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ORPA-pyOpenRPA/WPy32-3720/python-3.7.2/Lib/site-packages/dask/bag/text.py

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from __future__ import print_function, division, absolute_import
import io
import os
from toolz import concat
from ..compatibility import unicode
from ..utils import system_encoding, parse_bytes
from ..delayed import delayed
from ..bytes import open_files, read_bytes
from .core import from_delayed
delayed = delayed(pure=True)
def read_text(urlpath, blocksize=None, compression='infer',
encoding=system_encoding, errors='strict',
linedelimiter=os.linesep, collection=True,
storage_options=None, files_per_partition=None):
""" Read lines from text files
Parameters
----------
urlpath : string or list
Absolute or relative filepath(s). Prefix with a protocol like ``s3://``
to read from alternative filesystems. To read from multiple files you
can pass a globstring or a list of paths, with the caveat that they
must all have the same protocol.
blocksize: None, int, or str
Size (in bytes) to cut up larger files. Streams by default.
Can be ``None`` for streaming, an integer number of bytes, or a string
like "128MiB"
compression: string
Compression format like 'gzip' or 'xz'. Defaults to 'infer'
encoding: string
errors: string
linedelimiter: string
collection: bool, optional
Return dask.bag if True, or list of delayed values if false
storage_options: dict
Extra options that make sense to a particular storage connection, e.g.
host, port, username, password, etc.
files_per_partition: None or int
If set, group input files into partitions of the requested size,
instead of one partition per file. Mutually exclusive with blocksize.
Examples
--------
>>> b = read_text('myfiles.1.txt') # doctest: +SKIP
>>> b = read_text('myfiles.*.txt') # doctest: +SKIP
>>> b = read_text('myfiles.*.txt.gz') # doctest: +SKIP
>>> b = read_text('s3://bucket/myfiles.*.txt') # doctest: +SKIP
>>> b = read_text('s3://key:secret@bucket/myfiles.*.txt') # doctest: +SKIP
>>> b = read_text('hdfs://namenode.example.com/myfiles.*.txt') # doctest: +SKIP
Parallelize a large file by providing the number of uncompressed bytes to
load into each partition.
>>> b = read_text('largefile.txt', blocksize='10MB') # doctest: +SKIP
Returns
-------
dask.bag.Bag if collection is True or list of Delayed lists otherwise
See Also
--------
from_sequence: Build bag from Python sequence
"""
if blocksize is not None and files_per_partition is not None:
raise ValueError('Only one of blocksize or files_per_partition can be set')
if isinstance(blocksize, (str, unicode)):
blocksize = parse_bytes(blocksize)
files = open_files(urlpath, mode='rt', encoding=encoding,
errors=errors, compression=compression,
**(storage_options or {}))
if blocksize is None:
if files_per_partition is None:
blocks = [delayed(list)(delayed(file_to_blocks)(fil)) for fil in files]
else:
blocks = []
for start in range(0, len(files), files_per_partition):
block_files = files[start:(start + files_per_partition)]
block_lines = delayed(concat)(delayed(map)(file_to_blocks, block_files))
blocks.append(block_lines)
else:
_, blocks = read_bytes(urlpath, delimiter=linedelimiter.encode(),
blocksize=blocksize, sample=False,
compression=compression,
**(storage_options or {}))
blocks = [delayed(decode)(b, encoding, errors) for b in concat(blocks)]
if not blocks:
raise ValueError("No files found", urlpath)
if not collection:
return blocks
else:
return from_delayed(blocks)
def file_to_blocks(lazy_file):
with lazy_file as f:
for line in f:
yield line
def decode(block, encoding, errors):
text = block.decode(encoding, errors)
lines = io.StringIO(text)
return list(lines)