Skip to main content

Tools to convert observation data to and from a variety of useful formats

Project description

pyinaturalist-convert

Build status codecov Docs PyPI Conda PyPI - Python Versions

This package provides tools to convert iNaturalist observation data to and from a wide variety of useful formats. This is mainly intended for use with the iNaturalist API via pyinaturalist, but also works with other data sources.

Complete project documentation can be found at pyinaturalist-convert.readthedocs.io.

Formats

Import

Export

  • CSV, Excel, and anything else supported by tablib
  • Dataframes, Feather, Parquet, and anything else supported by pandas
  • Darwin Core
  • GeoJSON
  • GPX
  • SQLite
  • SQLite + FTS5 text search for taxonomy

Installation

Install with pip:

pip install pyinaturalist-convert

Or with conda:

conda install -c conda-forge pyinaturalist-convert

To keep things modular, many format-specific dependencies are not installed by default, so you may need to install some more packages depending on which features you want. Each module's docs lists any extra dependencies needed, and a full list can be found in pyproject.toml.

For getting started, it's recommended to install all optional dependencies:

pip install pyinaturalist-convert[all]

Usage

Export

Get your own observations and save to CSV:

from pyinaturalist import get_observations
from pyinaturalist_convert import *

observations = get_observations(user_id='my_username')
to_csv(observations, 'my_observations.csv')

Or any other supported format:

to_dwc(observations, 'my_observations.dwc')
to_excel(observations, 'my_observations.xlsx')
to_feather(observations, 'my_observations.feather')
to_geojson(observations, 'my_observations.geojson')
to_gpx(observations, 'my_observations.gpx')
to_hdf(observations, 'my_observations.hdf')
to_json(observations, 'my_observations.json')
to_parquet(observations, 'my_observations.parquet')
df = to_dataframe(observations)

Import

Most file formats can be loaded via pyinaturalist_convert.read():

observations = read('my_observations.csv')
observations = read('my_observations.xlsx')
observations = read('my_observations.feather')
observations = read('my_observations.hdf')
observations = read('my_observations.json')
observations = read('my_observations.parquet')

Download

Download the complete research-grade observations dataset:

download_dwca_observations()

And load it into a SQLite database:

load_dwca_observations()

And do the same with the complete taxonomy dataset:

download_dwca_taxa()
load_dwca_taxa()

Load taxonomy data into a full text search database:

load_taxon_fts_table(languages=['english', 'german'])

And get lightning-fast autocomplete results from it:

ta = TaxonAutocompleter()
ta.search('aves')
ta.search('flughund', language='german')

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

pyinaturalist_convert-0.6.1.tar.gz (1.6 MB view details)

Uploaded Source

Built Distribution

pyinaturalist_convert-0.6.1-py3-none-any.whl (47.0 kB view details)

Uploaded Python 3

File details

Details for the file pyinaturalist_convert-0.6.1.tar.gz.

File metadata

  • Download URL: pyinaturalist_convert-0.6.1.tar.gz
  • Upload date:
  • Size: 1.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.4.1 CPython/3.11.2 Linux/5.15.0-1034-azure

File hashes

Hashes for pyinaturalist_convert-0.6.1.tar.gz
Algorithm Hash digest
SHA256 7531e866e8387741eb8b56c9bbe3dabf52254c0cf9229cf27eae1e5982ee9c01
MD5 ea65fbce13302cc80e68c6bc37669e97
BLAKE2b-256 15b000a647d8c36ff3207099a7c70795bf7ac68a53ad452a5a5c1a7ab19ea993

See more details on using hashes here.

File details

Details for the file pyinaturalist_convert-0.6.1-py3-none-any.whl.

File metadata

File hashes

Hashes for pyinaturalist_convert-0.6.1-py3-none-any.whl
Algorithm Hash digest
SHA256 bccea193554087e015b3fd3b7ea6a34f5991f9f4276ba4a6a9bcbe4849bc3688
MD5 e3816f67ffeea708811cb3968d664e93
BLAKE2b-256 c289850278494c54691b493c3e8ef6d53039e047423f5e1c38c72dad8de28db0

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