Skip to main content

Automatically generated a RESTful API services for CRUD operation and queries on database

Project description

Inspired by: sandman2

based on: sqlalchemy-filters Flask-ResponseBuilder Flask-ErrorsHandler

Automatically generate a RESTful APIs for CRUD operation and advanced search on a database. If a list of Model is not provided, all tables are affected, instead you can customize:

  • resource name

  • fields name

  • resource url

  • allowed methods

  • hidden fields

Features

  • HATEOAS support

  • conditional requests via ETag header

  • full range of CRUD operations

  • filtering, sorting and pagination

  • customizable responses via query string

  • custom FETCH method for advanced search

  • JSON and XML response based on Accept header

  • export to csv available

  • meta resource description

  • cli tool to run autocrud on a database

Quickstart

Install flask_autocrud using pip:

$ pip install Flask-AutoCRUD

Example usage

from flask import Flask

from flask_autocrud import AutoCrud
from flask_sqlalchemy import SQLAlchemy


app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite+pysqlite:///db.sqlite3'
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
app.config['AUTOCRUD_METADATA_ENABLED'] = True

db = SQLAlchemy(app)
AutoCrud(app, db)

app.run(debug=True)

Go to http://127.0.0.1:5000/resources and see all available resources with its endpoint. NOTE: you must set SQLALCHEMY_DATABASE_URI with your database.

If you want to see an example use with Flask-Admin see in example folder.

Filtering and Sorting

Add filters as query string parameters, they are used in AND. NOTE: At this time OR operator are not implemented.

You can use entity fields as parameter with the following placeholders:

  • null value: null

  • in operator: list separated by ;

  • not operator: ! means: not equal, not null, not in

  • comparators: __gt__ (grater), __lt__ (lesser), __gte__ (grater-equal), __lte__ (lesser-equal)

  • like operator: % for example: %%test%, %test% or %%test NOTE first % are not used in expression, it only indicated that value must be used with like operator.

Other parameters:

  • Use _fields parameter to get only the fields listed as value, separated by ;.

  • Use _limit and _page parameters for pagination.

  • Sorting is implemented with _sort parameter. The value is a list of field separated by ; You can prepend - to reverse order.

  • Use _export parameter to export data into csv format.

  • Use _extended in order to fetch data of related resources.

  • Use _as_table in order to flatten nested dict useful if you want render response as table

Example requests:

  • /invoice?InvoiceId=(35;344)

  • /invoice?Total=__lte__10&sort=Total

  • /invoice?fields=BillingCountry;Total;InvoiceId&InvoiceId=!355;344&sort=-InvoiceId

  • /invoice?fields=Total;InvoiceId&BillingPostalCode=!null&BillingCountry=%%ermany

  • /invoice?fields=Total;InvoiceDate;InvoiceId;CustomerId&page=2&limit=10

  • /invoice?InvoiceDate=(2009-01-01;2009-02-01 00:00:00)

Example FETCH:

curl --request FETCH \
    --url http://127.0.0.1:5000/customer \
    --header 'content-type: application/json' \
    --data '{
        "fields": [
            "Address",
            "City"
        ],
        "related": {
            "Employee": [
                "FirstName",
                "LastName"
            ],
            "Invoice": [
                "*"
            ]
        },
        "filters": [
            {
                "model": "Customer",
                "field": "SupportRepId",
                "op": "==",
                "value": 5
            },
            {
                "model": "Invoice",
                "field": "Total",
                "op": ">",
                "value": 6
            }
        ],
        "sorting": [
            {
                "model": "Invoice",
                "field": "Total",
                "direction": "asc"
            },
            {
                "model": "Customer",
                "field": "Address",
                "direction": "desc"
            }
        ]
    }'

AutoCRUD cli

You can use autocrud as a standalone application configurable via yaml file. Some options could be given via cli see: autocrud -h, but if configuration file is given these options will be ignored.

If gunicorn is installed on your system it will be chosen as wsgi http server otherwise the default Flask builtin simple server will be used. Under windows you can install waitress.

Configuration file contains 2 principal macro section:

  • app: every configuration under it will be passed to Flask config object

  • wsgi: every configuration under it will be passed to the chosen wsgi

For example:

app:
  SQLALCHEMY_DATABASE_URI: sqlite+pysqlite:///examples/db.sqlite3
  SQLALCHEMY_TRACK_MODIFICATIONS: false
wsgi:
  bind: localhost:5000
  workers: 1
  threads: 1

Configuration

  1. AUTOCRUD_METADATA_ENABLED: (default: True) enable metadata endpoint for a resource

  2. AUTOCRUD_METADATA_URL: (default: ‘/meta) added at the end of url resource

  3. AUTOCRUD_READ_ONLY: (default: False) enable only http GET method

  4. AUTOCRUD_BASE_URL: (default: ‘’) prefix url for resources

  5. AUTOCRUD_RESOURCES_URL: (default: ‘/resources’) url for all available resources

  6. AUTOCRUD_RESOURCES_URL_ENABLED: (default: True) enable route for resources list

  7. AUTOCRUD_SUBDOMAIN: (default: None) bind autocrud endpoints to a subdomain

  8. AUTOCRUD_MAX_QUERY_LIMIT: (default 1000) max query limit, 0 means no limit

  9. AUTOCRUD_FETCH_ENABLED: (default True) enable or disable FETCH method

  10. AUTOCRUD_QUERY_STRING_FILTERS_ENABLED: (default True) enable or disable filters in querystring

  11. AUTOCRUD_EXPORT_ENABLED: (default True) enable or disable export to csv

  12. AUTOCRUD_DATABASE_SCHEMA: (default None) database schema to consider

  13. AUTOCRUD_CONDITIONAL_REQUEST_ENABLED: (default True) allow conditional request

License MIT

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

Flask-AutoCRUD-2.1.0.tar.gz (19.2 kB view details)

Uploaded Source

Built Distribution

Flask_AutoCRUD-2.1.0-py3-none-any.whl (28.7 kB view details)

Uploaded Python 3

File details

Details for the file Flask-AutoCRUD-2.1.0.tar.gz.

File metadata

  • Download URL: Flask-AutoCRUD-2.1.0.tar.gz
  • Upload date:
  • Size: 19.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.6.3 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/2.7.15

File hashes

Hashes for Flask-AutoCRUD-2.1.0.tar.gz
Algorithm Hash digest
SHA256 6d47248a2dbf5f379d0adfd0503c136a10ace61eb0556b9182b9444c5b091570
MD5 940dbd563a461b38ad1953f2a6b7db13
BLAKE2b-256 fbd090eed5310e00ea9ffb767df5eb3e3d17d7d14b3c1aef11232f3ff82fa234

See more details on using hashes here.

File details

Details for the file Flask_AutoCRUD-2.1.0-py3-none-any.whl.

File metadata

  • Download URL: Flask_AutoCRUD-2.1.0-py3-none-any.whl
  • Upload date:
  • Size: 28.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.6.3 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/2.7.15

File hashes

Hashes for Flask_AutoCRUD-2.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 95e5cfa4b20a209da0018a10ac6b74a816bcb110f6cb016acc427316179e9cd3
MD5 e7b9be9ebc202763ec34441e6952426f
BLAKE2b-256 4f8db162d0e02fcb0d470c1b12aea986be638676670fe56618984fc2e99b8704

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