tabulator 0.10.1

Consistent interface for stream reading and writing tabular data (csv/xls/json/etc)

Consistent interface for stream reading and writing tabular data (csv/xls/json/etc).

Release v0.10 contains changes in exceptions module introduced in NOT backward-compatibility manner.

Features

• supports various formats: csv/tsv/xls/xlsx/json/ndjson/ods/native/etc

• reads data from variables, filesystem or Internet

• streams data instead of using a lot of memory

• processes data via simple user processors

• saves data using the same interface

Getting Started

Installation

To get started:

$ pip install tabulator

Example

Open tabular stream from csv source:

from tabulator import Stream

with Stream('path.csv', headers=1) as stream:
    print(stream.headers) # will print headers from 1 row
    for row in stream:
        print(row)  # will print row values list

Stream

Stream takes the source argument:

<scheme>://path/to/file.<format>

and uses corresponding Loader and Parser to open and start to iterate over the tabular stream. Also user can pass scheme and format explicitly as constructor arguments. User can force Tabulator to use encoding of choice to open the table passing encoding argument.

In this example we use context manager to call stream.open() on enter and stream.close() when we exit:

• stream can be iterated like file-like object returning row by row

• stream can be used for manual iterating with iter(keyed/extended) function

• stream can be read into memory using read(keyed/extended) function with row count limit

• headers can be accessed via headers property

• rows sample can be accessed via sample property

• stream pointer can be set to start via reset method

• stream could be saved to filesystem using save method

Below the more expanded example is presented:

from tabulator import Stream

def skip_even_rows(extended_rows):
    for number, headers, row in extended_rows:
        if number % 2:
            yield (number, headers, row)

stream = Stream('http://example.com/source.xls',
    headers=1, encoding='utf-8', sample_size=1000,
    post_parse=[skip_even_rows], sheet=1)
stream.open()
print(stream.sample)  # will print sample
print(stream.headers)  # will print headers list
print(stream.read(limit=10))  # will print 10 rows
stream.reset()
for keyed_row in stream.iter(keyed=True):
    print keyed_row  # will print row dict
for extended_row in stream.iter(extended=True):
    print extended_row  # will print (number, headers, row)
stream.reset()
stream.save('target.csv')
stream.close()

For the full list of options see - https://github.com/frictionlessdata/tabulator-py/blob/master/tabulator/stream.py#L17

API Reference

Snapshot

Stream(source,
       headers=None,
       scheme=None,
       format=None,
       encoding=None,
       sample_size=None,
       post_parse=None,
       **options)
    closed/open/close/reset
    headers -> list
    sample -> rows
    iter(keyed/extended=False) -> (generator) (keyed/extended)row[]
    read(keyed/extended=False, limit=None) -> (keyed/extended)row[]
    save(target, format=None, encoding=None, **options)
exceptions
~cli

Detailed

• Docstrings

• Changelog

Contributing

Please read the contribution guideline:

How to Contribute

Thanks!