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def load_mnist():
'''Load the MNIST digits dataset.'''
mnist = skdata.mnist.dataset.MNIST()
mnist.meta # trigger download if needed.
def arr(n, dtype):
arr = mnist.arrays[n]
return arr.reshape((len(arr), -1)).astype(dtype)
train_images = arr('train_images', np.float32) / 128 - 1
train_labels = arr('train_labels', np.uint8)
return ((train_images[:50000], train_labels[:50000, 0]),
(train_images[50000:], train_labels[50000:, 0])) | Load the MNIST digits dataset. | entailment |
def build(algo, loss, params=None, inputs=None, updates=(), monitors=(),
monitor_gradients=False):
'''Construct an optimizer by name.
Parameters
----------
algo : str
The name of the optimization algorithm to build.
loss : Theano expression
Loss function to minimize. This must be a scalar-valued expression.
params : list of Theano variables, optional
Symbolic variables to adjust to minimize the loss. If not given, these
will be computed automatically by walking the computation graph.
inputs : list of Theano variables, optional
Symbolic variables required to compute the loss. If not given, these
will be computed automatically by walking the computation graph.
updates : list of update pairs, optional
A list of pairs providing updates for the internal of the loss
computation. Normally this is empty, but it can be provided if the loss,
for example, requires an update to an internal random number generator.
monitors : dict or sequence of (str, Theano expression) tuples, optional
Additional values to monitor during optimization. These must be provided
as either a sequence of (name, expression) tuples, or as a dictionary
mapping string names to Theano expressions.
monitor_gradients : bool, optional
If True, add monitors to log the norms of the parameter gradients during
optimization. Defaults to False.
Returns
-------
optimizer : :class:`Optimizer`
An optimizer instance.
'''
return Optimizer.build(algo, loss, params, inputs,
updates=updates, monitors=monitors,
monitor_gradients=monitor_gradients) | Construct an optimizer by name.
Parameters
----------
algo : str
The name of the optimization algorithm to build.
loss : Theano expression
Loss function to minimize. This must be a scalar-valued expression.
params : list of Theano variables, optional
Symbolic variables to adjust to minimize the loss. If not given, these
will be computed automatically by walking the computation graph.
inputs : list of Theano variables, optional
Symbolic variables required to compute the loss. If not given, these
will be computed automatically by walking the computation graph.
updates : list of update pairs, optional
A list of pairs providing updates for the internal of the loss
computation. Normally this is empty, but it can be provided if the loss,
for example, requires an update to an internal random number generator.
monitors : dict or sequence of (str, Theano expression) tuples, optional
Additional values to monitor during optimization. These must be provided
as either a sequence of (name, expression) tuples, or as a dictionary
mapping string names to Theano expressions.
monitor_gradients : bool, optional
If True, add monitors to log the norms of the parameter gradients during
optimization. Defaults to False.
Returns
-------
optimizer : :class:`Optimizer`
An optimizer instance. | entailment |
def _compile(self, **kwargs):
'''Compile the Theano functions for evaluating and updating our model.
'''
util.log('compiling evaluation function')
self.f_eval = theano.function(self._inputs,
self._monitor_exprs,
updates=self._updates,
name='evaluation')
label = self.__class__.__name__
util.log('compiling {} optimizer'.format(click.style(label, fg='red')))
updates = list(self._updates) + list(self.get_updates(**kwargs))
self.f_step = theano.function(self._inputs,
self._monitor_exprs,
updates=updates,
name=label) | Compile the Theano functions for evaluating and updating our model. | entailment |
def get_updates(self, **kwargs):
'''Get parameter update expressions for performing optimization.
Keyword arguments can be applied here to set any of the global
optimizer attributes.
Yields
------
updates : (parameter, expression) tuples
A sequence of parameter updates to be applied during optimization.
'''
self._prepare(**kwargs)
for param, grad in self._differentiate():
for var, update in self._get_updates_for(param, grad):
# For auxiliary variables, updates are meant to replace the
# existing variable value.
if var != param:
yield var, update
continue
# If momentum is disabled, just apply the parameter delta.
if self.momentum == 0:
yield var, param - update
continue
# Momentum is enabled, so we keep track of velocity here.
vel_tm1 = util.shared_like(param, 'vel')
vel_t = util.as_float(self.momentum) * vel_tm1 - update
if self.nesterov:
# see http://arxiv.org/pdf/1212.0901v2.pdf (eq 7) and
# https://github.com/lisa-lab/pylearn2/pull/136#issuecomment-10381617
mom_sqr = util.as_float(self.momentum ** 2)
mom_inc = util.as_float(1 + self.momentum)
vel_t = mom_sqr * vel_tm1 - mom_inc * update
yield vel_tm1, vel_t
yield param, param + vel_t | Get parameter update expressions for performing optimization.
Keyword arguments can be applied here to set any of the global
optimizer attributes.
Yields
------
updates : (parameter, expression) tuples
A sequence of parameter updates to be applied during optimization. | entailment |
def _differentiate(self, params=None):
'''Return a sequence of gradients for our parameters.
If this optimizer has been configured with a gradient norm limit, or
with elementwise gradient clipping, this method applies the appropriate
rescaling and clipping operations before returning the gradient.
Parameters
----------
params : list of Theano variables, optional
Return the gradient with respect to these parameters. Defaults to
all parameters that the optimizer knows about.
Yields
------
pairs : (param, grad) tuples
Generates a sequence of tuples representing each of the parameters
requested and the corresponding Theano gradient expressions.
'''
if params is None:
params = self._params
for param, grad in zip(params, TT.grad(self._loss, params)):
if self.max_gradient_elem > 0:
limit = util.as_float(self.max_gradient_elem)
yield param, TT.clip(grad, -limit, limit)
elif self.max_gradient_norm > 0:
norm = TT.sqrt((grad * grad).sum())
limit = util.as_float(self.max_gradient_norm)
yield param, grad * TT.minimum(1, limit / norm)
else:
yield param, grad | Return a sequence of gradients for our parameters.
If this optimizer has been configured with a gradient norm limit, or
with elementwise gradient clipping, this method applies the appropriate
rescaling and clipping operations before returning the gradient.
Parameters
----------
params : list of Theano variables, optional
Return the gradient with respect to these parameters. Defaults to
all parameters that the optimizer knows about.
Yields
------
pairs : (param, grad) tuples
Generates a sequence of tuples representing each of the parameters
requested and the corresponding Theano gradient expressions. | entailment |
def set_params(self, targets=None):
'''Set the values of the parameters to the given target values.
Parameters
----------
targets : sequence of ndarray, optional
Arrays for setting the parameters of our model. If this is not
provided, the current best parameters for this optimizer will be
used.
'''
if not isinstance(targets, (list, tuple)):
targets = self._best_params
for param, target in zip(self._params, targets):
param.set_value(target) | Set the values of the parameters to the given target values.
Parameters
----------
targets : sequence of ndarray, optional
Arrays for setting the parameters of our model. If this is not
provided, the current best parameters for this optimizer will be
used. | entailment |
def _log(self, monitors, iteration, label='', suffix=''):
'''Log the state of the optimizer on the console.
Parameters
----------
monitors : OrderedDict
A dictionary of monitor names mapped to values. These names and
values are what is being logged.
iteration : int
Optimization iteration that we are logging.
label : str, optional
A label for the name of the optimizer creating the log line.
Defaults to the name of the current class.
suffix : str, optional
A suffix to add to the end of the log line, if any.
'''
label = label or self.__class__.__name__
fields = (('{}={:.6f}').format(k, v) for k, v in monitors.items())
util.log('{} {} {}{}'.format(label, iteration, ' '.join(fields), suffix)) | Log the state of the optimizer on the console.
Parameters
----------
monitors : OrderedDict
A dictionary of monitor names mapped to values. These names and
values are what is being logged.
iteration : int
Optimization iteration that we are logging.
label : str, optional
A label for the name of the optimizer creating the log line.
Defaults to the name of the current class.
suffix : str, optional
A suffix to add to the end of the log line, if any. | entailment |
def evaluate(self, dataset):
'''Evaluate the current model parameters on a dataset.
Parameters
----------
dataset : :class:`Dataset <downhill.dataset.Dataset>`
A set of data to use for evaluating the model.
Returns
-------
monitors : OrderedDict
A dictionary mapping monitor names to values. Monitors are
quantities of interest during optimization---for example, loss
function, accuracy, or whatever the optimization task requires.
'''
if dataset is None:
values = [self.f_eval()]
else:
values = [self.f_eval(*x) for x in dataset]
monitors = zip(self._monitor_names, np.mean(values, axis=0))
return collections.OrderedDict(monitors) | Evaluate the current model parameters on a dataset.
Parameters
----------
dataset : :class:`Dataset <downhill.dataset.Dataset>`
A set of data to use for evaluating the model.
Returns
-------
monitors : OrderedDict
A dictionary mapping monitor names to values. Monitors are
quantities of interest during optimization---for example, loss
function, accuracy, or whatever the optimization task requires. | entailment |
def _prepare(self, **kwargs):
'''Set up properties for optimization.
This method can be overridden by base classes to provide parameters that
are specific to a particular optimization technique (e.g., setting up a
learning rate value).
'''
self.learning_rate = util.as_float(kwargs.pop('learning_rate', 1e-4))
self.momentum = kwargs.pop('momentum', 0)
self.nesterov = kwargs.pop('nesterov', False)
self.patience = kwargs.get('patience', 5)
self.validate_every = kwargs.pop('validate_every', 10)
self.min_improvement = kwargs.pop('min_improvement', 0)
self.max_gradient_norm = kwargs.pop('max_gradient_norm', 0)
self.max_gradient_elem = kwargs.pop('max_gradient_elem', 0)
util.log_param('patience', self.patience)
util.log_param('validate_every', self.validate_every)
util.log_param('min_improvement', self.min_improvement)
util.log_param('max_gradient_norm', self.max_gradient_norm)
util.log_param('max_gradient_elem', self.max_gradient_elem)
util.log_param('learning_rate', self.learning_rate)
util.log_param('momentum', self.momentum)
util.log_param('nesterov', self.nesterov) | Set up properties for optimization.
This method can be overridden by base classes to provide parameters that
are specific to a particular optimization technique (e.g., setting up a
learning rate value). | entailment |
def iterate(self, train=None, valid=None, max_updates=None, **kwargs):
r'''Optimize a loss iteratively using a training and validation dataset.
This method yields a series of monitor values to the caller. After every
optimization epoch, a pair of monitor dictionaries is generated: one
evaluated on the training dataset during the epoch, and another
evaluated on the validation dataset at the most recent validation epoch.
The validation monitors might not be updated during every optimization
iteration; in this case, the most recent validation monitors will be
yielded along with the training monitors.
Additional keyword arguments supplied here will set the global
optimizer attributes.
Parameters
----------
train : sequence or :class:`Dataset <downhill.dataset.Dataset>`
A set of training data for computing updates to model parameters.
valid : sequence or :class:`Dataset <downhill.dataset.Dataset>`
A set of validation data for computing monitor values and
determining when the loss has stopped improving. Defaults to the
training data.
max_updates : int, optional
If specified, halt optimization after this many gradient updates
have been processed. If not provided, uses early stopping to decide
when to halt.
Yields
------
train_monitors : dict
A dictionary mapping monitor names to values, evaluated on the
training dataset.
valid_monitors : dict
A dictionary containing monitor values evaluated on the validation
dataset.
'''
self._compile(**kwargs)
if valid is None:
valid = train
iteration = 0
training = validation = None
while max_updates is None or iteration < max_updates:
if not iteration % self.validate_every:
try:
validation = self.evaluate(valid)
except KeyboardInterrupt:
util.log('interrupted!')
break
if self._test_patience(validation):
util.log('patience elapsed!')
break
try:
training = self._step(train)
except KeyboardInterrupt:
util.log('interrupted!')
break
iteration += 1
self._log(training, iteration)
yield training, validation
self.set_params('best') | r'''Optimize a loss iteratively using a training and validation dataset.
This method yields a series of monitor values to the caller. After every
optimization epoch, a pair of monitor dictionaries is generated: one
evaluated on the training dataset during the epoch, and another
evaluated on the validation dataset at the most recent validation epoch.
The validation monitors might not be updated during every optimization
iteration; in this case, the most recent validation monitors will be
yielded along with the training monitors.
Additional keyword arguments supplied here will set the global
optimizer attributes.
Parameters
----------
train : sequence or :class:`Dataset <downhill.dataset.Dataset>`
A set of training data for computing updates to model parameters.
valid : sequence or :class:`Dataset <downhill.dataset.Dataset>`
A set of validation data for computing monitor values and
determining when the loss has stopped improving. Defaults to the
training data.
max_updates : int, optional
If specified, halt optimization after this many gradient updates
have been processed. If not provided, uses early stopping to decide
when to halt.
Yields
------
train_monitors : dict
A dictionary mapping monitor names to values, evaluated on the
training dataset.
valid_monitors : dict
A dictionary containing monitor values evaluated on the validation
dataset. | entailment |
def minimize(self, *args, **kwargs):
'''Optimize our loss exhaustively.
This method is a thin wrapper over the :func:`iterate` method. It simply
exhausts the iterative optimization process and returns the final
monitor values.
Returns
-------
train_monitors : dict
A dictionary mapping monitor names to values, evaluated on the
training dataset.
valid_monitors : dict
A dictionary containing monitor values evaluated on the validation
dataset.
'''
monitors = None
for monitors in self.iterate(*args, **kwargs):
pass
return monitors | Optimize our loss exhaustively.
This method is a thin wrapper over the :func:`iterate` method. It simply
exhausts the iterative optimization process and returns the final
monitor values.
Returns
-------
train_monitors : dict
A dictionary mapping monitor names to values, evaluated on the
training dataset.
valid_monitors : dict
A dictionary containing monitor values evaluated on the validation
dataset. | entailment |
def _step(self, dataset):
'''Advance the state of the optimizer by one step.
Parameters
----------
dataset : :class:`Dataset <downhill.dataset.Dataset>`
A dataset for optimizing the model.
Returns
-------
train_monitors : dict
A dictionary mapping monitor names to values.
'''
if dataset is None:
values = [self.f_step()]
else:
values = [self.f_step(*x) for x in dataset]
return collections.OrderedDict(
zip(self._monitor_names, np.mean(values, axis=0))) | Advance the state of the optimizer by one step.
Parameters
----------
dataset : :class:`Dataset <downhill.dataset.Dataset>`
A dataset for optimizing the model.
Returns
-------
train_monitors : dict
A dictionary mapping monitor names to values. | entailment |
def accept_arguments(method, number_of_arguments=1):
"""Returns True if the given method will accept the given number of arguments
method: the method to perform introspection on
number_of_arguments: the number_of_arguments
"""
if 'method' in method.__class__.__name__:
number_of_arguments += 1
func = getattr(method, 'im_func', getattr(method, '__func__'))
func_defaults = getattr(func, 'func_defaults', getattr(func, '__defaults__'))
number_of_defaults = func_defaults and len(func_defaults) or 0
elif method.__class__.__name__ == 'function':
func_defaults = getattr(method, 'func_defaults', getattr(method, '__defaults__'))
number_of_defaults = func_defaults and len(func_defaults) or 0
coArgCount = getattr(method, 'func_code', getattr(method, '__code__')).co_argcount
if(coArgCount >= number_of_arguments and coArgCount - number_of_defaults <= number_of_arguments):
return True
return False | Returns True if the given method will accept the given number of arguments
method: the method to perform introspection on
number_of_arguments: the number_of_arguments | entailment |
def emit(self, signal, value=None, gather=False):
"""Emits a signal, causing all slot methods connected with the signal to be called (optionally w/ related value)
signal: the name of the signal to emit, must be defined in the classes 'signals' list.
value: the value to pass to all connected slot methods.
gather: if set, causes emit to return a list of all slot results
"""
results = [] if gather else True
if hasattr(self, 'connections') and signal in self.connections:
for condition, values in self.connections[signal].items():
if condition is None or condition == value or (callable(condition) and condition(value)):
for slot, transform in values.items():
if transform is not None:
if callable(transform):
used_value = transform(value)
elif isinstance(transform, str):
used_value = transform.format(value=value)
else:
used_value = transform
else:
used_value = value
if used_value is not None:
if(accept_arguments(slot, 1)):
result = slot(used_value)
elif(accept_arguments(slot, 0)):
result = slot()
else:
result = ''
else:
result = slot()
if gather:
results.append(result)
return results | Emits a signal, causing all slot methods connected with the signal to be called (optionally w/ related value)
signal: the name of the signal to emit, must be defined in the classes 'signals' list.
value: the value to pass to all connected slot methods.
gather: if set, causes emit to return a list of all slot results | entailment |
def connect(self, signal, slot, transform=None, condition=None):
"""Defines a connection between this objects signal and another objects slot
signal: the signal this class will emit, to cause the slot method to be called
receiver: the object containing the slot method to be called
slot: the slot method to call
transform: an optional value override to pass into the slot method as the first variable
condition: only call the slot if the value emitted matches the required value or calling required returns True
"""
if not signal in self.signals:
print("WARNING: {0} is trying to connect a slot to an undefined signal: {1}".format(self.__class__.__name__,
str(signal)))
return
if not hasattr(self, 'connections'):
self.connections = {}
connection = self.connections.setdefault(signal, {})
connection = connection.setdefault(condition, {})
connection[slot] = transform | Defines a connection between this objects signal and another objects slot
signal: the signal this class will emit, to cause the slot method to be called
receiver: the object containing the slot method to be called
slot: the slot method to call
transform: an optional value override to pass into the slot method as the first variable
condition: only call the slot if the value emitted matches the required value or calling required returns True | entailment |
def disconnect(self, signal=None, slot=None, transform=None, condition=None):
"""Removes connection(s) between this objects signal and connected slot(s)
signal: the signal this class will emit, to cause the slot method to be called
receiver: the object containing the slot method to be called
slot: the slot method or function to call
transform: an optional value override to pass into the slot method as the first variable
condition: only call the slot method if the value emitted matches this condition
"""
if slot:
self.connections[signal][condition].pop(slot, None)
elif condition is not None:
self.connections[signal].pop(condition, None)
elif signal:
self.connections.pop(signal, None)
else:
delattr(self, 'connections') | Removes connection(s) between this objects signal and connected slot(s)
signal: the signal this class will emit, to cause the slot method to be called
receiver: the object containing the slot method to be called
slot: the slot method or function to call
transform: an optional value override to pass into the slot method as the first variable
condition: only call the slot method if the value emitted matches this condition | entailment |
def get(self, key):
""" Returns context data for a given app, can be an ID or a case insensitive name """
keystr = str(key)
res = None
try:
res = self.ctx[keystr]
except KeyError:
for k, v in self.ctx.items():
if "name" in v and v["name"].lower() == keystr.lower():
res = v
break
return res | Returns context data for a given app, can be an ID or a case insensitive name | entailment |
def hash_name(self):
""" The URL-friendly identifier for the item. Generates its own approximation if one isn't available """
name = self._item.get("market_hash_name")
if not name:
name = "{0.appid}-{0.name}".format(self)
return name | The URL-friendly identifier for the item. Generates its own approximation if one isn't available | entailment |
def quality(self):
""" Can't really trust presence of a schema here, but there is an ID sometimes """
try:
qid = int((self.tool_metadata or {}).get("quality", 0))
except:
qid = 0
# We might be able to get the quality strings from the item's tags
internal_name, name = "normal", "Normal"
if self.tags:
tags = {x.get('category'): x for x in self.tags}
if 'Quality' in tags:
internal_name, name = tags['Quality'].get('internal_name'), tags['Quality'].get('name')
return qid, internal_name, name | Can't really trust presence of a schema here, but there is an ID sometimes | entailment |
def get(cls):
"""Get the current API key.
if one has not been given via 'set' the env var STEAMODD_API_KEY will
be checked instead.
"""
apikey = cls.__api_key or cls.__api_key_env_var
if apikey:
return apikey
else:
raise APIKeyMissingError("API key not set") | Get the current API key.
if one has not been given via 'set' the env var STEAMODD_API_KEY will
be checked instead. | entailment |
def call(self):
""" Make the API call again and fetch fresh data. """
data = self._downloader.download()
# Only try to pass errors arg if supported
if sys.version >= "2.7":
data = data.decode("utf-8", errors="ignore")
else:
data = data.decode("utf-8")
self.update(json.loads(data))
self._fetched = True | Make the API call again and fetch fresh data. | entailment |
def _attribute_definition(self, attrid):
""" Returns the attribute definition dict of a given attribute
ID, can be the name or the integer ID """
attrs = self._schema["attributes"]
try:
# Make a new dict to avoid side effects
return dict(attrs[attrid])
except KeyError:
attr_names = self._schema["attribute_names"]
attrdef = attrs.get(attr_names.get(str(attrid).lower()))
if not attrdef:
return None
else:
return dict(attrdef) | Returns the attribute definition dict of a given attribute
ID, can be the name or the integer ID | entailment |
def _quality_definition(self, qid):
""" Returns the ID and localized name of the given quality, can be either ID type """
qualities = self._schema["qualities"]
try:
return qualities[qid]
except KeyError:
qid = self._schema["quality_names"].get(str(qid).lower(), 0)
return qualities.get(qid, (qid, "normal", "Normal")) | Returns the ID and localized name of the given quality, can be either ID type | entailment |
def attributes(self):
""" Returns all attributes in the schema """
attrs = self._schema["attributes"]
return [item_attribute(attr) for attr in sorted(attrs.values(),
key=operator.itemgetter("defindex"))] | Returns all attributes in the schema | entailment |
def origin_id_to_name(self, origin):
""" Returns a localized origin name for a given ID """
try:
oid = int(origin)
except (ValueError, TypeError):
return None
return self.origins.get(oid) | Returns a localized origin name for a given ID | entailment |
def attributes(self):
""" Returns a list of attributes """
overridden_attrs = self._attributes
sortmap = {"neutral": 1, "positive": 2,
"negative": 3}
sortedattrs = list(overridden_attrs.values())
sortedattrs.sort(key=operator.itemgetter("defindex"))
sortedattrs.sort(key=lambda t: sortmap.get(t.get("effect_type",
"neutral"), 99))
return [item_attribute(theattr) for theattr in sortedattrs] | Returns a list of attributes | entailment |
def equipped(self):
""" Returns a dict of classes that have the item equipped and in what slot """
equipped = self._item.get("equipped", [])
# WORKAROUND: 0 is probably an off-by-one error
# WORKAROUND: 65535 actually serves a purpose (according to Valve)
return dict([(eq["class"], eq["slot"]) for eq in equipped if eq["class"] != 0 and eq["slot"] != 65535]) | Returns a dict of classes that have the item equipped and in what slot | entailment |
def equipable_classes(self):
""" Returns a list of classes that _can_ use the item. """
sitem = self._schema_item
return [c for c in sitem.get("used_by_classes", self.equipped.keys()) if c] | Returns a list of classes that _can_ use the item. | entailment |
def contents(self):
""" Returns the item in the container, if there is one.
This will be a standard item object. """
rawitem = self._item.get("contained_item")
if rawitem:
return self.__class__(rawitem, self._schema) | Returns the item in the container, if there is one.
This will be a standard item object. | entailment |
def full_name(self):
"""
The full name of the item, generated depending
on things such as its quality, rank, the schema language,
and so on.
"""
qid, quality_str, pretty_quality_str = self.quality
custom_name = self.custom_name
item_name = self.name
english = (self._language == "en_US")
rank = self.rank
prefixed = self._schema_item.get("proper_name", False)
prefix = ''
suffix = ''
pfinal = ''
if item_name.startswith("The ") and prefixed:
item_name = item_name[4:]
if quality_str != "unique" and quality_str != "normal":
pfinal = pretty_quality_str
if english:
if prefixed:
if quality_str == "unique":
pfinal = "The"
elif quality_str == "unique":
pfinal = ''
if rank and quality_str == "strange":
pfinal = rank["name"]
if english:
prefix = pfinal
elif pfinal:
suffix = '(' + pfinal + ') ' + suffix
return (prefix + " " + item_name + " " + suffix).strip() | The full name of the item, generated depending
on things such as its quality, rank, the schema language,
and so on. | entailment |
def kill_eaters(self):
"""
Returns a list of tuples containing the proper localized kill eater type strings and their values
according to set/type/value "order"
"""
eaters = {}
ranktypes = self._kill_types
for attr in self:
aname = attr.name.strip()
aid = attr.id
if aname.startswith("kill eater"):
try:
# Get the name prefix (matches up type and score and
# determines the primary type for ranking)
eateri = list(filter(None, aname.split(' ')))[-1]
if eateri.isdigit():
eateri = int(eateri)
else:
# Probably the primary type/score which has no number
eateri = 0
except IndexError:
# Fallback to attr ID (will completely fail to make
# anything legible but better than nothing)
eateri = aid
if aname.find("user") != -1:
# User score types have lower sorting priority
eateri += 100
eaters.setdefault(eateri, [None, None])
if aname.find("score type") != -1 or aname.find("kill type") != -1:
# Score type attribute
if eaters[eateri][0] is None:
eaters[eateri][0] = attr.value
else:
# Value attribute
eaters[eateri][1] = attr.value
eaterlist = []
defaultleveldata = "KillEaterRank"
for key, eater in sorted(eaters.items()):
etype, count = eater
# Eater type can be null (it still is in some older items), null
# count means we're looking at either an uninitialized item or
# schema item
if count is not None:
rank = ranktypes.get(etype or 0,
{"level_data": defaultleveldata,
"type_name": "Count"})
eaterlist.append((rank.get("level_data", defaultleveldata),
rank["type_name"], count))
return eaterlist | Returns a list of tuples containing the proper localized kill eater type strings and their values
according to set/type/value "order" | entailment |
def rank(self):
"""
Returns the item's rank (if it has one)
as a dict that includes required score, name, and level.
"""
if self._rank != {}:
# Don't bother doing attribute lookups again
return self._rank
try:
# The eater determining the rank
levelkey, typename, count = self.kill_eaters[0]
except IndexError:
# Apparently no eater available
self._rank = None
return None
rankset = self._ranks.get(levelkey,
[{"level": 0,
"required_score": 0,
"name": "Strange"}])
for rank in rankset:
self._rank = rank
if count < rank["required_score"]:
break
return self._rank | Returns the item's rank (if it has one)
as a dict that includes required score, name, and level. | entailment |
def available_styles(self):
""" Returns a list of all styles defined for the item """
styles = self._schema_item.get("styles", [])
return list(map(operator.itemgetter("name"), styles)) | Returns a list of all styles defined for the item | entailment |
def formatted_value(self):
""" Returns a formatted value as a string"""
# TODO: Cleanup all of this, it's just weird and unnatural maths
val = self.value
pval = val
ftype = self.value_type
if ftype == "percentage":
pval = int(round(val * 100))
if self.type == "negative":
pval = 0 - (100 - pval)
else:
pval -= 100
elif ftype == "additive_percentage":
pval = int(round(val * 100))
elif ftype == "inverted_percentage":
pval = 100 - int(round(val * 100))
# Can't remember what workaround this was, is it needed?
if self.type == "negative":
if self.value > 1:
pval = 0 - pval
elif ftype == "additive" or ftype == "particle_index" or ftype == "account_id":
if int(val) == val:
pval = int(val)
elif ftype == "date":
d = time.gmtime(int(val))
pval = time.strftime("%Y-%m-%d %H:%M:%S", d)
return u"{0}".format(pval) | Returns a formatted value as a string | entailment |
def formatted_description(self):
""" Returns a formatted description string (%s* tokens replaced) or None if unavailable """
desc = self.description
if desc:
return desc.replace("%s1", self.formatted_value)
else:
return None | Returns a formatted description string (%s* tokens replaced) or None if unavailable | entailment |
def value_type(self):
""" The attribute's type, note that this is the type of the attribute's
value and not its affect on the item (i.e. negative or positive). See
'type' for that. """
redundantprefix = "value_is_"
vtype = self._attribute.get("description_format")
if vtype and vtype.startswith(redundantprefix):
return vtype[len(redundantprefix):]
else:
return vtype | The attribute's type, note that this is the type of the attribute's
value and not its affect on the item (i.e. negative or positive). See
'type' for that. | entailment |
def account_info(self):
""" Certain attributes have a user's account information
associated with it such as a gifted or crafted item.
A dict with two keys: 'persona' and 'id64'.
None if the attribute has no account information attached to it. """
account_info = self._attribute.get("account_info")
if account_info:
return {"persona": account_info.get("personaname", ""),
"id64": account_info["steamid"]}
else:
return None | Certain attributes have a user's account information
associated with it such as a gifted or crafted item.
A dict with two keys: 'persona' and 'id64'.
None if the attribute has no account information attached to it. | entailment |
def tags(self):
""" Returns a dict containing tags and their localized labels as values """
return dict([(t, self._catalog.tags.get(t, t)) for t in self._asset.get("tags", [])]) | Returns a dict containing tags and their localized labels as values | entailment |
def vanity(self):
""" Returns the user's vanity url if it exists, None otherwise """
purl = self.profile_url.strip('/')
if purl.find("/id/") != -1:
return os.path.basename(purl) | Returns the user's vanity url if it exists, None otherwise | entailment |
def creation_date(self):
""" Returns the account creation date as a localtime time.struct_time
struct if public"""
timestamp = self._prof.get("timecreated")
if timestamp:
return time.localtime(timestamp) | Returns the account creation date as a localtime time.struct_time
struct if public | entailment |
def current_game(self):
"""
Returns a tuple of 3 elements (each of which may be None if not available):
Current game app ID, server ip:port, misc. extra info (eg. game title)
"""
obj = self._prof
gameid = obj.get("gameid")
gameserverip = obj.get("gameserverip")
gameextrainfo = obj.get("gameextrainfo")
return (int(gameid) if gameid else None, gameserverip, gameextrainfo) | Returns a tuple of 3 elements (each of which may be None if not available):
Current game app ID, server ip:port, misc. extra info (eg. game title) | entailment |
def level(self):
"""
Returns the the user's profile level, note that this runs a separate
request because the profile level data isn't in the standard player summary
output even though it should be. Which is also why it's not implemented
as a separate class. You won't need this output and not the profile output
"""
level_key = "player_level"
if level_key in self._api["response"]:
return self._api["response"][level_key]
try:
lvl = api.interface("IPlayerService").GetSteamLevel(steamid=self.id64)["response"][level_key]
self._api["response"][level_key] = lvl
return lvl
except:
return -1 | Returns the the user's profile level, note that this runs a separate
request because the profile level data isn't in the standard player summary
output even though it should be. Which is also why it's not implemented
as a separate class. You won't need this output and not the profile output | entailment |
def from_def(cls, obj):
""" Builds a profile object from a raw player summary object """
prof = cls(obj["steamid"])
prof._cache = obj
return prof | Builds a profile object from a raw player summary object | entailment |
def on_status_withheld(self, status_id, user_id, countries):
"""Called when a status is withheld"""
logger.info('Status %s withheld for user %s', status_id, user_id)
return True | Called when a status is withheld | entailment |
def on_disconnect(self, code, stream_name, reason):
"""Called when a disconnect is received"""
logger.error('Disconnect message: %s %s %s', code, stream_name, reason)
return True | Called when a disconnect is received | entailment |
def on_error(self, status_code):
"""Called when a non-200 status code is returned"""
logger.error('Twitter returned error code %s', status_code)
self.error = status_code
return False | Called when a non-200 status code is returned | entailment |
def on_exception(self, exception):
"""An exception occurred in the streaming thread"""
logger.error('Exception from stream!', exc_info=True)
self.streaming_exception = exception | An exception occurred in the streaming thread | entailment |
def check(self):
"""
Checks if the list of tracked terms has changed.
Returns True if changed, otherwise False.
"""
new_tracking_terms = self.update_tracking_terms()
terms_changed = False
# any deleted terms?
if self._tracking_terms_set > new_tracking_terms:
logging.debug("Some tracking terms removed")
terms_changed = True
# any added terms?
elif self._tracking_terms_set < new_tracking_terms:
logging.debug("Some tracking terms added")
terms_changed = True
# Go ahead and store for later
self._tracking_terms_set = new_tracking_terms
# If the terms changed, we need to restart the stream
return terms_changed | Checks if the list of tracked terms has changed.
Returns True if changed, otherwise False. | entailment |
def update_tracking_terms(self):
"""
Terms must be one-per-line.
Blank lines will be skipped.
"""
import codecs
with codecs.open(self.filename,"r", encoding='utf8') as input:
# read all the lines
lines = input.readlines()
# build a set of terms
new_terms = set()
for line in lines:
line = line.strip()
if len(line):
new_terms.add(line)
return set(new_terms) | Terms must be one-per-line.
Blank lines will be skipped. | entailment |
def launch_debugger(frame, stream=None):
"""
Interrupt running process, and provide a python prompt for
interactive debugging.
"""
d = {'_frame': frame} # Allow access to frame object.
d.update(frame.f_globals) # Unless shadowed by global
d.update(frame.f_locals)
import code, traceback
i = code.InteractiveConsole(d)
message = "Signal received : entering python shell.\nTraceback:\n"
message += ''.join(traceback.format_stack(frame))
i.interact(message) | Interrupt running process, and provide a python prompt for
interactive debugging. | entailment |
def set_debug_listener(stream):
"""Break into a debugger if receives the SIGUSR1 signal"""
def debugger(sig, frame):
launch_debugger(frame, stream)
if hasattr(signal, 'SIGUSR1'):
signal.signal(signal.SIGUSR1, debugger)
else:
logger.warn("Cannot set SIGUSR1 signal for debug mode.") | Break into a debugger if receives the SIGUSR1 signal | entailment |
def set_terminate_listeners(stream):
"""Die on SIGTERM or SIGINT"""
def stop(signum, frame):
terminate(stream.listener)
# Installs signal handlers for handling SIGINT and SIGTERM
# gracefully.
signal.signal(signal.SIGINT, stop)
signal.signal(signal.SIGTERM, stop) | Die on SIGTERM or SIGINT | entailment |
def get_tweepy_auth(twitter_api_key,
twitter_api_secret,
twitter_access_token,
twitter_access_token_secret):
"""Make a tweepy auth object"""
auth = tweepy.OAuthHandler(twitter_api_key, twitter_api_secret)
auth.set_access_token(twitter_access_token, twitter_access_token_secret)
return auth | Make a tweepy auth object | entailment |
def construct_listener(outfile=None):
"""Create the listener that prints tweets"""
if outfile is not None:
if os.path.exists(outfile):
raise IOError("File %s already exists" % outfile)
outfile = open(outfile, 'wb')
return PrintingListener(out=outfile) | Create the listener that prints tweets | entailment |
def begin_stream_loop(stream, poll_interval):
"""Start and maintain the streaming connection..."""
while should_continue():
try:
stream.start_polling(poll_interval)
except Exception as e:
# Infinite restart
logger.error("Exception while polling. Restarting in 1 second.", exc_info=True)
time.sleep(1) | Start and maintain the streaming connection... | entailment |
def start(track_file,
twitter_api_key,
twitter_api_secret,
twitter_access_token,
twitter_access_token_secret,
poll_interval=15,
unfiltered=False,
languages=None,
debug=False,
outfile=None):
"""Start the stream."""
listener = construct_listener(outfile)
checker = BasicFileTermChecker(track_file, listener)
auth = get_tweepy_auth(twitter_api_key,
twitter_api_secret,
twitter_access_token,
twitter_access_token_secret)
stream = DynamicTwitterStream(auth, listener, checker, unfiltered=unfiltered, languages=languages)
set_terminate_listeners(stream)
if debug:
set_debug_listener(stream)
begin_stream_loop(stream, poll_interval) | Start the stream. | entailment |
def on_status(self, status):
"""Print out some tweets"""
self.out.write(json.dumps(status))
self.out.write(os.linesep)
self.received += 1
return not self.terminate | Print out some tweets | entailment |
def print_status(self):
"""Print out the current tweet rate and reset the counter"""
tweets = self.received
now = time.time()
diff = now - self.since
self.since = now
self.received = 0
if diff > 0:
logger.info("Receiving tweets at %s tps", tweets / diff) | Print out the current tweet rate and reset the counter | entailment |
def start_polling(self, interval):
"""
Start polling for term updates and streaming.
"""
interval = float(interval)
self.polling = True
# clear the stored list of terms - we aren't tracking any
self.term_checker.reset()
logger.info("Starting polling for changes to the track list")
while self.polling:
loop_start = time()
self.update_stream()
self.handle_exceptions()
# wait for the interval unless interrupted, compensating for time elapsed in the loop
elapsed = time() - loop_start
sleep(max(0.1, interval - elapsed))
logger.warning("Term poll ceased!") | Start polling for term updates and streaming. | entailment |
def update_stream(self):
"""
Restarts the stream with the current list of tracking terms.
"""
need_to_restart = False
# If we think we are running, but something has gone wrong in the streaming thread
# Restart it.
if self.stream is not None and not self.stream.running:
logger.warning("Stream exists but isn't running")
self.listener.error = False
self.listener.streaming_exception = None
need_to_restart = True
# Check if the tracking list has changed
if self.term_checker.check():
logger.info("Terms have changed")
need_to_restart = True
# If we aren't running and we are allowing unfiltered streams
if self.stream is None and self.unfiltered:
need_to_restart = True
if not need_to_restart:
return
logger.info("Restarting stream...")
# Stop any old stream
self.stop_stream()
# Start a new stream
self.start_stream() | Restarts the stream with the current list of tracking terms. | entailment |
def start_stream(self):
"""Starts a stream with teh current tracking terms"""
tracking_terms = self.term_checker.tracking_terms()
if len(tracking_terms) > 0 or self.unfiltered:
# we have terms to track, so build a new stream
self.stream = tweepy.Stream(self.auth, self.listener,
stall_warnings=True,
timeout=90,
retry_count=self.retry_count)
if len(tracking_terms) > 0:
logger.info("Starting new twitter stream with %s terms:", len(tracking_terms))
logger.info(" %s", repr(tracking_terms))
# Launch it in a new thread
self.stream.filter(track=tracking_terms, async=True, languages=self.languages)
else:
logger.info("Starting new unfiltered stream")
self.stream.sample(async=True, languages=self.languages) | Starts a stream with teh current tracking terms | entailment |
def stop_stream(self):
"""
Stops the current stream. Blocks until this is done.
"""
if self.stream is not None:
# There is a streaming thread
logger.warning("Stopping twitter stream...")
self.stream.disconnect()
self.stream = None
# wait a few seconds to allow the streaming to actually stop
sleep(self.STOP_TIMEOUT) | Stops the current stream. Blocks until this is done. | entailment |
def enrich(self, tweet):
""" Apply the local presentation logic to the fetched data."""
tweet = urlize_tweet(expand_tweet_urls(tweet))
# parses created_at "Wed Aug 27 13:08:45 +0000 2008"
if settings.USE_TZ:
tweet['datetime'] = datetime.strptime(tweet['created_at'], '%a %b %d %H:%M:%S +0000 %Y').replace(tzinfo=timezone.utc)
else:
tweet['datetime'] = datetime.strptime(tweet['created_at'], '%a %b %d %H:%M:%S +0000 %Y')
return tweet | Apply the local presentation logic to the fetched data. | entailment |
def get_user_cache_key(**kwargs):
""" Generate suitable key to cache twitter tag context
"""
key = 'get_tweets_%s' % ('_'.join([str(kwargs[key]) for key in sorted(kwargs) if kwargs[key]]))
not_allowed = re.compile('[^%s]' % ''.join([chr(i) for i in range(33, 128)]))
key = not_allowed.sub('', key)
return key | Generate suitable key to cache twitter tag context | entailment |
def get_search_cache_key(prefix, *args):
""" Generate suitable key to cache twitter tag context
"""
key = '%s_%s' % (prefix, '_'.join([str(arg) for arg in args if arg]))
not_allowed = re.compile('[^%s]' % ''.join([chr(i) for i in range(33, 128)]))
key = not_allowed.sub('', key)
return key | Generate suitable key to cache twitter tag context | entailment |
def urlize_tweet(tweet):
""" Turn #hashtag and @username in a text to Twitter hyperlinks,
similar to the ``urlize()`` function in Django.
"""
text = tweet.get('html', tweet['text'])
for hash in tweet['entities']['hashtags']:
text = text.replace('#%s' % hash['text'], TWITTER_HASHTAG_URL % (quote(hash['text'].encode("utf-8")), hash['text']))
for mention in tweet['entities']['user_mentions']:
text = text.replace('@%s' % mention['screen_name'], TWITTER_USERNAME_URL % (quote(mention['screen_name']), mention['screen_name']))
tweet['html'] = text
return tweet | Turn #hashtag and @username in a text to Twitter hyperlinks,
similar to the ``urlize()`` function in Django. | entailment |
def expand_tweet_urls(tweet):
""" Replace shortened URLs with long URLs in the twitter status, and add the "RT" flag.
Should be used before urlize_tweet
"""
if 'retweeted_status' in tweet:
text = 'RT @{user}: {text}'.format(user=tweet['retweeted_status']['user']['screen_name'],
text=tweet['retweeted_status']['text'])
urls = tweet['retweeted_status']['entities']['urls']
else:
text = tweet['text']
urls = tweet['entities']['urls']
for url in urls:
text = text.replace(url['url'], '<a href="%s">%s</a>' % (url['expanded_url'], url['display_url']))
tweet['html'] = text
return tweet | Replace shortened URLs with long URLs in the twitter status, and add the "RT" flag.
Should be used before urlize_tweet | entailment |
def safe_power(a, b):
"""
Same power of a ^ b
:param a: Number a
:param b: Number b
:return: a ^ b
"""
if abs(a) > MAX_POWER or abs(b) > MAX_POWER:
raise ValueError('Number too high!')
return a ** b | Same power of a ^ b
:param a: Number a
:param b: Number b
:return: a ^ b | entailment |
def rabin_miller(p):
"""
Performs a rabin-miller primality test
:param p: Number to test
:return: Bool of whether num is prime
"""
# From this stackoverflow answer: https://codegolf.stackexchange.com/questions/26739/super-speedy-totient-function
if p < 2:
return False
if p != 2 and p & 1 == 0:
return False
s = p - 1
while s & 1 == 0:
s >>= 1
for x in range(10):
a = random.randrange(p - 1) + 1
temp = s
mod = pow(a, temp, p)
while temp != p - 1 and mod != 1 and mod != p - 1:
mod = (mod * mod) % p
temp = temp * 2
if mod != p - 1 and temp % 2 == 0:
return False
return True | Performs a rabin-miller primality test
:param p: Number to test
:return: Bool of whether num is prime | entailment |
def zero_width_split(pattern, string):
"""
Split a string on a regex that only matches zero-width strings
:param pattern: Regex pattern that matches zero-width strings
:param string: String to split on.
:return: Split array
"""
splits = list((m.start(), m.end()) for m in regex.finditer(pattern, string, regex.VERBOSE))
starts = [0] + [i[1] for i in splits]
ends = [i[0] for i in splits] + [len(string)]
return [string[start:end] for start, end in zip(starts, ends)] | Split a string on a regex that only matches zero-width strings
:param pattern: Regex pattern that matches zero-width strings
:param string: String to split on.
:return: Split array | entailment |
def roll_group(group):
"""
Rolls a group of dice in 2d6, 3d10, d12, etc. format
:param group: String of dice group
:return: Array of results
"""
group = regex.match(r'^(\d*)d(\d+)$', group, regex.IGNORECASE)
num_of_dice = int(group[1]) if group[1] != '' else 1
type_of_dice = int(group[2])
assert num_of_dice > 0
result = []
for i in range(num_of_dice):
result.append(random.randint(1, type_of_dice))
return result | Rolls a group of dice in 2d6, 3d10, d12, etc. format
:param group: String of dice group
:return: Array of results | entailment |
def num_equal(result, operator, comparator):
"""
Returns the number of elements in a list that pass a comparison
:param result: The list of results of a dice roll
:param operator: Operator in string to perform comparison on:
Either '+', '-', or '*'
:param comparator: The value to compare
:return:
"""
if operator == '<':
return len([x for x in result if x < comparator])
elif operator == '>':
return len([x for x in result if x > comparator])
elif operator == '=':
return len([x for x in result if x == comparator])
else:
raise ValueError | Returns the number of elements in a list that pass a comparison
:param result: The list of results of a dice roll
:param operator: Operator in string to perform comparison on:
Either '+', '-', or '*'
:param comparator: The value to compare
:return: | entailment |
def roll_dice(roll, *, functions=True, floats=True):
"""
Rolls dice in dice notation with advanced syntax used according to tinyurl.com/pydice
:param roll: Roll in dice notation
:return: Result of roll, and an explanation string
"""
roll = ''.join(roll.split())
roll = regex.sub(r'(?<=d)%', '100', roll, regex.IGNORECASE)
roll = roll.replace('^', '**')
roll = zero_width_split(r'((?<=[\(\),%^\/+*-])(?=.))|((?<=.)(?=[\(\),%^\/+*-]))', roll) # Split the string on the boundary between operators and other chars
string = []
results = []
for group in roll:
if group in '()/=<>,%^+*-' or group in DEFAULT_FUNCTIONS: #Append operators without modification
results.append(group)
string.append(group)
continue
try:
explode = regex.match(r'^((\d*)d(\d+))!$', group, regex.IGNORECASE) # Regex for exploding dice, ie. 2d10!, 4d100!, d12!, etc.
specific_explode = regex.match(r'^((\d*)d(\d+))!(\d+)$', group) # Regex for exploding dice on specific number, ie. d20!10 or d12!4
comparison_explode = regex.match(r'^((\d*)d(\d+))!([<>])(\d+)$', group, regex.IGNORECASE) # Regex for exploding dice with a comparison, ie. d20!>10, d6!<2
penetrate = regex.match(r'^((\d*)d(\d+))!p$', group, regex.IGNORECASE) # Penetrating dice are the same as exploding except any dice after the initial number are added with a -1 penalty
specific_penetrate = regex.match(r'^((\d*)d(\d+))!p(\d+)$', group, regex.IGNORECASE) # See above
comparison_penetrate = regex.match(r'^((\d*)d(\d+))!p([<>])(\d+)$', group, regex.IGNORECASE) # See above
reroll = regex.match(r'^((\d*)d(\d+))([Rr])$', group, regex.IGNORECASE) # Reroll on a one, matches 1d6R, 4d12r, etc.
specific_reroll = regex.match(r'^((\d*)d(\d+))([Rr])(\d+)$', group, regex.IGNORECASE) # Reroll on a specific number
comparison_reroll = regex.match(r'^((\d*)d(\d+))([Rr])([<>])(\d+)$', group, regex.IGNORECASE) # Reroll on a comparison
success_comparison = regex.match(r'^((?:\d*)d(\d+))([<>])(\d+)$', group, regex.IGNORECASE) # Regex for dice with comparison, ie. 2d10>4, 5d3<2, etc.
success_fail_comparison = regex.match(r'^((?:\d*)d(\d+))(?|((<)(\d+)f(>)(\d+))|((>)(\d+)f(<)(\d+)))$', group, regex.IGNORECASE) # Regex for dice with success comparison and failure comparison.
keep = regex.match(r'^((?:\d*)d\d+)([Kk])(\d*)$', group, regex.IGNORECASE) # Regex for keeping a number of dice, ie. 2d10K, 2d10k3, etc.
drop = regex.match(r'^((?:\d*)d\d+)([Xx])(\d*)$', group, regex.IGNORECASE) # As above but with dropping dice and X
individual = regex.match(r'^((\d*)d(\d+))([asm])(\d+)$', group, regex.IGNORECASE) #Regex for rolling dice with a modifier attached to each roll
normal = regex.match(r'^((\d*)d(\d+))$', group, regex.IGNORECASE) # Regex for normal dice rolls
literal = regex.match(r'^(\d+)(?!\.)$', group, regex.IGNORECASE) # Regex for number literals.
float_literal = regex.match(r'^(\.\d+)|(\d+.\d+)$', group, regex.IGNORECASE) # Regex for floats
if explode is not None: # Handle exploding dice without a comparison modifier.
type_of_dice = int(explode[3])
result = []
last_result = roll_group(explode[1])
result.extend(last_result)
number_to_roll = num_equal(last_result, '=', type_of_dice)
while number_to_roll != 0:
last_result = roll_group(str(number_to_roll) + 'd' + str(type_of_dice)) # Reroll dice
result.extend(last_result)
number_to_roll = num_equal(last_result, '=', type_of_dice) # Check how many dice we have to reroll again
results.append(sum(result))
roll = ','.join([('!' + str(i) if i == type_of_dice else str(i)) for i in result]) # Build a string of the dice rolls, adding an exclamation mark before every roll that resulted in an explosion.
string.append('[%s]' % roll)
elif specific_explode is not None: # Handle exploding dice without a comparison modifier.
type_of_dice = int(specific_explode[3])
comparator = int(specific_explode[4])
assert 0 < comparator <= type_of_dice
result = []
last_result = roll_group(specific_explode[1])
result.extend(last_result)
number_to_roll = num_equal(last_result, '=', comparator)
while number_to_roll != 0:
last_result = roll_group(str(number_to_roll) + 'd' + str(type_of_dice))
result.extend(last_result)
number_to_roll = num_equal(last_result, '=', comparator)
results.append(sum(result))
roll = ','.join([('!' + str(i) if i == comparator else str(i)) for i in result]) # Build a string of the dice rolls, adding an exclamation mark before every roll that resulted in an explosion.
string.append('[%s]' % roll)
elif comparison_explode is not None: # Handle exploding dice with a comparison modifier
type_of_dice = int(comparison_explode[3])
comparator = int(comparison_explode[5])
if comparison_explode[4] == '>': # Ensure comparison is within bounds
assert 0 < comparator < type_of_dice
else:
assert 1 < comparator <= type_of_dice
result = []
last_result = roll_group(comparison_explode[1])
result.extend(last_result)
if comparison_explode[4] == '>':
number_to_roll = num_equal(last_result, '>', comparator)
while number_to_roll != 0:
last_result = roll_group(str(number_to_roll) + 'd' + str(type_of_dice))
result.extend(last_result)
number_to_roll = num_equal(last_result, '>', comparator)
roll = ','.join([('!' + str(i) if i > comparator else str(i)) for i in
result]) # Same as on other explodes except with a > or < comparison
else:
number_to_roll = num_equal(last_result, '<', comparator)
while number_to_roll != 0:
last_result = roll_group(str(number_to_roll) + 'd' + str(type_of_dice))
result.extend(last_result)
number_to_roll = num_equal(last_result, '<', comparator)
roll = ','.join([('!' + str(i) if i < comparator else str(i)) for i in
result]) # Same as on other explodes except with a > or < comparison
results.append(sum(result))
string.append('[%s]' % roll)
elif penetrate is not None: # Handle penetrating dice without a comparison modifier.
type_of_dice = int(penetrate[3])
first_num = int(penetrate[2])
result = []
last_result = roll_group(penetrate[1])
result.extend(last_result)
number_to_roll = num_equal(last_result, '=', type_of_dice)
while number_to_roll != 0:
last_result = roll_group(str(number_to_roll) + 'd' + str(type_of_dice))
result.extend(last_result)
number_to_roll = num_equal(last_result, '=', type_of_dice)
pre_result = result[:first_num] # Add the first rolls with no modifier
pre_result.extend([x - 1 for x in result[first_num:]]) # Add the second rolls with a -1 modifier
results.append(sum(pre_result))
roll = ','.join(['!' + str(i) if i == type_of_dice else str(i) for i in result[:first_num]]) # Add the first numbers, without the -1 but with a ! when roll is penetration
roll += (',' if len(pre_result) > first_num else '') # Only add the comma in between if there's at least one penetration
roll += ','.join([('!' + str(i) + '-1' if i == type_of_dice else str(i) + '-1') for i in result[first_num:]]) # Add the penetration dice with the '-1' tacked on the end
string.append('[%s]' % roll)
elif specific_penetrate is not None: # Handle penetrating dice without a comparison modifier.
type_of_dice = int(specific_penetrate[3])
first_num = int(specific_penetrate[2])
comparator = int(specific_penetrate[4])
assert 0 < comparator <= type_of_dice
result = []
last_result = roll_group(specific_penetrate[1])
result.extend(last_result)
number_to_roll = num_equal(last_result, '=', comparator)
while number_to_roll != 0:
last_result = roll_group(str(number_to_roll) + 'd' + str(type_of_dice))
result.extend(last_result)
number_to_roll = num_equal(last_result, '=', comparator)
pre_result = result[:first_num] # Same as normal penetration
pre_result.extend([x - 1 for x in result[first_num:]])
results.append(sum(pre_result))
roll = ','.join(['!' + str(i) if i == comparator else str(i) for i in result[:first_num]]) # Same as above
roll += (',' if len(pre_result) > first_num else '')
roll += ','.join([('!' + str(i) + '-1' if i == comparator else str(i) + '-1') for i in result[first_num:]])
string.append('[%s]' % roll)
elif comparison_penetrate is not None: # Handle penetrating dice without a comparison modifier.
type_of_dice = int(comparison_penetrate[3])
comparator = int(comparison_penetrate[5])
first_num = int(comparison_penetrate[2])
if comparison_penetrate[4] == '>': # Ensure comparison is within bounds
assert 0 < comparator < type_of_dice
else:
assert 1 < comparator <= type_of_dice
result = []
last_result = roll_group(comparison_penetrate[1])
result.extend(last_result)
# Do penetration based on more than or less than sign.
if comparison_penetrate[4] == '>':
number_to_roll = num_equal(last_result, '>', comparator)
while number_to_roll != 0:
last_result = roll_group(str(number_to_roll) + 'd' + str(type_of_dice))
result.extend(last_result)
number_to_roll = num_equal(last_result, '>', comparator)
else:
number_to_roll = num_equal(last_result, '<', comparator)
while number_to_roll != 0:
last_result = roll_group(str(number_to_roll) + 'd' + str(type_of_dice))
result.extend(last_result)
number_to_roll = num_equal(last_result, '<', comparator)
pre_result = result[:first_num]
pre_result.extend([x - 1 for x in result[first_num:]])
results.append(sum(pre_result))
if comparison_penetrate[4] == '>':
roll = ','.join(
['!' + str(i) if i > comparator else str(i) for i in result[:first_num]]) # Same as above
roll += (',' if len(pre_result) > first_num else '')
roll += ','.join(
[('!' + str(i) + '-1' if i > comparator else str(i) + '-1') for i in result[first_num:]])
else:
roll = ','.join(
['!' + str(i) if i < comparator else str(i) for i in result[:first_num]]) # Same as above
roll += (',' if len(pre_result) > first_num else '')
roll += ','.join(
[('!' + str(i) + '-1' if i < comparator else str(i) + '-1') for i in result[first_num:]])
string.append('[%s]' % roll)
elif reroll is not None: # Handle rerolling dice without a comparison modifier (ie. on 1)
type_of_dice = int(reroll[3])
result_strings = []
roll_strings = []
result = roll_group(reroll[1])
repeat = True if reroll[4] == 'R' else False # Reroll just once or infinite number of times
if repeat: #Handle rerolling the dice and building a string of all the rerolled ones
for i in range(len(result)):
prev = [result[i]]
while result[i] == 1:
result[i] = random.randint(1, type_of_dice)
prev.append(result[i])
roll_strings.append([str(x) for x in prev])
else:
for i in range(len(result)):
prev = [result[i]]
if result[i] == 1:
result[i] = random.randint(1, type_of_dice)
prev.append(result[i])
roll_strings.append([str(x) for x in prev])
results.append(sum(result))
for roll_string in roll_strings:
roll_string.reverse()
result_strings.append('%s' % roll_string[0] + ('~' if len(roll_string) > 1 else '') + '~'.join(roll_string[1:])) #Build the string
roll = ','.join(result_strings)
string.append('[%s]' % roll)
elif specific_reroll is not None: # Handle rerolling dice on a specific number, see reroll
type_of_dice = int(specific_reroll[3])
comparator = int(specific_reroll[5])
assert 0 < comparator <= type_of_dice # Ensure comparison is within bounds
result_strings = []
roll_strings = []
result = roll_group(specific_reroll[1])
repeat = True if specific_reroll[4] == 'R' else False
if repeat:
for i in range(len(result)):
prev = [result[i]]
while result[i] == comparator:
result[i] = random.randint(1, type_of_dice)
prev.append(result[i])
roll_strings.append([str(x) for x in prev])
else:
for i in range(len(result)):
prev = [result[i]]
if result[i] == comparator:
result[i] = random.randint(1, type_of_dice)
prev.append(result[i])
roll_strings.append([str(x) for x in prev])
results.append(sum(result))
for roll_string in roll_strings:
roll_string.reverse()
result_strings.append('%s' % roll_string[0] + ('~' if len(roll_string) > 1 else '') + '~'.join(roll_string[1:]))
roll = ','.join(result_strings)
string.append('[%s]' % roll)
elif comparison_reroll is not None: # Handle rerolling dice with a comparison modifier.
type_of_dice = int(comparison_reroll[3])
comparator = int(comparison_reroll[6])
if comparison_reroll[5] == '>': # Ensure comparison is within bounds
assert 0 < comparator < type_of_dice
else:
assert 1 < comparator <= type_of_dice
result_strings = []
roll_strings = []
result = roll_group(comparison_reroll[1])
repeat = True if comparison_reroll[4] == 'R' else False
if comparison_reroll[5] == '>':
if repeat:
for i in range(len(result)):
prev = [result[i]]
while result[i] > comparator:
result[i] = random.randint(1, type_of_dice)
prev.append(result[i])
roll_strings.append([str(x) for x in prev])
else:
for i in range(len(result)):
prev = [result[i]]
if result[i] > comparator:
result[i] = random.randint(1, type_of_dice)
prev.append(result[i])
roll_strings.append([str(x) for x in prev])
else:
if repeat:
for i in range(len(result)):
prev = [result[i]]
while result[i] < comparator:
result[i] = random.randint(1, type_of_dice)
prev.append(result[i])
roll_strings.append([str(x) for x in prev])
else:
for i in range(len(result)):
prev = [result[i]]
if result[i] < comparator:
result[i] = random.randint(1, type_of_dice)
prev.append(result[i])
roll_strings.append([str(x) for x in prev])
results.append(sum(result))
for roll_string in roll_strings:
roll_string.reverse()
result_strings.append('%s' % roll_string[0] + ('~' if len(roll_string) > 1 else '') + '~'.join(roll_string[1:]))
roll = ','.join(result_strings)
string.append('[%s]' % roll)
elif success_comparison is not None:
group_result = roll_group(success_comparison[1])
result = []
result_string = []
type_of_dice = int(success_comparison[2])
comparator = int(success_comparison[4])
if success_comparison[3] == '>': # Ensure comparison is within bounds
assert 0 < comparator < type_of_dice
else:
assert 1 < comparator <= type_of_dice
for die in group_result:
if success_comparison[3] == '>':
result.append(1 if die > comparator else 0)
result_string.append('!' + str(die) if die > comparator else str(die))
else:
result.append(1 if die < comparator else 0)
result_string.append('!' + str(die) if die < comparator else str(die))
results.append(sum(result))
roll = ','.join(result_string) # Craft the string, adding an exclamation mark before every string that passed the comparison.
string.append('[%s]' % roll)
elif success_fail_comparison is not None:
group_result = roll_group(success_fail_comparison[1])
result = []
result_string = []
type_of_dice = int(success_fail_comparison[2])
success_comp = int(success_fail_comparison[5])
fail_comp = int(success_fail_comparison[7])
# Ensure both comparisons are within bounds
if success_fail_comparison[4] == '>':
assert 0 < success_comp < type_of_dice
assert 1 < fail_comp <= type_of_dice
else:
assert 1 < success_comp <= type_of_dice
assert 0 < fail_comp < type_of_dice
for die in group_result:
if success_fail_comparison[4] == '>': # Get the actual list of successes and fails with both comparisons
if die > success_comp:
result.append(1)
result_string.append('!' + str(die))
elif die < fail_comp:
result.append(-1)
result_string.append('*' + str(die))
else:
result.append(0)
result_string.append(str(die))
else:
if die < success_comp:
result.append(1)
result_string.append('!' + str(die))
elif die > fail_comp:
result.append(-1)
result_string.append('*' + str(die))
else:
result.append(0)
result_string.append(str(die))
results.append(sum(result)) #
roll = ','.join(result_string)
string.append('[%s]' % roll)
elif keep is not None: # Handle rolling dice and keeping the x highest or lowest values
group_result = roll_group(keep[1])
group_result.sort(reverse=True if keep[
2] == 'K' else False) # Uppercase is keep highest and lowercase is keep lowest.
num_to_keep = int(keep[3] if keep[3] != '' else 1)
assert 1 <= num_to_keep < len(group_result)
results.append(sum(group_result[:num_to_keep]))
roll = ','.join([str(i) for i in group_result[
:num_to_keep]]) + ' ~~ ' # This time format the string with all kept rolls on the left and dropped rolls on the right
roll += ','.join([str(i) for i in group_result[num_to_keep:]])
string.append('[%s]' % roll)
elif drop is not None:
group_result = roll_group(drop[1])
group_result.sort(reverse=True if drop[2] == 'X' else False) # Same thing as keep dice
num_to_drop = int(drop[3] if drop[3] != '' else 1)
assert 1 <= num_to_drop < len(group_result)
results.append(sum(group_result[:num_to_drop]))
roll = ','.join([str(i) for i in group_result[num_to_drop:]]) + ' ~~ ' # Same as above.
roll += ','.join([str(i) for i in group_result[:num_to_drop]])
string.append('[%s]' % roll)
elif individual is not None:
group_result = roll_group(individual[1])
result = []
for i, j in enumerate(group_result): #add to each roll
if individual[4] == 'a':
result.append(j + int(individual[5]))
elif individual[4] == 's':
result.append(j - int(individual[5]))
elif individual[4] == 'm':
result.append(j * int(individual[5]))
else:
raise ValueError
results.append(sum(result))
roll = ','.join([str(x) + individual[4] + individual[5] for x in group_result]) #Create string with the modifier on each roll
string.append('[%s]' % roll)
elif normal is not None:
group_result = roll_group(group)
results.append(sum(group_result))
roll = ','.join([str(i) for i in group_result])
string.append('[%s]' % roll)
elif literal is not None:
results.append(int(literal[1])) # Just append the integer value
string.append(literal[1])
elif float_literal is not None:
if floats:
results.append(float(group))
string.append(group)
else:
raise TypeError
else:
raise Exception
except Exception:
raise DiceGroupException('"%s" is not a valid dicegroup.' % group)
parser = SimpleEval(floats=floats, functions=functions) #The parser object parses the dice rolls and functions
try:
final_result = parser.eval(''.join([str(x) for x in results])) #Call the parser to parse into one value
if not floats:
final_result = int(final_result)
except Exception:
raise DiceOperatorException('Error parsing operators and or functions')
#Create explanation string and remove extraneous spaces
explanation = ''.join(string)
explanation = zero_width_split(r"""((?<=[\/%^+])(?![\/,]))| # Split between /, %, ^, and +
((?<![\/,])(?=[\/%^+]))| # Same as above
((?<=[^(])(?=-))(?!-[^[]*])| # Split in front of - that are not in a roll
(?<=-)(?=[^\d()a-z])| # Same for splitting after - and before non-literals
(?<=[\d)\]]-)(?=.)(?![^[]*])| # Split after a - that is not in a roll
(?<=,)(?![^[]*])| # Split after a comma that is not in a roll
(?<=([^,]\*))(?!\*)| # Split after a * that is not in a roll
(?<![,\*])(?=\*) # Split before a * that is not in a roll""", explanation) #Split on ops to properly format the explanation
explanation = ' '.join(explanation)
explanation = explanation.strip()
explanation = regex.sub(r'[ \t]{2,}', ' ', explanation)
return final_result, explanation | Rolls dice in dice notation with advanced syntax used according to tinyurl.com/pydice
:param roll: Roll in dice notation
:return: Result of roll, and an explanation string | entailment |
def eval(self, expr):
"""
Evaluates an expression
:param expr: Expression to evaluate
:return: Result of expression
"""
# set a copy of the expression aside, so we can give nice errors...
self.expr = expr
# and evaluate:
return self._eval(ast.parse(expr.strip()).body[0].value) | Evaluates an expression
:param expr: Expression to evaluate
:return: Result of expression | entailment |
def _eval(self, node):
"""
Evaluate a node
:param node: Node to eval
:return: Result of node
"""
try:
handler = self.nodes[type(node)]
except KeyError:
raise ValueError("Sorry, {0} is not available in this evaluator".format(type(node).__name__))
return handler(node) | Evaluate a node
:param node: Node to eval
:return: Result of node | entailment |
def _eval_num(self, node):
"""
Evaluate a numerical node
:param node: Node to eval
:return: Result of node
"""
if self.floats:
return node.n
else:
return int(node.n) | Evaluate a numerical node
:param node: Node to eval
:return: Result of node | entailment |
def _eval_unaryop(self, node):
"""
Evaluate a unary operator node (ie. -2, +3)
Currently just supports positive and negative
:param node: Node to eval
:return: Result of node
"""
return self.operators[type(node.op)](self._eval(node.operand)) | Evaluate a unary operator node (ie. -2, +3)
Currently just supports positive and negative
:param node: Node to eval
:return: Result of node | entailment |
def _eval_binop(self, node):
"""
Evaluate a binary operator node (ie. 2+3, 5*6, 3 ** 4)
:param node: Node to eval
:return: Result of node
"""
return self.operators[type(node.op)](self._eval(node.left),
self._eval(node.right)) | Evaluate a binary operator node (ie. 2+3, 5*6, 3 ** 4)
:param node: Node to eval
:return: Result of node | entailment |
def _eval_call(self, node):
"""
Evaluate a function call
:param node: Node to eval
:return: Result of node
"""
try:
func = self.functions[node.func.id]
except KeyError:
raise NameError(node.func.id)
value = func(
*(self._eval(a) for a in node.args),
**dict(self._eval(k) for k in node.keywords)
)
if value is True:
return 1
elif value is False:
return 0
else:
return value | Evaluate a function call
:param node: Node to eval
:return: Result of node | entailment |
def roll_dice(self): # Roll dice with current roll
"""
Rolls dicebag and sets last_roll and last_explanation to roll results
:return: Roll results.
"""
roll = roll_dice(self.roll, floats=self.floats, functions=self.functions)
self._last_roll = roll[0]
self._last_explanation = roll[1]
return self.last_roll, self.last_explanation | Rolls dicebag and sets last_roll and last_explanation to roll results
:return: Roll results. | entailment |
def roll(self, value):
"""
Setter for roll, verifies the roll is valid
:param value: Roll
:return: None
"""
if type(value) != str: # Make sure dice roll is a str
raise TypeError('Dice roll must be a string in dice notation')
try:
roll_dice(value) # Make sure dice roll parses as a valid roll and not an error
except Exception as e:
raise ValueError('Dice roll specified was not a valid diceroll.\n%s\n' % str(e))
else:
self._roll = value | Setter for roll, verifies the roll is valid
:param value: Roll
:return: None | entailment |
def run(files, temp_folder, arg=''):
"Look for pdb.set_trace() commands in python files."
parser = get_parser()
args = parser.parse_args(arg.split())
py_files = filter_python_files(files)
if args.ignore:
orig_file_list = original_files(py_files, temp_folder)
py_files = set(orig_file_list) - set(args.ignore)
py_files = [temp_folder + f for f in py_files]
return check_files(py_files).value() | Look for pdb.set_trace() commands in python files. | entailment |
def checks():
"""
An iterator of valid checks that are in the installed checkers package.
yields check name, check module
"""
checkers_dir = os.path.dirname(checkers.__file__)
mod_names = [name for _, name, _ in pkgutil.iter_modules([checkers_dir])]
for name in mod_names:
mod = importlib.import_module("checkers.{0}".format(name))
# Does the module have a "run" function
if isinstance(getattr(mod, 'run', None), types.FunctionType):
# has a run method, yield it
yield getattr(mod, 'CHECK_NAME', name), mod | An iterator of valid checks that are in the installed checkers package.
yields check name, check module | entailment |
def files_to_check(commit_only):
"""
Validate the commit diff.
Make copies of the staged changes for analysis.
"""
global TEMP_FOLDER
safe_directory = tempfile.mkdtemp()
TEMP_FOLDER = safe_directory
files = get_files(commit_only=commit_only, copy_dest=safe_directory)
try:
yield files
finally:
shutil.rmtree(safe_directory) | Validate the commit diff.
Make copies of the staged changes for analysis. | entailment |
def main(commit_only=True):
"""
Run the configured code checks.
Return system exit code.
1 - reject commit
0 - accept commit
"""
global TEMP_FOLDER
exit_code = 0
hook_checks = HookConfig(get_config_file())
with files_to_check(commit_only) as files:
for name, mod in checks():
default = getattr(mod, 'DEFAULT', 'off')
if hook_checks.is_enabled(name, default=default):
if hasattr(mod, 'REQUIRED_FILES'):
for filename in mod.REQUIRED_FILES:
if os.path.isfile(filename):
try:
shutil.copy(filename, TEMP_FOLDER)
except shutil.Error:
# Copied over by a previous check
continue
args = hook_checks.arguments(name)
tmp_files = [os.path.join(TEMP_FOLDER, f) for f in files]
if args:
errors = mod.run(tmp_files, TEMP_FOLDER, args)
else:
errors = mod.run(tmp_files, TEMP_FOLDER)
if errors:
title_print("Checking {0}".format(name))
print((errors.replace(TEMP_FOLDER + "/", '')))
print("")
exit_code = 1
if exit_code == 1:
title_print("Rejecting commit")
return exit_code | Run the configured code checks.
Return system exit code.
1 - reject commit
0 - accept commit | entailment |
def get_files(commit_only=True, copy_dest=None):
"Get copies of files for analysis."
if commit_only:
real_files = bash(
"git diff --cached --name-status | "
"grep -v -E '^D' | "
"awk '{ print ( $(NF) ) }' "
).value().strip()
else:
real_files = bash(
"git ls-tree --name-only --full-tree -r HEAD"
).value().strip()
if real_files:
return create_fake_copies(real_files.split('\n'), copy_dest)
return [] | Get copies of files for analysis. | entailment |
def create_fake_copies(files, destination):
"""
Create copies of the given list of files in the destination given.
Creates copies of the actual files to be committed using
git show :<filename>
Return a list of destination files.
"""
dest_files = []
for filename in files:
leaf_dest_folder = os.path.join(destination, os.path.dirname(filename))
if not os.path.exists(leaf_dest_folder):
os.makedirs(leaf_dest_folder)
dest_file = os.path.join(destination, filename)
bash("git show :{filename} > {dest_file}".format(
filename=filename,
dest_file=dest_file)
)
dest_files.append(os.path.realpath(dest_file))
return dest_files | Create copies of the given list of files in the destination given.
Creates copies of the actual files to be committed using
git show :<filename>
Return a list of destination files. | entailment |
def filter_python_files(files):
"Get all python files from the list of files."
py_files = []
for f in files:
# If we end in .py, or if we don't have an extension and file says that
# we are a python script, then add us to the list
extension = os.path.splitext(f)[-1]
if extension:
if extension == '.py':
py_files.append(f)
elif 'python' in open(f, 'r').readline():
py_files.append(f)
elif 'python script' in bash('file {}'.format(f)).value().lower():
py_files.append(f)
return py_files | Get all python files from the list of files. | entailment |
def configuration(self, plugin):
"""
Get plugin configuration.
Return a tuple of (on|off|default, args)
"""
conf = self.config.get(plugin, "default;").split(';')
if len(conf) == 1:
conf.append('')
return tuple(conf) | Get plugin configuration.
Return a tuple of (on|off|default, args) | entailment |
def run(files, temp_folder):
"Check frosted errors in the code base."
try:
import frosted # NOQA
except ImportError:
return NO_FROSTED_MSG
py_files = filter_python_files(files)
cmd = 'frosted {0}'.format(' '.join(py_files))
return bash(cmd).value() | Check frosted errors in the code base. | entailment |
def run(files, temp_folder):
"""Check isort errors in the code base.
For the --quiet option, at least isort >= 4.1.1 is required.
https://github.com/timothycrosley/isort/blob/develop/CHANGELOG.md#411
"""
try:
import isort # NOQA
except ImportError:
return NO_ISORT_MSG
py_files = filter_python_files(files)
# --quiet because isort >= 4.1 outputs its logo in the console by default.
return bash('isort -df --quiet {0}'.format(' '.join(py_files))).value() | Check isort errors in the code base.
For the --quiet option, at least isort >= 4.1.1 is required.
https://github.com/timothycrosley/isort/blob/develop/CHANGELOG.md#411 | entailment |
def run(files, temp_folder, arg=None):
"Check we're not committing to a blocked branch"
parser = get_parser()
argos = parser.parse_args(arg.split())
current_branch = bash('git symbolic-ref HEAD').value()
current_branch = current_branch.replace('refs/heads/', '').strip()
if current_branch in argos.branches:
return ("Branch '{0}' is blocked from being "
"committed to.".format(current_branch)) | Check we're not committing to a blocked branch | entailment |
def run(files, temp_folder, arg=None):
"Check coding convention of the code base."
try:
import pylint
except ImportError:
return NO_PYLINT_MSG
# set default level of threshold
arg = arg or SCORE
py_files = filter_python_files(files)
if not py_files:
return False
str_py_files = " ".join(py_files)
cmd = "{0} {1}".format(PYLINT_CMD, str_py_files)
output = bash(cmd).value()
if 'rated' not in output:
return False
score = float(re.search("(\d.\d\d)/10", output).group(1))
if score >= float(arg):
return False
return ("Pylint appreciated your {0} as {1},"
"required threshold is {2}".format(PYLINT_TARGET, score, arg)
) | Check coding convention of the code base. | entailment |
def run(files, temp_folder):
"Check to see if python files are py3 compatible"
errors = []
for py_file in filter_python_files(files):
# We only want to show errors if we CAN'T compile to py3.
# but we want to show all the errors at once.
b = bash('python3 -m py_compile {0}'.format(py_file))
if b.stderr:
b = bash('2to3-2.7 {file}'.format(file=py_file))
errors.append(b.value())
return "\n".join(errors) | Check to see if python files are py3 compatible | entailment |
def run(files, temp_folder):
"Check flake8 errors in the code base."
try:
import flake8 # NOQA
except ImportError:
return NO_FLAKE_MSG
try:
from flake8.engine import get_style_guide
except ImportError:
# We're on a new version of flake8
from flake8.api.legacy import get_style_guide
py_files = filter_python_files(files)
if not py_files:
return
DEFAULT_CONFIG = join(temp_folder, get_config_file())
with change_folder(temp_folder):
flake8_style = get_style_guide(config_file=DEFAULT_CONFIG)
out, err = StringIO(), StringIO()
with redirected(out, err):
flake8_style.check_files(py_files)
return out.getvalue().strip() + err.getvalue().strip() | Check flake8 errors in the code base. | entailment |
def tictactoe(w, i, player, opponent, grid=None):
"Put two strategies to a classic battle of wits."
grid = grid or empty_grid
while True:
w.render_to_terminal(w.array_from_text(view(grid)))
if is_won(grid):
print(whose_move(grid), "wins.")
break
if not successors(grid):
print("A draw.")
break
grid = player(w, i, grid)
player, opponent = opponent, player | Put two strategies to a classic battle of wits. | entailment |
def memo(f):
"Return a function like f that remembers and reuses results of past calls."
table = {}
def memo_f(*args):
try:
return table[args]
except KeyError:
table[args] = value = f(*args)
return value
return memo_f | Return a function like f that remembers and reuses results of past calls. | entailment |
def human_play(w, i, grid):
"Just ask for a move."
plaint = ''
prompt = whose_move(grid) + " move? [1-9] "
while True:
w.render_to_terminal(w.array_from_text(view(grid)
+ '\n\n' + plaint + prompt))
key = c = i.next()
try:
move = int(key)
except ValueError:
pass
else:
if 1 <= move <= 9:
successor = apply_move(grid, from_human_move(move))
if successor: return successor
plaint = ("Hey, that's illegal. Give me one of these digits:\n\n"
+ (grid_format
% tuple(move if apply_move(grid, from_human_move(move)) else '-'
for move in range(1, 10))
+ '\n\n')) | Just ask for a move. | entailment |
def max_play(w, i, grid):
"Play like Spock, except breaking ties by drunk_value."
return min(successors(grid),
key=lambda succ: (evaluate(succ), drunk_value(succ))) | Play like Spock, except breaking ties by drunk_value. | entailment |
def drunk_value(grid):
"Return the expected value to the player if both players play at random."
if is_won(grid): return -1
succs = successors(grid)
return -average(map(drunk_value, succs)) if succs else 0 | Return the expected value to the player if both players play at random. | entailment |
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