Skip to main content

Partridge is python library for working with GTFS feeds using pandas DataFrames.

Project description

=========
Partridge
=========


.. image:: https://img.shields.io/pypi/v/partridge.svg
:target: https://pypi.python.org/pypi/partridge

.. image:: https://img.shields.io/travis/remix/partridge.svg
:target: https://travis-ci.org/remix/partridge


Partridge is python library for working with `GTFS <https://developers.google.com/transit/gtfs/>`__ feeds using `pandas <https://pandas.pydata.org/>`__ DataFrames.

The implementation of Partridge is heavily influenced by our experience at `Remix <https://www.remix.com/>`__ ingesting, analyzing, and debugging thousands of GTFS feeds from hundreds of agencies.

At the core of Partridge is a dependency graph rooted at ``trips.txt``. Disconnected data is pruned away according to this graph when reading the contents of a feed. The root node can optionally be filtered to create a view of the feed specific to your needs. It's most common to filter a feed down to specific dates (``service_id``), routes (``route_id``), or both.

.. figure:: dependency-graph.png
:alt: dependency graph


Usage
-----

.. code:: python

import datetime
import partridge as ptg

path = 'path/to/sfmta-2017-08-22.zip'

service_ids_by_date = ptg.read_service_ids_by_date(path)

service_ids = service_ids_by_date[datetime.date(2017, 9, 25)]

feed = ptg.feed(path, view={
'trips.txt': {
'service_id': service_ids,
'route_id': '12300', # 18-46TH AVENUE
},
})

assert set(feed.trips.service_id) == service_ids
assert list(feed.routes.route_id) == ['12300']

# Buses running the 18 - 46th Ave line use 88 stops (on September 25, 2017, at least).
assert len(feed.stops) == 88

Features
--------

- Surprisingly fast :)
- Load only what you need into memory
- Built-in support for resolving service dates
- Easily extended to support fields and files outside the official spec
(TODO: document this)
- Handle nested folders and bad data in zips
- Predictable type conversions

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

.. code:: console

pip install partridge

Thank You
---------

I hope you find this library useful. If you have suggestions for
improving Partridge, please open an `issue on
GitHub <https://github.com/remix/partridge/issues>`__.


=======
History
=======

0.4.0 (2017-12-10)
===================

* Add support for Python 2.7. Thanks @danielsclint!


0.3.0 (2017-10-12)
===================

* Fix service date resolution for raw_feed. Previously raw_feed considered all days of the week from calendar.txt to be active regardless of 0/1 value.


0.2.0 (2017-09-30)
===================

* Add missing edge from fare_rules.txt to routes.txt in default dependency graph.


0.1.0 (2017-09-23)
------------------

* First release on PyPI.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

partridge-0.4.0.tar.gz (889.1 kB view details)

Uploaded Source

Built Distribution

partridge-0.4.0-py2.py3-none-any.whl (10.3 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file partridge-0.4.0.tar.gz.

File metadata

  • Download URL: partridge-0.4.0.tar.gz
  • Upload date:
  • Size: 889.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for partridge-0.4.0.tar.gz
Algorithm Hash digest
SHA256 0c05c69aee1d8f4121a5bf780af9f0ade84d7d857dd735abfd9cf3bb8a93dbc9
MD5 91c2d765939157c7c7530b62bd7b11a9
BLAKE2b-256 4f20a805b64862d8eea4298f9672d60014f6d83ebfae2958ad0b417216e9b9e6

See more details on using hashes here.

File details

Details for the file partridge-0.4.0-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for partridge-0.4.0-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 ad735550638290a3cdab4209387e9d34ad4a1586610a86f16d72c75f96bd8b23
MD5 1e516cbd2e5432c81085276b74bc17de
BLAKE2b-256 075ce9a6c5fdd57dabef754c792e6bf0c3368062020602b8a774e76c5c9ec65f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page