pytubes 0.5.5

A library for efficiently loading data into Python

pytubes
=======

A library for loading data into Python

.. toctree::
:caption: Contents
:maxdepth: 2
:name: mastertoc

tubes
detail

Simple Example
--------------

>>> from tubes import Each
>>> import glob
>>> tube = (Each(glob.glob("*.json")) # Iterate over some filenames
.read_files() # Read each file, chunk by chunk
.split() # Split the file, line-by-line
.json() # parse json
.get('country_code', 'null')) # extract field named 'country_code'
>>> set(tube) # collect results in a set
{'A1', 'AD', 'AE', 'AF', 'AG', 'AL', 'AM', 'AO', 'AP', ...}

More Complex Example
--------------------

>>> from tubes import Each
>>> import glob

>>> x = (Each(glob.glob('*.jsonz'))
.map_files()
.gunzip()
.split(b'\n')
.json()
.enumerate()
.skip_unless(lambda x: x.slot(1).get('country_code', '""').to(str).equals('GB'))
.multi(lambda x: (
x.slot(0),
x.slot(1).get('timestamp', 'null'),
x.slot(1).get('country_code', 'null'),
x.slot(1).get('url', 'null'),
x.slot(1).get('file', '{}').get('filename', 'null'),
x.slot(1).get('file', '{}').get('project'),
x.slot(1).get('details', '{}').get('installer', '{}').get('name', 'null'),
x.slot(1).get('details', '{}').get('python', 'null'),
x.slot(1).get('details', '{}').get('system', 'null'),
x.slot(1).get('details', '{}').get('system', '{}').get('name', 'null'),
x.slot(1).get('details', '{}').get('cpu', 'null'),
x.slot(1).get('details', '{}').get('distro', '{}').get('libc', '{}').get('lib', 'null'),
x.slot(1).get('details', '{}').get('distro', '{}').get('libc', '{}').get('version', 'null'),
))
)
>>> print(list(x)[-3])
(15,612,767, '2017-12-14 09:33:31 UTC', 'GB', '/packages/29/9b/25ef61e948321296f029f53c9f67cc2b54e224db509eb67ce17e0df6044a/certifi-2017.11.5-py2.py3-none-any.whl', 'certifi-2017.11.5-py2.py3-none-any.whl', 'certifi', 'pip', '2.7.5', {'name': 'Linux', 'release': '2.6.32-696.10.3.el6.x86_64'}, 'Linux', 'x86_64', 'glibc', '2.17')


What is it?
-----------

Pytubes is a library that optimizes loading dataset into memory.

At it's core is a set of specialized c++ classes that can be chained together
to load and manipulate data using a standard iterator pattern. Around this
there is a cython extension module that makes defining and configuring a tube
simple and straight-forward.

A lot of the cost of loading data using pure python is typically centered around
function call overhead and allocating/copying object data.

Pytubes tackles these bottlenecks by using a number of strategies:

- iterator hot-loops are pure c++ function calls
- zero-copy views onto array data
- strict epoch-based lifetime rules avoid reference counting or GC during iteration
- where possible, zero allocations during iteration
- avoiding creating python objects where possible

These optimizations lead to significant performance improvements over pure python,
despite offering complex loading functionality.

Usage
-----

Usage is very simple:

#. Import ``tubes``
#. create an input tube (currently either: :class:`tube.Each` or :class:`tube.Count`) to get some data into the tube
#. continue to methods on the input tube to build up each step of the processing (e.g. ``read_files().split().json()``...)
#. Iterate over the tube to generate the data, by either:

- Calling ``list(tube)``
- looping over it in a for-loop: ``for item in tube:``
- or: Calling ``x = iter(tube)``, and then ``next(x)`` repeatedly.


Installation
------------

**From PyPi**::

$ pip install pytubes

**From source**::

$ pip install -r build_requirements.txt
$ cd pyx
$ python setup.py install

API
---

All tube methods are documented here: :ref:`api`