code stringlengths 66 870k | docstring stringlengths 19 26.7k | func_name stringlengths 1 138 | language stringclasses 1
value | repo stringlengths 7 68 | path stringlengths 5 324 | url stringlengths 46 389 | license stringclasses 7
values |
|---|---|---|---|---|---|---|---|
def _build_date(date, kwargs):
"""
Builds the date argument for event rules.
"""
if date is None:
if not kwargs:
raise ValueError('Must pass a date or kwargs')
else:
return datetime.date(**kwargs)
elif kwargs:
raise ValueError('Cannot pass kwargs and ... |
Builds the date argument for event rules.
| _build_date | python | quantopian/zipline | zipline/utils/events.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/events.py | Apache-2.0 |
def _build_time(time, kwargs):
"""
Builds the time argument for event rules.
"""
tz = kwargs.pop('tz', 'UTC')
if time:
if kwargs:
raise ValueError('Cannot pass kwargs and a time')
else:
return ensure_utc(time, tz)
elif not kwargs:
raise ValueError(... |
Builds the time argument for event rules.
| _build_time | python | quantopian/zipline | zipline/utils/events.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/events.py | Apache-2.0 |
def lossless_float_to_int(funcname, func, argname, arg):
"""
A preprocessor that coerces integral floats to ints.
Receipt of non-integral floats raises a TypeError.
"""
if not isinstance(arg, float):
return arg
arg_as_int = int(arg)
if arg == arg_as_int:
warnings.warn(
... |
A preprocessor that coerces integral floats to ints.
Receipt of non-integral floats raises a TypeError.
| lossless_float_to_int | python | quantopian/zipline | zipline/utils/events.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/events.py | Apache-2.0 |
def add_event(self, event, prepend=False):
"""
Adds an event to the manager.
"""
if prepend:
self._events.insert(0, event)
else:
self._events.append(event) |
Adds an event to the manager.
| add_event | python | quantopian/zipline | zipline/utils/events.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/events.py | Apache-2.0 |
def should_trigger(self, dt):
"""
Composes the two rules with a lazy composer.
"""
return self.composer(
self.first.should_trigger,
self.second.should_trigger,
dt
) |
Composes the two rules with a lazy composer.
| should_trigger | python | quantopian/zipline | zipline/utils/events.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/events.py | Apache-2.0 |
def calculate_dates(self, dt):
"""
Given a date, find that day's open and period end (open + offset).
"""
period_start, period_close = self.cal.open_and_close_for_session(
self.cal.minute_to_session_label(dt),
)
# Align the market open and close times here wi... |
Given a date, find that day's open and period end (open + offset).
| calculate_dates | python | quantopian/zipline | zipline/utils/events.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/events.py | Apache-2.0 |
def calculate_dates(self, dt):
"""
Given a dt, find that day's close and period start (close - offset).
"""
period_end = self.cal.open_and_close_for_session(
self.cal.minute_to_session_label(dt),
)[1]
# Align the market close time here with the execution time... |
Given a dt, find that day's close and period start (close - offset).
| calculate_dates | python | quantopian/zipline | zipline/utils/events.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/events.py | Apache-2.0 |
def make_eventrule(date_rule, time_rule, cal, half_days=True):
"""
Constructs an event rule from the factory api.
"""
_check_if_not_called(date_rule)
_check_if_not_called(time_rule)
if half_days:
inner_rule = date_rule & time_rule
else:
inner_rule = date_rule & time_rule & N... |
Constructs an event rule from the factory api.
| make_eventrule | python | quantopian/zipline | zipline/utils/events.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/events.py | Apache-2.0 |
def create_daily_trade_source(sids,
sim_params,
asset_finder,
trading_calendar):
"""
creates trade_count trades for each sid in sids list.
first trade will be on sim_params.start_session, and daily
thereafter for e... |
creates trade_count trades for each sid in sids list.
first trade will be on sim_params.start_session, and daily
thereafter for each sid. Thus, two sids should result in two trades per
day.
| create_daily_trade_source | python | quantopian/zipline | zipline/utils/factory.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/factory.py | Apache-2.0 |
def bases_mro(bases):
"""
Yield classes in the order that methods should be looked up from the
base classes of an object.
"""
for base in bases:
for class_ in base.__mro__:
yield class_ |
Yield classes in the order that methods should be looked up from the
base classes of an object.
| bases_mro | python | quantopian/zipline | zipline/utils/final.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/final.py | Apache-2.0 |
def is_final(name, mro):
"""
Checks if `name` is a `final` object in the given `mro`.
We need to check the mro because we need to directly go into the __dict__
of the classes. Because `final` objects are descriptor, we need to grab
them _BEFORE_ the `__call__` is invoked.
"""
return any(isin... |
Checks if `name` is a `final` object in the given `mro`.
We need to check the mro because we need to directly go into the __dict__
of the classes. Because `final` objects are descriptor, we need to grab
them _BEFORE_ the `__call__` is invoked.
| is_final | python | quantopian/zipline | zipline/utils/final.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/final.py | Apache-2.0 |
def __setattr__(self, name, value):
"""This stops the `final` attributes from being reassigned on the
class object.
"""
if is_final(name, self.__mro__):
raise _type_error
super(FinalMeta, self).__setattr__(name, value) | This stops the `final` attributes from being reassigned on the
class object.
| __setattr__ | python | quantopian/zipline | zipline/utils/final.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/final.py | Apache-2.0 |
def s(word, seq, suffix='s'):
"""Adds a suffix to ``word`` if some sequence has anything other than
exactly one element.
Parameters
----------
word : str
The string to add the suffix to.
seq : sequence
The sequence to check the length of.
suffix : str, optional.
The ... | Adds a suffix to ``word`` if some sequence has anything other than
exactly one element.
Parameters
----------
word : str
The string to add the suffix to.
seq : sequence
The sequence to check the length of.
suffix : str, optional.
The suffix to add to ``word``
Return... | s | python | quantopian/zipline | zipline/utils/formatting.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/formatting.py | Apache-2.0 |
def plural(singular, plural, seq):
"""Selects a singular or plural word based on the length of a sequence.
Parameters
----------
singlular : str
The string to use when ``len(seq) == 1``.
plural : str
The string to use when ``len(seq) != 1``.
seq : sequence
The sequence t... | Selects a singular or plural word based on the length of a sequence.
Parameters
----------
singlular : str
The string to use when ``len(seq) == 1``.
plural : str
The string to use when ``len(seq) != 1``.
seq : sequence
The sequence to check the length of.
Returns
--... | plural | python | quantopian/zipline | zipline/utils/formatting.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/formatting.py | Apache-2.0 |
def bulleted_list(items, indent=0, bullet_type='-'):
"""Format a bulleted list of values.
Parameters
----------
items : sequence
The items to make a list.
indent : int, optional
The number of spaces to add before each bullet.
bullet_type : str, optional
The bullet type t... | Format a bulleted list of values.
Parameters
----------
items : sequence
The items to make a list.
indent : int, optional
The number of spaces to add before each bullet.
bullet_type : str, optional
The bullet type to use.
Returns
-------
formatted_list : str
... | bulleted_list | python | quantopian/zipline | zipline/utils/formatting.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/formatting.py | Apache-2.0 |
def mapall(funcs, seq):
"""
Parameters
----------
funcs : iterable[function]
Sequence of functions to map over `seq`.
seq : iterable
Sequence over which to map funcs.
Yields
------
elem : object
Concatenated result of mapping each ``func`` over ``seq``.
Exam... |
Parameters
----------
funcs : iterable[function]
Sequence of functions to map over `seq`.
seq : iterable
Sequence over which to map funcs.
Yields
------
elem : object
Concatenated result of mapping each ``func`` over ``seq``.
Examples
--------
>>> list(... | mapall | python | quantopian/zipline | zipline/utils/functional.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/functional.py | Apache-2.0 |
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:]
... |
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
| same | python | quantopian/zipline | zipline/utils/functional.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/functional.py | Apache-2.0 |
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... |
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
... | dzip_exact | python | quantopian/zipline | zipline/utils/functional.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/functional.py | Apache-2.0 |
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... | 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... | _gen_unzip | python | quantopian/zipline | zipline/utils/functional.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/functional.py | Apache-2.0 |
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... | 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... | unzip | python | quantopian/zipline | zipline/utils/functional.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/functional.py | Apache-2.0 |
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.
... |
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 t... | getattrs | python | quantopian/zipline | zipline/utils/functional.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/functional.py | Apache-2.0 |
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__
... |
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'
| set_attribute | python | quantopian/zipline | zipline/utils/functional.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/functional.py | Apache-2.0 |
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... | 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... | foldr | python | quantopian/zipline | zipline/utils/functional.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/functional.py | Apache-2.0 |
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 |
Invert a dictionary into a dictionary of sets.
>>> invert({'a': 1, 'b': 2, 'c': 1}) # doctest: +SKIP
{1: {'a', 'c'}, 2: {'b'}}
| invert | python | quantopian/zipline | zipline/utils/functional.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/functional.py | Apache-2.0 |
def _qualified_name(obj):
"""
Return the fully-qualified name (ignoring inner classes) of a type.
"""
# If the obj has an explicitly-set __qualname__, use it.
try:
return getattr(obj, '__qualname__')
except AttributeError:
pass
# If not, b... |
Return the fully-qualified name (ignoring inner classes) of a type.
| _qualified_name | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def verify_indices_all_unique(obj):
"""
Check that all axes of a pandas object are unique.
Parameters
----------
obj : pd.Series / pd.DataFrame / pd.Panel
The object to validate.
Returns
-------
obj : pd.Series / pd.DataFrame / pd.Panel
The validated object, unchanged.
... |
Check that all axes of a pandas object are unique.
Parameters
----------
obj : pd.Series / pd.DataFrame / pd.Panel
The object to validate.
Returns
-------
obj : pd.Series / pd.DataFrame / pd.Panel
The validated object, unchanged.
Raises
------
ValueError
... | verify_indices_all_unique | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def optionally(preprocessor):
"""Modify a preprocessor to explicitly allow `None`.
Parameters
----------
preprocessor : callable[callable, str, any -> any]
A preprocessor to delegate to when `arg is not None`.
Returns
-------
optional_preprocessor : callable[callable, str, any -> a... | Modify a preprocessor to explicitly allow `None`.
Parameters
----------
preprocessor : callable[callable, str, any -> any]
A preprocessor to delegate to when `arg is not None`.
Returns
-------
optional_preprocessor : callable[callable, str, any -> any]
A preprocessor that deleg... | optionally | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def ensure_dtype(func, argname, arg):
"""
Argument preprocessor that converts the input into a numpy dtype.
Examples
--------
>>> import numpy as np
>>> from zipline.utils.preprocess import preprocess
>>> @preprocess(dtype=ensure_dtype)
... def foo(dtype):
... return dtype
.... |
Argument preprocessor that converts the input into a numpy dtype.
Examples
--------
>>> import numpy as np
>>> from zipline.utils.preprocess import preprocess
>>> @preprocess(dtype=ensure_dtype)
... def foo(dtype):
... return dtype
...
>>> foo(float)
dtype('float64')
... | ensure_dtype | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def ensure_timezone(func, argname, arg):
"""Argument preprocessor that converts the input into a tzinfo object.
Examples
--------
>>> from zipline.utils.preprocess import preprocess
>>> @preprocess(tz=ensure_timezone)
... def foo(tz):
... return tz
>>> foo('utc')
<UTC>
"""
... | Argument preprocessor that converts the input into a tzinfo object.
Examples
--------
>>> from zipline.utils.preprocess import preprocess
>>> @preprocess(tz=ensure_timezone)
... def foo(tz):
... return tz
>>> foo('utc')
<UTC>
| ensure_timezone | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def ensure_timestamp(func, argname, arg):
"""Argument preprocessor that converts the input into a pandas Timestamp
object.
Examples
--------
>>> from zipline.utils.preprocess import preprocess
>>> @preprocess(ts=ensure_timestamp)
... def foo(ts):
... return ts
>>> foo('2014-01-0... | Argument preprocessor that converts the input into a pandas Timestamp
object.
Examples
--------
>>> from zipline.utils.preprocess import preprocess
>>> @preprocess(ts=ensure_timestamp)
... def foo(ts):
... return ts
>>> foo('2014-01-01')
Timestamp('2014-01-01 00:00:00')
| ensure_timestamp | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def expect_dtypes(__funcname=_qualified_name, **named):
"""
Preprocessing decorator that verifies inputs have expected numpy dtypes.
Examples
--------
>>> from numpy import dtype, arange, int8, float64
>>> @expect_dtypes(x=dtype(int8))
... def foo(x, y):
... return x, y
...
>... |
Preprocessing decorator that verifies inputs have expected numpy dtypes.
Examples
--------
>>> from numpy import dtype, arange, int8, float64
>>> @expect_dtypes(x=dtype(int8))
... def foo(x, y):
... return x, y
...
>>> foo(arange(3, dtype=int8), 'foo')
(array([0, 1, 2], dtyp... | expect_dtypes | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def _expect_dtype(dtypes):
"""
Factory for dtype-checking functions that work with the @preprocess
decorator.
"""
def error_message(func, argname, value):
# If the bad value has a dtype, but it's wrong, show the dtype
# name. Otherwise just show the value... |
Factory for dtype-checking functions that work with the @preprocess
decorator.
| _expect_dtype | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def expect_kinds(**named):
"""
Preprocessing decorator that verifies inputs have expected dtype kinds.
Examples
--------
>>> from numpy import int64, int32, float32
>>> @expect_kinds(x='i')
... def foo(x):
... return x
...
>>> foo(int64(2))
2
>>> foo(int32(2))
2
... |
Preprocessing decorator that verifies inputs have expected dtype kinds.
Examples
--------
>>> from numpy import int64, int32, float32
>>> @expect_kinds(x='i')
... def foo(x):
... return x
...
>>> foo(int64(2))
2
>>> foo(int32(2))
2
>>> foo(float32(2)) # doctest:... | expect_kinds | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def _expect_kind(kinds):
"""
Factory for kind-checking functions that work the @preprocess
decorator.
"""
def error_message(func, argname, value):
# If the bad value has a dtype, but it's wrong, show the dtype
# kind. Otherwise just show the value.
... |
Factory for kind-checking functions that work the @preprocess
decorator.
| _expect_kind | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def expect_types(__funcname=_qualified_name, **named):
"""
Preprocessing decorator that verifies inputs have expected types.
Examples
--------
>>> @expect_types(x=int, y=str)
... def foo(x, y):
... return x, y
...
>>> foo(2, '3')
(2, '3')
>>> foo(2.0, '3') # doctest: +NO... |
Preprocessing decorator that verifies inputs have expected types.
Examples
--------
>>> @expect_types(x=int, y=str)
... def foo(x, y):
... return x, y
...
>>> foo(2, '3')
(2, '3')
>>> foo(2.0, '3') # doctest: +NORMALIZE_WHITESPACE +ELLIPSIS
Traceback (most recent call l... | expect_types | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def make_check(exc_type, template, pred, actual, funcname):
"""
Factory for making preprocessing functions that check a predicate on the
input value.
Parameters
----------
exc_type : Exception
The exception type to raise if the predicate fails.
template : str
A template stri... |
Factory for making preprocessing functions that check a predicate on the
input value.
Parameters
----------
exc_type : Exception
The exception type to raise if the predicate fails.
template : str
A template string to use to create error messages.
Should have %-style nam... | make_check | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def expect_element(__funcname=_qualified_name, **named):
"""
Preprocessing decorator that verifies inputs are elements of some
expected collection.
Examples
--------
>>> @expect_element(x=('a', 'b'))
... def foo(x):
... return x.upper()
...
>>> foo('a')
'A'
>>> foo('b... |
Preprocessing decorator that verifies inputs are elements of some
expected collection.
Examples
--------
>>> @expect_element(x=('a', 'b'))
... def foo(x):
... return x.upper()
...
>>> foo('a')
'A'
>>> foo('b')
'B'
>>> foo('c') # doctest: +NORMALIZE_WHITESPACE +E... | expect_element | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def expect_bounded(__funcname=_qualified_name, **named):
"""
Preprocessing decorator verifying that inputs fall INCLUSIVELY between
bounds.
Bounds should be passed as a pair of ``(min_value, max_value)``.
``None`` may be passed as ``min_value`` or ``max_value`` to signify that
the input is onl... |
Preprocessing decorator verifying that inputs fall INCLUSIVELY between
bounds.
Bounds should be passed as a pair of ``(min_value, max_value)``.
``None`` may be passed as ``min_value`` or ``max_value`` to signify that
the input is only bounded above or below.
Examples
--------
>>> @ex... | expect_bounded | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def expect_strictly_bounded(__funcname=_qualified_name, **named):
"""
Preprocessing decorator verifying that inputs fall EXCLUSIVELY between
bounds.
Bounds should be passed as a pair of ``(min_value, max_value)``.
``None`` may be passed as ``min_value`` or ``max_value`` to signify that
the inp... |
Preprocessing decorator verifying that inputs fall EXCLUSIVELY between
bounds.
Bounds should be passed as a pair of ``(min_value, max_value)``.
``None`` may be passed as ``min_value`` or ``max_value`` to signify that
the input is only bounded above or below.
Examples
--------
>>> @ex... | expect_strictly_bounded | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def expect_dimensions(__funcname=_qualified_name, **dimensions):
"""
Preprocessing decorator that verifies inputs are numpy arrays with a
specific dimensionality.
Examples
--------
>>> from numpy import array
>>> @expect_dimensions(x=1, y=2)
... def foo(x, y):
... return x[0] + y... |
Preprocessing decorator that verifies inputs are numpy arrays with a
specific dimensionality.
Examples
--------
>>> from numpy import array
>>> @expect_dimensions(x=1, y=2)
... def foo(x, y):
... return x[0] + y[0, 0]
...
>>> foo(array([1, 1]), array([[1, 1], [2, 2]]))
2... | expect_dimensions | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def coerce(from_, to, **to_kwargs):
"""
A preprocessing decorator that coerces inputs of a given type by passing
them to a callable.
Parameters
----------
from : type or tuple or types
Inputs types on which to call ``to``.
to : function
Coercion function to call on inputs.
... |
A preprocessing decorator that coerces inputs of a given type by passing
them to a callable.
Parameters
----------
from : type or tuple or types
Inputs types on which to call ``to``.
to : function
Coercion function to call on inputs.
**to_kwargs
Additional keywords ... | coerce | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def coerce_types(**kwargs):
"""
Preprocessing decorator that applies type coercions.
Parameters
----------
**kwargs : dict[str -> (type, callable)]
Keyword arguments mapping function parameter names to pairs of
(from_type, to_type).
Examples
--------
>>> @coerce_types... |
Preprocessing decorator that applies type coercions.
Parameters
----------
**kwargs : dict[str -> (type, callable)]
Keyword arguments mapping function parameter names to pairs of
(from_type, to_type).
Examples
--------
>>> @coerce_types(x=(float, int), y=(int, str))
... | coerce_types | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def validate_keys(dict_, expected, funcname):
"""Validate that a dictionary has an expected set of keys.
"""
expected = set(expected)
received = set(dict_)
missing = expected - received
if missing:
raise ValueError(
"Missing keys in {}:\n"
"Expected Keys: {}\n"
... | Validate that a dictionary has an expected set of keys.
| validate_keys | python | quantopian/zipline | zipline/utils/input_validation.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/input_validation.py | Apache-2.0 |
def tolerant_equals(a, b, atol=10e-7, rtol=10e-7, equal_nan=False):
"""Check if a and b are equal with some tolerance.
Parameters
----------
a, b : float
The floats to check for equality.
atol : float, optional
The absolute tolerance.
rtol : float, optional
The relative ... | Check if a and b are equal with some tolerance.
Parameters
----------
a, b : float
The floats to check for equality.
atol : float, optional
The absolute tolerance.
rtol : float, optional
The relative tolerance.
equal_nan : bool, optional
Should NaN compare equal?... | tolerant_equals | python | quantopian/zipline | zipline/utils/math_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/math_utils.py | Apache-2.0 |
def round_if_near_integer(a, epsilon=1e-4):
"""
Round a to the nearest integer if that integer is within an epsilon
of a.
"""
if abs(a - round(a)) <= epsilon:
return round(a)
else:
return a |
Round a to the nearest integer if that integer is within an epsilon
of a.
| round_if_near_integer | python | quantopian/zipline | zipline/utils/math_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/math_utils.py | Apache-2.0 |
def _weak_lru_cache(maxsize=100):
"""
Users should only access the lru_cache through its public API:
cache_info, cache_clear
The internals of the lru_cache are encapsulated for thread safety and
to allow the implementation to change.
"""
def decorating_function(
user_function, tu... |
Users should only access the lru_cache through its public API:
cache_info, cache_clear
The internals of the lru_cache are encapsulated for thread safety and
to allow the implementation to change.
| _weak_lru_cache | python | quantopian/zipline | zipline/utils/memoize.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/memoize.py | Apache-2.0 |
def cache_clear():
"""Clear the cache and cache statistics"""
with lock:
cache.clear()
hits[0] = misses[0] = 0 | Clear the cache and cache statistics | cache_clear | python | quantopian/zipline | zipline/utils/memoize.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/memoize.py | Apache-2.0 |
def weak_lru_cache(maxsize=100):
"""Weak least-recently-used cache decorator.
If *maxsize* is set to None, the LRU features are disabled and the cache
can grow without bound.
Arguments to the cached function must be hashable. Any that are weak-
referenceable will be stored by weak reference. Once... | Weak least-recently-used cache decorator.
If *maxsize* is set to None, the LRU features are disabled and the cache
can grow without bound.
Arguments to the cached function must be hashable. Any that are weak-
referenceable will be stored by weak reference. Once any of the args have
been garbage c... | weak_lru_cache | python | quantopian/zipline | zipline/utils/memoize.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/memoize.py | Apache-2.0 |
def compose_types(a, *cs):
"""Compose multiple classes together.
Parameters
----------
*mcls : tuple[type]
The classes that you would like to compose
Returns
-------
cls : type
A type that subclasses all of the types in ``mcls``.
Notes
-----
A common use case f... | Compose multiple classes together.
Parameters
----------
*mcls : tuple[type]
The classes that you would like to compose
Returns
-------
cls : type
A type that subclasses all of the types in ``mcls``.
Notes
-----
A common use case for this is to build composed metac... | compose_types | python | quantopian/zipline | zipline/utils/metautils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/metautils.py | Apache-2.0 |
def make_kind_check(python_types, numpy_kind):
"""
Make a function that checks whether a scalar or array is of a given kind
(e.g. float, int, datetime, timedelta).
"""
def check(value):
if hasattr(value, 'dtype'):
return value.dtype.kind == numpy_kind
return isinstance(va... |
Make a function that checks whether a scalar or array is of a given kind
(e.g. float, int, datetime, timedelta).
| make_kind_check | python | quantopian/zipline | zipline/utils/numpy_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/numpy_utils.py | Apache-2.0 |
def coerce_to_dtype(dtype, value):
"""
Make a value with the specified numpy dtype.
Only datetime64[ns] and datetime64[D] are supported for datetime dtypes.
"""
name = dtype.name
if name.startswith('datetime64'):
if name == 'datetime64[D]':
return make_datetime64D(value)
... |
Make a value with the specified numpy dtype.
Only datetime64[ns] and datetime64[D] are supported for datetime dtypes.
| coerce_to_dtype | python | quantopian/zipline | zipline/utils/numpy_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/numpy_utils.py | Apache-2.0 |
def default_missing_value_for_dtype(dtype):
"""
Get the default fill value for `dtype`.
"""
try:
return _FILLVALUE_DEFAULTS[dtype]
except KeyError:
raise NoDefaultMissingValue(
"No default value registered for dtype %s." % dtype
) |
Get the default fill value for `dtype`.
| default_missing_value_for_dtype | python | quantopian/zipline | zipline/utils/numpy_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/numpy_utils.py | Apache-2.0 |
def rolling_window(array, length):
"""
Restride an array of shape
(X_0, ... X_N)
into an array of shape
(length, X_0 - length + 1, ... X_N)
where each slice at index i along the first axis is equivalent to
result[i] = array[length * i:length * (i + 1)]
Parameters
--... |
Restride an array of shape
(X_0, ... X_N)
into an array of shape
(length, X_0 - length + 1, ... X_N)
where each slice at index i along the first axis is equivalent to
result[i] = array[length * i:length * (i + 1)]
Parameters
----------
array : np.ndarray
Th... | rolling_window | python | quantopian/zipline | zipline/utils/numpy_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/numpy_utils.py | Apache-2.0 |
def isnat(obj):
"""
Check if a value is np.NaT.
"""
if obj.dtype.kind not in ('m', 'M'):
raise ValueError("%s is not a numpy datetime or timedelta")
return obj.view(int64_dtype) == iNaT |
Check if a value is np.NaT.
| isnat | python | quantopian/zipline | zipline/utils/numpy_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/numpy_utils.py | Apache-2.0 |
def is_missing(data, missing_value):
"""
Generic is_missing function that handles NaN and NaT.
"""
if is_float(data) and isnan(missing_value):
return isnan(data)
elif is_datetime(data) and isnat(missing_value):
return isnat(data)
elif is_object(data) and missing_value is None:
... |
Generic is_missing function that handles NaN and NaT.
| is_missing | python | quantopian/zipline | zipline/utils/numpy_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/numpy_utils.py | Apache-2.0 |
def same(x, y):
"""
Check if two scalar values are "the same".
Returns True if `x == y`, or if x and y are both NaN or both NaT.
"""
if is_float(x) and isnan(x) and is_float(y) and isnan(y):
return True
elif is_datetime(x) and isnat(x) and is_datetime(y) and isnat(y):
return Tru... |
Check if two scalar values are "the same".
Returns True if `x == y`, or if x and y are both NaN or both NaT.
| same | python | quantopian/zipline | zipline/utils/numpy_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/numpy_utils.py | Apache-2.0 |
def busday_count_mask_NaT(begindates, enddates, out=None):
"""
Simple of numpy.busday_count that returns `float` arrays rather than int
arrays, and handles `NaT`s by returning `NaN`s where the inputs were `NaT`.
Doesn't support custom weekdays or calendars, but probably should in the
future.
S... |
Simple of numpy.busday_count that returns `float` arrays rather than int
arrays, and handles `NaT`s by returning `NaN`s where the inputs were `NaT`.
Doesn't support custom weekdays or calendars, but probably should in the
future.
See Also
--------
np.busday_count
| busday_count_mask_NaT | python | quantopian/zipline | zipline/utils/numpy_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/numpy_utils.py | Apache-2.0 |
def ignore_nanwarnings():
"""
Helper for building a WarningContext that ignores warnings from numpy's
nanfunctions.
"""
return WarningContext(
(
('ignore',),
{'category': RuntimeWarning, 'module': 'numpy.lib.nanfunctions'},
)
) |
Helper for building a WarningContext that ignores warnings from numpy's
nanfunctions.
| ignore_nanwarnings | python | quantopian/zipline | zipline/utils/numpy_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/numpy_utils.py | Apache-2.0 |
def as_column(a):
"""
Convert an array of shape (N,) into an array of shape (N, 1).
This is equivalent to `a[:, np.newaxis]`.
Parameters
----------
a : np.ndarray
Example
-------
>>> import numpy as np
>>> a = np.arange(5)
>>> a
array([0, 1, 2, 3, 4])
>>> as_column... |
Convert an array of shape (N,) into an array of shape (N, 1).
This is equivalent to `a[:, np.newaxis]`.
Parameters
----------
a : np.ndarray
Example
-------
>>> import numpy as np
>>> a = np.arange(5)
>>> a
array([0, 1, 2, 3, 4])
>>> as_column(a)
array([[0],
... | as_column | python | quantopian/zipline | zipline/utils/numpy_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/numpy_utils.py | Apache-2.0 |
def changed_locations(a, include_first):
"""
Compute indices of values in ``a`` that differ from the previous value.
Parameters
----------
a : np.ndarray
The array on which to indices of change.
include_first : bool
Whether or not to consider the first index of the array as "cha... |
Compute indices of values in ``a`` that differ from the previous value.
Parameters
----------
a : np.ndarray
The array on which to indices of change.
include_first : bool
Whether or not to consider the first index of the array as "changed".
Example
-------
>>> import n... | changed_locations | python | quantopian/zipline | zipline/utils/numpy_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/numpy_utils.py | Apache-2.0 |
def bytes_array_to_native_str_object_array(a):
"""Convert an array of dtype S to an object array containing `str`.
"""
if six.PY2:
return a.astype(object)
else:
return a.astype(str).astype(object) | Convert an array of dtype S to an object array containing `str`.
| bytes_array_to_native_str_object_array | python | quantopian/zipline | zipline/utils/numpy_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/numpy_utils.py | Apache-2.0 |
def _time_to_micros(time):
"""Convert a time into microseconds since midnight.
Parameters
----------
time : datetime.time
The time to convert.
Returns
-------
us : int
The number of microseconds since midnight.
Notes
-----
This does not account for leap seconds or... | Convert a time into microseconds since midnight.
Parameters
----------
time : datetime.time
The time to convert.
Returns
-------
us : int
The number of microseconds since midnight.
Notes
-----
This does not account for leap seconds or daylight savings.
| _time_to_micros | python | quantopian/zipline | zipline/utils/pandas_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/pandas_utils.py | Apache-2.0 |
def mask_between_time(dts, start, end, include_start=True, include_end=True):
"""Return a mask of all of the datetimes in ``dts`` that are between
``start`` and ``end``.
Parameters
----------
dts : pd.DatetimeIndex
The index to mask.
start : time
Mask away times less than the sta... | Return a mask of all of the datetimes in ``dts`` that are between
``start`` and ``end``.
Parameters
----------
dts : pd.DatetimeIndex
The index to mask.
start : time
Mask away times less than the start.
end : time
Mask away times greater than the end.
include_start : ... | mask_between_time | python | quantopian/zipline | zipline/utils/pandas_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/pandas_utils.py | Apache-2.0 |
def find_in_sorted_index(dts, dt):
"""
Find the index of ``dt`` in ``dts``.
This function should be used instead of `dts.get_loc(dt)` if the index is
large enough that we don't want to initialize a hash table in ``dts``. In
particular, this should always be used on minutely trading calendars.
... |
Find the index of ``dt`` in ``dts``.
This function should be used instead of `dts.get_loc(dt)` if the index is
large enough that we don't want to initialize a hash table in ``dts``. In
particular, this should always be used on minutely trading calendars.
Parameters
----------
dts : pd.Dat... | find_in_sorted_index | python | quantopian/zipline | zipline/utils/pandas_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/pandas_utils.py | Apache-2.0 |
def nearest_unequal_elements(dts, dt):
"""
Find values in ``dts`` closest but not equal to ``dt``.
Returns a pair of (last_before, first_after).
When ``dt`` is less than any element in ``dts``, ``last_before`` is None.
When ``dt`` is greater any element in ``dts``, ``first_after`` is None.
``... |
Find values in ``dts`` closest but not equal to ``dt``.
Returns a pair of (last_before, first_after).
When ``dt`` is less than any element in ``dts``, ``last_before`` is None.
When ``dt`` is greater any element in ``dts``, ``first_after`` is None.
``dts`` must be unique and sorted in increasing ... | nearest_unequal_elements | python | quantopian/zipline | zipline/utils/pandas_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/pandas_utils.py | Apache-2.0 |
def clear_dataframe_indexer_caches(df):
"""
Clear cached attributes from a pandas DataFrame.
By default pandas memoizes indexers (`iloc`, `loc`, `ix`, etc.) objects on
DataFrames, resulting in refcycles that can lead to unexpectedly long-lived
DataFrames. This function attempts to clear those cycle... |
Clear cached attributes from a pandas DataFrame.
By default pandas memoizes indexers (`iloc`, `loc`, `ix`, etc.) objects on
DataFrames, resulting in refcycles that can lead to unexpectedly long-lived
DataFrames. This function attempts to clear those cycles by deleting the
cached indexers from the ... | clear_dataframe_indexer_caches | python | quantopian/zipline | zipline/utils/pandas_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/pandas_utils.py | Apache-2.0 |
def categorical_df_concat(df_list, inplace=False):
"""
Prepare list of pandas DataFrames to be used as input to pd.concat.
Ensure any columns of type 'category' have the same categories across each
dataframe.
Parameters
----------
df_list : list
List of dataframes with same columns.... |
Prepare list of pandas DataFrames to be used as input to pd.concat.
Ensure any columns of type 'category' have the same categories across each
dataframe.
Parameters
----------
df_list : list
List of dataframes with same columns.
inplace : bool
True if input list can be modi... | categorical_df_concat | python | quantopian/zipline | zipline/utils/pandas_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/pandas_utils.py | Apache-2.0 |
def _sort_set_none_first(set_):
"""Sort a set, sorting ``None`` before other elements, if present.
"""
if None in set_:
set_.remove(None)
out = [None]
out.extend(sorted(set_))
set_.add(None)
return out
else:
return sorted(set_) | Sort a set, sorting ``None`` before other elements, if present.
| _sort_set_none_first | python | quantopian/zipline | zipline/utils/pandas_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/pandas_utils.py | Apache-2.0 |
def check_indexes_all_same(indexes, message="Indexes are not equal."):
"""Check that a list of Index objects are all equal.
Parameters
----------
indexes : iterable[pd.Index]
Iterable of indexes to check.
Raises
------
ValueError
If the indexes are not all the same.
"""... | Check that a list of Index objects are all equal.
Parameters
----------
indexes : iterable[pd.Index]
Iterable of indexes to check.
Raises
------
ValueError
If the indexes are not all the same.
| check_indexes_all_same | python | quantopian/zipline | zipline/utils/pandas_utils.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/pandas_utils.py | Apache-2.0 |
def ensure_directory(path):
"""
Ensure that a directory named "path" exists.
"""
try:
os.makedirs(path)
except OSError as exc:
if exc.errno == EEXIST and os.path.isdir(path):
return
raise |
Ensure that a directory named "path" exists.
| ensure_directory | python | quantopian/zipline | zipline/utils/paths.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/paths.py | Apache-2.0 |
def ensure_file(path):
"""
Ensure that a file exists. This will create any parent directories needed
and create an empty file if it does not exist.
Parameters
----------
path : str
The file path to ensure exists.
"""
ensure_directory_containing(path)
open(path, 'a+').close()... |
Ensure that a file exists. This will create any parent directories needed
and create an empty file if it does not exist.
Parameters
----------
path : str
The file path to ensure exists.
| ensure_file | python | quantopian/zipline | zipline/utils/paths.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/paths.py | Apache-2.0 |
def zipline_root(environ=None):
"""
Get the root directory for all zipline-managed files.
For testing purposes, this accepts a dictionary to interpret as the os
environment.
Parameters
----------
environ : dict, optional
A dict to interpret as the os environment.
Returns
-... |
Get the root directory for all zipline-managed files.
For testing purposes, this accepts a dictionary to interpret as the os
environment.
Parameters
----------
environ : dict, optional
A dict to interpret as the os environment.
Returns
-------
root : string
Path t... | zipline_root | python | quantopian/zipline | zipline/utils/paths.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/paths.py | Apache-2.0 |
def get(self):
"""Return the result of calling the function or reraise any exceptions
that were raised.
"""
if not self._successful:
raise self._value
return self._value | Return the result of calling the function or reraise any exceptions
that were raised.
| get | python | quantopian/zipline | zipline/utils/pool.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/pool.py | Apache-2.0 |
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... | 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, optional
The keyword arguments.
Returns
---... | apply_async | python | quantopian/zipline | zipline/utils/pool.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/pool.py | Apache-2.0 |
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... |
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: (func, argname, argvalue).
`func` is the t... | preprocess | python | quantopian/zipline | zipline/utils/preprocess.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/preprocess.py | Apache-2.0 |
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... |
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.
Examples
--------
... | call | python | quantopian/zipline | zipline/utils/preprocess.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/preprocess.py | Apache-2.0 |
def _build_preprocessed_function(func,
processors,
args_defaults,
varargs,
varkw):
"""
Build a preprocessed function with the same signature as `func`.
Uses `exec` internally ... |
Build a preprocessed function with the same signature as `func`.
Uses `exec` internally to build a function that actually has the same
signature as `func.
| _build_preprocessed_function | python | quantopian/zipline | zipline/utils/preprocess.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/preprocess.py | Apache-2.0 |
def __iter__(self):
"""
Examples
--------
>>> list(range(1))
[0]
>>> list(range(5))
[0, 1, 2, 3, 4]
>>> list(range(1, 5))
[1, 2, 3, 4]
>>> list(range(0, 5, 2))
[0, 2, 4]
>>> li... |
Examples
--------
>>> list(range(1))
[0]
>>> list(range(5))
[0, 1, 2, 3, 4]
>>> list(range(1, 5))
[1, 2, 3, 4]
>>> list(range(0, 5, 2))
[0, 2, 4]
>>> list(range(5, 0, -1))
[5,... | __iter__ | python | quantopian/zipline | zipline/utils/range.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/range.py | Apache-2.0 |
def __len__(self):
"""
Examples
--------
>>> len(range(1))
1
>>> len(range(5))
5
>>> len(range(1, 5))
4
>>> len(range(0, 5, 2))
3
>>> len(range(5, 0, -1))
5
... |
Examples
--------
>>> len(range(1))
1
>>> len(range(5))
5
>>> len(range(1, 5))
4
>>> len(range(0, 5, 2))
3
>>> len(range(5, 0, -1))
5
>>> len(range(5, 0, 1))
... | __len__ | python | quantopian/zipline | zipline/utils/range.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/range.py | Apache-2.0 |
def __eq__(self, other):
"""
Examples
--------
>>> range(1) == range(1)
True
>>> range(0, 5, 2) == range(0, 5, 2)
True
>>> range(5, 0, -2) == range(5, 0, -2)
True
>>> range(1) == range(2)
... |
Examples
--------
>>> range(1) == range(1)
True
>>> range(0, 5, 2) == range(0, 5, 2)
True
>>> range(5, 0, -2) == range(5, 0, -2)
True
>>> range(1) == range(2)
False
>>> range(0, 5, 2) ==... | __eq__ | python | quantopian/zipline | zipline/utils/range.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/range.py | Apache-2.0 |
def from_tuple(tup):
"""Convert a tuple into a range with error handling.
Parameters
----------
tup : tuple (len 2 or 3)
The tuple to turn into a range.
Returns
-------
range : range
The range from the tuple.
Raises
------
ValueError
Raised when the tup... | Convert a tuple into a range with error handling.
Parameters
----------
tup : tuple (len 2 or 3)
The tuple to turn into a range.
Returns
-------
range : range
The range from the tuple.
Raises
------
ValueError
Raised when the tuple length is not 2 or 3.
... | from_tuple | python | quantopian/zipline | zipline/utils/range.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/range.py | Apache-2.0 |
def maybe_from_tuple(tup_or_range):
"""Convert a tuple into a range but pass ranges through silently.
This is useful to ensure that input is a range so that attributes may
be accessed with `.start`, `.stop` or so that containment checks are
constant time.
Parameters
----------
tup_or_range... | Convert a tuple into a range but pass ranges through silently.
This is useful to ensure that input is a range so that attributes may
be accessed with `.start`, `.stop` or so that containment checks are
constant time.
Parameters
----------
tup_or_range : tuple or range
A tuple to pass t... | maybe_from_tuple | python | quantopian/zipline | zipline/utils/range.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/range.py | Apache-2.0 |
def _check_steps(a, b):
"""Check that the steps of ``a`` and ``b`` are both 1.
Parameters
----------
a : range
The first range to check.
b : range
The second range to check.
Raises
------
ValueError
Raised when either step is not 1.
"""
if a.step != 1:
... | Check that the steps of ``a`` and ``b`` are both 1.
Parameters
----------
a : range
The first range to check.
b : range
The second range to check.
Raises
------
ValueError
Raised when either step is not 1.
| _check_steps | python | quantopian/zipline | zipline/utils/range.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/range.py | Apache-2.0 |
def overlap(a, b):
"""Check if two ranges overlap.
Parameters
----------
a : range
The first range.
b : range
The second range.
Returns
-------
overlaps : bool
Do these ranges overlap.
Notes
-----
This function does not support ranges with step != ... | Check if two ranges overlap.
Parameters
----------
a : range
The first range.
b : range
The second range.
Returns
-------
overlaps : bool
Do these ranges overlap.
Notes
-----
This function does not support ranges with step != 1.
| overlap | python | quantopian/zipline | zipline/utils/range.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/range.py | Apache-2.0 |
def merge(a, b):
"""Merge two ranges with step == 1.
Parameters
----------
a : range
The first range.
b : range
The second range.
"""
_check_steps(a, b)
return range(min(a.start, b.start), max(a.stop, b.stop)) | Merge two ranges with step == 1.
Parameters
----------
a : range
The first range.
b : range
The second range.
| merge | python | quantopian/zipline | zipline/utils/range.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/range.py | Apache-2.0 |
def intersecting_ranges(ranges):
"""Return any ranges that intersect.
Parameters
----------
ranges : iterable[ranges]
A sequence of ranges to check for intersections.
Returns
-------
intersections : iterable[ranges]
A sequence of all of the ranges that intersected in ``rang... | Return any ranges that intersect.
Parameters
----------
ranges : iterable[ranges]
A sequence of ranges to check for intersections.
Returns
-------
intersections : iterable[ranges]
A sequence of all of the ranges that intersected in ``ranges``.
Examples
--------
>>>... | intersecting_ranges | python | quantopian/zipline | zipline/utils/range.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/range.py | Apache-2.0 |
def _run(handle_data,
initialize,
before_trading_start,
analyze,
algofile,
algotext,
defines,
data_frequency,
capital_base,
bundle,
bundle_timestamp,
start,
end,
output,
trading_calendar,
... | Run a backtest for the given algorithm.
This is shared between the cli and :func:`zipline.run_algo`.
| _run | python | quantopian/zipline | zipline/utils/run_algo.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/run_algo.py | Apache-2.0 |
def load_extensions(default, extensions, strict, environ, reload=False):
"""Load all of the given extensions. This should be called by run_algo
or the cli.
Parameters
----------
default : bool
Load the default exension (~/.zipline/extension.py)?
extension : iterable[str]
The pat... | Load all of the given extensions. This should be called by run_algo
or the cli.
Parameters
----------
default : bool
Load the default exension (~/.zipline/extension.py)?
extension : iterable[str]
The paths to the extensions to load. If the path ends in ``.py`` it is
treated ... | load_extensions | python | quantopian/zipline | zipline/utils/run_algo.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/run_algo.py | Apache-2.0 |
def run_algorithm(start,
end,
initialize,
capital_base,
handle_data=None,
before_trading_start=None,
analyze=None,
data_frequency='daily',
bundle='quantopian-quandl',
... |
Run a trading algorithm.
Parameters
----------
start : datetime
The start date of the backtest.
end : datetime
The end date of the backtest..
initialize : callable[context -> None]
The initialize function to use for the algorithm. This is called once
at the very... | run_algorithm | python | quantopian/zipline | zipline/utils/run_algo.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/run_algo.py | Apache-2.0 |
def resolve(self, asset_finder, start_date, end_date):
"""
Resolve inputs into values to be passed to TradingAlgorithm.
Returns a pair of ``(benchmark_sid, benchmark_returns)`` with at most
one non-None value. Both values may be None if no benchmark source has
been configured.
... |
Resolve inputs into values to be passed to TradingAlgorithm.
Returns a pair of ``(benchmark_sid, benchmark_returns)`` with at most
one non-None value. Both values may be None if no benchmark source has
been configured.
Parameters
----------
asset_finder : zipli... | resolve | python | quantopian/zipline | zipline/utils/run_algo.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/run_algo.py | Apache-2.0 |
def __init__(self, data, current_date_func, asset_finder):
"""
data: a nested dictionary:
knowledge_date -> lookup_date ->
{add: [symbol list], 'delete': []}, delete: [symbol list]}
current_date_func: function taking no parameters, returning
current datetime... |
data: a nested dictionary:
knowledge_date -> lookup_date ->
{add: [symbol list], 'delete': []}, delete: [symbol list]}
current_date_func: function taking no parameters, returning
current datetime
| __init__ | python | quantopian/zipline | zipline/utils/security_list.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/security_list.py | Apache-2.0 |
def load_from_directory(list_name):
"""
To resolve the symbol in the LEVERAGED_ETF list,
the date on which the symbol was in effect is needed.
Furthermore, to maintain a point in time record of our own maintenance
of the restricted list, we need a knowledge date. Thus, restricted lists
are dict... |
To resolve the symbol in the LEVERAGED_ETF list,
the date on which the symbol was in effect is needed.
Furthermore, to maintain a point in time record of our own maintenance
of the restricted list, we need a knowledge date. Thus, restricted lists
are dictionaries of datetime->symbol lists.
new... | load_from_directory | python | quantopian/zipline | zipline/utils/security_list.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/security_list.py | Apache-2.0 |
def format_docstring(owner_name, docstring, formatters):
"""
Template ``formatters`` into ``docstring``.
Parameters
----------
owner_name : str
The name of the function or class whose docstring is being templated.
Only used for error messages.
docstring : str
The docstri... |
Template ``formatters`` into ``docstring``.
Parameters
----------
owner_name : str
The name of the function or class whose docstring is being templated.
Only used for error messages.
docstring : str
The docstring to template.
formatters : dict[str -> str]
Parame... | format_docstring | python | quantopian/zipline | zipline/utils/sharedoc.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/sharedoc.py | Apache-2.0 |
def templated_docstring(**docs):
"""
Decorator allowing the use of templated docstrings.
Examples
--------
>>> @templated_docstring(foo='bar')
... def my_func(self, foo):
... '''{foo}'''
...
>>> my_func.__doc__
'bar'
"""
def decorator(f):
f.__doc__ = format_d... |
Decorator allowing the use of templated docstrings.
Examples
--------
>>> @templated_docstring(foo='bar')
... def my_func(self, foo):
... '''{foo}'''
...
>>> my_func.__doc__
'bar'
| templated_docstring | python | quantopian/zipline | zipline/utils/sharedoc.py | https://github.com/quantopian/zipline/blob/master/zipline/utils/sharedoc.py | Apache-2.0 |
def _init_config_schema(self):
"""
Initializes `config_schema.json` in the user's data dir whenever the
server extension starts. Users may add custom fields to their config
schema to insert new keys into the Jupyter AI config.
New in v2.31.1: Jupyter AI now merges the user's exi... |
Initializes `config_schema.json` in the user's data dir whenever the
server extension starts. Users may add custom fields to their config
schema to insert new keys into the Jupyter AI config.
New in v2.31.1: Jupyter AI now merges the user's existing config schema
with Jupyter A... | _init_config_schema | python | jupyterlab/jupyter-ai | packages/jupyter-ai/jupyter_ai/config_manager.py | https://github.com/jupyterlab/jupyter-ai/blob/master/packages/jupyter-ai/jupyter_ai/config_manager.py | BSD-3-Clause |
def _read_config(self) -> GlobalConfig:
"""Returns the user's current configuration as a GlobalConfig object.
This should never be sent to the client as it includes API keys. Prefer
self.get_config() for sending the config to the client."""
if self._config and self._last_read:
... | Returns the user's current configuration as a GlobalConfig object.
This should never be sent to the client as it includes API keys. Prefer
self.get_config() for sending the config to the client. | _read_config | python | jupyterlab/jupyter-ai | packages/jupyter-ai/jupyter_ai/config_manager.py | https://github.com/jupyterlab/jupyter-ai/blob/master/packages/jupyter-ai/jupyter_ai/config_manager.py | BSD-3-Clause |
def _validate_config(self, config: GlobalConfig):
"""Method used to validate the configuration. This is called after every
read and before every write to the config file. Guarantees that the
config file conforms to the JSON Schema, and that the language and
embedding models have authn cr... | Method used to validate the configuration. This is called after every
read and before every write to the config file. Guarantees that the
config file conforms to the JSON Schema, and that the language and
embedding models have authn credentials if specified. | _validate_config | python | jupyterlab/jupyter-ai | packages/jupyter-ai/jupyter_ai/config_manager.py | https://github.com/jupyterlab/jupyter-ai/blob/master/packages/jupyter-ai/jupyter_ai/config_manager.py | BSD-3-Clause |
def _validate_model(self, model_id: str, raise_exc=True):
"""
Validates a model against the set of allow/blocklists specified by the
traitlets configuration, returning `True` if the model is allowed, and
raising a `BlockedModelError` otherwise. If `raise_exc=False`, this
function... |
Validates a model against the set of allow/blocklists specified by the
traitlets configuration, returning `True` if the model is allowed, and
raising a `BlockedModelError` otherwise. If `raise_exc=False`, this
function returns `False` if the model is not allowed.
| _validate_model | python | jupyterlab/jupyter-ai | packages/jupyter-ai/jupyter_ai/config_manager.py | https://github.com/jupyterlab/jupyter-ai/blob/master/packages/jupyter-ai/jupyter_ai/config_manager.py | BSD-3-Clause |
def _write_config(self, new_config: GlobalConfig):
"""Updates configuration and persists it to disk. This accepts a
complete `GlobalConfig` object, and should not be called publicly."""
# remove any empty field dictionaries
new_config.fields = {k: v for k, v in new_config.fields.items() ... | Updates configuration and persists it to disk. This accepts a
complete `GlobalConfig` object, and should not be called publicly. | _write_config | python | jupyterlab/jupyter-ai | packages/jupyter-ai/jupyter_ai/config_manager.py | https://github.com/jupyterlab/jupyter-ai/blob/master/packages/jupyter-ai/jupyter_ai/config_manager.py | BSD-3-Clause |
def persona(self) -> Persona:
"""
The current agent persona, set by the selected LM provider. If the
selected LM provider is `None`, this property returns
`JupyternautPersona` by default.
"""
lm_provider = self.lm_provider
persona = getattr(lm_provider, "persona",... |
The current agent persona, set by the selected LM provider. If the
selected LM provider is `None`, this property returns
`JupyternautPersona` by default.
| persona | python | jupyterlab/jupyter-ai | packages/jupyter-ai/jupyter_ai/config_manager.py | https://github.com/jupyterlab/jupyter-ai/blob/master/packages/jupyter-ai/jupyter_ai/config_manager.py | BSD-3-Clause |
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