.. image:: https://codeclimate.com/github/18F/autoapi/badges/gpa.svg
:alt: Code Climate
AutoAPI is a very simple, very scalable API engine that converts flat data files into a web service. To add, edit, and remove data from the API, you just add, overwrite, or delete flat CSV files from either an s3 bucket or your local filesystem.
Currently, AutoAPI is the core offering of the
18F API Program <https://pages.18f.gov/api-program/>_, a comprehensive solution for government agencies to get up-and-running with production APIs quickly.
.. image:: https://travis-ci.org/18F/autoapi.svg?branch=master
How to use:
- To see json, you can
- You can also use an API viewer like
Postman for Chrome <https://chrome.google.com/webstore/detail/postman/fhbjgbiflinjbdggehcddcbncdddomop?hl=en>_
- ?[columnheader1]=[value1]&[columnheader1]=[value2] (returns results that have value1 OR value2)
- ?[columnheader1]=[value1]&[columnheader3]=[value4] (returns results that have both value1 and value2)
In order to use autoapi, you'll need:
- Python 3.5
Alternatively, if you use Docker for development and/or deployment, you don't
need anything (except Docker, of course).
First, let's get dependencies sorted out::
pip3 install -r requirements.txt npm install
To run tests::
The easiest way to get started with autoapi is by serving CSV files from
your local filesystem.
Here's a quick way to generate some sample data::
mkdir data_sources cat << EOF > data_sources/my_sample_data.csv name,color apple,red grapefruit,pink EOF
Now you can add your sample data to a local SQLite database::
invoke apify "/data_sources/**.*"
Finally, you can start the server with::
Now try visiting http://localhost:5000 in your browser, or poke at
the following URLs from the command-line::
curl http://localhost:5000/my_sample_data curl http://localhost:5000/my_sample_data/1 curl http://localhost:5000/my_sample_data?color=pink
More details can be found in
Deployment via docker
If you have
Docker <http://docker.io>_ installed, you can run from a Docker
container with no further setup::
docker run \ -p 5000:5000 \ -v `pwd`/data_sources:/data_sources \ --rm -it 18fgsa/autoapi
Any environment variables can be set via the
-e NAME=VALUE option.
Note that this sets up your autoapi instance by directly
pulling autoapi from its
Docker Hub image <https://hub.docker.com/r/18fgsa/autoapi/>_; it doesn't
even require you to clone autoapi's git repository. However, as a
result you won't be able to develop autoapi itself.
Development via docker
If you'd like to use Docker for developing autoapi, just clone its
repository, build the docker image and start the server::
docker-compose build docker-compose up
Now you can visit your server at http://localhost:5000.
If you want to set any environment variables, you can do so by creating
.env file in the root directory of the repository, where each line
consists of a
If any dependencies change, such as those listed in
package.json, just re-run
For more information on using Docker for development, see the
18F Docker Guide <https://pages.18f.gov/dev-environment-standardization/virtualization/docker/>_.
By default, autoapi uses a local SQLite database. To specify a different database URI, set the
DATABASE_URL environment variable. For use with Cloud Foundry, simply create and bind an RDS service; this will automatically configure the environment.
cf create-service rds shared-psql autoapi-rds cf bind-service autoapi autoapi-rds
For details on RDS services available through 18F Cloud Foundry, see https://docs.cloud.gov/apps/databases/.
To use AWS instead of local CSV files, you'll want to define the following
AUTOAPI_BUCKET- The bucket containing your CSV files.
AWS_ACCESS_KEY_ID- Your AWS access key.
AWS_SECRET_ACCESS_KEY- Your AWS secret access key.
autoapi synchronizes with the S3 bucket specified in the
AUTOAPI_BUCKET environment variable. On starting the API server, autoapi creates a subscription to the target bucket using Amazon SNS. When files are added to or deleted from the bucket, the corresponding endpoints will automatically be updated on the API.
This project is in the worldwide
public domain <LICENSE.md>. As stated in
This project is in the public domain within the United States, and copyright and related rights in the work worldwide are waived through the `CC0 1.0 Universal public domain dedication <https://creativecommons.org/publicdomain/zero/1.0/>`_. All contributions to this project will be released under the CC0 dedication. By submitting a pull request, you are agreeing to comply with this waiver of copyright interest.