INSTRUCTION stringlengths 1 46.3k | RESPONSE stringlengths 75 80.2k |
|---|---|
Read data for the named symbol. Returns a VersionedItem object with
a data and metdata element (as passed into write).
Parameters
----------
symbol : `str`
symbol name for the item
date_range : `date.DateRange`
Returns ticks in the specified DateRange
... | def read(self, symbol, date_range=None, columns=None, include_images=False, allow_secondary=None,
_target_tick_count=0):
"""
Read data for the named symbol. Returns a VersionedItem object with
a data and metdata element (as passed into write).
Parameters
----------... |
Writes a list of market data events.
Parameters
----------
symbol : `str`
symbol name for the item
data : list of dicts or a pandas.DataFrame
List of ticks to store to the tick-store.
if a list of dicts, each dict must contain a 'index' datetime
... | def write(self, symbol, data, initial_image=None, metadata=None):
"""
Writes a list of market data events.
Parameters
----------
symbol : `str`
symbol name for the item
data : list of dicts or a pandas.DataFrame
List of ticks to store to the tick-... |
Represent dtypes without byte order, as earlier Java tickstore code doesn't support explicit byte order. | def _str_dtype(dtype):
"""
Represent dtypes without byte order, as earlier Java tickstore code doesn't support explicit byte order.
"""
assert dtype.byteorder != '>'
if dtype.kind == 'i':
assert dtype.itemsize == 8
return 'int64'
elif dtype.kind ==... |
Return the maximum datetime stored for a particular symbol
Parameters
----------
symbol : `str`
symbol name for the item | def max_date(self, symbol):
"""
Return the maximum datetime stored for a particular symbol
Parameters
----------
symbol : `str`
symbol name for the item
"""
res = self._collection.find_one({SYMBOL: symbol}, projection={ID: 0, END: 1},
... |
Return the minimum datetime stored for a particular symbol
Parameters
----------
symbol : `str`
symbol name for the item | def min_date(self, symbol):
"""
Return the minimum datetime stored for a particular symbol
Parameters
----------
symbol : `str`
symbol name for the item
"""
res = self._collection.find_one({SYMBOL: symbol}, projection={ID: 0, START: 1},
... |
pass thru chunker of the dataframe/series
returns
-------
('NA', 'NA', 'NA', dataframe/series) | def to_chunks(self, df, **kwargs):
"""
pass thru chunker of the dataframe/series
returns
-------
('NA', 'NA', 'NA', dataframe/series)
"""
if len(df) > 0:
yield b'NA', b'NA', b'NA', df |
Return True / False on authentication success.
PyMongo 2.6 changed the auth API to raise on Auth failure. | def authenticate(db, user, password):
"""
Return True / False on authentication success.
PyMongo 2.6 changed the auth API to raise on Auth failure.
"""
try:
logger.debug("Authenticating {} with {}".format(db, user))
return db.authenticate(user, password)
except OperationFailure ... |
Authentication hook to allow plugging in custom authentication credential providers | def get_auth(host, app_name, database_name):
"""
Authentication hook to allow plugging in custom authentication credential providers
"""
from .hooks import _get_auth_hook
return _get_auth_hook(host, app_name, database_name) |
Returns a mongo library for the given connection string
Parameters
---------
connection_string: `str`
Format must be one of the following:
library@trading for known mongo servers
library@hostname:port
Returns:
--------
Arctic library | def get_arctic_lib(connection_string, **kwargs):
"""
Returns a mongo library for the given connection string
Parameters
---------
connection_string: `str`
Format must be one of the following:
library@trading for known mongo servers
library@hostname:port
Returns:... |
Attempts to authenticate against the mongo instance.
Tries:
- Auth'ing against admin as 'admin' ; credentials: <host>/arctic/admin/admin
- Auth'ing against db_name (which may be None if auth'ing against admin above)
returns True if authentication succeeded. | def do_db_auth(host, connection, db_name):
"""
Attempts to authenticate against the mongo instance.
Tries:
- Auth'ing against admin as 'admin' ; credentials: <host>/arctic/admin/admin
- Auth'ing against db_name (which may be None if auth'ing against admin above)
returns True if authenticat... |
External exception logging hook. | def log_exception(fn_name, exception, retry_count, **kwargs):
"""
External exception logging hook.
"""
_log_exception_hook(fn_name, exception, retry_count, **kwargs) |
Dataframe group-by operation that supports aggregating by different methods on the index.
Parameters
----------
df: ``DataFrame``
Pandas dataframe with a MultiIndex
grouping_level: ``int`` or ``str`` or ``list`` of ``str``
Index level to group by. Defaults to 0.
aggregate_level: ``i... | def fancy_group_by(df, grouping_level=0, aggregate_level=1, method='last', max_=None, min_=None, within=None):
""" Dataframe group-by operation that supports aggregating by different methods on the index.
Parameters
----------
df: ``DataFrame``
Pandas dataframe with a MultiIndex
grouping_le... |
Common use case for selecting the latest rows from a bitemporal dataframe as-of a certain date.
Parameters
----------
df: ``pd.DataFrame``
Dataframe with a MultiIndex index
as_of: ``datetime``
Return a timeseries with values observed <= this as-of date. By default, the latest observed
... | def groupby_asof(df, as_of=None, dt_col='sample_dt', asof_col='observed_dt'):
''' Common use case for selecting the latest rows from a bitemporal dataframe as-of a certain date.
Parameters
----------
df: ``pd.DataFrame``
Dataframe with a MultiIndex index
as_of: ``datetime``
Return a... |
Return a new dataframe with a row inserted for a multi-index dataframe.
This will sort the rows according to the ordered multi-index levels. | def multi_index_insert_row(df, index_row, values_row):
""" Return a new dataframe with a row inserted for a multi-index dataframe.
This will sort the rows according to the ordered multi-index levels.
"""
row_index = pd.MultiIndex(levels=[[i] for i in index_row],
labels=... |
Insert some values into a bi-temporal dataframe.
This is like what would happen when we get a price correction. | def insert_at(df, sample_date, values):
""" Insert some values into a bi-temporal dataframe.
This is like what would happen when we get a price correction.
"""
observed_dt = dt(datetime.now())
return multi_index_insert_row(df, [sample_date, observed_dt], values) |
Register a Arctic Library Type handler | def register_library_type(name, type_):
"""
Register a Arctic Library Type handler
"""
if name in LIBRARY_TYPES:
raise ArcticException("Library %s already registered as %s" % (name, LIBRARY_TYPES[name]))
LIBRARY_TYPES[name] = type_ |
Returns
-------
List of Arctic library names from a cached collection (global per mongo cluster) in mongo.
Long term list_libraries should have a use_cached argument. | def _list_libraries_cached(self, newer_than_secs=-1):
"""
Returns
-------
List of Arctic library names from a cached collection (global per mongo cluster) in mongo.
Long term list_libraries should have a use_cached argument.
"""
_ = self._conn # Ensures the conne... |
Check whether a given library exists.
Parameters
----------
library : `str`
The name of the library. e.g. 'library' or 'user.library'
Returns
-------
`bool`
True if the library with the given name already exists, False otherwise | def library_exists(self, library):
"""
Check whether a given library exists.
Parameters
----------
library : `str`
The name of the library. e.g. 'library' or 'user.library'
Returns
-------
`bool`
True if the library with the given... |
Create an Arctic Library or a particular type.
Parameters
----------
library : `str`
The name of the library. e.g. 'library' or 'user.library'
lib_type : `str`
The type of the library. e.g. arctic.VERSION_STORE or arctic.TICK_STORE
Or any type regis... | def initialize_library(self, library, lib_type=VERSION_STORE, **kwargs):
"""
Create an Arctic Library or a particular type.
Parameters
----------
library : `str`
The name of the library. e.g. 'library' or 'user.library'
lib_type : `str`
The type ... |
Delete an Arctic Library, and all associated collections in the MongoDB.
Parameters
----------
library : `str`
The name of the library. e.g. 'library' or 'user.library' | def delete_library(self, library):
"""
Delete an Arctic Library, and all associated collections in the MongoDB.
Parameters
----------
library : `str`
The name of the library. e.g. 'library' or 'user.library'
"""
lib = ArcticLibraryBinding(self, librar... |
Return the library instance. Can generally use slicing to return the library:
arctic_store[library]
Parameters
----------
library : `str`
The name of the library. e.g. 'library' or 'user.library' | def get_library(self, library):
"""
Return the library instance. Can generally use slicing to return the library:
arctic_store[library]
Parameters
----------
library : `str`
The name of the library. e.g. 'library' or 'user.library'
"""
if... |
Renames a library
Parameters
----------
from_lib: str
The name of the library to be renamed
to_lib: str
The new name of the library | def rename_library(self, from_lib, to_lib):
"""
Renames a library
Parameters
----------
from_lib: str
The name of the library to be renamed
to_lib: str
The new name of the library
"""
to_colname = to_lib
if '.' in from_lib ... |
Returns the canonical (database_name, library) for the passed in
string 'library'. | def _parse_db_lib(cls, library):
"""
Returns the canonical (database_name, library) for the passed in
string 'library'.
"""
database_name = library.split('.', 2)
if len(database_name) == 2:
library = database_name[1]
if database_name[0].startswith(... |
Set a quota (in bytes) on this user library. The quota is 'best effort',
and should be set conservatively.
A quota of 0 is 'unlimited' | def set_quota(self, quota_bytes):
"""
Set a quota (in bytes) on this user library. The quota is 'best effort',
and should be set conservatively.
A quota of 0 is 'unlimited'
"""
self.set_library_metadata(ArcticLibraryBinding.QUOTA, quota_bytes)
self.quota = quota... |
Check whether the user is within quota. Should be called before
every write. Will raise() if the library has exceeded its allotted
quota. | def check_quota(self):
"""
Check whether the user is within quota. Should be called before
every write. Will raise() if the library has exceeded its allotted
quota.
"""
# Don't check on every write, that would be slow
if self.quota_countdown > 0:
sel... |
Checksum the passed in dictionary | def _checksum(self, fields, data):
"""
Checksum the passed in dictionary
"""
sha = hashlib.sha1()
for field in fields:
sha.update(field)
sha.update(data)
return Binary(sha.digest()) |
Delete all chunks for a symbol, or optionally, chunks within a range
Parameters
----------
symbol : str
symbol name for the item
chunk_range: range object
a date range to delete
audit: dict
dict to store in the audit log | def delete(self, symbol, chunk_range=None, audit=None):
"""
Delete all chunks for a symbol, or optionally, chunks within a range
Parameters
----------
symbol : str
symbol name for the item
chunk_range: range object
a date range to delete
a... |
Returns all symbols in the library
Parameters
----------
partial: None or str
if not none, use this string to do a partial match on symbol names
Returns
-------
list of str | def list_symbols(self, partial_match=None):
"""
Returns all symbols in the library
Parameters
----------
partial: None or str
if not none, use this string to do a partial match on symbol names
Returns
-------
list of str
"""
s... |
Rename a symbol
Parameters
----------
from_symbol: str
the existing symbol that will be renamed
to_symbol: str
the new symbol name
audit: dict
audit information | def rename(self, from_symbol, to_symbol, audit=None):
"""
Rename a symbol
Parameters
----------
from_symbol: str
the existing symbol that will be renamed
to_symbol: str
the new symbol name
audit: dict
audit information
... |
Reads data for a given symbol from the database.
Parameters
----------
symbol: str, or list of str
the symbol(s) to retrieve
chunk_range: object
corresponding range object for the specified chunker (for
DateChunker it is a DateRange object or a Dateti... | def read(self, symbol, chunk_range=None, filter_data=True, **kwargs):
"""
Reads data for a given symbol from the database.
Parameters
----------
symbol: str, or list of str
the symbol(s) to retrieve
chunk_range: object
corresponding range object f... |
Reads the audit log
Parameters
----------
symbol: str
optionally only retrieve specific symbol's audit information
Returns
-------
list of dicts | def read_audit_log(self, symbol=None):
"""
Reads the audit log
Parameters
----------
symbol: str
optionally only retrieve specific symbol's audit information
Returns
-------
list of dicts
"""
if symbol:
return [x f... |
Writes data from item to symbol in the database
Parameters
----------
symbol: str
the symbol that will be used to reference the written data
item: Dataframe or Series
the data to write the database
metadata: ?
optional per symbol metadata
... | def write(self, symbol, item, metadata=None, chunker=DateChunker(), audit=None, **kwargs):
"""
Writes data from item to symbol in the database
Parameters
----------
symbol: str
the symbol that will be used to reference the written data
item: Dataframe or Seri... |
helper method used by update and append since they very closely
resemble eachother. Really differ only by the combine method.
append will combine existing date with new data (within a chunk),
whereas update will replace existing data with new data (within a
chunk). | def __update(self, sym, item, metadata=None, combine_method=None, chunk_range=None, audit=None):
'''
helper method used by update and append since they very closely
resemble eachother. Really differ only by the combine method.
append will combine existing date with new data (within a chu... |
Appends data from item to symbol's data in the database.
Is not idempotent
Parameters
----------
symbol: str
the symbol for the given item in the DB
item: DataFrame or Series
the data to append
upsert:
write data if symbol does not ex... | def append(self, symbol, item, upsert=False, metadata=None, audit=None, **kwargs):
"""
Appends data from item to symbol's data in the database.
Is not idempotent
Parameters
----------
symbol: str
the symbol for the given item in the DB
item: DataFram... |
Overwrites data in DB with data in item for the given symbol.
Is idempotent
Parameters
----------
symbol: str
the symbol for the given item in the DB
item: DataFrame or Series
the data to update
metadata: ?
optional per symbol metadat... | def update(self, symbol, item, metadata=None, chunk_range=None, upsert=False, audit=None, **kwargs):
"""
Overwrites data in DB with data in item for the given symbol.
Is idempotent
Parameters
----------
symbol: str
the symbol for the given item in the DB
... |
Returns information about the symbol, in a dictionary
Parameters
----------
symbol: str
the symbol for the given item in the DB
Returns
-------
dictionary | def get_info(self, symbol):
"""
Returns information about the symbol, in a dictionary
Parameters
----------
symbol: str
the symbol for the given item in the DB
Returns
-------
dictionary
"""
sym = self._get_symbol_info(symbol)... |
Reads user defined metadata out for the given symbol
Parameters
----------
symbol: str
symbol for the given item in the DB
Returns
-------
? | def read_metadata(self, symbol):
'''
Reads user defined metadata out for the given symbol
Parameters
----------
symbol: str
symbol for the given item in the DB
Returns
-------
?
'''
sym = self._get_symbol_info(symbol)
... |
writes user defined metadata for the given symbol
Parameters
----------
symbol: str
symbol for the given item in the DB
metadata: ?
metadata to write | def write_metadata(self, symbol, metadata):
'''
writes user defined metadata for the given symbol
Parameters
----------
symbol: str
symbol for the given item in the DB
metadata: ?
metadata to write
'''
sym = self._get_symbol_info(s... |
Returns a generator of (Start, End) tuples for each chunk in the symbol
Parameters
----------
symbol: str
the symbol for the given item in the DB
chunk_range: None, or a range object
allows you to subset the chunks by range
reverse: boolean
re... | def get_chunk_ranges(self, symbol, chunk_range=None, reverse=False):
"""
Returns a generator of (Start, End) tuples for each chunk in the symbol
Parameters
----------
symbol: str
the symbol for the given item in the DB
chunk_range: None, or a range object
... |
Returns a generator that accesses each chunk in ascending order
Parameters
----------
symbol: str
the symbol for the given item in the DB
chunk_range: None, or a range object
allows you to subset the chunks by range
Returns
-------
genera... | def iterator(self, symbol, chunk_range=None):
"""
Returns a generator that accesses each chunk in ascending order
Parameters
----------
symbol: str
the symbol for the given item in the DB
chunk_range: None, or a range object
allows you to subset t... |
Returns a generator that accesses each chunk in descending order
Parameters
----------
symbol: str
the symbol for the given item in the DB
chunk_range: None, or a range object
allows you to subset the chunks by range
Returns
-------
gener... | def reverse_iterator(self, symbol, chunk_range=None):
"""
Returns a generator that accesses each chunk in descending order
Parameters
----------
symbol: str
the symbol for the given item in the DB
chunk_range: None, or a range object
allows you to... |
Catch-all decorator that handles AutoReconnect and OperationFailure
errors from PyMongo | def mongo_retry(f):
"""
Catch-all decorator that handles AutoReconnect and OperationFailure
errors from PyMongo
"""
log_all_exceptions = 'arctic' in f.__module__ if f.__module__ else False
@wraps(f)
def f_retry(*args, **kwargs):
global _retry_count, _in_retry
top_level = not... |
Return tuple: [start, end] of np.datetime64 dates that are inclusive of the passed
in datetimes. | def _start_end(date_range, dts):
"""
Return tuple: [start, end] of np.datetime64 dates that are inclusive of the passed
in datetimes.
"""
# FIXME: timezones
assert len(dts)
_assert_no_timezone(date_range)
date_range = to_pandas_closed_closed(date_range, add_tz=False)
start = np.datet... |
Generate index of datetime64 -> item offset.
Parameters:
-----------
new_data: new data being written (or appended)
existing_index: index field from the versions document of the previous version
start: first (0-based) offset of the new data
segments: list of offsets. Eac... | def _segment_index(self, recarr, existing_index, start, new_segments):
"""
Generate index of datetime64 -> item offset.
Parameters:
-----------
new_data: new data being written (or appended)
existing_index: index field from the versions document of the previous version
... |
Given a np.recarray find the first datetime64 column | def _datetime64_index(self, recarr):
""" Given a np.recarray find the first datetime64 column """
# TODO: Handle multi-indexes
names = recarr.dtype.names
for name in names:
if recarr[name].dtype == DTN64_DTYPE:
return name
return None |
Given a version, read the segment_index and return the chunks associated
with the date_range. As the segment index is (id -> last datetime)
we need to take care in choosing the correct chunks. | def _index_range(self, version, symbol, date_range=None, **kwargs):
""" Given a version, read the segment_index and return the chunks associated
with the date_range. As the segment index is (id -> last datetime)
we need to take care in choosing the correct chunks. """
if date_range and '... |
Given a recarr, slice out the given artic.date.DateRange if a
datetime64 index exists | def _daterange(self, recarr, date_range):
""" Given a recarr, slice out the given artic.date.DateRange if a
datetime64 index exists """
idx = self._datetime64_index(recarr)
if idx and len(recarr):
dts = recarr[idx]
mask = Series(np.zeros(len(dts)), index=dts)
... |
parses out the relevant information in version
and returns it to the user in a dictionary | def get_info(self, version):
"""
parses out the relevant information in version
and returns it to the user in a dictionary
"""
ret = super(PandasStore, self).get_info(version)
ret['col_names'] = version['dtype_metadata']
ret['handler'] = self.__class__.__name__
... |
This function will transform arr into an array with the same type as dtype. It will do this by
filling new columns with zeros (or NaNs, if it is a float column). Also, columns that are not
in the new dtype will be dropped. | def _resize_with_dtype(arr, dtype):
"""
This function will transform arr into an array with the same type as dtype. It will do this by
filling new columns with zeros (or NaNs, if it is a float column). Also, columns that are not
in the new dtype will be dropped.
"""
structured_arrays = dtype.nam... |
This function will decide whether to update the version document with forward pointers to segments.
It detects cases where no prior writes/appends have been performed with FW pointers, and extracts the segment IDs.
It also sets the metadata which indicate the mode of operation at the time of the version creatio... | def _update_fw_pointers(collection, symbol, version, previous_version, is_append, shas_to_add=None):
"""
This function will decide whether to update the version document with forward pointers to segments.
It detects cases where no prior writes/appends have been performed with FW pointers, and extracts the s... |
This method updates the find query filter spec used to read the segment for a version.
It chooses whether to query via forward pointers or not based on the version details and current mode of operation. | def _spec_fw_pointers_aware(symbol, version, from_index=None, to_index=None):
"""
This method updates the find query filter spec used to read the segment for a version.
It chooses whether to query via forward pointers or not based on the version details and current mode of operation.
"""
spec = {'sy... |
This method decides whether to convert an append to a full write in order to avoid data integrity errors | def _fw_pointers_convert_append_to_write(previous_version):
"""
This method decides whether to convert an append to a full write in order to avoid data integrity errors
"""
# Switching from ENABLED --> DISABLED/HYBRID when appending can cause integrity errors for subsequent reads:
# - Assume the ... |
Tuple describing range to read from the ndarray - closed:open | def _index_range(self, version, symbol, from_version=None, **kwargs):
"""
Tuple describing range to read from the ndarray - closed:open
"""
from_index = None
if from_version:
from_index = from_version['up_to']
return from_index, None |
index_range is a 2-tuple of integers - a [from, to) range of segments to be read.
Either from or to can be None, indicating no bound. | def _do_read(self, collection, version, symbol, index_range=None):
"""
index_range is a 2-tuple of integers - a [from, to) range of segments to be read.
Either from or to can be None, indicating no bound.
"""
from_index = index_range[0] if index_range else None
to_ind... |
Adds the library with the given date range to the underlying collection of libraries used by this store.
The underlying libraries should not overlap as the date ranges are assumed to be CLOSED_CLOSED by this function
and the rest of the class.
Arguments:
date_range: A date range provid... | def add(self, date_range, library_name):
"""
Adds the library with the given date range to the underlying collection of libraries used by this store.
The underlying libraries should not overlap as the date ranges are assumed to be CLOSED_CLOSED by this function
and the rest of the class.... |
Split the tick data to the underlying collections and write the data to each low
level library.
Args:
symbol (str): the symbol for the timeseries data
data (list of dicts or pandas dataframe): Tick data to write
if a list of dicts is given the list must be in tim... | def write(self, symbol, data):
"""
Split the tick data to the underlying collections and write the data to each low
level library.
Args:
symbol (str): the symbol for the timeseries data
data (list of dicts or pandas dataframe): Tick data to write
... |
Retrieve the libraries for the given date range, the assumption is that the date ranges do not overlap and
they are CLOSED_CLOSED.
At the moment the date range is mandatory | def _get_library_metadata(self, date_range):
"""
Retrieve the libraries for the given date range, the assumption is that the date ranges do not overlap and
they are CLOSED_CLOSED.
At the moment the date range is mandatory
"""
if date_range is None:
raise Exce... |
Records a write request to be actioned on context exit. Takes exactly the same parameters as the regular
library write call. | def write(self, symbol, data, prune_previous_version=True, metadata=None, **kwargs):
"""
Records a write request to be actioned on context exit. Takes exactly the same parameters as the regular
library write call.
"""
if data is not None:
# We only write data if exist... |
Similar to DataFrame.to_records()
Differences:
Attempt type conversion for pandas columns stored as objects (e.g. strings),
as we can only store primitives in the ndarray.
Use dtype metadata to store column and index names.
string_max_len: integer - enforces a string... | def _to_records(self, df, string_max_len=None, forced_dtype=None):
"""
Similar to DataFrame.to_records()
Differences:
Attempt type conversion for pandas columns stored as objects (e.g. strings),
as we can only store primitives in the ndarray.
Use dtype metadat... |
Convert efficiently the frame's object-columns/object-index/multi-index/multi-column to
records, by creating a recarray only for the object fields instead for the whole dataframe.
If we have no object dtypes, we can safely convert only the first row to recarray to test if serializable.
Previousl... | def fast_check_serializable(self, df):
"""
Convert efficiently the frame's object-columns/object-index/multi-index/multi-column to
records, by creating a recarray only for the object fields instead for the whole dataframe.
If we have no object dtypes, we can safely convert only the first... |
Apply `func` to each chunk in lib.symbol
Parameters
----------
lib: arctic library
symbol: str
the symbol for the given item in the DB
chunk_range: None, or a range object
allows you to subset the chunks by range
Returns
-------
generator | def read_apply(lib, symbol, func, chunk_range=None):
"""
Apply `func` to each chunk in lib.symbol
Parameters
----------
lib: arctic library
symbol: str
the symbol for the given item in the DB
chunk_range: None, or a range object
allows you to subset the chunks by range
... |
Return the symbols in this library.
Parameters
----------
as_of : `datetime.datetime`
filter symbols valid at given time
regex : `str`
filter symbols by the passed in regular expression
kwargs :
kwarg keys are used as fields to query fo... | def list_symbols(self, regex=None, as_of=None, **kwargs):
"""
Return the symbols in this library.
Parameters
----------
as_of : `datetime.datetime`
filter symbols valid at given time
regex : `str`
filter symbols by the passed in regular expr... |
Return all metadata saved for `symbol`
Parameters
----------
symbol : `str`
symbol name for the item
Returns
-------
pandas.DateFrame containing timestamps and metadata entries | def read_history(self, symbol):
"""
Return all metadata saved for `symbol`
Parameters
----------
symbol : `str`
symbol name for the item
Returns
-------
pandas.DateFrame containing timestamps and metadata entries
"""
find = se... |
Return current metadata saved for `symbol`
Parameters
----------
symbol : `str`
symbol name for the item
as_of : `datetime.datetime`
return entry valid at given time
Returns
-------
metadata | def read(self, symbol, as_of=None):
"""
Return current metadata saved for `symbol`
Parameters
----------
symbol : `str`
symbol name for the item
as_of : `datetime.datetime`
return entry valid at given time
Returns
-------
... |
Manually overwrite entire metadata history for symbols in `collection`
Parameters
----------
collection : `list of pandas.DataFrame`
with symbol names as headers and timestamps as indices
(the same format as output of read_history)
Example:
[p... | def write_history(self, collection):
"""
Manually overwrite entire metadata history for symbols in `collection`
Parameters
----------
collection : `list of pandas.DataFrame`
with symbol names as headers and timestamps as indices
(the same format as output... |
Update metadata entry for `symbol`
Parameters
----------
symbol : `str`
symbol name for the item
metadata : `dict`
to be persisted
start_time : `datetime.datetime`
when metadata becomes effective
Default: datetime.datetime.utcnow() | def append(self, symbol, metadata, start_time=None):
"""
Update metadata entry for `symbol`
Parameters
----------
symbol : `str`
symbol name for the item
metadata : `dict`
to be persisted
start_time : `datetime.datetime`
when m... |
Prepend a metadata entry for `symbol`
Parameters
----------
symbol : `str`
symbol name for the item
metadata : `dict`
to be persisted
start_time : `datetime.datetime`
when metadata becomes effective
Default: datetime.datetime.min | def prepend(self, symbol, metadata, start_time=None):
"""
Prepend a metadata entry for `symbol`
Parameters
----------
symbol : `str`
symbol name for the item
metadata : `dict`
to be persisted
start_time : `datetime.datetime`
wh... |
Delete current metadata of `symbol`
Parameters
----------
symbol : `str`
symbol name to delete
Returns
-------
Deleted metadata | def pop(self, symbol):
"""
Delete current metadata of `symbol`
Parameters
----------
symbol : `str`
symbol name to delete
Returns
-------
Deleted metadata
"""
last_metadata = self.find_one({'symbol': symbol}, sort=[('start_tim... |
Delete all metadata of `symbol`
Parameters
----------
symbol : `str`
symbol name to delete | def purge(self, symbol):
"""
Delete all metadata of `symbol`
Parameters
----------
symbol : `str`
symbol name to delete
"""
logger.warning("Deleting entire metadata history for %r from %r" % (symbol, self._arctic_lib.get_name()))
self.delete_m... |
Generic query method.
In reality, your storage class would have its own query methods,
Performs a Mongo find on the Marketdata index metadata collection.
See:
http://api.mongodb.org/python/current/api/pymongo/collection.html | def query(self, *args, **kwargs):
"""
Generic query method.
In reality, your storage class would have its own query methods,
Performs a Mongo find on the Marketdata index metadata collection.
See:
http://api.mongodb.org/python/current/api/pymongo/collection.html
... |
Database usage statistics. Used by quota. | def stats(self):
"""
Database usage statistics. Used by quota.
"""
res = {}
db = self._collection.database
res['dbstats'] = db.command('dbstats')
res['data'] = db.command('collstats', self._collection.name)
res['totals'] = {'count': res['data']['count'],
... |
Simple persistence method | def store(self, thing):
"""
Simple persistence method
"""
to_store = {'field1': thing.field1,
'date_field': thing.date_field,
}
to_store['stuff'] = Binary(cPickle.dumps(thing.stuff))
# Respect any soft-quota on write - raises if sta... |
Read data for the named symbol. Returns a BitemporalItem object with
a data and metdata element (as passed into write).
Parameters
----------
symbol : `str`
symbol name for the item
as_of : `datetime.datetime`
Return the data as it was as_of the point in ... | def read(self, symbol, as_of=None, raw=False, **kwargs):
# TODO: shall we block from_version from getting into super.read?
"""Read data for the named symbol. Returns a BitemporalItem object with
a data and metdata element (as passed into write).
Parameters
----------
sym... |
Append 'data' under the specified 'symbol' name to this library.
Parameters
----------
symbol : `str`
symbol name for the item
data : `pd.DataFrame`
to be persisted
metadata : `dict`
An optional dictionary of metadata to persist along with the... | def update(self, symbol, data, metadata=None, upsert=True, as_of=None, **kwargs):
""" Append 'data' under the specified 'symbol' name to this library.
Parameters
----------
symbol : `str`
symbol name for the item
data : `pd.DataFrame`
to be persisted
... |
Returns a non-naive datetime.datetime.
Interprets numbers as ms-since-epoch.
Parameters
----------
date : `int` or `datetime.datetime`
The datetime to convert
default_tz : tzinfo
The TimeZone to use if none is found. If not supplied, and the
datetime doesn't have a timezo... | def to_dt(date, default_tz=None):
"""
Returns a non-naive datetime.datetime.
Interprets numbers as ms-since-epoch.
Parameters
----------
date : `int` or `datetime.datetime`
The datetime to convert
default_tz : tzinfo
The TimeZone to use if none is found. If not supplied, ... |
Convert a string to a DateRange type. If you put only one date, it generates the
relevant range for just that date or datetime till 24 hours later. You can optionally
use mixtures of []/() around the DateRange for OPEN/CLOSED interval behaviour.
Parameters
----------
str_range : `String`
Th... | def string_to_daterange(str_range, delimiter='-', as_dates=False, interval=CLOSED_CLOSED):
"""
Convert a string to a DateRange type. If you put only one date, it generates the
relevant range for just that date or datetime till 24 hours later. You can optionally
use mixtures of []/() around the DateRange... |
Pandas DateRange slicing is CLOSED-CLOSED inclusive at both ends.
Parameters
----------
date_range : `DateRange` object
converted to CLOSED_CLOSED form for Pandas slicing
add_tz : `bool`
Adds a TimeZone to the daterange start and end if it doesn't
have one.
Returns
---... | def to_pandas_closed_closed(date_range, add_tz=True):
"""
Pandas DateRange slicing is CLOSED-CLOSED inclusive at both ends.
Parameters
----------
date_range : `DateRange` object
converted to CLOSED_CLOSED form for Pandas slicing
add_tz : `bool`
Adds a TimeZone to the daterange ... |
Convert a millisecond time value to an offset-aware Python datetime object. | def ms_to_datetime(ms, tzinfo=None):
"""Convert a millisecond time value to an offset-aware Python datetime object."""
if not isinstance(ms, (int, long)):
raise TypeError('expected integer, not %s' % type(ms))
if tzinfo is None:
tzinfo = mktz()
return datetime.datetime.fromtimestamp(ms... |
Convert a Python datetime object to a millisecond epoch (UTC) time value. | def datetime_to_ms(d):
"""Convert a Python datetime object to a millisecond epoch (UTC) time value."""
try:
millisecond = d.microsecond // 1000
return calendar.timegm(_add_tzone(d).utctimetuple()) * 1000 + millisecond
except AttributeError:
raise TypeError('expect Python datetime obj... |
Convert a UTC datetime to datetime in local timezone | def utc_dt_to_local_dt(dtm):
"""Convert a UTC datetime to datetime in local timezone"""
utc_zone = mktz("UTC")
if dtm.tzinfo is not None and dtm.tzinfo != utc_zone:
raise ValueError(
"Expected dtm without tzinfo or with UTC, not %r" % (
dtm.tzinfo
)
)
... |
Create a new DateRange representing the maximal range enclosed by this range and other | def intersection(self, other):
"""
Create a new DateRange representing the maximal range enclosed by this range and other
"""
startopen = other.startopen if self.start is None \
else self.startopen if other.start is None \
else other.startopen if self.start < othe... |
Create a new DateRange with the datetimes converted to dates and changing to CLOSED/CLOSED. | def as_dates(self):
"""
Create a new DateRange with the datetimes converted to dates and changing to CLOSED/CLOSED.
"""
new_start = self.start.date() if self.start and isinstance(self.start, datetime.datetime) else self.start
new_end = self.end.date() if self.end and isinstance(s... |
Convert a DateRange into a MongoDb query string. FIXME: Mongo can only handle
datetimes in queries, so we should make this handle the case where start/end are
datetime.date and extend accordingly (being careful about the interval logic). | def mongo_query(self):
"""
Convert a DateRange into a MongoDb query string. FIXME: Mongo can only handle
datetimes in queries, so we should make this handle the case where start/end are
datetime.date and extend accordingly (being careful about the interval logic).
"""
com... |
Return the upper and lower bounds along
with operators that are needed to do an 'in range' test.
Useful for SQL commands.
Returns
-------
tuple: (`str`, `date`, `str`, `date`)
(date_gt, start, date_lt, end)
e.g.:
('>=', start_date, '<', en... | def get_date_bounds(self):
"""
Return the upper and lower bounds along
with operators that are needed to do an 'in range' test.
Useful for SQL commands.
Returns
-------
tuple: (`str`, `date`, `str`, `date`)
(date_gt, start, date_lt, end)
e... |
chunks the dataframe/series by dates
Parameters
----------
df: pandas dataframe or series
chunk_size: str
any valid Pandas frequency string
func: function
func will be applied to each `chunk` generated by the chunker.
This function CANNOT modi... | def to_chunks(self, df, chunk_size='D', func=None, **kwargs):
"""
chunks the dataframe/series by dates
Parameters
----------
df: pandas dataframe or series
chunk_size: str
any valid Pandas frequency string
func: function
func will be appli... |
takes the range object used for this chunker type
and converts it into a string that can be use for a
mongo query that filters by the range
returns
-------
dict | def to_mongo(self, range_obj):
"""
takes the range object used for this chunker type
and converts it into a string that can be use for a
mongo query that filters by the range
returns
-------
dict
"""
if isinstance(range_obj, (pd.DatetimeIndex, tup... |
ensures data is properly subset to the range in range_obj.
(Depending on how the chunking is implemented, it might be possible
to specify a chunk range that reads out more than the actual range
eg: date range, chunked monthly. read out 2016-01-01 to 2016-01-02.
This will read ALL of Janu... | def filter(self, data, range_obj):
"""
ensures data is properly subset to the range in range_obj.
(Depending on how the chunking is implemented, it might be possible
to specify a chunk range that reads out more than the actual range
eg: date range, chunked monthly. read out 2016-... |
Removes data within the bounds of the range object (inclusive)
returns
-------
data, filtered by range_obj | def exclude(self, data, range_obj):
"""
Removes data within the bounds of the range object (inclusive)
returns
-------
data, filtered by range_obj
"""
if isinstance(range_obj, (pd.DatetimeIndex, tuple)):
range_obj = DateRange(range_obj[0], range_obj[-... |
Enable sharding on a library
Parameters:
-----------
arctic: `arctic.Arctic` Arctic class
library_name: `basestring` library name
hashed: `bool` if True, use hashed sharding, if False, use range sharding
See https://docs.mongodb.com/manual/core/hashed-sharding/,
as well as... | def enable_sharding(arctic, library_name, hashed=True, key='symbol'):
"""
Enable sharding on a library
Parameters:
-----------
arctic: `arctic.Arctic` Arctic class
library_name: `basestring` library name
hashed: `bool` if True, use hashed sharding, if False, use range sharding
... |
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.insert_one | def insert_one(self, document, **kwargs):
"""
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.insert_one
"""
self._arctic_lib.check_quota()
return self._collection.insert_one(document, **kwargs) |
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.insert_many | def insert_many(self, documents, **kwargs):
"""
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.insert_many
"""
self._arctic_lib.check_quota()
return self._collection.insert_many(documents, **kwargs) |
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.update_one | def update_one(self, filter, update, **kwargs):
"""
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.update_one
"""
self._arctic_lib.check_quota()
return self._collection.update_one(filter, update, **kwargs) |
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.update_many | def update_many(self, filter, update, **kwargs):
"""
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.update_many
"""
self._arctic_lib.check_quota()
return self._collection.update_many(filter, update, **kwargs) |
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.replace_one | def replace_one(self, filter, replacement, **kwargs):
"""
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.replace_one
"""
self._arctic_lib.check_quota()
return self._collection.replace_one(filter, replacement, **kwargs) |
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.find_one_and_replace | def find_one_and_replace(self, filter, replacement, **kwargs):
"""
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.find_one_and_replace
"""
self._arctic_lib.check_quota()
return self._collection.find_one_and_replace(filter, repl... |
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.find_one_and_update | def find_one_and_update(self, filter, update, **kwargs):
"""
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.find_one_and_update
"""
self._arctic_lib.check_quota()
return self._collection.find_one_and_update(filter, update, **kw... |
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.bulk_write
Warning: this is wrapped in mongo_retry, and is therefore potentially unsafe if the write you want to execute
isn't idempotent. | def bulk_write(self, requests, **kwargs):
"""
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.bulk_write
Warning: this is wrapped in mongo_retry, and is therefore potentially unsafe if the write you want to execute
isn't idempotent.
... |
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.count | def count(self, filter, **kwargs):
"""
See http://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.count
"""
return mongo_count(self._collection, filter=filter, **kwargs) |
Return a new timezone (tzinfo object) based on the zone using the python-dateutil
package.
The concise name 'mktz' is for convenient when using it on the
console.
Parameters
----------
zone : `String`
The zone for the timezone. This defaults to local, returning:
tzlocal.g... | def mktz(zone=None):
"""
Return a new timezone (tzinfo object) based on the zone using the python-dateutil
package.
The concise name 'mktz' is for convenient when using it on the
console.
Parameters
----------
zone : `String`
The zone for the timezone. This defaults to local... |
Ensure that symbol(s) have contiguous segment ids
Parameters
----------
library: arctic library
symbol: None, str, list of str
None: all symbols
str: single symbol
list: list of symbols
Returns
-------
list of str - Symbols 'fixed' | def segment_id_repair(library, symbol=None):
"""
Ensure that symbol(s) have contiguous segment ids
Parameters
----------
library: arctic library
symbol: None, str, list of str
None: all symbols
str: single symbol
list: list of symbols
Returns
-------
list of... |
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