Skip to main content

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

Project description

Partridge

https://img.shields.io/pypi/v/partridge.svg https://img.shields.io/travis/remix/partridge.svg

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

The implementation of Partridge is heavily influenced by our experience at Remix 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.

dependency graph

Philosphy

The design of Partridge is guided by the following principles:

  • as much as possible

    • favor speed

    • allow for extension

    • succeed lazily on expensive paths

    • fail eagerly on inexpensive paths

  • as little as possible

    • do anything other than efficiently read GTFS files into DataFrames

    • take an opinion on the GTFS spec

Usage

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

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.

History

0.6.0.dev1 (2018-01-23)

  • Add support for reading files from a folder. Thanks again @danielsclint!

0.5.0 (2017-12-22)

  • Easily build a representative view of a zip with ptg.get_representative_feed. Inspired by peartree.

  • Extract out GTFS zips by agency_id/route_id with ptg.extract_{agencies,routes}.

  • Read arbitrary files from a zip with feed.get('myfile.txt').

  • Remove service_ids_by_date, dates_by_service_ids, and trip_counts_by_date from the feed class. Instead use ptg.{read_service_ids_by_date,read_dates_by_service_ids,read_trip_counts_by_date}.

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-0.6.0.dev1.tar.gz (1.7 MB view details)

Uploaded Source

Built Distribution

partridge-0.6.0.dev1-py2.py3-none-any.whl (12.7 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file partridge-0.6.0.dev1.tar.gz.

File metadata

File hashes

Hashes for partridge-0.6.0.dev1.tar.gz
Algorithm Hash digest
SHA256 32c14b034fbceb0b33f9b366460a489351517cb52a3c8b4b81af5b4af3cc1312
MD5 8256f0e2f69d96e821a311ec6f021217
BLAKE2b-256 b4e07b3cd3e87c50fb0b58e78ab84776c394b60f6559637290cbec57c63870e8

See more details on using hashes here.

File details

Details for the file partridge-0.6.0.dev1-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for partridge-0.6.0.dev1-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 bb459f87361a574272b20c01247a4970eec381e1b4429e504ee839b1167867af
MD5 c7dca3f592b2ceea65269508e7558efb
BLAKE2b-256 25717daa4cea599ccdd08c9de027bdbebe302524aadc3ba178004c060ab3ccf7

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