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25,700 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | find_undeclared | 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... | python | def find_undeclared(nodes, names):
"""Check if the names passed are accessed undeclared. The return value
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"""
visitor = UndeclaredNameVisitor(names)
try:
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25,701 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | Frame.inner | def inner(self, isolated=False):
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return Frame(self.eval_ctx, self) | python | def inner(self, isolated=False):
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25,702 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | CodeGenerator.buffer | def buffer(self, frame):
"""Enable buffering for the frame from that point onwards."""
frame.buffer = self.temporary_identifier()
self.writeline('%s = []' % frame.buffer) | python | def buffer(self, frame):
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25,703 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | CodeGenerator.return_buffer_contents | def return_buffer_contents(self, frame, force_unescaped=False):
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self.indent()
self.writeline('r... | python | def return_buffer_contents(self, frame, force_unescaped=False):
"""Return the buffer contents of the frame."""
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self.writeline('if context.eval_ctx.autoescape:')
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25,704 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | CodeGenerator.start_write | def start_write(self, frame, node=None):
"""Yield or write into the frame buffer."""
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self.writeline('yield ', node)
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25,705 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | CodeGenerator.simple_write | def simple_write(self, s, frame, node=None):
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self.end_write(frame) | python | def simple_write(self, s, frame, node=None):
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25,706 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | CodeGenerator.write | def write(self, x):
"""Write a string into the output stream."""
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self.stream.write('\n' * self._new_lines)
self.code_lineno += self._new_lines
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... | python | def write(self, x):
"""Write a string into the output stream."""
if self._new_lines:
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25,707 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | CodeGenerator.writeline | def writeline(self, x, node=None, extra=0):
"""Combination of newline and write."""
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self.write(x) | python | def writeline(self, x, node=None, extra=0):
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self.newline(node, extra)
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25,708 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | CodeGenerator.newline | 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)
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self._last_line = node.lineno | python | 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)
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25,709 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | CodeGenerator.signature | def signature(self, node, frame, extra_kwargs=None):
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25,710 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | CodeGenerator.pull_dependencies | def pull_dependencies(self, nodes):
"""Pull all the dependencies."""
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for node in nodes:
visitor.visit(node)
for dependency in 'filters', 'tests':
mapping = getattr(self, dependency)
for name in getattr(visitor, depen... | python | def pull_dependencies(self, nodes):
"""Pull all the dependencies."""
visitor = DependencyFinderVisitor()
for node in nodes:
visitor.visit(node)
for dependency in 'filters', 'tests':
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25,711 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | CodeGenerator.position | def position(self, node):
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rv = 'line %d' % node.lineno
if self.name is not None:
rv += ' in ' + repr(self.name)
return rv | python | def position(self, node):
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25,712 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | CodeGenerator.pop_assign_tracking | def pop_assign_tracking(self, frame):
"""Pops the topmost level for assignment tracking and updates the
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"""
vars = self._assign_stack.pop()
if not frame.toplevel or not vars:
return
public_names = [x for x in vars if x[:1] != '_... | python | def pop_assign_tracking(self, frame):
"""Pops the topmost level for assignment tracking and updates the
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"""
vars = self._assign_stack.pop()
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25,713 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | CodeGenerator.visit_Extends | def visit_Extends(self, node, frame):
"""Calls the extender."""
if not frame.toplevel:
self.fail('cannot use extend from a non top-level scope',
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# if the number of extends statements in general is zero so
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"""Calls the extender."""
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25,714 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | CodeGenerator.visit_Include | 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)... | python | def visit_Include(self, node, frame):
"""Handles includes."""
if node.ignore_missing:
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25,715 | pypa/pipenv | pipenv/vendor/jinja2/compiler.py | CodeGenerator.visit_FromImport | def visit_FromImport(self, node, frame):
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self.newline(node)
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25,716 | pypa/pipenv | pipenv/vendor/backports/weakref.py | finalize.atexit | def atexit(self):
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info = self._registry.get(self)
return bool(info) and info.atexit | python | def atexit(self):
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25,718 | pypa/pipenv | pipenv/vendor/jinja2/visitor.py | NodeVisitor.get_visitor | def get_visitor(self, node):
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25,719 | pypa/pipenv | pipenv/vendor/jinja2/visitor.py | NodeTransformer.visit_list | def visit_list(self, node, *args, **kwargs):
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25,720 | pypa/pipenv | pipenv/vendor/pep517/wrappers.py | Pep517HookCaller.build_wheel | def build_wheel(
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25,721 | Cadene/pretrained-models.pytorch | pretrainedmodels/models/fbresnet/resnet152_load.py | resnet18 | 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'])... | python | 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)
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25,722 | Cadene/pretrained-models.pytorch | pretrainedmodels/models/fbresnet.py | fbresnet152 | def fbresnet152(num_classes=1000, pretrained='imagenet'):
"""Constructs a ResNet-152 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
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model = FBResNet(Bottleneck, [3, 8, 36, 3], num_classes=num_classes)
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settings = pretra... | python | def fbresnet152(num_classes=1000, pretrained='imagenet'):
"""Constructs a ResNet-152 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
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25,723 | Cadene/pretrained-models.pytorch | pretrainedmodels/models/dpn.py | adaptive_avgmax_pool2d | def adaptive_avgmax_pool2d(x, pool_type='avg', padding=0, count_include_pad=False):
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"""Selectable global pooling function with dynamic input kernel size
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25,724 | Cadene/pretrained-models.pytorch | pretrainedmodels/datasets/utils.py | download_url | 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.
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25,725 | quantopian/zipline | zipline/utils/cache.py | CachedObject.unwrap | 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... | python | def unwrap(self, dt):
"""
Get the cached value.
Returns
-------
value : object
The cached value.
Raises
------
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Raised when `dt` is greater than self.expires.
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25,726 | quantopian/zipline | zipline/utils/cache.py | ExpiringCache.get | def get(self, key, dt):
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Parameters
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key : any
The key to lookup.
dt : datetime
The time of the lookup.
Returns
-------
result : any
The value for ``key``.
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25,727 | quantopian/zipline | zipline/utils/cache.py | ExpiringCache.set | def set(self, key, value, expiration_dt):
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value : any
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25,728 | quantopian/zipline | zipline/utils/cache.py | working_dir.ensure_dir | 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)
... | python | 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)
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25,729 | quantopian/zipline | zipline/data/in_memory_daily_bars.py | verify_frames_aligned | 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... | python | def verify_frames_aligned(frames, calendar):
"""
Verify that DataFrames in ``frames`` have the same indexing scheme and are
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----------
frames : list[pd.DataFrame]
calendar : trading_calendars.TradingCalendar
Raises
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25,730 | quantopian/zipline | zipline/utils/functional.py | same | def same(*values):
"""
Check if all values in a sequence are equal.
Returns True on empty sequences.
Examples
--------
>>> same(1, 1, 1, 1)
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>>> same(1, 2, 1)
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>>> same()
True
"""
if not values:
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"""
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
"""
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Returns True on empty sequences.
Examples
--------
>>> same(1, 1, 1, 1)
True
>>> same(1, 2, 1)
False
>>> same()
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25,731 | quantopian/zipline | zipline/utils/functional.py | getattrs | 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.
... | python | 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.
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25,732 | quantopian/zipline | zipline/utils/functional.py | set_attribute | 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__
... | python | 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__
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Examples
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>>> @set_attribute('__name__', 'foo')
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25,733 | quantopian/zipline | zipline/utils/functional.py | foldr | 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... | python | 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
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25,734 | quantopian/zipline | zipline/utils/functional.py | invert | 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 | python | 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 | [
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25,735 | quantopian/zipline | zipline/examples/olmar.py | simplex_projection | 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... | python | 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
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25,736 | quantopian/zipline | zipline/examples/__init__.py | run_example | 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... | python | 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... | [
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25,737 | quantopian/zipline | zipline/pipeline/factors/statistical.py | vectorized_beta | 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``.
... | python | 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``.
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25,738 | quantopian/zipline | zipline/data/treasuries_can.py | _format_url | 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... | python | 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"
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25,739 | quantopian/zipline | zipline/data/treasuries_can.py | load_frame | 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... | python | 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... | [
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25,740 | quantopian/zipline | zipline/data/treasuries_can.py | check_known_inconsistencies | 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 = [
... | python | 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 = [
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25,741 | quantopian/zipline | zipline/data/treasuries_can.py | earliest_possible_date | 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) | python | 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) | [
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25,742 | quantopian/zipline | zipline/finance/slippage.py | fill_price_worse_than_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
... | python | 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
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25,743 | quantopian/zipline | zipline/finance/slippage.py | MarketImpactBase._get_window_data | 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 ... | python | 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.
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----------
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25,744 | quantopian/zipline | zipline/pipeline/term.py | _assert_valid_categorical_missing_value | 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... | python | 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
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25,745 | quantopian/zipline | zipline/pipeline/term.py | Term._static_identity | def _static_identity(cls,
domain,
dtype,
missing_value,
window_safe,
ndim,
params):
"""
Return the identity of the Term that would be constructed from the... | python | def _static_identity(cls,
domain,
dtype,
missing_value,
window_safe,
ndim,
params):
"""
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25,746 | quantopian/zipline | zipline/pipeline/term.py | ComputableTerm.dependencies | 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
... | python | 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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25,747 | quantopian/zipline | zipline/pipeline/term.py | ComputableTerm.to_workspace_value | def to_workspace_value(self, result, assets):
"""
Called with a column of the result of a pipeline. This needs to put
the data into a format that can be used in a workspace to continue
doing computations.
Parameters
----------
result : pd.Series
A mul... | python | def to_workspace_value(self, result, assets):
"""
Called with a column of the result of a pipeline. This needs to put
the data into a format that can be used in a workspace to continue
doing computations.
Parameters
----------
result : pd.Series
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25,748 | quantopian/zipline | zipline/finance/position.py | Position.earn_stock_dividend | def earn_stock_dividend(self, stock_dividend):
"""
Register the number of shares we held at this dividend's ex date so
that we can pay out the correct amount on the dividend's pay date.
"""
return {
'payment_asset': stock_dividend.payment_asset,
'share_cou... | python | def earn_stock_dividend(self, stock_dividend):
"""
Register the number of shares we held at this dividend's ex date so
that we can pay out the correct amount on the dividend's pay date.
"""
return {
'payment_asset': stock_dividend.payment_asset,
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25,749 | quantopian/zipline | zipline/finance/position.py | Position.handle_split | def handle_split(self, asset, ratio):
"""
Update the position by the split ratio, and return the resulting
fractional share that will be converted into cash.
Returns the unused cash.
"""
if self.asset != asset:
raise Exception("updating split with the wrong a... | python | def handle_split(self, asset, ratio):
"""
Update the position by the split ratio, and return the resulting
fractional share that will be converted into cash.
Returns the unused cash.
"""
if self.asset != asset:
raise Exception("updating split with the wrong a... | [
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25,750 | quantopian/zipline | zipline/utils/deprecate.py | deprecated | def deprecated(msg=None, stacklevel=2):
"""
Used to mark a function as deprecated.
Parameters
----------
msg : str
The message to display in the deprecation warning.
stacklevel : int
How far up the stack the warning needs to go, before
showing the relevant calling lines.... | python | def deprecated(msg=None, stacklevel=2):
"""
Used to mark a function as deprecated.
Parameters
----------
msg : str
The message to display in the deprecation warning.
stacklevel : int
How far up the stack the warning needs to go, before
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25,751 | quantopian/zipline | zipline/data/history_loader.py | HistoryCompatibleUSEquityAdjustmentReader._get_adjustments_in_range | def _get_adjustments_in_range(self, asset, dts, field):
"""
Get the Float64Multiply objects to pass to an AdjustedArrayWindow.
For the use of AdjustedArrayWindow in the loader, which looks back
from current simulation time back to a window of data the dictionary is
structured wi... | python | def _get_adjustments_in_range(self, asset, dts, field):
"""
Get the Float64Multiply objects to pass to an AdjustedArrayWindow.
For the use of AdjustedArrayWindow in the loader, which looks back
from current simulation time back to a window of data the dictionary is
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25,752 | quantopian/zipline | zipline/data/history_loader.py | HistoryLoader.history | def history(self, assets, dts, field, is_perspective_after):
"""
A window of pricing data with adjustments applied assuming that the
end of the window is the day before the current simulation time.
Parameters
----------
assets : iterable of Assets
The assets ... | python | def history(self, assets, dts, field, is_perspective_after):
"""
A window of pricing data with adjustments applied assuming that the
end of the window is the day before the current simulation time.
Parameters
----------
assets : iterable of Assets
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25,753 | quantopian/zipline | zipline/sources/requests_csv.py | PandasCSV._lookup_unconflicted_symbol | def _lookup_unconflicted_symbol(self, symbol):
"""
Attempt to find a unique asset whose symbol is the given string.
If multiple assets have held the given symbol, return a 0.
If no asset has held the given symbol, return a NaN.
"""
try:
uppered = symbol.upp... | python | def _lookup_unconflicted_symbol(self, symbol):
"""
Attempt to find a unique asset whose symbol is the given string.
If multiple assets have held the given symbol, return a 0.
If no asset has held the given symbol, return a NaN.
"""
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25,754 | quantopian/zipline | zipline/gens/tradesimulation.py | AlgorithmSimulator._cleanup_expired_assets | def _cleanup_expired_assets(self, dt, position_assets):
"""
Clear out any assets that have expired before starting a new sim day.
Performs two functions:
1. Finds all assets for which we have open orders and clears any
orders whose assets are on or after their auto_close_dat... | python | def _cleanup_expired_assets(self, dt, position_assets):
"""
Clear out any assets that have expired before starting a new sim day.
Performs two functions:
1. Finds all assets for which we have open orders and clears any
orders whose assets are on or after their auto_close_dat... | [
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25,755 | quantopian/zipline | zipline/data/adjustments.py | SQLiteAdjustmentReader.load_adjustments | def load_adjustments(self,
dates,
assets,
should_include_splits,
should_include_mergers,
should_include_dividends,
adjustment_type):
"""
Load collection o... | python | def load_adjustments(self,
dates,
assets,
should_include_splits,
should_include_mergers,
should_include_dividends,
adjustment_type):
"""
Load collection o... | [
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25,756 | quantopian/zipline | zipline/data/adjustments.py | SQLiteAdjustmentReader.unpack_db_to_component_dfs | def unpack_db_to_component_dfs(self, convert_dates=False):
"""Returns the set of known tables in the adjustments file in DataFrame
form.
Parameters
----------
convert_dates : bool, optional
By default, dates are returned in seconds since EPOCH. If
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"""Returns the set of known tables in the adjustments file in DataFrame
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Parameters
----------
convert_dates : bool, optional
By default, dates are returned in seconds since EPOCH. If
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25,757 | quantopian/zipline | zipline/data/adjustments.py | SQLiteAdjustmentReader._df_dtypes | def _df_dtypes(self, table_name, convert_dates):
"""Get dtypes to use when unpacking sqlite tables as dataframes.
"""
out = self._raw_table_dtypes[table_name]
if convert_dates:
out = out.copy()
for date_column in self._datetime_int_cols[table_name]:
... | python | def _df_dtypes(self, table_name, convert_dates):
"""Get dtypes to use when unpacking sqlite tables as dataframes.
"""
out = self._raw_table_dtypes[table_name]
if convert_dates:
out = out.copy()
for date_column in self._datetime_int_cols[table_name]:
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25,758 | quantopian/zipline | zipline/data/adjustments.py | SQLiteAdjustmentWriter.calc_dividend_ratios | def calc_dividend_ratios(self, dividends):
"""
Calculate the ratios to apply to equities when looking back at pricing
history so that the price is smoothed over the ex_date, when the market
adjusts to the change in equity value due to upcoming dividend.
Returns
-------
... | python | def calc_dividend_ratios(self, dividends):
"""
Calculate the ratios to apply to equities when looking back at pricing
history so that the price is smoothed over the ex_date, when the market
adjusts to the change in equity value due to upcoming dividend.
Returns
-------
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25,759 | quantopian/zipline | zipline/data/adjustments.py | SQLiteAdjustmentWriter.write_dividend_data | def write_dividend_data(self, dividends, stock_dividends=None):
"""
Write both dividend payouts and the derived price adjustment ratios.
"""
# First write the dividend payouts.
self._write_dividends(dividends)
self._write_stock_dividends(stock_dividends)
# Secon... | python | def write_dividend_data(self, dividends, stock_dividends=None):
"""
Write both dividend payouts and the derived price adjustment ratios.
"""
# First write the dividend payouts.
self._write_dividends(dividends)
self._write_stock_dividends(stock_dividends)
# Secon... | [
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25,760 | quantopian/zipline | zipline/data/adjustments.py | SQLiteAdjustmentWriter.write | def write(self,
splits=None,
mergers=None,
dividends=None,
stock_dividends=None):
"""
Writes data to a SQLite file to be read by SQLiteAdjustmentReader.
Parameters
----------
splits : pandas.DataFrame, optional
... | python | def write(self,
splits=None,
mergers=None,
dividends=None,
stock_dividends=None):
"""
Writes data to a SQLite file to be read by SQLiteAdjustmentReader.
Parameters
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splits : pandas.DataFrame, optional
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25,761 | quantopian/zipline | zipline/pipeline/mixins.py | CustomTermMixin.compute | def compute(self, today, assets, out, *arrays):
"""
Override this method with a function that writes a value into `out`.
"""
raise NotImplementedError(
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name=type(self).__name__
)
) | python | def compute(self, today, assets, out, *arrays):
"""
Override this method with a function that writes a value into `out`.
"""
raise NotImplementedError(
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name=type(self).__name__
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25,762 | quantopian/zipline | zipline/pipeline/mixins.py | CustomTermMixin._compute | def _compute(self, windows, dates, assets, mask):
"""
Call the user's `compute` function on each window with a pre-built
output array.
"""
format_inputs = self._format_inputs
compute = self.compute
params = self.params
ndim = self.ndim
shape = (le... | python | def _compute(self, windows, dates, assets, mask):
"""
Call the user's `compute` function on each window with a pre-built
output array.
"""
format_inputs = self._format_inputs
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25,763 | quantopian/zipline | zipline/pipeline/mixins.py | DownsampledMixin.compute_extra_rows | def compute_extra_rows(self,
all_dates,
start_date,
end_date,
min_extra_rows):
"""
Ensure that min_extra_rows pushes us back to a computation date.
Parameters
----------
a... | python | def compute_extra_rows(self,
all_dates,
start_date,
end_date,
min_extra_rows):
"""
Ensure that min_extra_rows pushes us back to a computation date.
Parameters
----------
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start_date : pd.Timestamp
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25,764 | quantopian/zipline | zipline/pipeline/mixins.py | DownsampledMixin._compute | def _compute(self, inputs, dates, assets, mask):
"""
Compute by delegating to self._wrapped_term._compute on sample dates.
On non-sample dates, forward-fill from previously-computed samples.
"""
to_sample = dates[select_sampling_indices(dates, self._frequency)]
assert to... | python | def _compute(self, inputs, dates, assets, mask):
"""
Compute by delegating to self._wrapped_term._compute on sample dates.
On non-sample dates, forward-fill from previously-computed samples.
"""
to_sample = dates[select_sampling_indices(dates, self._frequency)]
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25,765 | quantopian/zipline | zipline/utils/preprocess.py | preprocess | def preprocess(*_unused, **processors):
"""
Decorator that applies pre-processors to the arguments of a function before
calling the function.
Parameters
----------
**processors : dict
Map from argument name -> processor function.
A processor function takes three arguments: (fun... | python | def preprocess(*_unused, **processors):
"""
Decorator that applies pre-processors to the arguments of a function before
calling the function.
Parameters
----------
**processors : dict
Map from argument name -> processor function.
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A processor function takes three arguments: (func, argname, argvalue).
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25,766 | quantopian/zipline | zipline/utils/preprocess.py | call | def call(f):
"""
Wrap a function in a processor that calls `f` on the argument before
passing it along.
Useful for creating simple arguments to the `@preprocess` decorator.
Parameters
----------
f : function
Function accepting a single argument and returning a replacement.
Exa... | python | def call(f):
"""
Wrap a function in a processor that calls `f` on the argument before
passing it along.
Useful for creating simple arguments to the `@preprocess` decorator.
Parameters
----------
f : function
Function accepting a single argument and returning a replacement.
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Useful for creating simple arguments to the `@preprocess` decorator.
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25,767 | quantopian/zipline | zipline/utils/preprocess.py | _build_preprocessed_function | def _build_preprocessed_function(func,
processors,
args_defaults,
varargs,
varkw):
"""
Build a preprocessed function with the same signature as `func`.
Uses `exec` internally ... | python | def _build_preprocessed_function(func,
processors,
args_defaults,
varargs,
varkw):
"""
Build a preprocessed function with the same signature as `func`.
Uses `exec` internally ... | [
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25,768 | quantopian/zipline | zipline/data/benchmarks.py | get_benchmark_returns | def get_benchmark_returns(symbol):
"""
Get a Series of benchmark returns from IEX associated with `symbol`.
Default is `SPY`.
Parameters
----------
symbol : str
Benchmark symbol for which we're getting the returns.
The data is provided by IEX (https://iextrading.com/), and we can
... | python | def get_benchmark_returns(symbol):
"""
Get a Series of benchmark returns from IEX associated with `symbol`.
Default is `SPY`.
Parameters
----------
symbol : str
Benchmark symbol for which we're getting the returns.
The data is provided by IEX (https://iextrading.com/), and we can
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25,769 | quantopian/zipline | zipline/pipeline/visualize.py | delimit | def delimit(delimiters, content):
"""
Surround `content` with the first and last characters of `delimiters`.
>>> delimit('[]', "foo") # doctest: +SKIP
'[foo]'
>>> delimit('""', "foo") # doctest: +SKIP
'"foo"'
"""
if len(delimiters) != 2:
raise ValueError(
"`delimit... | python | def delimit(delimiters, content):
"""
Surround `content` with the first and last characters of `delimiters`.
>>> delimit('[]', "foo") # doctest: +SKIP
'[foo]'
>>> delimit('""', "foo") # doctest: +SKIP
'"foo"'
"""
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25,770 | quantopian/zipline | zipline/pipeline/visualize.py | roots | def roots(g):
"Get nodes from graph G with indegree 0"
return set(n for n, d in iteritems(g.in_degree()) if d == 0) | python | def roots(g):
"Get nodes from graph G with indegree 0"
return set(n for n, d in iteritems(g.in_degree()) if d == 0) | [
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25,771 | quantopian/zipline | zipline/pipeline/visualize.py | _render | def _render(g, out, format_, include_asset_exists=False):
"""
Draw `g` as a graph to `out`, in format `format`.
Parameters
----------
g : zipline.pipeline.graph.TermGraph
Graph to render.
out : file-like object
format_ : str {'png', 'svg'}
Output format.
include_asset_ex... | python | def _render(g, out, format_, include_asset_exists=False):
"""
Draw `g` as a graph to `out`, in format `format`.
Parameters
----------
g : zipline.pipeline.graph.TermGraph
Graph to render.
out : file-like object
format_ : str {'png', 'svg'}
Output format.
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25,772 | quantopian/zipline | zipline/pipeline/visualize.py | display_graph | def display_graph(g, format='svg', include_asset_exists=False):
"""
Display a TermGraph interactively from within IPython.
"""
try:
import IPython.display as display
except ImportError:
raise NoIPython("IPython is not installed. Can't display graph.")
if format == 'svg':
... | python | def display_graph(g, format='svg', include_asset_exists=False):
"""
Display a TermGraph interactively from within IPython.
"""
try:
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raise NoIPython("IPython is not installed. Can't display graph.")
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25,773 | quantopian/zipline | zipline/pipeline/visualize.py | format_attrs | def format_attrs(attrs):
"""
Format key, value pairs from attrs into graphviz attrs format
Examples
--------
>>> format_attrs({'key1': 'value1', 'key2': 'value2'}) # doctest: +SKIP
'[key1=value1, key2=value2]'
"""
if not attrs:
return ''
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"""
Format key, value pairs from attrs into graphviz attrs format
Examples
--------
>>> format_attrs({'key1': 'value1', 'key2': 'value2'}) # doctest: +SKIP
'[key1=value1, key2=value2]'
"""
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25,774 | quantopian/zipline | zipline/utils/pool.py | SequentialPool.apply_async | def apply_async(f, args=(), kwargs=None, callback=None):
"""Apply a function but emulate the API of an asynchronous call.
Parameters
----------
f : callable
The function to call.
args : tuple, optional
The positional arguments.
kwargs : dict, opti... | python | def apply_async(f, args=(), kwargs=None, callback=None):
"""Apply a function but emulate the API of an asynchronous call.
Parameters
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f : callable
The function to call.
args : tuple, optional
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25,775 | quantopian/zipline | zipline/utils/cli.py | maybe_show_progress | def maybe_show_progress(it, show_progress, **kwargs):
"""Optionally show a progress bar for the given iterator.
Parameters
----------
it : iterable
The underlying iterator.
show_progress : bool
Should progress be shown.
**kwargs
Forwarded to the click progress bar.
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"""Optionally show a progress bar for the given iterator.
Parameters
----------
it : iterable
The underlying iterator.
show_progress : bool
Should progress be shown.
**kwargs
Forwarded to the click progress bar.
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25,776 | quantopian/zipline | zipline/__main__.py | main | def main(extension, strict_extensions, default_extension, x):
"""Top level zipline entry point.
"""
# install a logbook handler before performing any other operations
logbook.StderrHandler().push_application()
create_args(x, zipline.extension_args)
load_extensions(
default_extension,
... | python | def main(extension, strict_extensions, default_extension, x):
"""Top level zipline entry point.
"""
# install a logbook handler before performing any other operations
logbook.StderrHandler().push_application()
create_args(x, zipline.extension_args)
load_extensions(
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25,777 | quantopian/zipline | zipline/__main__.py | ipython_only | def ipython_only(option):
"""Mark that an option should only be exposed in IPython.
Parameters
----------
option : decorator
A click.option decorator.
Returns
-------
ipython_only_dec : decorator
A decorator that correctly applies the argument even when not
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"""Mark that an option should only be exposed in IPython.
Parameters
----------
option : decorator
A click.option decorator.
Returns
-------
ipython_only_dec : decorator
A decorator that correctly applies the argument even when not
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25,778 | quantopian/zipline | zipline/__main__.py | zipline_magic | def zipline_magic(line, cell=None):
"""The zipline IPython cell magic.
"""
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extensions=[],
strict=True,
environ=os.environ,
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try:
return run.main(
# put our overrides at the start of the parameter list so that
... | python | def zipline_magic(line, cell=None):
"""The zipline IPython cell magic.
"""
load_extensions(
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25,779 | quantopian/zipline | zipline/__main__.py | ingest | def ingest(bundle, assets_version, show_progress):
"""Ingest the data for the given bundle.
"""
bundles_module.ingest(
bundle,
os.environ,
pd.Timestamp.utcnow(),
assets_version,
show_progress,
) | python | def ingest(bundle, assets_version, show_progress):
"""Ingest the data for the given bundle.
"""
bundles_module.ingest(
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25,780 | quantopian/zipline | zipline/__main__.py | clean | def clean(bundle, before, after, keep_last):
"""Clean up data downloaded with the ingest command.
"""
bundles_module.clean(
bundle,
before,
after,
keep_last,
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"""Clean up data downloaded with the ingest command.
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25,781 | quantopian/zipline | zipline/__main__.py | bundles | def bundles():
"""List all of the available data bundles.
"""
for bundle in sorted(bundles_module.bundles.keys()):
if bundle.startswith('.'):
# hide the test data
continue
try:
ingestions = list(
map(text_type, bundles_module.ingestions_for... | python | def bundles():
"""List all of the available data bundles.
"""
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if bundle.startswith('.'):
# hide the test data
continue
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25,782 | quantopian/zipline | zipline/pipeline/filters/filter.py | binary_operator | def binary_operator(op):
"""
Factory function for making binary operator methods on a Filter subclass.
Returns a function "binary_operator" suitable for implementing functions
like __and__ or __or__.
"""
# When combining a Filter with a NumericalExpression, we use this
# attrgetter instance... | python | def binary_operator(op):
"""
Factory function for making binary operator methods on a Filter subclass.
Returns a function "binary_operator" suitable for implementing functions
like __and__ or __or__.
"""
# When combining a Filter with a NumericalExpression, we use this
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25,783 | quantopian/zipline | zipline/pipeline/filters/filter.py | unary_operator | def unary_operator(op):
"""
Factory function for making unary operator methods for Filters.
"""
valid_ops = {'~'}
if op not in valid_ops:
raise ValueError("Invalid unary operator %s." % op)
def unary_operator(self):
# This can't be hoisted up a scope because the types returned b... | python | def unary_operator(op):
"""
Factory function for making unary operator methods for Filters.
"""
valid_ops = {'~'}
if op not in valid_ops:
raise ValueError("Invalid unary operator %s." % op)
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25,784 | quantopian/zipline | zipline/pipeline/filters/filter.py | NumExprFilter.create | def create(cls, expr, binds):
"""
Helper for creating new NumExprFactors.
This is just a wrapper around NumericalExpression.__new__ that always
forwards `bool` as the dtype, since Filters can only be of boolean
dtype.
"""
return cls(expr=expr, binds=binds, dtype=... | python | def create(cls, expr, binds):
"""
Helper for creating new NumExprFactors.
This is just a wrapper around NumericalExpression.__new__ that always
forwards `bool` as the dtype, since Filters can only be of boolean
dtype.
"""
return cls(expr=expr, binds=binds, dtype=... | [
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25,785 | quantopian/zipline | zipline/pipeline/filters/filter.py | NumExprFilter._compute | def _compute(self, arrays, dates, assets, mask):
"""
Compute our result with numexpr, then re-apply `mask`.
"""
return super(NumExprFilter, self)._compute(
arrays,
dates,
assets,
mask,
) & mask | python | def _compute(self, arrays, dates, assets, mask):
"""
Compute our result with numexpr, then re-apply `mask`.
"""
return super(NumExprFilter, self)._compute(
arrays,
dates,
assets,
mask,
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25,786 | quantopian/zipline | zipline/pipeline/filters/filter.py | PercentileFilter._validate | def _validate(self):
"""
Ensure that our percentile bounds are well-formed.
"""
if not 0.0 <= self._min_percentile < self._max_percentile <= 100.0:
raise BadPercentileBounds(
min_percentile=self._min_percentile,
max_percentile=self._max_percent... | python | def _validate(self):
"""
Ensure that our percentile bounds are well-formed.
"""
if not 0.0 <= self._min_percentile < self._max_percentile <= 100.0:
raise BadPercentileBounds(
min_percentile=self._min_percentile,
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25,787 | quantopian/zipline | zipline/pipeline/filters/filter.py | PercentileFilter._compute | def _compute(self, arrays, dates, assets, mask):
"""
For each row in the input, compute a mask of all values falling between
the given percentiles.
"""
# TODO: Review whether there's a better way of handling small numbers
# of columns.
data = arrays[0].copy().asty... | python | def _compute(self, arrays, dates, assets, mask):
"""
For each row in the input, compute a mask of all values falling between
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# TODO: Review whether there's a better way of handling small numbers
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25,788 | quantopian/zipline | zipline/data/treasuries.py | parse_treasury_csv_column | def parse_treasury_csv_column(column):
"""
Parse a treasury CSV column into a more human-readable format.
Columns start with 'RIFLGFC', followed by Y or M (year or month), followed
by a two-digit number signifying number of years/months, followed by _N.B.
We only care about the middle two entries, ... | python | def parse_treasury_csv_column(column):
"""
Parse a treasury CSV column into a more human-readable format.
Columns start with 'RIFLGFC', followed by Y or M (year or month), followed
by a two-digit number signifying number of years/months, followed by _N.B.
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25,789 | quantopian/zipline | zipline/data/treasuries.py | get_daily_10yr_treasury_data | def get_daily_10yr_treasury_data():
"""Download daily 10 year treasury rates from the Federal Reserve and
return a pandas.Series."""
url = "https://www.federalreserve.gov/datadownload/Output.aspx?rel=H15" \
"&series=bcb44e57fb57efbe90002369321bfb3f&lastObs=&from=&to=" \
"&filetype=csv&la... | python | def get_daily_10yr_treasury_data():
"""Download daily 10 year treasury rates from the Federal Reserve and
return a pandas.Series."""
url = "https://www.federalreserve.gov/datadownload/Output.aspx?rel=H15" \
"&series=bcb44e57fb57efbe90002369321bfb3f&lastObs=&from=&to=" \
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25,790 | quantopian/zipline | zipline/data/minute_bars.py | _sid_subdir_path | def _sid_subdir_path(sid):
"""
Format subdir path to limit the number directories in any given
subdirectory to 100.
The number in each directory is designed to support at least 100000
equities.
Parameters
----------
sid : int
Asset identifier.
Returns
-------
out :... | python | def _sid_subdir_path(sid):
"""
Format subdir path to limit the number directories in any given
subdirectory to 100.
The number in each directory is designed to support at least 100000
equities.
Parameters
----------
sid : int
Asset identifier.
Returns
-------
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25,791 | quantopian/zipline | zipline/data/minute_bars.py | convert_cols | def convert_cols(cols, scale_factor, sid, invalid_data_behavior):
"""Adapt OHLCV columns into uint32 columns.
Parameters
----------
cols : dict
A dict mapping each column name (open, high, low, close, volume)
to a float column to convert to uint32.
scale_factor : int
Factor ... | python | def convert_cols(cols, scale_factor, sid, invalid_data_behavior):
"""Adapt OHLCV columns into uint32 columns.
Parameters
----------
cols : dict
A dict mapping each column name (open, high, low, close, volume)
to a float column to convert to uint32.
scale_factor : int
Factor ... | [
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25,792 | quantopian/zipline | zipline/data/minute_bars.py | BcolzMinuteBarMetadata.write | def write(self, rootdir):
"""
Write the metadata to a JSON file in the rootdir.
Values contained in the metadata are:
version : int
The value of FORMAT_VERSION of this class.
ohlc_ratio : int
The default ratio by which to multiply the pricing data to
... | python | def write(self, rootdir):
"""
Write the metadata to a JSON file in the rootdir.
Values contained in the metadata are:
version : int
The value of FORMAT_VERSION of this class.
ohlc_ratio : int
The default ratio by which to multiply the pricing data to
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25,793 | quantopian/zipline | zipline/data/minute_bars.py | BcolzMinuteBarWriter.open | def open(cls, rootdir, end_session=None):
"""
Open an existing ``rootdir`` for writing.
Parameters
----------
end_session : Timestamp (optional)
When appending, the intended new ``end_session``.
"""
metadata = BcolzMinuteBarMetadata.read(rootdir)
... | python | def open(cls, rootdir, end_session=None):
"""
Open an existing ``rootdir`` for writing.
Parameters
----------
end_session : Timestamp (optional)
When appending, the intended new ``end_session``.
"""
metadata = BcolzMinuteBarMetadata.read(rootdir)
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25,794 | quantopian/zipline | zipline/data/minute_bars.py | BcolzMinuteBarWriter._init_ctable | def _init_ctable(self, path):
"""
Create empty ctable for given path.
Parameters
----------
path : string
The path to rootdir of the new ctable.
"""
# Only create the containing subdir on creation.
# This is not to be confused with the `.bcolz... | python | def _init_ctable(self, path):
"""
Create empty ctable for given path.
Parameters
----------
path : string
The path to rootdir of the new ctable.
"""
# Only create the containing subdir on creation.
# This is not to be confused with the `.bcolz... | [
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25,795 | quantopian/zipline | zipline/data/minute_bars.py | BcolzMinuteBarWriter._ensure_ctable | def _ensure_ctable(self, sid):
"""Ensure that a ctable exists for ``sid``, then return it."""
sidpath = self.sidpath(sid)
if not os.path.exists(sidpath):
return self._init_ctable(sidpath)
return bcolz.ctable(rootdir=sidpath, mode='a') | python | def _ensure_ctable(self, sid):
"""Ensure that a ctable exists for ``sid``, then return it."""
sidpath = self.sidpath(sid)
if not os.path.exists(sidpath):
return self._init_ctable(sidpath)
return bcolz.ctable(rootdir=sidpath, mode='a') | [
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25,796 | quantopian/zipline | zipline/data/minute_bars.py | BcolzMinuteBarWriter.pad | def pad(self, sid, date):
"""
Fill sid container with empty data through the specified date.
If the last recorded trade is not at the close, then that day will be
padded with zeros until its close. Any day after that (up to and
including the specified date) will be padded with `... | python | def pad(self, sid, date):
"""
Fill sid container with empty data through the specified date.
If the last recorded trade is not at the close, then that day will be
padded with zeros until its close. Any day after that (up to and
including the specified date) will be padded with `... | [
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25,797 | quantopian/zipline | zipline/data/minute_bars.py | BcolzMinuteBarWriter.set_sid_attrs | def set_sid_attrs(self, sid, **kwargs):
"""Write all the supplied kwargs as attributes of the sid's file.
"""
table = self._ensure_ctable(sid)
for k, v in kwargs.items():
table.attrs[k] = v | python | def set_sid_attrs(self, sid, **kwargs):
"""Write all the supplied kwargs as attributes of the sid's file.
"""
table = self._ensure_ctable(sid)
for k, v in kwargs.items():
table.attrs[k] = v | [
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25,798 | quantopian/zipline | zipline/data/minute_bars.py | BcolzMinuteBarWriter.write | def write(self, data, show_progress=False, invalid_data_behavior='warn'):
"""Write a stream of minute data.
Parameters
----------
data : iterable[(int, pd.DataFrame)]
The data to write. Each element should be a tuple of sid, data
where data has the following form... | python | def write(self, data, show_progress=False, invalid_data_behavior='warn'):
"""Write a stream of minute data.
Parameters
----------
data : iterable[(int, pd.DataFrame)]
The data to write. Each element should be a tuple of sid, data
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25,799 | quantopian/zipline | zipline/data/minute_bars.py | BcolzMinuteBarWriter.data_len_for_day | def data_len_for_day(self, day):
"""
Return the number of data points up to and including the
provided day.
"""
day_ix = self._session_labels.get_loc(day)
# Add one to the 0-indexed day_ix to get the number of days.
num_days = day_ix + 1
return num_days * ... | python | def data_len_for_day(self, day):
"""
Return the number of data points up to and including the
provided day.
"""
day_ix = self._session_labels.get_loc(day)
# Add one to the 0-indexed day_ix to get the number of days.
num_days = day_ix + 1
return num_days * ... | [
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