError if the pipeline with the given ID already exists.
"""
# Adjust all pipeline output keys for this Pipeline to be children of
# the _PipelineRecord, that way we can write them all and submit in a
# single transaction.
for name, slot in pipeline.outputs._output_dict.iteritems():
slot.key = db.Key.from_path(
*slot.key.to_path(), **dict(parent=pipeline._pipeline_key))
_, output_slots, params_text, params_blob = _generate_args(
pipeline, pipeline.outputs, self.queue_name, self.base_path)
@db.transactional(propagation=db.INDEPENDENT)
def txn():
pipeline_record = db.get(pipeline._pipeline_key)
if pipeline_record is not None:
raise PipelineExistsError(
'Pipeline with idempotence key "%s" already exists; params=%s' %
(pipeline._pipeline_key.name(),
_short_repr(pipeline_record.params)))
entities_to_put = []
for name, slot in pipeline.outputs._output_dict.iteritems():
entities_to_put.append(_SlotRecord(
key=slot.key,
root_pipeline=pipeline._pipeline_key))
entities_to_put.append(_PipelineRecord(
key=pipeline._pipeline_key,
root_pipeline=pipeline._pipeline_key,
is_root_pipeline=True,
# Bug in DB means we need to use the storage name here,
# not the local property name.
params=params_text,
params_blob=params_blob,
start_time=self._gettime(),
class_path=pipeline._class_path,
max_attempts=pipeline.max_attempts))
entities_to_put.extend(_PipelineContext._create_barrier_entities(
pipeline._pipeline_key,
pipeline._pipeline_key,
_BarrierRecord.FINALIZE,
output_slots))
db.put(entities_to_put)
task = taskqueue.Task(
url=self.pipeline_handler_path,
params=dict(pipeline_key=pipeline._pipeline_key),
headers={'X-Ae-Pipeline-Key': pipeline._pipeline_key},
target=pipeline.target,
countdown=countdown,
eta=eta)
if return_task:
return task
task.add(queue_name=self.queue_name, transactional=True)
task = txn()
# Immediately mark the output slots as existing so they can be filled
# by asynchronous pipelines or used in test mode.
for output_slot in pipeline.outputs._output_dict.itervalues():
output_slot._exists = True
return task | Starts a pipeline.
Args:
pipeline: Pipeline instance to run.
return_task: When True, do not submit the task to start the pipeline
but instead return it for someone else to enqueue.
countdown: Time in seconds into the future that this Task should execute.
Defaults to zero.
eta: A datetime.datetime specifying the absolute time at which the task
should be executed. Must not be specified if 'countdown' is specified.
This may be timezone-aware or timezone-naive. If None, defaults to now.
For pull tasks, no worker will be able to lease this task before the
time indicated by eta.
Returns:
The task to start this pipeline if return_task was True.
Raises:
PipelineExistsError if the pipeline with the given ID already exists. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1773-L1855 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _PipelineContext.evaluate | def evaluate(self, pipeline_key, purpose=None, attempt=0):
"""Evaluates the given Pipeline and enqueues sub-stages for execution.
Args:
pipeline_key: The db.Key or stringified key of the _PipelineRecord to run.
purpose: Why evaluate was called ('start', 'finalize', or 'abort').
attempt: The attempt number that should be tried.
"""
After._thread_init()
InOrder._thread_init()
InOrder._local._activated = False
if not isinstance(pipeline_key, db.Key):
pipeline_key = db.Key(pipeline_key)
pipeline_record = db.get(pipeline_key)
if pipeline_record is None:
logging.error('Pipeline ID "%s" does not exist.', pipeline_key.name())
return
if pipeline_record.status not in (
_PipelineRecord.WAITING, _PipelineRecord.RUN):
# If we're attempting to abort an already aborted pipeline,
# we silently advance. #50
if (pipeline_record.status == _PipelineRecord.ABORTED and
purpose == _BarrierRecord.ABORT):
return
logging.error('Pipeline ID "%s" in bad state for purpose "%s": "%s"',
pipeline_key.name(), purpose or _BarrierRecord.START,
pipeline_record.status)
return
params = pipeline_record.params
root_pipeline_key = \
_PipelineRecord.root_pipeline.get_value_for_datastore(pipeline_record)
default_slot_key = db.Key(params['output_slots']['default'])
default_slot_record, root_pipeline_record = db.get([
default_slot_key, root_pipeline_key])
if default_slot_record is None:
logging.error('Pipeline ID "%s" default slot "%s" does not exist.',
pipeline_key.name(), default_slot_key)
return
if root_pipeline_record is None:
logging.error('Pipeline ID "%s" root pipeline ID "%s" is missing.',
pipeline_key.name(), root_pipeline_key.name())
return
# Always finalize if we're aborting so pipelines have a chance to cleanup
# before they terminate. Pipelines must access 'was_aborted' to find
# out how their finalization should work.
abort_signal = (
purpose == _BarrierRecord.ABORT or
root_pipeline_record.abort_requested == True)
finalize_signal = (
(default_slot_record.status == _SlotRecord.FILLED and
purpose == _BarrierRecord.FINALIZE) or abort_signal)
try:
pipeline_func_class = mr_util.for_name(pipeline_record.class_path)
except ImportError, e:
# This means something is wrong with the deployed code. Rely on the
# taskqueue system to do retries.
retry_message = '%s: %s' % (e.__class__.__name__, str(e))
logging.exception(
'Could not locate %s#%s. %s',
pipeline_record.class_path, pipeline_key.name(), retry_message)
raise
try:
pipeline_func = pipeline_func_class.from_id(
pipeline_key.name(),
resolve_outputs=finalize_signal,
_pipeline_record=pipeline_record)
except SlotNotFilledError, e:
logging.exception(
'Could not resolve arguments for %s#%s. Most likely this means there '
'is a bug in the Pipeline runtime or some intermediate data has been '
'deleted from the Datastore. Giving up.',
pipeline_record.class_path, pipeline_key.name())
self.transition_aborted(pipeline_key)
return
except Exception, e:
retry_message = '%s: %s' % (e.__class__.__name__, str(e))
logging.exception(
'Instantiating %s#%s raised exception. %s',
pipeline_record.class_path, pipeline_key.name(), retry_message)
self.transition_retry(pipeline_key, retry_message)
if pipeline_record.params['task_retry']:
raise
else:
return
else:
pipeline_generator = mr_util.is_generator_function(
pipeline_func_class.run)
caller_output = pipeline_func.outputs
if (abort_signal and pipeline_func.async and
pipeline_record.status == _PipelineRecord.RUN
and not pipeline_func.try_cancel()):
logging.warning(
'Could not cancel and abort mid-flight async pipeline: %r#%s',
pipeline_func, pipeline_key.name())
return
if finalize_signal:
try:
pipeline_func._finalized_internal(
self, pipeline_key, root_pipeline_key,
caller_output, abort_signal)
except Exception, e:
# This means something is wrong with the deployed finalization code.
# Rely on the taskqueue system to do retries.
retry_message = '%s: %s' % (e.__class__.__name__, str(e))
logging.exception('Finalizing %r#%s raised exception. %s',
pipeline_func, pipeline_key.name(), retry_message)
raise
else:
if not abort_signal:
self.transition_complete(pipeline_key)
return
if abort_signal:
logging.debug('Marking as aborted %s#%s', pipeline_func,
pipeline_key.name())
self.transition_aborted(pipeline_key)
return
if pipeline_record.current_attempt != attempt:
logging.error(
'Received evaluation task for pipeline ID "%s" attempt %d but '
'current pending attempt is %d', pipeline_key.name(), attempt,
pipeline_record.current_attempt)
return
if pipeline_record.current_attempt >= pipeline_record.max_attempts:
logging.error(
'Received evaluation task for pipeline ID "%s" on attempt %d '
'but that exceeds max attempts %d', pipeline_key.name(), attempt,
pipeline_record.max_attempts)
return
if pipeline_record.next_retry_time is not None:
retry_time = pipeline_record.next_retry_time - _RETRY_WIGGLE_TIMEDELTA
if self._gettime() <= retry_time:
detail_message = (
'Received evaluation task for pipeline ID "%s" on attempt %d, '
'which will not be ready until: %s' % (pipeline_key.name(),
pipeline_record.current_attempt, pipeline_record.next_retry_time))
logging.warning(detail_message)
raise UnexpectedPipelineError(detail_message)
if pipeline_record.status == _PipelineRecord.RUN and pipeline_generator:
if (default_slot_record.status == _SlotRecord.WAITING and
not pipeline_record.fanned_out):
# This properly handles the yield-less generator case when the
# RUN state transition worked properly but outputting to the default
# slot failed.
self.fill_slot(pipeline_key, caller_output.default, None)
return
if (pipeline_record.status == _PipelineRecord.WAITING and
pipeline_func.async):
self.transition_run(pipeline_key)
try:
result = pipeline_func._run_internal(
self, pipeline_key, root_pipeline_key, caller_output)
except Exception, e:
if self.handle_run_exception(pipeline_key, pipeline_func, e):
raise
else:
return
if pipeline_func.async:
return
if not pipeline_generator:
# Catch any exceptions that are thrown when the pipeline's return
# value is being serialized. This ensures that serialization errors
# will cause normal abort/retry behavior.
try:
self.fill_slot(pipeline_key, caller_output.default, result)
except Exception, e:
retry_message = 'Bad return value. %s: %s' % (
e.__class__.__name__, str(e))
logging.exception(
'Generator %r#%s caused exception while serializing return '
'value %r. %s', pipeline_func, pipeline_key.name(), result,
retry_message)
self.transition_retry(pipeline_key, retry_message)
if pipeline_func.task_retry:
raise
else:
return
expected_outputs = set(caller_output._output_dict.iterkeys())
found_outputs = self.session_filled_output_names
if expected_outputs != found_outputs:
exception = SlotNotFilledError(
'Outputs %r for pipeline ID "%s" were never filled by "%s".' % (
expected_outputs - found_outputs,
pipeline_key.name(), pipeline_func._class_path))
if self.handle_run_exception(pipeline_key, pipeline_func, exception):
raise exception
return
pipeline_iter = result
next_value = None
last_sub_stage = None
sub_stage = None
sub_stage_dict = {}
sub_stage_ordering = []
while True:
try:
yielded = pipeline_iter.send(next_value)
except StopIteration:
break
except Exception, e:
if self.handle_run_exception(pipeline_key, pipeline_func, e):
raise
else:
return
if isinstance(yielded, Pipeline):
if yielded in sub_stage_dict:
raise UnexpectedPipelineError(
'Already yielded pipeline object %r with pipeline ID %s' %
(yielded, yielded.pipeline_id))
last_sub_stage = yielded
next_value = PipelineFuture(yielded.output_names)
next_value._after_all_pipelines.update(After._local._after_all_futures)
next_value._after_all_pipelines.update(InOrder._local._in_order_futures)
sub_stage_dict[yielded] = next_value
sub_stage_ordering.append(yielded)
InOrder._add_future(next_value)
# To aid local testing, the task_retry flag (which instructs the
# evaluator to raise all exceptions back up to the task queue) is
# inherited by all children from the root down.
yielded.task_retry = pipeline_func.task_retry
else:
raise UnexpectedPipelineError(
'Yielded a disallowed value: %r' % yielded)
if last_sub_stage:
# Final yielded stage inherits outputs from calling pipeline that were not
# already filled during the generator's execution.
inherited_outputs = params['output_slots']
for slot_name in self.session_filled_output_names:
del inherited_outputs[slot_name]
sub_stage_dict[last_sub_stage]._inherit_outputs(
pipeline_record.class_path, inherited_outputs)
else:
# Here the generator has yielded nothing, and thus acts as a synchronous
# function. We can skip the rest of the generator steps completely and
# fill the default output slot to cause finalizing.
expected_outputs = set(caller_output._output_dict.iterkeys())
expected_outputs.remove('default')
found_outputs = self.session_filled_output_names
if expected_outputs != found_outputs:
exception = SlotNotFilledError(
'Outputs %r for pipeline ID "%s" were never filled by "%s".' % (
expected_outputs - found_outputs,
pipeline_key.name(), pipeline_func._class_path))
if self.handle_run_exception(pipeline_key, pipeline_func, exception):
raise exception
else:
self.fill_slot(pipeline_key, caller_output.default, None)
self.transition_run(pipeline_key)
return
# Allocate any SlotRecords that do not yet exist.
entities_to_put = []
for future in sub_stage_dict.itervalues():
for slot in future._output_dict.itervalues():
if not slot._exists:
entities_to_put.append(_SlotRecord(
key=slot.key, root_pipeline=root_pipeline_key))
# Allocate PipelineRecords and BarrierRecords for generator-run Pipelines.
pipelines_to_run = set()
all_children_keys = []
all_output_slots = set()
for sub_stage in sub_stage_ordering:
future = sub_stage_dict[sub_stage]
# Catch any exceptions that are thrown when the pipeline's parameters
# are being serialized. This ensures that serialization errors will
# cause normal retry/abort behavior.
try:
dependent_slots, output_slots, params_text, params_blob = \
_generate_args(sub_stage, future, self.queue_name, self.base_path)
except Exception, e:
retry_message = 'Bad child arguments. %s: %s' % (
e.__class__.__name__, str(e))
logging.exception(
'Generator %r#%s caused exception while serializing args for '
'child pipeline %r. %s', pipeline_func, pipeline_key.name(),
sub_stage, retry_message)
self.transition_retry(pipeline_key, retry_message)
if pipeline_func.task_retry:
raise
else:
return
child_pipeline_key = db.Key.from_path(
_PipelineRecord.kind(), uuid.uuid4().hex)
all_output_slots.update(output_slots)
all_children_keys.append(child_pipeline_key)
child_pipeline = _PipelineRecord(
key=child_pipeline_key,
root_pipeline=root_pipeline_key,
# Bug in DB means we need to use the storage name here,
# not the local property name.
params=params_text,
params_blob=params_blob,
class_path=sub_stage._class_path,
max_attempts=sub_stage.max_attempts)
entities_to_put.append(child_pipeline)
if not dependent_slots:
# This child pipeline will run immediately.
pipelines_to_run.add(child_pipeline_key)
child_pipeline.start_time = self._gettime()
else:
entities_to_put.extend(_PipelineContext._create_barrier_entities(
root_pipeline_key,
child_pipeline_key,
_BarrierRecord.START,
dependent_slots))
entities_to_put.extend(_PipelineContext._create_barrier_entities(
root_pipeline_key,
child_pipeline_key,
_BarrierRecord.FINALIZE,
output_slots))
# This generator pipeline's finalization barrier must include all of the
# outputs of any child pipelines that it runs. This ensures the finalized
# calls will not happen until all child pipelines have completed.
#
# The transition_run() call below will update the FINALIZE _BarrierRecord
# for this generator pipeline to include all of these child outputs in
# its list of blocking_slots. That update is done transactionally to
# make sure the _BarrierRecord only lists the slots that matter.
#
# However, the notify_barriers() method doesn't find _BarrierRecords
# through the blocking_slots field. It finds them through _BarrierIndexes
# entities. Thus, before we update the FINALIZE _BarrierRecord in
# transition_run(), we need to write _BarrierIndexes for all child outputs.
barrier_entities = _PipelineContext._create_barrier_entities(
root_pipeline_key,
pipeline_key,
_BarrierRecord.FINALIZE,
all_output_slots)
# Ignore the first element which is the _BarrierRecord. That entity must
# have already been created and put in the datastore for the parent
# pipeline before this code generated child pipelines.
barrier_indexes = barrier_entities[1:]
entities_to_put.extend(barrier_indexes)
db.put(entities_to_put)
self.transition_run(pipeline_key,
blocking_slot_keys=all_output_slots,
fanned_out_pipelines=all_children_keys,
pipelines_to_run=pipelines_to_run) | python | def evaluate(self, pipeline_key, purpose=None, attempt=0):
"""Evaluates the given Pipeline and enqueues sub-stages for execution.
Args:
pipeline_key: The db.Key or stringified key of the _PipelineRecord to run.
purpose: Why evaluate was called ('start', 'finalize', or 'abort').
attempt: The attempt number that should be tried.
"""
After._thread_init()
InOrder._thread_init()
InOrder._local._activated = False
if not isinstance(pipeline_key, db.Key):
pipeline_key = db.Key(pipeline_key)
pipeline_record = db.get(pipeline_key)
if pipeline_record is None:
logging.error('Pipeline ID "%s" does not exist.', pipeline_key.name())
return
if pipeline_record.status not in (
_PipelineRecord.WAITING, _PipelineRecord.RUN):
# If we're attempting to abort an already aborted pipeline,
# we silently advance. #50
if (pipeline_record.status == _PipelineRecord.ABORTED and
purpose == _BarrierRecord.ABORT):
return
logging.error('Pipeline ID "%s" in bad state for purpose "%s": "%s"',
pipeline_key.name(), purpose or _BarrierRecord.START,
pipeline_record.status)
return
params = pipeline_record.params
root_pipeline_key = \
_PipelineRecord.root_pipeline.get_value_for_datastore(pipeline_record)
default_slot_key = db.Key(params['output_slots']['default'])
default_slot_record, root_pipeline_record = db.get([
default_slot_key, root_pipeline_key])
if default_slot_record is None:
logging.error('Pipeline ID "%s" default slot "%s" does not exist.',
pipeline_key.name(), default_slot_key)
return
if root_pipeline_record is None:
logging.error('Pipeline ID "%s" root pipeline ID "%s" is missing.',
pipeline_key.name(), root_pipeline_key.name())
return
# Always finalize if we're aborting so pipelines have a chance to cleanup
# before they terminate. Pipelines must access 'was_aborted' to find
# out how their finalization should work.
abort_signal = (
purpose == _BarrierRecord.ABORT or
root_pipeline_record.abort_requested == True)
finalize_signal = (
(default_slot_record.status == _SlotRecord.FILLED and
purpose == _BarrierRecord.FINALIZE) or abort_signal)
try:
pipeline_func_class = mr_util.for_name(pipeline_record.class_path)
except ImportError, e:
# This means something is wrong with the deployed code. Rely on the
# taskqueue system to do retries.
retry_message = '%s: %s' % (e.__class__.__name__, str(e))
logging.exception(
'Could not locate %s#%s. %s',
pipeline_record.class_path, pipeline_key.name(), retry_message)
raise
try:
pipeline_func = pipeline_func_class.from_id(
pipeline_key.name(),
resolve_outputs=finalize_signal,
_pipeline_record=pipeline_record)
except SlotNotFilledError, e:
logging.exception(
'Could not resolve arguments for %s#%s. Most likely this means there '
'is a bug in the Pipeline runtime or some intermediate data has been '
'deleted from the Datastore. Giving up.',
pipeline_record.class_path, pipeline_key.name())
self.transition_aborted(pipeline_key)
return
except Exception, e:
retry_message = '%s: %s' % (e.__class__.__name__, str(e))
logging.exception(
'Instantiating %s#%s raised exception. %s',
pipeline_record.class_path, pipeline_key.name(), retry_message)
self.transition_retry(pipeline_key, retry_message)
if pipeline_record.params['task_retry']:
raise
else:
return
else:
pipeline_generator = mr_util.is_generator_function(
pipeline_func_class.run)
caller_output = pipeline_func.outputs
if (abort_signal and pipeline_func.async and
pipeline_record.status == _PipelineRecord.RUN
and not pipeline_func.try_cancel()):
logging.warning(
'Could not cancel and abort mid-flight async pipeline: %r#%s',
pipeline_func, pipeline_key.name())
return
if finalize_signal:
try:
pipeline_func._finalized_internal(
self, pipeline_key, root_pipeline_key,
caller_output, abort_signal)
except Exception, e:
# This means something is wrong with the deployed finalization code.
# Rely on the taskqueue system to do retries.
retry_message = '%s: %s' % (e.__class__.__name__, str(e))
logging.exception('Finalizing %r#%s raised exception. %s',
pipeline_func, pipeline_key.name(), retry_message)
raise
else:
if not abort_signal:
self.transition_complete(pipeline_key)
return
if abort_signal:
logging.debug('Marking as aborted %s#%s', pipeline_func,
pipeline_key.name())
self.transition_aborted(pipeline_key)
return
if pipeline_record.current_attempt != attempt:
logging.error(
'Received evaluation task for pipeline ID "%s" attempt %d but '
'current pending attempt is %d', pipeline_key.name(), attempt,
pipeline_record.current_attempt)
return
if pipeline_record.current_attempt >= pipeline_record.max_attempts:
logging.error(
'Received evaluation task for pipeline ID "%s" on attempt %d '
'but that exceeds max attempts %d', pipeline_key.name(), attempt,
pipeline_record.max_attempts)
return
if pipeline_record.next_retry_time is not None:
retry_time = pipeline_record.next_retry_time - _RETRY_WIGGLE_TIMEDELTA
if self._gettime() <= retry_time:
detail_message = (
'Received evaluation task for pipeline ID "%s" on attempt %d, '
'which will not be ready until: %s' % (pipeline_key.name(),
pipeline_record.current_attempt, pipeline_record.next_retry_time))
logging.warning(detail_message)
raise UnexpectedPipelineError(detail_message)
if pipeline_record.status == _PipelineRecord.RUN and pipeline_generator:
if (default_slot_record.status == _SlotRecord.WAITING and
not pipeline_record.fanned_out):
# This properly handles the yield-less generator case when the
# RUN state transition worked properly but outputting to the default
# slot failed.
self.fill_slot(pipeline_key, caller_output.default, None)
return
if (pipeline_record.status == _PipelineRecord.WAITING and
pipeline_func.async):
self.transition_run(pipeline_key)
try:
result = pipeline_func._run_internal(
self, pipeline_key, root_pipeline_key, caller_output)
except Exception, e:
if self.handle_run_exception(pipeline_key, pipeline_func, e):
raise
else:
return
if pipeline_func.async:
return
if not pipeline_generator:
# Catch any exceptions that are thrown when the pipeline's return
# value is being serialized. This ensures that serialization errors
# will cause normal abort/retry behavior.
try:
self.fill_slot(pipeline_key, caller_output.default, result)
except Exception, e:
retry_message = 'Bad return value. %s: %s' % (
e.__class__.__name__, str(e))
logging.exception(
'Generator %r#%s caused exception while serializing return '
'value %r. %s', pipeline_func, pipeline_key.name(), result,
retry_message)
self.transition_retry(pipeline_key, retry_message)
if pipeline_func.task_retry:
raise
else:
return
expected_outputs = set(caller_output._output_dict.iterkeys())
found_outputs = self.session_filled_output_names
if expected_outputs != found_outputs:
exception = SlotNotFilledError(
'Outputs %r for pipeline ID "%s" were never filled by "%s".' % (
expected_outputs - found_outputs,
pipeline_key.name(), pipeline_func._class_path))
if self.handle_run_exception(pipeline_key, pipeline_func, exception):
raise exception
return
pipeline_iter = result
next_value = None
last_sub_stage = None
sub_stage = None
sub_stage_dict = {}
sub_stage_ordering = []
while True:
try:
yielded = pipeline_iter.send(next_value)
except StopIteration:
break
except Exception, e:
if self.handle_run_exception(pipeline_key, pipeline_func, e):
raise
else:
return
if isinstance(yielded, Pipeline):
if yielded in sub_stage_dict:
raise UnexpectedPipelineError(
'Already yielded pipeline object %r with pipeline ID %s' %
(yielded, yielded.pipeline_id))
last_sub_stage = yielded
next_value = PipelineFuture(yielded.output_names)
next_value._after_all_pipelines.update(After._local._after_all_futures)
next_value._after_all_pipelines.update(InOrder._local._in_order_futures)
sub_stage_dict[yielded] = next_value
sub_stage_ordering.append(yielded)
InOrder._add_future(next_value)
# To aid local testing, the task_retry flag (which instructs the
# evaluator to raise all exceptions back up to the task queue) is
# inherited by all children from the root down.
yielded.task_retry = pipeline_func.task_retry
else:
raise UnexpectedPipelineError(
'Yielded a disallowed value: %r' % yielded)
if last_sub_stage:
# Final yielded stage inherits outputs from calling pipeline that were not
# already filled during the generator's execution.
inherited_outputs = params['output_slots']
for slot_name in self.session_filled_output_names:
del inherited_outputs[slot_name]
sub_stage_dict[last_sub_stage]._inherit_outputs(
pipeline_record.class_path, inherited_outputs)
else:
# Here the generator has yielded nothing, and thus acts as a synchronous
# function. We can skip the rest of the generator steps completely and
# fill the default output slot to cause finalizing.
expected_outputs = set(caller_output._output_dict.iterkeys())
expected_outputs.remove('default')
found_outputs = self.session_filled_output_names
if expected_outputs != found_outputs:
exception = SlotNotFilledError(
'Outputs %r for pipeline ID "%s" were never filled by "%s".' % (
expected_outputs - found_outputs,
pipeline_key.name(), pipeline_func._class_path))
if self.handle_run_exception(pipeline_key, pipeline_func, exception):
raise exception
else:
self.fill_slot(pipeline_key, caller_output.default, None)
self.transition_run(pipeline_key)
return
# Allocate any SlotRecords that do not yet exist.
entities_to_put = []
for future in sub_stage_dict.itervalues():
for slot in future._output_dict.itervalues():
if not slot._exists:
entities_to_put.append(_SlotRecord(
key=slot.key, root_pipeline=root_pipeline_key))
# Allocate PipelineRecords and BarrierRecords for generator-run Pipelines.
pipelines_to_run = set()
all_children_keys = []
all_output_slots = set()
for sub_stage in sub_stage_ordering:
future = sub_stage_dict[sub_stage]
# Catch any exceptions that are thrown when the pipeline's parameters
# are being serialized. This ensures that serialization errors will
# cause normal retry/abort behavior.
try:
dependent_slots, output_slots, params_text, params_blob = \
_generate_args(sub_stage, future, self.queue_name, self.base_path)
except Exception, e:
retry_message = 'Bad child arguments. %s: %s' % (
e.__class__.__name__, str(e))
logging.exception(
'Generator %r#%s caused exception while serializing args for '
'child pipeline %r. %s', pipeline_func, pipeline_key.name(),
sub_stage, retry_message)
self.transition_retry(pipeline_key, retry_message)
if pipeline_func.task_retry:
raise
else:
return
child_pipeline_key = db.Key.from_path(
_PipelineRecord.kind(), uuid.uuid4().hex)
all_output_slots.update(output_slots)
all_children_keys.append(child_pipeline_key)
child_pipeline = _PipelineRecord(
key=child_pipeline_key,
root_pipeline=root_pipeline_key,
# Bug in DB means we need to use the storage name here,
# not the local property name.
params=params_text,
params_blob=params_blob,
class_path=sub_stage._class_path,
max_attempts=sub_stage.max_attempts)
entities_to_put.append(child_pipeline)
if not dependent_slots:
# This child pipeline will run immediately.
pipelines_to_run.add(child_pipeline_key)
child_pipeline.start_time = self._gettime()
else:
entities_to_put.extend(_PipelineContext._create_barrier_entities(
root_pipeline_key,
child_pipeline_key,
_BarrierRecord.START,
dependent_slots))
entities_to_put.extend(_PipelineContext._create_barrier_entities(
root_pipeline_key,
child_pipeline_key,
_BarrierRecord.FINALIZE,
output_slots))
# This generator pipeline's finalization barrier must include all of the
# outputs of any child pipelines that it runs. This ensures the finalized
# calls will not happen until all child pipelines have completed.
#
# The transition_run() call below will update the FINALIZE _BarrierRecord
# for this generator pipeline to include all of these child outputs in
# its list of blocking_slots. That update is done transactionally to
# make sure the _BarrierRecord only lists the slots that matter.
#
# However, the notify_barriers() method doesn't find _BarrierRecords
# through the blocking_slots field. It finds them through _BarrierIndexes
# entities. Thus, before we update the FINALIZE _BarrierRecord in
# transition_run(), we need to write _BarrierIndexes for all child outputs.
barrier_entities = _PipelineContext._create_barrier_entities(
root_pipeline_key,
pipeline_key,
_BarrierRecord.FINALIZE,
all_output_slots)
# Ignore the first element which is the _BarrierRecord. That entity must
# have already been created and put in the datastore for the parent
# pipeline before this code generated child pipelines.
barrier_indexes = barrier_entities[1:]
entities_to_put.extend(barrier_indexes)
db.put(entities_to_put)
self.transition_run(pipeline_key,
blocking_slot_keys=all_output_slots,
fanned_out_pipelines=all_children_keys,
pipelines_to_run=pipelines_to_run) | Evaluates the given Pipeline and enqueues sub-stages for execution.
Args:
pipeline_key: The db.Key or stringified key of the _PipelineRecord to run.
purpose: Why evaluate was called ('start', 'finalize', or 'abort').
attempt: The attempt number that should be tried. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L1989-L2359 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _PipelineContext._create_barrier_entities | def _create_barrier_entities(root_pipeline_key,
child_pipeline_key,
purpose,
blocking_slot_keys):
"""Creates all of the entities required for a _BarrierRecord.
Args:
root_pipeline_key: The root pipeline this is part of.
child_pipeline_key: The pipeline this barrier is for.
purpose: _BarrierRecord.START or _BarrierRecord.FINALIZE.
blocking_slot_keys: Set of db.Keys corresponding to _SlotRecords that
this barrier should wait on before firing.
Returns:
List of entities, starting with the _BarrierRecord entity, followed by
_BarrierIndexes used for firing when _SlotRecords are filled in the same
order as the blocking_slot_keys list provided. All of these entities
should be put in the Datastore to ensure the barrier fires properly.
"""
result = []
blocking_slot_keys = list(blocking_slot_keys)
barrier = _BarrierRecord(
parent=child_pipeline_key,
key_name=purpose,
target=child_pipeline_key,
root_pipeline=root_pipeline_key,
blocking_slots=blocking_slot_keys)
result.append(barrier)
for slot_key in blocking_slot_keys:
barrier_index_path = []
barrier_index_path.extend(slot_key.to_path())
barrier_index_path.extend(child_pipeline_key.to_path())
barrier_index_path.extend([_BarrierIndex.kind(), purpose])
barrier_index_key = db.Key.from_path(*barrier_index_path)
barrier_index = _BarrierIndex(
key=barrier_index_key,
root_pipeline=root_pipeline_key)
result.append(barrier_index)
return result | python | def _create_barrier_entities(root_pipeline_key,
child_pipeline_key,
purpose,
blocking_slot_keys):
"""Creates all of the entities required for a _BarrierRecord.
Args:
root_pipeline_key: The root pipeline this is part of.
child_pipeline_key: The pipeline this barrier is for.
purpose: _BarrierRecord.START or _BarrierRecord.FINALIZE.
blocking_slot_keys: Set of db.Keys corresponding to _SlotRecords that
this barrier should wait on before firing.
Returns:
List of entities, starting with the _BarrierRecord entity, followed by
_BarrierIndexes used for firing when _SlotRecords are filled in the same
order as the blocking_slot_keys list provided. All of these entities
should be put in the Datastore to ensure the barrier fires properly.
"""
result = []
blocking_slot_keys = list(blocking_slot_keys)
barrier = _BarrierRecord(
parent=child_pipeline_key,
key_name=purpose,
target=child_pipeline_key,
root_pipeline=root_pipeline_key,
blocking_slots=blocking_slot_keys)
result.append(barrier)
for slot_key in blocking_slot_keys:
barrier_index_path = []
barrier_index_path.extend(slot_key.to_path())
barrier_index_path.extend(child_pipeline_key.to_path())
barrier_index_path.extend([_BarrierIndex.kind(), purpose])
barrier_index_key = db.Key.from_path(*barrier_index_path)
barrier_index = _BarrierIndex(
key=barrier_index_key,
root_pipeline=root_pipeline_key)
result.append(barrier_index)
return result | Creates all of the entities required for a _BarrierRecord.
Args:
root_pipeline_key: The root pipeline this is part of.
child_pipeline_key: The pipeline this barrier is for.
purpose: _BarrierRecord.START or _BarrierRecord.FINALIZE.
blocking_slot_keys: Set of db.Keys corresponding to _SlotRecords that
this barrier should wait on before firing.
Returns:
List of entities, starting with the _BarrierRecord entity, followed by
_BarrierIndexes used for firing when _SlotRecords are filled in the same
order as the blocking_slot_keys list provided. All of these entities
should be put in the Datastore to ensure the barrier fires properly. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L2362-L2405 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _PipelineContext.handle_run_exception | def handle_run_exception(self, pipeline_key, pipeline_func, e):
"""Handles an exception raised by a Pipeline's user code.
Args:
pipeline_key: The pipeline that raised the error.
pipeline_func: The class path name of the Pipeline that was running.
e: The exception that was raised.
Returns:
True if the exception should be re-raised up through the calling stack
by the caller of this method.
"""
if isinstance(e, Retry):
retry_message = str(e)
logging.warning('User forced retry for pipeline ID "%s" of %r: %s',
pipeline_key.name(), pipeline_func, retry_message)
self.transition_retry(pipeline_key, retry_message)
elif isinstance(e, Abort):
abort_message = str(e)
logging.warning('User forced abort for pipeline ID "%s" of %r: %s',
pipeline_key.name(), pipeline_func, abort_message)
pipeline_func.abort(abort_message)
else:
retry_message = '%s: %s' % (e.__class__.__name__, str(e))
logging.exception('Generator %r#%s raised exception. %s',
pipeline_func, pipeline_key.name(), retry_message)
self.transition_retry(pipeline_key, retry_message)
return pipeline_func.task_retry | python | def handle_run_exception(self, pipeline_key, pipeline_func, e):
"""Handles an exception raised by a Pipeline's user code.
Args:
pipeline_key: The pipeline that raised the error.
pipeline_func: The class path name of the Pipeline that was running.
e: The exception that was raised.
Returns:
True if the exception should be re-raised up through the calling stack
by the caller of this method.
"""
if isinstance(e, Retry):
retry_message = str(e)
logging.warning('User forced retry for pipeline ID "%s" of %r: %s',
pipeline_key.name(), pipeline_func, retry_message)
self.transition_retry(pipeline_key, retry_message)
elif isinstance(e, Abort):
abort_message = str(e)
logging.warning('User forced abort for pipeline ID "%s" of %r: %s',
pipeline_key.name(), pipeline_func, abort_message)
pipeline_func.abort(abort_message)
else:
retry_message = '%s: %s' % (e.__class__.__name__, str(e))
logging.exception('Generator %r#%s raised exception. %s',
pipeline_func, pipeline_key.name(), retry_message)
self.transition_retry(pipeline_key, retry_message)
return pipeline_func.task_retry | Handles an exception raised by a Pipeline's user code.
Args:
pipeline_key: The pipeline that raised the error.
pipeline_func: The class path name of the Pipeline that was running.
e: The exception that was raised.
Returns:
True if the exception should be re-raised up through the calling stack
by the caller of this method. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L2407-L2435 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _PipelineContext.transition_run | def transition_run(self,
pipeline_key,
blocking_slot_keys=None,
fanned_out_pipelines=None,
pipelines_to_run=None):
"""Marks an asynchronous or generator pipeline as running.
Does nothing if the pipeline is no longer in a runnable state.
Args:
pipeline_key: The db.Key of the _PipelineRecord to update.
blocking_slot_keys: List of db.Key instances that this pipeline's
finalization barrier should wait on in addition to the existing one.
This is used to update the barrier to include all child outputs. When
None, the barrier will not be updated.
fanned_out_pipelines: List of db.Key instances of _PipelineRecords that
were fanned out by this generator pipeline. This is distinct from the
'pipelines_to_run' list because not all of the pipelines listed here
will be immediately ready to execute. When None, then this generator
yielded no children.
pipelines_to_run: List of db.Key instances of _PipelineRecords that should
be kicked off (fan-out) transactionally as part of this transition.
When None, no child pipelines will run. All db.Keys in this list must
also be present in the fanned_out_pipelines list.
Raises:
UnexpectedPipelineError if blocking_slot_keys was not empty and the
_BarrierRecord has gone missing.
"""
def txn():
pipeline_record = db.get(pipeline_key)
if pipeline_record is None:
logging.warning('Pipeline ID "%s" cannot be marked as run. '
'Does not exist.', pipeline_key.name())
raise db.Rollback()
if pipeline_record.status != _PipelineRecord.WAITING:
logging.warning('Pipeline ID "%s" in bad state to be marked as run: %s',
pipeline_key.name(), pipeline_record.status)
raise db.Rollback()
pipeline_record.status = _PipelineRecord.RUN
if fanned_out_pipelines:
# NOTE: We must model the pipeline relationship in a top-down manner,
# meaning each pipeline must point forward to the pipelines that it
# fanned out to. The reason is race conditions. If evaluate()
# dies early, it may create many unused _PipelineRecord and _SlotRecord
# instances that never progress. The only way we know which of these
# are valid is by traversing the graph from the root, where the
# fanned_out property refers to those pipelines that were run using a
# transactional task.
child_pipeline_list = list(fanned_out_pipelines)
pipeline_record.fanned_out = child_pipeline_list
if pipelines_to_run:
child_indexes = [
child_pipeline_list.index(p) for p in pipelines_to_run]
child_indexes.sort()
task = taskqueue.Task(
url=self.fanout_handler_path,
params=dict(parent_key=str(pipeline_key),
child_indexes=child_indexes))
task.add(queue_name=self.queue_name, transactional=True)
pipeline_record.put()
if blocking_slot_keys:
# NOTE: Always update a generator pipeline's finalization barrier to
# include all of the outputs of any pipelines that it runs, to ensure
# that finalized calls will not happen until all child pipelines have
# completed. This must happen transactionally with the enqueue of
# the fan-out kickoff task above to ensure the child output slots and
# the barrier blocking slots are the same.
barrier_key = db.Key.from_path(
_BarrierRecord.kind(), _BarrierRecord.FINALIZE,
parent=pipeline_key)
finalize_barrier = db.get(barrier_key)
if finalize_barrier is None:
raise UnexpectedPipelineError(
'Pipeline ID "%s" cannot update finalize barrier. '
'Does not exist.' % pipeline_key.name())
else:
finalize_barrier.blocking_slots = list(
blocking_slot_keys.union(set(finalize_barrier.blocking_slots)))
finalize_barrier.put()
db.run_in_transaction(txn) | python | def transition_run(self,
pipeline_key,
blocking_slot_keys=None,
fanned_out_pipelines=None,
pipelines_to_run=None):
"""Marks an asynchronous or generator pipeline as running.
Does nothing if the pipeline is no longer in a runnable state.
Args:
pipeline_key: The db.Key of the _PipelineRecord to update.
blocking_slot_keys: List of db.Key instances that this pipeline's
finalization barrier should wait on in addition to the existing one.
This is used to update the barrier to include all child outputs. When
None, the barrier will not be updated.
fanned_out_pipelines: List of db.Key instances of _PipelineRecords that
were fanned out by this generator pipeline. This is distinct from the
'pipelines_to_run' list because not all of the pipelines listed here
will be immediately ready to execute. When None, then this generator
yielded no children.
pipelines_to_run: List of db.Key instances of _PipelineRecords that should
be kicked off (fan-out) transactionally as part of this transition.
When None, no child pipelines will run. All db.Keys in this list must
also be present in the fanned_out_pipelines list.
Raises:
UnexpectedPipelineError if blocking_slot_keys was not empty and the
_BarrierRecord has gone missing.
"""
def txn():
pipeline_record = db.get(pipeline_key)
if pipeline_record is None:
logging.warning('Pipeline ID "%s" cannot be marked as run. '
'Does not exist.', pipeline_key.name())
raise db.Rollback()
if pipeline_record.status != _PipelineRecord.WAITING:
logging.warning('Pipeline ID "%s" in bad state to be marked as run: %s',
pipeline_key.name(), pipeline_record.status)
raise db.Rollback()
pipeline_record.status = _PipelineRecord.RUN
if fanned_out_pipelines:
# NOTE: We must model the pipeline relationship in a top-down manner,
# meaning each pipeline must point forward to the pipelines that it
# fanned out to. The reason is race conditions. If evaluate()
# dies early, it may create many unused _PipelineRecord and _SlotRecord
# instances that never progress. The only way we know which of these
# are valid is by traversing the graph from the root, where the
# fanned_out property refers to those pipelines that were run using a
# transactional task.
child_pipeline_list = list(fanned_out_pipelines)
pipeline_record.fanned_out = child_pipeline_list
if pipelines_to_run:
child_indexes = [
child_pipeline_list.index(p) for p in pipelines_to_run]
child_indexes.sort()
task = taskqueue.Task(
url=self.fanout_handler_path,
params=dict(parent_key=str(pipeline_key),
child_indexes=child_indexes))
task.add(queue_name=self.queue_name, transactional=True)
pipeline_record.put()
if blocking_slot_keys:
# NOTE: Always update a generator pipeline's finalization barrier to
# include all of the outputs of any pipelines that it runs, to ensure
# that finalized calls will not happen until all child pipelines have
# completed. This must happen transactionally with the enqueue of
# the fan-out kickoff task above to ensure the child output slots and
# the barrier blocking slots are the same.
barrier_key = db.Key.from_path(
_BarrierRecord.kind(), _BarrierRecord.FINALIZE,
parent=pipeline_key)
finalize_barrier = db.get(barrier_key)
if finalize_barrier is None:
raise UnexpectedPipelineError(
'Pipeline ID "%s" cannot update finalize barrier. '
'Does not exist.' % pipeline_key.name())
else:
finalize_barrier.blocking_slots = list(
blocking_slot_keys.union(set(finalize_barrier.blocking_slots)))
finalize_barrier.put()
db.run_in_transaction(txn) | Marks an asynchronous or generator pipeline as running.
Does nothing if the pipeline is no longer in a runnable state.
Args:
pipeline_key: The db.Key of the _PipelineRecord to update.
blocking_slot_keys: List of db.Key instances that this pipeline's
finalization barrier should wait on in addition to the existing one.
This is used to update the barrier to include all child outputs. When
None, the barrier will not be updated.
fanned_out_pipelines: List of db.Key instances of _PipelineRecords that
were fanned out by this generator pipeline. This is distinct from the
'pipelines_to_run' list because not all of the pipelines listed here
will be immediately ready to execute. When None, then this generator
yielded no children.
pipelines_to_run: List of db.Key instances of _PipelineRecords that should
be kicked off (fan-out) transactionally as part of this transition.
When None, no child pipelines will run. All db.Keys in this list must
also be present in the fanned_out_pipelines list.
Raises:
UnexpectedPipelineError if blocking_slot_keys was not empty and the
_BarrierRecord has gone missing. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L2437-L2523 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _PipelineContext.transition_complete | def transition_complete(self, pipeline_key):
"""Marks the given pipeline as complete.
Does nothing if the pipeline is no longer in a state that can be completed.
Args:
pipeline_key: db.Key of the _PipelineRecord that has completed.
"""
def txn():
pipeline_record = db.get(pipeline_key)
if pipeline_record is None:
logging.warning(
'Tried to mark pipeline ID "%s" as complete but it does not exist.',
pipeline_key.name())
raise db.Rollback()
if pipeline_record.status not in (
_PipelineRecord.WAITING, _PipelineRecord.RUN):
logging.warning(
'Tried to mark pipeline ID "%s" as complete, found bad state: %s',
pipeline_key.name(), pipeline_record.status)
raise db.Rollback()
pipeline_record.status = _PipelineRecord.DONE
pipeline_record.finalized_time = self._gettime()
pipeline_record.put()
db.run_in_transaction(txn) | python | def transition_complete(self, pipeline_key):
"""Marks the given pipeline as complete.
Does nothing if the pipeline is no longer in a state that can be completed.
Args:
pipeline_key: db.Key of the _PipelineRecord that has completed.
"""
def txn():
pipeline_record = db.get(pipeline_key)
if pipeline_record is None:
logging.warning(
'Tried to mark pipeline ID "%s" as complete but it does not exist.',
pipeline_key.name())
raise db.Rollback()
if pipeline_record.status not in (
_PipelineRecord.WAITING, _PipelineRecord.RUN):
logging.warning(
'Tried to mark pipeline ID "%s" as complete, found bad state: %s',
pipeline_key.name(), pipeline_record.status)
raise db.Rollback()
pipeline_record.status = _PipelineRecord.DONE
pipeline_record.finalized_time = self._gettime()
pipeline_record.put()
db.run_in_transaction(txn) | Marks the given pipeline as complete.
Does nothing if the pipeline is no longer in a state that can be completed.
Args:
pipeline_key: db.Key of the _PipelineRecord that has completed. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L2525-L2551 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _PipelineContext.transition_retry | def transition_retry(self, pipeline_key, retry_message):
"""Marks the given pipeline as requiring another retry.
Does nothing if all attempts have been exceeded.
Args:
pipeline_key: db.Key of the _PipelineRecord that needs to be retried.
retry_message: User-supplied message indicating the reason for the retry.
"""
def txn():
pipeline_record = db.get(pipeline_key)
if pipeline_record is None:
logging.warning(
'Tried to retry pipeline ID "%s" but it does not exist.',
pipeline_key.name())
raise db.Rollback()
if pipeline_record.status not in (
_PipelineRecord.WAITING, _PipelineRecord.RUN):
logging.warning(
'Tried to retry pipeline ID "%s", found bad state: %s',
pipeline_key.name(), pipeline_record.status)
raise db.Rollback()
params = pipeline_record.params
offset_seconds = (
params['backoff_seconds'] *
(params['backoff_factor'] ** pipeline_record.current_attempt))
pipeline_record.next_retry_time = (
self._gettime() + datetime.timedelta(seconds=offset_seconds))
pipeline_record.current_attempt += 1
pipeline_record.retry_message = retry_message
pipeline_record.status = _PipelineRecord.WAITING
if pipeline_record.current_attempt >= pipeline_record.max_attempts:
root_pipeline_key = (
_PipelineRecord.root_pipeline.get_value_for_datastore(
pipeline_record))
logging.warning(
'Giving up on pipeline ID "%s" after %d attempt(s); causing abort '
'all the way to the root pipeline ID "%s"', pipeline_key.name(),
pipeline_record.current_attempt, root_pipeline_key.name())
# NOTE: We do *not* set the status to aborted here to ensure that
# this pipeline will be finalized before it has been marked as aborted.
pipeline_record.abort_message = (
'Aborting after %d attempts' % pipeline_record.current_attempt)
task = taskqueue.Task(
url=self.fanout_abort_handler_path,
params=dict(root_pipeline_key=root_pipeline_key))
task.add(queue_name=self.queue_name, transactional=True)
else:
task = taskqueue.Task(
url=self.pipeline_handler_path,
eta=pipeline_record.next_retry_time,
params=dict(pipeline_key=pipeline_key,
purpose=_BarrierRecord.START,
attempt=pipeline_record.current_attempt),
headers={'X-Ae-Pipeline-Key': pipeline_key},
target=pipeline_record.params['target'])
task.add(queue_name=self.queue_name, transactional=True)
pipeline_record.put()
db.run_in_transaction(txn) | python | def transition_retry(self, pipeline_key, retry_message):
"""Marks the given pipeline as requiring another retry.
Does nothing if all attempts have been exceeded.
Args:
pipeline_key: db.Key of the _PipelineRecord that needs to be retried.
retry_message: User-supplied message indicating the reason for the retry.
"""
def txn():
pipeline_record = db.get(pipeline_key)
if pipeline_record is None:
logging.warning(
'Tried to retry pipeline ID "%s" but it does not exist.',
pipeline_key.name())
raise db.Rollback()
if pipeline_record.status not in (
_PipelineRecord.WAITING, _PipelineRecord.RUN):
logging.warning(
'Tried to retry pipeline ID "%s", found bad state: %s',
pipeline_key.name(), pipeline_record.status)
raise db.Rollback()
params = pipeline_record.params
offset_seconds = (
params['backoff_seconds'] *
(params['backoff_factor'] ** pipeline_record.current_attempt))
pipeline_record.next_retry_time = (
self._gettime() + datetime.timedelta(seconds=offset_seconds))
pipeline_record.current_attempt += 1
pipeline_record.retry_message = retry_message
pipeline_record.status = _PipelineRecord.WAITING
if pipeline_record.current_attempt >= pipeline_record.max_attempts:
root_pipeline_key = (
_PipelineRecord.root_pipeline.get_value_for_datastore(
pipeline_record))
logging.warning(
'Giving up on pipeline ID "%s" after %d attempt(s); causing abort '
'all the way to the root pipeline ID "%s"', pipeline_key.name(),
pipeline_record.current_attempt, root_pipeline_key.name())
# NOTE: We do *not* set the status to aborted here to ensure that
# this pipeline will be finalized before it has been marked as aborted.
pipeline_record.abort_message = (
'Aborting after %d attempts' % pipeline_record.current_attempt)
task = taskqueue.Task(
url=self.fanout_abort_handler_path,
params=dict(root_pipeline_key=root_pipeline_key))
task.add(queue_name=self.queue_name, transactional=True)
else:
task = taskqueue.Task(
url=self.pipeline_handler_path,
eta=pipeline_record.next_retry_time,
params=dict(pipeline_key=pipeline_key,
purpose=_BarrierRecord.START,
attempt=pipeline_record.current_attempt),
headers={'X-Ae-Pipeline-Key': pipeline_key},
target=pipeline_record.params['target'])
task.add(queue_name=self.queue_name, transactional=True)
pipeline_record.put()
db.run_in_transaction(txn) | Marks the given pipeline as requiring another retry.
Does nothing if all attempts have been exceeded.
Args:
pipeline_key: db.Key of the _PipelineRecord that needs to be retried.
retry_message: User-supplied message indicating the reason for the retry. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L2553-L2615 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/pipeline.py | _CallbackHandler.run_callback | def run_callback(self):
"""Runs the callback for the pipeline specified in the request.
Raises:
_CallbackTaskError if something was wrong with the request parameters.
"""
pipeline_id = self.request.get('pipeline_id')
if not pipeline_id:
raise _CallbackTaskError('"pipeline_id" parameter missing.')
pipeline_key = db.Key.from_path(_PipelineRecord.kind(), pipeline_id)
pipeline_record = db.get(pipeline_key)
if pipeline_record is None:
raise _CallbackTaskError(
'Pipeline ID "%s" for callback does not exist.' % pipeline_id)
params = pipeline_record.params
real_class_path = params['class_path']
try:
pipeline_func_class = mr_util.for_name(real_class_path)
except ImportError, e:
raise _CallbackTaskError(
'Cannot load class named "%s" for pipeline ID "%s".'
% (real_class_path, pipeline_id))
if 'HTTP_X_APPENGINE_TASKNAME' not in self.request.environ:
if pipeline_func_class.public_callbacks:
pass
elif pipeline_func_class.admin_callbacks:
if not users.is_current_user_admin():
raise _CallbackTaskError(
'Unauthorized callback for admin-only pipeline ID "%s"'
% pipeline_id)
else:
raise _CallbackTaskError(
'External callback for internal-only pipeline ID "%s"'
% pipeline_id)
kwargs = {}
for key in self.request.arguments():
if key != 'pipeline_id':
kwargs[str(key)] = self.request.get(key)
def perform_callback():
stage = pipeline_func_class.from_id(pipeline_id)
if stage is None:
raise _CallbackTaskError(
'Pipeline ID "%s" deleted during callback' % pipeline_id)
return stage._callback_internal(kwargs)
# callback_xg_transaction is a 3-valued setting (None=no trans,
# False=1-eg-trans, True=xg-trans)
if pipeline_func_class._callback_xg_transaction is not None:
transaction_options = db.create_transaction_options(
xg=pipeline_func_class._callback_xg_transaction)
callback_result = db.run_in_transaction_options(transaction_options,
perform_callback)
else:
callback_result = perform_callback()
if callback_result is not None:
status_code, content_type, content = callback_result
self.response.set_status(status_code)
self.response.headers['Content-Type'] = content_type
self.response.out.write(content) | python | def run_callback(self):
"""Runs the callback for the pipeline specified in the request.
Raises:
_CallbackTaskError if something was wrong with the request parameters.
"""
pipeline_id = self.request.get('pipeline_id')
if not pipeline_id:
raise _CallbackTaskError('"pipeline_id" parameter missing.')
pipeline_key = db.Key.from_path(_PipelineRecord.kind(), pipeline_id)
pipeline_record = db.get(pipeline_key)
if pipeline_record is None:
raise _CallbackTaskError(
'Pipeline ID "%s" for callback does not exist.' % pipeline_id)
params = pipeline_record.params
real_class_path = params['class_path']
try:
pipeline_func_class = mr_util.for_name(real_class_path)
except ImportError, e:
raise _CallbackTaskError(
'Cannot load class named "%s" for pipeline ID "%s".'
% (real_class_path, pipeline_id))
if 'HTTP_X_APPENGINE_TASKNAME' not in self.request.environ:
if pipeline_func_class.public_callbacks:
pass
elif pipeline_func_class.admin_callbacks:
if not users.is_current_user_admin():
raise _CallbackTaskError(
'Unauthorized callback for admin-only pipeline ID "%s"'
% pipeline_id)
else:
raise _CallbackTaskError(
'External callback for internal-only pipeline ID "%s"'
% pipeline_id)
kwargs = {}
for key in self.request.arguments():
if key != 'pipeline_id':
kwargs[str(key)] = self.request.get(key)
def perform_callback():
stage = pipeline_func_class.from_id(pipeline_id)
if stage is None:
raise _CallbackTaskError(
'Pipeline ID "%s" deleted during callback' % pipeline_id)
return stage._callback_internal(kwargs)
# callback_xg_transaction is a 3-valued setting (None=no trans,
# False=1-eg-trans, True=xg-trans)
if pipeline_func_class._callback_xg_transaction is not None:
transaction_options = db.create_transaction_options(
xg=pipeline_func_class._callback_xg_transaction)
callback_result = db.run_in_transaction_options(transaction_options,
perform_callback)
else:
callback_result = perform_callback()
if callback_result is not None:
status_code, content_type, content = callback_result
self.response.set_status(status_code)
self.response.headers['Content-Type'] = content_type
self.response.out.write(content) | Runs the callback for the pipeline specified in the request.
Raises:
_CallbackTaskError if something was wrong with the request parameters. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/pipeline.py#L2803-L2867 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/__init__.py | _fix_path | def _fix_path():
"""Finds the google_appengine directory and fixes Python imports to use it."""
import os
import sys
all_paths = os.environ.get('PYTHONPATH').split(os.pathsep)
for path_dir in all_paths:
dev_appserver_path = os.path.join(path_dir, 'dev_appserver.py')
if os.path.exists(dev_appserver_path):
logging.debug('Found appengine SDK on path!')
google_appengine = os.path.dirname(os.path.realpath(dev_appserver_path))
sys.path.append(google_appengine)
# Use the next import will fix up sys.path even further to bring in
# any dependent lib directories that the SDK needs.
dev_appserver = __import__('dev_appserver')
sys.path.extend(dev_appserver.EXTRA_PATHS)
return | python | def _fix_path():
"""Finds the google_appengine directory and fixes Python imports to use it."""
import os
import sys
all_paths = os.environ.get('PYTHONPATH').split(os.pathsep)
for path_dir in all_paths:
dev_appserver_path = os.path.join(path_dir, 'dev_appserver.py')
if os.path.exists(dev_appserver_path):
logging.debug('Found appengine SDK on path!')
google_appengine = os.path.dirname(os.path.realpath(dev_appserver_path))
sys.path.append(google_appengine)
# Use the next import will fix up sys.path even further to bring in
# any dependent lib directories that the SDK needs.
dev_appserver = __import__('dev_appserver')
sys.path.extend(dev_appserver.EXTRA_PATHS)
return | Finds the google_appengine directory and fixes Python imports to use it. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/__init__.py#L22-L37 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/models.py | _PipelineRecord.params | def params(self):
"""Returns the dictionary of parameters for this Pipeline."""
if hasattr(self, '_params_decoded'):
return self._params_decoded
if self.params_blob is not None:
value_encoded = self.params_blob.open().read()
else:
value_encoded = self.params_text
value = json.loads(value_encoded, cls=util.JsonDecoder)
if isinstance(value, dict):
kwargs = value.get('kwargs')
if kwargs:
adjusted_kwargs = {}
for arg_key, arg_value in kwargs.iteritems():
# Python only allows non-unicode strings as keyword arguments.
adjusted_kwargs[str(arg_key)] = arg_value
value['kwargs'] = adjusted_kwargs
self._params_decoded = value
return self._params_decoded | python | def params(self):
"""Returns the dictionary of parameters for this Pipeline."""
if hasattr(self, '_params_decoded'):
return self._params_decoded
if self.params_blob is not None:
value_encoded = self.params_blob.open().read()
else:
value_encoded = self.params_text
value = json.loads(value_encoded, cls=util.JsonDecoder)
if isinstance(value, dict):
kwargs = value.get('kwargs')
if kwargs:
adjusted_kwargs = {}
for arg_key, arg_value in kwargs.iteritems():
# Python only allows non-unicode strings as keyword arguments.
adjusted_kwargs[str(arg_key)] = arg_value
value['kwargs'] = adjusted_kwargs
self._params_decoded = value
return self._params_decoded | Returns the dictionary of parameters for this Pipeline. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/models.py#L96-L117 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/models.py | _SlotRecord.value | def value(self):
"""Returns the value of this Slot."""
if hasattr(self, '_value_decoded'):
return self._value_decoded
if self.value_blob is not None:
encoded_value = self.value_blob.open().read()
else:
encoded_value = self.value_text
self._value_decoded = json.loads(encoded_value, cls=util.JsonDecoder)
return self._value_decoded | python | def value(self):
"""Returns the value of this Slot."""
if hasattr(self, '_value_decoded'):
return self._value_decoded
if self.value_blob is not None:
encoded_value = self.value_blob.open().read()
else:
encoded_value = self.value_text
self._value_decoded = json.loads(encoded_value, cls=util.JsonDecoder)
return self._value_decoded | Returns the value of this Slot. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/models.py#L156-L167 |
GoogleCloudPlatform/appengine-pipelines | python/src/pipeline/models.py | _BarrierIndex.to_barrier_key | def to_barrier_key(cls, barrier_index_key):
"""Converts a _BarrierIndex key to a _BarrierRecord key.
Args:
barrier_index_key: db.Key for a _BarrierIndex entity.
Returns:
db.Key for the corresponding _BarrierRecord entity.
"""
barrier_index_path = barrier_index_key.to_path()
# Pick out the items from the _BarrierIndex key path that we need to
# construct the _BarrierRecord key path.
(pipeline_kind, dependent_pipeline_id,
unused_kind, purpose) = barrier_index_path[-4:]
barrier_record_path = (
pipeline_kind, dependent_pipeline_id,
_BarrierRecord.kind(), purpose)
return db.Key.from_path(*barrier_record_path) | python | def to_barrier_key(cls, barrier_index_key):
"""Converts a _BarrierIndex key to a _BarrierRecord key.
Args:
barrier_index_key: db.Key for a _BarrierIndex entity.
Returns:
db.Key for the corresponding _BarrierRecord entity.
"""
barrier_index_path = barrier_index_key.to_path()
# Pick out the items from the _BarrierIndex key path that we need to
# construct the _BarrierRecord key path.
(pipeline_kind, dependent_pipeline_id,
unused_kind, purpose) = barrier_index_path[-4:]
barrier_record_path = (
pipeline_kind, dependent_pipeline_id,
_BarrierRecord.kind(), purpose)
return db.Key.from_path(*barrier_record_path) | Converts a _BarrierIndex key to a _BarrierRecord key.
Args:
barrier_index_key: db.Key for a _BarrierIndex entity.
Returns:
db.Key for the corresponding _BarrierRecord entity. | https://github.com/GoogleCloudPlatform/appengine-pipelines/blob/277394648dac3e8214677af898935d07399ac8e1/python/src/pipeline/models.py#L251-L271 |
bcbnz/pylabels | labels/sheet.py | Sheet.partial_page | def partial_page(self, page, used_labels):
"""Allows a page to be marked as already partially used so you can
generate a PDF to print on the remaining labels.
Parameters
----------
page: positive integer
The page number to mark as partially used. The page must not have
already been started, i.e., for page 1 this must be called before
any labels have been started, for page 2 this must be called before
the first page is full and so on.
used_labels: iterable
An iterable of (row, column) pairs marking which labels have been
used already. The rows and columns must be within the bounds of the
sheet.
"""
# Check the page number is valid.
if page <= self.page_count:
raise ValueError("Page {0:d} has already started, cannot mark used labels now.".format(page))
# Add these to any existing labels marked as used.
used = self._used.get(page, set())
for row, column in used_labels:
# Check the index is valid.
if row < 1 or row > self.specs.rows:
raise IndexError("Invalid row number: {0:d}.".format(row))
if column < 1 or column > self.specs.columns:
raise IndexError("Invalid column number: {0:d}.".format(column))
# Add it.
used.add((int(row), int(column)))
# Save the details.
self._used[page] = used | python | def partial_page(self, page, used_labels):
"""Allows a page to be marked as already partially used so you can
generate a PDF to print on the remaining labels.
Parameters
----------
page: positive integer
The page number to mark as partially used. The page must not have
already been started, i.e., for page 1 this must be called before
any labels have been started, for page 2 this must be called before
the first page is full and so on.
used_labels: iterable
An iterable of (row, column) pairs marking which labels have been
used already. The rows and columns must be within the bounds of the
sheet.
"""
# Check the page number is valid.
if page <= self.page_count:
raise ValueError("Page {0:d} has already started, cannot mark used labels now.".format(page))
# Add these to any existing labels marked as used.
used = self._used.get(page, set())
for row, column in used_labels:
# Check the index is valid.
if row < 1 or row > self.specs.rows:
raise IndexError("Invalid row number: {0:d}.".format(row))
if column < 1 or column > self.specs.columns:
raise IndexError("Invalid column number: {0:d}.".format(column))
# Add it.
used.add((int(row), int(column)))
# Save the details.
self._used[page] = used | Allows a page to be marked as already partially used so you can
generate a PDF to print on the remaining labels.
Parameters
----------
page: positive integer
The page number to mark as partially used. The page must not have
already been started, i.e., for page 1 this must be called before
any labels have been started, for page 2 this must be called before
the first page is full and so on.
used_labels: iterable
An iterable of (row, column) pairs marking which labels have been
used already. The rows and columns must be within the bounds of the
sheet. | https://github.com/bcbnz/pylabels/blob/ecdb4ca48061d8f1dc0fcfe2d55ce2b89e0e5ec6/labels/sheet.py#L205-L239 |
bcbnz/pylabels | labels/sheet.py | Sheet._new_page | def _new_page(self):
"""Helper function to start a new page. Not intended for external use.
"""
self._current_page = Drawing(*self._pagesize)
if self._bgimage:
self._current_page.add(self._bgimage)
self._pages.append(self._current_page)
self.page_count += 1
self._position = [1, 0] | python | def _new_page(self):
"""Helper function to start a new page. Not intended for external use.
"""
self._current_page = Drawing(*self._pagesize)
if self._bgimage:
self._current_page.add(self._bgimage)
self._pages.append(self._current_page)
self.page_count += 1
self._position = [1, 0] | Helper function to start a new page. Not intended for external use. | https://github.com/bcbnz/pylabels/blob/ecdb4ca48061d8f1dc0fcfe2d55ce2b89e0e5ec6/labels/sheet.py#L241-L250 |
bcbnz/pylabels | labels/sheet.py | Sheet._next_label | def _next_label(self):
"""Helper method to move to the next label. Not intended for external use.
This does not increment the label_count attribute as the next label may
not be usable (it may have been marked as missing through
partial_pages). See _next_unused_label for generally more useful method.
"""
# Special case for the very first label.
if self.page_count == 0:
self._new_page()
# Filled up a page.
elif self._position == self._numlabels:
self._new_page()
# Filled up a row.
elif self._position[1] == self.specs.columns:
self._position[0] += 1
self._position[1] = 0
# Move to the next column.
self._position[1] += 1 | python | def _next_label(self):
"""Helper method to move to the next label. Not intended for external use.
This does not increment the label_count attribute as the next label may
not be usable (it may have been marked as missing through
partial_pages). See _next_unused_label for generally more useful method.
"""
# Special case for the very first label.
if self.page_count == 0:
self._new_page()
# Filled up a page.
elif self._position == self._numlabels:
self._new_page()
# Filled up a row.
elif self._position[1] == self.specs.columns:
self._position[0] += 1
self._position[1] = 0
# Move to the next column.
self._position[1] += 1 | Helper method to move to the next label. Not intended for external use.
This does not increment the label_count attribute as the next label may
not be usable (it may have been marked as missing through
partial_pages). See _next_unused_label for generally more useful method. | https://github.com/bcbnz/pylabels/blob/ecdb4ca48061d8f1dc0fcfe2d55ce2b89e0e5ec6/labels/sheet.py#L252-L274 |
bcbnz/pylabels | labels/sheet.py | Sheet._next_unused_label | def _next_unused_label(self):
"""Helper method to move to the next unused label. Not intended for external use.
This method will shade in any missing labels if desired, and will
increment the label_count attribute once a suitable label position has
been found.
"""
self._next_label()
# This label may be missing.
if self.page_count in self._used:
# Keep try while the label is missing.
missing = self._used.get(self.page_count, set())
while tuple(self._position) in missing:
# Throw the missing information away now we have used it. This
# allows the _shade_remaining_missing method to work.
missing.discard(tuple(self._position))
# Shade the missing label if desired.
if self.shade_missing:
self._shade_missing_label()
# Try our luck with the next label.
self._next_label()
missing = self._used.get(self.page_count, set())
# Increment the count now we have found a suitable position.
self.label_count += 1 | python | def _next_unused_label(self):
"""Helper method to move to the next unused label. Not intended for external use.
This method will shade in any missing labels if desired, and will
increment the label_count attribute once a suitable label position has
been found.
"""
self._next_label()
# This label may be missing.
if self.page_count in self._used:
# Keep try while the label is missing.
missing = self._used.get(self.page_count, set())
while tuple(self._position) in missing:
# Throw the missing information away now we have used it. This
# allows the _shade_remaining_missing method to work.
missing.discard(tuple(self._position))
# Shade the missing label if desired.
if self.shade_missing:
self._shade_missing_label()
# Try our luck with the next label.
self._next_label()
missing = self._used.get(self.page_count, set())
# Increment the count now we have found a suitable position.
self.label_count += 1 | Helper method to move to the next unused label. Not intended for external use.
This method will shade in any missing labels if desired, and will
increment the label_count attribute once a suitable label position has
been found. | https://github.com/bcbnz/pylabels/blob/ecdb4ca48061d8f1dc0fcfe2d55ce2b89e0e5ec6/labels/sheet.py#L276-L304 |
bcbnz/pylabels | labels/sheet.py | Sheet._calculate_edges | def _calculate_edges(self):
"""Calculate edges of the current label. Not intended for external use.
"""
# Calculate the left edge of the label.
left = self.specs.left_margin
left += (self.specs.label_width * (self._position[1] - 1))
if self.specs.column_gap:
left += (self.specs.column_gap * (self._position[1] - 1))
left *= mm
# And the bottom.
bottom = self.specs.sheet_height - self.specs.top_margin
bottom -= (self.specs.label_height * self._position[0])
if self.specs.row_gap:
bottom -= (self.specs.row_gap * (self._position[0] - 1))
bottom *= mm
# Done.
return float(left), float(bottom) | python | def _calculate_edges(self):
"""Calculate edges of the current label. Not intended for external use.
"""
# Calculate the left edge of the label.
left = self.specs.left_margin
left += (self.specs.label_width * (self._position[1] - 1))
if self.specs.column_gap:
left += (self.specs.column_gap * (self._position[1] - 1))
left *= mm
# And the bottom.
bottom = self.specs.sheet_height - self.specs.top_margin
bottom -= (self.specs.label_height * self._position[0])
if self.specs.row_gap:
bottom -= (self.specs.row_gap * (self._position[0] - 1))
bottom *= mm
# Done.
return float(left), float(bottom) | Calculate edges of the current label. Not intended for external use. | https://github.com/bcbnz/pylabels/blob/ecdb4ca48061d8f1dc0fcfe2d55ce2b89e0e5ec6/labels/sheet.py#L306-L326 |
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