INSTRUCTION stringlengths 1 46.3k | RESPONSE stringlengths 75 80.2k |
|---|---|
Returns content type and parameters from given header
:param header: string
:return: tuple containing content type and dictionary of
parameters | def _parse_content_type_header(header):
"""Returns content type and parameters from given header
:param header: string
:return: tuple containing content type and dictionary of
parameters
"""
tokens = header.split(';')
content_type, params = tokens[0].strip(), tokens[1:]
params_dic... |
Returns encodings from given HTTP Header Dict.
:param headers: dictionary to extract encoding from.
:rtype: str | def get_encoding_from_headers(headers):
"""Returns encodings from given HTTP Header Dict.
:param headers: dictionary to extract encoding from.
:rtype: str
"""
content_type = headers.get('content-type')
if not content_type:
return None
content_type, params = _parse_content_type_he... |
Iterate over slices of a string. | def iter_slices(string, slice_length):
"""Iterate over slices of a string."""
pos = 0
if slice_length is None or slice_length <= 0:
slice_length = len(string)
while pos < len(string):
yield string[pos:pos + slice_length]
pos += slice_length |
Returns the requested content back in unicode.
:param r: Response object to get unicode content from.
Tried:
1. charset from content-type
2. fall back and replace all unicode characters
:rtype: str | def get_unicode_from_response(r):
"""Returns the requested content back in unicode.
:param r: Response object to get unicode content from.
Tried:
1. charset from content-type
2. fall back and replace all unicode characters
:rtype: str
"""
warnings.warn((
'In requests 3.0, get... |
Re-quote the given URI.
This function passes the given URI through an unquote/quote cycle to
ensure that it is fully and consistently quoted.
:rtype: str | def requote_uri(uri):
"""Re-quote the given URI.
This function passes the given URI through an unquote/quote cycle to
ensure that it is fully and consistently quoted.
:rtype: str
"""
safe_with_percent = "!#$%&'()*+,/:;=?@[]~"
safe_without_percent = "!#$&'()*+,/:;=?@[]~"
try:
# ... |
This function allows you to check if an IP belongs to a network subnet
Example: returns True if ip = 192.168.1.1 and net = 192.168.1.0/24
returns False if ip = 192.168.1.1 and net = 192.168.100.0/24
:rtype: bool | def address_in_network(ip, net):
"""This function allows you to check if an IP belongs to a network subnet
Example: returns True if ip = 192.168.1.1 and net = 192.168.1.0/24
returns False if ip = 192.168.1.1 and net = 192.168.100.0/24
:rtype: bool
"""
ipaddr = struct.unpack('=L', sock... |
Very simple check of the cidr format in no_proxy variable.
:rtype: bool | def is_valid_cidr(string_network):
"""
Very simple check of the cidr format in no_proxy variable.
:rtype: bool
"""
if string_network.count('/') == 1:
try:
mask = int(string_network.split('/')[1])
except ValueError:
return False
if mask < 1 or mask > ... |
Set the environment variable 'env_name' to 'value'
Save previous value, yield, and then restore the previous value stored in
the environment variable 'env_name'.
If 'value' is None, do nothing | def set_environ(env_name, value):
"""Set the environment variable 'env_name' to 'value'
Save previous value, yield, and then restore the previous value stored in
the environment variable 'env_name'.
If 'value' is None, do nothing"""
value_changed = value is not None
if value_changed:
o... |
Returns whether we should bypass proxies or not.
:rtype: bool | def should_bypass_proxies(url, no_proxy):
"""
Returns whether we should bypass proxies or not.
:rtype: bool
"""
# Prioritize lowercase environment variables over uppercase
# to keep a consistent behaviour with other http projects (curl, wget).
get_proxy = lambda k: os.environ.get(k) or os.e... |
Select a proxy for the url, if applicable.
:param url: The url being for the request
:param proxies: A dictionary of schemes or schemes and hosts to proxy URLs | def select_proxy(url, proxies):
"""Select a proxy for the url, if applicable.
:param url: The url being for the request
:param proxies: A dictionary of schemes or schemes and hosts to proxy URLs
"""
proxies = proxies or {}
urlparts = urlparse(url)
if urlparts.hostname is None:
retur... |
Given a URL that may or may not have a scheme, prepend the given scheme.
Does not replace a present scheme with the one provided as an argument.
:rtype: str | def prepend_scheme_if_needed(url, new_scheme):
"""Given a URL that may or may not have a scheme, prepend the given scheme.
Does not replace a present scheme with the one provided as an argument.
:rtype: str
"""
scheme, netloc, path, params, query, fragment = urlparse(url, new_scheme)
# urlpars... |
Given a url with authentication components, extract them into a tuple of
username,password.
:rtype: (str,str) | def get_auth_from_url(url):
"""Given a url with authentication components, extract them into a tuple of
username,password.
:rtype: (str,str)
"""
parsed = urlparse(url)
try:
auth = (unquote(parsed.username), unquote(parsed.password))
except (AttributeError, TypeError):
auth ... |
Verifies that header value is a string which doesn't contain
leading whitespace or return characters. This prevents unintended
header injection.
:param header: tuple, in the format (name, value). | def check_header_validity(header):
"""Verifies that header value is a string which doesn't contain
leading whitespace or return characters. This prevents unintended
header injection.
:param header: tuple, in the format (name, value).
"""
name, value = header
if isinstance(value, bytes):
... |
Given a url remove the fragment and the authentication part.
:rtype: str | def urldefragauth(url):
"""
Given a url remove the fragment and the authentication part.
:rtype: str
"""
scheme, netloc, path, params, query, fragment = urlparse(url)
# see func:`prepend_scheme_if_needed`
if not netloc:
netloc, path = path, netloc
netloc = netloc.rsplit('@', 1... |
Move file pointer back to its recorded starting position
so it can be read again on redirect. | def rewind_body(prepared_request):
"""Move file pointer back to its recorded starting position
so it can be read again on redirect.
"""
body_seek = getattr(prepared_request.body, 'seek', None)
if body_seek is not None and isinstance(prepared_request._body_position, integer_types):
try:
... |
This is very similar to Version.__str__, but has one subtle differences
with the way it handles the release segment. | def canonicalize_version(version):
"""
This is very similar to Version.__str__, but has one subtle differences
with the way it handles the release segment.
"""
try:
version = Version(version)
except InvalidVersion:
# Legacy versions cannot be normalized
return version
... |
Generate the python source for a node tree. | def generate(node, environment, name, filename, stream=None,
defer_init=False, optimized=True):
"""Generate the python source for a node tree."""
if not isinstance(node, nodes.Template):
raise TypeError('Can\'t compile non template nodes')
generator = environment.code_generator_class(en... |
Does the node have a safe representation? | def has_safe_repr(value):
"""Does the node have a safe representation?"""
if value is None or value is NotImplemented or value is Ellipsis:
return True
if type(value) in (bool, int, float, complex, range_type, Markup) + string_types:
return True
if type(value) in (tuple, list, set, froze... |
Check if the names passed are accessed undeclared. The return value
is a set of all the undeclared names from the sequence of names found. | def find_undeclared(nodes, names):
"""Check if the names passed are accessed undeclared. The return value
is a set of all the undeclared names from the sequence of names found.
"""
visitor = UndeclaredNameVisitor(names)
try:
for node in nodes:
visitor.visit(node)
except Visi... |
Create a copy of the current one. | def copy(self):
"""Create a copy of the current one."""
rv = object.__new__(self.__class__)
rv.__dict__.update(self.__dict__)
rv.symbols = self.symbols.copy()
return rv |
Return an inner frame. | def inner(self, isolated=False):
"""Return an inner frame."""
if isolated:
return Frame(self.eval_ctx, level=self.symbols.level + 1)
return Frame(self.eval_ctx, self) |
Fail with a :exc:`TemplateAssertionError`. | def fail(self, msg, lineno):
"""Fail with a :exc:`TemplateAssertionError`."""
raise TemplateAssertionError(msg, lineno, self.name, self.filename) |
Enable buffering for the frame from that point onwards. | def buffer(self, frame):
"""Enable buffering for the frame from that point onwards."""
frame.buffer = self.temporary_identifier()
self.writeline('%s = []' % frame.buffer) |
Return the buffer contents of the frame. | def return_buffer_contents(self, frame, force_unescaped=False):
"""Return the buffer contents of the frame."""
if not force_unescaped:
if frame.eval_ctx.volatile:
self.writeline('if context.eval_ctx.autoescape:')
self.indent()
self.writeline('r... |
Yield or write into the frame buffer. | def start_write(self, frame, node=None):
"""Yield or write into the frame buffer."""
if frame.buffer is None:
self.writeline('yield ', node)
else:
self.writeline('%s.append(' % frame.buffer, node) |
Simple shortcut for start_write + write + end_write. | def simple_write(self, s, frame, node=None):
"""Simple shortcut for start_write + write + end_write."""
self.start_write(frame, node)
self.write(s)
self.end_write(frame) |
Write a string into the output stream. | def write(self, x):
"""Write a string into the output stream."""
if self._new_lines:
if not self._first_write:
self.stream.write('\n' * self._new_lines)
self.code_lineno += self._new_lines
if self._write_debug_info is not None:
... |
Combination of newline and write. | def writeline(self, x, node=None, extra=0):
"""Combination of newline and write."""
self.newline(node, extra)
self.write(x) |
Add one or more newlines before the next write. | def newline(self, node=None, extra=0):
"""Add one or more newlines before the next write."""
self._new_lines = max(self._new_lines, 1 + extra)
if node is not None and node.lineno != self._last_line:
self._write_debug_info = node.lineno
self._last_line = node.lineno |
Writes a function call to the stream for the current node.
A leading comma is added automatically. The extra keyword
arguments may not include python keywords otherwise a syntax
error could occour. The extra keyword arguments should be given
as python dict. | def signature(self, node, frame, extra_kwargs=None):
"""Writes a function call to the stream for the current node.
A leading comma is added automatically. The extra keyword
arguments may not include python keywords otherwise a syntax
error could occour. The extra keyword arguments shou... |
Pull all the dependencies. | def pull_dependencies(self, nodes):
"""Pull all the dependencies."""
visitor = DependencyFinderVisitor()
for node in nodes:
visitor.visit(node)
for dependency in 'filters', 'tests':
mapping = getattr(self, dependency)
for name in getattr(visitor, depen... |
Dump the function def of a macro or call block. | def macro_body(self, node, frame):
"""Dump the function def of a macro or call block."""
frame = frame.inner()
frame.symbols.analyze_node(node)
macro_ref = MacroRef(node)
explicit_caller = None
skip_special_params = set()
args = []
for idx, arg in enumera... |
Dump the macro definition for the def created by macro_body. | def macro_def(self, macro_ref, frame):
"""Dump the macro definition for the def created by macro_body."""
arg_tuple = ', '.join(repr(x.name) for x in macro_ref.node.args)
name = getattr(macro_ref.node, 'name', None)
if len(macro_ref.node.args) == 1:
arg_tuple += ','
s... |
Return a human readable position for the node. | def position(self, node):
"""Return a human readable position for the node."""
rv = 'line %d' % node.lineno
if self.name is not None:
rv += ' in ' + repr(self.name)
return rv |
Pops the topmost level for assignment tracking and updates the
context variables if necessary. | def pop_assign_tracking(self, frame):
"""Pops the topmost level for assignment tracking and updates the
context variables if necessary.
"""
vars = self._assign_stack.pop()
if not frame.toplevel or not vars:
return
public_names = [x for x in vars if x[:1] != '_... |
Call a block and register it for the template. | def visit_Block(self, node, frame):
"""Call a block and register it for the template."""
level = 0
if frame.toplevel:
# if we know that we are a child template, there is no need to
# check if we are one
if self.has_known_extends:
return
... |
Calls the extender. | def visit_Extends(self, node, frame):
"""Calls the extender."""
if not frame.toplevel:
self.fail('cannot use extend from a non top-level scope',
node.lineno)
# if the number of extends statements in general is zero so
# far, we don't have to add a check... |
Handles includes. | def visit_Include(self, node, frame):
"""Handles includes."""
if node.ignore_missing:
self.writeline('try:')
self.indent()
func_name = 'get_or_select_template'
if isinstance(node.template, nodes.Const):
if isinstance(node.template.value, string_types)... |
Visit regular imports. | def visit_Import(self, node, frame):
"""Visit regular imports."""
self.writeline('%s = ' % frame.symbols.ref(node.target), node)
if frame.toplevel:
self.write('context.vars[%r] = ' % node.target)
if self.environment.is_async:
self.write('await ')
self.writ... |
Visit named imports. | def visit_FromImport(self, node, frame):
"""Visit named imports."""
self.newline(node)
self.write('included_template = %senvironment.get_template('
% (self.environment.is_async and 'await ' or ''))
self.visit(node.template, frame)
self.write(', %r).' % self.nam... |
If alive then mark as dead and return (obj, func, args, kwargs);
otherwise return None | def detach(self):
"""If alive then mark as dead and return (obj, func, args, kwargs);
otherwise return None"""
info = self._registry.get(self)
obj = info and info.weakref()
if obj is not None and self._registry.pop(self, None):
return (obj, info.func, info.args, info.... |
If alive then return (obj, func, args, kwargs);
otherwise return None | def peek(self):
"""If alive then return (obj, func, args, kwargs);
otherwise return None"""
info = self._registry.get(self)
obj = info and info.weakref()
if obj is not None:
return (obj, info.func, info.args, info.kwargs or {}) |
Whether finalizer should be called at exit | def atexit(self):
"""Whether finalizer should be called at exit"""
info = self._registry.get(self)
return bool(info) and info.atexit |
Serialize an element and its child nodes to a string | def tostring(element):
"""Serialize an element and its child nodes to a string"""
rv = []
def serializeElement(element):
if not hasattr(element, "tag"):
if element.docinfo.internalDTD:
if element.docinfo.doctype:
dtd_str = element.docinfo.doctype
... |
Return the visitor function for this node or `None` if no visitor
exists for this node. In that case the generic visit function is
used instead. | def get_visitor(self, node):
"""Return the visitor function for this node or `None` if no visitor
exists for this node. In that case the generic visit function is
used instead.
"""
method = 'visit_' + node.__class__.__name__
return getattr(self, method, None) |
Visit a node. | def visit(self, node, *args, **kwargs):
"""Visit a node."""
f = self.get_visitor(node)
if f is not None:
return f(node, *args, **kwargs)
return self.generic_visit(node, *args, **kwargs) |
Called if no explicit visitor function exists for a node. | def generic_visit(self, node, *args, **kwargs):
"""Called if no explicit visitor function exists for a node."""
for node in node.iter_child_nodes():
self.visit(node, *args, **kwargs) |
As transformers may return lists in some places this method
can be used to enforce a list as return value. | def visit_list(self, node, *args, **kwargs):
"""As transformers may return lists in some places this method
can be used to enforce a list as return value.
"""
rv = self.visit(node, *args, **kwargs)
if not isinstance(rv, list):
rv = [rv]
return rv |
The default method of calling the wrapper subprocess. | def default_subprocess_runner(cmd, cwd=None, extra_environ=None):
"""The default method of calling the wrapper subprocess."""
env = os.environ.copy()
if extra_environ:
env.update(extra_environ)
check_call(cmd, cwd=cwd, env=env) |
Build a wheel from this project.
Returns the name of the newly created file.
In general, this will call the 'build_wheel' hook in the backend.
However, if that was previously called by
'prepare_metadata_for_build_wheel', and the same metadata_directory is
used, the previously b... | def build_wheel(
self, wheel_directory, config_settings=None,
metadata_directory=None):
"""Build a wheel from this project.
Returns the name of the newly created file.
In general, this will call the 'build_wheel' hook in the backend.
However, if that was previou... |
r"""BNInception model architecture from <https://arxiv.org/pdf/1502.03167.pdf>`_ paper. | def bninception(num_classes=1000, pretrained='imagenet'):
r"""BNInception model architecture from <https://arxiv.org/pdf/1502.03167.pdf>`_ paper.
"""
model = BNInception(num_classes=num_classes)
if pretrained is not None:
settings = pretrained_settings['bninception'][pretrained]
assert n... |
3x3 convolution with padding | def conv3x3(in_planes, out_planes, stride=1):
"3x3 convolution with padding"
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
padding=1, bias=True) |
Constructs a ResNet-18 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet | def resnet18(pretrained=False, **kwargs):
"""Constructs a ResNet-18 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
"""
model = ResNet(BasicBlock, [2, 2, 2, 2], **kwargs)
if pretrained:
model.load_state_dict(model_zoo.load_url(model_urls['resnet18'])... |
r"""NASNetALarge model architecture from the
`"NASNet" <https://arxiv.org/abs/1707.07012>`_ paper. | def nasnetamobile(num_classes=1000, pretrained='imagenet'):
r"""NASNetALarge model architecture from the
`"NASNet" <https://arxiv.org/abs/1707.07012>`_ paper.
"""
if pretrained:
settings = pretrained_settings['nasnetamobile'][pretrained]
assert num_classes == settings['num_classes'], \
... |
Constructs a ResNet-50 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet | def resnet50(pretrained=False, **kwargs):
"""Constructs a ResNet-50 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
"""
model = ResNet(Bottleneck, [3, 4, 6, 3], **kwargs)
if pretrained:
model.load_state_dict(model_zoo.load_url(model_urls['resnet50'])... |
Constructs a ResNet-101 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet | def cafferesnet101(num_classes=1000, pretrained='imagenet'):
"""Constructs a ResNet-101 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
"""
model = ResNet(Bottleneck, [3, 4, 23, 3], num_classes=num_classes)
if pretrained is not None:
settings = pretrained... |
Constructs a ResNet-152 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet | def fbresnet152(num_classes=1000, pretrained='imagenet'):
"""Constructs a ResNet-152 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
"""
model = FBResNet(Bottleneck, [3, 8, 36, 3], num_classes=num_classes)
if pretrained is not None:
settings = pretra... |
r"""AlexNet model architecture from the
`"One weird trick..." <https://arxiv.org/abs/1404.5997>`_ paper. | def alexnet(num_classes=1000, pretrained='imagenet'):
r"""AlexNet model architecture from the
`"One weird trick..." <https://arxiv.org/abs/1404.5997>`_ paper.
"""
# https://github.com/pytorch/vision/blob/master/torchvision/models/alexnet.py
model = models.alexnet(pretrained=False)
if pretrained ... |
r"""Densenet-121 model from
`"Densely Connected Convolutional Networks" <https://arxiv.org/pdf/1608.06993.pdf>` | def densenet121(num_classes=1000, pretrained='imagenet'):
r"""Densenet-121 model from
`"Densely Connected Convolutional Networks" <https://arxiv.org/pdf/1608.06993.pdf>`
"""
model = models.densenet121(pretrained=False)
if pretrained is not None:
settings = pretrained_settings['densenet121'][... |
r"""Inception v3 model architecture from
`"Rethinking the Inception Architecture for Computer Vision" <http://arxiv.org/abs/1512.00567>`_. | def inceptionv3(num_classes=1000, pretrained='imagenet'):
r"""Inception v3 model architecture from
`"Rethinking the Inception Architecture for Computer Vision" <http://arxiv.org/abs/1512.00567>`_.
"""
model = models.inception_v3(pretrained=False)
if pretrained is not None:
settings = pretrai... |
Constructs a ResNet-50 model. | def resnet50(num_classes=1000, pretrained='imagenet'):
"""Constructs a ResNet-50 model.
"""
model = models.resnet50(pretrained=False)
if pretrained is not None:
settings = pretrained_settings['resnet50'][pretrained]
model = load_pretrained(model, num_classes, settings)
model = modify... |
r"""SqueezeNet model architecture from the `"SqueezeNet: AlexNet-level
accuracy with 50x fewer parameters and <0.5MB model size"
<https://arxiv.org/abs/1602.07360>`_ paper. | def squeezenet1_0(num_classes=1000, pretrained='imagenet'):
r"""SqueezeNet model architecture from the `"SqueezeNet: AlexNet-level
accuracy with 50x fewer parameters and <0.5MB model size"
<https://arxiv.org/abs/1602.07360>`_ paper.
"""
model = models.squeezenet1_0(pretrained=False)
if pretraine... |
VGG 11-layer model (configuration "A") | def vgg11(num_classes=1000, pretrained='imagenet'):
"""VGG 11-layer model (configuration "A")
"""
model = models.vgg11(pretrained=False)
if pretrained is not None:
settings = pretrained_settings['vgg11'][pretrained]
model = load_pretrained(model, num_classes, settings)
model = modify... |
Sets the learning rate to the initial LR decayed by 10 every 30 epochs | def adjust_learning_rate(optimizer, epoch):
"""Sets the learning rate to the initial LR decayed by 10 every 30 epochs"""
lr = args.lr * (0.1 ** (epoch // 30))
for param_group in optimizer.param_groups:
param_group['lr'] = lr |
r"""NASNetALarge model architecture from the
`"NASNet" <https://arxiv.org/abs/1707.07012>`_ paper. | def nasnetalarge(num_classes=1001, pretrained='imagenet'):
r"""NASNetALarge model architecture from the
`"NASNet" <https://arxiv.org/abs/1707.07012>`_ paper.
"""
if pretrained:
settings = pretrained_settings['nasnetalarge'][pretrained]
assert num_classes == settings['num_classes'], \
... |
Selectable global pooling function with dynamic input kernel size | def adaptive_avgmax_pool2d(x, pool_type='avg', padding=0, count_include_pad=False):
"""Selectable global pooling function with dynamic input kernel size
"""
if pool_type == 'avgmaxc':
x = torch.cat([
F.avg_pool2d(
x, kernel_size=(x.size(2), x.size(3)), padding=padding, co... |
Download a URL to a local file.
Parameters
----------
url : str
The URL to download.
destination : str, None
The destination of the file. If None is given the file is saved to a temporary directory.
progress_bar : bool
Whether to show a command-line progress bar while downlo... | def download_url(url, destination=None, progress_bar=True):
"""Download a URL to a local file.
Parameters
----------
url : str
The URL to download.
destination : str, None
The destination of the file. If None is given the file is saved to a temporary directory.
progress_bar : bo... |
Args:
output (Tensor): NxK tensor that for each of the N examples
indicates the probability of the example belonging to each of
the K classes, according to the model. The probabilities should
sum to one over all classes
target (Tensor): binary NxK ... | def add(self, output, target):
"""
Args:
output (Tensor): NxK tensor that for each of the N examples
indicates the probability of the example belonging to each of
the K classes, according to the model. The probabilities should
sum to one over a... |
Returns the model's average precision for each class
Return:
ap (FloatTensor): 1xK tensor, with avg precision for each class k | def value(self):
"""Returns the model's average precision for each class
Return:
ap (FloatTensor): 1xK tensor, with avg precision for each class k
"""
if self.scores.numel() == 0:
return 0
ap = torch.zeros(self.scores.size(1))
rg = torch.arange(1,... |
PolyNet architecture from the paper
'PolyNet: A Pursuit of Structural Diversity in Very Deep Networks'
https://arxiv.org/abs/1611.05725 | def polynet(num_classes=1000, pretrained='imagenet'):
"""PolyNet architecture from the paper
'PolyNet: A Pursuit of Structural Diversity in Very Deep Networks'
https://arxiv.org/abs/1611.05725
"""
if pretrained:
settings = pretrained_settings['polynet'][pretrained]
assert num_classes... |
Get the cached value.
Returns
-------
value : object
The cached value.
Raises
------
Expired
Raised when `dt` is greater than self.expires. | def unwrap(self, dt):
"""
Get the cached value.
Returns
-------
value : object
The cached value.
Raises
------
Expired
Raised when `dt` is greater than self.expires.
"""
expires = self._expires
if expires i... |
Get the value of a cached object.
Parameters
----------
key : any
The key to lookup.
dt : datetime
The time of the lookup.
Returns
-------
result : any
The value for ``key``.
Raises
------
KeyError
... | def get(self, key, dt):
"""Get the value of a cached object.
Parameters
----------
key : any
The key to lookup.
dt : datetime
The time of the lookup.
Returns
-------
result : any
The value for ``key``.
Raises
... |
Adds a new key value pair to the cache.
Parameters
----------
key : any
The key to use for the pair.
value : any
The value to store under the name ``key``.
expiration_dt : datetime
When should this mapping expire? The cache is considered inval... | def set(self, key, value, expiration_dt):
"""Adds a new key value pair to the cache.
Parameters
----------
key : any
The key to use for the pair.
value : any
The value to store under the name ``key``.
expiration_dt : datetime
When shou... |
Ensures a subdirectory of the working directory.
Parameters
----------
path_parts : iterable[str]
The parts of the path after the working directory. | def ensure_dir(self, *path_parts):
"""Ensures a subdirectory of the working directory.
Parameters
----------
path_parts : iterable[str]
The parts of the path after the working directory.
"""
path = self.getpath(*path_parts)
ensure_directory(path)
... |
Verify that DataFrames in ``frames`` have the same indexing scheme and are
aligned to ``calendar``.
Parameters
----------
frames : list[pd.DataFrame]
calendar : trading_calendars.TradingCalendar
Raises
------
ValueError
If frames have different indexes/columns, or if frame inde... | def verify_frames_aligned(frames, calendar):
"""
Verify that DataFrames in ``frames`` have the same indexing scheme and are
aligned to ``calendar``.
Parameters
----------
frames : list[pd.DataFrame]
calendar : trading_calendars.TradingCalendar
Raises
------
ValueError
I... |
Parameters
----------
sid : int
The asset identifier.
day : datetime64-like
Midnight of the day for which data is requested.
field : string
The price field. e.g. ('open', 'high', 'low', 'close', 'volume')
Returns
-------
float
... | def get_value(self, sid, dt, field):
"""
Parameters
----------
sid : int
The asset identifier.
day : datetime64-like
Midnight of the day for which data is requested.
field : string
The price field. e.g. ('open', 'high', 'low', 'close', ... |
Parameters
----------
asset : zipline.asset.Asset
The asset identifier.
dt : datetime64-like
Midnight of the day for which data is requested.
Returns
-------
pd.Timestamp : The last know dt for the asset and dt;
NaT if no tr... | def get_last_traded_dt(self, asset, dt):
"""
Parameters
----------
asset : zipline.asset.Asset
The asset identifier.
dt : datetime64-like
Midnight of the day for which data is requested.
Returns
-------
pd.Timestamp : The last know... |
Check if all values in a sequence are equal.
Returns True on empty sequences.
Examples
--------
>>> same(1, 1, 1, 1)
True
>>> same(1, 2, 1)
False
>>> same()
True | def same(*values):
"""
Check if all values in a sequence are equal.
Returns True on empty sequences.
Examples
--------
>>> same(1, 1, 1, 1)
True
>>> same(1, 2, 1)
False
>>> same()
True
"""
if not values:
return True
first, rest = values[0], values[1:]
... |
Parameters
----------
*dicts : iterable[dict]
A sequence of dicts all sharing the same keys.
Returns
-------
zipped : dict
A dict whose keys are the union of all keys in *dicts, and whose values
are tuples of length len(dicts) containing the result of looking up
each... | def dzip_exact(*dicts):
"""
Parameters
----------
*dicts : iterable[dict]
A sequence of dicts all sharing the same keys.
Returns
-------
zipped : dict
A dict whose keys are the union of all keys in *dicts, and whose values
are tuples of length len(dicts) containing t... |
Helper for unzip which checks the lengths of each element in it.
Parameters
----------
it : iterable[tuple]
An iterable of tuples. ``unzip`` should map ensure that these are
already tuples.
elem_len : int or None
The expected element length. If this is None it is infered from the... | def _gen_unzip(it, elem_len):
"""Helper for unzip which checks the lengths of each element in it.
Parameters
----------
it : iterable[tuple]
An iterable of tuples. ``unzip`` should map ensure that these are
already tuples.
elem_len : int or None
The expected element length. I... |
Unzip a length n sequence of length m sequences into m seperate length
n sequences.
Parameters
----------
seq : iterable[iterable]
The sequence to unzip.
elem_len : int, optional
The expected length of each element of ``seq``. If not provided this
will be infered from the len... | def unzip(seq, elem_len=None):
"""Unzip a length n sequence of length m sequences into m seperate length
n sequences.
Parameters
----------
seq : iterable[iterable]
The sequence to unzip.
elem_len : int, optional
The expected length of each element of ``seq``. If not provided thi... |
Perform a chained application of ``getattr`` on ``value`` with the values
in ``attrs``.
If ``default`` is supplied, return it if any of the attribute lookups fail.
Parameters
----------
value : object
Root of the lookup chain.
attrs : iterable[str]
Sequence of attributes to loo... | def getattrs(value, attrs, default=_no_default):
"""
Perform a chained application of ``getattr`` on ``value`` with the values
in ``attrs``.
If ``default`` is supplied, return it if any of the attribute lookups fail.
Parameters
----------
value : object
Root of the lookup chain.
... |
Decorator factory for setting attributes on a function.
Doesn't change the behavior of the wrapped function.
Examples
--------
>>> @set_attribute('__name__', 'foo')
... def bar():
... return 3
...
>>> bar()
3
>>> bar.__name__
'foo' | def set_attribute(name, value):
"""
Decorator factory for setting attributes on a function.
Doesn't change the behavior of the wrapped function.
Examples
--------
>>> @set_attribute('__name__', 'foo')
... def bar():
... return 3
...
>>> bar()
3
>>> bar.__name__
... |
Fold a function over a sequence with right associativity.
Parameters
----------
f : callable[any, any]
The function to reduce the sequence with.
The first argument will be the element of the sequence; the second
argument will be the accumulator.
seq : iterable[any]
The s... | def foldr(f, seq, default=_no_default):
"""Fold a function over a sequence with right associativity.
Parameters
----------
f : callable[any, any]
The function to reduce the sequence with.
The first argument will be the element of the sequence; the second
argument will be the acc... |
Invert a dictionary into a dictionary of sets.
>>> invert({'a': 1, 'b': 2, 'c': 1}) # doctest: +SKIP
{1: {'a', 'c'}, 2: {'b'}} | def invert(d):
"""
Invert a dictionary into a dictionary of sets.
>>> invert({'a': 1, 'b': 2, 'c': 1}) # doctest: +SKIP
{1: {'a', 'c'}, 2: {'b'}}
"""
out = {}
for k, v in iteritems(d):
try:
out[v].add(k)
except KeyError:
out[v] = {k}
return out |
r"""Projection vectors to the simplex domain
Implemented according to the paper: Efficient projections onto the
l1-ball for learning in high dimensions, John Duchi, et al. ICML 2008.
Implementation Time: 2011 June 17 by Bin@libin AT pmail.ntu.edu.sg
Optimization Problem: min_{w}\| w - v \|_{2}^{2}
... | def simplex_projection(v, b=1):
r"""Projection vectors to the simplex domain
Implemented according to the paper: Efficient projections onto the
l1-ball for learning in high dimensions, John Duchi, et al. ICML 2008.
Implementation Time: 2011 June 17 by Bin@libin AT pmail.ntu.edu.sg
Optimization Prob... |
Run an example module from zipline.examples. | def run_example(example_name, environ):
"""
Run an example module from zipline.examples.
"""
mod = EXAMPLE_MODULES[example_name]
register_calendar("YAHOO", get_calendar("NYSE"), force=True)
return run_algorithm(
initialize=getattr(mod, 'initialize', None),
handle_data=getattr(m... |
Compute slopes of linear regressions between columns of ``dependents`` and
``independent``.
Parameters
----------
dependents : np.array[N, M]
Array with columns of data to be regressed against ``independent``.
independent : np.array[N, 1]
Independent variable of the regression
a... | def vectorized_beta(dependents, independent, allowed_missing, out=None):
"""
Compute slopes of linear regressions between columns of ``dependents`` and
``independent``.
Parameters
----------
dependents : np.array[N, M]
Array with columns of data to be regressed against ``independent``.
... |
Format a URL for loading data from Bank of Canada. | def _format_url(instrument_type,
instrument_ids,
start_date,
end_date,
earliest_allowed_date):
"""
Format a URL for loading data from Bank of Canada.
"""
return (
"http://www.bankofcanada.ca/stats/results/csv"
"?lP=lookup_{i... |
Load a DataFrame of data from a Bank of Canada site. | def load_frame(url, skiprows):
"""
Load a DataFrame of data from a Bank of Canada site.
"""
return pd.read_csv(
url,
skiprows=skiprows,
skipinitialspace=True,
na_values=["Bank holiday", "Not available"],
parse_dates=["Date"],
index_col="Date",
).dropna... |
There are a couple quirks in the data provided by Bank of Canada.
Check that no new quirks have been introduced in the latest download. | def check_known_inconsistencies(bill_data, bond_data):
"""
There are a couple quirks in the data provided by Bank of Canada.
Check that no new quirks have been introduced in the latest download.
"""
inconsistent_dates = bill_data.index.sym_diff(bond_data.index)
known_inconsistencies = [
... |
The earliest date for which we can load data from this module. | def earliest_possible_date():
"""
The earliest date for which we can load data from this module.
"""
today = pd.Timestamp('now', tz='UTC').normalize()
# Bank of Canada only has the last 10 years of data at any given time.
return today.replace(year=today.year - 10) |
Checks whether the fill price is worse than the order's limit price.
Parameters
----------
fill_price: float
The price to check.
order: zipline.finance.order.Order
The order whose limit price to check.
Returns
-------
bool: Whether the fill price is above the limit price (... | def fill_price_worse_than_limit_price(fill_price, order):
"""
Checks whether the fill price is worse than the order's limit price.
Parameters
----------
fill_price: float
The price to check.
order: zipline.finance.order.Order
The order whose limit price to check.
Returns
... |
Internal utility method to return the trailing mean volume over the
past 'window_length' days, and volatility of close prices for a
specific asset.
Parameters
----------
data : The BarData from which to fetch the daily windows.
asset : The Asset whose data we are fetchin... | def _get_window_data(self, data, asset, window_length):
"""
Internal utility method to return the trailing mean volume over the
past 'window_length' days, and volatility of close prices for a
specific asset.
Parameters
----------
data : The BarData from which to ... |
Validate a `dtype` and `missing_value` passed to Term.__new__.
Ensures that we know how to represent ``dtype``, and that missing_value
is specified for types without default missing values.
Returns
-------
validated_dtype, validated_missing_value : np.dtype, any
The dtype and missing_value... | def validate_dtype(termname, dtype, missing_value):
"""
Validate a `dtype` and `missing_value` passed to Term.__new__.
Ensures that we know how to represent ``dtype``, and that missing_value
is specified for types without default missing values.
Returns
-------
validated_dtype, validated_m... |
Check that value is a valid categorical missing_value.
Raises a TypeError if the value is cannot be used as the missing_value for
a categorical_dtype Term. | def _assert_valid_categorical_missing_value(value):
"""
Check that value is a valid categorical missing_value.
Raises a TypeError if the value is cannot be used as the missing_value for
a categorical_dtype Term.
"""
label_types = LabelArray.SUPPORTED_SCALAR_TYPES
if not isinstance(value, la... |
Pop entries from the `kwargs` passed to cls.__new__ based on the values
in `cls.params`.
Parameters
----------
kwargs : dict
The kwargs passed to cls.__new__.
Returns
-------
params : list[(str, object)]
A list of string, value pairs cont... | def _pop_params(cls, kwargs):
"""
Pop entries from the `kwargs` passed to cls.__new__ based on the values
in `cls.params`.
Parameters
----------
kwargs : dict
The kwargs passed to cls.__new__.
Returns
-------
params : list[(str, objec... |
Return the identity of the Term that would be constructed from the
given arguments.
Identities that compare equal will cause us to return a cached instance
rather than constructing a new one. We do this primarily because it
makes dependency resolution easier.
This is a classme... | def _static_identity(cls,
domain,
dtype,
missing_value,
window_safe,
ndim,
params):
"""
Return the identity of the Term that would be constructed from the... |
Parameters
----------
domain : zipline.pipeline.domain.Domain
The domain of this term.
dtype : np.dtype
Dtype of this term's output.
missing_value : object
Missing value for this term.
ndim : 1 or 2
The dimensionality of this term.
... | def _init(self, domain, dtype, missing_value, window_safe, ndim, params):
"""
Parameters
----------
domain : zipline.pipeline.domain.Domain
The domain of this term.
dtype : np.dtype
Dtype of this term's output.
missing_value : object
Mi... |
The number of extra rows needed for each of our inputs to compute this
term. | def dependencies(self):
"""
The number of extra rows needed for each of our inputs to compute this
term.
"""
extra_input_rows = max(0, self.window_length - 1)
out = {}
for term in self.inputs:
out[term] = extra_input_rows
out[self.mask] = 0
... |
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