pyinaturalist-convert#

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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')

Feedback#

If you have any problems, suggestions, or questions about pyinaturalist-convert, you are welcome to create an issue or discussion. Also, PRs are welcome!

API Reference#

Modules#

pyinaturalist_convert.converters

Base utilities for converting observation data to common formats.

pyinaturalist_convert.csv

Import CSV observation data from the iNaturalist bulk export tool.

pyinaturalist_convert.db

Data models and utilities for storing observations and related data in a relational database, including SQLite, PostgreSQL, and any other database supported by SQLAlchemy.

pyinaturalist_convert.dwc

Convert observations to and from Darwin Core.

pyinaturalist_convert.dwca

Download and convert the iNaturalist GBIF and taxonomy datasets from DwC-A to SQLite.

pyinaturalist_convert.fts

Build and search a full text search tables for taxa and observations using FTS5.

pyinaturalist_convert.geojson

Convert observations to GeoJSON FeatureCollections.

pyinaturalist_convert.gpx

Convert observations to GPX tracks or waypoints.

pyinaturalist_convert.odp

Download and convert observation, taxon, photo, and user metadata from inaturalist-open-data.

Additional utility modules#

pyinaturalist_convert.download

Helper utilities for downloading and extracting files, with progress bars

pyinaturalist_convert.sqlite

Helper utilities to load data directly from CSV into a SQLite database

pyinaturalist_convert.taxonomy

Helper utilities for navigating tabular taxonomy data as a tree and adding additional derived information to it.