id int32 0 252k | repo stringlengths 7 55 | path stringlengths 4 127 | func_name stringlengths 1 88 | original_string stringlengths 75 19.8k | language stringclasses 1
value | code stringlengths 75 19.8k | code_tokens list | docstring stringlengths 3 17.3k | docstring_tokens list | sha stringlengths 40 40 | url stringlengths 87 242 |
|---|---|---|---|---|---|---|---|---|---|---|---|
26,000 | quantopian/zipline | zipline/utils/input_validation.py | validate_keys | 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"
... | python | 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"
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26,001 | quantopian/zipline | zipline/utils/enum.py | enum | def enum(option, *options):
"""
Construct a new enum object.
Parameters
----------
*options : iterable of str
The names of the fields for the enum.
Returns
-------
enum
A new enum collection.
Examples
--------
>>> e = enum('a', 'b', 'c')
>>> e
<enum... | python | def enum(option, *options):
"""
Construct a new enum object.
Parameters
----------
*options : iterable of str
The names of the fields for the enum.
Returns
-------
enum
A new enum collection.
Examples
--------
>>> e = enum('a', 'b', 'c')
>>> e
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26,002 | quantopian/zipline | zipline/utils/data.py | RollingPanel.extend_back | def extend_back(self, missing_dts):
"""
Resizes the buffer to hold a new window with a new cap_multiple.
If cap_multiple is None, then the old cap_multiple is used.
"""
delta = len(missing_dts)
if not delta:
raise ValueError(
'missing_dts must... | python | def extend_back(self, missing_dts):
"""
Resizes the buffer to hold a new window with a new cap_multiple.
If cap_multiple is None, then the old cap_multiple is used.
"""
delta = len(missing_dts)
if not delta:
raise ValueError(
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26,003 | quantopian/zipline | zipline/utils/data.py | RollingPanel.set_current | def set_current(self, panel):
"""
Set the values stored in our current in-view data to be values of the
passed panel. The passed panel must have the same indices as the panel
that would be returned by self.get_current.
"""
where = slice(self._start_index, self._pos)
... | python | def set_current(self, panel):
"""
Set the values stored in our current in-view data to be values of the
passed panel. The passed panel must have the same indices as the panel
that would be returned by self.get_current.
"""
where = slice(self._start_index, self._pos)
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26,004 | quantopian/zipline | zipline/utils/data.py | RollingPanel._roll_data | def _roll_data(self):
"""
Roll window worth of data up to position zero.
Save the effort of having to expensively roll at each iteration
"""
self.buffer.values[:, :self._window, :] = \
self.buffer.values[:, -self._window:, :]
self.date_buf[:self._window] = se... | python | def _roll_data(self):
"""
Roll window worth of data up to position zero.
Save the effort of having to expensively roll at each iteration
"""
self.buffer.values[:, :self._window, :] = \
self.buffer.values[:, -self._window:, :]
self.date_buf[:self._window] = se... | [
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26,005 | quantopian/zipline | zipline/finance/order.py | Order.check_triggers | def check_triggers(self, price, dt):
"""
Update internal state based on price triggers and the
trade event's price.
"""
stop_reached, limit_reached, sl_stop_reached = \
self.check_order_triggers(price)
if (stop_reached, limit_reached) \
!= (sel... | python | def check_triggers(self, price, dt):
"""
Update internal state based on price triggers and the
trade event's price.
"""
stop_reached, limit_reached, sl_stop_reached = \
self.check_order_triggers(price)
if (stop_reached, limit_reached) \
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26,006 | quantopian/zipline | zipline/finance/order.py | Order.triggered | def triggered(self):
"""
For a market order, True.
For a stop order, True IFF stop_reached.
For a limit order, True IFF limit_reached.
"""
if self.stop is not None and not self.stop_reached:
return False
if self.limit is not None and not self.limit_re... | python | def triggered(self):
"""
For a market order, True.
For a stop order, True IFF stop_reached.
For a limit order, True IFF limit_reached.
"""
if self.stop is not None and not self.stop_reached:
return False
if self.limit is not None and not self.limit_re... | [
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26,007 | quantopian/zipline | zipline/gens/utils.py | hash_args | def hash_args(*args, **kwargs):
"""Define a unique string for any set of representable args."""
arg_string = '_'.join([str(arg) for arg in args])
kwarg_string = '_'.join([str(key) + '=' + str(value)
for key, value in iteritems(kwargs)])
combined = ':'.join([arg_string, kwarg... | python | def hash_args(*args, **kwargs):
"""Define a unique string for any set of representable args."""
arg_string = '_'.join([str(arg) for arg in args])
kwarg_string = '_'.join([str(key) + '=' + str(value)
for key, value in iteritems(kwargs)])
combined = ':'.join([arg_string, kwarg... | [
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26,008 | quantopian/zipline | zipline/gens/utils.py | assert_datasource_protocol | def assert_datasource_protocol(event):
"""Assert that an event meets the protocol for datasource outputs."""
assert event.type in DATASOURCE_TYPE
# Done packets have no dt.
if not event.type == DATASOURCE_TYPE.DONE:
assert isinstance(event.dt, datetime)
assert event.dt.tzinfo == pytz.u... | python | def assert_datasource_protocol(event):
"""Assert that an event meets the protocol for datasource outputs."""
assert event.type in DATASOURCE_TYPE
# Done packets have no dt.
if not event.type == DATASOURCE_TYPE.DONE:
assert isinstance(event.dt, datetime)
assert event.dt.tzinfo == pytz.u... | [
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26,009 | quantopian/zipline | zipline/gens/utils.py | assert_trade_protocol | def assert_trade_protocol(event):
"""Assert that an event meets the protocol for datasource TRADE outputs."""
assert_datasource_protocol(event)
assert event.type == DATASOURCE_TYPE.TRADE
assert isinstance(event.price, numbers.Real)
assert isinstance(event.volume, numbers.Integral)
assert isinst... | python | def assert_trade_protocol(event):
"""Assert that an event meets the protocol for datasource TRADE outputs."""
assert_datasource_protocol(event)
assert event.type == DATASOURCE_TYPE.TRADE
assert isinstance(event.price, numbers.Real)
assert isinstance(event.volume, numbers.Integral)
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26,010 | quantopian/zipline | zipline/gens/composites.py | date_sorted_sources | def date_sorted_sources(*sources):
"""
Takes an iterable of sources, generating namestrings and
piping their output into date_sort.
"""
sorted_stream = heapq.merge(*(_decorate_source(s) for s in sources))
# Strip out key decoration
for _, message in sorted_stream:
yield message | python | def date_sorted_sources(*sources):
"""
Takes an iterable of sources, generating namestrings and
piping their output into date_sort.
"""
sorted_stream = heapq.merge(*(_decorate_source(s) for s in sources))
# Strip out key decoration
for _, message in sorted_stream:
yield message | [
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26,011 | quantopian/zipline | zipline/utils/factory.py | create_daily_trade_source | 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... | python | 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... | [
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26,012 | quantopian/zipline | zipline/data/bundles/quandl.py | load_data_table | def load_data_table(file,
index_col,
show_progress=False):
""" Load data table from zip file provided by Quandl.
"""
with ZipFile(file) as zip_file:
file_names = zip_file.namelist()
assert len(file_names) == 1, "Expected a single file from Quandl."
... | python | def load_data_table(file,
index_col,
show_progress=False):
""" Load data table from zip file provided by Quandl.
"""
with ZipFile(file) as zip_file:
file_names = zip_file.namelist()
assert len(file_names) == 1, "Expected a single file from Quandl."
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26,013 | quantopian/zipline | zipline/data/bundles/quandl.py | fetch_data_table | def fetch_data_table(api_key,
show_progress,
retries):
""" Fetch WIKI Prices data table from Quandl
"""
for _ in range(retries):
try:
if show_progress:
log.info('Downloading WIKI metadata.')
metadata = pd.read_csv(
... | python | def fetch_data_table(api_key,
show_progress,
retries):
""" Fetch WIKI Prices data table from Quandl
"""
for _ in range(retries):
try:
if show_progress:
log.info('Downloading WIKI metadata.')
metadata = pd.read_csv(
... | [
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26,014 | quantopian/zipline | zipline/data/bundles/quandl.py | quandl_bundle | def quandl_bundle(environ,
asset_db_writer,
minute_bar_writer,
daily_bar_writer,
adjustment_writer,
calendar,
start_session,
end_session,
cache,
show_progress... | python | def quandl_bundle(environ,
asset_db_writer,
minute_bar_writer,
daily_bar_writer,
adjustment_writer,
calendar,
start_session,
end_session,
cache,
show_progress... | [
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26,015 | quantopian/zipline | zipline/data/bundles/quandl.py | download_with_progress | def download_with_progress(url, chunk_size, **progress_kwargs):
"""
Download streaming data from a URL, printing progress information to the
terminal.
Parameters
----------
url : str
A URL that can be understood by ``requests.get``.
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"""
Download streaming data from a URL, printing progress information to the
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url : str
A URL that can be understood by ``requests.get``.
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26,016 | quantopian/zipline | zipline/data/bundles/quandl.py | download_without_progress | def download_without_progress(url):
"""
Download data from a URL, returning a BytesIO containing the loaded data.
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----------
url : str
A URL that can be understood by ``requests.get``.
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data : BytesIO
A BytesIO containing the downloaded data.
... | python | def download_without_progress(url):
"""
Download data from a URL, returning a BytesIO containing the loaded data.
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url : str
A URL that can be understood by ``requests.get``.
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data : BytesIO
A BytesIO containing the downloaded data.
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26,017 | quantopian/zipline | zipline/data/resample.py | minute_frame_to_session_frame | def minute_frame_to_session_frame(minute_frame, calendar):
"""
Resample a DataFrame with minute data into the frame expected by a
BcolzDailyBarWriter.
Parameters
----------
minute_frame : pd.DataFrame
A DataFrame with the columns `open`, `high`, `low`, `close`, `volume`,
and `d... | python | def minute_frame_to_session_frame(minute_frame, calendar):
"""
Resample a DataFrame with minute data into the frame expected by a
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Parameters
----------
minute_frame : pd.DataFrame
A DataFrame with the columns `open`, `high`, `low`, `close`, `volume`,
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26,018 | quantopian/zipline | zipline/data/resample.py | minute_to_session | def minute_to_session(column, close_locs, data, out):
"""
Resample an array with minute data into an array with session data.
This function assumes that the minute data is the exact length of all
minutes in the sessions in the output.
Parameters
----------
column : str
The `open`, ... | python | def minute_to_session(column, close_locs, data, out):
"""
Resample an array with minute data into an array with session data.
This function assumes that the minute data is the exact length of all
minutes in the sessions in the output.
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column : str
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26,019 | quantopian/zipline | zipline/data/resample.py | DailyHistoryAggregator.opens | def opens(self, assets, dt):
"""
The open field's aggregation returns the first value that occurs
for the day, if there has been no data on or before the `dt` the open
is `nan`.
Once the first non-nan open is seen, that value remains constant per
asset for the remainder ... | python | def opens(self, assets, dt):
"""
The open field's aggregation returns the first value that occurs
for the day, if there has been no data on or before the `dt` the open
is `nan`.
Once the first non-nan open is seen, that value remains constant per
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26,020 | quantopian/zipline | zipline/data/resample.py | DailyHistoryAggregator.highs | def highs(self, assets, dt):
"""
The high field's aggregation returns the largest high seen between
the market open and the current dt.
If there has been no data on or before the `dt` the high is `nan`.
Returns
-------
np.array with dtype=float64, in order of ass... | python | def highs(self, assets, dt):
"""
The high field's aggregation returns the largest high seen between
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If there has been no data on or before the `dt` the high is `nan`.
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26,021 | quantopian/zipline | zipline/data/resample.py | DailyHistoryAggregator.lows | def lows(self, assets, dt):
"""
The low field's aggregation returns the smallest low seen between
the market open and the current dt.
If there has been no data on or before the `dt` the low is `nan`.
Returns
-------
np.array with dtype=float64, in order of assets... | python | def lows(self, assets, dt):
"""
The low field's aggregation returns the smallest low seen between
the market open and the current dt.
If there has been no data on or before the `dt` the low is `nan`.
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26,022 | quantopian/zipline | zipline/data/resample.py | DailyHistoryAggregator.closes | def closes(self, assets, dt):
"""
The close field's aggregation returns the latest close at the given
dt.
If the close for the given dt is `nan`, the most recent non-nan
`close` is used.
If there has been no data on or before the `dt` the close is `nan`.
Returns
... | python | def closes(self, assets, dt):
"""
The close field's aggregation returns the latest close at the given
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If the close for the given dt is `nan`, the most recent non-nan
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If there has been no data on or before the `dt` the close is `nan`.
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26,023 | quantopian/zipline | zipline/data/resample.py | DailyHistoryAggregator.volumes | def volumes(self, assets, dt):
"""
The volume field's aggregation returns the sum of all volumes
between the market open and the `dt`
If there has been no data on or before the `dt` the volume is 0.
Returns
-------
np.array with dtype=int64, in order of assets pa... | python | def volumes(self, assets, dt):
"""
The volume field's aggregation returns the sum of all volumes
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26,024 | quantopian/zipline | zipline/pipeline/domain.py | infer_domain | def infer_domain(terms):
"""
Infer the domain from a collection of terms.
The algorithm for inferring domains is as follows:
- If all input terms have a domain of GENERIC, the result is GENERIC.
- If there is exactly one non-generic domain in the input terms, the result
is that domain.
... | python | def infer_domain(terms):
"""
Infer the domain from a collection of terms.
The algorithm for inferring domains is as follows:
- If all input terms have a domain of GENERIC, the result is GENERIC.
- If there is exactly one non-generic domain in the input terms, the result
is that domain.
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26,025 | quantopian/zipline | zipline/pipeline/domain.py | IDomain.roll_forward | def roll_forward(self, dt):
"""
Given a date, align it to the calendar of the pipeline's domain.
Parameters
----------
dt : pd.Timestamp
Returns
-------
pd.Timestamp
"""
dt = pd.Timestamp(dt, tz='UTC')
trading_days = self.all_ses... | python | def roll_forward(self, dt):
"""
Given a date, align it to the calendar of the pipeline's domain.
Parameters
----------
dt : pd.Timestamp
Returns
-------
pd.Timestamp
"""
dt = pd.Timestamp(dt, tz='UTC')
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26,026 | quantopian/zipline | zipline/data/hdf5_daily_bars.py | days_and_sids_for_frames | def days_and_sids_for_frames(frames):
"""
Returns the date index and sid columns shared by a list of dataframes,
ensuring they all match.
Parameters
----------
frames : list[pd.DataFrame]
A list of dataframes indexed by day, with a column per sid.
Returns
-------
days : np.... | python | def days_and_sids_for_frames(frames):
"""
Returns the date index and sid columns shared by a list of dataframes,
ensuring they all match.
Parameters
----------
frames : list[pd.DataFrame]
A list of dataframes indexed by day, with a column per sid.
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-------
days : np.... | [
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26,027 | quantopian/zipline | zipline/data/hdf5_daily_bars.py | HDF5DailyBarWriter.write | def write(self, country_code, frames, scaling_factors=None):
"""Write the OHLCV data for one country to the HDF5 file.
Parameters
----------
country_code : str
The ISO 3166 alpha-2 country code for this country.
frames : dict[str, pd.DataFrame]
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"""Write the OHLCV data for one country to the HDF5 file.
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----------
country_code : str
The ISO 3166 alpha-2 country code for this country.
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26,028 | quantopian/zipline | zipline/data/hdf5_daily_bars.py | HDF5DailyBarReader.from_file | def from_file(cls, h5_file, country_code):
"""
Construct from an h5py.File and a country code.
Parameters
----------
h5_file : h5py.File
An HDF5 daily pricing file.
country_code : str
The ISO 3166 alpha-2 country code for the country to read.
... | python | def from_file(cls, h5_file, country_code):
"""
Construct from an h5py.File and a country code.
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----------
h5_file : h5py.File
An HDF5 daily pricing file.
country_code : str
The ISO 3166 alpha-2 country code for the country to read.
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26,029 | quantopian/zipline | zipline/data/hdf5_daily_bars.py | HDF5DailyBarReader.from_path | def from_path(cls, path, country_code):
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Construct from a file path and a country code.
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path : str
The path to an HDF5 daily pricing file.
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The ISO 3166 alpha-2 country code for the country to read.
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"""
Construct from a file path and a country code.
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path : str
The path to an HDF5 daily pricing file.
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The ISO 3166 alpha-2 country code for the country to read.
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26,030 | quantopian/zipline | zipline/data/hdf5_daily_bars.py | HDF5DailyBarReader._make_sid_selector | def _make_sid_selector(self, assets):
"""
Build an indexer mapping ``self.sids`` to ``assets``.
Parameters
----------
assets : list[int]
List of assets requested by a caller of ``load_raw_arrays``.
Returns
-------
index : np.array[int64]
... | python | def _make_sid_selector(self, assets):
"""
Build an indexer mapping ``self.sids`` to ``assets``.
Parameters
----------
assets : list[int]
List of assets requested by a caller of ``load_raw_arrays``.
Returns
-------
index : np.array[int64]
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26,031 | quantopian/zipline | zipline/data/hdf5_daily_bars.py | HDF5DailyBarReader._validate_assets | def _validate_assets(self, assets):
"""Validate that asset identifiers are contained in the daily bars.
Parameters
----------
assets : array-like[int]
The asset identifiers to validate.
Raises
------
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"""Validate that asset identifiers are contained in the daily bars.
Parameters
----------
assets : array-like[int]
The asset identifiers to validate.
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26,032 | quantopian/zipline | zipline/data/hdf5_daily_bars.py | MultiCountryDailyBarReader.from_file | def from_file(cls, h5_file):
"""
Construct from an h5py.File.
Parameters
----------
h5_file : h5py.File
An HDF5 daily pricing file.
"""
return cls({
country: HDF5DailyBarReader.from_file(h5_file, country)
for country in h5_file... | python | def from_file(cls, h5_file):
"""
Construct from an h5py.File.
Parameters
----------
h5_file : h5py.File
An HDF5 daily pricing file.
"""
return cls({
country: HDF5DailyBarReader.from_file(h5_file, country)
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26,033 | quantopian/zipline | zipline/assets/asset_writer.py | _normalize_index_columns_in_place | def _normalize_index_columns_in_place(equities,
equity_supplementary_mappings,
futures,
exchanges,
root_symbols):
"""
Update dataframes in place to set indentif... | python | def _normalize_index_columns_in_place(equities,
equity_supplementary_mappings,
futures,
exchanges,
root_symbols):
"""
Update dataframes in place to set indentif... | [
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26,034 | quantopian/zipline | zipline/assets/asset_writer.py | split_delimited_symbol | def split_delimited_symbol(symbol):
"""
Takes in a symbol that may be delimited and splits it in to a company
symbol and share class symbol. Also returns the fuzzy symbol, which is the
symbol without any fuzzy characters at all.
Parameters
----------
symbol : str
The possibly-delimi... | python | def split_delimited_symbol(symbol):
"""
Takes in a symbol that may be delimited and splits it in to a company
symbol and share class symbol. Also returns the fuzzy symbol, which is the
symbol without any fuzzy characters at all.
Parameters
----------
symbol : str
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26,035 | quantopian/zipline | zipline/assets/asset_writer.py | _generate_output_dataframe | def _generate_output_dataframe(data_subset, defaults):
"""
Generates an output dataframe from the given subset of user-provided
data, the given column names, and the given default values.
Parameters
----------
data_subset : DataFrame
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... | python | def _generate_output_dataframe(data_subset, defaults):
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Generates an output dataframe from the given subset of user-provided
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26,036 | quantopian/zipline | zipline/assets/asset_writer.py | _check_symbol_mappings | def _check_symbol_mappings(df, exchanges, asset_exchange):
"""Check that there are no cases where multiple symbols resolve to the same
asset at the same time in the same country.
Parameters
----------
df : pd.DataFrame
The equity symbol mappings table.
exchanges : pd.DataFrame
T... | python | def _check_symbol_mappings(df, exchanges, asset_exchange):
"""Check that there are no cases where multiple symbols resolve to the same
asset at the same time in the same country.
Parameters
----------
df : pd.DataFrame
The equity symbol mappings table.
exchanges : pd.DataFrame
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26,037 | quantopian/zipline | zipline/assets/asset_writer.py | _dt_to_epoch_ns | def _dt_to_epoch_ns(dt_series):
"""Convert a timeseries into an Int64Index of nanoseconds since the epoch.
Parameters
----------
dt_series : pd.Series
The timeseries to convert.
Returns
-------
idx : pd.Int64Index
The index converted to nanoseconds since the epoch.
"""
... | python | def _dt_to_epoch_ns(dt_series):
"""Convert a timeseries into an Int64Index of nanoseconds since the epoch.
Parameters
----------
dt_series : pd.Series
The timeseries to convert.
Returns
-------
idx : pd.Int64Index
The index converted to nanoseconds since the epoch.
"""
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26,038 | quantopian/zipline | zipline/assets/asset_writer.py | check_version_info | def check_version_info(conn, version_table, expected_version):
"""
Checks for a version value in the version table.
Parameters
----------
conn : sa.Connection
The connection to use to perform the check.
version_table : sa.Table
The version table of the asset database
expecte... | python | def check_version_info(conn, version_table, expected_version):
"""
Checks for a version value in the version table.
Parameters
----------
conn : sa.Connection
The connection to use to perform the check.
version_table : sa.Table
The version table of the asset database
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26,039 | quantopian/zipline | zipline/assets/asset_writer.py | write_version_info | def write_version_info(conn, version_table, version_value):
"""
Inserts the version value in to the version table.
Parameters
----------
conn : sa.Connection
The connection to use to execute the insert.
version_table : sa.Table
The version table of the asset database
version... | python | def write_version_info(conn, version_table, version_value):
"""
Inserts the version value in to the version table.
Parameters
----------
conn : sa.Connection
The connection to use to execute the insert.
version_table : sa.Table
The version table of the asset database
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26,040 | quantopian/zipline | zipline/assets/asset_writer.py | AssetDBWriter.write_direct | def write_direct(self,
equities=None,
equity_symbol_mappings=None,
equity_supplementary_mappings=None,
futures=None,
exchanges=None,
root_symbols=None,
chunk_size=DEFAULT_CH... | python | def write_direct(self,
equities=None,
equity_symbol_mappings=None,
equity_supplementary_mappings=None,
futures=None,
exchanges=None,
root_symbols=None,
chunk_size=DEFAULT_CH... | [
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26,041 | quantopian/zipline | zipline/assets/asset_writer.py | AssetDBWriter.write | def write(self,
equities=None,
futures=None,
exchanges=None,
root_symbols=None,
equity_supplementary_mappings=None,
chunk_size=DEFAULT_CHUNK_SIZE):
"""Write asset metadata to a sqlite database.
Parameters
------... | python | def write(self,
equities=None,
futures=None,
exchanges=None,
root_symbols=None,
equity_supplementary_mappings=None,
chunk_size=DEFAULT_CHUNK_SIZE):
"""Write asset metadata to a sqlite database.
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26,042 | quantopian/zipline | zipline/assets/asset_writer.py | AssetDBWriter._all_tables_present | def _all_tables_present(self, txn):
"""
Checks if any tables are present in the current assets database.
Parameters
----------
txn : Transaction
The open transaction to check in.
Returns
-------
has_tables : bool
True if any table... | python | def _all_tables_present(self, txn):
"""
Checks if any tables are present in the current assets database.
Parameters
----------
txn : Transaction
The open transaction to check in.
Returns
-------
has_tables : bool
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26,043 | quantopian/zipline | zipline/assets/asset_writer.py | AssetDBWriter.init_db | def init_db(self, txn=None):
"""Connect to database and create tables.
Parameters
----------
txn : sa.engine.Connection, optional
The transaction to execute in. If this is not provided, a new
transaction will be started with the engine provided.
Returns
... | python | def init_db(self, txn=None):
"""Connect to database and create tables.
Parameters
----------
txn : sa.engine.Connection, optional
The transaction to execute in. If this is not provided, a new
transaction will be started with the engine provided.
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26,044 | quantopian/zipline | zipline/pipeline/loaders/blaze/utils.py | load_raw_data | def load_raw_data(assets,
data_query_cutoff_times,
expr,
odo_kwargs,
checkpoints=None):
"""
Given an expression representing data to load, perform normalization and
forward-filling and return the data, materialized. Only accepts data wi... | python | def load_raw_data(assets,
data_query_cutoff_times,
expr,
odo_kwargs,
checkpoints=None):
"""
Given an expression representing data to load, perform normalization and
forward-filling and return the data, materialized. Only accepts data wi... | [
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26,045 | quantopian/zipline | zipline/utils/range.py | from_tuple | 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... | python | 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.
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26,046 | quantopian/zipline | zipline/utils/range.py | maybe_from_tuple | 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
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Parameters
----------
tup_or_range... | python | def maybe_from_tuple(tup_or_range):
"""Convert a tuple into a range but pass ranges through silently.
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be accessed with `.start`, `.stop` or so that containment checks are
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26,047 | quantopian/zipline | zipline/utils/range.py | _check_steps | 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:
... | python | 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:
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26,048 | quantopian/zipline | zipline/utils/range.py | overlap | 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 != ... | python | 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.
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26,049 | quantopian/zipline | zipline/utils/range.py | merge | 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)) | python | 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)) | [
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26,050 | quantopian/zipline | zipline/utils/range.py | _combine | def _combine(n, rs):
"""helper for ``_group_ranges``
"""
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return
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"""helper for ``_group_ranges``
"""
try:
r, rs = peek(rs)
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yield n
return
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26,051 | quantopian/zipline | zipline/utils/range.py | intersecting_ranges | 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... | python | def intersecting_ranges(ranges):
"""Return any ranges that intersect.
Parameters
----------
ranges : iterable[ranges]
A sequence of ranges to check for intersections.
Returns
-------
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26,052 | quantopian/zipline | zipline/data/loader.py | get_data_filepath | def get_data_filepath(name, environ=None):
"""
Returns a handle to data file.
Creates containing directory, if needed.
"""
dr = data_root(environ)
if not os.path.exists(dr):
os.makedirs(dr)
return os.path.join(dr, name) | python | def get_data_filepath(name, environ=None):
"""
Returns a handle to data file.
Creates containing directory, if needed.
"""
dr = data_root(environ)
if not os.path.exists(dr):
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26,053 | quantopian/zipline | zipline/data/loader.py | has_data_for_dates | def has_data_for_dates(series_or_df, first_date, last_date):
"""
Does `series_or_df` have data on or before first_date and on or after
last_date?
"""
dts = series_or_df.index
if not isinstance(dts, pd.DatetimeIndex):
raise TypeError("Expected a DatetimeIndex, but got %s." % type(dts))
... | python | def has_data_for_dates(series_or_df, first_date, last_date):
"""
Does `series_or_df` have data on or before first_date and on or after
last_date?
"""
dts = series_or_df.index
if not isinstance(dts, pd.DatetimeIndex):
raise TypeError("Expected a DatetimeIndex, but got %s." % type(dts))
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26,054 | quantopian/zipline | zipline/data/loader.py | load_market_data | def load_market_data(trading_day=None, trading_days=None, bm_symbol='SPY',
environ=None):
"""
Load benchmark returns and treasury yield curves for the given calendar and
benchmark symbol.
Benchmarks are downloaded as a Series from IEX Trading. Treasury curves
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"""
Load benchmark returns and treasury yield curves for the given calendar and
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Benchmarks are downloaded as a Series from IEX Trading. Treasury curves
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26,055 | quantopian/zipline | zipline/data/loader.py | ensure_benchmark_data | def ensure_benchmark_data(symbol, first_date, last_date, now, trading_day,
environ=None):
"""
Ensure we have benchmark data for `symbol` from `first_date` to `last_date`
Parameters
----------
symbol : str
The symbol for the benchmark to load.
first_date : pd.Ti... | python | def ensure_benchmark_data(symbol, first_date, last_date, now, trading_day,
environ=None):
"""
Ensure we have benchmark data for `symbol` from `first_date` to `last_date`
Parameters
----------
symbol : str
The symbol for the benchmark to load.
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last_date : pd.Timestamp
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26,056 | quantopian/zipline | zipline/data/loader.py | ensure_treasury_data | def ensure_treasury_data(symbol, first_date, last_date, now, environ=None):
"""
Ensure we have treasury data from treasury module associated with
`symbol`.
Parameters
----------
symbol : str
Benchmark symbol for which we're loading associated treasury curves.
first_date : pd.Timesta... | python | def ensure_treasury_data(symbol, first_date, last_date, now, environ=None):
"""
Ensure we have treasury data from treasury module associated with
`symbol`.
Parameters
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symbol : str
Benchmark symbol for which we're loading associated treasury curves.
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26,057 | quantopian/zipline | zipline/pipeline/graph.py | maybe_specialize | def maybe_specialize(term, domain):
"""Specialize a term if it's loadable.
"""
if isinstance(term, LoadableTerm):
return term.specialize(domain)
return term | python | def maybe_specialize(term, domain):
"""Specialize a term if it's loadable.
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26,058 | quantopian/zipline | zipline/pipeline/graph.py | TermGraph._add_to_graph | def _add_to_graph(self, term, parents):
"""
Add a term and all its children to ``graph``.
``parents`` is the set of all the parents of ``term` that we've added
so far. It is only used to detect dependency cycles.
"""
if self._frozen:
raise ValueError(
... | python | def _add_to_graph(self, term, parents):
"""
Add a term and all its children to ``graph``.
``parents`` is the set of all the parents of ``term` that we've added
so far. It is only used to detect dependency cycles.
"""
if self._frozen:
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26,059 | quantopian/zipline | zipline/pipeline/graph.py | TermGraph.execution_order | def execution_order(self, refcounts):
"""
Return a topologically-sorted iterator over the terms in ``self`` which
need to be computed.
"""
return iter(nx.topological_sort(
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"""
Return a topologically-sorted iterator over the terms in ``self`` which
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26,060 | quantopian/zipline | zipline/pipeline/graph.py | TermGraph.initial_refcounts | def initial_refcounts(self, initial_terms):
"""
Calculate initial refcounts for execution of this graph.
Parameters
----------
initial_terms : iterable[Term]
An iterable of terms that were pre-computed before graph execution.
Each node starts with a refcount... | python | def initial_refcounts(self, initial_terms):
"""
Calculate initial refcounts for execution of this graph.
Parameters
----------
initial_terms : iterable[Term]
An iterable of terms that were pre-computed before graph execution.
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26,061 | quantopian/zipline | zipline/pipeline/graph.py | TermGraph._decref_dependencies_recursive | def _decref_dependencies_recursive(self, term, refcounts, garbage):
"""
Decrement terms recursively.
Notes
-----
This should only be used to build the initial workspace, after that we
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:meth:`~zipline.pipeline.graph.TermGraph.decref_dependencies`
... | python | def _decref_dependencies_recursive(self, term, refcounts, garbage):
"""
Decrement terms recursively.
Notes
-----
This should only be used to build the initial workspace, after that we
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:meth:`~zipline.pipeline.graph.TermGraph.decref_dependencies`
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26,062 | quantopian/zipline | zipline/pipeline/graph.py | TermGraph.decref_dependencies | def decref_dependencies(self, term, refcounts):
"""
Decrement in-edges for ``term`` after computation.
Parameters
----------
term : zipline.pipeline.Term
The term whose parents should be decref'ed.
refcounts : dict[Term -> int]
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"""
Decrement in-edges for ``term`` after computation.
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term : zipline.pipeline.Term
The term whose parents should be decref'ed.
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26,063 | quantopian/zipline | zipline/pipeline/graph.py | ExecutionPlan._ensure_extra_rows | def _ensure_extra_rows(self, term, N):
"""
Ensure that we're going to compute at least N extra rows of `term`.
"""
attrs = self.graph.node[term]
attrs['extra_rows'] = max(N, attrs.get('extra_rows', 0)) | python | def _ensure_extra_rows(self, term, N):
"""
Ensure that we're going to compute at least N extra rows of `term`.
"""
attrs = self.graph.node[term]
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26,064 | quantopian/zipline | zipline/pipeline/graph.py | ExecutionPlan.mask_and_dates_for_term | def mask_and_dates_for_term(self,
term,
root_mask_term,
workspace,
all_dates):
"""
Load mask and mask row labels for term.
Parameters
----------
term :... | python | def mask_and_dates_for_term(self,
term,
root_mask_term,
workspace,
all_dates):
"""
Load mask and mask row labels for term.
Parameters
----------
term :... | [
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26,065 | quantopian/zipline | zipline/pipeline/graph.py | ExecutionPlan._assert_all_loadable_terms_specialized_to | def _assert_all_loadable_terms_specialized_to(self, domain):
"""Make sure that we've specialized all loadable terms in the graph.
"""
for term in self.graph.node:
if isinstance(term, LoadableTerm):
assert term.domain is domain | python | def _assert_all_loadable_terms_specialized_to(self, domain):
"""Make sure that we've specialized all loadable terms in the graph.
"""
for term in self.graph.node:
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26,066 | quantopian/zipline | setup.py | window_specialization | def window_specialization(typename):
"""Make an extension for an AdjustedArrayWindow specialization."""
return Extension(
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['zipline/lib/_{name}window.pyx'.format(name=typename)],
depends=['zipline/lib/_windowtemplate.pxi'],
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"""Make an extension for an AdjustedArrayWindow specialization."""
return Extension(
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26,067 | quantopian/zipline | setup.py | read_requirements | def read_requirements(path,
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conda_format=False,
filter_names=None):
"""
Read a requirements.txt file, expressed as a path relative to Zipline root.
Returns requirements with the pinned versions as lower bounds
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Read a requirements.txt file, expressed as a path relative to Zipline root.
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26,068 | quantopian/zipline | zipline/utils/events.py | ensure_utc | def ensure_utc(time, tz='UTC'):
"""
Normalize a time. If the time is tz-naive, assume it is UTC.
"""
if not time.tzinfo:
time = time.replace(tzinfo=pytz.timezone(tz))
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"""
Normalize a time. If the time is tz-naive, assume it is UTC.
"""
if not time.tzinfo:
time = time.replace(tzinfo=pytz.timezone(tz))
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26,069 | quantopian/zipline | zipline/utils/events.py | _build_offset | def _build_offset(offset, kwargs, default):
"""
Builds the offset argument for event rules.
"""
if offset is None:
if not kwargs:
return default # use the default.
else:
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"""
Builds the offset argument for event rules.
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26,070 | quantopian/zipline | zipline/utils/events.py | _build_date | 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)
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Builds the date argument for event rules.
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26,071 | quantopian/zipline | zipline/utils/events.py | _build_time | 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(... | python | 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(... | [
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26,072 | quantopian/zipline | zipline/utils/events.py | lossless_float_to_int | def lossless_float_to_int(funcname, func, argname, arg):
"""
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Receipt of non-integral floats raises a TypeError.
"""
if not isinstance(arg, float):
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arg_as_int = int(arg)
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warnings.warn(
... | python | def lossless_float_to_int(funcname, func, argname, arg):
"""
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26,073 | quantopian/zipline | zipline/utils/events.py | EventManager.add_event | 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) | python | def add_event(self, event, prepend=False):
"""
Adds an event to the manager.
"""
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self._events.insert(0, event)
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26,074 | quantopian/zipline | zipline/utils/events.py | Event.handle_data | def handle_data(self, context, data, dt):
"""
Calls the callable only when the rule is triggered.
"""
if self.rule.should_trigger(dt):
self.callback(context, data) | python | def handle_data(self, context, data, dt):
"""
Calls the callable only when the rule is triggered.
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26,075 | quantopian/zipline | zipline/utils/events.py | ComposedRule.should_trigger | def should_trigger(self, dt):
"""
Composes the two rules with a lazy composer.
"""
return self.composer(
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self.second.should_trigger,
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26,076 | quantopian/zipline | zipline/data/bcolz_daily_bars.py | winsorise_uint32 | def winsorise_uint32(df, invalid_data_behavior, column, *columns):
"""Drops any record where a value would not fit into a uint32.
Parameters
----------
df : pd.DataFrame
The dataframe to winsorise.
invalid_data_behavior : {'warn', 'raise', 'ignore'}
What to do when data is outside t... | python | def winsorise_uint32(df, invalid_data_behavior, column, *columns):
"""Drops any record where a value would not fit into a uint32.
Parameters
----------
df : pd.DataFrame
The dataframe to winsorise.
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26,077 | quantopian/zipline | zipline/data/bcolz_daily_bars.py | BcolzDailyBarWriter.write_csvs | def write_csvs(self,
asset_map,
show_progress=False,
invalid_data_behavior='warn'):
"""Read CSVs as DataFrames from our asset map.
Parameters
----------
asset_map : dict[int -> str]
A mapping from asset id to file path... | python | def write_csvs(self,
asset_map,
show_progress=False,
invalid_data_behavior='warn'):
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Parameters
----------
asset_map : dict[int -> str]
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26,078 | quantopian/zipline | zipline/data/bcolz_daily_bars.py | BcolzDailyBarReader._compute_slices | def _compute_slices(self, start_idx, end_idx, assets):
"""
Compute the raw row indices to load for each asset on a query for the
given dates after applying a shift.
Parameters
----------
start_idx : int
Index of first date for which we want data.
end_... | python | def _compute_slices(self, start_idx, end_idx, assets):
"""
Compute the raw row indices to load for each asset on a query for the
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Parameters
----------
start_idx : int
Index of first date for which we want data.
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26,079 | quantopian/zipline | zipline/data/bcolz_daily_bars.py | BcolzDailyBarReader._spot_col | def _spot_col(self, colname):
"""
Get the colname from daily_bar_table and read all of it into memory,
caching the result.
Parameters
----------
colname : string
A name of a OHLCV carray in the daily_bar_table
Returns
-------
array (u... | python | def _spot_col(self, colname):
"""
Get the colname from daily_bar_table and read all of it into memory,
caching the result.
Parameters
----------
colname : string
A name of a OHLCV carray in the daily_bar_table
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-------
array (u... | [
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26,080 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.init_engine | def init_engine(self, get_loader):
"""
Construct and store a PipelineEngine from loader.
If get_loader is None, constructs an ExplodingPipelineEngine
"""
if get_loader is not None:
self.engine = SimplePipelineEngine(
get_loader,
self.a... | python | def init_engine(self, get_loader):
"""
Construct and store a PipelineEngine from loader.
If get_loader is None, constructs an ExplodingPipelineEngine
"""
if get_loader is not None:
self.engine = SimplePipelineEngine(
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26,081 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.initialize | def initialize(self, *args, **kwargs):
"""
Call self._initialize with `self` made available to Zipline API
functions.
"""
with ZiplineAPI(self):
self._initialize(self, *args, **kwargs) | python | def initialize(self, *args, **kwargs):
"""
Call self._initialize with `self` made available to Zipline API
functions.
"""
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26,082 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm._create_clock | def _create_clock(self):
"""
If the clock property is not set, then create one based on frequency.
"""
trading_o_and_c = self.trading_calendar.schedule.ix[
self.sim_params.sessions]
market_closes = trading_o_and_c['market_close']
minutely_emission = False
... | python | def _create_clock(self):
"""
If the clock property is not set, then create one based on frequency.
"""
trading_o_and_c = self.trading_calendar.schedule.ix[
self.sim_params.sessions]
market_closes = trading_o_and_c['market_close']
minutely_emission = False
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26,083 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.compute_eager_pipelines | def compute_eager_pipelines(self):
"""
Compute any pipelines attached with eager=True.
"""
for name, pipe in self._pipelines.items():
if pipe.eager:
self.pipeline_output(name) | python | def compute_eager_pipelines(self):
"""
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"""
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26,084 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.run | def run(self, data_portal=None):
"""Run the algorithm.
"""
# HACK: I don't think we really want to support passing a data portal
# this late in the long term, but this is needed for now for backwards
# compat downstream.
if data_portal is not None:
self.data_p... | python | def run(self, data_portal=None):
"""Run the algorithm.
"""
# HACK: I don't think we really want to support passing a data portal
# this late in the long term, but this is needed for now for backwards
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26,085 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.calculate_capital_changes | def calculate_capital_changes(self, dt, emission_rate, is_interday,
portfolio_value_adjustment=0.0):
"""
If there is a capital change for a given dt, this means the the change
occurs before `handle_data` on the given dt. In the case of the
change being a... | python | def calculate_capital_changes(self, dt, emission_rate, is_interday,
portfolio_value_adjustment=0.0):
"""
If there is a capital change for a given dt, this means the the change
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26,086 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.get_environment | def get_environment(self, field='platform'):
"""Query the execution environment.
Parameters
----------
field : {'platform', 'arena', 'data_frequency',
'start', 'end', 'capital_base', 'platform', '*'}
The field to query. The options have the following meaning... | python | def get_environment(self, field='platform'):
"""Query the execution environment.
Parameters
----------
field : {'platform', 'arena', 'data_frequency',
'start', 'end', 'capital_base', 'platform', '*'}
The field to query. The options have the following meaning... | [
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Parameters
----------
field : {'platform', 'arena', 'data_frequency',
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The field to query. The options have the following meanings:
arena : str
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26,087 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.fetch_csv | def fetch_csv(self,
url,
pre_func=None,
post_func=None,
date_column='date',
date_format=None,
timezone=pytz.utc.zone,
symbol=None,
mask=True,
symbol_column=No... | python | def fetch_csv(self,
url,
pre_func=None,
post_func=None,
date_column='date',
date_format=None,
timezone=pytz.utc.zone,
symbol=None,
mask=True,
symbol_column=No... | [
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url : str
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pre_func : callable[pd.DataFrame -> pd.DataFrame], optional
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26,088 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.add_event | def add_event(self, rule, callback):
"""Adds an event to the algorithm's EventManager.
Parameters
----------
rule : EventRule
The rule for when the callback should be triggered.
callback : callable[(context, data) -> None]
The function to execute when the... | python | def add_event(self, rule, callback):
"""Adds an event to the algorithm's EventManager.
Parameters
----------
rule : EventRule
The rule for when the callback should be triggered.
callback : callable[(context, data) -> None]
The function to execute when the... | [
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The rule for when the callback should be triggered.
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26,089 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.schedule_function | def schedule_function(self,
func,
date_rule=None,
time_rule=None,
half_days=True,
calendar=None):
"""Schedules a function to be called according to some timed rules.
Paramet... | python | def schedule_function(self,
func,
date_rule=None,
time_rule=None,
half_days=True,
calendar=None):
"""Schedules a function to be called according to some timed rules.
Paramet... | [
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26,090 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.continuous_future | def continuous_future(self,
root_symbol_str,
offset=0,
roll='volume',
adjustment='mul'):
"""Create a specifier for a continuous contract.
Parameters
----------
root_symbol_str : str
... | python | def continuous_future(self,
root_symbol_str,
offset=0,
roll='volume',
adjustment='mul'):
"""Create a specifier for a continuous contract.
Parameters
----------
root_symbol_str : str
... | [
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The root symbol for the future chain.
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The distance from the primary contract. Default is 0.
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26,091 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.symbol | def symbol(self, symbol_str, country_code=None):
"""Lookup an Equity by its ticker symbol.
Parameters
----------
symbol_str : str
The ticker symbol for the equity to lookup.
country_code : str or None, optional
A country to limit symbol searches to.
... | python | def symbol(self, symbol_str, country_code=None):
"""Lookup an Equity by its ticker symbol.
Parameters
----------
symbol_str : str
The ticker symbol for the equity to lookup.
country_code : str or None, optional
A country to limit symbol searches to.
... | [
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country_code : str or None, optional
A country to limit symbol searches to.
Returns
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26,092 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.symbols | def symbols(self, *args, **kwargs):
"""Lookup multuple Equities as a list.
Parameters
----------
*args : iterable[str]
The ticker symbols to lookup.
country_code : str or None, optional
A country to limit symbol searches to.
Returns
---... | python | def symbols(self, *args, **kwargs):
"""Lookup multuple Equities as a list.
Parameters
----------
*args : iterable[str]
The ticker symbols to lookup.
country_code : str or None, optional
A country to limit symbol searches to.
Returns
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Returns
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26,093 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.validate_order_params | def validate_order_params(self,
asset,
amount,
limit_price,
stop_price,
style):
"""
Helper method for validating parameters to the order API function.
... | python | def validate_order_params(self,
asset,
amount,
limit_price,
stop_price,
style):
"""
Helper method for validating parameters to the order API function.
... | [
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26,094 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.__convert_order_params_for_blotter | def __convert_order_params_for_blotter(asset,
limit_price,
stop_price,
style):
"""
Helper method for converting deprecated limit_price and stop_price
arguments into Ex... | python | def __convert_order_params_for_blotter(asset,
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stop_price,
style):
"""
Helper method for converting deprecated limit_price and stop_price
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26,095 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.order_value | def order_value(self,
asset,
value,
limit_price=None,
stop_price=None,
style=None):
"""Place an order by desired value rather than desired number of
shares.
Parameters
----------
... | python | def order_value(self,
asset,
value,
limit_price=None,
stop_price=None,
style=None):
"""Place an order by desired value rather than desired number of
shares.
Parameters
----------
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The asset that this order is for.
value : float
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26,096 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm._sync_last_sale_prices | def _sync_last_sale_prices(self, dt=None):
"""Sync the last sale prices on the metrics tracker to a given
datetime.
Parameters
----------
dt : datetime
The time to sync the prices to.
Notes
-----
This call is cached by the datetime. Repeated ... | python | def _sync_last_sale_prices(self, dt=None):
"""Sync the last sale prices on the metrics tracker to a given
datetime.
Parameters
----------
dt : datetime
The time to sync the prices to.
Notes
-----
This call is cached by the datetime. Repeated ... | [
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26,097 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.on_dt_changed | def on_dt_changed(self, dt):
"""
Callback triggered by the simulation loop whenever the current dt
changes.
Any logic that should happen exactly once at the start of each datetime
group should happen here.
"""
self.datetime = dt
self.blotter.set_date(dt) | python | def on_dt_changed(self, dt):
"""
Callback triggered by the simulation loop whenever the current dt
changes.
Any logic that should happen exactly once at the start of each datetime
group should happen here.
"""
self.datetime = dt
self.blotter.set_date(dt) | [
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26,098 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.get_datetime | def get_datetime(self, tz=None):
"""
Returns the current simulation datetime.
Parameters
----------
tz : tzinfo or str, optional
The timezone to return the datetime in. This defaults to utc.
Returns
-------
dt : datetime
The curre... | python | def get_datetime(self, tz=None):
"""
Returns the current simulation datetime.
Parameters
----------
tz : tzinfo or str, optional
The timezone to return the datetime in. This defaults to utc.
Returns
-------
dt : datetime
The curre... | [
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tz : tzinfo or str, optional
The timezone to return the datetime in. This defaults to utc.
Returns
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dt : datetime
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26,099 | quantopian/zipline | zipline/algorithm.py | TradingAlgorithm.set_slippage | def set_slippage(self, us_equities=None, us_futures=None):
"""Set the slippage models for the simulation.
Parameters
----------
us_equities : EquitySlippageModel
The slippage model to use for trading US equities.
us_futures : FutureSlippageModel
The slipp... | python | def set_slippage(self, us_equities=None, us_futures=None):
"""Set the slippage models for the simulation.
Parameters
----------
us_equities : EquitySlippageModel
The slippage model to use for trading US equities.
us_futures : FutureSlippageModel
The slipp... | [
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Parameters
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us_equities : EquitySlippageModel
The slippage model to use for trading US equities.
us_futures : FutureSlippageModel
The slippage model to use for trading US futures.
See Also
---... | [
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