code stringlengths 66 870k | docstring stringlengths 19 26.7k | func_name stringlengths 1 138 | language stringclasses 1
value | repo stringlengths 7 68 | path stringlengths 5 324 | url stringlengths 46 389 | license stringclasses 7
values |
|---|---|---|---|---|---|---|---|
def render_git_describe(pieces):
"""TAG[-DISTANCE-gHEX][-dirty].
Like 'git describe --tags --dirty --always'.
Exceptions:
1: no tags. HEX[-dirty] (note: no 'g' prefix)
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"]:
rendered +=... | TAG[-DISTANCE-gHEX][-dirty].
Like 'git describe --tags --dirty --always'.
Exceptions:
1: no tags. HEX[-dirty] (note: no 'g' prefix)
| render_git_describe | python | mars-project/mars | mars/_version.py | https://github.com/mars-project/mars/blob/master/mars/_version.py | Apache-2.0 |
def render_git_describe_long(pieces):
"""TAG-DISTANCE-gHEX[-dirty].
Like 'git describe --tags --dirty --always -long'.
The distance/hash is unconditional.
Exceptions:
1: no tags. HEX[-dirty] (note: no 'g' prefix)
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
... | TAG-DISTANCE-gHEX[-dirty].
Like 'git describe --tags --dirty --always -long'.
The distance/hash is unconditional.
Exceptions:
1: no tags. HEX[-dirty] (note: no 'g' prefix)
| render_git_describe_long | python | mars-project/mars | mars/_version.py | https://github.com/mars-project/mars/blob/master/mars/_version.py | Apache-2.0 |
def render(pieces, style):
"""Render the given version pieces into the requested style."""
if pieces["error"]:
return {"version": "unknown",
"full-revisionid": pieces.get("long"),
"dirty": None,
"error": pieces["error"],
"date": None}
... | Render the given version pieces into the requested style. | render | python | mars-project/mars | mars/_version.py | https://github.com/mars-project/mars/blob/master/mars/_version.py | Apache-2.0 |
def get_versions():
"""Get version information or return default if unable to do so."""
# I am in _version.py, which lives at ROOT/VERSIONFILE_SOURCE. If we have
# __file__, we can work backwards from there to the root. Some
# py2exe/bbfreeze/non-CPython implementations don't do __file__, in which
#... | Get version information or return default if unable to do so. | get_versions | python | mars-project/mars | mars/_version.py | https://github.com/mars-project/mars/blob/master/mars/_version.py | Apache-2.0 |
def convert_dask_collection(dc):
"""
Convert dask collection object into mars.core.Object via remote API
Parameters
----------
dc: dask collection
Dask collection object to be converted.
Returns
-------
Object
Mars Object.
"""
if not is_dask_collection(dc):
... |
Convert dask collection object into mars.core.Object via remote API
Parameters
----------
dc: dask collection
Dask collection object to be converted.
Returns
-------
Object
Mars Object.
| convert_dask_collection | python | mars-project/mars | mars/contrib/dask/converter.py | https://github.com/mars-project/mars/blob/master/mars/contrib/dask/converter.py | Apache-2.0 |
def mars_scheduler(dsk: dict, keys: Union[List[List[str]], List[str]]):
"""
A Dask-Mars scheduler
This scheduler is intended to be compatible with existing
dask user interface, no callbacks are implemented.
Parameters
----------
dsk: Dict
Dask graph, represented as a task DAG dicti... |
A Dask-Mars scheduler
This scheduler is intended to be compatible with existing
dask user interface, no callbacks are implemented.
Parameters
----------
dsk: Dict
Dask graph, represented as a task DAG dictionary.
keys: Union[List[List[str]], List[str]]
1d or 2d list of Das... | mars_scheduler | python | mars-project/mars | mars/contrib/dask/scheduler.py | https://github.com/mars-project/mars/blob/master/mars/contrib/dask/scheduler.py | Apache-2.0 |
def mars_dask_get(dsk: dict, keys: Union[List[List[str]], List[str]]):
"""
A Dask-Mars convert function. This function will send the dask graph layers
to Mars Remote API, generating mars objects correspond to the provided keys.
Parameters
----------
dsk: Dict
Dask graph, represented... |
A Dask-Mars convert function. This function will send the dask graph layers
to Mars Remote API, generating mars objects correspond to the provided keys.
Parameters
----------
dsk: Dict
Dask graph, represented as a task DAG dictionary.
keys: Union[List[List[str]], List[str]]
... | mars_dask_get | python | mars-project/mars | mars/contrib/dask/scheduler.py | https://github.com/mars-project/mars/blob/master/mars/contrib/dask/scheduler.py | Apache-2.0 |
def concat(objs: List):
"""
Concat the results of partitioned dask task executions. This function guess the
types of resulting list, then calls the corresponding native dask concat functions.
Parameters
----------
objs: List
List of the partitioned dask task execution results, which... |
Concat the results of partitioned dask task executions. This function guess the
types of resulting list, then calls the corresponding native dask concat functions.
Parameters
----------
objs: List
List of the partitioned dask task execution results, which will be concat.
Returns
... | concat | python | mars-project/mars | mars/contrib/dask/utils.py | https://github.com/mars-project/mars/blob/master/mars/contrib/dask/utils.py | Apache-2.0 |
def get_local_host_ip(self) -> str:
"""
Get local worker's host ip
Returns
-------
host_ip : str
""" |
Get local worker's host ip
Returns
-------
host_ip : str
| get_local_host_ip | python | mars-project/mars | mars/core/context.py | https://github.com/mars-project/mars/blob/master/mars/core/context.py | Apache-2.0 |
def get_total_n_cpu(self) -> int:
"""
Get number of cpus.
Returns
-------
number_of_cpu: int
""" |
Get number of cpus.
Returns
-------
number_of_cpu: int
| get_total_n_cpu | python | mars-project/mars | mars/core/context.py | https://github.com/mars-project/mars/blob/master/mars/core/context.py | Apache-2.0 |
def get_slots(self) -> int:
"""
Get num of slots of current band
Returns
-------
number_of_bands: int
""" |
Get num of slots of current band
Returns
-------
number_of_bands: int
| get_slots | python | mars-project/mars | mars/core/context.py | https://github.com/mars-project/mars/blob/master/mars/core/context.py | Apache-2.0 |
def get_chunks_result(self, data_keys: List[str], fetch_only: bool = False) -> List:
"""
Get result of chunks.
Parameters
----------
data_keys : list
Data keys.
fetch_only : bool
If fetch_only, only fetch data but not return.
Returns
... |
Get result of chunks.
Parameters
----------
data_keys : list
Data keys.
fetch_only : bool
If fetch_only, only fetch data but not return.
Returns
-------
results : list
Result of chunks if not fetch_only, else return N... | get_chunks_result | python | mars-project/mars | mars/core/context.py | https://github.com/mars-project/mars/blob/master/mars/core/context.py | Apache-2.0 |
def get_chunks_meta(
self, data_keys: List[str], fields: List[str] = None, error="raise"
) -> List[Dict]:
"""
Get meta of chunks.
Parameters
----------
data_keys : list
Data keys.
fields : list
Fields to filter.
error : str
... |
Get meta of chunks.
Parameters
----------
data_keys : list
Data keys.
fields : list
Fields to filter.
error : str
raise, ignore
Returns
-------
meta_list : list
Meta list.
| get_chunks_meta | python | mars-project/mars | mars/core/context.py | https://github.com/mars-project/mars/blob/master/mars/core/context.py | Apache-2.0 |
def get_storage_info(self, address: str, level: StorageLevel):
"""
Get the customized storage backend info of requested storage backend level at given worker.
Parameters
----------
address: str
The worker address.
level: StorageLevel
The storage l... |
Get the customized storage backend info of requested storage backend level at given worker.
Parameters
----------
address: str
The worker address.
level: StorageLevel
The storage level to fetch the backend info.
Returns
-------
i... | get_storage_info | python | mars-project/mars | mars/core/context.py | https://github.com/mars-project/mars/blob/master/mars/core/context.py | Apache-2.0 |
def create_remote_object(self, name: str, object_cls, *args, **kwargs):
"""
Create remote object.
Parameters
----------
name : str
Object name.
object_cls
Object class.
args
kwargs
Returns
-------
ref
... |
Create remote object.
Parameters
----------
name : str
Object name.
object_cls
Object class.
args
kwargs
Returns
-------
ref
| create_remote_object | python | mars-project/mars | mars/core/context.py | https://github.com/mars-project/mars/blob/master/mars/core/context.py | Apache-2.0 |
def get_remote_object(self, name: str):
"""
Get remote object
Parameters
----------
name : str
Object name.
Returns
-------
ref
""" |
Get remote object
Parameters
----------
name : str
Object name.
Returns
-------
ref
| get_remote_object | python | mars-project/mars | mars/core/context.py | https://github.com/mars-project/mars/blob/master/mars/core/context.py | Apache-2.0 |
def destroy_remote_object(self, name: str):
"""
Destroy remote object.
Parameters
----------
name : str
Object name.
""" |
Destroy remote object.
Parameters
----------
name : str
Object name.
| destroy_remote_object | python | mars-project/mars | mars/core/context.py | https://github.com/mars-project/mars/blob/master/mars/core/context.py | Apache-2.0 |
def register_custom_log_path(
self,
session_id: str,
tileable_op_key: str,
chunk_op_key: str,
worker_address: str,
log_path: str,
):
"""
Register custom log path.
Parameters
----------
session_id : str
Session ID.
... |
Register custom log path.
Parameters
----------
session_id : str
Session ID.
tileable_op_key : str
Key of tileable's op.
chunk_op_key : str
Kye of chunk's op.
worker_address : str
Worker address.
log_path :... | register_custom_log_path | python | mars-project/mars | mars/core/context.py | https://github.com/mars-project/mars/blob/master/mars/core/context.py | Apache-2.0 |
def new_custom_log_dir(self) -> str:
"""
New custom log dir.
Returns
-------
custom_log_dir : str
Custom log dir.
""" |
New custom log dir.
Returns
-------
custom_log_dir : str
Custom log dir.
| new_custom_log_dir | python | mars-project/mars | mars/core/context.py | https://github.com/mars-project/mars/blob/master/mars/core/context.py | Apache-2.0 |
def set_running_operand_key(self, session_id: str, op_key: str):
"""
Set key of running operand.
Parameters
----------
session_id : str
op_key : str
""" |
Set key of running operand.
Parameters
----------
session_id : str
op_key : str
| set_running_operand_key | python | mars-project/mars | mars/core/context.py | https://github.com/mars-project/mars/blob/master/mars/core/context.py | Apache-2.0 |
def set_progress(self, progress: float):
"""
Set progress of running operand.
Parameters
----------
progress : float
""" |
Set progress of running operand.
Parameters
----------
progress : float
| set_progress | python | mars-project/mars | mars/core/context.py | https://github.com/mars-project/mars/blob/master/mars/core/context.py | Apache-2.0 |
def redirect_custom_log(func: Callable[[Type, Context, OperandType], None]):
"""
Redirect stdout to a file by wrapping ``Operand.execute(ctx, op)``
"""
@functools.wraps(func)
def wrap(cls, ctx: Context, op: OperandType):
custom_log_dir = ctx.new_custom_log_dir()
if custom_log_dir i... |
Redirect stdout to a file by wrapping ``Operand.execute(ctx, op)``
| redirect_custom_log | python | mars-project/mars | mars/core/custom_log.py | https://github.com/mars-project/mars/blob/master/mars/core/custom_log.py | Apache-2.0 |
def init_extension_entrypoints():
"""Execute all `mars_extensions` entry points with the name `init`
If extensions have already been initialized, this function does nothing.
"""
from pkg_resources import iter_entry_points
for entry_point in iter_entry_points("mars_extensions", "init"):
logg... | Execute all `mars_extensions` entry points with the name `init`
If extensions have already been initialized, this function does nothing.
| init_extension_entrypoints | python | mars-project/mars | mars/core/entrypoints.py | https://github.com/mars-project/mars/blob/master/mars/core/entrypoints.py | Apache-2.0 |
def __getitem__(self, item):
"""
The indices for `cix` can be [x, y] or [x, :].
For the former the result will be a single chunk,
and for the later the result will be a list of chunks (flattened).
The length of indices must be the same with `chunk_shape` of tileable.
"""... |
The indices for `cix` can be [x, y] or [x, :].
For the former the result will be a single chunk,
and for the later the result will be a list of chunks (flattened).
The length of indices must be the same with `chunk_shape` of tileable.
| __getitem__ | python | mars-project/mars | mars/core/entity/tileables.py | https://github.com/mars-project/mars/blob/master/mars/core/entity/tileables.py | Apache-2.0 |
def results(self):
"""
Return result tileables or chunks.
Returns
-------
results
""" |
Return result tileables or chunks.
Returns
-------
results
| results | python | mars-project/mars | mars/core/graph/entity.py | https://github.com/mars-project/mars/blob/master/mars/core/graph/entity.py | Apache-2.0 |
def results(self, new_results):
"""
Set result tileables or chunks.
Parameters
----------
new_results
Returns
-------
""" |
Set result tileables or chunks.
Parameters
----------
new_results
Returns
-------
| results | python | mars-project/mars | mars/core/graph/entity.py | https://github.com/mars-project/mars/blob/master/mars/core/graph/entity.py | Apache-2.0 |
def build(self) -> Generator[Union[EntityGraph, ChunkGraph], None, None]:
"""
Build a entity graph.
Returns
-------
graph : EntityGraph
Entity graph.
""" |
Build a entity graph.
Returns
-------
graph : EntityGraph
Entity graph.
| build | python | mars-project/mars | mars/core/graph/builder/base.py | https://github.com/mars-project/mars/blob/master/mars/core/graph/builder/base.py | Apache-2.0 |
def get_logic_key(self):
"""The subclass may need to override this method to ensure unique and deterministic."""
fields = self._get_logic_key_token_values()
try:
return tokenize(*fields)
except Exception as e: # pragma: no cover
raise ValueError(
... | The subclass may need to override this method to ensure unique and deterministic. | get_logic_key | python | mars-project/mars | mars/core/operand/base.py | https://github.com/mars-project/mars/blob/master/mars/core/operand/base.py | Apache-2.0 |
def new_chunks(
self, inputs: List[ChunkType], kws: List[Dict] = None, **kwargs
) -> List[ChunkType]:
"""
Create chunks.
A chunk is a node in a fine grained graph, all the chunk objects are created by
calling this function, it happens mostly in tiles.
The generated c... |
Create chunks.
A chunk is a node in a fine grained graph, all the chunk objects are created by
calling this function, it happens mostly in tiles.
The generated chunks will be set as this operand's outputs and each chunk will
hold this operand as it's op.
Parameters
... | new_chunks | python | mars-project/mars | mars/core/operand/core.py | https://github.com/mars-project/mars/blob/master/mars/core/operand/core.py | Apache-2.0 |
def new_tileables(
self, inputs: List[TileableType], kws: List[dict] = None, **kw
) -> List[TileableType]:
"""
Create tileable objects(Tensors or DataFrames).
This is a base function for create tileable objects like tensors or dataframes,
it will be called inside the `new_te... |
Create tileable objects(Tensors or DataFrames).
This is a base function for create tileable objects like tensors or dataframes,
it will be called inside the `new_tensors` and `new_dataframes`.
If eager mode is on, it will trigger the execution after tileable objects are created.
... | new_tileables | python | mars-project/mars | mars/core/operand/core.py | https://github.com/mars-project/mars/blob/master/mars/core/operand/core.py | Apache-2.0 |
def pre_tile(cls, op: OperandType):
"""
Operation before tile.
Parameters
----------
op : OperandType
Operand to tile
""" |
Operation before tile.
Parameters
----------
op : OperandType
Operand to tile
| pre_tile | python | mars-project/mars | mars/core/operand/core.py | https://github.com/mars-project/mars/blob/master/mars/core/operand/core.py | Apache-2.0 |
def post_tile(cls, op: OperandType, results: List[TileableType]):
"""
Operation after tile.
Parameters
----------
op : OperandType
Operand to tile.
results: list
List of tiled results.
""" |
Operation after tile.
Parameters
----------
op : OperandType
Operand to tile.
results: list
List of tiled results.
| post_tile | python | mars-project/mars | mars/core/operand/core.py | https://github.com/mars-project/mars/blob/master/mars/core/operand/core.py | Apache-2.0 |
def pre_execute(cls, ctx: Union[dict, Context], op: OperandType):
"""
Operation before execute.
Parameters
----------
ctx : dict
Data store.
op : OperandType
Operand to execute.
""" |
Operation before execute.
Parameters
----------
ctx : dict
Data store.
op : OperandType
Operand to execute.
| pre_execute | python | mars-project/mars | mars/core/operand/core.py | https://github.com/mars-project/mars/blob/master/mars/core/operand/core.py | Apache-2.0 |
def post_execute(cls, ctx: Union[dict, Context], op: OperandType):
"""
Operand before execute.
Parameters
----------
ctx : dict
Data store
op : OperandType
Operand to execute.
""" |
Operand before execute.
Parameters
----------
ctx : dict
Data store
op : OperandType
Operand to execute.
| post_execute | python | mars-project/mars | mars/core/operand/core.py | https://github.com/mars-project/mars/blob/master/mars/core/operand/core.py | Apache-2.0 |
def execute(cls, ctx, op):
"""
Fetch operand needs nothing to do.
""" |
Fetch operand needs nothing to do.
| execute | python | mars-project/mars | mars/core/operand/fetch.py | https://github.com/mars-project/mars/blob/master/mars/core/operand/fetch.py | Apache-2.0 |
def execute(self, ctx, op):
"""The mapper stage must ensure all mapper blocks are inserted into ctx and no blocks
for some reducers are missing. This is needed by shuffle fetch by index,
which shuffle block are identified by the index instead of data keys.
For operands implementation si... | The mapper stage must ensure all mapper blocks are inserted into ctx and no blocks
for some reducers are missing. This is needed by shuffle fetch by index,
which shuffle block are identified by the index instead of data keys.
For operands implementation simplicity, we can sort the `ctx` by key ... | execute | python | mars-project/mars | mars/core/operand/shuffle.py | https://github.com/mars-project/mars/blob/master/mars/core/operand/shuffle.py | Apache-2.0 |
def to_frame(self, index: bool = True, name=None):
"""
Create a DataFrame with a column containing the Index.
Parameters
----------
index : bool, default True
Set the index of the returned DataFrame as the original Index.
name : object, default None
... |
Create a DataFrame with a column containing the Index.
Parameters
----------
index : bool, default True
Set the index of the returned DataFrame as the original Index.
name : object, default None
The passed name should substitute for the index name (if i... | to_frame | python | mars-project/mars | mars/dataframe/core.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/core.py | Apache-2.0 |
def to_series(self, index=None, name=None):
"""
Create a Series with both index and values equal to the index keys.
Useful with map for returning an indexer based on an index.
Parameters
----------
index : Index, optional
Index of resulting Series. If None, ... |
Create a Series with both index and values equal to the index keys.
Useful with map for returning an indexer based on an index.
Parameters
----------
index : Index, optional
Index of resulting Series. If None, defaults to original index.
name : str, optiona... | to_series | python | mars-project/mars | mars/dataframe/core.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/core.py | Apache-2.0 |
def index(self):
"""
The index (axis labels) of the Series.
"""
idx = self._data.index
idx._set_df_or_series(self, 0)
return idx |
The index (axis labels) of the Series.
| index | python | mars-project/mars | mars/dataframe/core.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/core.py | Apache-2.0 |
def copy(self, deep=True): # pylint: disable=arguments-differ
"""
Make a copy of this object's indices and data.
When ``deep=True`` (default), a new object will be created with a
copy of the calling object's data and indices. Modifications to
the data or indices of the copy wil... |
Make a copy of this object's indices and data.
When ``deep=True`` (default), a new object will be created with a
copy of the calling object's data and indices. Modifications to
the data or indices of the copy will not be reflected in the
original object (see notes below).
... | copy | python | mars-project/mars | mars/dataframe/core.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/core.py | Apache-2.0 |
def to_frame(self, name=None):
"""
Convert Series to DataFrame.
Parameters
----------
name : object, default None
The passed name should substitute for the series name (if it has
one).
Returns
-------
DataFrame
DataFra... |
Convert Series to DataFrame.
Parameters
----------
name : object, default None
The passed name should substitute for the series name (if it has
one).
Returns
-------
DataFrame
DataFrame representation of Series.
Exam... | to_frame | python | mars-project/mars | mars/dataframe/core.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/core.py | Apache-2.0 |
def between(self, left, right, inclusive="both"):
"""
Return boolean Series equivalent to left <= series <= right.
This function returns a boolean vector containing `True` wherever the
corresponding Series element is between the boundary values `left` and
`right`. NA values are t... |
Return boolean Series equivalent to left <= series <= right.
This function returns a boolean vector containing `True` wherever the
corresponding Series element is between the boundary values `left` and
`right`. NA values are treated as `False`.
Parameters
----------
... | between | python | mars-project/mars | mars/dataframe/core.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/core.py | Apache-2.0 |
def median(
self, axis=None, skipna=True, out=None, overwrite_input=False, keepdims=False
):
"""
Return the median of the values over the requested axis.
Parameters
----------
axis : {index (0)}
Axis or axes along which the medians are computed. The defau... |
Return the median of the values over the requested axis.
Parameters
----------
axis : {index (0)}
Axis or axes along which the medians are computed. The default
is to compute the median along a flattened version of the tensor.
A sequence of axes is s... | median | python | mars-project/mars | mars/dataframe/core.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/core.py | Apache-2.0 |
def itertuples(self, index=True, name="Pandas", batch_size=1000, session=None):
"""
Iterate over DataFrame rows as namedtuples.
Parameters
----------
index : bool, default True
If True, return the index as the first element of the tuple.
name : str or None, d... |
Iterate over DataFrame rows as namedtuples.
Parameters
----------
index : bool, default True
If True, return the index as the first element of the tuple.
name : str or None, default "Pandas"
The name of the returned namedtuples or None to return regular
... | itertuples | python | mars-project/mars | mars/dataframe/core.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/core.py | Apache-2.0 |
def assign(self, **kwargs):
"""
Assign new columns to a DataFrame.
Returns a new object with all original columns in addition to new ones.
Existing columns that are re-assigned will be overwritten.
Parameters
----------
**kwargs : dict of {str: callable or Series... |
Assign new columns to a DataFrame.
Returns a new object with all original columns in addition to new ones.
Existing columns that are re-assigned will be overwritten.
Parameters
----------
**kwargs : dict of {str: callable or Series}
The column names are keyw... | assign | python | mars-project/mars | mars/dataframe/core.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/core.py | Apache-2.0 |
def decide_dataframe_chunk_sizes(shape, chunk_size, memory_usage):
"""
Decide how a given DataFrame can be split into chunk.
:param shape: DataFrame's shape
:param chunk_size: if dict provided, it's dimension id to chunk size;
if provided, it's the chunk size for each dimension.
... |
Decide how a given DataFrame can be split into chunk.
:param shape: DataFrame's shape
:param chunk_size: if dict provided, it's dimension id to chunk size;
if provided, it's the chunk size for each dimension.
:param memory_usage: pandas Series in which each column's memory usage... | decide_dataframe_chunk_sizes | python | mars-project/mars | mars/dataframe/utils.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/utils.py | Apache-2.0 |
def split_monotonic_index_min_max(
left_min_max, left_increase, right_min_max, right_increase
):
"""
Split the original two min_max into new min_max. Each min_max should be a list
in which each item should be a 4-tuple indicates that this chunk's min value,
whether the min value is close, the max va... |
Split the original two min_max into new min_max. Each min_max should be a list
in which each item should be a 4-tuple indicates that this chunk's min value,
whether the min value is close, the max value, and whether the max value is close.
The return value would be a nested list, each item is a list
... | split_monotonic_index_min_max | python | mars-project/mars | mars/dataframe/utils.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/utils.py | Apache-2.0 |
def merge_index_value(to_merge_index_values: dict, store_data: bool = False):
"""
Merge index value according to their chunk index.
Parameters
----------
to_merge_index_values : dict
index to index_value
store_data : bool
store data in index_value
Returns
-------
me... |
Merge index value according to their chunk index.
Parameters
----------
to_merge_index_values : dict
index to index_value
store_data : bool
store data in index_value
Returns
-------
merged_index_value
| merge_index_value | python | mars-project/mars | mars/dataframe/utils.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/utils.py | Apache-2.0 |
def in_range_index(i, pd_range_index):
"""
Check whether the input `i` is within `pd_range_index` which is a pd.RangeIndex.
"""
start, stop, step = (
_get_range_index_start(pd_range_index),
_get_range_index_stop(pd_range_index),
_get_range_index_step(pd_range_index),
)
if... |
Check whether the input `i` is within `pd_range_index` which is a pd.RangeIndex.
| in_range_index | python | mars-project/mars | mars/dataframe/utils.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/utils.py | Apache-2.0 |
def validate_axis_style_args(
data, args, kwargs, arg_name, method_name
): # pragma: no cover
"""Argument handler for mixed index, columns / axis functions
In an attempt to handle both `.method(index, columns)`, and
`.method(arg, axis=.)`, we have to do some bad things to argument
parsing. This tr... | Argument handler for mixed index, columns / axis functions
In an attempt to handle both `.method(index, columns)`, and
`.method(arg, axis=.)`, we have to do some bad things to argument
parsing. This translates all arguments to `{index=., columns=.}` style.
Parameters
----------
data : DataFram... | validate_axis_style_args | python | mars-project/mars | mars/dataframe/utils.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/utils.py | Apache-2.0 |
def fetch_corner_data(df_or_series, session=None) -> pd.DataFrame:
"""
Fetch corner DataFrame or Series for repr usage.
:param df_or_series: DataFrame or Series
:return: corner DataFrame
"""
from .indexing.iloc import iloc
max_rows = pd.get_option("display.max_rows")
try:
min_r... |
Fetch corner DataFrame or Series for repr usage.
:param df_or_series: DataFrame or Series
:return: corner DataFrame
| fetch_corner_data | python | mars-project/mars | mars/dataframe/utils.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/utils.py | Apache-2.0 |
def patch_sa_engine_execute():
"""
pandas did not resolve compatibility issue of sqlalchemy 2.0, the issue
is https://github.com/pandas-dev/pandas/issues/40686. We need to patch
Engine class in SQLAlchemy, and then our code can work well.
"""
try:
from sqlalchemy.engine import Engine
... |
pandas did not resolve compatibility issue of sqlalchemy 2.0, the issue
is https://github.com/pandas-dev/pandas/issues/40686. We need to patch
Engine class in SQLAlchemy, and then our code can work well.
| patch_sa_engine_execute | python | mars-project/mars | mars/dataframe/utils.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/utils.py | Apache-2.0 |
def df_apply(
df,
func,
axis=0,
raw=False,
result_type=None,
args=(),
dtypes=None,
dtype=None,
name=None,
output_type=None,
index=None,
elementwise=None,
skip_infer=False,
**kwds,
):
"""
Apply a function along an axis of the DataFrame.
Objects passed ... |
Apply a function along an axis of the DataFrame.
Objects passed to the function are Series objects whose index is
either the DataFrame's index (``axis=0``) or the DataFrame's columns
(``axis=1``). By default (``result_type=None``), the final return type
is inferred from the return type of the appl... | df_apply | python | mars-project/mars | mars/dataframe/base/apply.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/apply.py | Apache-2.0 |
def series_apply(
series,
func,
convert_dtype=True,
output_type=None,
args=(),
dtypes=None,
dtype=None,
name=None,
index=None,
skip_infer=False,
**kwds,
):
"""
Invoke function on values of Series.
Can be ufunc (a NumPy function that applies to the entire Series)
... |
Invoke function on values of Series.
Can be ufunc (a NumPy function that applies to the entire Series)
or a Python function that only works on single values.
Parameters
----------
func : function
Python function or NumPy ufunc to apply.
convert_dtype : bool, default True
... | series_apply | python | mars-project/mars | mars/dataframe/base/apply.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/apply.py | Apache-2.0 |
def astype(df, dtype, copy=True, errors="raise"):
"""
Cast a pandas object to a specified dtype ``dtype``.
Parameters
----------
dtype : data type, or dict of column name -> data type
Use a numpy.dtype or Python type to cast entire pandas object to
the same type. Alternatively, use ... |
Cast a pandas object to a specified dtype ``dtype``.
Parameters
----------
dtype : data type, or dict of column name -> data type
Use a numpy.dtype or Python type to cast entire pandas object to
the same type. Alternatively, use {col: dtype, ...}, where col is a
column label an... | astype | python | mars-project/mars | mars/dataframe/base/astype.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/astype.py | Apache-2.0 |
def filter_by_bloom_filter(
df1: TileableType,
df2: TileableType,
left_on: Union[str, List],
right_on: Union[str, List],
max_elements: int = 10000,
error_rate: float = 0.1,
combine_size: int = None,
):
"""
Use bloom filter to filter DataFrame.
Parameters
----------
df1: ... |
Use bloom filter to filter DataFrame.
Parameters
----------
df1: DataFrame.
DataFrame to be filtered.
df2: DataFrame.
Dataframe to build filter.
left_on: str or list.
Column(s) selected on df1.
right_on: str or list.
Column(s) selected on df2.
max_elemen... | filter_by_bloom_filter | python | mars-project/mars | mars/dataframe/base/bloom_filter.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/bloom_filter.py | Apache-2.0 |
def cut(
x,
bins,
right: bool = True,
labels=None,
retbins: bool = False,
precision: int = 3,
include_lowest: bool = False,
duplicates: str = "raise",
ordered: bool = True,
):
"""
Bin values into discrete intervals.
Use `cut` when you need to segment and sort data values... |
Bin values into discrete intervals.
Use `cut` when you need to segment and sort data values into bins. This
function is also useful for going from a continuous variable to a
categorical variable. For example, `cut` could convert ages to groups of
age ranges. Supports binning into an equal number o... | cut | python | mars-project/mars | mars/dataframe/base/cut.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/cut.py | Apache-2.0 |
def df_diff(df, periods=1, axis=0):
"""
First discrete difference of element.
Calculates the difference of a DataFrame element compared with another
element in the DataFrame (default is the element in the same column
of the previous row).
Parameters
----------
periods : int, default 1
... |
First discrete difference of element.
Calculates the difference of a DataFrame element compared with another
element in the DataFrame (default is the element in the same column
of the previous row).
Parameters
----------
periods : int, default 1
Periods to shift for calculating dif... | df_diff | python | mars-project/mars | mars/dataframe/base/diff.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/diff.py | Apache-2.0 |
def df_pop(df, item):
"""
Return item and drop from frame. Raise KeyError if not found.
Parameters
----------
item : str
Label of column to be popped.
Returns
-------
Series
Examples
--------
>>> import numpy as np
>>> import mars.dataframe as md
>>> df = m... |
Return item and drop from frame. Raise KeyError if not found.
Parameters
----------
item : str
Label of column to be popped.
Returns
-------
Series
Examples
--------
>>> import numpy as np
>>> import mars.dataframe as md
>>> df = md.DataFrame([('falcon', 'bird... | df_pop | python | mars-project/mars | mars/dataframe/base/drop.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/drop.py | Apache-2.0 |
def series_drop(
series,
labels=None,
axis=0,
index=None,
columns=None,
level=None,
inplace=False,
errors="raise",
):
"""
Return Series with specified index labels removed.
Remove elements of a Series based on specifying the index labels.
When using a multi-index, labels... |
Return Series with specified index labels removed.
Remove elements of a Series based on specifying the index labels.
When using a multi-index, labels on different levels can be removed
by specifying the level.
Parameters
----------
labels : single label or list-like
Index labels t... | series_drop | python | mars-project/mars | mars/dataframe/base/drop.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/drop.py | Apache-2.0 |
def series_drop_duplicates(series, keep="first", inplace=False, method="auto"):
"""
Return Series with duplicate values removed.
Parameters
----------
keep : {'first', 'last', ``False``}, default 'first'
Method to handle dropping duplicates:
- 'first' : Drop duplicates except for t... |
Return Series with duplicate values removed.
Parameters
----------
keep : {'first', 'last', ``False``}, default 'first'
Method to handle dropping duplicates:
- 'first' : Drop duplicates except for the first occurrence.
- 'last' : Drop duplicates except for the last occurrence.... | series_drop_duplicates | python | mars-project/mars | mars/dataframe/base/drop_duplicates.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/drop_duplicates.py | Apache-2.0 |
def index_drop_duplicates(index, keep="first", method="auto"):
"""
Return Index with duplicate values removed.
Parameters
----------
keep : {'first', 'last', ``False``}, default 'first'
- 'first' : Drop duplicates except for the first occurrence.
- 'last' : Drop duplicates except fo... |
Return Index with duplicate values removed.
Parameters
----------
keep : {'first', 'last', ``False``}, default 'first'
- 'first' : Drop duplicates except for the first occurrence.
- 'last' : Drop duplicates except for the last occurrence.
- ``False`` : Drop all duplicates.
... | index_drop_duplicates | python | mars-project/mars | mars/dataframe/base/drop_duplicates.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/drop_duplicates.py | Apache-2.0 |
def df_duplicated(df, subset=None, keep="first", method="auto"):
"""
Return boolean Series denoting duplicate rows.
Considering certain columns is optional.
Parameters
----------
subset : column label or sequence of labels, optional
Only consider certain columns for identifying duplica... |
Return boolean Series denoting duplicate rows.
Considering certain columns is optional.
Parameters
----------
subset : column label or sequence of labels, optional
Only consider certain columns for identifying duplicates, by
default use all of the columns.
keep : {'first', 'la... | df_duplicated | python | mars-project/mars | mars/dataframe/base/duplicated.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/duplicated.py | Apache-2.0 |
def series_duplicated(series, keep="first", method="auto"):
"""
Indicate duplicate Series values.
Duplicated values are indicated as ``True`` values in the resulting
Series. Either all duplicates, all except the first or all except the
last occurrence of duplicates can be indicated.
Parameters... |
Indicate duplicate Series values.
Duplicated values are indicated as ``True`` values in the resulting
Series. Either all duplicates, all except the first or all except the
last occurrence of duplicates can be indicated.
Parameters
----------
keep : {'first', 'last', False}, default 'first... | series_duplicated | python | mars-project/mars | mars/dataframe/base/duplicated.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/duplicated.py | Apache-2.0 |
def mars_eval(
expr,
parser="mars",
engine=None,
local_dict=None,
global_dict=None,
resolvers=(),
level=0,
target=None,
inplace=False,
):
"""
Evaluate a Python expression as a string using various backends.
The following arithmetic operations are supported: ``+``, ``-``... |
Evaluate a Python expression as a string using various backends.
The following arithmetic operations are supported: ``+``, ``-``, ``*``,
``/``, ``**``, ``%``, ``//`` (python engine only) along with the following
boolean operations: ``|`` (or), ``&`` (and), and ``~`` (not).
Additionally, the ``'pa... | mars_eval | python | mars-project/mars | mars/dataframe/base/eval.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/eval.py | Apache-2.0 |
def df_eval(df, expr, inplace=False, **kwargs):
"""
Evaluate a string describing operations on DataFrame columns.
Operates on columns only, not specific rows or elements. This allows
`eval` to run arbitrary code, which can make you vulnerable to code
injection if you pass user input to this functi... |
Evaluate a string describing operations on DataFrame columns.
Operates on columns only, not specific rows or elements. This allows
`eval` to run arbitrary code, which can make you vulnerable to code
injection if you pass user input to this function.
Parameters
----------
expr : str
... | df_eval | python | mars-project/mars | mars/dataframe/base/eval.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/eval.py | Apache-2.0 |
def df_query(df, expr, inplace=False, **kwargs):
"""
Query the columns of a DataFrame with a boolean expression.
Parameters
----------
expr : str
The query string to evaluate.
You can refer to variables
in the environment by prefixing them with an '@' character like
... |
Query the columns of a DataFrame with a boolean expression.
Parameters
----------
expr : str
The query string to evaluate.
You can refer to variables
in the environment by prefixing them with an '@' character like
``@a + b``.
You can refer to column names that... | df_query | python | mars-project/mars | mars/dataframe/base/eval.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/eval.py | Apache-2.0 |
def series_isin(elements, values):
"""
Whether elements in Series are contained in `values`.
Return a boolean Series showing whether each element in the Series
matches an element in the passed sequence of `values` exactly.
Parameters
----------
values : set or list-like
The sequenc... |
Whether elements in Series are contained in `values`.
Return a boolean Series showing whether each element in the Series
matches an element in the passed sequence of `values` exactly.
Parameters
----------
values : set or list-like
The sequence of values to test. Passing in a single s... | series_isin | python | mars-project/mars | mars/dataframe/base/isin.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/isin.py | Apache-2.0 |
def df_isin(df, values):
"""
Whether each element in the DataFrame is contained in values.
Parameters
----------
values : iterable, Series, DataFrame or dict
The result will only be true at a location if all the
labels match. If `values` is a Series, that's the index. If
`va... |
Whether each element in the DataFrame is contained in values.
Parameters
----------
values : iterable, Series, DataFrame or dict
The result will only be true at a location if all the
labels match. If `values` is a Series, that's the index. If
`values` is a dict, the keys must b... | df_isin | python | mars-project/mars | mars/dataframe/base/isin.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/isin.py | Apache-2.0 |
def series_map(
series, arg, na_action=None, dtype=None, memory_scale=None, skip_infer=False
):
"""
Map values of Series according to input correspondence.
Used for substituting each value in a Series with another value,
that may be derived from a function, a ``dict`` or
a :class:`Series`.
... |
Map values of Series according to input correspondence.
Used for substituting each value in a Series with another value,
that may be derived from a function, a ``dict`` or
a :class:`Series`.
Parameters
----------
arg : function, collections.abc.Mapping subclass or Series
Mapping c... | series_map | python | mars-project/mars | mars/dataframe/base/map.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/map.py | Apache-2.0 |
def index_map(
idx, mapper, na_action=None, dtype=None, memory_scale=None, skip_infer=False
):
"""
Map values using input correspondence (a dict, Series, or function).
Parameters
----------
mapper : function, dict, or Series
Mapping correspondence.
na_action : {None, 'ignore'}
... |
Map values using input correspondence (a dict, Series, or function).
Parameters
----------
mapper : function, dict, or Series
Mapping correspondence.
na_action : {None, 'ignore'}
If 'ignore', propagate NA values, without passing them to the
mapping correspondence.
dtype... | index_map | python | mars-project/mars | mars/dataframe/base/map.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/map.py | Apache-2.0 |
def map_chunk(df_or_series, func, args=(), kwargs=None, skip_infer=False, **kw):
"""
Apply function to each chunk.
Parameters
----------
func : function
Function to apply to each chunk.
args : tuple
Positional arguments to pass to func in addition to the array/series.
kwargs... |
Apply function to each chunk.
Parameters
----------
func : function
Function to apply to each chunk.
args : tuple
Positional arguments to pass to func in addition to the array/series.
kwargs: Dict
Additional keyword arguments to pass as keywords arguments to func.
s... | map_chunk | python | mars-project/mars | mars/dataframe/base/map_chunk.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/map_chunk.py | Apache-2.0 |
def melt(
frame,
id_vars=None,
value_vars=None,
var_name=None,
value_name="value",
col_level=None,
):
"""
Unpivot a DataFrame from wide to long format, optionally leaving identifiers set.
This function is useful to massage a DataFrame into a format where one
or more columns are ... |
Unpivot a DataFrame from wide to long format, optionally leaving identifiers set.
This function is useful to massage a DataFrame into a format where one
or more columns are identifier variables (`id_vars`), while all other
columns, considered measured variables (`value_vars`), are "unpivoted" to
t... | melt | python | mars-project/mars | mars/dataframe/base/melt.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/melt.py | Apache-2.0 |
def _adapt_index(self, input_index, index=0):
"""
When ``index=True`` is passed, an extra column will be prepended to the result series
Thus we need to update the index of initial chunk for returned dataframe chunks
"""
if not self.index or index != 0:
return input_in... |
When ``index=True`` is passed, an extra column will be prepended to the result series
Thus we need to update the index of initial chunk for returned dataframe chunks
| _adapt_index | python | mars-project/mars | mars/dataframe/base/memory_usage.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/memory_usage.py | Apache-2.0 |
def _adapt_nsplits(self, input_nsplit):
"""
When ``index=True`` is passed, the size of returned series is one element larger
than the number of columns, which affects ``nsplits``.
"""
if not self.index:
return (input_nsplit[-1],)
nsplits_list = list(input_nspl... |
When ``index=True`` is passed, the size of returned series is one element larger
than the number of columns, which affects ``nsplits``.
| _adapt_nsplits | python | mars-project/mars | mars/dataframe/base/memory_usage.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/memory_usage.py | Apache-2.0 |
def _tile_single(cls, op: "DataFrameMemoryUsage"):
"""
Tile when input data has only one chunk on rows
"""
df_or_series = op.inputs[0]
output = op.outputs[0]
chunks = []
for c in df_or_series.chunks:
new_op = op.copy().reset_key()
if c.ndi... |
Tile when input data has only one chunk on rows
| _tile_single | python | mars-project/mars | mars/dataframe/base/memory_usage.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/memory_usage.py | Apache-2.0 |
def qcut(x, q, labels=None, retbins=False, precision=3, duplicate="raise"):
"""
Quantile-based discretization function.
Discretize variable into equal-sized buckets based on rank or based
on sample quantiles. For example 1000 values for 10 quantiles would
produce a Categorical object indicating qua... |
Quantile-based discretization function.
Discretize variable into equal-sized buckets based on rank or based
on sample quantiles. For example 1000 values for 10 quantiles would
produce a Categorical object indicating quantile membership for each data point.
Parameters
----------
x : 1d ten... | qcut | python | mars-project/mars | mars/dataframe/base/qcut.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/qcut.py | Apache-2.0 |
def rebalance(
df_or_series, factor=None, axis=0, num_partitions=None, reassign_worker=True
):
"""
Make Data more balanced across entire cluster.
Parameters
----------
factor : float
Specified so that number of chunks after balance is
total CPU count of cluster * factor.
axi... |
Make Data more balanced across entire cluster.
Parameters
----------
factor : float
Specified so that number of chunks after balance is
total CPU count of cluster * factor.
axis : int
The axis to rebalance.
num_partitions : int
Specified so the number of chunks ... | rebalance | python | mars-project/mars | mars/dataframe/base/rebalance.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/rebalance.py | Apache-2.0 |
def select_dtypes(df, include=None, exclude=None):
"""
Return a subset of the DataFrame's columns based on the column dtypes.
Parameters
----------
include, exclude : scalar or list-like
A selection of dtypes or strings to be included/excluded. At least
one of these parameters must ... |
Return a subset of the DataFrame's columns based on the column dtypes.
Parameters
----------
include, exclude : scalar or list-like
A selection of dtypes or strings to be included/excluded. At least
one of these parameters must be supplied.
Returns
-------
DataFrame
... | select_dtypes | python | mars-project/mars | mars/dataframe/base/select_dtypes.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/select_dtypes.py | Apache-2.0 |
def shift(df_or_series, periods=1, freq=None, axis=0, fill_value=None):
"""
Shift index by desired number of periods with an optional time `freq`.
When `freq` is not passed, shift the index without realigning the data.
If `freq` is passed (in this case, the index must be date or datetime,
or it wil... |
Shift index by desired number of periods with an optional time `freq`.
When `freq` is not passed, shift the index without realigning the data.
If `freq` is passed (in this case, the index must be date or datetime,
or it will raise a `NotImplementedError`), the index will be
increased using the per... | shift | python | mars-project/mars | mars/dataframe/base/shift.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/shift.py | Apache-2.0 |
def df_transform(df, func, axis=0, *args, dtypes=None, skip_infer=False, **kwargs):
"""
Call ``func`` on self producing a DataFrame with transformed values.
Produced DataFrame will have same axis length as self.
Parameters
----------
func : function, str, list or dict
Function to use f... |
Call ``func`` on self producing a DataFrame with transformed values.
Produced DataFrame will have same axis length as self.
Parameters
----------
func : function, str, list or dict
Function to use for transforming the data. If a function, must either
work when passed a DataFrame o... | df_transform | python | mars-project/mars | mars/dataframe/base/transform.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/transform.py | Apache-2.0 |
def series_transform(
series,
func,
convert_dtype=True,
axis=0,
*args,
skip_infer=False,
dtype=None,
**kwargs
):
"""
Call ``func`` on self producing a Series with transformed values.
Produced Series will have same axis length as self.
Parameters
----------
func ... |
Call ``func`` on self producing a Series with transformed values.
Produced Series will have same axis length as self.
Parameters
----------
func : function, str, list or dict
Function to use for transforming the data. If a function, must either
work when passed a Series or when passed to ... | series_transform | python | mars-project/mars | mars/dataframe/base/transform.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/transform.py | Apache-2.0 |
def value_counts(
series,
normalize=False,
sort=True,
ascending=False,
bins=None,
dropna=True,
method="auto",
):
"""
Return a Series containing counts of unique values.
The resulting object will be in descending order so that the
first element is the most frequently-occurrin... |
Return a Series containing counts of unique values.
The resulting object will be in descending order so that the
first element is the most frequently-occurring element.
Excludes NA values by default.
Parameters
----------
normalize : bool, default False
If True then the object ret... | value_counts | python | mars-project/mars | mars/dataframe/base/value_counts.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/base/value_counts.py | Apache-2.0 |
def to_ray_dataset(df, num_shards: int = None):
"""Create a Ray Dataset from Mars DataFrame
Args:
df (mars.dataframe.Dataframe): the Mars DataFrame
num_shards (int, optional): the number of shards that will be created
for the Ray Dataset. Defaults to None.
If num_shards ... | Create a Ray Dataset from Mars DataFrame
Args:
df (mars.dataframe.Dataframe): the Mars DataFrame
num_shards (int, optional): the number of shards that will be created
for the Ray Dataset. Defaults to None.
If num_shards is None, chunks will be grouped by nodes where they lie... | to_ray_dataset | python | mars-project/mars | mars/dataframe/contrib/raydataset/dataset.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/contrib/raydataset/dataset.py | Apache-2.0 |
def __init__(self, shard_id: int, obj_refs: "ray.ObjectRef"):
"""Iterable batch holding a list of ray.ObjectRefs.
Args:
shard_id (int): id of the shard
prefix (str): prefix name of the batch
obj_refs (List[ray.ObjectRefs]): list of ray.ObjectRefs
"""
... | Iterable batch holding a list of ray.ObjectRefs.
Args:
shard_id (int): id of the shard
prefix (str): prefix name of the batch
obj_refs (List[ray.ObjectRefs]): list of ray.ObjectRefs
| __init__ | python | mars-project/mars | mars/dataframe/contrib/raydataset/mldataset.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/contrib/raydataset/mldataset.py | Apache-2.0 |
def _group_chunk_refs(
chunk_addr_refs: List[Tuple[Tuple, "ray.ObjectRef"]], num_shards: int
):
"""Group fetched ray.ObjectRefs into a dict for later use.
Args:
chunk_addr_refs (List[Tuple[Tuple, ray.ObjectRef]]): a list of tuples of
band & ray.ObjectRef of each chunk.
num_shard... | Group fetched ray.ObjectRefs into a dict for later use.
Args:
chunk_addr_refs (List[Tuple[Tuple, ray.ObjectRef]]): a list of tuples of
band & ray.ObjectRef of each chunk.
num_shards (int): the number of shards that will be created for the MLDataset.
Returns:
Dict[str, List[... | _group_chunk_refs | python | mars-project/mars | mars/dataframe/contrib/raydataset/mldataset.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/contrib/raydataset/mldataset.py | Apache-2.0 |
def to_ray_mldataset(df, num_shards: int = None):
"""Create a MLDataset from Mars DataFrame
Args:
df (mars.dataframe.Dataframe): the Mars DataFrame
num_shards (int, optional): the number of shards that will be created
for the MLDataset. Defaults to None.
If num_shards is... | Create a MLDataset from Mars DataFrame
Args:
df (mars.dataframe.Dataframe): the Mars DataFrame
num_shards (int, optional): the number of shards that will be created
for the MLDataset. Defaults to None.
If num_shards is None, chunks will be grouped by nodes where they lie.
... | to_ray_mldataset | python | mars-project/mars | mars/dataframe/contrib/raydataset/mldataset.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/contrib/raydataset/mldataset.py | Apache-2.0 |
def _infer_tz_from_endpoints(start, end, tz): # pragma: no cover
"""
If a timezone is not explicitly given via `tz`, see if one can
be inferred from the `start` and `end` endpoints. If more than one
of these inputs provides a timezone, require that they all agree.
Parameters
----------
st... |
If a timezone is not explicitly given via `tz`, see if one can
be inferred from the `start` and `end` endpoints. If more than one
of these inputs provides a timezone, require that they all agree.
Parameters
----------
start : Timestamp
end : Timestamp
tz : tzinfo or None
Returns
... | _infer_tz_from_endpoints | python | mars-project/mars | mars/dataframe/datasource/date_range.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/datasource/date_range.py | Apache-2.0 |
def _maybe_localize_point(
ts, is_none, is_not_none, freq, tz, ambiguous, nonexistent
): # pragma: no cover
"""
Localize a start or end Timestamp to the timezone of the corresponding
start or end Timestamp
Parameters
----------
ts : start or end Timestamp to potentially localize
is_non... |
Localize a start or end Timestamp to the timezone of the corresponding
start or end Timestamp
Parameters
----------
ts : start or end Timestamp to potentially localize
is_none : argument that should be None
is_not_none : argument that should not be None
freq : Tick, DateOffset, or None... | _maybe_localize_point | python | mars-project/mars | mars/dataframe/datasource/date_range.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/datasource/date_range.py | Apache-2.0 |
def read_parquet(
path,
engine: str = "auto",
columns: list = None,
groups_as_chunks: bool = False,
use_arrow_dtype: bool = None,
incremental_index: bool = False,
storage_options: dict = None,
memory_scale: int = None,
merge_small_files: bool = True,
merge_small_file_options: dic... |
Load a parquet object from the file path, returning a DataFrame.
Parameters
----------
path : str, path object or file-like object
Any valid string path is acceptable. The string could be a URL.
For file URLs, a host is expected. A local file could be:
``file://localhost/path/t... | read_parquet | python | mars-project/mars | mars/dataframe/datasource/read_parquet.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/datasource/read_parquet.py | Apache-2.0 |
def _update_key(self):
"""We can't direct generate token for mldataset when we use
ray client, so we use all mldataset's actor_id to generate
token.
"""
datas = []
for value in self._values_:
if isinstance(value, ray.util.data.MLDataset):
actor... | We can't direct generate token for mldataset when we use
ray client, so we use all mldataset's actor_id to generate
token.
| _update_key | python | mars-project/mars | mars/dataframe/datasource/read_raydataset.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/datasource/read_raydataset.py | Apache-2.0 |
def to_parquet(
df,
path,
engine="auto",
compression="snappy",
index=None,
partition_cols=None,
storage_options: dict = None,
**kwargs,
):
"""
Write a DataFrame to the binary parquet format, each chunk will be
written to a Parquet file.
Parameters
----------
path... |
Write a DataFrame to the binary parquet format, each chunk will be
written to a Parquet file.
Parameters
----------
path : str or file-like object
If path is a string with wildcard e.g. '/to/path/out-*.parquet',
`to_parquet` will try to write multiple files, for instance,
c... | to_parquet | python | mars-project/mars | mars/dataframe/datastore/to_parquet.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/datastore/to_parquet.py | Apache-2.0 |
def to_sql(
df,
name: str,
con,
schema=None,
if_exists: str = "fail",
index: bool = True,
index_label=None,
chunksize=None,
dtype=None,
method=None,
):
"""
Write records stored in a DataFrame to a SQL database.
Databases supported by SQLAlchemy [1]_ are supported. Ta... |
Write records stored in a DataFrame to a SQL database.
Databases supported by SQLAlchemy [1]_ are supported. Tables can be
newly created, appended to, or overwritten.
Parameters
----------
name : str
Name of SQL table.
con : sqlalchemy.engine.Engine or sqlite3.Connection
U... | to_sql | python | mars-project/mars | mars/dataframe/datastore/to_sql.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/datastore/to_sql.py | Apache-2.0 |
def agg(groupby, func=None, method="auto", combine_size=None, *args, **kwargs):
"""
Aggregate using one or more operations on grouped data.
Parameters
----------
groupby : Mars Groupby
Groupby data.
func : str or list-like
Aggregation functions.
method : {'auto', 'shuffle', ... |
Aggregate using one or more operations on grouped data.
Parameters
----------
groupby : Mars Groupby
Groupby data.
func : str or list-like
Aggregation functions.
method : {'auto', 'shuffle', 'tree'}, default 'auto'
'tree' method provide a better performance, 'shuffle' i... | agg | python | mars-project/mars | mars/dataframe/groupby/aggregation.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/groupby/aggregation.py | Apache-2.0 |
def groupby_apply(
groupby,
func,
*args,
output_type=None,
dtypes=None,
dtype=None,
name=None,
index=None,
skip_infer=None,
**kwargs,
):
"""
Apply function `func` group-wise and combine the results together.
The function passed to `apply` must take a dataframe as its... |
Apply function `func` group-wise and combine the results together.
The function passed to `apply` must take a dataframe as its first
argument and return a DataFrame, Series or scalar. `apply` will
then take care of combining the results back together into a single
dataframe or series. `apply` is t... | groupby_apply | python | mars-project/mars | mars/dataframe/groupby/apply.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/groupby/apply.py | Apache-2.0 |
def execute_map(cls, op, in_data: pd.DataFrame) -> Union[pd.DataFrame, pd.Series]:
"""
Map stage implement.
Parameters
-------
op : Any operand
DataFrame operand.
in_data : pd.DataFrame
Input dataframe.
Returns
-------
... |
Map stage implement.
Parameters
-------
op : Any operand
DataFrame operand.
in_data : pd.DataFrame
Input dataframe.
Returns
-------
The result of op map stage.
| execute_map | python | mars-project/mars | mars/dataframe/groupby/custom_aggregation.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/groupby/custom_aggregation.py | Apache-2.0 |
def execute_combine(
cls, op, in_data: pd.DataFrame
) -> Union[pd.DataFrame, pd.Series]:
"""
Combine stage implement.
Parameters
----------
op : Any operand
DataFrame operand.
in_data : pd.Dataframe
Input dataframe.
Returns
... |
Combine stage implement.
Parameters
----------
op : Any operand
DataFrame operand.
in_data : pd.Dataframe
Input dataframe.
Returns
-------
The result of op combine stage.
| execute_combine | python | mars-project/mars | mars/dataframe/groupby/custom_aggregation.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/groupby/custom_aggregation.py | Apache-2.0 |
def execute_agg(cls, op, in_data: pd.DataFrame) -> Union[pd.DataFrame, pd.Series]:
"""
Agg stage implement.
Parameters
----------
op : Any operand
DataFrame operand.
in_data : pd.Dataframe
Input dataframe.
Returns
-------
... |
Agg stage implement.
Parameters
----------
op : Any operand
DataFrame operand.
in_data : pd.Dataframe
Input dataframe.
Returns
-------
The result of op agg stage.
| execute_agg | python | mars-project/mars | mars/dataframe/groupby/custom_aggregation.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/groupby/custom_aggregation.py | Apache-2.0 |
def head(groupby, n=5):
"""
Return first n rows of each group.
Similar to ``.apply(lambda x: x.head(n))``, but it returns a subset of rows
from the original Series or DataFrame with original index and order preserved
(``as_index`` flag is ignored).
Does not work for negative values of `n`.
... |
Return first n rows of each group.
Similar to ``.apply(lambda x: x.head(n))``, but it returns a subset of rows
from the original Series or DataFrame with original index and order preserved
(``as_index`` flag is ignored).
Does not work for negative values of `n`.
Returns
-------
Serie... | head | python | mars-project/mars | mars/dataframe/groupby/head.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/groupby/head.py | Apache-2.0 |
def _get_level_indexes(
cls, op: DataFrameGroupByAgg, data: pd.DataFrame
) -> List[int]:
"""
When group by level, get the level index list.
Level can be int, level name, or sequence of such.
This function calculates the corresponding indexes.
Parameters
------... |
When group by level, get the level index list.
Level can be int, level name, or sequence of such.
This function calculates the corresponding indexes.
Parameters
----------
op
data
Returns
-------
| _get_level_indexes | python | mars-project/mars | mars/dataframe/groupby/nunique.py | https://github.com/mars-project/mars/blob/master/mars/dataframe/groupby/nunique.py | Apache-2.0 |
Subsets and Splits
Django Code with Docstrings
Filters Python code examples from Django repository that contain Django-related code, helping identify relevant code snippets for understanding Django framework usage patterns.
SQL Console for Shuu12121/python-treesitter-filtered-datasetsV2
Retrieves specific code examples from the Flask repository but doesn't provide meaningful analysis or patterns beyond basic data retrieval.
HTTPX Repo Code and Docstrings
Retrieves specific code examples from the httpx repository, which is useful for understanding how particular libraries are used but doesn't provide broader analytical insights about the dataset.
Requests Repo Docstrings & Code
Retrieves code examples with their docstrings and file paths from the requests repository, providing basic filtering but limited analytical value beyond finding specific code samples.
Quart Repo Docstrings & Code
Retrieves code examples with their docstrings from the Quart repository, providing basic code samples but offering limited analytical value for understanding broader patterns or relationships in the dataset.