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 adjustments_from_deltas_no_sids(dense_dates,
sparse_dates,
column_idx,
column_name,
asset_idx,
deltas):
"""Collect all the adjustmen... | Collect all the adjustments that occur in a dataset that does not
have a sid column.
Parameters
----------
dense_dates : pd.DatetimeIndex
The dates requested by the loader.
sparse_dates : pd.DatetimeIndex
The dates that were in the raw data.
column_idx : int
The index of... | adjustments_from_deltas_no_sids | python | scrtlabs/catalyst | catalyst/pipeline/loaders/blaze/core.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/pipeline/loaders/blaze/core.py | Apache-2.0 |
def adjustments_from_deltas_with_sids(dense_dates,
sparse_dates,
column_idx,
column_name,
asset_idx,
deltas):
"""Collect all t... | Collect all the adjustments that occur in a dataset that has a sid
column.
Parameters
----------
dense_dates : pd.DatetimeIndex
The dates requested by the loader.
sparse_dates : pd.DatetimeIndex
The dates that were in the raw data.
column_idx : int
The index of the colum... | adjustments_from_deltas_with_sids | python | scrtlabs/catalyst | catalyst/pipeline/loaders/blaze/core.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/pipeline/loaders/blaze/core.py | Apache-2.0 |
def load_raw_data(assets,
dates,
data_query_time,
data_query_tz,
expr,
odo_kwargs,
checkpoints=None):
"""
Given an expression representing data to load, perform normalization and
forward-filling and r... |
Given an expression representing data to load, perform normalization and
forward-filling and return the data, materialized. Only accepts data with a
`sid` field.
Parameters
----------
assets : pd.int64index
the assets to load data for.
dates : pd.datetimeindex
the simulatio... | load_raw_data | python | scrtlabs/catalyst | catalyst/pipeline/loaders/blaze/utils.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/pipeline/loaders/blaze/utils.py | Apache-2.0 |
def _initialize_precalculated_series(self, asset, trading_calendar,
trading_days, data_portal):
"""
Internal method that pre-calculates the benchmark return series for
use in the simulation.
Parameters
----------
asset: Asset to ... |
Internal method that pre-calculates the benchmark return series for
use in the simulation.
Parameters
----------
asset: Asset to use
trading_calendar: TradingCalendar
trading_days: pd.DateTimeIndex
data_portal: DataPortal
Notes
-----... | _initialize_precalculated_series | python | scrtlabs/catalyst | catalyst/sources/benchmark_source.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/sources/benchmark_source.py | Apache-2.0 |
def subtest(iterator, *_names):
"""
Construct a subtest in a unittest.
Consider using ``catalyst.testing.parameter_space`` when subtests
are constructed over a single input or over the cross-product of multiple
inputs.
``subtest`` works by decorating a function as a subtest. The decorated
... |
Construct a subtest in a unittest.
Consider using ``catalyst.testing.parameter_space`` when subtests
are constructed over a single input or over the cross-product of multiple
inputs.
``subtest`` works by decorating a function as a subtest. The decorated
function will be run by iterating over ... | subtest | python | scrtlabs/catalyst | catalyst/testing/core.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/testing/core.py | Apache-2.0 |
def parameter_space(__fail_fast=False, **params):
"""
Wrapper around subtest that allows passing keywords mapping names to
iterables of values.
The decorated test function will be called with the cross-product of all
possible inputs
Examples
--------
>>> from unittest import TestCase
... |
Wrapper around subtest that allows passing keywords mapping names to
iterables of values.
The decorated test function will be called with the cross-product of all
possible inputs
Examples
--------
>>> from unittest import TestCase
>>> class SomeTestCase(TestCase):
... @paramet... | parameter_space | python | scrtlabs/catalyst | catalyst/testing/core.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/testing/core.py | Apache-2.0 |
def make_asset_finder(cls):
"""Returns a new AssetFinder
Returns
-------
asset_finder : catalyst.assets.AssetFinder
"""
return cls.enter_class_context(tmp_asset_finder(
url=cls.make_asset_finder_db_url(),
equities=cls.make_equity_info(),
... | Returns a new AssetFinder
Returns
-------
asset_finder : catalyst.assets.AssetFinder
| make_asset_finder | python | scrtlabs/catalyst | catalyst/testing/fixtures.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/testing/fixtures.py | Apache-2.0 |
def invert_unique(d, check=True):
"""
Invert a dictionary with unique values into a dictionary with (k, v) pairs
flipped.
"""
if check:
assert len(set(d.values())) == len(d), "Values were not unique!"
return {v: k for k, v in iteritems(d)} |
Invert a dictionary with unique values into a dictionary with (k, v) pairs
flipped.
| invert_unique | python | scrtlabs/catalyst | catalyst/utils/control_flow.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/control_flow.py | Apache-2.0 |
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.... |
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.
Examples
--------
@deprecated(msg=... | deprecated | python | scrtlabs/catalyst | catalyst/utils/deprecate.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/deprecate.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 catalyst.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 catalyst.utils.preprocess import preprocess
>>> @preprocess(dtype=ensure_dtype)
... def foo(dtype):
... return dtype
...
>>> foo(float)
dtype('float64')
... | ensure_dtype | python | scrtlabs/catalyst | catalyst/utils/input_validation.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/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 catalyst.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 catalyst.utils.preprocess import preprocess
>>> @preprocess(tz=ensure_timezone)
... def foo(tz):
... return tz
>>> foo('utc')
<UTC>
| ensure_timezone | python | scrtlabs/catalyst | catalyst/utils/input_validation.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/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 catalyst.utils.preprocess import preprocess
>>> @preprocess(ts=ensure_timestamp)
... def foo(ts):
... return ts
>>> foo('2014-01-... | Argument preprocessor that converts the input into a pandas Timestamp
object.
Examples
--------
>>> from catalyst.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 | scrtlabs/catalyst | catalyst/utils/input_validation.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/input_validation.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 | scrtlabs/catalyst | catalyst/utils/metautils.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/metautils.py | Apache-2.0 |
def catalyst_root(environ=None):
"""
Get the root directory for all catalyst-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 catalyst-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 ... | catalyst_root | python | scrtlabs/catalyst | catalyst/utils/paths.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/paths.py | Apache-2.0 |
def handle_response(response, mode):
"""
handles the response given by the server according to it's status code
:param response: the format returned from a request
:param mode: Backtest/ status
:return: DataFrame/ str
"""
if response.status_code == 500:
raise Exception("issues with ... |
handles the response given by the server according to it's status code
:param response: the format returned from a request
:param mode: Backtest/ status
:return: DataFrame/ str
| handle_response | python | scrtlabs/catalyst | catalyst/utils/remote.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/remote.py | Apache-2.0 |
def prepare_args(file, text):
"""
send the algo as a base64 decoded text object
:param file: File
:param text: str
:return: None, text: str
"""
if text:
text = base64.b64encode(text)
else:
text = base64.b64encode(bytes(file.read(), 'utf-8')).decode('utf-8')
file... |
send the algo as a base64 decoded text object
:param file: File
:param text: str
:return: None, text: str
| prepare_args | python | scrtlabs/catalyst | catalyst/utils/remote_utils.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/remote_utils.py | Apache-2.0 |
def is_valid_uuid(uuid_to_test, version=4):
"""
Check if uuid_to_test is a valid UUID.
Parameters
----------
uuid_to_test : str
version : {1, 2, 3, 4}
Returns
-------
`True` if uuid_to_test is a valid UUID, otherwise `False`.
Examples
--------
>>> is_valid_uuid('c9bf9e... |
Check if uuid_to_test is a valid UUID.
Parameters
----------
uuid_to_test : str
version : {1, 2, 3, 4}
Returns
-------
`True` if uuid_to_test is a valid UUID, otherwise `False`.
Examples
--------
>>> is_valid_uuid('c9bf9e57-1685-4c89-bafb-ff5af830be8a')
True
>>> i... | is_valid_uuid | python | scrtlabs/catalyst | catalyst/utils/remote_utils.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/remote_utils.py | Apache-2.0 |
def _run(handle_data,
initialize,
before_trading_start,
analyze,
algofile,
algotext,
defines,
data_frequency,
capital_base,
data,
bundle,
bundle_timestamp,
start,
end,
output,
print_alg... | Run a backtest for the given algorithm.
This is shared between the cli and :func:`catalyst.run_algo`.
| _run | python | scrtlabs/catalyst | catalyst/utils/run_algo.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/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 (~/.catalyst/extension.py)?
extension : iterable[str]
The pa... | Load all of the given extensions. This should be called by run_algo
or the cli.
Parameters
----------
default : bool
Load the default exension (~/.catalyst/extension.py)?
extension : iterable[str]
The paths to the extensions to load. If the path ends in ``.py`` it is
treated... | load_extensions | python | scrtlabs/catalyst | catalyst/utils/run_algo.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/run_algo.py | Apache-2.0 |
def dumps_with_persistent_ids(obj, protocol=None):
"""
Performs a pickle dumps on the given object, substituting all references to
a TradingEnvironment or AssetFinder with tokenized representations.
All arguments are passed to pickle.Pickler and are described therein.
"""
file = BytesIO()
p... |
Performs a pickle dumps on the given object, substituting all references to
a TradingEnvironment or AssetFinder with tokenized representations.
All arguments are passed to pickle.Pickler and are described therein.
| dumps_with_persistent_ids | python | scrtlabs/catalyst | catalyst/utils/serialization_utils.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/serialization_utils.py | Apache-2.0 |
def loads_with_persistent_ids(str, env):
"""
Performs a pickle loads on the given string, substituting the given
TradingEnvironment in to any tokenized representations of a
TradingEnvironment or AssetFinder.
Parameters
----------
str : String
The string representation of the object ... |
Performs a pickle loads on the given string, substituting the given
TradingEnvironment in to any tokenized representations of a
TradingEnvironment or AssetFinder.
Parameters
----------
str : String
The string representation of the object to be unpickled.
env : TradingEnvironment
... | loads_with_persistent_ids | python | scrtlabs/catalyst | catalyst/utils/serialization_utils.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/serialization_utils.py | Apache-2.0 |
def create_test_catalyst(**config):
"""
:param config: A configuration object that is a dict with:
- sid - an integer, which will be used as the asset ID.
- order_count - the number of orders the test algo will place,
defaults to 100
- order_amount - the number ... |
:param config: A configuration object that is a dict with:
- sid - an integer, which will be used as the asset ID.
- order_count - the number of orders the test algo will place,
defaults to 100
- order_amount - the number of shares per order, defaults to 100
... | create_test_catalyst | python | scrtlabs/catalyst | catalyst/utils/simfactory.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/simfactory.py | Apache-2.0 |
def get_calendar(self, name):
"""
Retrieves an instance of a TradingCalendar whose name is given.
Parameters
----------
name : str
The name of the TradingCalendar to be retrieved.
Returns
-------
calendar : catalyst.utils.calendars.TradingCal... |
Retrieves an instance of a TradingCalendar whose name is given.
Parameters
----------
name : str
The name of the TradingCalendar to be retrieved.
Returns
-------
calendar : catalyst.utils.calendars.TradingCalendar
The desired calendar.
... | get_calendar | python | scrtlabs/catalyst | catalyst/utils/calendars/calendar_utils.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/calendar_utils.py | Apache-2.0 |
def has_calendar(self, name):
"""
Do we have (or have the ability to make) a calendar with ``name``?
"""
return (
name in self._calendars or
name in self._calendar_factories or
name in self._aliases
) |
Do we have (or have the ability to make) a calendar with ``name``?
| has_calendar | python | scrtlabs/catalyst | catalyst/utils/calendars/calendar_utils.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/calendar_utils.py | Apache-2.0 |
def register_calendar(self, name, calendar, force=False):
"""
Registers a calendar for retrieval by the get_calendar method.
Parameters
----------
name: str
The key with which to register this calendar.
calendar: TradingCalendar
The calendar to be... |
Registers a calendar for retrieval by the get_calendar method.
Parameters
----------
name: str
The key with which to register this calendar.
calendar: TradingCalendar
The calendar to be registered for retrieval.
force : bool, optional
... | register_calendar | python | scrtlabs/catalyst | catalyst/utils/calendars/calendar_utils.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/calendar_utils.py | Apache-2.0 |
def register_calendar_type(self, name, calendar_type, force=False):
"""
Registers a calendar by type.
This is useful for registering a new calendar to be lazily instantiated
at some future point in time.
Parameters
----------
name: str
The key with w... |
Registers a calendar by type.
This is useful for registering a new calendar to be lazily instantiated
at some future point in time.
Parameters
----------
name: str
The key with which to register this calendar.
calendar_type: type
The typ... | register_calendar_type | python | scrtlabs/catalyst | catalyst/utils/calendars/calendar_utils.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/calendar_utils.py | Apache-2.0 |
def register_calendar_alias(self, alias, real_name, force=False):
"""
Register an alias for a calendar.
This is useful when multiple exchanges should share a calendar, or when
there are multiple ways to refer to the same exchange.
After calling ``register_alias('alias', 'real_n... |
Register an alias for a calendar.
This is useful when multiple exchanges should share a calendar, or when
there are multiple ways to refer to the same exchange.
After calling ``register_alias('alias', 'real_name')``, subsequent
calls to ``get_calendar('alias')`` will return th... | register_calendar_alias | python | scrtlabs/catalyst | catalyst/utils/calendars/calendar_utils.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/calendar_utils.py | Apache-2.0 |
def resolve_alias(self, name):
"""
Resolve a calendar alias for retrieval.
Parameters
----------
name : str
The name of the requested calendar.
Returns
-------
canonical_name : str
The real name of the calendar to create/return.
... |
Resolve a calendar alias for retrieval.
Parameters
----------
name : str
The name of the requested calendar.
Returns
-------
canonical_name : str
The real name of the calendar to create/return.
| resolve_alias | python | scrtlabs/catalyst | catalyst/utils/calendars/calendar_utils.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/calendar_utils.py | Apache-2.0 |
def deregister_calendar(self, name):
"""
If a calendar is registered with the given name, it is de-registered.
Parameters
----------
cal_name : str
The name of the calendar to be deregistered.
"""
self._calendars.pop(name, None)
self._calendar... |
If a calendar is registered with the given name, it is de-registered.
Parameters
----------
cal_name : str
The name of the calendar to be deregistered.
| deregister_calendar | python | scrtlabs/catalyst | catalyst/utils/calendars/calendar_utils.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/calendar_utils.py | Apache-2.0 |
def next_open(self, dt):
"""
Given a dt, returns the next open.
If the given dt happens to be a session open, the next session's open
will be returned.
Parameters
----------
dt: pd.Timestamp
The dt for which to get the next open.
Returns
... |
Given a dt, returns the next open.
If the given dt happens to be a session open, the next session's open
will be returned.
Parameters
----------
dt: pd.Timestamp
The dt for which to get the next open.
Returns
-------
pd.Timestamp
... | next_open | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def next_close(self, dt):
"""
Given a dt, returns the next close.
Parameters
----------
dt: pd.Timestamp
The dt for which to get the next close.
Returns
-------
pd.Timestamp
The UTC timestamp of the next close.
"""
... |
Given a dt, returns the next close.
Parameters
----------
dt: pd.Timestamp
The dt for which to get the next close.
Returns
-------
pd.Timestamp
The UTC timestamp of the next close.
| next_close | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def previous_open(self, dt):
"""
Given a dt, returns the previous open.
Parameters
----------
dt: pd.Timestamp
The dt for which to get the previous open.
Returns
-------
pd.Timestamp
The UTC imestamp of the previous open.
... |
Given a dt, returns the previous open.
Parameters
----------
dt: pd.Timestamp
The dt for which to get the previous open.
Returns
-------
pd.Timestamp
The UTC imestamp of the previous open.
| previous_open | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def previous_close(self, dt):
"""
Given a dt, returns the previous close.
Parameters
----------
dt: pd.Timestamp
The dt for which to get the previous close.
Returns
-------
pd.Timestamp
The UTC timestamp of the previous close.
... |
Given a dt, returns the previous close.
Parameters
----------
dt: pd.Timestamp
The dt for which to get the previous close.
Returns
-------
pd.Timestamp
The UTC timestamp of the previous close.
| previous_close | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def next_session_label(self, session_label):
"""
Given a session label, returns the label of the next session.
Parameters
----------
session_label: pd.Timestamp
A session whose next session is desired.
Returns
-------
pd.Timestamp
... |
Given a session label, returns the label of the next session.
Parameters
----------
session_label: pd.Timestamp
A session whose next session is desired.
Returns
-------
pd.Timestamp
The next session label (midnight UTC).
Notes
... | next_session_label | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def previous_session_label(self, session_label):
"""
Given a session label, returns the label of the previous session.
Parameters
----------
session_label: pd.Timestamp
A session whose previous session is desired.
Returns
-------
pd.Timestamp... |
Given a session label, returns the label of the previous session.
Parameters
----------
session_label: pd.Timestamp
A session whose previous session is desired.
Returns
-------
pd.Timestamp
The previous session label (midnight UTC).
... | previous_session_label | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def minutes_for_session(self, session_label):
"""
Given a session label, return the minutes for that session.
Parameters
----------
session_label: pd.Timestamp (midnight UTC)
A session label whose session's minutes are desired.
Returns
-------
... |
Given a session label, return the minutes for that session.
Parameters
----------
session_label: pd.Timestamp (midnight UTC)
A session label whose session's minutes are desired.
Returns
-------
pd.DateTimeIndex
All the minutes for the gi... | minutes_for_session | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def sessions_in_range(self, start_session_label, end_session_label):
"""
Given start and end session labels, return all the sessions in that
range, inclusive.
Parameters
----------
start_session_label: pd.Timestamp (midnight UTC)
The label representing the fi... |
Given start and end session labels, return all the sessions in that
range, inclusive.
Parameters
----------
start_session_label: pd.Timestamp (midnight UTC)
The label representing the first session of the desired range.
end_session_label: pd.Timestamp (midn... | sessions_in_range | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def sessions_window(self, session_label, count):
"""
Given a session label and a window size, returns a list of sessions
of size `count` + 1, that either starts with the given session
(if `count` is positive) or ends with the given session (if `count` is
negative).
Param... |
Given a session label and a window size, returns a list of sessions
of size `count` + 1, that either starts with the given session
(if `count` is positive) or ends with the given session (if `count` is
negative).
Parameters
----------
session_label: pd.Timestamp... | sessions_window | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def session_distance(self, start_session_label, end_session_label):
"""
Given a start and end session label, returns the distance between
them. For example, for three consecutive sessions Mon., Tues., and
Wed, `session_distance(Mon, Wed)` would return 2.
Parameters
----... |
Given a start and end session label, returns the distance between
them. For example, for three consecutive sessions Mon., Tues., and
Wed, `session_distance(Mon, Wed)` would return 2.
Parameters
----------
start_session_label: pd.Timestamp
The label of the s... | session_distance | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def minutes_in_range(self, start_minute, end_minute):
"""
Given start and end minutes, return all the calendar minutes
in that range, inclusive.
Given minutes don't need to be calendar minutes.
Parameters
----------
start_minute: pd.Timestamp
The min... |
Given start and end minutes, return all the calendar minutes
in that range, inclusive.
Given minutes don't need to be calendar minutes.
Parameters
----------
start_minute: pd.Timestamp
The minute representing the start of the desired range.
end_min... | minutes_in_range | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def minutes_for_sessions_in_range(self, start_session_label,
end_session_label):
"""
Returns all the minutes for all the sessions from the given start
session label to the given end session label, inclusive.
Parameters
----------
sta... |
Returns all the minutes for all the sessions from the given start
session label to the given end session label, inclusive.
Parameters
----------
start_session_label: pd.Timestamp
The label of the first session in the range.
end_session_label: pd.Timestamp
... | minutes_for_sessions_in_range | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def open_and_close_for_session(self, session_label):
"""
Returns a tuple of timestamps of the open and close of the session
represented by the given label.
Parameters
----------
session_label: pd.Timestamp
The session whose open and close are desired.
... |
Returns a tuple of timestamps of the open and close of the session
represented by the given label.
Parameters
----------
session_label: pd.Timestamp
The session whose open and close are desired.
Returns
-------
(Timestamp, Timestamp)
... | open_and_close_for_session | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def _all_minutes_with_interval(self, interval):
"""
Returns a DatetimeIndex representing all the minutes in this calendar.
"""
opens_in_ns = \
self._opens.values.astype('datetime64[ns]')
closes_in_ns = \
self._closes.values.astype('datetime64[ns]')
... |
Returns a DatetimeIndex representing all the minutes in this calendar.
| _all_minutes_with_interval | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def minute_to_session_label(self, dt, direction="next"):
"""
Given a minute, get the label of its containing session.
Parameters
----------
dt : pd.Timestamp or nanosecond offset
The dt for which to get the containing session.
direction: str
"nex... |
Given a minute, get the label of its containing session.
Parameters
----------
dt : pd.Timestamp or nanosecond offset
The dt for which to get the containing session.
direction: str
"next" (default) means that if the given dt is not part of a
... | minute_to_session_label | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def minute_index_to_session_labels(self, index):
"""
Given a sorted DatetimeIndex of market minutes, return a
DatetimeIndex of the corresponding session labels.
Parameters
----------
index: pd.DatetimeIndex or pd.Series
The ordered list of market minutes we w... |
Given a sorted DatetimeIndex of market minutes, return a
DatetimeIndex of the corresponding session labels.
Parameters
----------
index: pd.DatetimeIndex or pd.Series
The ordered list of market minutes we want session labels for.
Returns
-------
... | minute_index_to_session_labels | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def _special_dates(self, calendars, ad_hoc_dates, start_date, end_date):
"""
Union an iterable of pairs of the form (time, calendar)
and an iterable of pairs of the form (time, [dates])
(This is shared logic for computing special opens and special closes.)
"""
_dates = D... |
Union an iterable of pairs of the form (time, calendar)
and an iterable of pairs of the form (time, [dates])
(This is shared logic for computing special opens and special closes.)
| _special_dates | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def days_at_time(days, t, tz, day_offset=0):
"""
Create an index of days at time ``t``, interpreted in timezone ``tz``.
The returned index is localized to UTC.
Parameters
----------
days : DatetimeIndex
An index of dates (represented as midnight).
t : datetime.time
The time... |
Create an index of days at time ``t``, interpreted in timezone ``tz``.
The returned index is localized to UTC.
Parameters
----------
days : DatetimeIndex
An index of dates (represented as midnight).
t : datetime.time
The time to apply as an offset to each day in ``days``.
... | days_at_time | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def _overwrite_special_dates(midnight_utcs,
opens_or_closes,
special_opens_or_closes):
"""
Overwrite dates in open_or_closes with corresponding dates in
special_opens_or_closes, using midnight_utcs for alignment.
"""
# Short circuit when noth... |
Overwrite dates in open_or_closes with corresponding dates in
special_opens_or_closes, using midnight_utcs for alignment.
| _overwrite_special_dates | python | scrtlabs/catalyst | catalyst/utils/calendars/trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/catalyst/utils/calendars/trading_calendar.py | Apache-2.0 |
def test_algo_record_allow_mock(self):
"""
Test that values from "MagicMock"ed methods can be passed to record.
Relevant for our basic/validation and methods like history, which
will end up returning a MagicMock instead of a DataFrame.
"""
test_algo = TradingAlgorithm(
... |
Test that values from "MagicMock"ed methods can be passed to record.
Relevant for our basic/validation and methods like history, which
will end up returning a MagicMock instead of a DataFrame.
| test_algo_record_allow_mock | python | scrtlabs/catalyst | tests/test_algorithm.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_algorithm.py | Apache-2.0 |
def _test_order_methods(self):
"""
Only test that order methods can be called without error.
Correct filling of orders is tested in catalyst.
"""
test_algo = TradingAlgorithm(
script=call_all_order_methods,
sim_params=self.sim_params,
env=self.... |
Only test that order methods can be called without error.
Correct filling of orders is tested in catalyst.
| _test_order_methods | python | scrtlabs/catalyst | tests/test_algorithm.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_algorithm.py | Apache-2.0 |
def _test_order_in_init(self):
"""
Test that calling order in initialize
will raise an error.
"""
with self.assertRaises(OrderDuringInitialize):
test_algo = TradingAlgorithm(
script=call_order_in_init,
sim_params=self.sim_params,
... |
Test that calling order in initialize
will raise an error.
| _test_order_in_init | python | scrtlabs/catalyst | tests/test_algorithm.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_algorithm.py | Apache-2.0 |
def _test_portfolio_in_init(self):
"""
Test that accessing portfolio in init doesn't break.
"""
test_algo = TradingAlgorithm(
script=access_portfolio_in_init,
sim_params=self.sim_params,
env=self.env,
)
test_algo.run(self.data_portal) |
Test that accessing portfolio in init doesn't break.
| _test_portfolio_in_init | python | scrtlabs/catalyst | tests/test_algorithm.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_algorithm.py | Apache-2.0 |
def _test_account_in_init(self):
"""
Test that accessing account in init doesn't break.
"""
test_algo = TradingAlgorithm(
script=access_account_in_init,
sim_params=self.sim_params,
env=self.env,
)
test_algo.run(self.data_portal) |
Test that accessing account in init doesn't break.
| _test_account_in_init | python | scrtlabs/catalyst | tests/test_algorithm.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_algorithm.py | Apache-2.0 |
def _test_zero_trading_days(self, name, algocode):
"""
Test that when we run a simulation with no trading days (e.g. beginning
and ending the same weekend), we don't crash on calculating the
benchmark
"""
sim_params = factory.create_simulation_parameters(
star... |
Test that when we run a simulation with no trading days (e.g. beginning
and ending the same weekend), we don't crash on calculating the
benchmark
| _test_zero_trading_days | python | scrtlabs/catalyst | tests/test_algorithm.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_algorithm.py | Apache-2.0 |
def test_can_trade_delisted(self):
"""
Test that can_trade returns False for an asset on or after its auto
close date.
"""
auto_closing_asset = self.asset_finder.retrieve_asset(7)
# Our asset's auto close date is 2016-01-20, which means that as of the
# market op... |
Test that can_trade returns False for an asset on or after its auto
close date.
| test_can_trade_delisted | python | scrtlabs/catalyst | tests/test_bar_data.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_bar_data.py | Apache-2.0 |
def _test_set_portfolio(self):
"""
Are we protected against overwriting an algo's portfolio?
"""
algo = SetPortfolioAlgorithm(self.sid,
sim_params=self.sim_params,
env=self.env)
with self.assertRaises(Attr... |
Are we protected against overwriting an algo's portfolio?
| _test_set_portfolio | python | scrtlabs/catalyst | tests/test_exception_handling.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_exception_handling.py | Apache-2.0 |
def create_txn(asset, dt, price, amount):
"""
Create a fake transaction to be filled and processed prior to the execution
of a given trade event.
"""
if not isinstance(asset, Asset):
raise ValueError("pass an asset to create_txn")
mock_order = Order(dt, asset, amount, id=None)
retur... |
Create a fake transaction to be filled and processed prior to the execution
of a given trade event.
| create_txn | python | scrtlabs/catalyst | tests/test_perf_tracking.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_perf_tracking.py | Apache-2.0 |
def calculate_results(sim_params,
env,
data_portal,
splits=None,
txns=None,
commissions=None):
"""
Run the given events through a stripped down version of the loop in
AlgorithmSimulator.transform.
... |
Run the given events through a stripped down version of the loop in
AlgorithmSimulator.transform.
IMPORTANT NOTE FOR TEST WRITERS/READERS:
This loop has some wonky logic for the order of event processing for
datasource types. This exists mostly to accommodate legacy tests that were
making as... | calculate_results | python | scrtlabs/catalyst | tests/test_perf_tracking.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_perf_tracking.py | Apache-2.0 |
def _test_long_short_positions(self):
"""
start with $1000
buy 100 stock1 shares at $10
sell short 100 stock2 shares at $10
stock1 then goes down to $9
stock2 goes to $11
"""
self.create_environment_stuff()
trades_1 = factory.create_trade_history(... |
start with $1000
buy 100 stock1 shares at $10
sell short 100 stock2 shares at $10
stock1 then goes down to $9
stock2 goes to $11
| _test_long_short_positions | python | scrtlabs/catalyst | tests/test_perf_tracking.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_perf_tracking.py | Apache-2.0 |
def _test_levered_long_position(self):
"""
start with $1,000, then buy 1000 shares at $10.
price goes to $11
"""
# post some trades in the market
self.create_environment_stuff()
trades = factory.create_trade_history(
self.asset1,
... |
start with $1,000, then buy 1000 shares at $10.
price goes to $11
| _test_levered_long_position | python | scrtlabs/catalyst | tests/test_perf_tracking.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_perf_tracking.py | Apache-2.0 |
def _test_long_position(self):
"""
verify that the performance period calculates properly for a
single buy transaction
"""
self.create_environment_stuff()
# post some trades in the market
trades = factory.create_trade_history(
self.asset1,
... |
verify that the performance period calculates properly for a
single buy transaction
| _test_long_position | python | scrtlabs/catalyst | tests/test_perf_tracking.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_perf_tracking.py | Apache-2.0 |
def _test_short_position(self):
"""verify that the performance period calculates properly for a \
single short-sale transaction"""
self.create_environment_stuff(num_days=6)
trades = factory.create_trade_history(
self.asset1,
[10, 10, 10, 11, 10, 9],
[100, 100... | verify that the performance period calculates properly for a single short-sale transaction | _test_short_position | python | scrtlabs/catalyst | tests/test_perf_tracking.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_perf_tracking.py | Apache-2.0 |
def _test_covering_short(self):
"""verify performance where short is bought and covered, and shares \
trade after cover"""
self.create_environment_stuff(num_days=10)
trades = factory.create_trade_history(
self.asset1,
[10, 10, 10, 11, 9, 8, 7, 8, 9, 10],
[100... | verify performance where short is bought and covered, and shares trade after cover | _test_covering_short | python | scrtlabs/catalyst | tests/test_perf_tracking.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_perf_tracking.py | Apache-2.0 |
def test_empty_positions(self):
"""
make sure all the empty position stats return a numeric 0
Originally this bug was due to np.dot([], []) returning
np.bool_(False)
"""
sim_params = factory.create_simulation_parameters(num_days=4)
pt = perf.PositionTracker(sim_... |
make sure all the empty position stats return a numeric 0
Originally this bug was due to np.dot([], []) returning
np.bool_(False)
| test_empty_positions | python | scrtlabs/catalyst | tests/test_perf_tracking.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_perf_tracking.py | Apache-2.0 |
def test_security_list_restrictions(self):
"""
Test single- and multi-asset queries on restrictions defined by
catalyst.utils.security_list.SecurityList
"""
# A mock SecurityList object filled with fake data
class SecurityList(object):
def __init__(self, asse... |
Test single- and multi-asset queries on restrictions defined by
catalyst.utils.security_list.SecurityList
| test_security_list_restrictions | python | scrtlabs/catalyst | tests/test_restrictions.py | https://github.com/scrtlabs/catalyst/blob/master/tests/test_restrictions.py | Apache-2.0 |
def test_new_years(self):
"""
Check whether the TradingCalendar contains certain dates.
"""
# January 2012
# Su Mo Tu We Th Fr Sa
# 1 2 3 4 5 6 7
# 8 9 10 11 12 13 14
# 15 16 17 18 19 20 21
# 22 23 24 25 26 27 28
# 29 30 31
... |
Check whether the TradingCalendar contains certain dates.
| test_new_years | python | scrtlabs/catalyst | tests/calendars/test_nyse_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/tests/calendars/test_nyse_calendar.py | Apache-2.0 |
def test_early_close_independence_day_thursday(self):
"""
Until 2013, the market closed early the Friday after an
Independence Day on Thursday. Since then, the early close is on
Wednesday.
"""
# July 2002
# Su Mo Tu We Th Fr Sa
# 1 2 3 4 5 6... |
Until 2013, the market closed early the Friday after an
Independence Day on Thursday. Since then, the early close is on
Wednesday.
| test_early_close_independence_day_thursday | python | scrtlabs/catalyst | tests/calendars/test_nyse_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/tests/calendars/test_nyse_calendar.py | Apache-2.0 |
def test_start_end(self):
"""
Check TradingCalendar with defined start/end dates.
"""
start = pd.Timestamp('2010-1-3', tz='UTC')
end = pd.Timestamp('2010-1-10', tz='UTC')
calendar = NYSEExchangeCalendar(start=start, end=end)
expected_first = pd.Timestamp('2010-1-4... |
Check TradingCalendar with defined start/end dates.
| test_start_end | python | scrtlabs/catalyst | tests/calendars/test_nyse_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/tests/calendars/test_nyse_calendar.py | Apache-2.0 |
def load_answer_key(filename):
"""
Load a CSV from tests/resources/calendars/{filename}.csv
"""
fullpath = join(
dirname(abspath(__file__)),
'../resources',
'calendars',
filename + '.csv',
)
return read_csv(
ful... |
Load a CSV from tests/resources/calendars/{filename}.csv
| load_answer_key | python | scrtlabs/catalyst | tests/calendars/test_trading_calendar.py | https://github.com/scrtlabs/catalyst/blob/master/tests/calendars/test_trading_calendar.py | Apache-2.0 |
def create_orders_dict(self, asset, last_order):
"""
create an orders dict which mocks the .orders object
:param asset: TradingPair
:param last_order: bool, adds another order to the dict.
mocks the functionality of the fetchOrder methods
:return: dict... |
create an orders dict which mocks the .orders object
:param asset: TradingPair
:param last_order: bool, adds another order to the dict.
mocks the functionality of the fetchOrder methods
:return: dict(Order)
| create_orders_dict | python | scrtlabs/catalyst | tests/exchange/test_ccxt.py | https://github.com/scrtlabs/catalyst/blob/master/tests/exchange/test_ccxt.py | Apache-2.0 |
def create_trades_dict(self, symbol):
"""
:param symbol: only for the side effect
:return: list(dict)
"""
trades = list()
trades.append(
{'info': {'globalTradeID': 369156767, 'tradeID': '8415970',
'rate': '0.0025', 'amount': '0.78', 'tota... |
:param symbol: only for the side effect
:return: list(dict)
| create_trades_dict | python | scrtlabs/catalyst | tests/exchange/test_ccxt.py | https://github.com/scrtlabs/catalyst/blob/master/tests/exchange/test_ccxt.py | Apache-2.0 |
def mod_last_order(self):
"""
adds the last order into .orders
:return:
"""
self.last_order = True
asset = [pair for pair in self.exchange.assets if
pair.symbol == 'eth_usdt'][0]
orders_dict = self.create_orders_dict(asset, self.last_order)
... |
adds the last order into .orders
:return:
| mod_last_order | python | scrtlabs/catalyst | tests/exchange/test_ccxt.py | https://github.com/scrtlabs/catalyst/blob/master/tests/exchange/test_ccxt.py | Apache-2.0 |
def compare_orders(self, observed, expected):
"""
compares orders arguments to make sure that they are equal
:param observed: Order
:param expected: Order
:return: bool
"""
return observed.id == expected.id and \
observed.amount == expected.amount and ... |
compares orders arguments to make sure that they are equal
:param observed: Order
:param expected: Order
:return: bool
| compare_orders | python | scrtlabs/catalyst | tests/exchange/test_ccxt.py | https://github.com/scrtlabs/catalyst/blob/master/tests/exchange/test_ccxt.py | Apache-2.0 |
def test_create_order_timeout_order(self):
"""
create_order method
tests the handling of a RequestTimeout exception and locating the
order, if was created, using the fetchOrders method
:return:
"""
asset = [pair for pair in self.exchange.assets if
... |
create_order method
tests the handling of a RequestTimeout exception and locating the
order, if was created, using the fetchOrders method
:return:
| test_create_order_timeout_order | python | scrtlabs/catalyst | tests/exchange/test_ccxt.py | https://github.com/scrtlabs/catalyst/blob/master/tests/exchange/test_ccxt.py | Apache-2.0 |
def test_create_order_timeout_open(self):
"""
create_order method
tests the handling of a RequestTimeout exception and locating the
order, if was created, using the fetchOpenOrders method
:return:
"""
asset = [pair for pair in self.exchange.assets if
... |
create_order method
tests the handling of a RequestTimeout exception and locating the
order, if was created, using the fetchOpenOrders method
:return:
| test_create_order_timeout_open | python | scrtlabs/catalyst | tests/exchange/test_ccxt.py | https://github.com/scrtlabs/catalyst/blob/master/tests/exchange/test_ccxt.py | Apache-2.0 |
def test_create_order_timeout_closed(self):
"""
create_order method
tests the handling of a RequestTimeout exception and locating the
order, if was created, using the fetchClosedOrders method
:return:
"""
asset = [pair for pair in self.exchange.assets if
... |
create_order method
tests the handling of a RequestTimeout exception and locating the
order, if was created, using the fetchClosedOrders method
:return:
| test_create_order_timeout_closed | python | scrtlabs/catalyst | tests/exchange/test_ccxt.py | https://github.com/scrtlabs/catalyst/blob/master/tests/exchange/test_ccxt.py | Apache-2.0 |
def test_create_order_timeout_trade(self):
"""
create_order method
tests the handling of a RequestTimeout exception and locating the
order, if was created, using the fetchTrades method.
checks as well, the case that the order was not created at all,
and makes sure an exce... |
create_order method
tests the handling of a RequestTimeout exception and locating the
order, if was created, using the fetchTrades method.
checks as well, the case that the order was not created at all,
and makes sure an exception is raised in order to retry the
creation... | test_create_order_timeout_trade | python | scrtlabs/catalyst | tests/exchange/test_ccxt.py | https://github.com/scrtlabs/catalyst/blob/master/tests/exchange/test_ccxt.py | Apache-2.0 |
def test_process_order_timeout(self):
"""
in case of a requestTimeout make sure that the process_order method
returns an exception so the retry method can request the trades again.
:return:
"""
asset = [pair for pair in self.exchange.assets if
pair.symbol... |
in case of a requestTimeout make sure that the process_order method
returns an exception so the retry method can request the trades again.
:return:
| test_process_order_timeout | python | scrtlabs/catalyst | tests/exchange/test_ccxt.py | https://github.com/scrtlabs/catalyst/blob/master/tests/exchange/test_ccxt.py | Apache-2.0 |
def compare_bundle_with_exchange(self, exchange, assets, end_dt, bar_count,
freq, data_frequency, data_portal, field):
"""
Creates DataFrames from the bundle and exchange for the specified
data set.
Parameters
----------
exchange: Exc... |
Creates DataFrames from the bundle and exchange for the specified
data set.
Parameters
----------
exchange: Exchange
assets
end_dt
bar_count
freq
data_frequency
data_portal
Returns
-------
| compare_bundle_with_exchange | python | scrtlabs/catalyst | tests/exchange/test_suites/test_suite_bundle.py | https://github.com/scrtlabs/catalyst/blob/master/tests/exchange/test_suites/test_suite_bundle.py | Apache-2.0 |
def run_graph(self, graph, initial_workspace, mask=None):
"""
Compute the given TermGraph, seeding the workspace of our engine with
`initial_workspace`.
Parameters
----------
graph : catalyst.pipeline.graph.TermGraph
Graph to run.
initial_workspace : ... |
Compute the given TermGraph, seeding the workspace of our engine with
`initial_workspace`.
Parameters
----------
graph : catalyst.pipeline.graph.TermGraph
Graph to run.
initial_workspace : dict
Initial workspace to forward to SimplePipelineEngine... | run_graph | python | scrtlabs/catalyst | tests/pipeline/base.py | https://github.com/scrtlabs/catalyst/blob/master/tests/pipeline/base.py | Apache-2.0 |
def _utc_localize_index_level_0(df):
"""``tz_localize`` the first level of a multiindexed dataframe to utc.
Mutates df in place.
"""
idx = df.index
df.index = pd.MultiIndex.from_product(
(idx.levels[0].tz_localize('utc'), idx.levels[1]),
names=idx.names,
)
return df | ``tz_localize`` the first level of a multiindexed dataframe to utc.
Mutates df in place.
| _utc_localize_index_level_0 | python | scrtlabs/catalyst | tests/pipeline/test_blaze.py | https://github.com/scrtlabs/catalyst/blob/master/tests/pipeline/test_blaze.py | Apache-2.0 |
def _test_checkpoints(self, checkpoints, ffilled_values=None):
"""Simple checkpoints test that accepts a checkpoints dataframe and
the expected value for 2014-01-03.
The underlying data has value -1.0 on 2014-01-01 and 1.0 on 2014-01-04.
Parameters
----------
checkpoint... | Simple checkpoints test that accepts a checkpoints dataframe and
the expected value for 2014-01-03.
The underlying data has value -1.0 on 2014-01-01 and 1.0 on 2014-01-04.
Parameters
----------
checkpoints : pd.DataFrame
The checkpoints data.
ffilled_value :... | _test_checkpoints | python | scrtlabs/catalyst | tests/pipeline/test_blaze.py | https://github.com/scrtlabs/catalyst/blob/master/tests/pipeline/test_blaze.py | Apache-2.0 |
def retrieve_timesteps(
scheduler,
num_inference_steps: Optional[int] = None,
device: Optional[Union[str, torch.device]] = None,
timesteps: Optional[List[int]] = None,
sigmas: Optional[List[float]] = None,
**kwargs,
):
r"""
Calls the scheduler's `set_timesteps` method and retrieves times... |
Calls the scheduler's `set_timesteps` method and retrieves timesteps from the scheduler after the call. Handles
custom timesteps. Any kwargs will be supplied to `scheduler.set_timesteps`.
Args:
scheduler (`SchedulerMixin`):
The scheduler to get timesteps from.
num_inference_ste... | retrieve_timesteps | python | bytedance/InfiniteYou | pipelines/pipeline_flux_infusenet.py | https://github.com/bytedance/InfiniteYou/blob/master/pipelines/pipeline_flux_infusenet.py | Apache-2.0 |
def __call__(
self,
prompt: Union[str, List[str]] = None,
prompt_2: Optional[Union[str, List[str]]] = None,
height: Optional[int] = None,
width: Optional[int] = None,
num_inference_steps: int = 28,
timesteps: List[int] = None,
guidance_scale: float = 3.5,
... |
Function invoked when calling the pipeline for generation.
Args:
prompt (`str` or `List[str]`, *optional*):
The prompt or prompts to guide the image generation. If not defined, one has to pass `prompt_embeds`.
instead.
prompt_2 (`str` or `List[st... | __call__ | python | bytedance/InfiniteYou | pipelines/pipeline_flux_infusenet.py | https://github.com/bytedance/InfiniteYou/blob/master/pipelines/pipeline_flux_infusenet.py | Apache-2.0 |
def seed_everything(seed, deterministic=False):
"""Set random seed.
Args:
seed (int): Seed to be used.
deterministic (bool): Whether to set the deterministic option for
CUDNN backend, i.e., set `torch.backends.cudnn.deterministic`
to True and `torch.backends.cudnn.benchm... | Set random seed.
Args:
seed (int): Seed to be used.
deterministic (bool): Whether to set the deterministic option for
CUDNN backend, i.e., set `torch.backends.cudnn.deterministic`
to True and `torch.backends.cudnn.benchmark` to False.
Default: False.
| seed_everything | python | bytedance/InfiniteYou | pipelines/pipeline_infu_flux.py | https://github.com/bytedance/InfiniteYou/blob/master/pipelines/pipeline_infu_flux.py | Apache-2.0 |
def forward(self, x, latents):
"""
Args:
x (torch.Tensor): image features
shape (b, n1, D)
latent (torch.Tensor): latent features
shape (b, n2, D)
"""
x = self.norm1(x)
latents = self.norm2(latents)
b, l, _ ... |
Args:
x (torch.Tensor): image features
shape (b, n1, D)
latent (torch.Tensor): latent features
shape (b, n2, D)
| forward | python | bytedance/InfiniteYou | pipelines/resampler.py | https://github.com/bytedance/InfiniteYou/blob/master/pipelines/resampler.py | Apache-2.0 |
def get_mock_processor_inputs(array_library, num_tokens=30000):
"""
logits: (4, 30,000 ) dtype=float
input_ids shape: (4, 2048) dtype=int
"""
if array_library.startswith("torch"):
device = array_library.split("_")[1] if "_" in array_library else "cpu"
logits = torch.rand((4, num_tok... |
logits: (4, 30,000 ) dtype=float
input_ids shape: (4, 2048) dtype=int
| get_mock_processor_inputs | python | dottxt-ai/outlines | benchmarks/bench_processors.py | https://github.com/dottxt-ai/outlines/blob/master/benchmarks/bench_processors.py | Apache-2.0 |
def one_cycle(objective: str, task_list, next_task_id: int):
"""One BabyAGI cycle.
It consists in executing the highest-priority task, creating some new tasks
given the result, and re-priotizing the tasks.
Parameters
----------
objective
The overall objective of the session.
task_l... | One BabyAGI cycle.
It consists in executing the highest-priority task, creating some new tasks
given the result, and re-priotizing the tasks.
Parameters
----------
objective
The overall objective of the session.
task_list
The current list of tasks to perform.
task_id_counte... | one_cycle | python | dottxt-ai/outlines | examples/babyagi.py | https://github.com/dottxt-ai/outlines/blob/master/examples/babyagi.py | Apache-2.0 |
def call_thunk(self):
"""Call a vectorized thunk.
Thunks have no arguments and can thus be called directly.
"""
if self.is_coroutine_fn:
loop = asyncio.new_event_loop()
try:
outputs = loop.run_until_complete(self.func())
finally:
... | Call a vectorized thunk.
Thunks have no arguments and can thus be called directly.
| call_thunk | python | dottxt-ai/outlines | outlines/base.py | https://github.com/dottxt-ai/outlines/blob/master/outlines/base.py | Apache-2.0 |
def call_no_signature(self, *args, **kwargs):
"""Call functions and coroutines when no signature is specified.
When no signature is specified we assume that all of the function's
inputs and outputs are scalars (core dimension of zero). We first
broadcast the input arrays, then iterative... | Call functions and coroutines when no signature is specified.
When no signature is specified we assume that all of the function's
inputs and outputs are scalars (core dimension of zero). We first
broadcast the input arrays, then iteratively apply the function over the
elements of the br... | call_no_signature | python | dottxt-ai/outlines | outlines/base.py | https://github.com/dottxt-ai/outlines/blob/master/outlines/base.py | Apache-2.0 |
def call_with_signature(self, *args, **kwargs):
"""Call functions and coroutines when a signature is specified."""
input_core_dims, output_core_dims = self._in_and_out_core_dimensions
# Make sure that the numbers of arguments passed is compatible with
# the signature.
num_args =... | Call functions and coroutines when a signature is specified. | call_with_signature | python | dottxt-ai/outlines | outlines/base.py | https://github.com/dottxt-ai/outlines/blob/master/outlines/base.py | Apache-2.0 |
def vectorize_call(self, broadcast_shape, args, kwargs):
"""Run the function in a for loop.
A possible extension would be to parallelize the calls.
Parameters
----------
broadcast_shape
The brodcast shape of the input arrays.
args
The function's ... | Run the function in a for loop.
A possible extension would be to parallelize the calls.
Parameters
----------
broadcast_shape
The brodcast shape of the input arrays.
args
The function's broadcasted arguments.
kwargs
The function's bro... | vectorize_call | python | dottxt-ai/outlines | outlines/base.py | https://github.com/dottxt-ai/outlines/blob/master/outlines/base.py | Apache-2.0 |
def vectorize_call_coroutine(self, broadcast_shape, args, kwargs):
"""Run coroutines concurrently.
Creates as many tasks as needed and executes them in a new event
loop.
Parameters
----------
broadcast_shape
The brodcast shape of the input arrays.
ar... | Run coroutines concurrently.
Creates as many tasks as needed and executes them in a new event
loop.
Parameters
----------
broadcast_shape
The brodcast shape of the input arrays.
args
The function's broadcasted arguments.
kwargs
... | vectorize_call_coroutine | python | dottxt-ai/outlines | outlines/base.py | https://github.com/dottxt-ai/outlines/blob/master/outlines/base.py | Apache-2.0 |
def _update_arrays_type(arrays, results):
"""Update the dtype of arrays.
String arrays contain strings of fixed length. Here they are initialized with
the type of the first results, so that if the next results contain longer
strings they will be truncated when added to the output arrays. Here we
up... | Update the dtype of arrays.
String arrays contain strings of fixed length. Here they are initialized with
the type of the first results, so that if the next results contain longer
strings they will be truncated when added to the output arrays. Here we
update the type if the current results contain long... | _update_arrays_type | python | dottxt-ai/outlines | outlines/base.py | https://github.com/dottxt-ai/outlines/blob/master/outlines/base.py | Apache-2.0 |
def get_cache():
"""Get the context object that contains previously-computed return values.
The cache is used to avoid unnecessary computations and API calls, which can
be long and expensive for large models.
The cache directory defaults to `HOMEDIR/.cache/outlines`, but this choice
can be overrid... | Get the context object that contains previously-computed return values.
The cache is used to avoid unnecessary computations and API calls, which can
be long and expensive for large models.
The cache directory defaults to `HOMEDIR/.cache/outlines`, but this choice
can be overridden by the user by setti... | get_cache | python | dottxt-ai/outlines | outlines/caching.py | https://github.com/dottxt-ai/outlines/blob/master/outlines/caching.py | Apache-2.0 |
def cache(expire: Optional[float] = None, typed=False, ignore=()):
"""Caching decorator for memoizing function calls.
The cache key is created based on the values returned by the key_function callable
if provided or based on the arguments of the decorated function directly otherwise
This is based on `... | Caching decorator for memoizing function calls.
The cache key is created based on the values returned by the key_function callable
if provided or based on the arguments of the decorated function directly otherwise
This is based on `diskcache`'s `memoize`.
Parameters
----------
expire
... | cache | python | dottxt-ai/outlines | outlines/caching.py | https://github.com/dottxt-ai/outlines/blob/master/outlines/caching.py | Apache-2.0 |
def disable_cache():
"""Disable the cache for this session.
Generative models output different results each time they are called when
sampling. This can be a desirable property for some workflows, in which case
one can call `outlines.call.disable` to disable the cache for the session.
This functio... | Disable the cache for this session.
Generative models output different results each time they are called when
sampling. This can be a desirable property for some workflows, in which case
one can call `outlines.call.disable` to disable the cache for the session.
This function does not delete the cache,... | disable_cache | python | dottxt-ai/outlines | outlines/caching.py | https://github.com/dottxt-ai/outlines/blob/master/outlines/caching.py | Apache-2.0 |
def init_generator(self):
"""Load the model and initialize the generator."""
model = models.transformers(self.model_name)
self.generator = generate.json(model, self.schema) | Load the model and initialize the generator. | init_generator | python | dottxt-ai/outlines | outlines/function.py | https://github.com/dottxt-ai/outlines/blob/master/outlines/function.py | Apache-2.0 |
def __call__(self, *args, **kwargs):
"""Call the function.
.. warning::
This currently does not support batching.
Parameters
----------
args
Values to pass to the prompt template as positional arguments.
kwargs
Values to pass to the p... | Call the function.
.. warning::
This currently does not support batching.
Parameters
----------
args
Values to pass to the prompt template as positional arguments.
kwargs
Values to pass to the prompt template as keyword arguments.
| __call__ | python | dottxt-ai/outlines | outlines/function.py | https://github.com/dottxt-ai/outlines/blob/master/outlines/function.py | Apache-2.0 |
def download_from_github(short_path: str):
"""Download the file in which the function is stored on GitHub."""
GITHUB_BASE_URL = "https://raw.githubusercontent.com"
BRANCH = "main"
path = short_path.split("/")
if len(path) < 3:
raise ValueError(
"Please provide a valid path in th... | Download the file in which the function is stored on GitHub. | download_from_github | python | dottxt-ai/outlines | outlines/function.py | https://github.com/dottxt-ai/outlines/blob/master/outlines/function.py | Apache-2.0 |
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