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bradmontgomery/django-blargg | blargg/models.py | TagManager.create_tags | def create_tags(self, entry):
"""Inspects an ``Entry`` instance, and builds associates ``Tag``
objects based on the values in the ``Entry``'s ``tag_string``."""
tag_list = [t.lower().strip() for t in entry.tag_string.split(',')]
for t in tag_list:
tag, created = self.get_or_create(name=t)
entry.tags.add(tag) | python | def create_tags(self, entry):
"""Inspects an ``Entry`` instance, and builds associates ``Tag``
objects based on the values in the ``Entry``'s ``tag_string``."""
tag_list = [t.lower().strip() for t in entry.tag_string.split(',')]
for t in tag_list:
tag, created = self.get_or_create(name=t)
entry.tags.add(tag) | [
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| 5d683e04723889a0d1c6d6cf1a67a3d431a2e617 | https://github.com/bradmontgomery/django-blargg/blob/5d683e04723889a0d1c6d6cf1a67a3d431a2e617/blargg/models.py#L33-L39 | train |
bradmontgomery/django-blargg | blargg/models.py | Entry._create_date_slug | def _create_date_slug(self):
"""Prefixes the slug with the ``published_on`` date."""
if not self.pk:
# haven't saved this yet, so use today's date
d = utc_now()
elif self.published and self.published_on:
# use the actual published on date
d = self.published_on
elif self.updated_on:
# default to the last-updated date
d = self.updated_on
self.date_slug = u"{0}/{1}".format(d.strftime("%Y/%m/%d"), self.slug) | python | def _create_date_slug(self):
"""Prefixes the slug with the ``published_on`` date."""
if not self.pk:
# haven't saved this yet, so use today's date
d = utc_now()
elif self.published and self.published_on:
# use the actual published on date
d = self.published_on
elif self.updated_on:
# default to the last-updated date
d = self.updated_on
self.date_slug = u"{0}/{1}".format(d.strftime("%Y/%m/%d"), self.slug) | [
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| 5d683e04723889a0d1c6d6cf1a67a3d431a2e617 | https://github.com/bradmontgomery/django-blargg/blob/5d683e04723889a0d1c6d6cf1a67a3d431a2e617/blargg/models.py#L126-L137 | train |
bradmontgomery/django-blargg | blargg/models.py | Entry._render_content | def _render_content(self):
"""Renders the content according to the ``content_format``."""
if self.content_format == "rst" and docutils_publish is not None:
doc_parts = docutils_publish(
source=self.raw_content,
writer_name="html4css1"
)
self.rendered_content = doc_parts['fragment']
elif self.content_format == "rs" and docutils_publish is None:
raise RuntimeError("Install docutils to pubilsh reStructuredText")
elif self.content_format == "md" and markdown is not None:
self.rendered_content = markdown(self.raw_content)
elif self.content_format == "md" and markdown is None:
raise RuntimeError("Install Markdown to pubilsh markdown")
else: # Assume we've got html
self.rendered_content = self.raw_content | python | def _render_content(self):
"""Renders the content according to the ``content_format``."""
if self.content_format == "rst" and docutils_publish is not None:
doc_parts = docutils_publish(
source=self.raw_content,
writer_name="html4css1"
)
self.rendered_content = doc_parts['fragment']
elif self.content_format == "rs" and docutils_publish is None:
raise RuntimeError("Install docutils to pubilsh reStructuredText")
elif self.content_format == "md" and markdown is not None:
self.rendered_content = markdown(self.raw_content)
elif self.content_format == "md" and markdown is None:
raise RuntimeError("Install Markdown to pubilsh markdown")
else: # Assume we've got html
self.rendered_content = self.raw_content | [
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| 5d683e04723889a0d1c6d6cf1a67a3d431a2e617 | https://github.com/bradmontgomery/django-blargg/blob/5d683e04723889a0d1c6d6cf1a67a3d431a2e617/blargg/models.py#L139-L154 | train |
bradmontgomery/django-blargg | blargg/models.py | Entry.save | def save(self, *args, **kwargs):
"""Auto-generate a slug from the name."""
self._create_slug()
self._create_date_slug()
self._render_content()
# Call ``_set_published`` the *first* time this Entry is published.
# NOTE: if this is unpublished, and then republished, this method won't
# get called; e.g. the date won't get changed and the
# ``entry_published`` signal won't get re-sent.
send_published_signal = False
if self.published and self.published_on is None:
send_published_signal = self._set_published()
super(Entry, self).save(*args, **kwargs)
# We need an ID before we can send this signal.
if send_published_signal:
entry_published.send(sender=self, entry=self) | python | def save(self, *args, **kwargs):
"""Auto-generate a slug from the name."""
self._create_slug()
self._create_date_slug()
self._render_content()
# Call ``_set_published`` the *first* time this Entry is published.
# NOTE: if this is unpublished, and then republished, this method won't
# get called; e.g. the date won't get changed and the
# ``entry_published`` signal won't get re-sent.
send_published_signal = False
if self.published and self.published_on is None:
send_published_signal = self._set_published()
super(Entry, self).save(*args, **kwargs)
# We need an ID before we can send this signal.
if send_published_signal:
entry_published.send(sender=self, entry=self) | [
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| 5d683e04723889a0d1c6d6cf1a67a3d431a2e617 | https://github.com/bradmontgomery/django-blargg/blob/5d683e04723889a0d1c6d6cf1a67a3d431a2e617/blargg/models.py#L163-L181 | train |
bradmontgomery/django-blargg | blargg/models.py | Entry.get_absolute_url_with_date | def get_absolute_url_with_date(self):
"""URL based on the entry's date & slug."""
pub_date = self.published_on
if pub_date and settings.USE_TZ:
# If TZ is enabled, convert all of these dates from UTC to whatever
# the project's timezone is set as. Ideally, we'd pull this form
# some user settings, but the *canonical* publish time is that of
# the author (asssuming author == owner of this project).
pub_date = make_naive(pub_date, pytz.utc) # Make naive
pub_date = pytz.timezone(settings.TIME_ZONE).localize(pub_date)
if pub_date:
args = [
pub_date.strftime("%Y"),
pub_date.strftime("%m"),
pub_date.strftime("%d"),
self.slug
]
else:
args = [self.slug]
return reverse('blargg:entry_detail', args=args) | python | def get_absolute_url_with_date(self):
"""URL based on the entry's date & slug."""
pub_date = self.published_on
if pub_date and settings.USE_TZ:
# If TZ is enabled, convert all of these dates from UTC to whatever
# the project's timezone is set as. Ideally, we'd pull this form
# some user settings, but the *canonical* publish time is that of
# the author (asssuming author == owner of this project).
pub_date = make_naive(pub_date, pytz.utc) # Make naive
pub_date = pytz.timezone(settings.TIME_ZONE).localize(pub_date)
if pub_date:
args = [
pub_date.strftime("%Y"),
pub_date.strftime("%m"),
pub_date.strftime("%d"),
self.slug
]
else:
args = [self.slug]
return reverse('blargg:entry_detail', args=args) | [
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| 5d683e04723889a0d1c6d6cf1a67a3d431a2e617 | https://github.com/bradmontgomery/django-blargg/blob/5d683e04723889a0d1c6d6cf1a67a3d431a2e617/blargg/models.py#L187-L207 | train |
bradmontgomery/django-blargg | blargg/models.py | Entry.tag_list | def tag_list(self):
"""Return a plain python list containing all of this Entry's tags."""
tags = [tag.strip() for tag in self.tag_string.split(",")]
return sorted(filter(None, tags)) | python | def tag_list(self):
"""Return a plain python list containing all of this Entry's tags."""
tags = [tag.strip() for tag in self.tag_string.split(",")]
return sorted(filter(None, tags)) | [
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| 5d683e04723889a0d1c6d6cf1a67a3d431a2e617 | https://github.com/bradmontgomery/django-blargg/blob/5d683e04723889a0d1c6d6cf1a67a3d431a2e617/blargg/models.py#L220-L223 | train |
striglia/stockfighter | stockfighter/stockfighter.py | Stockfighter.heartbeat | def heartbeat(self):
"""Check The API Is Up.
https://starfighter.readme.io/docs/heartbeat
"""
url = urljoin(self.base_url, 'heartbeat')
return self.session.get(url).json()['ok'] | python | def heartbeat(self):
"""Check The API Is Up.
https://starfighter.readme.io/docs/heartbeat
"""
url = urljoin(self.base_url, 'heartbeat')
return self.session.get(url).json()['ok'] | [
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| df908f5919d6f861601cd00c906a049d04253d47 | https://github.com/striglia/stockfighter/blob/df908f5919d6f861601cd00c906a049d04253d47/stockfighter/stockfighter.py#L24-L30 | train |
striglia/stockfighter | stockfighter/stockfighter.py | Stockfighter.venue_healthcheck | def venue_healthcheck(self):
"""Check A Venue Is Up.
https://starfighter.readme.io/docs/venue-healthcheck
"""
url = urljoin(self.base_url, 'venues/TESTEX/heartbeat')
return self.session.get(url).json()['ok'] | python | def venue_healthcheck(self):
"""Check A Venue Is Up.
https://starfighter.readme.io/docs/venue-healthcheck
"""
url = urljoin(self.base_url, 'venues/TESTEX/heartbeat')
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| df908f5919d6f861601cd00c906a049d04253d47 | https://github.com/striglia/stockfighter/blob/df908f5919d6f861601cd00c906a049d04253d47/stockfighter/stockfighter.py#L32-L38 | train |
striglia/stockfighter | stockfighter/stockfighter.py | Stockfighter.venue_stocks | def venue_stocks(self):
"""List the stocks available for trading on the venue.
https://starfighter.readme.io/docs/list-stocks-on-venue
"""
url = urljoin(self.base_url, 'venues/{0}/stocks'.format(self.venue))
return self.session.get(url).json() | python | def venue_stocks(self):
"""List the stocks available for trading on the venue.
https://starfighter.readme.io/docs/list-stocks-on-venue
"""
url = urljoin(self.base_url, 'venues/{0}/stocks'.format(self.venue))
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| df908f5919d6f861601cd00c906a049d04253d47 | https://github.com/striglia/stockfighter/blob/df908f5919d6f861601cd00c906a049d04253d47/stockfighter/stockfighter.py#L40-L46 | train |
striglia/stockfighter | stockfighter/stockfighter.py | Stockfighter.orderbook_for_stock | def orderbook_for_stock(self, stock):
"""Get the orderbook for a particular stock.
https://starfighter.readme.io/docs/get-orderbook-for-stock
"""
url_fragment = 'venues/{venue}/stocks/{stock}'.format(
venue=self.venue,
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)
url = urljoin(self.base_url, url_fragment)
return self.session.get(url).json() | python | def orderbook_for_stock(self, stock):
"""Get the orderbook for a particular stock.
https://starfighter.readme.io/docs/get-orderbook-for-stock
"""
url_fragment = 'venues/{venue}/stocks/{stock}'.format(
venue=self.venue,
stock=stock,
)
url = urljoin(self.base_url, url_fragment)
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| df908f5919d6f861601cd00c906a049d04253d47 | https://github.com/striglia/stockfighter/blob/df908f5919d6f861601cd00c906a049d04253d47/stockfighter/stockfighter.py#L48-L58 | train |
striglia/stockfighter | stockfighter/stockfighter.py | Stockfighter.place_new_order | def place_new_order(self, stock, price, qty, direction, order_type):
"""Place an order for a stock.
https://starfighter.readme.io/docs/place-new-order
"""
url_fragment = 'venues/{venue}/stocks/{stock}/orders'.format(
venue=self.venue,
stock=stock,
)
data = {
"stock": stock,
"price": price,
"venue": self.venue,
"account": self.account,
"qty": qty,
"direction": direction,
"orderType": order_type,
}
url = urljoin(self.base_url, url_fragment)
resp = self.session.post(url, json=data)
return resp.json() | python | def place_new_order(self, stock, price, qty, direction, order_type):
"""Place an order for a stock.
https://starfighter.readme.io/docs/place-new-order
"""
url_fragment = 'venues/{venue}/stocks/{stock}/orders'.format(
venue=self.venue,
stock=stock,
)
data = {
"stock": stock,
"price": price,
"venue": self.venue,
"account": self.account,
"qty": qty,
"direction": direction,
"orderType": order_type,
}
url = urljoin(self.base_url, url_fragment)
resp = self.session.post(url, json=data)
return resp.json() | [
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| df908f5919d6f861601cd00c906a049d04253d47 | https://github.com/striglia/stockfighter/blob/df908f5919d6f861601cd00c906a049d04253d47/stockfighter/stockfighter.py#L60-L80 | train |
striglia/stockfighter | stockfighter/stockfighter.py | Stockfighter.status_for_order | def status_for_order(self, order_id, stock):
"""Status For An Existing Order
https://starfighter.readme.io/docs/status-for-an-existing-order
"""
url_fragment = 'venues/{venue}/stocks/{stock}/orders/{order_id}'.format(
venue=self.venue,
stock=stock,
order_id=order_id,
)
url = urljoin(self.base_url, url_fragment)
return self.session.get(url).json() | python | def status_for_order(self, order_id, stock):
"""Status For An Existing Order
https://starfighter.readme.io/docs/status-for-an-existing-order
"""
url_fragment = 'venues/{venue}/stocks/{stock}/orders/{order_id}'.format(
venue=self.venue,
stock=stock,
order_id=order_id,
)
url = urljoin(self.base_url, url_fragment)
return self.session.get(url).json() | [
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| df908f5919d6f861601cd00c906a049d04253d47 | https://github.com/striglia/stockfighter/blob/df908f5919d6f861601cd00c906a049d04253d47/stockfighter/stockfighter.py#L94-L105 | train |
striglia/stockfighter | stockfighter/stockfighter.py | Stockfighter.cancel_order | def cancel_order(self, order_id, stock):
"""Cancel An Order
https://starfighter.readme.io/docs/cancel-an-order
"""
url_fragment = 'venues/{venue}/stocks/{stock}/orders/{order_id}'.format(
venue=self.venue,
stock=stock,
order_id=order_id,
)
url = urljoin(self.base_url, url_fragment)
return self.session.delete(url).json() | python | def cancel_order(self, order_id, stock):
"""Cancel An Order
https://starfighter.readme.io/docs/cancel-an-order
"""
url_fragment = 'venues/{venue}/stocks/{stock}/orders/{order_id}'.format(
venue=self.venue,
stock=stock,
order_id=order_id,
)
url = urljoin(self.base_url, url_fragment)
return self.session.delete(url).json() | [
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https://starfighter.readme.io/docs/cancel-an-order | [
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| df908f5919d6f861601cd00c906a049d04253d47 | https://github.com/striglia/stockfighter/blob/df908f5919d6f861601cd00c906a049d04253d47/stockfighter/stockfighter.py#L107-L118 | train |
striglia/stockfighter | stockfighter/stockfighter.py | Stockfighter.status_for_all_orders | def status_for_all_orders(self):
"""Status for all orders
https://starfighter.readme.io/docs/status-for-all-orders
"""
url_fragment = 'venues/{venue}/accounts/{account}/orders'.format(
venue=self.venue,
account=self.account,
)
url = urljoin(self.base_url, url_fragment)
return self.session.get(url).json() | python | def status_for_all_orders(self):
"""Status for all orders
https://starfighter.readme.io/docs/status-for-all-orders
"""
url_fragment = 'venues/{venue}/accounts/{account}/orders'.format(
venue=self.venue,
account=self.account,
)
url = urljoin(self.base_url, url_fragment)
return self.session.get(url).json() | [
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| df908f5919d6f861601cd00c906a049d04253d47 | https://github.com/striglia/stockfighter/blob/df908f5919d6f861601cd00c906a049d04253d47/stockfighter/stockfighter.py#L120-L130 | train |
striglia/stockfighter | stockfighter/stockfighter.py | Stockfighter.status_for_all_orders_in_a_stock | def status_for_all_orders_in_a_stock(self, stock):
"""Status for all orders in a stock
https://starfighter.readme.io/docs/status-for-all-orders-in-a-stock
"""
url_fragment = 'venues/{venue}/accounts/{account}/stocks/{stock}/orders'.format(
stock=stock,
venue=self.venue,
account=self.account,
)
url = urljoin(self.base_url, url_fragment)
return self.session.get(url).json() | python | def status_for_all_orders_in_a_stock(self, stock):
"""Status for all orders in a stock
https://starfighter.readme.io/docs/status-for-all-orders-in-a-stock
"""
url_fragment = 'venues/{venue}/accounts/{account}/stocks/{stock}/orders'.format(
stock=stock,
venue=self.venue,
account=self.account,
)
url = urljoin(self.base_url, url_fragment)
return self.session.get(url).json() | [
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| df908f5919d6f861601cd00c906a049d04253d47 | https://github.com/striglia/stockfighter/blob/df908f5919d6f861601cd00c906a049d04253d47/stockfighter/stockfighter.py#L132-L143 | train |
tweekmonster/moult | moult/frameworks/django.py | scan_django_settings | def scan_django_settings(values, imports):
'''Recursively scans Django settings for values that appear to be
imported modules.
'''
if isinstance(values, (str, bytes)):
if utils.is_import_str(values):
imports.add(values)
elif isinstance(values, dict):
for k, v in values.items():
scan_django_settings(k, imports)
scan_django_settings(v, imports)
elif hasattr(values, '__file__') and getattr(values, '__file__'):
imp, _ = utils.import_path_from_file(getattr(values, '__file__'))
imports.add(imp)
elif hasattr(values, '__iter__'):
for item in values:
scan_django_settings(item, imports) | python | def scan_django_settings(values, imports):
'''Recursively scans Django settings for values that appear to be
imported modules.
'''
if isinstance(values, (str, bytes)):
if utils.is_import_str(values):
imports.add(values)
elif isinstance(values, dict):
for k, v in values.items():
scan_django_settings(k, imports)
scan_django_settings(v, imports)
elif hasattr(values, '__file__') and getattr(values, '__file__'):
imp, _ = utils.import_path_from_file(getattr(values, '__file__'))
imports.add(imp)
elif hasattr(values, '__iter__'):
for item in values:
scan_django_settings(item, imports) | [
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| 38d3a3b9002336219897ebe263ca1d8dcadbecf5 | https://github.com/tweekmonster/moult/blob/38d3a3b9002336219897ebe263ca1d8dcadbecf5/moult/frameworks/django.py#L21-L37 | train |
tweekmonster/moult | moult/frameworks/django.py | handle_django_settings | def handle_django_settings(filename):
'''Attempts to load a Django project and get package dependencies from
settings.
Tested using Django 1.4 and 1.8. Not sure if some nuances are missed in
the other versions.
'''
old_sys_path = sys.path[:]
dirpath = os.path.dirname(filename)
project = os.path.basename(dirpath)
cwd = os.getcwd()
project_path = os.path.normpath(os.path.join(dirpath, '..'))
if project_path not in sys.path:
sys.path.insert(0, project_path)
os.chdir(project_path)
project_settings = '{}.settings'.format(project)
os.environ['DJANGO_SETTINGS_MODULE'] = project_settings
try:
import django
# Sanity
django.setup = lambda: False
except ImportError:
log.error('Found Django settings, but Django is not installed.')
return
log.warn('Loading Django Settings (Using {}): {}'
.format(django.get_version(), filename))
from django.conf import LazySettings
installed_apps = set()
settings_imports = set()
try:
settings = LazySettings()
settings._setup()
for k, v in vars(settings._wrapped).items():
if k not in _excluded_settings and re.match(r'^[A-Z_]+$', k):
# log.debug('Scanning Django setting: %s', k)
scan_django_settings(v, settings_imports)
# Manually scan INSTALLED_APPS since the broad scan won't include
# strings without a period in it .
for app in getattr(settings, 'INSTALLED_APPS', []):
if hasattr(app, '__file__') and getattr(app, '__file__'):
imp, _ = utils.import_path_from_file(getattr(app, '__file__'))
installed_apps.add(imp)
else:
installed_apps.add(app)
except Exception as e:
log.error('Could not load Django settings: %s', e)
log.debug('', exc_info=True)
return
if not installed_apps or not settings_imports:
log.error('Got empty settings values from Django settings.')
try:
from django.apps.registry import apps, Apps, AppRegistryNotReady
# Django doesn't like it when the initial instance of `apps` is reused,
# but it has to be populated before other instances can be created.
if not apps.apps_ready:
apps.populate(installed_apps)
else:
apps = Apps(installed_apps)
start = time.time()
while True:
try:
for app in apps.get_app_configs():
installed_apps.add(app.name)
except AppRegistryNotReady:
if time.time() - start > 10:
raise Exception('Bail out of waiting for Django')
log.debug('Waiting for apps to load...')
continue
break
except Exception as e:
log.debug('Could not use AppConfig: {}'.format(e))
# Restore before sub scans can occur
sys.path[:] = old_sys_path
os.chdir(cwd)
for item in settings_imports:
need_scan = item.startswith(_filescan_modules)
yield ('django', item, project_path if need_scan else None)
for app in installed_apps:
need_scan = app.startswith(project)
yield ('django', app, project_path if need_scan else None) | python | def handle_django_settings(filename):
'''Attempts to load a Django project and get package dependencies from
settings.
Tested using Django 1.4 and 1.8. Not sure if some nuances are missed in
the other versions.
'''
old_sys_path = sys.path[:]
dirpath = os.path.dirname(filename)
project = os.path.basename(dirpath)
cwd = os.getcwd()
project_path = os.path.normpath(os.path.join(dirpath, '..'))
if project_path not in sys.path:
sys.path.insert(0, project_path)
os.chdir(project_path)
project_settings = '{}.settings'.format(project)
os.environ['DJANGO_SETTINGS_MODULE'] = project_settings
try:
import django
# Sanity
django.setup = lambda: False
except ImportError:
log.error('Found Django settings, but Django is not installed.')
return
log.warn('Loading Django Settings (Using {}): {}'
.format(django.get_version(), filename))
from django.conf import LazySettings
installed_apps = set()
settings_imports = set()
try:
settings = LazySettings()
settings._setup()
for k, v in vars(settings._wrapped).items():
if k not in _excluded_settings and re.match(r'^[A-Z_]+$', k):
# log.debug('Scanning Django setting: %s', k)
scan_django_settings(v, settings_imports)
# Manually scan INSTALLED_APPS since the broad scan won't include
# strings without a period in it .
for app in getattr(settings, 'INSTALLED_APPS', []):
if hasattr(app, '__file__') and getattr(app, '__file__'):
imp, _ = utils.import_path_from_file(getattr(app, '__file__'))
installed_apps.add(imp)
else:
installed_apps.add(app)
except Exception as e:
log.error('Could not load Django settings: %s', e)
log.debug('', exc_info=True)
return
if not installed_apps or not settings_imports:
log.error('Got empty settings values from Django settings.')
try:
from django.apps.registry import apps, Apps, AppRegistryNotReady
# Django doesn't like it when the initial instance of `apps` is reused,
# but it has to be populated before other instances can be created.
if not apps.apps_ready:
apps.populate(installed_apps)
else:
apps = Apps(installed_apps)
start = time.time()
while True:
try:
for app in apps.get_app_configs():
installed_apps.add(app.name)
except AppRegistryNotReady:
if time.time() - start > 10:
raise Exception('Bail out of waiting for Django')
log.debug('Waiting for apps to load...')
continue
break
except Exception as e:
log.debug('Could not use AppConfig: {}'.format(e))
# Restore before sub scans can occur
sys.path[:] = old_sys_path
os.chdir(cwd)
for item in settings_imports:
need_scan = item.startswith(_filescan_modules)
yield ('django', item, project_path if need_scan else None)
for app in installed_apps:
need_scan = app.startswith(project)
yield ('django', app, project_path if need_scan else None) | [
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Tested using Django 1.4 and 1.8. Not sure if some nuances are missed in
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| 38d3a3b9002336219897ebe263ca1d8dcadbecf5 | https://github.com/tweekmonster/moult/blob/38d3a3b9002336219897ebe263ca1d8dcadbecf5/moult/frameworks/django.py#L40-L132 | train |
Dullage/starlingbank | starlingbank/__init__.py | _url | def _url(endpoint: str, sandbox: bool=False) -> str:
"""Build a URL from the API's base URLs."""
if sandbox is True:
url = BASE_URL_SANDBOX
else:
url = BASE_URL
return "{0}{1}".format(url, endpoint) | python | def _url(endpoint: str, sandbox: bool=False) -> str:
"""Build a URL from the API's base URLs."""
if sandbox is True:
url = BASE_URL_SANDBOX
else:
url = BASE_URL
return "{0}{1}".format(url, endpoint) | [
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| 9495456980d5d6d85c4e999a17dc69481067af09 | https://github.com/Dullage/starlingbank/blob/9495456980d5d6d85c4e999a17dc69481067af09/starlingbank/__init__.py#L12-L18 | train |
Dullage/starlingbank | starlingbank/__init__.py | SavingsGoal.update | def update(self, goal: Dict=None) -> None:
"""Update a single savings goals data."""
if goal is None:
endpoint = "/account/{0}/savings-goals/{1}".format(
self._account_uid,
self.uid
)
response = get(
_url(endpoint, self._sandbox),
headers=self._auth_headers
)
response.raise_for_status()
goal = response.json()
self.uid = goal.get('savingsGoalUid')
self.name = goal.get('name')
target = goal.get('target', {})
self.target_currency = target.get('currency')
self.target_minor_units = target.get('minorUnits')
total_saved = goal.get('totalSaved', {})
self.total_saved_currency = total_saved.get('currency')
self.total_saved_minor_units = total_saved.get('minorUnits') | python | def update(self, goal: Dict=None) -> None:
"""Update a single savings goals data."""
if goal is None:
endpoint = "/account/{0}/savings-goals/{1}".format(
self._account_uid,
self.uid
)
response = get(
_url(endpoint, self._sandbox),
headers=self._auth_headers
)
response.raise_for_status()
goal = response.json()
self.uid = goal.get('savingsGoalUid')
self.name = goal.get('name')
target = goal.get('target', {})
self.target_currency = target.get('currency')
self.target_minor_units = target.get('minorUnits')
total_saved = goal.get('totalSaved', {})
self.total_saved_currency = total_saved.get('currency')
self.total_saved_minor_units = total_saved.get('minorUnits') | [
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| 9495456980d5d6d85c4e999a17dc69481067af09 | https://github.com/Dullage/starlingbank/blob/9495456980d5d6d85c4e999a17dc69481067af09/starlingbank/__init__.py#L37-L61 | train |
Dullage/starlingbank | starlingbank/__init__.py | SavingsGoal.deposit | def deposit(self, deposit_minor_units: int) -> None:
"""Add funds to a savings goal."""
endpoint = "/account/{0}/savings-goals/{1}/add-money/{2}".format(
self._account_uid,
self.uid,
uuid4()
)
body = {
"amount": {
"currency": self.total_saved_currency,
"minorUnits": deposit_minor_units
}
}
response = put(
_url(endpoint, self._sandbox),
headers=self._auth_headers,
data=json_dumps(body)
)
response.raise_for_status()
self.update() | python | def deposit(self, deposit_minor_units: int) -> None:
"""Add funds to a savings goal."""
endpoint = "/account/{0}/savings-goals/{1}/add-money/{2}".format(
self._account_uid,
self.uid,
uuid4()
)
body = {
"amount": {
"currency": self.total_saved_currency,
"minorUnits": deposit_minor_units
}
}
response = put(
_url(endpoint, self._sandbox),
headers=self._auth_headers,
data=json_dumps(body)
)
response.raise_for_status()
self.update() | [
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| 9495456980d5d6d85c4e999a17dc69481067af09 | https://github.com/Dullage/starlingbank/blob/9495456980d5d6d85c4e999a17dc69481067af09/starlingbank/__init__.py#L63-L85 | train |
Dullage/starlingbank | starlingbank/__init__.py | SavingsGoal.get_image | def get_image(self, filename: str=None) -> None:
"""Download the photo associated with a Savings Goal."""
if filename is None:
filename = "{0}.png".format(self.name)
endpoint = "/account/{0}/savings-goals/{1}/photo".format(
self._account_uid,
self.uid
)
response = get(
_url(endpoint, self._sandbox),
headers=self._auth_headers
)
response.raise_for_status()
base64_image = response.json()['base64EncodedPhoto']
with open(filename, 'wb') as file:
file.write(b64decode(base64_image)) | python | def get_image(self, filename: str=None) -> None:
"""Download the photo associated with a Savings Goal."""
if filename is None:
filename = "{0}.png".format(self.name)
endpoint = "/account/{0}/savings-goals/{1}/photo".format(
self._account_uid,
self.uid
)
response = get(
_url(endpoint, self._sandbox),
headers=self._auth_headers
)
response.raise_for_status()
base64_image = response.json()['base64EncodedPhoto']
with open(filename, 'wb') as file:
file.write(b64decode(base64_image)) | [
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| 9495456980d5d6d85c4e999a17dc69481067af09 | https://github.com/Dullage/starlingbank/blob/9495456980d5d6d85c4e999a17dc69481067af09/starlingbank/__init__.py#L111-L129 | train |
Dullage/starlingbank | starlingbank/__init__.py | StarlingAccount.update_account_data | def update_account_data(self) -> None:
"""Get basic information for the account."""
response = get(
_url(
"/accounts/{0}/identifiers".format(self._account_uid),
self._sandbox
),
headers=self._auth_headers
)
response.raise_for_status()
response = response.json()
self.account_identifier = response.get('accountIdentifier')
self.bank_identifier = response.get('bankIdentifier')
self.iban = response.get('iban')
self.bic = response.get('bic') | python | def update_account_data(self) -> None:
"""Get basic information for the account."""
response = get(
_url(
"/accounts/{0}/identifiers".format(self._account_uid),
self._sandbox
),
headers=self._auth_headers
)
response.raise_for_status()
response = response.json()
self.account_identifier = response.get('accountIdentifier')
self.bank_identifier = response.get('bankIdentifier')
self.iban = response.get('iban')
self.bic = response.get('bic') | [
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| 9495456980d5d6d85c4e999a17dc69481067af09 | https://github.com/Dullage/starlingbank/blob/9495456980d5d6d85c4e999a17dc69481067af09/starlingbank/__init__.py#L135-L151 | train |
Dullage/starlingbank | starlingbank/__init__.py | StarlingAccount.update_balance_data | def update_balance_data(self) -> None:
"""Get the latest balance information for the account."""
response = get(
_url(
"/accounts/{0}/balance".format(self._account_uid),
self._sandbox
),
headers=self._auth_headers
)
response.raise_for_status()
response = response.json()
self.cleared_balance = response['clearedBalance']['minorUnits']
self.effective_balance = response['effectiveBalance']['minorUnits']
self.pending_transactions \
= response['pendingTransactions']['minorUnits']
self.available_to_spend = response['availableToSpend']['minorUnits']
self.accepted_overdraft = response['acceptedOverdraft']['minorUnits'] | python | def update_balance_data(self) -> None:
"""Get the latest balance information for the account."""
response = get(
_url(
"/accounts/{0}/balance".format(self._account_uid),
self._sandbox
),
headers=self._auth_headers
)
response.raise_for_status()
response = response.json()
self.cleared_balance = response['clearedBalance']['minorUnits']
self.effective_balance = response['effectiveBalance']['minorUnits']
self.pending_transactions \
= response['pendingTransactions']['minorUnits']
self.available_to_spend = response['availableToSpend']['minorUnits']
self.accepted_overdraft = response['acceptedOverdraft']['minorUnits'] | [
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| 9495456980d5d6d85c4e999a17dc69481067af09 | https://github.com/Dullage/starlingbank/blob/9495456980d5d6d85c4e999a17dc69481067af09/starlingbank/__init__.py#L153-L170 | train |
Dullage/starlingbank | starlingbank/__init__.py | StarlingAccount.update_savings_goal_data | def update_savings_goal_data(self) -> None:
"""Get the latest savings goal information for the account."""
response = get(
_url(
"/account/{0}/savings-goals".format(self._account_uid),
self._sandbox
),
headers=self._auth_headers
)
response.raise_for_status()
response = response.json()
response_savings_goals = response.get('savingsGoalList', {})
returned_uids = []
# New / Update
for goal in response_savings_goals:
uid = goal.get('savingsGoalUid')
returned_uids.append(uid)
# Intiialise new _SavingsGoal object if new
if uid not in self.savings_goals:
self.savings_goals[uid] = SavingsGoal(
self._auth_headers,
self._sandbox,
self._account_uid
)
self.savings_goals[uid].update(goal)
# Forget about savings goals if the UID isn't returned by Starling
for uid in list(self.savings_goals):
if uid not in returned_uids:
self.savings_goals.pop(uid) | python | def update_savings_goal_data(self) -> None:
"""Get the latest savings goal information for the account."""
response = get(
_url(
"/account/{0}/savings-goals".format(self._account_uid),
self._sandbox
),
headers=self._auth_headers
)
response.raise_for_status()
response = response.json()
response_savings_goals = response.get('savingsGoalList', {})
returned_uids = []
# New / Update
for goal in response_savings_goals:
uid = goal.get('savingsGoalUid')
returned_uids.append(uid)
# Intiialise new _SavingsGoal object if new
if uid not in self.savings_goals:
self.savings_goals[uid] = SavingsGoal(
self._auth_headers,
self._sandbox,
self._account_uid
)
self.savings_goals[uid].update(goal)
# Forget about savings goals if the UID isn't returned by Starling
for uid in list(self.savings_goals):
if uid not in returned_uids:
self.savings_goals.pop(uid) | [
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| 9495456980d5d6d85c4e999a17dc69481067af09 | https://github.com/Dullage/starlingbank/blob/9495456980d5d6d85c4e999a17dc69481067af09/starlingbank/__init__.py#L172-L206 | train |
mintchaos/django_inlines | django_inlines/templatetags/inlines.py | process_inlines | def process_inlines(parser, token):
"""
Searches through the provided content and applies inlines where ever they
are found.
Syntax::
{% process_inlines entry.body [in template_dir] [as varname] }
Examples::
{% process_inlines entry.body %}
{% process_inlines entry.body as body %}
{% process_inlines entry.body in 'inlines/sidebar' %}
{% process_inlines entry.body in 'inlines/sidebar' as body %}
"""
args = token.split_contents()
if not len(args) in (2, 4, 6):
raise template.TemplateSyntaxError("%r tag requires either 1, 3 or 5 arguments." % args[0])
var_name = args[1]
ALLOWED_ARGS = ['as', 'in']
kwargs = { 'template_directory': None }
if len(args) > 2:
tuples = zip(*[args[2:][i::2] for i in range(2)])
for k,v in tuples:
if not k in ALLOWED_ARGS:
raise template.TemplateSyntaxError("%r tag options arguments must be one of %s." % (args[0], ', '.join(ALLOWED_ARGS)))
if k == 'in':
kwargs['template_directory'] = v
if k == 'as':
kwargs['asvar'] = v
return InlinesNode(var_name, **kwargs) | python | def process_inlines(parser, token):
"""
Searches through the provided content and applies inlines where ever they
are found.
Syntax::
{% process_inlines entry.body [in template_dir] [as varname] }
Examples::
{% process_inlines entry.body %}
{% process_inlines entry.body as body %}
{% process_inlines entry.body in 'inlines/sidebar' %}
{% process_inlines entry.body in 'inlines/sidebar' as body %}
"""
args = token.split_contents()
if not len(args) in (2, 4, 6):
raise template.TemplateSyntaxError("%r tag requires either 1, 3 or 5 arguments." % args[0])
var_name = args[1]
ALLOWED_ARGS = ['as', 'in']
kwargs = { 'template_directory': None }
if len(args) > 2:
tuples = zip(*[args[2:][i::2] for i in range(2)])
for k,v in tuples:
if not k in ALLOWED_ARGS:
raise template.TemplateSyntaxError("%r tag options arguments must be one of %s." % (args[0], ', '.join(ALLOWED_ARGS)))
if k == 'in':
kwargs['template_directory'] = v
if k == 'as':
kwargs['asvar'] = v
return InlinesNode(var_name, **kwargs) | [
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| 1912e508d04884713a6c44a068c21fbd217d478a | https://github.com/mintchaos/django_inlines/blob/1912e508d04884713a6c44a068c21fbd217d478a/django_inlines/templatetags/inlines.py#L40-L80 | train |
klichukb/django-migrate-sql | migrate_sql/graph.py | build_current_graph | def build_current_graph():
"""
Read current state of SQL items from the current project state.
Returns:
(SQLStateGraph) Current project state graph.
"""
graph = SQLStateGraph()
for app_name, config in apps.app_configs.items():
try:
module = import_module(
'.'.join((config.module.__name__, SQL_CONFIG_MODULE)))
sql_items = module.sql_items
except (ImportError, AttributeError):
continue
for sql_item in sql_items:
graph.add_node((app_name, sql_item.name), sql_item)
for dep in sql_item.dependencies:
graph.add_lazy_dependency((app_name, sql_item.name), dep)
graph.build_graph()
return graph | python | def build_current_graph():
"""
Read current state of SQL items from the current project state.
Returns:
(SQLStateGraph) Current project state graph.
"""
graph = SQLStateGraph()
for app_name, config in apps.app_configs.items():
try:
module = import_module(
'.'.join((config.module.__name__, SQL_CONFIG_MODULE)))
sql_items = module.sql_items
except (ImportError, AttributeError):
continue
for sql_item in sql_items:
graph.add_node((app_name, sql_item.name), sql_item)
for dep in sql_item.dependencies:
graph.add_lazy_dependency((app_name, sql_item.name), dep)
graph.build_graph()
return graph | [
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| be48ff2c9283404e3d951128c459c3496d1ba25d | https://github.com/klichukb/django-migrate-sql/blob/be48ff2c9283404e3d951128c459c3496d1ba25d/migrate_sql/graph.py#L100-L122 | train |
klichukb/django-migrate-sql | migrate_sql/graph.py | SQLStateGraph.build_graph | def build_graph(self):
"""
Read lazy dependency list and build graph.
"""
for child, parents in self.dependencies.items():
if child not in self.nodes:
raise NodeNotFoundError(
"App %s SQL item dependencies reference nonexistent child node %r" % (
child[0], child),
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for parent in parents:
if parent not in self.nodes:
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self.node_map[child].add_parent(self.node_map[parent])
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for node in self.nodes:
self.ensure_not_cyclic(node,
lambda x: (parent.key for parent in self.node_map[x].parents)) | python | def build_graph(self):
"""
Read lazy dependency list and build graph.
"""
for child, parents in self.dependencies.items():
if child not in self.nodes:
raise NodeNotFoundError(
"App %s SQL item dependencies reference nonexistent child node %r" % (
child[0], child),
child
)
for parent in parents:
if parent not in self.nodes:
raise NodeNotFoundError(
"App %s SQL item dependencies reference nonexistent parent node %r" % (
child[0], parent),
parent
)
self.node_map[child].add_parent(self.node_map[parent])
self.node_map[parent].add_child(self.node_map[child])
for node in self.nodes:
self.ensure_not_cyclic(node,
lambda x: (parent.key for parent in self.node_map[x].parents)) | [
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| be48ff2c9283404e3d951128c459c3496d1ba25d | https://github.com/klichukb/django-migrate-sql/blob/be48ff2c9283404e3d951128c459c3496d1ba25d/migrate_sql/graph.py#L54-L77 | train |
ngmarchant/oasis | oasis/passive.py | PassiveSampler.sample | def sample(self, n_to_sample, **kwargs):
"""Sample a sequence of items from the pool
Parameters
----------
n_to_sample : int
number of items to sample
"""
n_to_sample = verify_positive(int(n_to_sample))
n_remaining = self._max_iter - self.t_
if n_remaining == 0:
if (not self.replace) and (self._n_items == self._max_iter):
raise Exception("All items have already been sampled")
else:
raise Exception("No more space available to continue sampling. "
"Consider re-initialising with a larger value "
"of max_iter.")
if n_to_sample > n_remaining:
warnings.warn("Space only remains for {} more iteration(s). "
"Setting n_to_sample = {}.".format(n_remaining, \
n_remaining))
n_to_sample = n_remaining
for _ in range(n_to_sample):
self._iterate(**kwargs) | python | def sample(self, n_to_sample, **kwargs):
"""Sample a sequence of items from the pool
Parameters
----------
n_to_sample : int
number of items to sample
"""
n_to_sample = verify_positive(int(n_to_sample))
n_remaining = self._max_iter - self.t_
if n_remaining == 0:
if (not self.replace) and (self._n_items == self._max_iter):
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else:
raise Exception("No more space available to continue sampling. "
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if n_to_sample > n_remaining:
warnings.warn("Space only remains for {} more iteration(s). "
"Setting n_to_sample = {}.".format(n_remaining, \
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n_to_sample = n_remaining
for _ in range(n_to_sample):
self._iterate(**kwargs) | [
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| 28a037a8924b85ae97db8a93960a910a219d6a4a | https://github.com/ngmarchant/oasis/blob/28a037a8924b85ae97db8a93960a910a219d6a4a/oasis/passive.py#L174-L201 | train |
ngmarchant/oasis | oasis/passive.py | PassiveSampler.sample_distinct | def sample_distinct(self, n_to_sample, **kwargs):
"""Sample a sequence of items from the pool until a minimum number of
distinct items are queried
Parameters
----------
n_to_sample : int
number of distinct items to sample. If sampling with replacement,
this number is not necessarily the same as the number of
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"""
# Record how many distinct items have not yet been sampled
n_notsampled = np.sum(np.isnan(self.cached_labels_))
if n_notsampled == 0:
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if n_to_sample > n_notsampled:
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n_to_sample = n_notsampled
n_sampled = 0 # number of distinct items sampled this round
while n_sampled < n_to_sample:
self.sample(1,**kwargs)
n_sampled += self._queried_oracle[self.t_ - 1]*1 | python | def sample_distinct(self, n_to_sample, **kwargs):
"""Sample a sequence of items from the pool until a minimum number of
distinct items are queried
Parameters
----------
n_to_sample : int
number of distinct items to sample. If sampling with replacement,
this number is not necessarily the same as the number of
iterations.
"""
# Record how many distinct items have not yet been sampled
n_notsampled = np.sum(np.isnan(self.cached_labels_))
if n_notsampled == 0:
raise Exception("All distinct items have already been sampled.")
if n_to_sample > n_notsampled:
warnings.warn("Only {} distinct item(s) have not yet been sampled."
" Setting n_to_sample = {}.".format(n_notsampled, \
n_notsampled))
n_to_sample = n_notsampled
n_sampled = 0 # number of distinct items sampled this round
while n_sampled < n_to_sample:
self.sample(1,**kwargs)
n_sampled += self._queried_oracle[self.t_ - 1]*1 | [
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| 28a037a8924b85ae97db8a93960a910a219d6a4a | https://github.com/ngmarchant/oasis/blob/28a037a8924b85ae97db8a93960a910a219d6a4a/oasis/passive.py#L203-L229 | train |
ngmarchant/oasis | oasis/passive.py | PassiveSampler._sample_item | def _sample_item(self, **kwargs):
"""Sample an item from the pool"""
if self.replace:
# Can sample from any of the items
loc = np.random.choice(self._n_items)
else:
# Can only sample from items that have not been seen
# Find ids that haven't been seen yet
not_seen_ids = np.where(np.isnan(self.cached_labels_))[0]
loc = np.random.choice(not_seen_ids)
return loc, 1, {} | python | def _sample_item(self, **kwargs):
"""Sample an item from the pool"""
if self.replace:
# Can sample from any of the items
loc = np.random.choice(self._n_items)
else:
# Can only sample from items that have not been seen
# Find ids that haven't been seen yet
not_seen_ids = np.where(np.isnan(self.cached_labels_))[0]
loc = np.random.choice(not_seen_ids)
return loc, 1, {} | [
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| 28a037a8924b85ae97db8a93960a910a219d6a4a | https://github.com/ngmarchant/oasis/blob/28a037a8924b85ae97db8a93960a910a219d6a4a/oasis/passive.py#L231-L241 | train |
ngmarchant/oasis | oasis/passive.py | PassiveSampler._query_label | def _query_label(self, loc):
"""Query the label for the item with index `loc`. Preferentially
queries the label from the cache, but if not yet cached, queries the
oracle.
Returns
-------
int
the true label "0" or "1".
"""
# Try to get label from cache
ell = self.cached_labels_[loc]
if np.isnan(ell):
# Label has not been cached. Need to query oracle
oracle_arg = self.identifiers[loc]
ell = self.oracle(oracle_arg)
if ell not in [0, 1]:
raise Exception("Oracle provided an invalid label.")
#TODO Gracefully handle errors from oracle?
self._queried_oracle[self.t_] = True
self.cached_labels_[loc] = ell
return ell | python | def _query_label(self, loc):
"""Query the label for the item with index `loc`. Preferentially
queries the label from the cache, but if not yet cached, queries the
oracle.
Returns
-------
int
the true label "0" or "1".
"""
# Try to get label from cache
ell = self.cached_labels_[loc]
if np.isnan(ell):
# Label has not been cached. Need to query oracle
oracle_arg = self.identifiers[loc]
ell = self.oracle(oracle_arg)
if ell not in [0, 1]:
raise Exception("Oracle provided an invalid label.")
#TODO Gracefully handle errors from oracle?
self._queried_oracle[self.t_] = True
self.cached_labels_[loc] = ell
return ell | [
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| 28a037a8924b85ae97db8a93960a910a219d6a4a | https://github.com/ngmarchant/oasis/blob/28a037a8924b85ae97db8a93960a910a219d6a4a/oasis/passive.py#L243-L266 | train |
ngmarchant/oasis | oasis/passive.py | PassiveSampler._F_measure | def _F_measure(self, alpha, TP, FP, FN, return_num_den=False):
"""Calculate the weighted F-measure"""
num = np.float64(TP)
den = np.float64(alpha * (TP + FP) + (1 - alpha) * (TP + FN))
with np.errstate(divide='ignore', invalid='ignore'):
F_measure = num/den
#F_measure = num/den
if return_num_den:
return F_measure, num, den
else:
return F_measure | python | def _F_measure(self, alpha, TP, FP, FN, return_num_den=False):
"""Calculate the weighted F-measure"""
num = np.float64(TP)
den = np.float64(alpha * (TP + FP) + (1 - alpha) * (TP + FN))
with np.errstate(divide='ignore', invalid='ignore'):
F_measure = num/den
#F_measure = num/den
if return_num_den:
return F_measure, num, den
else:
return F_measure | [
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| 28a037a8924b85ae97db8a93960a910a219d6a4a | https://github.com/ngmarchant/oasis/blob/28a037a8924b85ae97db8a93960a910a219d6a4a/oasis/passive.py#L268-L279 | train |
openearth/mmi-python | mmi/tracker_client.py | MMITracker.key_occurrence | def key_occurrence(self, key, update=True):
"""
Return a dict containing the value of the provided key and its uuid as
value.
"""
if update:
self.update()
result = {}
for k, v in self.database.items():
if key in v:
result[str(v[key])] = k
return result | python | def key_occurrence(self, key, update=True):
"""
Return a dict containing the value of the provided key and its uuid as
value.
"""
if update:
self.update()
result = {}
for k, v in self.database.items():
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return result | [
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openearth/mmi-python | mmi/tracker_client.py | MMITracker.zmq_address | def zmq_address(self, key):
"""
Return a ZeroMQ address to the module with the provided key.
"""
zmq_address = "tcp://" + self.database[key]['node'] + ":" + str(self.database[key]['ports']['REQ'])
return zmq_address | python | def zmq_address(self, key):
"""
Return a ZeroMQ address to the module with the provided key.
"""
zmq_address = "tcp://" + self.database[key]['node'] + ":" + str(self.database[key]['ports']['REQ'])
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| a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d | https://github.com/openearth/mmi-python/blob/a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d/mmi/tracker_client.py#L30-L35 | train |
mkoura/dump2polarion | dump2polarion/results/ostriztools.py | _get_json | def _get_json(location):
"""Reads JSON data from file or URL."""
location = os.path.expanduser(location)
try:
if os.path.isfile(location):
with io.open(location, encoding="utf-8") as json_data:
return json.load(json_data, object_pairs_hook=OrderedDict).get("tests")
elif "http" in location:
json_data = requests.get(location)
if not json_data:
raise Dump2PolarionException("Failed to download")
return json.loads(json_data.text, object_pairs_hook=OrderedDict).get("tests")
else:
raise Dump2PolarionException("Invalid location")
except Exception as err:
raise Dump2PolarionException("Failed to parse JSON from {}: {}".format(location, err)) | python | def _get_json(location):
"""Reads JSON data from file or URL."""
location = os.path.expanduser(location)
try:
if os.path.isfile(location):
with io.open(location, encoding="utf-8") as json_data:
return json.load(json_data, object_pairs_hook=OrderedDict).get("tests")
elif "http" in location:
json_data = requests.get(location)
if not json_data:
raise Dump2PolarionException("Failed to download")
return json.loads(json_data.text, object_pairs_hook=OrderedDict).get("tests")
else:
raise Dump2PolarionException("Invalid location")
except Exception as err:
raise Dump2PolarionException("Failed to parse JSON from {}: {}".format(location, err)) | [
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| f4bd24e9d5070e282aad15f1e8bb514c0525cd37 | https://github.com/mkoura/dump2polarion/blob/f4bd24e9d5070e282aad15f1e8bb514c0525cd37/dump2polarion/results/ostriztools.py#L29-L44 | train |
mkoura/dump2polarion | dump2polarion/results/ostriztools.py | _calculate_duration | def _calculate_duration(start_time, finish_time):
"""Calculates how long it took to execute the testcase."""
if not (start_time and finish_time):
return 0
start = datetime.datetime.fromtimestamp(start_time)
finish = datetime.datetime.fromtimestamp(finish_time)
duration = finish - start
decimals = float(("0." + str(duration.microseconds)))
return duration.seconds + decimals | python | def _calculate_duration(start_time, finish_time):
"""Calculates how long it took to execute the testcase."""
if not (start_time and finish_time):
return 0
start = datetime.datetime.fromtimestamp(start_time)
finish = datetime.datetime.fromtimestamp(finish_time)
duration = finish - start
decimals = float(("0." + str(duration.microseconds)))
return duration.seconds + decimals | [
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| f4bd24e9d5070e282aad15f1e8bb514c0525cd37 | https://github.com/mkoura/dump2polarion/blob/f4bd24e9d5070e282aad15f1e8bb514c0525cd37/dump2polarion/results/ostriztools.py#L67-L76 | train |
mkoura/dump2polarion | dump2polarion/results/ostriztools.py | _filter_parameters | def _filter_parameters(parameters):
"""Filters the ignored parameters out."""
if not parameters:
return None
return OrderedDict(
(param, value) for param, value in six.iteritems(parameters) if param not in IGNORED_PARAMS
) | python | def _filter_parameters(parameters):
"""Filters the ignored parameters out."""
if not parameters:
return None
return OrderedDict(
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| f4bd24e9d5070e282aad15f1e8bb514c0525cd37 | https://github.com/mkoura/dump2polarion/blob/f4bd24e9d5070e282aad15f1e8bb514c0525cd37/dump2polarion/results/ostriztools.py#L88-L94 | train |
mkoura/dump2polarion | dump2polarion/results/ostriztools.py | _append_record | def _append_record(test_data, results, test_path):
"""Adds data of single testcase results to results database."""
statuses = test_data.get("statuses")
jenkins_data = test_data.get("jenkins") or {}
data = [
("title", test_data.get("test_name") or _get_testname(test_path)),
("verdict", statuses.get("overall")),
("source", test_data.get("source")),
("job_name", jenkins_data.get("job_name")),
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),
]
test_id = test_data.get("polarion")
if test_id:
if isinstance(test_id, list):
test_id = test_id[0]
data.append(("test_id", test_id))
results.append(OrderedDict(data)) | python | def _append_record(test_data, results, test_path):
"""Adds data of single testcase results to results database."""
statuses = test_data.get("statuses")
jenkins_data = test_data.get("jenkins") or {}
data = [
("title", test_data.get("test_name") or _get_testname(test_path)),
("verdict", statuses.get("overall")),
("source", test_data.get("source")),
("job_name", jenkins_data.get("job_name")),
("run", jenkins_data.get("build_number")),
("params", _filter_parameters(test_data.get("params"))),
(
"time",
_calculate_duration(test_data.get("start_time"), test_data.get("finish_time")) or 0,
),
]
test_id = test_data.get("polarion")
if test_id:
if isinstance(test_id, list):
test_id = test_id[0]
data.append(("test_id", test_id))
results.append(OrderedDict(data)) | [
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| f4bd24e9d5070e282aad15f1e8bb514c0525cd37 | https://github.com/mkoura/dump2polarion/blob/f4bd24e9d5070e282aad15f1e8bb514c0525cd37/dump2polarion/results/ostriztools.py#L97-L120 | train |
mkoura/dump2polarion | dump2polarion/results/ostriztools.py | _parse_ostriz | def _parse_ostriz(ostriz_data):
"""Reads the content of the input JSON and returns testcases results."""
if not ostriz_data:
raise NothingToDoException("No data to import")
results = []
found_build = None
last_finish_time = [0]
for test_path, test_data in six.iteritems(ostriz_data):
curr_build = test_data.get("build")
if not curr_build:
continue
# set `found_build` from first record where it's present
if not found_build:
found_build = curr_build
# make sure we are collecting data for the same build
if found_build != curr_build:
continue
if not test_data.get("statuses"):
continue
_append_record(test_data, results, test_path)
_comp_finish_time(test_data, last_finish_time)
if last_finish_time[0]:
logger.info("Last result finished at %s", last_finish_time[0])
testrun_id = _get_testrun_id(found_build)
return xunit_exporter.ImportedData(results=results, testrun=testrun_id) | python | def _parse_ostriz(ostriz_data):
"""Reads the content of the input JSON and returns testcases results."""
if not ostriz_data:
raise NothingToDoException("No data to import")
results = []
found_build = None
last_finish_time = [0]
for test_path, test_data in six.iteritems(ostriz_data):
curr_build = test_data.get("build")
if not curr_build:
continue
# set `found_build` from first record where it's present
if not found_build:
found_build = curr_build
# make sure we are collecting data for the same build
if found_build != curr_build:
continue
if not test_data.get("statuses"):
continue
_append_record(test_data, results, test_path)
_comp_finish_time(test_data, last_finish_time)
if last_finish_time[0]:
logger.info("Last result finished at %s", last_finish_time[0])
testrun_id = _get_testrun_id(found_build)
return xunit_exporter.ImportedData(results=results, testrun=testrun_id) | [
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| f4bd24e9d5070e282aad15f1e8bb514c0525cd37 | https://github.com/mkoura/dump2polarion/blob/f4bd24e9d5070e282aad15f1e8bb514c0525cd37/dump2polarion/results/ostriztools.py#L129-L160 | train |
openearth/mmi-python | mmi/__init__.py | send_array | def send_array(
socket, A=None, metadata=None, flags=0,
copy=False, track=False, compress=None,
chunksize=50 * 1000 * 1000
):
"""send a numpy array with metadata over zmq
message is mostly multipart:
metadata | array part 1 | array part 2, etc
only metadata:
metadata
the chunksize roughly determines the size of the parts being sent
if the chunksize is too big, you get an error like:
zmq.error.Again: Resource temporarily unavailable
"""
# create a metadata dictionary for the message
md = {}
# always add a timestamp
md['timestamp'] = datetime.datetime.now().isoformat()
# copy extra metadata
if metadata:
md.update(metadata)
# if we don't have an array
if A is None:
# send only json
md['parts'] = 0
socket.send_json(md, flags)
# and we're done
return
# support single values (empty shape)
if isinstance(A, float) or isinstance(A, int):
A = np.asarray(A)
# add array metadata
md['dtype'] = str(A.dtype)
md['shape'] = A.shape
# determine number of parts
md['parts'] = int(np.prod(A.shape) // chunksize + 1)
try:
# If an array has a fill value assume it's an array with missings
# store the fill_Value in the metadata and fill the array before sending.
# asscalar should work for scalar, 0d array or nd array of size 1
md['fill_value'] = np.asscalar(A.fill_value)
A = A.filled()
except AttributeError:
# no masked array, nothing to do
pass
# send json, followed by array (in x parts)
socket.send_json(md, flags | zmq.SNDMORE)
# although the check is not strictly necessary, we try to maintain fast
# pointer transfer when there is only 1 part
if md['parts'] == 1:
msg = memoryview(np.ascontiguousarray(A))
socket.send(msg, flags, copy=copy, track=track)
else:
# split array at first dimension and send parts
for i, a in enumerate(np.array_split(A, md['parts'])):
# Make a copy if required and pass along the memoryview
msg = memoryview(np.ascontiguousarray(a))
flags_ = flags
if i != md['parts'] - 1:
flags_ |= zmq.SNDMORE
socket.send(msg, flags_, copy=copy, track=track)
return | python | def send_array(
socket, A=None, metadata=None, flags=0,
copy=False, track=False, compress=None,
chunksize=50 * 1000 * 1000
):
"""send a numpy array with metadata over zmq
message is mostly multipart:
metadata | array part 1 | array part 2, etc
only metadata:
metadata
the chunksize roughly determines the size of the parts being sent
if the chunksize is too big, you get an error like:
zmq.error.Again: Resource temporarily unavailable
"""
# create a metadata dictionary for the message
md = {}
# always add a timestamp
md['timestamp'] = datetime.datetime.now().isoformat()
# copy extra metadata
if metadata:
md.update(metadata)
# if we don't have an array
if A is None:
# send only json
md['parts'] = 0
socket.send_json(md, flags)
# and we're done
return
# support single values (empty shape)
if isinstance(A, float) or isinstance(A, int):
A = np.asarray(A)
# add array metadata
md['dtype'] = str(A.dtype)
md['shape'] = A.shape
# determine number of parts
md['parts'] = int(np.prod(A.shape) // chunksize + 1)
try:
# If an array has a fill value assume it's an array with missings
# store the fill_Value in the metadata and fill the array before sending.
# asscalar should work for scalar, 0d array or nd array of size 1
md['fill_value'] = np.asscalar(A.fill_value)
A = A.filled()
except AttributeError:
# no masked array, nothing to do
pass
# send json, followed by array (in x parts)
socket.send_json(md, flags | zmq.SNDMORE)
# although the check is not strictly necessary, we try to maintain fast
# pointer transfer when there is only 1 part
if md['parts'] == 1:
msg = memoryview(np.ascontiguousarray(A))
socket.send(msg, flags, copy=copy, track=track)
else:
# split array at first dimension and send parts
for i, a in enumerate(np.array_split(A, md['parts'])):
# Make a copy if required and pass along the memoryview
msg = memoryview(np.ascontiguousarray(a))
flags_ = flags
if i != md['parts'] - 1:
flags_ |= zmq.SNDMORE
socket.send(msg, flags_, copy=copy, track=track)
return | [
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| a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d | https://github.com/openearth/mmi-python/blob/a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d/mmi/__init__.py#L27-L98 | train |
openearth/mmi-python | mmi/__init__.py | recv_array | def recv_array(
socket,
flags=0,
copy=False,
track=False,
poll=None,
poll_timeout=10000
):
"""recv a metadata and an optional numpy array from a zmq socket
Optionally provide poll object to use recv_array with timeout
poll_timeout is in millis
"""
if poll is None:
md = socket.recv_json(flags=flags)
else:
# one-try "Lazy Pirate" method: http://zguide.zeromq.org/php:chapter4
socks = dict(poll.poll(poll_timeout))
if socks.get(socket) == zmq.POLLIN:
reply = socket.recv_json(flags=flags)
# note that reply can be an empty array
md = reply
else:
raise NoResponseException(
"Recv_array got no response within timeout (1)")
if md['parts'] == 0:
# No array expected
A = None
elif md['parts'] == 1:
# although the check is not strictly necessary, we try to maintain fast
# pointer transfer when there is only 1 part
if poll is None:
msg = socket.recv(flags=flags, copy=copy, track=track)
else:
# one-try "Lazy Pirate" method: http://zguide.zeromq.org/php:chapter4
socks = dict(poll.poll(poll_timeout))
if socks.get(socket) == zmq.POLLIN:
reply = socket.recv(flags=flags, copy=copy, track=track)
# note that reply can be an empty array
msg = reply
else:
raise NoResponseException(
"Recv_array got no response within timeout (2)")
buf = buffer(msg)
A = np.frombuffer(buf, dtype=md['dtype'])
A = A.reshape(md['shape'])
if 'fill_value' in md:
A = np.ma.masked_equal(A, md['fill_value'])
else:
# multi part array
A = np.zeros(np.prod(md['shape']), dtype=md['dtype'])
arr_position = 0
for i in range(md['parts']):
if poll is None:
msg = socket.recv(flags=flags, copy=copy, track=track)
else:
# one-try "Lazy Pirate" method: http://zguide.zeromq.org/php:chapter4
socks = dict(poll.poll(poll_timeout))
if socks.get(socket) == zmq.POLLIN:
reply = socket.recv(flags=flags, copy=copy, track=track)
if not reply:
raise EmptyResponseException(
"Recv_array got an empty response (2)")
msg = reply
else:
raise NoResponseException(
"Recv_array got no response within timeout (2)")
buf = buffer(msg)
a = np.frombuffer(buf, dtype=md['dtype'])
A[arr_position:arr_position + a.shape[0]] = a[:]
arr_position += a.shape[0]
A = A.reshape(md['shape'])
if 'fill_value' in md:
A = np.ma.masked_equal(A, md['fill_value'])
return A, md | python | def recv_array(
socket,
flags=0,
copy=False,
track=False,
poll=None,
poll_timeout=10000
):
"""recv a metadata and an optional numpy array from a zmq socket
Optionally provide poll object to use recv_array with timeout
poll_timeout is in millis
"""
if poll is None:
md = socket.recv_json(flags=flags)
else:
# one-try "Lazy Pirate" method: http://zguide.zeromq.org/php:chapter4
socks = dict(poll.poll(poll_timeout))
if socks.get(socket) == zmq.POLLIN:
reply = socket.recv_json(flags=flags)
# note that reply can be an empty array
md = reply
else:
raise NoResponseException(
"Recv_array got no response within timeout (1)")
if md['parts'] == 0:
# No array expected
A = None
elif md['parts'] == 1:
# although the check is not strictly necessary, we try to maintain fast
# pointer transfer when there is only 1 part
if poll is None:
msg = socket.recv(flags=flags, copy=copy, track=track)
else:
# one-try "Lazy Pirate" method: http://zguide.zeromq.org/php:chapter4
socks = dict(poll.poll(poll_timeout))
if socks.get(socket) == zmq.POLLIN:
reply = socket.recv(flags=flags, copy=copy, track=track)
# note that reply can be an empty array
msg = reply
else:
raise NoResponseException(
"Recv_array got no response within timeout (2)")
buf = buffer(msg)
A = np.frombuffer(buf, dtype=md['dtype'])
A = A.reshape(md['shape'])
if 'fill_value' in md:
A = np.ma.masked_equal(A, md['fill_value'])
else:
# multi part array
A = np.zeros(np.prod(md['shape']), dtype=md['dtype'])
arr_position = 0
for i in range(md['parts']):
if poll is None:
msg = socket.recv(flags=flags, copy=copy, track=track)
else:
# one-try "Lazy Pirate" method: http://zguide.zeromq.org/php:chapter4
socks = dict(poll.poll(poll_timeout))
if socks.get(socket) == zmq.POLLIN:
reply = socket.recv(flags=flags, copy=copy, track=track)
if not reply:
raise EmptyResponseException(
"Recv_array got an empty response (2)")
msg = reply
else:
raise NoResponseException(
"Recv_array got no response within timeout (2)")
buf = buffer(msg)
a = np.frombuffer(buf, dtype=md['dtype'])
A[arr_position:arr_position + a.shape[0]] = a[:]
arr_position += a.shape[0]
A = A.reshape(md['shape'])
if 'fill_value' in md:
A = np.ma.masked_equal(A, md['fill_value'])
return A, md | [
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| a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d | https://github.com/openearth/mmi-python/blob/a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d/mmi/__init__.py#L101-L182 | train |
klichukb/django-migrate-sql | migrate_sql/autodetector.py | is_sql_equal | def is_sql_equal(sqls1, sqls2):
"""
Find out equality of two SQL items.
See https://docs.djangoproject.com/en/1.8/ref/migration-operations/#runsql.
Args:
sqls1, sqls2: SQL items, have the same format as supported by Django's RunSQL operation.
Returns:
(bool) `True` if equal, otherwise `False`.
"""
is_seq1 = isinstance(sqls1, (list, tuple))
is_seq2 = isinstance(sqls2, (list, tuple))
if not is_seq1:
sqls1 = (sqls1,)
if not is_seq2:
sqls2 = (sqls2,)
if len(sqls1) != len(sqls2):
return False
for sql1, sql2 in zip(sqls1, sqls2):
sql1, params1 = _sql_params(sql1)
sql2, params2 = _sql_params(sql2)
if sql1 != sql2 or params1 != params2:
return False
return True | python | def is_sql_equal(sqls1, sqls2):
"""
Find out equality of two SQL items.
See https://docs.djangoproject.com/en/1.8/ref/migration-operations/#runsql.
Args:
sqls1, sqls2: SQL items, have the same format as supported by Django's RunSQL operation.
Returns:
(bool) `True` if equal, otherwise `False`.
"""
is_seq1 = isinstance(sqls1, (list, tuple))
is_seq2 = isinstance(sqls2, (list, tuple))
if not is_seq1:
sqls1 = (sqls1,)
if not is_seq2:
sqls2 = (sqls2,)
if len(sqls1) != len(sqls2):
return False
for sql1, sql2 in zip(sqls1, sqls2):
sql1, params1 = _sql_params(sql1)
sql2, params2 = _sql_params(sql2)
if sql1 != sql2 or params1 != params2:
return False
return True | [
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| be48ff2c9283404e3d951128c459c3496d1ba25d | https://github.com/klichukb/django-migrate-sql/blob/be48ff2c9283404e3d951128c459c3496d1ba25d/migrate_sql/autodetector.py#L33-L59 | train |
klichukb/django-migrate-sql | migrate_sql/autodetector.py | MigrationAutodetector.add_sql_operation | def add_sql_operation(self, app_label, sql_name, operation, dependencies):
"""
Add SQL operation and register it to be used as dependency for further
sequential operations.
"""
deps = [(dp[0], SQL_BLOB, dp[1], self._sql_operations.get(dp)) for dp in dependencies]
self.add_operation(app_label, operation, dependencies=deps)
self._sql_operations[(app_label, sql_name)] = operation | python | def add_sql_operation(self, app_label, sql_name, operation, dependencies):
"""
Add SQL operation and register it to be used as dependency for further
sequential operations.
"""
deps = [(dp[0], SQL_BLOB, dp[1], self._sql_operations.get(dp)) for dp in dependencies]
self.add_operation(app_label, operation, dependencies=deps)
self._sql_operations[(app_label, sql_name)] = operation | [
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| be48ff2c9283404e3d951128c459c3496d1ba25d | https://github.com/klichukb/django-migrate-sql/blob/be48ff2c9283404e3d951128c459c3496d1ba25d/migrate_sql/autodetector.py#L110-L118 | train |
klichukb/django-migrate-sql | migrate_sql/autodetector.py | MigrationAutodetector._generate_reversed_sql | def _generate_reversed_sql(self, keys, changed_keys):
"""
Generate reversed operations for changes, that require full rollback and creation.
"""
for key in keys:
if key not in changed_keys:
continue
app_label, sql_name = key
old_item = self.from_sql_graph.nodes[key]
new_item = self.to_sql_graph.nodes[key]
if not old_item.reverse_sql or old_item.reverse_sql == RunSQL.noop or new_item.replace:
continue
# migrate backwards
operation = ReverseAlterSQL(sql_name, old_item.reverse_sql, reverse_sql=old_item.sql)
sql_deps = [n.key for n in self.from_sql_graph.node_map[key].children]
sql_deps.append(key)
self.add_sql_operation(app_label, sql_name, operation, sql_deps) | python | def _generate_reversed_sql(self, keys, changed_keys):
"""
Generate reversed operations for changes, that require full rollback and creation.
"""
for key in keys:
if key not in changed_keys:
continue
app_label, sql_name = key
old_item = self.from_sql_graph.nodes[key]
new_item = self.to_sql_graph.nodes[key]
if not old_item.reverse_sql or old_item.reverse_sql == RunSQL.noop or new_item.replace:
continue
# migrate backwards
operation = ReverseAlterSQL(sql_name, old_item.reverse_sql, reverse_sql=old_item.sql)
sql_deps = [n.key for n in self.from_sql_graph.node_map[key].children]
sql_deps.append(key)
self.add_sql_operation(app_label, sql_name, operation, sql_deps) | [
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| be48ff2c9283404e3d951128c459c3496d1ba25d | https://github.com/klichukb/django-migrate-sql/blob/be48ff2c9283404e3d951128c459c3496d1ba25d/migrate_sql/autodetector.py#L120-L137 | train |
klichukb/django-migrate-sql | migrate_sql/autodetector.py | MigrationAutodetector._generate_delete_sql | def _generate_delete_sql(self, delete_keys):
"""
Generate forward delete operations for SQL items.
"""
for key in delete_keys:
app_label, sql_name = key
old_node = self.from_sql_graph.nodes[key]
operation = DeleteSQL(sql_name, old_node.reverse_sql, reverse_sql=old_node.sql)
sql_deps = [n.key for n in self.from_sql_graph.node_map[key].children]
sql_deps.append(key)
self.add_sql_operation(app_label, sql_name, operation, sql_deps) | python | def _generate_delete_sql(self, delete_keys):
"""
Generate forward delete operations for SQL items.
"""
for key in delete_keys:
app_label, sql_name = key
old_node = self.from_sql_graph.nodes[key]
operation = DeleteSQL(sql_name, old_node.reverse_sql, reverse_sql=old_node.sql)
sql_deps = [n.key for n in self.from_sql_graph.node_map[key].children]
sql_deps.append(key)
self.add_sql_operation(app_label, sql_name, operation, sql_deps) | [
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| be48ff2c9283404e3d951128c459c3496d1ba25d | https://github.com/klichukb/django-migrate-sql/blob/be48ff2c9283404e3d951128c459c3496d1ba25d/migrate_sql/autodetector.py#L186-L196 | train |
klichukb/django-migrate-sql | migrate_sql/autodetector.py | MigrationAutodetector.generate_sql_changes | def generate_sql_changes(self):
"""
Starting point of this tool, which identifies changes and generates respective
operations.
"""
from_keys = set(self.from_sql_graph.nodes.keys())
to_keys = set(self.to_sql_graph.nodes.keys())
new_keys = to_keys - from_keys
delete_keys = from_keys - to_keys
changed_keys = set()
dep_changed_keys = []
for key in from_keys & to_keys:
old_node = self.from_sql_graph.nodes[key]
new_node = self.to_sql_graph.nodes[key]
# identify SQL changes -- these will alter database.
if not is_sql_equal(old_node.sql, new_node.sql):
changed_keys.add(key)
# identify dependencies change
old_deps = self.from_sql_graph.dependencies[key]
new_deps = self.to_sql_graph.dependencies[key]
removed_deps = old_deps - new_deps
added_deps = new_deps - old_deps
if removed_deps or added_deps:
dep_changed_keys.append((key, removed_deps, added_deps))
# we do basic sort here and inject dependency keys here.
# operations built using these keys will properly set operation dependencies which will
# enforce django to build/keep a correct order of operations (stable_topological_sort).
keys = self.assemble_changes(new_keys, changed_keys, self.to_sql_graph)
delete_keys = self.assemble_changes(delete_keys, set(), self.from_sql_graph)
self._sql_operations = {}
self._generate_reversed_sql(keys, changed_keys)
self._generate_sql(keys, changed_keys)
self._generate_delete_sql(delete_keys)
self._generate_altered_sql_dependencies(dep_changed_keys) | python | def generate_sql_changes(self):
"""
Starting point of this tool, which identifies changes and generates respective
operations.
"""
from_keys = set(self.from_sql_graph.nodes.keys())
to_keys = set(self.to_sql_graph.nodes.keys())
new_keys = to_keys - from_keys
delete_keys = from_keys - to_keys
changed_keys = set()
dep_changed_keys = []
for key in from_keys & to_keys:
old_node = self.from_sql_graph.nodes[key]
new_node = self.to_sql_graph.nodes[key]
# identify SQL changes -- these will alter database.
if not is_sql_equal(old_node.sql, new_node.sql):
changed_keys.add(key)
# identify dependencies change
old_deps = self.from_sql_graph.dependencies[key]
new_deps = self.to_sql_graph.dependencies[key]
removed_deps = old_deps - new_deps
added_deps = new_deps - old_deps
if removed_deps or added_deps:
dep_changed_keys.append((key, removed_deps, added_deps))
# we do basic sort here and inject dependency keys here.
# operations built using these keys will properly set operation dependencies which will
# enforce django to build/keep a correct order of operations (stable_topological_sort).
keys = self.assemble_changes(new_keys, changed_keys, self.to_sql_graph)
delete_keys = self.assemble_changes(delete_keys, set(), self.from_sql_graph)
self._sql_operations = {}
self._generate_reversed_sql(keys, changed_keys)
self._generate_sql(keys, changed_keys)
self._generate_delete_sql(delete_keys)
self._generate_altered_sql_dependencies(dep_changed_keys) | [
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| be48ff2c9283404e3d951128c459c3496d1ba25d | https://github.com/klichukb/django-migrate-sql/blob/be48ff2c9283404e3d951128c459c3496d1ba25d/migrate_sql/autodetector.py#L198-L236 | train |
klichukb/django-migrate-sql | migrate_sql/autodetector.py | MigrationAutodetector.check_dependency | def check_dependency(self, operation, dependency):
"""
Enhances default behavior of method by checking dependency for matching operation.
"""
if isinstance(dependency[1], SQLBlob):
# NOTE: we follow the sort order created by `assemble_changes` so we build a fixed chain
# of operations. thus we should match exact operation here.
return dependency[3] == operation
return super(MigrationAutodetector, self).check_dependency(operation, dependency) | python | def check_dependency(self, operation, dependency):
"""
Enhances default behavior of method by checking dependency for matching operation.
"""
if isinstance(dependency[1], SQLBlob):
# NOTE: we follow the sort order created by `assemble_changes` so we build a fixed chain
# of operations. thus we should match exact operation here.
return dependency[3] == operation
return super(MigrationAutodetector, self).check_dependency(operation, dependency) | [
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| be48ff2c9283404e3d951128c459c3496d1ba25d | https://github.com/klichukb/django-migrate-sql/blob/be48ff2c9283404e3d951128c459c3496d1ba25d/migrate_sql/autodetector.py#L238-L246 | train |
skioo/django-customer-billing | billing/actions/credit_cards.py | reactivate | def reactivate(credit_card_id: str) -> None:
"""
Reactivates a credit card.
"""
logger.info('reactivating-credit-card', credit_card_id=credit_card_id)
with transaction.atomic():
cc = CreditCard.objects.get(pk=credit_card_id)
cc.reactivate()
cc.save() | python | def reactivate(credit_card_id: str) -> None:
"""
Reactivates a credit card.
"""
logger.info('reactivating-credit-card', credit_card_id=credit_card_id)
with transaction.atomic():
cc = CreditCard.objects.get(pk=credit_card_id)
cc.reactivate()
cc.save() | [
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| 6ac1ed9ef9d1d7eee0379de7f0c4b76919ae1f2d | https://github.com/skioo/django-customer-billing/blob/6ac1ed9ef9d1d7eee0379de7f0c4b76919ae1f2d/billing/actions/credit_cards.py#L20-L28 | train |
mgoral/subconvert | src/subconvert/parsing/Offset.py | TimeSync.sync | def sync(self, syncPointList):
"""Synchronise subtitles using a given list of SyncPoints."""
if len(syncPointList) == 0:
return
subsCopy = self._subs.clone()
syncPointList.sort()
SubAssert(syncPointList[0].subNo >= 0)
SubAssert(syncPointList[0].subNo < subsCopy.size())
SubAssert(syncPointList[-1].subNo < subsCopy.size())
# Always start from the first subtitle.
firstSyncPoint = self._getLowestSyncPoint(syncPointList, subsCopy)
if firstSyncPoint != syncPointList[0]:
syncPointList.insert(0, firstSyncPoint)
for i, syncPoint in enumerate(syncPointList):
# Algorithm:
# 1. Calculate time deltas between sync points and between subs:
# DE_OLD = subTime[secondSyncSubNo] - subTime[firstSyncSubNo]
# DE_NEW = secondSyncTime - firstSyncTime
# 2. Calculate proportional sub position within DE_OLD:
# d = (subTime - subTime[firstSubNo]) / DE_OLD
# 3. "d" is constant within deltas, so we can now calculate newSubTime:
# newSubTime = DE_NEW * d + firstSyncTime
firstSyncPoint = syncPointList[i]
secondSyncPoint = self._getSyncPointOrEnd(i + 1, syncPointList, subsCopy)
log.debug(_("Syncing times for sync points:"))
log.debug(" %s" % firstSyncPoint)
log.debug(" %s" % secondSyncPoint)
# A case for the last one syncPoint
if firstSyncPoint == secondSyncPoint:
continue
secondSubNo = secondSyncPoint.subNo
firstSubNo = firstSyncPoint.subNo
firstOldSub = subsCopy[firstSubNo]
secondOldSub = subsCopy[secondSubNo]
oldStartDelta, oldEndDelta = self._getDeltas(firstOldSub, secondOldSub)
newStartDelta, newEndDelta = self._getDeltas(firstSyncPoint, secondSyncPoint)
for subNo in range(firstSubNo, secondSubNo + 1):
sub = subsCopy[subNo]
newStartTime = self._calculateTime(sub.start, firstOldSub.start,
firstSyncPoint.start, oldStartDelta, newStartDelta)
newEndTime = self._calculateTime(sub.end, firstOldSub.end,
firstSyncPoint.end, oldEndDelta, newEndDelta)
self._subs.changeSubStart(subNo, newStartTime)
self._subs.changeSubEnd(subNo, newEndTime) | python | def sync(self, syncPointList):
"""Synchronise subtitles using a given list of SyncPoints."""
if len(syncPointList) == 0:
return
subsCopy = self._subs.clone()
syncPointList.sort()
SubAssert(syncPointList[0].subNo >= 0)
SubAssert(syncPointList[0].subNo < subsCopy.size())
SubAssert(syncPointList[-1].subNo < subsCopy.size())
# Always start from the first subtitle.
firstSyncPoint = self._getLowestSyncPoint(syncPointList, subsCopy)
if firstSyncPoint != syncPointList[0]:
syncPointList.insert(0, firstSyncPoint)
for i, syncPoint in enumerate(syncPointList):
# Algorithm:
# 1. Calculate time deltas between sync points and between subs:
# DE_OLD = subTime[secondSyncSubNo] - subTime[firstSyncSubNo]
# DE_NEW = secondSyncTime - firstSyncTime
# 2. Calculate proportional sub position within DE_OLD:
# d = (subTime - subTime[firstSubNo]) / DE_OLD
# 3. "d" is constant within deltas, so we can now calculate newSubTime:
# newSubTime = DE_NEW * d + firstSyncTime
firstSyncPoint = syncPointList[i]
secondSyncPoint = self._getSyncPointOrEnd(i + 1, syncPointList, subsCopy)
log.debug(_("Syncing times for sync points:"))
log.debug(" %s" % firstSyncPoint)
log.debug(" %s" % secondSyncPoint)
# A case for the last one syncPoint
if firstSyncPoint == secondSyncPoint:
continue
secondSubNo = secondSyncPoint.subNo
firstSubNo = firstSyncPoint.subNo
firstOldSub = subsCopy[firstSubNo]
secondOldSub = subsCopy[secondSubNo]
oldStartDelta, oldEndDelta = self._getDeltas(firstOldSub, secondOldSub)
newStartDelta, newEndDelta = self._getDeltas(firstSyncPoint, secondSyncPoint)
for subNo in range(firstSubNo, secondSubNo + 1):
sub = subsCopy[subNo]
newStartTime = self._calculateTime(sub.start, firstOldSub.start,
firstSyncPoint.start, oldStartDelta, newStartDelta)
newEndTime = self._calculateTime(sub.end, firstOldSub.end,
firstSyncPoint.end, oldEndDelta, newEndDelta)
self._subs.changeSubStart(subNo, newStartTime)
self._subs.changeSubEnd(subNo, newEndTime) | [
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| 59701e5e69ef1ca26ce7d1d766c936664aa2cb32 | https://github.com/mgoral/subconvert/blob/59701e5e69ef1ca26ce7d1d766c936664aa2cb32/src/subconvert/parsing/Offset.py#L60-L118 | train |
mgoral/subconvert | src/subconvert/parsing/Offset.py | TimeSync._getDeltas | def _getDeltas(self, firstSub, secondSub):
"""Arguments must have "start" and "end" properties which are FrameTimes."""
startDelta = max(firstSub.start, secondSub.start) - min(firstSub.start, secondSub.start)
endDelta = max(firstSub.end, secondSub.end) - min(firstSub.end, secondSub.end)
return (startDelta, endDelta) | python | def _getDeltas(self, firstSub, secondSub):
"""Arguments must have "start" and "end" properties which are FrameTimes."""
startDelta = max(firstSub.start, secondSub.start) - min(firstSub.start, secondSub.start)
endDelta = max(firstSub.end, secondSub.end) - min(firstSub.end, secondSub.end)
return (startDelta, endDelta) | [
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| 59701e5e69ef1ca26ce7d1d766c936664aa2cb32 | https://github.com/mgoral/subconvert/blob/59701e5e69ef1ca26ce7d1d766c936664aa2cb32/src/subconvert/parsing/Offset.py#L120-L124 | train |
ludeeus/GHLocalApi | ghlocalapi/scan.py | NetworkScan.scan_for_units | async def scan_for_units(self, iprange):
"""Scan local network for GH units."""
units = []
for ip_address in ipaddress.IPv4Network(iprange):
sock = socket.socket()
sock.settimeout(0.02)
host = str(ip_address)
try:
scan_result = sock.connect((host, PORT))
except socket.error:
scan_result = 1
_LOGGER.debug('Checking port connectivity on %s:%s',
host, (str(PORT)))
if scan_result is None:
ghlocalapi = DeviceInfo(self._loop, self._session, host)
await ghlocalapi.get_device_info()
data = ghlocalapi.device_info
if data is not None:
cap = data['device_info']['capabilities']
units.append({
'host': host,
'name': data['name'],
'model': data['device_info']['model_name'],
'assistant_supported': cap.get('assistant_supported',
False)
})
sock.close()
return units | python | async def scan_for_units(self, iprange):
"""Scan local network for GH units."""
units = []
for ip_address in ipaddress.IPv4Network(iprange):
sock = socket.socket()
sock.settimeout(0.02)
host = str(ip_address)
try:
scan_result = sock.connect((host, PORT))
except socket.error:
scan_result = 1
_LOGGER.debug('Checking port connectivity on %s:%s',
host, (str(PORT)))
if scan_result is None:
ghlocalapi = DeviceInfo(self._loop, self._session, host)
await ghlocalapi.get_device_info()
data = ghlocalapi.device_info
if data is not None:
cap = data['device_info']['capabilities']
units.append({
'host': host,
'name': data['name'],
'model': data['device_info']['model_name'],
'assistant_supported': cap.get('assistant_supported',
False)
})
sock.close()
return units | [
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| 93abdee299c4a4b65aa9dd03c77ec34e174e3c56 | https://github.com/ludeeus/GHLocalApi/blob/93abdee299c4a4b65aa9dd03c77ec34e174e3c56/ghlocalapi/scan.py#L24-L51 | train |
ludeeus/GHLocalApi | examples/bluetooth_scan_unit.py | bluetooth_scan | async def bluetooth_scan():
"""Get nearby bluetooth devices."""
async with aiohttp.ClientSession() as session:
ghlocalapi = Bluetooth(LOOP, session, IPADDRESS)
await ghlocalapi.scan_for_devices() # Start device scan
await ghlocalapi.get_scan_result() # Returns the result
print("Device info:", ghlocalapi.devices) | python | async def bluetooth_scan():
"""Get nearby bluetooth devices."""
async with aiohttp.ClientSession() as session:
ghlocalapi = Bluetooth(LOOP, session, IPADDRESS)
await ghlocalapi.scan_for_devices() # Start device scan
await ghlocalapi.get_scan_result() # Returns the result
print("Device info:", ghlocalapi.devices) | [
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| 93abdee299c4a4b65aa9dd03c77ec34e174e3c56 | https://github.com/ludeeus/GHLocalApi/blob/93abdee299c4a4b65aa9dd03c77ec34e174e3c56/examples/bluetooth_scan_unit.py#L9-L16 | train |
romanorac/discomll | discomll/classification/naivebayes.py | reduce_fit | def reduce_fit(interface, state, label, inp):
"""
Function separates aggregation of continuous and discrete features.
For continuous features it aggregates partially calculated means and variances and returns them. For discrete
features it aggregates pairs and returns them. Pairs with label occurrences are used to calculate prior probabilities
"""
from disco.util import kvgroup # function for grouping values by key
import numpy as np
out = interface.output(0) # all outputted pairs have the same output label
# model of naive Bayes stores label names, sum of all label occurrences and pairs
# (feature index, feature values) for discrete features which are needed to optimize predict phase.
fit_model = {"y_labels": [], "y_sum": 0, "iv": set()}
combiner = {} # combiner maintains correct order of means and variances.
means, variances = [], []
k_prev = ""
for key, value in kvgroup(inp): # input pairs are sorted and grouped by key
k_split = key.split(state["delimiter"]) # pair is split
if len(k_split) == 3: # discrete features
# store pair (feature index, feature value)
fit_model["iv"].add(tuple(k_split[1:]))
# aggregate and output occurrences of a pair
out.add(tuple(k_split), sum(value))
elif len(k_split) == 2: # continuous features
# if label is different than previous.
# This enables calculation of all variances and means for every feature for current label.
if k_split[0] != k_prev and k_prev != "":
mean, var = zip(*[combiner[key] for key in sorted(combiner.keys())])
means.append(mean)
variances.append(var)
# number of elements, partial mean, partial variance.
n_a = mean_a = var_a = 0
# code aggregates partially calculated means and variances
for n_b, mean_b, var_b in value:
n_ab = n_a + n_b
var_a = ((n_a * var_a + n_b * var_b) / float(n_ab)) + (
n_a * n_b * ((mean_b - mean_a) / float(n_ab)) ** 2)
mean_a = (n_a * mean_a + n_b * mean_b) / float(n_ab)
n_a = n_ab
# maintains correct order of statistics for every feature
combiner[int(k_split[1])] = (mean_a, var_a + 1e-9)
k_prev = k_split[0]
else: # aggregates label occurrences
fit_model[key] = np.sum(value)
fit_model["y_sum"] += fit_model[key] # sum of all label occurrences
fit_model["y_labels"].append(key)
# if statistics for continuous features were not output in last iteration
if len(means) > 0:
mean, var = zip(*[combiner[key] for key in sorted(combiner.keys())])
out.add("mean", np.array(means + [mean], dtype=np.float32))
variances = np.array(variances + [var], dtype=np.float32)
out.add("var", variances)
out.add("var_log", np.log(np.pi * variances))
# calculation of prior probabilities
prior = [fit_model[y_label] / float(fit_model["y_sum"]) for y_label in fit_model["y_labels"]]
out.add("prior", np.array(prior, dtype=np.float32))
out.add("prior_log", np.log(prior))
out.add("iv", list(fit_model["iv"]))
out.add("y_labels", fit_model["y_labels"]) | python | def reduce_fit(interface, state, label, inp):
"""
Function separates aggregation of continuous and discrete features.
For continuous features it aggregates partially calculated means and variances and returns them. For discrete
features it aggregates pairs and returns them. Pairs with label occurrences are used to calculate prior probabilities
"""
from disco.util import kvgroup # function for grouping values by key
import numpy as np
out = interface.output(0) # all outputted pairs have the same output label
# model of naive Bayes stores label names, sum of all label occurrences and pairs
# (feature index, feature values) for discrete features which are needed to optimize predict phase.
fit_model = {"y_labels": [], "y_sum": 0, "iv": set()}
combiner = {} # combiner maintains correct order of means and variances.
means, variances = [], []
k_prev = ""
for key, value in kvgroup(inp): # input pairs are sorted and grouped by key
k_split = key.split(state["delimiter"]) # pair is split
if len(k_split) == 3: # discrete features
# store pair (feature index, feature value)
fit_model["iv"].add(tuple(k_split[1:]))
# aggregate and output occurrences of a pair
out.add(tuple(k_split), sum(value))
elif len(k_split) == 2: # continuous features
# if label is different than previous.
# This enables calculation of all variances and means for every feature for current label.
if k_split[0] != k_prev and k_prev != "":
mean, var = zip(*[combiner[key] for key in sorted(combiner.keys())])
means.append(mean)
variances.append(var)
# number of elements, partial mean, partial variance.
n_a = mean_a = var_a = 0
# code aggregates partially calculated means and variances
for n_b, mean_b, var_b in value:
n_ab = n_a + n_b
var_a = ((n_a * var_a + n_b * var_b) / float(n_ab)) + (
n_a * n_b * ((mean_b - mean_a) / float(n_ab)) ** 2)
mean_a = (n_a * mean_a + n_b * mean_b) / float(n_ab)
n_a = n_ab
# maintains correct order of statistics for every feature
combiner[int(k_split[1])] = (mean_a, var_a + 1e-9)
k_prev = k_split[0]
else: # aggregates label occurrences
fit_model[key] = np.sum(value)
fit_model["y_sum"] += fit_model[key] # sum of all label occurrences
fit_model["y_labels"].append(key)
# if statistics for continuous features were not output in last iteration
if len(means) > 0:
mean, var = zip(*[combiner[key] for key in sorted(combiner.keys())])
out.add("mean", np.array(means + [mean], dtype=np.float32))
variances = np.array(variances + [var], dtype=np.float32)
out.add("var", variances)
out.add("var_log", np.log(np.pi * variances))
# calculation of prior probabilities
prior = [fit_model[y_label] / float(fit_model["y_sum"]) for y_label in fit_model["y_labels"]]
out.add("prior", np.array(prior, dtype=np.float32))
out.add("prior_log", np.log(prior))
out.add("iv", list(fit_model["iv"]))
out.add("y_labels", fit_model["y_labels"]) | [
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For continuous features it aggregates partially calculated means and variances and returns them. For discrete
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| a4703daffb2ba3c9f614bc3dbe45ae55884aea00 | https://github.com/romanorac/discomll/blob/a4703daffb2ba3c9f614bc3dbe45ae55884aea00/discomll/classification/naivebayes.py#L60-L128 | train |
romanorac/discomll | discomll/classification/naivebayes.py | map_predict | def map_predict(interface, state, label, inp):
"""
Function makes a predictions of samples with given model. It calculates probabilities with multinomial and Gaussian distribution.
"""
import numpy as np
out = interface.output(0)
continuous = [j for i, j in enumerate(state["X_indices"]) if
state["X_meta"][i] == "c"] # indices of continuous features
discrete = [j for i, j in enumerate(state["X_indices"]) if
state["X_meta"][i] == "d"] # indices of discrete features
cont = True if len(continuous) > 0 else False # enables calculation of Gaussian probabilities
disc = True if len(discrete) > 0 else False # enables calculation of multinomial probabilities.
for row in inp:
row = row.strip().split(state["delimiter"])
if len(row) > 1: # if row is empty
# set id of a sample
x_id = "" if state["id_index"] == -1 else row[state["id_index"]]
# initialize prior probability for all labels
probs = state["fit_model"]["prior_log"]
if cont: # continuous features
x = np.array([(0 if row[j] in state["missing_vals"] else float(row[j])) for j in
continuous]) # sets selected features of the sample
# Gaussian distribution
probs = probs - 0.5 * np.sum(
np.true_divide((x - state["fit_model"]["mean"]) ** 2, state["fit_model"]["var"]) +
state["fit_model"]["var_log"], axis=1)
if disc: # discrete features
# multinomial distribution
probs = probs + np.sum(
[(0 if row[i] in state["missing_vals"] else state["fit_model"].get((str(i), row[i]), np.zeros(1)))
for i in discrete], axis=0)
# normalize by P(x) = P(f_1, ..., f_n)
log_prob_x = np.log(np.sum(np.exp(probs)))
probs = np.exp(np.array(probs) - log_prob_x)
# Predicted label is the one with highest probability
y_predicted = max(zip(probs, state["fit_model"]["y_labels"]))[1]
out.add(x_id, (y_predicted, probs.tolist())) | python | def map_predict(interface, state, label, inp):
"""
Function makes a predictions of samples with given model. It calculates probabilities with multinomial and Gaussian distribution.
"""
import numpy as np
out = interface.output(0)
continuous = [j for i, j in enumerate(state["X_indices"]) if
state["X_meta"][i] == "c"] # indices of continuous features
discrete = [j for i, j in enumerate(state["X_indices"]) if
state["X_meta"][i] == "d"] # indices of discrete features
cont = True if len(continuous) > 0 else False # enables calculation of Gaussian probabilities
disc = True if len(discrete) > 0 else False # enables calculation of multinomial probabilities.
for row in inp:
row = row.strip().split(state["delimiter"])
if len(row) > 1: # if row is empty
# set id of a sample
x_id = "" if state["id_index"] == -1 else row[state["id_index"]]
# initialize prior probability for all labels
probs = state["fit_model"]["prior_log"]
if cont: # continuous features
x = np.array([(0 if row[j] in state["missing_vals"] else float(row[j])) for j in
continuous]) # sets selected features of the sample
# Gaussian distribution
probs = probs - 0.5 * np.sum(
np.true_divide((x - state["fit_model"]["mean"]) ** 2, state["fit_model"]["var"]) +
state["fit_model"]["var_log"], axis=1)
if disc: # discrete features
# multinomial distribution
probs = probs + np.sum(
[(0 if row[i] in state["missing_vals"] else state["fit_model"].get((str(i), row[i]), np.zeros(1)))
for i in discrete], axis=0)
# normalize by P(x) = P(f_1, ..., f_n)
log_prob_x = np.log(np.sum(np.exp(probs)))
probs = np.exp(np.array(probs) - log_prob_x)
# Predicted label is the one with highest probability
y_predicted = max(zip(probs, state["fit_model"]["y_labels"]))[1]
out.add(x_id, (y_predicted, probs.tolist())) | [
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| a4703daffb2ba3c9f614bc3dbe45ae55884aea00 | https://github.com/romanorac/discomll/blob/a4703daffb2ba3c9f614bc3dbe45ae55884aea00/discomll/classification/naivebayes.py#L131-L173 | train |
romanorac/discomll | discomll/classification/naivebayes.py | predict | def predict(dataset, fitmodel_url, m=1, save_results=True, show=False):
"""
Function starts a job that makes predictions to input data with a given model
Parameters
----------
input - dataset object with input urls and other parameters
fitmodel_url - model created in fit phase
m - m estimate is used with discrete features
save_results - save results to ddfs
show - show info about job execution
Returns
-------
Urls of predictions on ddfs
"""
from disco.worker.pipeline.worker import Worker, Stage
from disco.core import Job, result_iterator
import numpy as np
try:
m = float(m)
except ValueError:
raise Exception("Parameter m should be numerical.")
if "naivebayes_fitmodel" in fitmodel_url:
# fit model is loaded from ddfs
fit_model = dict((k, v) for k, v in result_iterator(fitmodel_url["naivebayes_fitmodel"]))
if len(fit_model["y_labels"]) < 2:
print "There is only one class in training data."
return []
else:
raise Exception("Incorrect fit model.")
if dataset.params["X_meta"].count("d") > 0: # if there are discrete features in the model
# code calculates logarithms to optimize predict phase as opposed to calculation by every mapped.
np.seterr(divide='ignore')
for iv in fit_model["iv"]:
dist = [fit_model.pop((y,) + iv, 0) for y in fit_model["y_labels"]]
fit_model[iv] = np.nan_to_num(
np.log(np.true_divide(np.array(dist) + m * fit_model["prior"], np.sum(dist) + m))) - fit_model[
"prior_log"]
del (fit_model["iv"])
# define a job and set save of results to ddfs
job = Job(worker=Worker(save_results=save_results))
# job parallelizes execution of mappers
job.pipeline = [
("split", Stage("map", input_chain=dataset.params["input_chain"], init=simple_init, process=map_predict))]
job.params = dataset.params # job parameters (dataset object)
job.params["fit_model"] = fit_model
# define name of a job and input data urls
job.run(name="naivebayes_predict", input=dataset.params["data_tag"])
results = job.wait(show=show)
return results | python | def predict(dataset, fitmodel_url, m=1, save_results=True, show=False):
"""
Function starts a job that makes predictions to input data with a given model
Parameters
----------
input - dataset object with input urls and other parameters
fitmodel_url - model created in fit phase
m - m estimate is used with discrete features
save_results - save results to ddfs
show - show info about job execution
Returns
-------
Urls of predictions on ddfs
"""
from disco.worker.pipeline.worker import Worker, Stage
from disco.core import Job, result_iterator
import numpy as np
try:
m = float(m)
except ValueError:
raise Exception("Parameter m should be numerical.")
if "naivebayes_fitmodel" in fitmodel_url:
# fit model is loaded from ddfs
fit_model = dict((k, v) for k, v in result_iterator(fitmodel_url["naivebayes_fitmodel"]))
if len(fit_model["y_labels"]) < 2:
print "There is only one class in training data."
return []
else:
raise Exception("Incorrect fit model.")
if dataset.params["X_meta"].count("d") > 0: # if there are discrete features in the model
# code calculates logarithms to optimize predict phase as opposed to calculation by every mapped.
np.seterr(divide='ignore')
for iv in fit_model["iv"]:
dist = [fit_model.pop((y,) + iv, 0) for y in fit_model["y_labels"]]
fit_model[iv] = np.nan_to_num(
np.log(np.true_divide(np.array(dist) + m * fit_model["prior"], np.sum(dist) + m))) - fit_model[
"prior_log"]
del (fit_model["iv"])
# define a job and set save of results to ddfs
job = Job(worker=Worker(save_results=save_results))
# job parallelizes execution of mappers
job.pipeline = [
("split", Stage("map", input_chain=dataset.params["input_chain"], init=simple_init, process=map_predict))]
job.params = dataset.params # job parameters (dataset object)
job.params["fit_model"] = fit_model
# define name of a job and input data urls
job.run(name="naivebayes_predict", input=dataset.params["data_tag"])
results = job.wait(show=show)
return results | [
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show - show info about job execution
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Urls of predictions on ddfs | [
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| a4703daffb2ba3c9f614bc3dbe45ae55884aea00 | https://github.com/romanorac/discomll/blob/a4703daffb2ba3c9f614bc3dbe45ae55884aea00/discomll/classification/naivebayes.py#L208-L264 | train |
pneff/wsgiservice | wsgiservice/resource.py | Resource.data | def data(self):
"""Returns the request data as a dictionary.
Merges the path parameters, GET parameters and POST parameters
(form-encoded or JSON dictionary). If a key is present in multiple of
these, the first one defined is used.
"""
if self._data:
return self._data
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data = self.get_request_data()
for subdata in data:
for key, value in subdata.iteritems():
if not key in retval:
retval[key] = value
self._data = retval
return retval | python | def data(self):
"""Returns the request data as a dictionary.
Merges the path parameters, GET parameters and POST parameters
(form-encoded or JSON dictionary). If a key is present in multiple of
these, the first one defined is used.
"""
if self._data:
return self._data
retval = {}
data = self.get_request_data()
for subdata in data:
for key, value in subdata.iteritems():
if not key in retval:
retval[key] = value
self._data = retval
return retval | [
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| 03c064ac2e8c53a1aac9c7b99970f23cf79e20f4 | https://github.com/pneff/wsgiservice/blob/03c064ac2e8c53a1aac9c7b99970f23cf79e20f4/wsgiservice/resource.py#L157-L175 | train |
pneff/wsgiservice | wsgiservice/resource.py | Resource.get_resource | def get_resource(self, resource, **kwargs):
"""Returns a new instance of the resource class passed in as resource.
This is a helper to make future-compatibility easier when new
arguments get added to the constructor.
:param resource: Resource class to instantiate. Gets called with the
named arguments as required for the constructor.
:type resource: :class:`Resource`
:param kwargs: Additional named arguments to pass to the constructor
function.
:type kwargs: dict
"""
return resource(request=self.request, response=self.response,
path_params=self.path_params, application=self.application,
**kwargs) | python | def get_resource(self, resource, **kwargs):
"""Returns a new instance of the resource class passed in as resource.
This is a helper to make future-compatibility easier when new
arguments get added to the constructor.
:param resource: Resource class to instantiate. Gets called with the
named arguments as required for the constructor.
:type resource: :class:`Resource`
:param kwargs: Additional named arguments to pass to the constructor
function.
:type kwargs: dict
"""
return resource(request=self.request, response=self.response,
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| 03c064ac2e8c53a1aac9c7b99970f23cf79e20f4 | https://github.com/pneff/wsgiservice/blob/03c064ac2e8c53a1aac9c7b99970f23cf79e20f4/wsgiservice/resource.py#L177-L191 | train |
pneff/wsgiservice | wsgiservice/resource.py | Resource.assert_conditions | def assert_conditions(self):
"""Handles various HTTP conditions and raises HTTP exceptions to
abort the request.
- Content-MD5 request header must match the MD5 hash of the full
input (:func:`assert_condition_md5`).
- If-Match and If-None-Match etags are checked against the ETag of
this resource (:func:`assert_condition_etag`).
- If-Modified-Since and If-Unmodified-Since are checked against
the modification date of this resource
(:func:`assert_condition_last_modified`).
.. todo:: Return a 501 exception when any Content-* headers have been
set in the request. (See :rfc:`2616`, section 9.6)
"""
self.assert_condition_md5()
etag = self.clean_etag(self.call_method('get_etag'))
self.response.last_modified = self.call_method('get_last_modified')
self.assert_condition_etag()
self.assert_condition_last_modified() | python | def assert_conditions(self):
"""Handles various HTTP conditions and raises HTTP exceptions to
abort the request.
- Content-MD5 request header must match the MD5 hash of the full
input (:func:`assert_condition_md5`).
- If-Match and If-None-Match etags are checked against the ETag of
this resource (:func:`assert_condition_etag`).
- If-Modified-Since and If-Unmodified-Since are checked against
the modification date of this resource
(:func:`assert_condition_last_modified`).
.. todo:: Return a 501 exception when any Content-* headers have been
set in the request. (See :rfc:`2616`, section 9.6)
"""
self.assert_condition_md5()
etag = self.clean_etag(self.call_method('get_etag'))
self.response.last_modified = self.call_method('get_last_modified')
self.assert_condition_etag()
self.assert_condition_last_modified() | [
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| 03c064ac2e8c53a1aac9c7b99970f23cf79e20f4 | https://github.com/pneff/wsgiservice/blob/03c064ac2e8c53a1aac9c7b99970f23cf79e20f4/wsgiservice/resource.py#L258-L277 | train |
pneff/wsgiservice | wsgiservice/resource.py | Resource.assert_condition_md5 | def assert_condition_md5(self):
"""If the ``Content-MD5`` request header is present in the request
it's verified against the MD5 hash of the request body. If they don't
match, a 400 HTTP response is returned.
:raises: :class:`webob.exceptions.ResponseException` of status 400 if
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"""
if 'Content-MD5' in self.request.headers:
body_md5 = hashlib.md5(self.request.body).hexdigest()
if body_md5 != self.request.headers['Content-MD5']:
raise_400(self, msg='Invalid Content-MD5 request header.') | python | def assert_condition_md5(self):
"""If the ``Content-MD5`` request header is present in the request
it's verified against the MD5 hash of the request body. If they don't
match, a 400 HTTP response is returned.
:raises: :class:`webob.exceptions.ResponseException` of status 400 if
the MD5 hash does not match the body.
"""
if 'Content-MD5' in self.request.headers:
body_md5 = hashlib.md5(self.request.body).hexdigest()
if body_md5 != self.request.headers['Content-MD5']:
raise_400(self, msg='Invalid Content-MD5 request header.') | [
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| 03c064ac2e8c53a1aac9c7b99970f23cf79e20f4 | https://github.com/pneff/wsgiservice/blob/03c064ac2e8c53a1aac9c7b99970f23cf79e20f4/wsgiservice/resource.py#L279-L290 | train |
pneff/wsgiservice | wsgiservice/resource.py | Resource.get_allowed_methods | def get_allowed_methods(self):
"""Returns a coma-separated list of method names that are allowed on
this instance. Useful to set the ``Allowed`` response header.
"""
return ", ".join([method for method in dir(self)
if method.upper() == method
and callable(getattr(self, method))]) | python | def get_allowed_methods(self):
"""Returns a coma-separated list of method names that are allowed on
this instance. Useful to set the ``Allowed`` response header.
"""
return ", ".join([method for method in dir(self)
if method.upper() == method
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| 03c064ac2e8c53a1aac9c7b99970f23cf79e20f4 | https://github.com/pneff/wsgiservice/blob/03c064ac2e8c53a1aac9c7b99970f23cf79e20f4/wsgiservice/resource.py#L373-L379 | train |
pneff/wsgiservice | wsgiservice/resource.py | Resource.convert_param | def convert_param(self, method, param, value):
"""Converts the parameter using the function 'convert' function of the
validation rules. Same parameters as the `validate_param` method, so
it might have just been added there. But lumping together the two
functionalities would make overwriting harder.
:param method: A function to get the validation information from (done
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:type method: Python function
:param param: Name of the parameter to validate the value for.
:type param: str
:param value: Value passed in for the given parameter.
:type value: Any valid Python value
:raises: :class:`wsgiservice.exceptions.ValidationException` if the
value is invalid for the given method and parameter.
"""
rules = self._get_validation(method, param)
if not rules or not rules.get('convert'):
return value
try:
return rules['convert'](value)
except ValueError:
raise ValidationException(
"{0} value {1} does not validate.".format(param, value)) | python | def convert_param(self, method, param, value):
"""Converts the parameter using the function 'convert' function of the
validation rules. Same parameters as the `validate_param` method, so
it might have just been added there. But lumping together the two
functionalities would make overwriting harder.
:param method: A function to get the validation information from (done
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:type method: Python function
:param param: Name of the parameter to validate the value for.
:type param: str
:param value: Value passed in for the given parameter.
:type value: Any valid Python value
:raises: :class:`wsgiservice.exceptions.ValidationException` if the
value is invalid for the given method and parameter.
"""
rules = self._get_validation(method, param)
if not rules or not rules.get('convert'):
return value
try:
return rules['convert'](value)
except ValueError:
raise ValidationException(
"{0} value {1} does not validate.".format(param, value)) | [
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| 03c064ac2e8c53a1aac9c7b99970f23cf79e20f4 | https://github.com/pneff/wsgiservice/blob/03c064ac2e8c53a1aac9c7b99970f23cf79e20f4/wsgiservice/resource.py#L442-L466 | train |
pneff/wsgiservice | wsgiservice/resource.py | Resource._get_validation | def _get_validation(self, method, param):
"""Return the correct validations dictionary for this parameter.
First checks the method itself and then its class. If no validation is
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:param method: A function to get the validation information from.
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:type param: str
"""
if hasattr(method, '_validations') and param in method._validations:
return method._validations[param]
elif (hasattr(method.im_class, '_validations') and
param in method.im_class._validations):
return method.im_class._validations[param]
else:
return None | python | def _get_validation(self, method, param):
"""Return the correct validations dictionary for this parameter.
First checks the method itself and then its class. If no validation is
defined for this parameter, None is returned.
:param method: A function to get the validation information from.
:type method: Python function
:param param: Name of the parameter to get validation information for.
:type param: str
"""
if hasattr(method, '_validations') and param in method._validations:
return method._validations[param]
elif (hasattr(method.im_class, '_validations') and
param in method.im_class._validations):
return method.im_class._validations[param]
else:
return None | [
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| 03c064ac2e8c53a1aac9c7b99970f23cf79e20f4 | https://github.com/pneff/wsgiservice/blob/03c064ac2e8c53a1aac9c7b99970f23cf79e20f4/wsgiservice/resource.py#L468-L484 | train |
pneff/wsgiservice | wsgiservice/resource.py | Resource.convert_response | def convert_response(self):
"""Finish filling the instance's response object so it's ready to be
served to the client. This includes converting the body_raw property
to the content type requested by the user if necessary.
"""
if hasattr(self.response, 'body_raw'):
if self.response.body_raw is not None:
to_type = re.sub('[^a-zA-Z_]', '_', self.type)
to_type_method = 'to_' + to_type
if hasattr(self, to_type_method):
self.response.body = getattr(self, to_type_method)(
self.response.body_raw)
del self.response.body_raw | python | def convert_response(self):
"""Finish filling the instance's response object so it's ready to be
served to the client. This includes converting the body_raw property
to the content type requested by the user if necessary.
"""
if hasattr(self.response, 'body_raw'):
if self.response.body_raw is not None:
to_type = re.sub('[^a-zA-Z_]', '_', self.type)
to_type_method = 'to_' + to_type
if hasattr(self, to_type_method):
self.response.body = getattr(self, to_type_method)(
self.response.body_raw)
del self.response.body_raw | [
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| 03c064ac2e8c53a1aac9c7b99970f23cf79e20f4 | https://github.com/pneff/wsgiservice/blob/03c064ac2e8c53a1aac9c7b99970f23cf79e20f4/wsgiservice/resource.py#L486-L498 | train |
pneff/wsgiservice | wsgiservice/resource.py | Resource.handle_exception | def handle_exception(self, e, status=500):
"""Handle the given exception. Log, sets the response code and
output the exception message as an error message.
:param e: Exception which is being handled.
:type e: :class:`Exception`
:param status: Status code to set.
:type status: int
"""
logger.exception(
"An exception occurred while handling the request: %s", e)
self.response.body_raw = {'error': str(e)}
self.response.status = status | python | def handle_exception(self, e, status=500):
"""Handle the given exception. Log, sets the response code and
output the exception message as an error message.
:param e: Exception which is being handled.
:type e: :class:`Exception`
:param status: Status code to set.
:type status: int
"""
logger.exception(
"An exception occurred while handling the request: %s", e)
self.response.body_raw = {'error': str(e)}
self.response.status = status | [
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| 03c064ac2e8c53a1aac9c7b99970f23cf79e20f4 | https://github.com/pneff/wsgiservice/blob/03c064ac2e8c53a1aac9c7b99970f23cf79e20f4/wsgiservice/resource.py#L525-L537 | train |
pneff/wsgiservice | wsgiservice/resource.py | Resource.handle_exception_404 | def handle_exception_404(self, e):
"""Handle the given exception. Log, sets the response code to 404 and
output the exception message as an error message.
:param e: Exception which is being handled.
:type e: :class:`Exception`
"""
logger.debug("A 404 Not Found exception occurred while handling "
"the request.")
self.response.body_raw = {'error': 'Not Found'}
self.response.status = 404 | python | def handle_exception_404(self, e):
"""Handle the given exception. Log, sets the response code to 404 and
output the exception message as an error message.
:param e: Exception which is being handled.
:type e: :class:`Exception`
"""
logger.debug("A 404 Not Found exception occurred while handling "
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self.response.body_raw = {'error': 'Not Found'}
self.response.status = 404 | [
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| 03c064ac2e8c53a1aac9c7b99970f23cf79e20f4 | https://github.com/pneff/wsgiservice/blob/03c064ac2e8c53a1aac9c7b99970f23cf79e20f4/wsgiservice/resource.py#L539-L549 | train |
pneff/wsgiservice | wsgiservice/resource.py | Resource.set_response_content_md5 | def set_response_content_md5(self):
"""Set the Content-MD5 response header. Calculated from the the
response body by creating the MD5 hash from it.
"""
self.response.content_md5 = hashlib.md5(self.response.body).hexdigest() | python | def set_response_content_md5(self):
"""Set the Content-MD5 response header. Calculated from the the
response body by creating the MD5 hash from it.
"""
self.response.content_md5 = hashlib.md5(self.response.body).hexdigest() | [
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| 03c064ac2e8c53a1aac9c7b99970f23cf79e20f4 | https://github.com/pneff/wsgiservice/blob/03c064ac2e8c53a1aac9c7b99970f23cf79e20f4/wsgiservice/resource.py#L569-L573 | train |
pneff/wsgiservice | wsgiservice/resource.py | Resource.get_request_data | def get_request_data(self):
"""
Read the input values.
Returns a list of dictionaries. These will be used to automatically
pass them into the method.
Additionally a combined dictionary is written to `self.data`.
In the case of JSON input, that element in this list will be the parsed
JSON value. That may not be a dictionary.
"""
request_data = [self.path_params, self.request.GET]
if self.request.headers.get('Content-Type') == 'application/json' \
and self.request.body:
try:
post = json.loads(self.request.body)
except ValueError:
raise_400(self, msg='Invalid JSON content data')
if isinstance(post, dict):
request_data.append(post)
else:
request_data.append(self.request.POST)
return request_data | python | def get_request_data(self):
"""
Read the input values.
Returns a list of dictionaries. These will be used to automatically
pass them into the method.
Additionally a combined dictionary is written to `self.data`.
In the case of JSON input, that element in this list will be the parsed
JSON value. That may not be a dictionary.
"""
request_data = [self.path_params, self.request.GET]
if self.request.headers.get('Content-Type') == 'application/json' \
and self.request.body:
try:
post = json.loads(self.request.body)
except ValueError:
raise_400(self, msg='Invalid JSON content data')
if isinstance(post, dict):
request_data.append(post)
else:
request_data.append(self.request.POST)
return request_data | [
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| 03c064ac2e8c53a1aac9c7b99970f23cf79e20f4 | https://github.com/pneff/wsgiservice/blob/03c064ac2e8c53a1aac9c7b99970f23cf79e20f4/wsgiservice/resource.py#L575-L600 | train |
pneff/wsgiservice | wsgiservice/resource.py | Resource._merge_defaults | def _merge_defaults(self, data, method_params, defaults):
"""Helper method for adding default values to the data dictionary.
The `defaults` are the default values inspected from the method that
will be called. For any values that are not present in the incoming
data, the default value is added.
"""
if defaults:
optional_args = method_params[-len(defaults):]
for key, value in zip(optional_args, defaults):
if not key in data:
data[key] = value
return data | python | def _merge_defaults(self, data, method_params, defaults):
"""Helper method for adding default values to the data dictionary.
The `defaults` are the default values inspected from the method that
will be called. For any values that are not present in the incoming
data, the default value is added.
"""
if defaults:
optional_args = method_params[-len(defaults):]
for key, value in zip(optional_args, defaults):
if not key in data:
data[key] = value
return data | [
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| 03c064ac2e8c53a1aac9c7b99970f23cf79e20f4 | https://github.com/pneff/wsgiservice/blob/03c064ac2e8c53a1aac9c7b99970f23cf79e20f4/wsgiservice/resource.py#L602-L614 | train |
mouradmourafiq/pandas2sklearn | pandas_sklearn/__init__.py | DataSetTransformer._get_columns | def _get_columns(self, X, cols):
"""
Get a subset of columns from the given table X.
X a Pandas dataframe; the table to select columns from
cols a string or list of strings representing the columns
to select
Returns a numpy array with the data from the selected columns
"""
if isinstance(X, DataSet):
X = X[cols]
return_vector = False
if isinstance(cols, basestring):
return_vector = True
cols = [cols]
if isinstance(X, list):
X = [x[cols] for x in X]
X = pd.DataFrame(X)
if return_vector:
t = X[cols[0]]
else:
t = X.as_matrix(cols)
return t | python | def _get_columns(self, X, cols):
"""
Get a subset of columns from the given table X.
X a Pandas dataframe; the table to select columns from
cols a string or list of strings representing the columns
to select
Returns a numpy array with the data from the selected columns
"""
if isinstance(X, DataSet):
X = X[cols]
return_vector = False
if isinstance(cols, basestring):
return_vector = True
cols = [cols]
if isinstance(X, list):
X = [x[cols] for x in X]
X = pd.DataFrame(X)
if return_vector:
t = X[cols[0]]
else:
t = X.as_matrix(cols)
return t | [
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| dbaf5180a893f4612852c1c217551b161fd519d4 | https://github.com/mouradmourafiq/pandas2sklearn/blob/dbaf5180a893f4612852c1c217551b161fd519d4/pandas_sklearn/__init__.py#L181-L206 | train |
mkoura/dump2polarion | dump2polarion/exporters/requirements_exporter.py | RequirementExport._requirement_element | def _requirement_element(self, parent_element, req_data):
"""Adds requirement XML element."""
req_data = self._transform_result(req_data)
if not req_data:
return
title = req_data.get("title")
if not title:
logger.warning("Skipping requirement, title is missing")
return
req_id = req_data.get("id")
if not self._check_lookup_prop(req_id):
logger.warning(
"Skipping requirement `%s`, data missing for selected lookup method", title
)
return
attrs, custom_fields = self._classify_data(req_data)
attrs, custom_fields = self._fill_defaults(attrs, custom_fields)
# For testing purposes, the order of fields in resulting XML
# needs to be always the same.
attrs = OrderedDict(sorted(attrs.items()))
custom_fields = OrderedDict(sorted(custom_fields.items()))
requirement = etree.SubElement(parent_element, "requirement", attrs)
title_el = etree.SubElement(requirement, "title")
title_el.text = title
description = req_data.get("description")
if description:
description_el = etree.SubElement(requirement, "description")
description_el.text = description
self._fill_custom_fields(requirement, custom_fields) | python | def _requirement_element(self, parent_element, req_data):
"""Adds requirement XML element."""
req_data = self._transform_result(req_data)
if not req_data:
return
title = req_data.get("title")
if not title:
logger.warning("Skipping requirement, title is missing")
return
req_id = req_data.get("id")
if not self._check_lookup_prop(req_id):
logger.warning(
"Skipping requirement `%s`, data missing for selected lookup method", title
)
return
attrs, custom_fields = self._classify_data(req_data)
attrs, custom_fields = self._fill_defaults(attrs, custom_fields)
# For testing purposes, the order of fields in resulting XML
# needs to be always the same.
attrs = OrderedDict(sorted(attrs.items()))
custom_fields = OrderedDict(sorted(custom_fields.items()))
requirement = etree.SubElement(parent_element, "requirement", attrs)
title_el = etree.SubElement(requirement, "title")
title_el.text = title
description = req_data.get("description")
if description:
description_el = etree.SubElement(requirement, "description")
description_el.text = description
self._fill_custom_fields(requirement, custom_fields) | [
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| f4bd24e9d5070e282aad15f1e8bb514c0525cd37 | https://github.com/mkoura/dump2polarion/blob/f4bd24e9d5070e282aad15f1e8bb514c0525cd37/dump2polarion/exporters/requirements_exporter.py#L159-L195 | train |
mkoura/dump2polarion | dump2polarion/exporters/requirements_exporter.py | RequirementExport.export | def export(self):
"""Returns requirements XML."""
top = self._top_element()
properties = self._properties_element(top)
self._fill_requirements(top)
self._fill_lookup_prop(properties)
return utils.prettify_xml(top) | python | def export(self):
"""Returns requirements XML."""
top = self._top_element()
properties = self._properties_element(top)
self._fill_requirements(top)
self._fill_lookup_prop(properties)
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| f4bd24e9d5070e282aad15f1e8bb514c0525cd37 | https://github.com/mkoura/dump2polarion/blob/f4bd24e9d5070e282aad15f1e8bb514c0525cd37/dump2polarion/exporters/requirements_exporter.py#L203-L209 | train |
mkoura/dump2polarion | dump2polarion/exporters/requirements_exporter.py | RequirementExport.write_xml | def write_xml(xml, output_file=None):
"""Outputs the XML content into a file."""
gen_filename = "requirements-{:%Y%m%d%H%M%S}.xml".format(datetime.datetime.now())
utils.write_xml(xml, output_loc=output_file, filename=gen_filename) | python | def write_xml(xml, output_file=None):
"""Outputs the XML content into a file."""
gen_filename = "requirements-{:%Y%m%d%H%M%S}.xml".format(datetime.datetime.now())
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SpringerPE/python-cfconfigurator | cfconfigurator/uaa.py | UAA._client | def _client(self, id, secret):
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url = self.api_url + self.auth_token_url
auth_string = '%s:%s' % (id, secret)
authorization = base64.b64encode(auth_string.encode()).decode()
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}
params = {
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'response_type': 'token'
}
return self.session.post(url, params=params, headers=headers) | python | def _client(self, id, secret):
"""Performs client login with the provided credentials"""
url = self.api_url + self.auth_token_url
auth_string = '%s:%s' % (id, secret)
authorization = base64.b64encode(auth_string.encode()).decode()
headers = {
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'Content-Type': "application/x-www-form-urlencoded"
}
params = {
'grant_type': 'client_credentials',
'response_type': 'token'
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return self.session.post(url, params=params, headers=headers) | [
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oemof/oemof.db | oemof/db/feedin_pg.py | Feedin.aggregate_cap_val | def aggregate_cap_val(self, conn, **kwargs):
'''
Returns the normalised feedin profile and installed capacity for
a given region.
Parameters
----------
region : Region instance
region.geom : shapely.geometry object
Geo-spatial data with information for location/region-shape. The
geometry can be a polygon/multi-polygon or a point.
Returns
-------
feedin_df : pandas dataframe
Dataframe containing the normalised feedin profile of the given
region. Index of the dataframe is the hour of the year; columns
are 'pv_pwr' and 'wind_pwr'.
cap : pandas series
Series containing the installed capacity (in W) of PV and wind
turbines of the given region.
'''
region = kwargs['region']
[pv_df, wind_df, cap] = self.get_timeseries(
conn,
geometry=region.geom,
**kwargs)
if kwargs.get('store', False):
self.store_full_df(pv_df, wind_df, **kwargs)
# Summerize the results to one column for pv and one for wind
cap = cap.sum()
df = pd.concat([pv_df.sum(axis=1) / cap['pv_pwr'],
wind_df.sum(axis=1) / cap['wind_pwr']], axis=1)
feedin_df = df.rename(columns={0: 'pv_pwr', 1: 'wind_pwr'})
return feedin_df, cap | python | def aggregate_cap_val(self, conn, **kwargs):
'''
Returns the normalised feedin profile and installed capacity for
a given region.
Parameters
----------
region : Region instance
region.geom : shapely.geometry object
Geo-spatial data with information for location/region-shape. The
geometry can be a polygon/multi-polygon or a point.
Returns
-------
feedin_df : pandas dataframe
Dataframe containing the normalised feedin profile of the given
region. Index of the dataframe is the hour of the year; columns
are 'pv_pwr' and 'wind_pwr'.
cap : pandas series
Series containing the installed capacity (in W) of PV and wind
turbines of the given region.
'''
region = kwargs['region']
[pv_df, wind_df, cap] = self.get_timeseries(
conn,
geometry=region.geom,
**kwargs)
if kwargs.get('store', False):
self.store_full_df(pv_df, wind_df, **kwargs)
# Summerize the results to one column for pv and one for wind
cap = cap.sum()
df = pd.concat([pv_df.sum(axis=1) / cap['pv_pwr'],
wind_df.sum(axis=1) / cap['wind_pwr']], axis=1)
feedin_df = df.rename(columns={0: 'pv_pwr', 1: 'wind_pwr'})
return feedin_df, cap | [
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| d51ac50187f03a875bd7ce5991ed4772e8b77b93 | https://github.com/oemof/oemof.db/blob/d51ac50187f03a875bd7ce5991ed4772e8b77b93/oemof/db/feedin_pg.py#L21-L58 | train |
davidfokkema/artist | artist/multi_plot.py | MultiPlot.save_assets | def save_assets(self, dest_path):
"""Save plot assets alongside dest_path.
Some plots may have assets, like bitmap files, which need to be
saved alongside the rendered plot file.
:param dest_path: path of the main output file.
"""
for idx, subplot in enumerate(self.subplots):
subplot.save_assets(dest_path, suffix='_%d' % idx) | python | def save_assets(self, dest_path):
"""Save plot assets alongside dest_path.
Some plots may have assets, like bitmap files, which need to be
saved alongside the rendered plot file.
:param dest_path: path of the main output file.
"""
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| 26ae7987522622710f2910980770c50012fda47d | https://github.com/davidfokkema/artist/blob/26ae7987522622710f2910980770c50012fda47d/artist/multi_plot.py#L65-L75 | train |
davidfokkema/artist | artist/multi_plot.py | MultiPlot.set_empty | def set_empty(self, row, column):
"""Keep one of the subplots completely empty.
:param row,column: specify the subplot.
"""
subplot = self.get_subplot_at(row, column)
subplot.set_empty() | python | def set_empty(self, row, column):
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davidfokkema/artist | artist/multi_plot.py | MultiPlot.set_empty_for_all | def set_empty_for_all(self, row_column_list):
"""Keep all specified subplots completely empty.
:param row_column_list: a list containing (row, column) tuples to
specify the subplots, or None to indicate *all* subplots.
:type row_column_list: list or None
"""
for row, column in row_column_list:
self.set_empty(row, column) | python | def set_empty_for_all(self, row_column_list):
"""Keep all specified subplots completely empty.
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davidfokkema/artist | artist/multi_plot.py | MultiPlot.set_title | def set_title(self, row, column, text):
"""Set a title text.
:param row,column: specify the subplot.
:param text: title text.
"""
subplot = self.get_subplot_at(row, column)
subplot.set_title(text) | python | def set_title(self, row, column, text):
"""Set a title text.
:param row,column: specify the subplot.
:param text: title text.
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davidfokkema/artist | artist/multi_plot.py | MultiPlot.set_label | def set_label(self, row, column, text, location='upper right',
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"""Set a label for the subplot.
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:param text: the label text.
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:param style: any TikZ style to style the text.
"""
subplot = self.get_subplot_at(row, column)
subplot.set_label(text, location, style) | python | def set_label(self, row, column, text, location='upper right',
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"""Set a label for the subplot.
:param row,column: specify the subplot.
:param text: the label text.
:param location: the location of the label inside the plot. May
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| 26ae7987522622710f2910980770c50012fda47d | https://github.com/davidfokkema/artist/blob/26ae7987522622710f2910980770c50012fda47d/artist/multi_plot.py#L107-L120 | train |
davidfokkema/artist | artist/multi_plot.py | MultiPlot.show_xticklabels | def show_xticklabels(self, row, column):
"""Show the x-axis tick labels for a subplot.
:param row,column: specify the subplot.
"""
subplot = self.get_subplot_at(row, column)
subplot.show_xticklabels() | python | def show_xticklabels(self, row, column):
"""Show the x-axis tick labels for a subplot.
:param row,column: specify the subplot.
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| 26ae7987522622710f2910980770c50012fda47d | https://github.com/davidfokkema/artist/blob/26ae7987522622710f2910980770c50012fda47d/artist/multi_plot.py#L122-L129 | train |
davidfokkema/artist | artist/multi_plot.py | MultiPlot.show_xticklabels_for_all | def show_xticklabels_for_all(self, row_column_list=None):
"""Show the x-axis tick labels for all specified subplots.
:param row_column_list: a list containing (row, column) tuples to
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self.show_xticklabels(row, column) | python | def show_xticklabels_for_all(self, row_column_list=None):
"""Show the x-axis tick labels for all specified subplots.
:param row_column_list: a list containing (row, column) tuples to
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:type row_column_list: list or None
"""
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davidfokkema/artist | artist/multi_plot.py | MultiPlot.show_yticklabels | def show_yticklabels(self, row, column):
"""Show the y-axis tick labels for a subplot.
:param row,column: specify the subplot.
"""
subplot = self.get_subplot_at(row, column)
subplot.show_yticklabels() | python | def show_yticklabels(self, row, column):
"""Show the y-axis tick labels for a subplot.
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subplot = self.get_subplot_at(row, column)
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davidfokkema/artist | artist/multi_plot.py | MultiPlot.show_yticklabels_for_all | def show_yticklabels_for_all(self, row_column_list=None):
"""Show the y-axis tick labels for all specified subplots.
:param row_column_list: a list containing (row, column) tuples to
specify the subplots, or None to indicate *all* subplots.
:type row_column_list: list or None
"""
if row_column_list is None:
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for row, column in row_column_list:
self.show_yticklabels(row, column) | python | def show_yticklabels_for_all(self, row_column_list=None):
"""Show the y-axis tick labels for all specified subplots.
:param row_column_list: a list containing (row, column) tuples to
specify the subplots, or None to indicate *all* subplots.
:type row_column_list: list or None
"""
if row_column_list is None:
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davidfokkema/artist | artist/multi_plot.py | MultiPlot.set_xlimits | def set_xlimits(self, row, column, min=None, max=None):
"""Set x-axis limits of a subplot.
:param row,column: specify the subplot.
:param min: minimal axis value
:param max: maximum axis value
"""
subplot = self.get_subplot_at(row, column)
subplot.set_xlimits(min, max) | python | def set_xlimits(self, row, column, min=None, max=None):
"""Set x-axis limits of a subplot.
:param row,column: specify the subplot.
:param min: minimal axis value
:param max: maximum axis value
"""
subplot = self.get_subplot_at(row, column)
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davidfokkema/artist | artist/multi_plot.py | MultiPlot.set_xlimits_for_all | def set_xlimits_for_all(self, row_column_list=None, min=None, max=None):
"""Set x-axis limits of specified subplots.
:param row_column_list: a list containing (row, column) tuples to
specify the subplots, or None to indicate *all* subplots.
:type row_column_list: list or None
:param min: minimal axis value
:param max: maximum axis value
"""
if row_column_list is None:
self.limits['xmin'] = min
self.limits['xmax'] = max
else:
for row, column in row_column_list:
self.set_xlimits(row, column, min, max) | python | def set_xlimits_for_all(self, row_column_list=None, min=None, max=None):
"""Set x-axis limits of specified subplots.
:param row_column_list: a list containing (row, column) tuples to
specify the subplots, or None to indicate *all* subplots.
:type row_column_list: list or None
:param min: minimal axis value
:param max: maximum axis value
"""
if row_column_list is None:
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for row, column in row_column_list:
self.set_xlimits(row, column, min, max) | [
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davidfokkema/artist | artist/multi_plot.py | MultiPlot.set_ylimits | def set_ylimits(self, row, column, min=None, max=None):
"""Set y-axis limits of a subplot.
:param row,column: specify the subplot.
:param min: minimal axis value
:param max: maximum axis value
"""
subplot = self.get_subplot_at(row, column)
subplot.set_ylimits(min, max) | python | def set_ylimits(self, row, column, min=None, max=None):
"""Set y-axis limits of a subplot.
:param row,column: specify the subplot.
:param min: minimal axis value
:param max: maximum axis value
"""
subplot = self.get_subplot_at(row, column)
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davidfokkema/artist | artist/multi_plot.py | MultiPlot.set_ylimits_for_all | def set_ylimits_for_all(self, row_column_list=None, min=None, max=None):
"""Set y-axis limits of specified subplots.
:param row_column_list: a list containing (row, column) tuples to
specify the subplots, or None to indicate *all* subplots.
:type row_column_list: list or None
:param min: minimal axis value
:param max: maximum axis value
"""
if row_column_list is None:
self.limits['ymin'] = min
self.limits['ymax'] = max
else:
for row, column in row_column_list:
self.set_ylimits(row, column, min, max) | python | def set_ylimits_for_all(self, row_column_list=None, min=None, max=None):
"""Set y-axis limits of specified subplots.
:param row_column_list: a list containing (row, column) tuples to
specify the subplots, or None to indicate *all* subplots.
:type row_column_list: list or None
:param min: minimal axis value
:param max: maximum axis value
"""
if row_column_list is None:
self.limits['ymin'] = min
self.limits['ymax'] = max
else:
for row, column in row_column_list:
self.set_ylimits(row, column, min, max) | [
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davidfokkema/artist | artist/multi_plot.py | MultiPlot.set_slimits | def set_slimits(self, row, column, min, max):
"""Set limits for the point sizes.
:param min: point size for the lowest value.
:param max: point size for the highest value.
"""
subplot = self.get_subplot_at(row, column)
subplot.set_slimits(min, max) | python | def set_slimits(self, row, column, min, max):
"""Set limits for the point sizes.
:param min: point size for the lowest value.
:param max: point size for the highest value.
"""
subplot = self.get_subplot_at(row, column)
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| 26ae7987522622710f2910980770c50012fda47d | https://github.com/davidfokkema/artist/blob/26ae7987522622710f2910980770c50012fda47d/artist/multi_plot.py#L285-L293 | train |
davidfokkema/artist | artist/multi_plot.py | MultiPlot.set_ytick_labels | def set_ytick_labels(self, row, column, labels):
"""Manually specify the y-axis tick labels.
:param row,column: specify the subplot.
:param labels: list of tick labels.
"""
subplot = self.get_subplot_at(row, column)
subplot.set_ytick_labels(labels) | python | def set_ytick_labels(self, row, column, labels):
"""Manually specify the y-axis tick labels.
:param row,column: specify the subplot.
:param labels: list of tick labels.
"""
subplot = self.get_subplot_at(row, column)
subplot.set_ytick_labels(labels) | [
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| 26ae7987522622710f2910980770c50012fda47d | https://github.com/davidfokkema/artist/blob/26ae7987522622710f2910980770c50012fda47d/artist/multi_plot.py#L456-L464 | train |
davidfokkema/artist | artist/multi_plot.py | MultiPlot.get_subplot_at | def get_subplot_at(self, row, column):
"""Return the subplot at row, column position.
:param row,column: specify the subplot.
"""
idx = row * self.columns + column
return self.subplots[idx] | python | def get_subplot_at(self, row, column):
"""Return the subplot at row, column position.
:param row,column: specify the subplot.
"""
idx = row * self.columns + column
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davidfokkema/artist | artist/multi_plot.py | MultiPlot.set_subplot_xlabel | def set_subplot_xlabel(self, row, column, text):
"""Set a label for the x-axis of a subplot.
:param row,column: specify the subplot.
:param text: text of the label.
"""
subplot = self.get_subplot_at(row, column)
subplot.set_xlabel(text) | python | def set_subplot_xlabel(self, row, column, text):
"""Set a label for the x-axis of a subplot.
:param row,column: specify the subplot.
:param text: text of the label.
"""
subplot = self.get_subplot_at(row, column)
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davidfokkema/artist | artist/multi_plot.py | MultiPlot.set_subplot_ylabel | def set_subplot_ylabel(self, row, column, text):
"""Set a label for the y-axis of a subplot.
:param row,column: specify the subplot.
:param text: text of the label.
"""
subplot = self.get_subplot_at(row, column)
subplot.set_ylabel(text) | python | def set_subplot_ylabel(self, row, column, text):
"""Set a label for the y-axis of a subplot.
:param row,column: specify the subplot.
:param text: text of the label.
"""
subplot = self.get_subplot_at(row, column)
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davidfokkema/artist | artist/multi_plot.py | MultiPlot.set_scalebar_for_all | def set_scalebar_for_all(self, row_column_list=None,
location='lower right'):
"""Show marker area scale for subplots.
:param row_column_list: a list containing (row, column) tuples to
specify the subplots, or None to indicate *all* subplots.
:param location: the location of the label inside the plot. May
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left', 'lower left'.
"""
if row_column_list is None:
for subplot in self.subplots:
subplot.set_scalebar(location)
else:
for row, column in row_column_list:
subplot = self.get_subplot_at(row, column)
subplot.set_scalebar(location) | python | def set_scalebar_for_all(self, row_column_list=None,
location='lower right'):
"""Show marker area scale for subplots.
:param row_column_list: a list containing (row, column) tuples to
specify the subplots, or None to indicate *all* subplots.
:param location: the location of the label inside the plot. May
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"""
if row_column_list is None:
for subplot in self.subplots:
subplot.set_scalebar(location)
else:
for row, column in row_column_list:
subplot = self.get_subplot_at(row, column)
subplot.set_scalebar(location) | [
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:param row_column_list: a list containing (row, column) tuples to
specify the subplots, or None to indicate *all* subplots.
:param location: the location of the label inside the plot. May
be one of 'center', 'upper right', 'lower right', 'upper
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| 26ae7987522622710f2910980770c50012fda47d | https://github.com/davidfokkema/artist/blob/26ae7987522622710f2910980770c50012fda47d/artist/multi_plot.py#L559-L576 | train |
davidfokkema/artist | artist/multi_plot.py | MultiPlot.set_colorbar | def set_colorbar(self, label='', horizontal=False):
"""Show the colorbar, it will be attached to the last plot.
Not for the histogram2d, only for the scatter_table.
Global mlimits should be set for this to properly reflect the
colormap of each subplot.
:param label: axis label for the colorbar.
:param horizontal: boolean, if True the colobar will be horizontal.
"""
if self.limits['mmin'] is None or self.limits['mmax'] is None:
warnings.warn('Set (only) global point meta limits to ensure the '
'colorbar is correct for all subplots.')
self.colorbar = {'label': label,
'horizontal': horizontal} | python | def set_colorbar(self, label='', horizontal=False):
"""Show the colorbar, it will be attached to the last plot.
Not for the histogram2d, only for the scatter_table.
Global mlimits should be set for this to properly reflect the
colormap of each subplot.
:param label: axis label for the colorbar.
:param horizontal: boolean, if True the colobar will be horizontal.
"""
if self.limits['mmin'] is None or self.limits['mmax'] is None:
warnings.warn('Set (only) global point meta limits to ensure the '
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self.colorbar = {'label': label,
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| 26ae7987522622710f2910980770c50012fda47d | https://github.com/davidfokkema/artist/blob/26ae7987522622710f2910980770c50012fda47d/artist/multi_plot.py#L578-L593 | train |
davidfokkema/artist | artist/multi_plot.py | MultiPlot.set_axis_options | def set_axis_options(self, row, column, text):
"""Set additionnal options as plain text."""
subplot = self.get_subplot_at(row, column)
subplot.set_axis_options(text) | python | def set_axis_options(self, row, column, text):
"""Set additionnal options as plain text."""
subplot = self.get_subplot_at(row, column)
subplot.set_axis_options(text) | [
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| 26ae7987522622710f2910980770c50012fda47d | https://github.com/davidfokkema/artist/blob/26ae7987522622710f2910980770c50012fda47d/artist/multi_plot.py#L604-L608 | train |
openearth/mmi-python | mmi/mmi_client.py | MMIClient.initialize | def initialize(self, configfile=None):
"""
Initialize the module
"""
method = "initialize"
A = None
metadata = {method: configfile}
send_array(self.socket, A, metadata)
A, metadata = recv_array(
self.socket, poll=self.poll, poll_timeout=self.poll_timeout,
flags=self.zmq_flags) | python | def initialize(self, configfile=None):
"""
Initialize the module
"""
method = "initialize"
A = None
metadata = {method: configfile}
send_array(self.socket, A, metadata)
A, metadata = recv_array(
self.socket, poll=self.poll, poll_timeout=self.poll_timeout,
flags=self.zmq_flags) | [
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| a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d | https://github.com/openearth/mmi-python/blob/a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d/mmi/mmi_client.py#L56-L69 | train |
openearth/mmi-python | mmi/mmi_client.py | MMIClient.finalize | def finalize(self):
"""
Finalize the module
"""
method = "finalize"
A = None
metadata = {method: -1}
send_array(self.socket, A, metadata)
A, metadata = recv_array(
self.socket, poll=self.poll, poll_timeout=self.poll_timeout,
flags=self.zmq_flags) | python | def finalize(self):
"""
Finalize the module
"""
method = "finalize"
A = None
metadata = {method: -1}
send_array(self.socket, A, metadata)
A, metadata = recv_array(
self.socket, poll=self.poll, poll_timeout=self.poll_timeout,
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| a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d | https://github.com/openearth/mmi-python/blob/a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d/mmi/mmi_client.py#L71-L84 | train |
openearth/mmi-python | mmi/mmi_client.py | MMIClient.set_current_time | def set_current_time(self, t):
"""
Set current time of simulation
"""
method = "set_current_time"
A = None
metadata = {method: t}
send_array(self.socket, A, metadata)
A, metadata = recv_array(
self.socket, poll=self.poll, poll_timeout=self.poll_timeout,
flags=self.zmq_flags) | python | def set_current_time(self, t):
"""
Set current time of simulation
"""
method = "set_current_time"
A = None
metadata = {method: t}
send_array(self.socket, A, metadata)
A, metadata = recv_array(
self.socket, poll=self.poll, poll_timeout=self.poll_timeout,
flags=self.zmq_flags) | [
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| a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d | https://github.com/openearth/mmi-python/blob/a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d/mmi/mmi_client.py#L188-L201 | train |
openearth/mmi-python | mmi/mmi_client.py | MMIClient.set_var_slice | def set_var_slice(self, name, start, count, var):
"""
Set the variable name with the values of var
"""
method = "set_var_slice"
A = var
metadata = {
method: name,
"start": start,
"count": count
}
send_array(self.socket, A, metadata)
A, metadata = recv_array(
self.socket, poll=self.poll, poll_timeout=self.poll_timeout,
flags=self.zmq_flags) | python | def set_var_slice(self, name, start, count, var):
"""
Set the variable name with the values of var
"""
method = "set_var_slice"
A = var
metadata = {
method: name,
"start": start,
"count": count
}
send_array(self.socket, A, metadata)
A, metadata = recv_array(
self.socket, poll=self.poll, poll_timeout=self.poll_timeout,
flags=self.zmq_flags) | [
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| a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d | https://github.com/openearth/mmi-python/blob/a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d/mmi/mmi_client.py#L218-L234 | train |
openearth/mmi-python | mmi/mmi_client.py | MMIClient.update | def update(self, dt):
"""
Advance the module with timestep dt
"""
method = "update"
A = None
metadata = {method: dt}
send_array(self.socket, A, metadata)
A, metadata = recv_array(
self.socket, poll=self.poll, poll_timeout=self.poll_timeout,
flags=self.zmq_flags) | python | def update(self, dt):
"""
Advance the module with timestep dt
"""
method = "update"
A = None
metadata = {method: dt}
send_array(self.socket, A, metadata)
A, metadata = recv_array(
self.socket, poll=self.poll, poll_timeout=self.poll_timeout,
flags=self.zmq_flags) | [
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| a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d | https://github.com/openearth/mmi-python/blob/a2f4ac96b1e7f2fa903f668b3e05c4e86ad42e8d/mmi/mmi_client.py#L304-L317 | train |
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