Extract swagger specs from your flask project
Project description
Flasgger
Easy Swagger UI for your Flask API
Flasgger is a Flask extension to extract OpenAPI-Specification from all Flask views registered in your API.
Flasgger also comes with SwaggerUI embedded so you can access http://localhost:5000/apidocs and visualize and interact with your API resources.
Flasgger also provides validation of the incoming data, using the same specification it can validates if the data received as as a POST, PUT, PATCH is valid against the schema defined using YAML, Python dictionaries or Marshmallow Schemas.
Flasgger can work with simple function views or MethodViews using docstring as specification, or using @swag_from
decorator to get specification from YAML or dict and also provides SwaggerView which can use Marshmallow Schemas as specification.
Flasgger is compatible with Flask-RESTful
so you can use Resources
and swag
specifications together, take a look at restful example.
Flasgger also supports Marshmallow APISpec
as base template for specification, if you are using APISPec from Marshmallow take a look at apispec example.
Table of Contents
- Top Contributors
- Examples and demo app
- Installation
- Getting started
- Use the same data to validate your API POST body.
- Get defined schemas as python dictionaries
- HTML sanitizer
- Swagger UI and templates
- OpenAPI 3.0 Support
- Initializing Flasgger with default data.
- Customize default configurations
Created by gh-md-toc
Top Contributors
Examples and demo app
There are some example applications and you can also play with examples in Flasgger demo app
NOTE: all the examples apps are also test cases and run automatically in Travis CI to ensure quality and coverage.
Docker
The examples and demo app can also be built and run as a Docker image/container:
docker build -t flasgger .
docker run -it --rm -p 5000:5000 --name flasgger flasgger
Then access the Flasgger demo app at http://localhost:5000 .
Installation
under your virtualenv do:
Ensure you have latest setuptools
pip install -U setuptools
then
pip install flasgger
or (dev version)
pip install https://github.com/rochacbruno/flasgger/tarball/master
NOTE: If you want to use Marshmallow Schemas you also need to run
pip install marshmallow apispec
How to run tests
(You may see the command in .travis.yml for before_install
part)
In your virtualenv:
pip install -r requirements.txt
pip install -r requirements-dev.txt
make test
Getting started
Using docstrings as specification
Create a file called for example colors.py
from flask import Flask, jsonify
from flasgger import Swagger
app = Flask(__name__)
swagger = Swagger(app)
@app.route('/colors/<palette>/')
def colors(palette):
"""Example endpoint returning a list of colors by palette
This is using docstrings for specifications.
---
parameters:
- name: palette
in: path
type: string
enum: ['all', 'rgb', 'cmyk']
required: true
default: all
definitions:
Palette:
type: object
properties:
palette_name:
type: array
items:
$ref: '#/definitions/Color'
Color:
type: string
responses:
200:
description: A list of colors (may be filtered by palette)
schema:
$ref: '#/definitions/Palette'
examples:
rgb: ['red', 'green', 'blue']
"""
all_colors = {
'cmyk': ['cyan', 'magenta', 'yellow', 'black'],
'rgb': ['red', 'green', 'blue']
}
if palette == 'all':
result = all_colors
else:
result = {palette: all_colors.get(palette)}
return jsonify(result)
app.run(debug=True)
Now run:
python colors.py
And go to: http://localhost:5000/apidocs/
You should get:
Using external YAML files
Save a new file colors.yml
Example endpoint returning a list of colors by palette
In this example the specification is taken from external YAML file
---
parameters:
- name: palette
in: path
type: string
enum: ['all', 'rgb', 'cmyk']
required: true
default: all
definitions:
Palette:
type: object
properties:
palette_name:
type: array
items:
$ref: '#/definitions/Color'
Color:
type: string
responses:
200:
description: A list of colors (may be filtered by palette)
schema:
$ref: '#/definitions/Palette'
examples:
rgb: ['red', 'green', 'blue']
lets use the same example changing only the view function.
from flasgger import swag_from
@app.route('/colors/<palette>/')
@swag_from('colors.yml')
def colors(palette):
...
If you do not want to use the decorator you can use the docstring file:
shortcut.
@app.route('/colors/<palette>/')
def colors(palette):
"""
file: colors.yml
"""
...
Using dictionaries as raw specs
Create a Python dictionary as:
specs_dict = {
"parameters": [
{
"name": "palette",
"in": "path",
"type": "string",
"enum": [
"all",
"rgb",
"cmyk"
],
"required": "true",
"default": "all"
}
],
"definitions": {
"Palette": {
"type": "object",
"properties": {
"palette_name": {
"type": "array",
"items": {
"$ref": "#/definitions/Color"
}
}
}
},
"Color": {
"type": "string"
}
},
"responses": {
"200": {
"description": "A list of colors (may be filtered by palette)",
"schema": {
"$ref": "#/definitions/Palette"
},
"examples": {
"rgb": [
"red",
"green",
"blue"
]
}
}
}
}
Now take the same function and use the dict in the place of YAML file.
@app.route('/colors/<palette>/')
@swag_from(specs_dict)
def colors(palette):
"""Example endpoint returning a list of colors by palette
In this example the specification is taken from specs_dict
"""
...
Using Marshmallow Schemas
FIRST:
pip install marshmallow apispec
USAGE #1:
SwaggerView
from flask import Flask, jsonify
from flasgger import Swagger, SwaggerView, Schema, fields
class Color(Schema):
name = fields.Str()
class Palette(Schema):
pallete_name = fields.Str()
colors = fields.Nested(Color, many=True)
class PaletteView(SwaggerView):
parameters = [
{
"name": "palette",
"in": "path",
"type": "string",
"enum": ["all", "rgb", "cmyk"],
"required": True,
"default": "all"
}
]
responses = {
200: {
"description": "A list of colors (may be filtered by palette)",
"schema": Palette
}
}
def get(self, palette):
"""
Colors API using schema
This example is using marshmallow schemas
"""
all_colors = {
'cmyk': ['cyan', 'magenta', 'yellow', 'black'],
'rgb': ['red', 'green', 'blue']
}
if palette == 'all':
result = all_colors
else:
result = {palette: all_colors.get(palette)}
return jsonify(result)
app = Flask(__name__)
swagger = Swagger(app)
app.add_url_rule(
'/colors/<palette>',
view_func=PaletteView.as_view('colors'),
methods=['GET']
)
app.run(debug=True)
USAGE #2:
Custom Schema from flasgger
Body
- support all fields in marshmallowQuery
- support simple fields in marshmallow (Int, String and etc)Path
- support only int and str
from flask import Flask, abort
from flasgger import Swagger, Schema, fields
from marshmallow.validate import Length, OneOf
app = Flask(__name__)
Swagger(app)
swag = {"swag": True,
"tags": ["demo"],
"responses": {200: {"description": "Success request"},
400: {"description": "Validation error"}}}
class Body(Schema):
color = fields.List(fields.String(), required=True, validate=Length(max=5), example=["white", "blue", "red"])
def swag_validation_function(self, data, main_def):
self.load(data)
def swag_validation_error_handler(self, err, data, main_def):
abort(400, err)
class Query(Schema):
color = fields.String(required=True, validate=OneOf(["white", "blue", "red"]))
def swag_validation_function(self, data, main_def):
self.load(data)
def swag_validation_error_handler(self, err, data, main_def):
abort(400, err)
swag_in = "query"
@app.route("/color/<id>/<name>", methods=["POST"], **swag)
def index(body: Body, query: Query, id: int, name: str):
return {"body": body, "query": query, "id": id, "name": name}
if __name__ == "__main__":
app.run(debug=True)
NOTE: take a look at
examples/validation.py
for a more complete example.
NOTE: when catching arguments in path rule always use explicit types, bad:
/api/<username>
good:/api/<string:username>
Using Flask RESTful Resources
Flasgger is compatible with Flask-RESTful you only need to install pip install flask-restful
and then:
from flask import Flask
from flasgger import Swagger
from flask_restful import Api, Resource
app = Flask(__name__)
api = Api(app)
swagger = Swagger(app)
class Username(Resource):
def get(self, username):
"""
This examples uses FlaskRESTful Resource
It works also with swag_from, schemas and spec_dict
---
parameters:
- in: path
name: username
type: string
required: true
responses:
200:
description: A single user item
schema:
id: User
properties:
username:
type: string
description: The name of the user
default: Steven Wilson
"""
return {'username': username}, 200
api.add_resource(Username, '/username/<username>')
app.run(debug=True)
Auto-parsing external YAML docs and MethodView
s
Flasgger can be configured to auto-parse external YAML API docs. Set a doc_dir
in your app.config['SWAGGER']
and Swagger will load API docs by looking in doc_dir
for YAML files stored by endpoint-name and method-name. For example, 'doc_dir': './examples/docs/'
and a file ./examples/docs/items/get.yml
will provide a Swagger doc for ItemsView
method get
.
Additionally, when using Flask RESTful per above, by passing parse=True
when constructing Swagger
, Flasgger will use flask_restful.reqparse.RequestParser
, locate all MethodView
s and parsed and validated data will be stored in flask.request.parsed_data
.
Handling multiple http methods and routes for a single function
You can separate specifications by endpoint or methods
from flasgger.utils import swag_from
@app.route('/api/<string:username>', endpoint='with_user_name', methods=['PUT', 'GET'])
@app.route('/api/', endpoint='without_user_name')
@swag_from('path/to/external_file.yml', endpoint='with_user_name')
@swag_from('path/to/external_file_no_user_get.yml', endpoint='without_user_name', methods=['GET'])
@swag_from('path/to/external_file_no_user_put.yml', endpoint='without_user_name', methods=['PUT'])
def fromfile_decorated(username=None):
if not username:
return "No user!"
return jsonify({'username': username})
And the same can be achieved with multiple methods in a MethodView
or SwaggerView
by
registering the url_rule
many times. Take a look at examples/example_app
Use the same data to validate your API POST body.
Setting swag_from
's validation parameter to True
will validate incoming data automatically:
from flasgger import swag_from
@swag_from('defs.yml', validation=True)
def post():
# if not validate returns ValidationError response with status 400
# also returns the validation message.
Using swagger.validate
annotation is also possible:
from flasgger import Swagger
swagger = Swagger(app)
@swagger.validate('UserSchema')
def post():
'''
file: defs.yml
'''
# if not validate returns ValidationError response with status 400
# also returns the validation message.
Yet you can call validate
manually:
from flasgger import swag_from, validate
@swag_from('defs.yml')
def post():
validate(request.json, 'UserSchema', 'defs.yml')
# if not validate returns ValidationError response with status 400
# also returns the validation message.
It is also possible to define validation=True
in SwaggerView
and also use
specs_dict
for validation.
Take a look at examples/validation.py
for more information.
All validation options can be found at http://json-schema.org/latest/json-schema-validation.html
Custom validation
By default Flasgger will use python-jsonschema to perform validation.
Custom validation functions are supported as long as they meet the requirements:
- take two, and only two, positional arguments:
- the data to be validated as the first; and
- the schema to validate against as the second argument
- raise any kind of exception when validation fails.
Any return value is discarded.
Providing the function to the Swagger instance will make it the default:
from flasgger import Swagger
swagger = Swagger(app, validation_function=my_validation_function)
Providing the function as parameter of swag_from
or swagger.validate
annotations or directly to the validate
function will force it's use
over the default validation function for Swagger:
from flasgger import swag_from
@swag_from('spec.yml', validation=True, validation_function=my_function)
...
from flasgger import Swagger
swagger = Swagger(app)
@swagger.validate('Pet', validation_function=my_function)
...
from flasgger import validate
...
validate(
request.json, 'Pet', 'defs.yml', validation_function=my_function)
Validation Error handling
By default Flasgger will handle validation errors by aborting the request with a 400 BAD REQUEST response with the error message.
A custom validation error handling function can be provided to supersede default behavior as long as it meets the requirements:
- take three, and only three, positional arguments:
- the error raised as the first;
- the data which failed validation as the second; and
- the schema used in to validate as the third argument
Providing the function to the Swagger instance will make it the default:
from flasgger import Swagger
swagger = Swagger(app, validation_error_handler=my_handler)
Providing the function as parameter of swag_from
or swagger.validate
annotations or directly to the validate
function will force it's use
over the default validation function for Swagger:
from flasgger import swag_from
@swag_from(
'spec.yml', validation=True, validation_error_handler=my_handler)
...
from flasgger import Swagger
swagger = Swagger(app)
@swagger.validate('Pet', validation_error_handler=my_handler)
...
from flasgger import validate
...
validate(
request.json, 'Pet', 'defs.yml',
validation_error_handler=my_handler)
Examples of use of a custom validation error handler function can be found at example validation_error_handler.py
Get defined schemas as python dictionaries
You may wish to use schemas you defined in your Swagger specs as dictionaries
without replicating the specification. For that you can use the get_schema
method:
from flask import Flask, jsonify
from flasgger import Swagger, swag_from
app = Flask(__name__)
swagger = Swagger(app)
@swagger.validate('Product')
def post():
"""
post endpoint
---
tags:
- products
parameters:
- name: body
in: body
required: true
schema:
id: Product
required:
- name
properties:
name:
type: string
description: The product's name.
default: "Guarana"
responses:
200:
description: The product inserted in the database
schema:
$ref: '#/definitions/Product'
"""
rv = db.insert(request.json)
return jsonify(rv)
...
product_schema = swagger.get_schema('product')
This method returns a dictionary which contains the Flasgger schema id, all defined parameters and a list of required parameters.
HTML sanitizer
By default Flasgger will try to sanitize the content in YAML definitions
replacing every \n
with <br>
but you can change this behaviour
setting another kind of sanitizer.
from flasgger import Swagger, NO_SANITIZER
app =Flask()
swagger = Swagger(app, sanitizer=NO_SANITIZER)
You can write your own sanitizer
swagger = Swagger(app, sanitizer=lambda text: do_anything_with(text))
There is also a Markdown parser available, if you want to be able to render Markdown in your specs description use MK_SANITIZER
Swagger UI and templates
You can override the templates/flasgger/index.html
in your application and
this template will be the index.html
for SwaggerUI. Use flasgger/ui2/templates/index.html
as base for your customization.
Flasgger supports Swagger UI versions 2 and 3, The version 3 is still experimental but you
can try setting app.config['SWAGGER']['uiversion']
.
app = Flask(__name__)
app.config['SWAGGER'] = {
'title': 'My API',
'uiversion': 3
}
swagger = Swagger(app)
OpenAPI 3.0 Support
There is experimental support for OpenAPI 3.0 that should work when using SwaggerUI 3. To use OpenAPI 3.0, set app.config['SWAGGER']['openapi']
to a version that the current SwaggerUI 3 supports such as '3.0.2'
.
For an example of this that uses callbacks
and requestBody
, see the callbacks example.
Externally loading Swagger UI and jQuery JS/CSS
Starting with Flasgger 0.9.2 you can specify external URL locations for loading the JavaScript and CSS for the Swagger and jQuery libraries loaded in the Flasgger default templates. If the configuration properties below are omitted, Flasgger will serve static versions it includes - these versions may be older than the current Swagger UI v2 or v3 releases.
The following example loads Swagger UI and jQuery versions from unpkg.com:
swagger_config = Swagger.DEFAULT_CONFIG
swagger_config['swagger_ui_bundle_js'] = '//unpkg.com/swagger-ui-dist@3/swagger-ui-bundle.js'
swagger_config['swagger_ui_standalone_preset_js'] = '//unpkg.com/swagger-ui-dist@3/swagger-ui-standalone-preset.js'
swagger_config['jquery_js'] = '//unpkg.com/jquery@2.2.4/dist/jquery.min.js'
swagger_config['swagger_ui_css'] = '//unpkg.com/swagger-ui-dist@3/swagger-ui.css'
Swagger(app, config=swagger_config)
Initializing Flasgger with default data.
You can start your Swagger spec with any default data providing a template:
template = {
"swagger": "2.0",
"info": {
"title": "My API",
"description": "API for my data",
"contact": {
"responsibleOrganization": "ME",
"responsibleDeveloper": "Me",
"email": "me@me.com",
"url": "www.me.com",
},
"termsOfService": "http://me.com/terms",
"version": "0.0.1"
},
"host": "mysite.com", # overrides localhost:500
"basePath": "/api", # base bash for blueprint registration
"schemes": [
"http",
"https"
],
"operationId": "getmyData"
}
swagger = Swagger(app, template=template)
And then the template is the default data unless some view changes it. You can also provide all your specs as template and have no views. Or views in external APP.
Getting default data at runtime
Sometimes you need to get some data at runtime depending on dynamic values ex: you want to check request.is_secure
to decide if schemes
will be https
you can do that by using LazyString
.
from flask import Flask
from flasgger import, Swagger, LazyString, LazyJSONEncoder
app = Flask(__init__)
# Set the custom Encoder (Inherit it if you need to customize)
app.json_encoder = LazyJSONEncoder
template = dict(
info={
'title': LazyString(lambda: 'Lazy Title'),
'version': LazyString(lambda: '99.9.9'),
'description': LazyString(lambda: 'Hello Lazy World'),
'termsOfService': LazyString(lambda: '/there_is_no_tos')
},
host=LazyString(lambda: request.host),
schemes=[LazyString(lambda: 'https' if request.is_secure else 'http')],
foo=LazyString(lambda: "Bar")
)
Swagger(app, template=template)
The LazyString
values will be evaluated only when jsonify
encodes the value at runtime, so you have access to Flask request, session, g, etc..
and also may want to access a database.
Behind a reverse proxy
Sometimes you're serving your swagger docs behind an reverse proxy (e.g. NGINX). When following the Flask guidance, the swagger docs will load correctly, but the "Try it Out" button points to the wrong place. This can be fixed with the following code:
from flask import Flask, request
from flasgger import Swagger, LazyString, LazyJSONEncoder
app = Flask(__name__)
app.json_encoder = LazyJSONEncoder
template = dict(swaggerUiPrefix=LazyString(lambda : request.environ.get('HTTP_X_SCRIPT_NAME', '')))
swagger = Swagger(app, template=template)
Customize default configurations
Custom configurations such as a different specs route or disabling Swagger UI can be provided to Flasgger:
swagger_config = {
"headers": [
],
"specs": [
{
"endpoint": 'apispec_1',
"route": '/apispec_1.json',
"rule_filter": lambda rule: True, # all in
"model_filter": lambda tag: True, # all in
}
],
"static_url_path": "/flasgger_static",
# "static_folder": "static", # must be set by user
"swagger_ui": True,
"specs_route": "/apidocs/"
}
swagger = Swagger(app, config=swagger_config)
Extracting Definitions
Definitions can be extracted when id
is found in spec, example:
from flask import Flask, jsonify
from flasgger import Swagger
app = Flask(__name__)
swagger = Swagger(app)
@app.route('/colors/<palette>/')
def colors(palette):
"""Example endpoint returning a list of colors by palette
---
parameters:
- name: palette
in: path
type: string
enum: ['all', 'rgb', 'cmyk']
required: true
default: all
responses:
200:
description: A list of colors (may be filtered by palette)
schema:
id: Palette
type: object
properties:
palette_name:
type: array
items:
schema:
id: Color
type: string
examples:
rgb: ['red', 'green', 'blue']
"""
all_colors = {
'cmyk': ['cyan', 'magenta', 'yellow', 'black'],
'rgb': ['red', 'green', 'blue']
}
if palette == 'all':
result = all_colors
else:
result = {palette: all_colors.get(palette)}
return jsonify(result)
app.run(debug=True)
In this example you do not have to pass definitions
but need to add id
to
your schemas.
Python2 Compatibility
Version 0.9.5.*
will be the last verison that supports Python2.
Please direct discussions to #399.
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