Fix Read the Docs build failure

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degerahmet 2025-03-24 20:10:13 -07:00
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# Sphinx build info version 1
# This file records the configuration used when building these files. When it is not found, a full rebuild will be done.
config: 600360abbe6c4808701ab5031e46e0b0
tags: d77d1c0d9ca2f4c8421862c7c5a0d620

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API
===
.. module:: flask
This part of the documentation covers all the interfaces of Flask. For
parts where Flask depends on external libraries, we document the most
important right here and provide links to the canonical documentation.
Application Object
------------------
.. autoclass:: Flask
:members:
:inherited-members:
Blueprint Objects
-----------------
.. autoclass:: Blueprint
:members:
:inherited-members:
Incoming Request Data
---------------------
.. autoclass:: Request
:members:
:inherited-members:
:exclude-members: json_module
.. attribute:: request
To access incoming request data, you can use the global `request`
object. Flask parses incoming request data for you and gives you
access to it through that global object. Internally Flask makes
sure that you always get the correct data for the active thread if you
are in a multithreaded environment.
This is a proxy. See :ref:`notes-on-proxies` for more information.
The request object is an instance of a :class:`~flask.Request`.
Response Objects
----------------
.. autoclass:: flask.Response
:members:
:inherited-members:
:exclude-members: json_module
Sessions
--------
If you have set :attr:`Flask.secret_key` (or configured it from
:data:`SECRET_KEY`) you can use sessions in Flask applications. A session makes
it possible to remember information from one request to another. The way Flask
does this is by using a signed cookie. The user can look at the session
contents, but can't modify it unless they know the secret key, so make sure to
set that to something complex and unguessable.
To access the current session you can use the :class:`session` object:
.. class:: session
The session object works pretty much like an ordinary dict, with the
difference that it keeps track of modifications.
This is a proxy. See :ref:`notes-on-proxies` for more information.
The following attributes are interesting:
.. attribute:: new
``True`` if the session is new, ``False`` otherwise.
.. attribute:: modified
``True`` if the session object detected a modification. Be advised
that modifications on mutable structures are not picked up
automatically, in that situation you have to explicitly set the
attribute to ``True`` yourself. Here an example::
# this change is not picked up because a mutable object (here
# a list) is changed.
session['objects'].append(42)
# so mark it as modified yourself
session.modified = True
.. attribute:: permanent
If set to ``True`` the session lives for
:attr:`~flask.Flask.permanent_session_lifetime` seconds. The
default is 31 days. If set to ``False`` (which is the default) the
session will be deleted when the user closes the browser.
Session Interface
-----------------
.. versionadded:: 0.8
The session interface provides a simple way to replace the session
implementation that Flask is using.
.. currentmodule:: flask.sessions
.. autoclass:: SessionInterface
:members:
.. autoclass:: SecureCookieSessionInterface
:members:
.. autoclass:: SecureCookieSession
:members:
.. autoclass:: NullSession
:members:
.. autoclass:: SessionMixin
:members:
.. admonition:: Notice
The :data:`PERMANENT_SESSION_LIFETIME` config can be an integer or ``timedelta``.
The :attr:`~flask.Flask.permanent_session_lifetime` attribute is always a
``timedelta``.
Test Client
-----------
.. currentmodule:: flask.testing
.. autoclass:: FlaskClient
:members:
Test CLI Runner
---------------
.. currentmodule:: flask.testing
.. autoclass:: FlaskCliRunner
:members:
Application Globals
-------------------
.. currentmodule:: flask
To share data that is valid for one request only from one function to
another, a global variable is not good enough because it would break in
threaded environments. Flask provides you with a special object that
ensures it is only valid for the active request and that will return
different values for each request. In a nutshell: it does the right
thing, like it does for :class:`request` and :class:`session`.
.. data:: g
A namespace object that can store data during an
:doc:`application context </appcontext>`. This is an instance of
:attr:`Flask.app_ctx_globals_class`, which defaults to
:class:`ctx._AppCtxGlobals`.
This is a good place to store resources during a request. For
example, a ``before_request`` function could load a user object from
a session id, then set ``g.user`` to be used in the view function.
This is a proxy. See :ref:`notes-on-proxies` for more information.
.. versionchanged:: 0.10
Bound to the application context instead of the request context.
.. autoclass:: flask.ctx._AppCtxGlobals
:members:
Useful Functions and Classes
----------------------------
.. data:: current_app
A proxy to the application handling the current request. This is
useful to access the application without needing to import it, or if
it can't be imported, such as when using the application factory
pattern or in blueprints and extensions.
This is only available when an
:doc:`application context </appcontext>` is pushed. This happens
automatically during requests and CLI commands. It can be controlled
manually with :meth:`~flask.Flask.app_context`.
This is a proxy. See :ref:`notes-on-proxies` for more information.
.. autofunction:: has_request_context
.. autofunction:: copy_current_request_context
.. autofunction:: has_app_context
.. autofunction:: url_for
.. autofunction:: abort
.. autofunction:: redirect
.. autofunction:: make_response
.. autofunction:: after_this_request
.. autofunction:: send_file
.. autofunction:: send_from_directory
Message Flashing
----------------
.. autofunction:: flash
.. autofunction:: get_flashed_messages
JSON Support
------------
.. module:: flask.json
Flask uses Python's built-in :mod:`json` module for handling JSON by
default. The JSON implementation can be changed by assigning a different
provider to :attr:`flask.Flask.json_provider_class` or
:attr:`flask.Flask.json`. The functions provided by ``flask.json`` will
use methods on ``app.json`` if an app context is active.
Jinja's ``|tojson`` filter is configured to use the app's JSON provider.
The filter marks the output with ``|safe``. Use it to render data inside
HTML ``<script>`` tags.
.. sourcecode:: html+jinja
<script>
const names = {{ names|tojson }};
renderChart(names, {{ axis_data|tojson }});
</script>
.. autofunction:: jsonify
.. autofunction:: dumps
.. autofunction:: dump
.. autofunction:: loads
.. autofunction:: load
.. autoclass:: flask.json.provider.JSONProvider
:members:
:member-order: bysource
.. autoclass:: flask.json.provider.DefaultJSONProvider
:members:
:member-order: bysource
.. automodule:: flask.json.tag
Template Rendering
------------------
.. currentmodule:: flask
.. autofunction:: render_template
.. autofunction:: render_template_string
.. autofunction:: stream_template
.. autofunction:: stream_template_string
.. autofunction:: get_template_attribute
Configuration
-------------
.. autoclass:: Config
:members:
Stream Helpers
--------------
.. autofunction:: stream_with_context
Useful Internals
----------------
.. autoclass:: flask.ctx.RequestContext
:members:
.. data:: flask.globals.request_ctx
The current :class:`~flask.ctx.RequestContext`. If a request context
is not active, accessing attributes on this proxy will raise a
``RuntimeError``.
This is an internal object that is essential to how Flask handles
requests. Accessing this should not be needed in most cases. Most
likely you want :data:`request` and :data:`session` instead.
.. autoclass:: flask.ctx.AppContext
:members:
.. data:: flask.globals.app_ctx
The current :class:`~flask.ctx.AppContext`. If an app context is not
active, accessing attributes on this proxy will raise a
``RuntimeError``.
This is an internal object that is essential to how Flask handles
requests. Accessing this should not be needed in most cases. Most
likely you want :data:`current_app` and :data:`g` instead.
.. autoclass:: flask.blueprints.BlueprintSetupState
:members:
.. _core-signals-list:
Signals
-------
Signals are provided by the `Blinker`_ library. See :doc:`signals` for an introduction.
.. _blinker: https://blinker.readthedocs.io/
.. data:: template_rendered
This signal is sent when a template was successfully rendered. The
signal is invoked with the instance of the template as `template`
and the context as dictionary (named `context`).
Example subscriber::
def log_template_renders(sender, template, context, **extra):
sender.logger.debug('Rendering template "%s" with context %s',
template.name or 'string template',
context)
from flask import template_rendered
template_rendered.connect(log_template_renders, app)
.. data:: flask.before_render_template
:noindex:
This signal is sent before template rendering process. The
signal is invoked with the instance of the template as `template`
and the context as dictionary (named `context`).
Example subscriber::
def log_template_renders(sender, template, context, **extra):
sender.logger.debug('Rendering template "%s" with context %s',
template.name or 'string template',
context)
from flask import before_render_template
before_render_template.connect(log_template_renders, app)
.. data:: request_started
This signal is sent when the request context is set up, before
any request processing happens. Because the request context is already
bound, the subscriber can access the request with the standard global
proxies such as :class:`~flask.request`.
Example subscriber::
def log_request(sender, **extra):
sender.logger.debug('Request context is set up')
from flask import request_started
request_started.connect(log_request, app)
.. data:: request_finished
This signal is sent right before the response is sent to the client.
It is passed the response to be sent named `response`.
Example subscriber::
def log_response(sender, response, **extra):
sender.logger.debug('Request context is about to close down. '
'Response: %s', response)
from flask import request_finished
request_finished.connect(log_response, app)
.. data:: got_request_exception
This signal is sent when an unhandled exception happens during
request processing, including when debugging. The exception is
passed to the subscriber as ``exception``.
This signal is not sent for
:exc:`~werkzeug.exceptions.HTTPException`, or other exceptions that
have error handlers registered, unless the exception was raised from
an error handler.
This example shows how to do some extra logging if a theoretical
``SecurityException`` was raised:
.. code-block:: python
from flask import got_request_exception
def log_security_exception(sender, exception, **extra):
if not isinstance(exception, SecurityException):
return
security_logger.exception(
f"SecurityException at {request.url!r}",
exc_info=exception,
)
got_request_exception.connect(log_security_exception, app)
.. data:: request_tearing_down
This signal is sent when the request is tearing down. This is always
called, even if an exception is caused. Currently functions listening
to this signal are called after the regular teardown handlers, but this
is not something you can rely on.
Example subscriber::
def close_db_connection(sender, **extra):
session.close()
from flask import request_tearing_down
request_tearing_down.connect(close_db_connection, app)
As of Flask 0.9, this will also be passed an `exc` keyword argument
that has a reference to the exception that caused the teardown if
there was one.
.. data:: appcontext_tearing_down
This signal is sent when the app context is tearing down. This is always
called, even if an exception is caused. Currently functions listening
to this signal are called after the regular teardown handlers, but this
is not something you can rely on.
Example subscriber::
def close_db_connection(sender, **extra):
session.close()
from flask import appcontext_tearing_down
appcontext_tearing_down.connect(close_db_connection, app)
This will also be passed an `exc` keyword argument that has a reference
to the exception that caused the teardown if there was one.
.. data:: appcontext_pushed
This signal is sent when an application context is pushed. The sender
is the application. This is usually useful for unittests in order to
temporarily hook in information. For instance it can be used to
set a resource early onto the `g` object.
Example usage::
from contextlib import contextmanager
from flask import appcontext_pushed
@contextmanager
def user_set(app, user):
def handler(sender, **kwargs):
g.user = user
with appcontext_pushed.connected_to(handler, app):
yield
And in the testcode::
def test_user_me(self):
with user_set(app, 'john'):
c = app.test_client()
resp = c.get('/users/me')
assert resp.data == 'username=john'
.. versionadded:: 0.10
.. data:: appcontext_popped
This signal is sent when an application context is popped. The sender
is the application. This usually falls in line with the
:data:`appcontext_tearing_down` signal.
.. versionadded:: 0.10
.. data:: message_flashed
This signal is sent when the application is flashing a message. The
messages is sent as `message` keyword argument and the category as
`category`.
Example subscriber::
recorded = []
def record(sender, message, category, **extra):
recorded.append((message, category))
from flask import message_flashed
message_flashed.connect(record, app)
.. versionadded:: 0.10
Class-Based Views
-----------------
.. versionadded:: 0.7
.. currentmodule:: None
.. autoclass:: flask.views.View
:members:
.. autoclass:: flask.views.MethodView
:members:
.. _url-route-registrations:
URL Route Registrations
-----------------------
Generally there are three ways to define rules for the routing system:
1. You can use the :meth:`flask.Flask.route` decorator.
2. You can use the :meth:`flask.Flask.add_url_rule` function.
3. You can directly access the underlying Werkzeug routing system
which is exposed as :attr:`flask.Flask.url_map`.
Variable parts in the route can be specified with angular brackets
(``/user/<username>``). By default a variable part in the URL accepts any
string without a slash however a different converter can be specified as
well by using ``<converter:name>``.
Variable parts are passed to the view function as keyword arguments.
The following converters are available:
=========== ===============================================
`string` accepts any text without a slash (the default)
`int` accepts integers
`float` like `int` but for floating point values
`path` like the default but also accepts slashes
`any` matches one of the items provided
`uuid` accepts UUID strings
=========== ===============================================
Custom converters can be defined using :attr:`flask.Flask.url_map`.
Here are some examples::
@app.route('/')
def index():
pass
@app.route('/<username>')
def show_user(username):
pass
@app.route('/post/<int:post_id>')
def show_post(post_id):
pass
An important detail to keep in mind is how Flask deals with trailing
slashes. The idea is to keep each URL unique so the following rules
apply:
1. If a rule ends with a slash and is requested without a slash by the
user, the user is automatically redirected to the same page with a
trailing slash attached.
2. If a rule does not end with a trailing slash and the user requests the
page with a trailing slash, a 404 not found is raised.
This is consistent with how web servers deal with static files. This
also makes it possible to use relative link targets safely.
You can also define multiple rules for the same function. They have to be
unique however. Defaults can also be specified. Here for example is a
definition for a URL that accepts an optional page::
@app.route('/users/', defaults={'page': 1})
@app.route('/users/page/<int:page>')
def show_users(page):
pass
This specifies that ``/users/`` will be the URL for page one and
``/users/page/N`` will be the URL for page ``N``.
If a URL contains a default value, it will be redirected to its simpler
form with a 301 redirect. In the above example, ``/users/page/1`` will
be redirected to ``/users/``. If your route handles ``GET`` and ``POST``
requests, make sure the default route only handles ``GET``, as redirects
can't preserve form data. ::
@app.route('/region/', defaults={'id': 1})
@app.route('/region/<int:id>', methods=['GET', 'POST'])
def region(id):
pass
Here are the parameters that :meth:`~flask.Flask.route` and
:meth:`~flask.Flask.add_url_rule` accept. The only difference is that
with the route parameter the view function is defined with the decorator
instead of the `view_func` parameter.
=============== ==========================================================
`rule` the URL rule as string
`endpoint` the endpoint for the registered URL rule. Flask itself
assumes that the name of the view function is the name
of the endpoint if not explicitly stated.
`view_func` the function to call when serving a request to the
provided endpoint. If this is not provided one can
specify the function later by storing it in the
:attr:`~flask.Flask.view_functions` dictionary with the
endpoint as key.
`defaults` A dictionary with defaults for this rule. See the
example above for how defaults work.
`subdomain` specifies the rule for the subdomain in case subdomain
matching is in use. If not specified the default
subdomain is assumed.
`**options` the options to be forwarded to the underlying
:class:`~werkzeug.routing.Rule` object. A change to
Werkzeug is handling of method options. methods is a list
of methods this rule should be limited to (``GET``, ``POST``
etc.). By default a rule just listens for ``GET`` (and
implicitly ``HEAD``). Starting with Flask 0.6, ``OPTIONS`` is
implicitly added and handled by the standard request
handling. They have to be specified as keyword arguments.
=============== ==========================================================
View Function Options
---------------------
For internal usage the view functions can have some attributes attached to
customize behavior the view function would normally not have control over.
The following attributes can be provided optionally to either override
some defaults to :meth:`~flask.Flask.add_url_rule` or general behavior:
- `__name__`: The name of a function is by default used as endpoint. If
endpoint is provided explicitly this value is used. Additionally this
will be prefixed with the name of the blueprint by default which
cannot be customized from the function itself.
- `methods`: If methods are not provided when the URL rule is added,
Flask will look on the view function object itself if a `methods`
attribute exists. If it does, it will pull the information for the
methods from there.
- `provide_automatic_options`: if this attribute is set Flask will
either force enable or disable the automatic implementation of the
HTTP ``OPTIONS`` response. This can be useful when working with
decorators that want to customize the ``OPTIONS`` response on a per-view
basis.
- `required_methods`: if this attribute is set, Flask will always add
these methods when registering a URL rule even if the methods were
explicitly overridden in the ``route()`` call.
Full example::
def index():
if request.method == 'OPTIONS':
# custom options handling here
...
return 'Hello World!'
index.provide_automatic_options = False
index.methods = ['GET', 'OPTIONS']
app.add_url_rule('/', index)
.. versionadded:: 0.8
The `provide_automatic_options` functionality was added.
Command Line Interface
----------------------
.. currentmodule:: flask.cli
.. autoclass:: FlaskGroup
:members:
.. autoclass:: AppGroup
:members:
.. autoclass:: ScriptInfo
:members:
.. autofunction:: load_dotenv
.. autofunction:: with_appcontext
.. autofunction:: pass_script_info
Marks a function so that an instance of :class:`ScriptInfo` is passed
as first argument to the click callback.
.. autodata:: run_command
.. autodata:: shell_command

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.. currentmodule:: flask
The Application Context
=======================
The application context keeps track of the application-level data during
a request, CLI command, or other activity. Rather than passing the
application around to each function, the :data:`current_app` and
:data:`g` proxies are accessed instead.
This is similar to :doc:`/reqcontext`, which keeps track of
request-level data during a request. A corresponding application context
is pushed when a request context is pushed.
Purpose of the Context
----------------------
The :class:`Flask` application object has attributes, such as
:attr:`~Flask.config`, that are useful to access within views and
:doc:`CLI commands </cli>`. However, importing the ``app`` instance
within the modules in your project is prone to circular import issues.
When using the :doc:`app factory pattern </patterns/appfactories>` or
writing reusable :doc:`blueprints </blueprints>` or
:doc:`extensions </extensions>` there won't be an ``app`` instance to
import at all.
Flask solves this issue with the *application context*. Rather than
referring to an ``app`` directly, you use the :data:`current_app`
proxy, which points to the application handling the current activity.
Flask automatically *pushes* an application context when handling a
request. View functions, error handlers, and other functions that run
during a request will have access to :data:`current_app`.
Flask will also automatically push an app context when running CLI
commands registered with :attr:`Flask.cli` using ``@app.cli.command()``.
Lifetime of the Context
-----------------------
The application context is created and destroyed as necessary. When a
Flask application begins handling a request, it pushes an application
context and a :doc:`request context </reqcontext>`. When the request
ends it pops the request context then the application context.
Typically, an application context will have the same lifetime as a
request.
See :doc:`/reqcontext` for more information about how the contexts work
and the full life cycle of a request.
Manually Push a Context
-----------------------
If you try to access :data:`current_app`, or anything that uses it,
outside an application context, you'll get this error message:
.. code-block:: pytb
RuntimeError: Working outside of application context.
This typically means that you attempted to use functionality that
needed to interface with the current application object in some way.
To solve this, set up an application context with app.app_context().
If you see that error while configuring your application, such as when
initializing an extension, you can push a context manually since you
have direct access to the ``app``. Use :meth:`~Flask.app_context` in a
``with`` block, and everything that runs in the block will have access
to :data:`current_app`. ::
def create_app():
app = Flask(__name__)
with app.app_context():
init_db()
return app
If you see that error somewhere else in your code not related to
configuring the application, it most likely indicates that you should
move that code into a view function or CLI command.
Storing Data
------------
The application context is a good place to store common data during a
request or CLI command. Flask provides the :data:`g object <g>` for this
purpose. It is a simple namespace object that has the same lifetime as
an application context.
.. note::
The ``g`` name stands for "global", but that is referring to the
data being global *within a context*. The data on ``g`` is lost
after the context ends, and it is not an appropriate place to store
data between requests. Use the :data:`session` or a database to
store data across requests.
A common use for :data:`g` is to manage resources during a request.
1. ``get_X()`` creates resource ``X`` if it does not exist, caching it
as ``g.X``.
2. ``teardown_X()`` closes or otherwise deallocates the resource if it
exists. It is registered as a :meth:`~Flask.teardown_appcontext`
handler.
For example, you can manage a database connection using this pattern::
from flask import g
def get_db():
if 'db' not in g:
g.db = connect_to_database()
return g.db
@app.teardown_appcontext
def teardown_db(exception):
db = g.pop('db', None)
if db is not None:
db.close()
During a request, every call to ``get_db()`` will return the same
connection, and it will be closed automatically at the end of the
request.
You can use :class:`~werkzeug.local.LocalProxy` to make a new context
local from ``get_db()``::
from werkzeug.local import LocalProxy
db = LocalProxy(get_db)
Accessing ``db`` will call ``get_db`` internally, in the same way that
:data:`current_app` works.
Events and Signals
------------------
The application will call functions registered with :meth:`~Flask.teardown_appcontext`
when the application context is popped.
The following signals are sent: :data:`appcontext_pushed`,
:data:`appcontext_tearing_down`, and :data:`appcontext_popped`.

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.. _async_await:
Using ``async`` and ``await``
=============================
.. versionadded:: 2.0
Routes, error handlers, before request, after request, and teardown
functions can all be coroutine functions if Flask is installed with the
``async`` extra (``pip install flask[async]``). This allows views to be
defined with ``async def`` and use ``await``.
.. code-block:: python
@app.route("/get-data")
async def get_data():
data = await async_db_query(...)
return jsonify(data)
Pluggable class-based views also support handlers that are implemented as
coroutines. This applies to the :meth:`~flask.views.View.dispatch_request`
method in views that inherit from the :class:`flask.views.View` class, as
well as all the HTTP method handlers in views that inherit from the
:class:`flask.views.MethodView` class.
.. admonition:: Using ``async`` with greenlet
When using gevent or eventlet to serve an application or patch the
runtime, greenlet>=1.0 is required. When using PyPy, PyPy>=7.3.7 is
required.
Performance
-----------
Async functions require an event loop to run. Flask, as a WSGI
application, uses one worker to handle one request/response cycle.
When a request comes in to an async view, Flask will start an event loop
in a thread, run the view function there, then return the result.
Each request still ties up one worker, even for async views. The upside
is that you can run async code within a view, for example to make
multiple concurrent database queries, HTTP requests to an external API,
etc. However, the number of requests your application can handle at one
time will remain the same.
**Async is not inherently faster than sync code.** Async is beneficial
when performing concurrent IO-bound tasks, but will probably not improve
CPU-bound tasks. Traditional Flask views will still be appropriate for
most use cases, but Flask's async support enables writing and using
code that wasn't possible natively before.
Background tasks
----------------
Async functions will run in an event loop until they complete, at
which stage the event loop will stop. This means any additional
spawned tasks that haven't completed when the async function completes
will be cancelled. Therefore you cannot spawn background tasks, for
example via ``asyncio.create_task``.
If you wish to use background tasks it is best to use a task queue to
trigger background work, rather than spawn tasks in a view
function. With that in mind you can spawn asyncio tasks by serving
Flask with an ASGI server and utilising the asgiref WsgiToAsgi adapter
as described in :doc:`deploying/asgi`. This works as the adapter creates
an event loop that runs continually.
When to use Quart instead
-------------------------
Flask's async support is less performant than async-first frameworks due
to the way it is implemented. If you have a mainly async codebase it
would make sense to consider `Quart`_. Quart is a reimplementation of
Flask based on the `ASGI`_ standard instead of WSGI. This allows it to
handle many concurrent requests, long running requests, and websockets
without requiring multiple worker processes or threads.
It has also already been possible to run Flask with Gevent or Eventlet
to get many of the benefits of async request handling. These libraries
patch low-level Python functions to accomplish this, whereas ``async``/
``await`` and ASGI use standard, modern Python capabilities. Deciding
whether you should use Flask, Quart, or something else is ultimately up
to understanding the specific needs of your project.
.. _Quart: https://github.com/pallets/quart
.. _ASGI: https://asgi.readthedocs.io/en/latest/
Extensions
----------
Flask extensions predating Flask's async support do not expect async views.
If they provide decorators to add functionality to views, those will probably
not work with async views because they will not await the function or be
awaitable. Other functions they provide will not be awaitable either and
will probably be blocking if called within an async view.
Extension authors can support async functions by utilising the
:meth:`flask.Flask.ensure_sync` method. For example, if the extension
provides a view function decorator add ``ensure_sync`` before calling
the decorated function,
.. code-block:: python
def extension(func):
@wraps(func)
def wrapper(*args, **kwargs):
... # Extension logic
return current_app.ensure_sync(func)(*args, **kwargs)
return wrapper
Check the changelog of the extension you want to use to see if they've
implemented async support, or make a feature request or PR to them.
Other event loops
-----------------
At the moment Flask only supports :mod:`asyncio`. It's possible to
override :meth:`flask.Flask.ensure_sync` to change how async functions
are wrapped to use a different library.

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Modular Applications with Blueprints
====================================
.. currentmodule:: flask
.. versionadded:: 0.7
Flask uses a concept of *blueprints* for making application components and
supporting common patterns within an application or across applications.
Blueprints can greatly simplify how large applications work and provide a
central means for Flask extensions to register operations on applications.
A :class:`Blueprint` object works similarly to a :class:`Flask`
application object, but it is not actually an application. Rather it is a
*blueprint* of how to construct or extend an application.
Why Blueprints?
---------------
Blueprints in Flask are intended for these cases:
* Factor an application into a set of blueprints. This is ideal for
larger applications; a project could instantiate an application object,
initialize several extensions, and register a collection of blueprints.
* Register a blueprint on an application at a URL prefix and/or subdomain.
Parameters in the URL prefix/subdomain become common view arguments
(with defaults) across all view functions in the blueprint.
* Register a blueprint multiple times on an application with different URL
rules.
* Provide template filters, static files, templates, and other utilities
through blueprints. A blueprint does not have to implement applications
or view functions.
* Register a blueprint on an application for any of these cases when
initializing a Flask extension.
A blueprint in Flask is not a pluggable app because it is not actually an
application -- it's a set of operations which can be registered on an
application, even multiple times. Why not have multiple application
objects? You can do that (see :doc:`/patterns/appdispatch`), but your
applications will have separate configs and will be managed at the WSGI
layer.
Blueprints instead provide separation at the Flask level, share
application config, and can change an application object as necessary with
being registered. The downside is that you cannot unregister a blueprint
once an application was created without having to destroy the whole
application object.
The Concept of Blueprints
-------------------------
The basic concept of blueprints is that they record operations to execute
when registered on an application. Flask associates view functions with
blueprints when dispatching requests and generating URLs from one endpoint
to another.
My First Blueprint
------------------
This is what a very basic blueprint looks like. In this case we want to
implement a blueprint that does simple rendering of static templates::
from flask import Blueprint, render_template, abort
from jinja2 import TemplateNotFound
simple_page = Blueprint('simple_page', __name__,
template_folder='templates')
@simple_page.route('/', defaults={'page': 'index'})
@simple_page.route('/<page>')
def show(page):
try:
return render_template(f'pages/{page}.html')
except TemplateNotFound:
abort(404)
When you bind a function with the help of the ``@simple_page.route``
decorator, the blueprint will record the intention of registering the
function ``show`` on the application when it's later registered.
Additionally it will prefix the endpoint of the function with the
name of the blueprint which was given to the :class:`Blueprint`
constructor (in this case also ``simple_page``). The blueprint's name
does not modify the URL, only the endpoint.
Registering Blueprints
----------------------
So how do you register that blueprint? Like this::
from flask import Flask
from yourapplication.simple_page import simple_page
app = Flask(__name__)
app.register_blueprint(simple_page)
If you check the rules registered on the application, you will find
these::
>>> app.url_map
Map([<Rule '/static/<filename>' (HEAD, OPTIONS, GET) -> static>,
<Rule '/<page>' (HEAD, OPTIONS, GET) -> simple_page.show>,
<Rule '/' (HEAD, OPTIONS, GET) -> simple_page.show>])
The first one is obviously from the application itself for the static
files. The other two are for the `show` function of the ``simple_page``
blueprint. As you can see, they are also prefixed with the name of the
blueprint and separated by a dot (``.``).
Blueprints however can also be mounted at different locations::
app.register_blueprint(simple_page, url_prefix='/pages')
And sure enough, these are the generated rules::
>>> app.url_map
Map([<Rule '/static/<filename>' (HEAD, OPTIONS, GET) -> static>,
<Rule '/pages/<page>' (HEAD, OPTIONS, GET) -> simple_page.show>,
<Rule '/pages/' (HEAD, OPTIONS, GET) -> simple_page.show>])
On top of that you can register blueprints multiple times though not every
blueprint might respond properly to that. In fact it depends on how the
blueprint is implemented if it can be mounted more than once.
Nesting Blueprints
------------------
It is possible to register a blueprint on another blueprint.
.. code-block:: python
parent = Blueprint('parent', __name__, url_prefix='/parent')
child = Blueprint('child', __name__, url_prefix='/child')
parent.register_blueprint(child)
app.register_blueprint(parent)
The child blueprint will gain the parent's name as a prefix to its
name, and child URLs will be prefixed with the parent's URL prefix.
.. code-block:: python
url_for('parent.child.create')
/parent/child/create
In addition a child blueprint's will gain their parent's subdomain,
with their subdomain as prefix if present i.e.
.. code-block:: python
parent = Blueprint('parent', __name__, subdomain='parent')
child = Blueprint('child', __name__, subdomain='child')
parent.register_blueprint(child)
app.register_blueprint(parent)
url_for('parent.child.create', _external=True)
"child.parent.domain.tld"
Blueprint-specific before request functions, etc. registered with the
parent will trigger for the child. If a child does not have an error
handler that can handle a given exception, the parent's will be tried.
Blueprint Resources
-------------------
Blueprints can provide resources as well. Sometimes you might want to
introduce a blueprint only for the resources it provides.
Blueprint Resource Folder
`````````````````````````
Like for regular applications, blueprints are considered to be contained
in a folder. While multiple blueprints can originate from the same folder,
it does not have to be the case and it's usually not recommended.
The folder is inferred from the second argument to :class:`Blueprint` which
is usually `__name__`. This argument specifies what logical Python
module or package corresponds to the blueprint. If it points to an actual
Python package that package (which is a folder on the filesystem) is the
resource folder. If it's a module, the package the module is contained in
will be the resource folder. You can access the
:attr:`Blueprint.root_path` property to see what the resource folder is::
>>> simple_page.root_path
'/Users/username/TestProject/yourapplication'
To quickly open sources from this folder you can use the
:meth:`~Blueprint.open_resource` function::
with simple_page.open_resource('static/style.css') as f:
code = f.read()
Static Files
````````````
A blueprint can expose a folder with static files by providing the path
to the folder on the filesystem with the ``static_folder`` argument.
It is either an absolute path or relative to the blueprint's location::
admin = Blueprint('admin', __name__, static_folder='static')
By default the rightmost part of the path is where it is exposed on the
web. This can be changed with the ``static_url_path`` argument. Because the
folder is called ``static`` here it will be available at the
``url_prefix`` of the blueprint + ``/static``. If the blueprint
has the prefix ``/admin``, the static URL will be ``/admin/static``.
The endpoint is named ``blueprint_name.static``. You can generate URLs
to it with :func:`url_for` like you would with the static folder of the
application::
url_for('admin.static', filename='style.css')
However, if the blueprint does not have a ``url_prefix``, it is not
possible to access the blueprint's static folder. This is because the
URL would be ``/static`` in this case, and the application's ``/static``
route takes precedence. Unlike template folders, blueprint static
folders are not searched if the file does not exist in the application
static folder.
Templates
`````````
If you want the blueprint to expose templates you can do that by providing
the `template_folder` parameter to the :class:`Blueprint` constructor::
admin = Blueprint('admin', __name__, template_folder='templates')
For static files, the path can be absolute or relative to the blueprint
resource folder.
The template folder is added to the search path of templates but with a lower
priority than the actual application's template folder. That way you can
easily override templates that a blueprint provides in the actual application.
This also means that if you don't want a blueprint template to be accidentally
overridden, make sure that no other blueprint or actual application template
has the same relative path. When multiple blueprints provide the same relative
template path the first blueprint registered takes precedence over the others.
So if you have a blueprint in the folder ``yourapplication/admin`` and you
want to render the template ``'admin/index.html'`` and you have provided
``templates`` as a `template_folder` you will have to create a file like
this: :file:`yourapplication/admin/templates/admin/index.html`. The reason
for the extra ``admin`` folder is to avoid getting our template overridden
by a template named ``index.html`` in the actual application template
folder.
To further reiterate this: if you have a blueprint named ``admin`` and you
want to render a template called :file:`index.html` which is specific to this
blueprint, the best idea is to lay out your templates like this::
yourpackage/
blueprints/
admin/
templates/
admin/
index.html
__init__.py
And then when you want to render the template, use :file:`admin/index.html` as
the name to look up the template by. If you encounter problems loading
the correct templates enable the ``EXPLAIN_TEMPLATE_LOADING`` config
variable which will instruct Flask to print out the steps it goes through
to locate templates on every ``render_template`` call.
Building URLs
-------------
If you want to link from one page to another you can use the
:func:`url_for` function just like you normally would do just that you
prefix the URL endpoint with the name of the blueprint and a dot (``.``)::
url_for('admin.index')
Additionally if you are in a view function of a blueprint or a rendered
template and you want to link to another endpoint of the same blueprint,
you can use relative redirects by prefixing the endpoint with a dot only::
url_for('.index')
This will link to ``admin.index`` for instance in case the current request
was dispatched to any other admin blueprint endpoint.
Blueprint Error Handlers
------------------------
Blueprints support the ``errorhandler`` decorator just like the :class:`Flask`
application object, so it is easy to make Blueprint-specific custom error
pages.
Here is an example for a "404 Page Not Found" exception::
@simple_page.errorhandler(404)
def page_not_found(e):
return render_template('pages/404.html')
Most errorhandlers will simply work as expected; however, there is a caveat
concerning handlers for 404 and 405 exceptions. These errorhandlers are only
invoked from an appropriate ``raise`` statement or a call to ``abort`` in another
of the blueprint's view functions; they are not invoked by, e.g., an invalid URL
access. This is because the blueprint does not "own" a certain URL space, so
the application instance has no way of knowing which blueprint error handler it
should run if given an invalid URL. If you would like to execute different
handling strategies for these errors based on URL prefixes, they may be defined
at the application level using the ``request`` proxy object::
@app.errorhandler(404)
@app.errorhandler(405)
def _handle_api_error(ex):
if request.path.startswith('/api/'):
return jsonify(error=str(ex)), ex.code
else:
return ex
See :doc:`/errorhandling`.

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Changes
=======
.. include:: ../CHANGES.rst

556
_build/_sources/cli.rst.txt Normal file
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.. currentmodule:: flask
Command Line Interface
======================
Installing Flask installs the ``flask`` script, a `Click`_ command line
interface, in your virtualenv. Executed from the terminal, this script gives
access to built-in, extension, and application-defined commands. The ``--help``
option will give more information about any commands and options.
.. _Click: https://click.palletsprojects.com/
Application Discovery
---------------------
The ``flask`` command is installed by Flask, not your application; it must be
told where to find your application in order to use it. The ``--app``
option is used to specify how to load the application.
While ``--app`` supports a variety of options for specifying your
application, most use cases should be simple. Here are the typical values:
(nothing)
The name "app" or "wsgi" is imported (as a ".py" file, or package),
automatically detecting an app (``app`` or ``application``) or
factory (``create_app`` or ``make_app``).
``--app hello``
The given name is imported, automatically detecting an app (``app``
or ``application``) or factory (``create_app`` or ``make_app``).
----
``--app`` has three parts: an optional path that sets the current working
directory, a Python file or dotted import path, and an optional variable
name of the instance or factory. If the name is a factory, it can optionally
be followed by arguments in parentheses. The following values demonstrate these
parts:
``--app src/hello``
Sets the current working directory to ``src`` then imports ``hello``.
``--app hello.web``
Imports the path ``hello.web``.
``--app hello:app2``
Uses the ``app2`` Flask instance in ``hello``.
``--app 'hello:create_app("dev")'``
The ``create_app`` factory in ``hello`` is called with the string ``'dev'``
as the argument.
If ``--app`` is not set, the command will try to import "app" or
"wsgi" (as a ".py" file, or package) and try to detect an application
instance or factory.
Within the given import, the command looks for an application instance named
``app`` or ``application``, then any application instance. If no instance is
found, the command looks for a factory function named ``create_app`` or
``make_app`` that returns an instance.
If parentheses follow the factory name, their contents are parsed as
Python literals and passed as arguments and keyword arguments to the
function. This means that strings must still be in quotes.
Run the Development Server
--------------------------
The :func:`run <cli.run_command>` command will start the development server. It
replaces the :meth:`Flask.run` method in most cases. ::
$ flask --app hello run
* Serving Flask app "hello"
* Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)
.. warning:: Do not use this command to run your application in production.
Only use the development server during development. The development server
is provided for convenience, but is not designed to be particularly secure,
stable, or efficient. See :doc:`/deploying/index` for how to run in production.
If another program is already using port 5000, you'll see
``OSError: [Errno 98]`` or ``OSError: [WinError 10013]`` when the
server tries to start. See :ref:`address-already-in-use` for how to
handle that.
Debug Mode
~~~~~~~~~~
In debug mode, the ``flask run`` command will enable the interactive debugger and the
reloader by default, and make errors easier to see and debug. To enable debug mode, use
the ``--debug`` option.
.. code-block:: console
$ flask --app hello run --debug
* Serving Flask app "hello"
* Debug mode: on
* Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)
* Restarting with inotify reloader
* Debugger is active!
* Debugger PIN: 223-456-919
The ``--debug`` option can also be passed to the top level ``flask`` command to enable
debug mode for any command. The following two ``run`` calls are equivalent.
.. code-block:: console
$ flask --app hello --debug run
$ flask --app hello run --debug
Watch and Ignore Files with the Reloader
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
When using debug mode, the reloader will trigger whenever your Python code or imported
modules change. The reloader can watch additional files with the ``--extra-files``
option. Multiple paths are separated with ``:``, or ``;`` on Windows.
.. code-block:: text
$ flask run --extra-files file1:dirA/file2:dirB/
* Running on http://127.0.0.1:8000/
* Detected change in '/path/to/file1', reloading
The reloader can also ignore files using :mod:`fnmatch` patterns with the
``--exclude-patterns`` option. Multiple patterns are separated with ``:``, or ``;`` on
Windows.
Open a Shell
------------
To explore the data in your application, you can start an interactive Python
shell with the :func:`shell <cli.shell_command>` command. An application
context will be active, and the app instance will be imported. ::
$ flask shell
Python 3.10.0 (default, Oct 27 2021, 06:59:51) [GCC 11.1.0] on linux
App: example [production]
Instance: /home/david/Projects/pallets/flask/instance
>>>
Use :meth:`~Flask.shell_context_processor` to add other automatic imports.
.. _dotenv:
Environment Variables From dotenv
---------------------------------
The ``flask`` command supports setting any option for any command with
environment variables. The variables are named like ``FLASK_OPTION`` or
``FLASK_COMMAND_OPTION``, for example ``FLASK_APP`` or
``FLASK_RUN_PORT``.
Rather than passing options every time you run a command, or environment
variables every time you open a new terminal, you can use Flask's dotenv
support to set environment variables automatically.
If `python-dotenv`_ is installed, running the ``flask`` command will set
environment variables defined in the files ``.env`` and ``.flaskenv``.
You can also specify an extra file to load with the ``--env-file``
option. Dotenv files can be used to avoid having to set ``--app`` or
``FLASK_APP`` manually, and to set configuration using environment
variables similar to how some deployment services work.
Variables set on the command line are used over those set in :file:`.env`,
which are used over those set in :file:`.flaskenv`. :file:`.flaskenv` should be
used for public variables, such as ``FLASK_APP``, while :file:`.env` should not
be committed to your repository so that it can set private variables.
Directories are scanned upwards from the directory you call ``flask``
from to locate the files.
The files are only loaded by the ``flask`` command or calling
:meth:`~Flask.run`. If you would like to load these files when running in
production, you should call :func:`~cli.load_dotenv` manually.
.. _python-dotenv: https://github.com/theskumar/python-dotenv#readme
Setting Command Options
~~~~~~~~~~~~~~~~~~~~~~~
Click is configured to load default values for command options from
environment variables. The variables use the pattern
``FLASK_COMMAND_OPTION``. For example, to set the port for the run
command, instead of ``flask run --port 8000``:
.. tabs::
.. group-tab:: Bash
.. code-block:: text
$ export FLASK_RUN_PORT=8000
$ flask run
* Running on http://127.0.0.1:8000/
.. group-tab:: Fish
.. code-block:: text
$ set -x FLASK_RUN_PORT 8000
$ flask run
* Running on http://127.0.0.1:8000/
.. group-tab:: CMD
.. code-block:: text
> set FLASK_RUN_PORT=8000
> flask run
* Running on http://127.0.0.1:8000/
.. group-tab:: Powershell
.. code-block:: text
> $env:FLASK_RUN_PORT = 8000
> flask run
* Running on http://127.0.0.1:8000/
These can be added to the ``.flaskenv`` file just like ``FLASK_APP`` to
control default command options.
Disable dotenv
~~~~~~~~~~~~~~
The ``flask`` command will show a message if it detects dotenv files but
python-dotenv is not installed.
.. code-block:: bash
$ flask run
* Tip: There are .env files present. Do "pip install python-dotenv" to use them.
You can tell Flask not to load dotenv files even when python-dotenv is
installed by setting the ``FLASK_SKIP_DOTENV`` environment variable.
This can be useful if you want to load them manually, or if you're using
a project runner that loads them already. Keep in mind that the
environment variables must be set before the app loads or it won't
configure as expected.
.. tabs::
.. group-tab:: Bash
.. code-block:: text
$ export FLASK_SKIP_DOTENV=1
$ flask run
.. group-tab:: Fish
.. code-block:: text
$ set -x FLASK_SKIP_DOTENV 1
$ flask run
.. group-tab:: CMD
.. code-block:: text
> set FLASK_SKIP_DOTENV=1
> flask run
.. group-tab:: Powershell
.. code-block:: text
> $env:FLASK_SKIP_DOTENV = 1
> flask run
Environment Variables From virtualenv
-------------------------------------
If you do not want to install dotenv support, you can still set environment
variables by adding them to the end of the virtualenv's :file:`activate`
script. Activating the virtualenv will set the variables.
.. tabs::
.. group-tab:: Bash
Unix Bash, :file:`.venv/bin/activate`::
$ export FLASK_APP=hello
.. group-tab:: Fish
Fish, :file:`.venv/bin/activate.fish`::
$ set -x FLASK_APP hello
.. group-tab:: CMD
Windows CMD, :file:`.venv\\Scripts\\activate.bat`::
> set FLASK_APP=hello
.. group-tab:: Powershell
Windows Powershell, :file:`.venv\\Scripts\\activate.ps1`::
> $env:FLASK_APP = "hello"
It is preferred to use dotenv support over this, since :file:`.flaskenv` can be
committed to the repository so that it works automatically wherever the project
is checked out.
Custom Commands
---------------
The ``flask`` command is implemented using `Click`_. See that project's
documentation for full information about writing commands.
This example adds the command ``create-user`` that takes the argument
``name``. ::
import click
from flask import Flask
app = Flask(__name__)
@app.cli.command("create-user")
@click.argument("name")
def create_user(name):
...
::
$ flask create-user admin
This example adds the same command, but as ``user create``, a command in a
group. This is useful if you want to organize multiple related commands. ::
import click
from flask import Flask
from flask.cli import AppGroup
app = Flask(__name__)
user_cli = AppGroup('user')
@user_cli.command('create')
@click.argument('name')
def create_user(name):
...
app.cli.add_command(user_cli)
::
$ flask user create demo
See :ref:`testing-cli` for an overview of how to test your custom
commands.
Registering Commands with Blueprints
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
If your application uses blueprints, you can optionally register CLI
commands directly onto them. When your blueprint is registered onto your
application, the associated commands will be available to the ``flask``
command. By default, those commands will be nested in a group matching
the name of the blueprint.
.. code-block:: python
from flask import Blueprint
bp = Blueprint('students', __name__)
@bp.cli.command('create')
@click.argument('name')
def create(name):
...
app.register_blueprint(bp)
.. code-block:: text
$ flask students create alice
You can alter the group name by specifying the ``cli_group`` parameter
when creating the :class:`Blueprint` object, or later with
:meth:`app.register_blueprint(bp, cli_group='...') <Flask.register_blueprint>`.
The following are equivalent:
.. code-block:: python
bp = Blueprint('students', __name__, cli_group='other')
# or
app.register_blueprint(bp, cli_group='other')
.. code-block:: text
$ flask other create alice
Specifying ``cli_group=None`` will remove the nesting and merge the
commands directly to the application's level:
.. code-block:: python
bp = Blueprint('students', __name__, cli_group=None)
# or
app.register_blueprint(bp, cli_group=None)
.. code-block:: text
$ flask create alice
Application Context
~~~~~~~~~~~~~~~~~~~
Commands added using the Flask app's :attr:`~Flask.cli` or
:class:`~flask.cli.FlaskGroup` :meth:`~cli.AppGroup.command` decorator
will be executed with an application context pushed, so your custom
commands and parameters have access to the app and its configuration. The
:func:`~cli.with_appcontext` decorator can be used to get the same
behavior, but is not needed in most cases.
.. code-block:: python
import click
from flask.cli import with_appcontext
@click.command()
@with_appcontext
def do_work():
...
app.cli.add_command(do_work)
Plugins
-------
Flask will automatically load commands specified in the ``flask.commands``
`entry point`_. This is useful for extensions that want to add commands when
they are installed. Entry points are specified in :file:`pyproject.toml`:
.. code-block:: toml
[project.entry-points."flask.commands"]
my-command = "my_extension.commands:cli"
.. _entry point: https://packaging.python.org/tutorials/packaging-projects/#entry-points
Inside :file:`my_extension/commands.py` you can then export a Click
object::
import click
@click.command()
def cli():
...
Once that package is installed in the same virtualenv as your Flask project,
you can run ``flask my-command`` to invoke the command.
.. _custom-scripts:
Custom Scripts
--------------
When you are using the app factory pattern, it may be more convenient to define
your own Click script. Instead of using ``--app`` and letting Flask load
your application, you can create your own Click object and export it as a
`console script`_ entry point.
Create an instance of :class:`~cli.FlaskGroup` and pass it the factory::
import click
from flask import Flask
from flask.cli import FlaskGroup
def create_app():
app = Flask('wiki')
# other setup
return app
@click.group(cls=FlaskGroup, create_app=create_app)
def cli():
"""Management script for the Wiki application."""
Define the entry point in :file:`pyproject.toml`:
.. code-block:: toml
[project.scripts]
wiki = "wiki:cli"
Install the application in the virtualenv in editable mode and the custom
script is available. Note that you don't need to set ``--app``. ::
$ pip install -e .
$ wiki run
.. admonition:: Errors in Custom Scripts
When using a custom script, if you introduce an error in your
module-level code, the reloader will fail because it can no longer
load the entry point.
The ``flask`` command, being separate from your code, does not have
this issue and is recommended in most cases.
.. _console script: https://packaging.python.org/tutorials/packaging-projects/#console-scripts
PyCharm Integration
-------------------
PyCharm Professional provides a special Flask run configuration to run the development
server. For the Community Edition, and for other commands besides ``run``, you need to
create a custom run configuration. These instructions should be similar for any other
IDE you use.
In PyCharm, with your project open, click on *Run* from the menu bar and go to *Edit
Configurations*. You'll see a screen similar to this:
.. image:: _static/pycharm-run-config.png
:align: center
:class: screenshot
:alt: Screenshot of PyCharm run configuration.
Once you create a configuration for the ``flask run``, you can copy and change it to
call any other command.
Click the *+ (Add New Configuration)* button and select *Python*. Give the configuration
a name such as "flask run".
Click the *Script path* dropdown and change it to *Module name*, then input ``flask``.
The *Parameters* field is set to the CLI command to execute along with any arguments.
This example uses ``--app hello run --debug``, which will run the development server in
debug mode. ``--app hello`` should be the import or file with your Flask app.
If you installed your project as a package in your virtualenv, you may uncheck the
*PYTHONPATH* options. This will more accurately match how you deploy later.
Click *OK* to save and close the configuration. Select the configuration in the main
PyCharm window and click the play button next to it to run the server.
Now that you have a configuration for ``flask run``, you can copy that configuration and
change the *Parameters* argument to run a different CLI command.

View file

@ -0,0 +1,836 @@
Configuration Handling
======================
Applications need some kind of configuration. There are different settings
you might want to change depending on the application environment like
toggling the debug mode, setting the secret key, and other such
environment-specific things.
The way Flask is designed usually requires the configuration to be
available when the application starts up. You can hard code the
configuration in the code, which for many small applications is not
actually that bad, but there are better ways.
Independent of how you load your config, there is a config object
available which holds the loaded configuration values:
The :attr:`~flask.Flask.config` attribute of the :class:`~flask.Flask`
object. This is the place where Flask itself puts certain configuration
values and also where extensions can put their configuration values. But
this is also where you can have your own configuration.
Configuration Basics
--------------------
The :attr:`~flask.Flask.config` is actually a subclass of a dictionary and
can be modified just like any dictionary::
app = Flask(__name__)
app.config['TESTING'] = True
Certain configuration values are also forwarded to the
:attr:`~flask.Flask` object so you can read and write them from there::
app.testing = True
To update multiple keys at once you can use the :meth:`dict.update`
method::
app.config.update(
TESTING=True,
SECRET_KEY='192b9bdd22ab9ed4d12e236c78afcb9a393ec15f71bbf5dc987d54727823bcbf'
)
Debug Mode
----------
The :data:`DEBUG` config value is special because it may behave inconsistently if
changed after the app has begun setting up. In order to set debug mode reliably, use the
``--debug`` option on the ``flask`` or ``flask run`` command. ``flask run`` will use the
interactive debugger and reloader by default in debug mode.
.. code-block:: text
$ flask --app hello run --debug
Using the option is recommended. While it is possible to set :data:`DEBUG` in your
config or code, this is strongly discouraged. It can't be read early by the
``flask run`` command, and some systems or extensions may have already configured
themselves based on a previous value.
Builtin Configuration Values
----------------------------
The following configuration values are used internally by Flask:
.. py:data:: DEBUG
Whether debug mode is enabled. When using ``flask run`` to start the development
server, an interactive debugger will be shown for unhandled exceptions, and the
server will be reloaded when code changes. The :attr:`~flask.Flask.debug` attribute
maps to this config key. This is set with the ``FLASK_DEBUG`` environment variable.
It may not behave as expected if set in code.
**Do not enable debug mode when deploying in production.**
Default: ``False``
.. py:data:: TESTING
Enable testing mode. Exceptions are propagated rather than handled by the
the app's error handlers. Extensions may also change their behavior to
facilitate easier testing. You should enable this in your own tests.
Default: ``False``
.. py:data:: PROPAGATE_EXCEPTIONS
Exceptions are re-raised rather than being handled by the app's error
handlers. If not set, this is implicitly true if ``TESTING`` or ``DEBUG``
is enabled.
Default: ``None``
.. py:data:: TRAP_HTTP_EXCEPTIONS
If there is no handler for an ``HTTPException``-type exception, re-raise it
to be handled by the interactive debugger instead of returning it as a
simple error response.
Default: ``False``
.. py:data:: TRAP_BAD_REQUEST_ERRORS
Trying to access a key that doesn't exist from request dicts like ``args``
and ``form`` will return a 400 Bad Request error page. Enable this to treat
the error as an unhandled exception instead so that you get the interactive
debugger. This is a more specific version of ``TRAP_HTTP_EXCEPTIONS``. If
unset, it is enabled in debug mode.
Default: ``None``
.. py:data:: SECRET_KEY
A secret key that will be used for securely signing the session cookie
and can be used for any other security related needs by extensions or your
application. It should be a long random ``bytes`` or ``str``. For
example, copy the output of this to your config::
$ python -c 'import secrets; print(secrets.token_hex())'
'192b9bdd22ab9ed4d12e236c78afcb9a393ec15f71bbf5dc987d54727823bcbf'
**Do not reveal the secret key when posting questions or committing code.**
Default: ``None``
.. py:data:: SECRET_KEY_FALLBACKS
A list of old secret keys that can still be used for unsigning, most recent
first. This allows a project to implement key rotation without invalidating
active sessions or other recently-signed secrets.
Keys should be removed after an appropriate period of time, as checking each
additional key adds some overhead.
Flask's built-in secure cookie session supports this. Extensions that use
:data:`SECRET_KEY` may not support this yet.
Default: ``None``
.. versionadded:: 3.1
.. py:data:: SESSION_COOKIE_NAME
The name of the session cookie. Can be changed in case you already have a
cookie with the same name.
Default: ``'session'``
.. py:data:: SESSION_COOKIE_DOMAIN
The value of the ``Domain`` parameter on the session cookie. If not set, browsers
will only send the cookie to the exact domain it was set from. Otherwise, they
will send it to any subdomain of the given value as well.
Not setting this value is more restricted and secure than setting it.
Default: ``None``
.. warning::
If this is changed after the browser created a cookie is created with
one setting, it may result in another being created. Browsers may send
send both in an undefined order. In that case, you may want to change
:data:`SESSION_COOKIE_NAME` as well or otherwise invalidate old sessions.
.. versionchanged:: 2.3
Not set by default, does not fall back to ``SERVER_NAME``.
.. py:data:: SESSION_COOKIE_PATH
The path that the session cookie will be valid for. If not set, the cookie
will be valid underneath ``APPLICATION_ROOT`` or ``/`` if that is not set.
Default: ``None``
.. py:data:: SESSION_COOKIE_HTTPONLY
Browsers will not allow JavaScript access to cookies marked as "HTTP only"
for security.
Default: ``True``
.. py:data:: SESSION_COOKIE_SECURE
Browsers will only send cookies with requests over HTTPS if the cookie is
marked "secure". The application must be served over HTTPS for this to make
sense.
Default: ``False``
.. py:data:: SESSION_COOKIE_PARTITIONED
Browsers will send cookies based on the top-level document's domain, rather
than only the domain of the document setting the cookie. This prevents third
party cookies set in iframes from "leaking" between separate sites.
Browsers are beginning to disallow non-partitioned third party cookies, so
you need to mark your cookies partitioned if you expect them to work in such
embedded situations.
Enabling this implicitly enables :data:`SESSION_COOKIE_SECURE` as well, as
it is only valid when served over HTTPS.
Default: ``False``
.. versionadded:: 3.1
.. py:data:: SESSION_COOKIE_SAMESITE
Restrict how cookies are sent with requests from external sites. Can
be set to ``'Lax'`` (recommended) or ``'Strict'``.
See :ref:`security-cookie`.
Default: ``None``
.. versionadded:: 1.0
.. py:data:: PERMANENT_SESSION_LIFETIME
If ``session.permanent`` is true, the cookie's expiration will be set this
number of seconds in the future. Can either be a
:class:`datetime.timedelta` or an ``int``.
Flask's default cookie implementation validates that the cryptographic
signature is not older than this value.
Default: ``timedelta(days=31)`` (``2678400`` seconds)
.. py:data:: SESSION_REFRESH_EACH_REQUEST
Control whether the cookie is sent with every response when
``session.permanent`` is true. Sending the cookie every time (the default)
can more reliably keep the session from expiring, but uses more bandwidth.
Non-permanent sessions are not affected.
Default: ``True``
.. py:data:: USE_X_SENDFILE
When serving files, set the ``X-Sendfile`` header instead of serving the
data with Flask. Some web servers, such as Apache, recognize this and serve
the data more efficiently. This only makes sense when using such a server.
Default: ``False``
.. py:data:: SEND_FILE_MAX_AGE_DEFAULT
When serving files, set the cache control max age to this number of
seconds. Can be a :class:`datetime.timedelta` or an ``int``.
Override this value on a per-file basis using
:meth:`~flask.Flask.get_send_file_max_age` on the application or
blueprint.
If ``None``, ``send_file`` tells the browser to use conditional
requests will be used instead of a timed cache, which is usually
preferable.
Default: ``None``
.. py:data:: TRUSTED_HOSTS
Validate :attr:`.Request.host` and other attributes that use it against
these trusted values. Raise a :exc:`~werkzeug.exceptions.SecurityError` if
the host is invalid, which results in a 400 error. If it is ``None``, all
hosts are valid. Each value is either an exact match, or can start with
a dot ``.`` to match any subdomain.
Validation is done during routing against this value. ``before_request`` and
``after_request`` callbacks will still be called.
Default: ``None``
.. versionadded:: 3.1
.. py:data:: SERVER_NAME
Inform the application what host and port it is bound to.
Must be set if ``subdomain_matching`` is enabled, to be able to extract the
subdomain from the request.
Must be set for ``url_for`` to generate external URLs outside of a
request context.
Default: ``None``
.. versionchanged:: 3.1
Does not restrict requests to only this domain, for both
``subdomain_matching`` and ``host_matching``.
.. versionchanged:: 1.0
Does not implicitly enable ``subdomain_matching``.
.. versionchanged:: 2.3
Does not affect ``SESSION_COOKIE_DOMAIN``.
.. py:data:: APPLICATION_ROOT
Inform the application what path it is mounted under by the application /
web server. This is used for generating URLs outside the context of a
request (inside a request, the dispatcher is responsible for setting
``SCRIPT_NAME`` instead; see :doc:`/patterns/appdispatch`
for examples of dispatch configuration).
Will be used for the session cookie path if ``SESSION_COOKIE_PATH`` is not
set.
Default: ``'/'``
.. py:data:: PREFERRED_URL_SCHEME
Use this scheme for generating external URLs when not in a request context.
Default: ``'http'``
.. py:data:: MAX_CONTENT_LENGTH
The maximum number of bytes that will be read during this request. If
this limit is exceeded, a 413 :exc:`~werkzeug.exceptions.RequestEntityTooLarge`
error is raised. If it is set to ``None``, no limit is enforced at the
Flask application level. However, if it is ``None`` and the request has no
``Content-Length`` header and the WSGI server does not indicate that it
terminates the stream, then no data is read to avoid an infinite stream.
Each request defaults to this config. It can be set on a specific
:attr:`.Request.max_content_length` to apply the limit to that specific
view. This should be set appropriately based on an application's or view's
specific needs.
Default: ``None``
.. versionadded:: 0.6
.. py:data:: MAX_FORM_MEMORY_SIZE
The maximum size in bytes any non-file form field may be in a
``multipart/form-data`` body. If this limit is exceeded, a 413
:exc:`~werkzeug.exceptions.RequestEntityTooLarge` error is raised. If it is
set to ``None``, no limit is enforced at the Flask application level.
Each request defaults to this config. It can be set on a specific
:attr:`.Request.max_form_memory_parts` to apply the limit to that specific
view. This should be set appropriately based on an application's or view's
specific needs.
Default: ``500_000``
.. versionadded:: 3.1
.. py:data:: MAX_FORM_PARTS
The maximum number of fields that may be present in a
``multipart/form-data`` body. If this limit is exceeded, a 413
:exc:`~werkzeug.exceptions.RequestEntityTooLarge` error is raised. If it
is set to ``None``, no limit is enforced at the Flask application level.
Each request defaults to this config. It can be set on a specific
:attr:`.Request.max_form_parts` to apply the limit to that specific view.
This should be set appropriately based on an application's or view's
specific needs.
Default: ``1_000``
.. versionadded:: 3.1
.. py:data:: TEMPLATES_AUTO_RELOAD
Reload templates when they are changed. If not set, it will be enabled in
debug mode.
Default: ``None``
.. py:data:: EXPLAIN_TEMPLATE_LOADING
Log debugging information tracing how a template file was loaded. This can
be useful to figure out why a template was not loaded or the wrong file
appears to be loaded.
Default: ``False``
.. py:data:: MAX_COOKIE_SIZE
Warn if cookie headers are larger than this many bytes. Defaults to
``4093``. Larger cookies may be silently ignored by browsers. Set to
``0`` to disable the warning.
.. py:data:: PROVIDE_AUTOMATIC_OPTIONS
Set to ``False`` to disable the automatic addition of OPTIONS
responses. This can be overridden per route by altering the
``provide_automatic_options`` attribute.
.. versionadded:: 0.4
``LOGGER_NAME``
.. versionadded:: 0.5
``SERVER_NAME``
.. versionadded:: 0.6
``MAX_CONTENT_LENGTH``
.. versionadded:: 0.7
``PROPAGATE_EXCEPTIONS``, ``PRESERVE_CONTEXT_ON_EXCEPTION``
.. versionadded:: 0.8
``TRAP_BAD_REQUEST_ERRORS``, ``TRAP_HTTP_EXCEPTIONS``,
``APPLICATION_ROOT``, ``SESSION_COOKIE_DOMAIN``,
``SESSION_COOKIE_PATH``, ``SESSION_COOKIE_HTTPONLY``,
``SESSION_COOKIE_SECURE``
.. versionadded:: 0.9
``PREFERRED_URL_SCHEME``
.. versionadded:: 0.10
``JSON_AS_ASCII``, ``JSON_SORT_KEYS``, ``JSONIFY_PRETTYPRINT_REGULAR``
.. versionadded:: 0.11
``SESSION_REFRESH_EACH_REQUEST``, ``TEMPLATES_AUTO_RELOAD``,
``LOGGER_HANDLER_POLICY``, ``EXPLAIN_TEMPLATE_LOADING``
.. versionchanged:: 1.0
``LOGGER_NAME`` and ``LOGGER_HANDLER_POLICY`` were removed. See
:doc:`/logging` for information about configuration.
Added :data:`ENV` to reflect the :envvar:`FLASK_ENV` environment
variable.
Added :data:`SESSION_COOKIE_SAMESITE` to control the session
cookie's ``SameSite`` option.
Added :data:`MAX_COOKIE_SIZE` to control a warning from Werkzeug.
.. versionchanged:: 2.2
Removed ``PRESERVE_CONTEXT_ON_EXCEPTION``.
.. versionchanged:: 2.3
``JSON_AS_ASCII``, ``JSON_SORT_KEYS``, ``JSONIFY_MIMETYPE``, and
``JSONIFY_PRETTYPRINT_REGULAR`` were removed. The default ``app.json`` provider has
equivalent attributes instead.
.. versionchanged:: 2.3
``ENV`` was removed.
.. versionadded:: 3.10
Added :data:`PROVIDE_AUTOMATIC_OPTIONS` to control the default
addition of autogenerated OPTIONS responses.
Configuring from Python Files
-----------------------------
Configuration becomes more useful if you can store it in a separate file, ideally
located outside the actual application package. You can deploy your application, then
separately configure it for the specific deployment.
A common pattern is this::
app = Flask(__name__)
app.config.from_object('yourapplication.default_settings')
app.config.from_envvar('YOURAPPLICATION_SETTINGS')
This first loads the configuration from the
`yourapplication.default_settings` module and then overrides the values
with the contents of the file the :envvar:`YOURAPPLICATION_SETTINGS`
environment variable points to. This environment variable can be set
in the shell before starting the server:
.. tabs::
.. group-tab:: Bash
.. code-block:: text
$ export YOURAPPLICATION_SETTINGS=/path/to/settings.cfg
$ flask run
* Running on http://127.0.0.1:5000/
.. group-tab:: Fish
.. code-block:: text
$ set -x YOURAPPLICATION_SETTINGS /path/to/settings.cfg
$ flask run
* Running on http://127.0.0.1:5000/
.. group-tab:: CMD
.. code-block:: text
> set YOURAPPLICATION_SETTINGS=\path\to\settings.cfg
> flask run
* Running on http://127.0.0.1:5000/
.. group-tab:: Powershell
.. code-block:: text
> $env:YOURAPPLICATION_SETTINGS = "\path\to\settings.cfg"
> flask run
* Running on http://127.0.0.1:5000/
The configuration files themselves are actual Python files. Only values
in uppercase are actually stored in the config object later on. So make
sure to use uppercase letters for your config keys.
Here is an example of a configuration file::
# Example configuration
SECRET_KEY = '192b9bdd22ab9ed4d12e236c78afcb9a393ec15f71bbf5dc987d54727823bcbf'
Make sure to load the configuration very early on, so that extensions have
the ability to access the configuration when starting up. There are other
methods on the config object as well to load from individual files. For a
complete reference, read the :class:`~flask.Config` object's
documentation.
Configuring from Data Files
---------------------------
It is also possible to load configuration from a file in a format of
your choice using :meth:`~flask.Config.from_file`. For example to load
from a TOML file:
.. code-block:: python
import tomllib
app.config.from_file("config.toml", load=tomllib.load, text=False)
Or from a JSON file:
.. code-block:: python
import json
app.config.from_file("config.json", load=json.load)
Configuring from Environment Variables
--------------------------------------
In addition to pointing to configuration files using environment
variables, you may find it useful (or necessary) to control your
configuration values directly from the environment. Flask can be
instructed to load all environment variables starting with a specific
prefix into the config using :meth:`~flask.Config.from_prefixed_env`.
Environment variables can be set in the shell before starting the
server:
.. tabs::
.. group-tab:: Bash
.. code-block:: text
$ export FLASK_SECRET_KEY="5f352379324c22463451387a0aec5d2f"
$ export FLASK_MAIL_ENABLED=false
$ flask run
* Running on http://127.0.0.1:5000/
.. group-tab:: Fish
.. code-block:: text
$ set -x FLASK_SECRET_KEY "5f352379324c22463451387a0aec5d2f"
$ set -x FLASK_MAIL_ENABLED false
$ flask run
* Running on http://127.0.0.1:5000/
.. group-tab:: CMD
.. code-block:: text
> set FLASK_SECRET_KEY="5f352379324c22463451387a0aec5d2f"
> set FLASK_MAIL_ENABLED=false
> flask run
* Running on http://127.0.0.1:5000/
.. group-tab:: Powershell
.. code-block:: text
> $env:FLASK_SECRET_KEY = "5f352379324c22463451387a0aec5d2f"
> $env:FLASK_MAIL_ENABLED = "false"
> flask run
* Running on http://127.0.0.1:5000/
The variables can then be loaded and accessed via the config with a key
equal to the environment variable name without the prefix i.e.
.. code-block:: python
app.config.from_prefixed_env()
app.config["SECRET_KEY"] # Is "5f352379324c22463451387a0aec5d2f"
The prefix is ``FLASK_`` by default. This is configurable via the
``prefix`` argument of :meth:`~flask.Config.from_prefixed_env`.
Values will be parsed to attempt to convert them to a more specific type
than strings. By default :func:`json.loads` is used, so any valid JSON
value is possible, including lists and dicts. This is configurable via
the ``loads`` argument of :meth:`~flask.Config.from_prefixed_env`.
When adding a boolean value with the default JSON parsing, only "true"
and "false", lowercase, are valid values. Keep in mind that any
non-empty string is considered ``True`` by Python.
It is possible to set keys in nested dictionaries by separating the
keys with double underscore (``__``). Any intermediate keys that don't
exist on the parent dict will be initialized to an empty dict.
.. code-block:: text
$ export FLASK_MYAPI__credentials__username=user123
.. code-block:: python
app.config["MYAPI"]["credentials"]["username"] # Is "user123"
On Windows, environment variable keys are always uppercase, therefore
the above example would end up as ``MYAPI__CREDENTIALS__USERNAME``.
For even more config loading features, including merging and
case-insensitive Windows support, try a dedicated library such as
Dynaconf_, which includes integration with Flask.
.. _Dynaconf: https://www.dynaconf.com/
Configuration Best Practices
----------------------------
The downside with the approach mentioned earlier is that it makes testing
a little harder. There is no single 100% solution for this problem in
general, but there are a couple of things you can keep in mind to improve
that experience:
1. Create your application in a function and register blueprints on it.
That way you can create multiple instances of your application with
different configurations attached which makes unit testing a lot
easier. You can use this to pass in configuration as needed.
2. Do not write code that needs the configuration at import time. If you
limit yourself to request-only accesses to the configuration you can
reconfigure the object later on as needed.
3. Make sure to load the configuration very early on, so that
extensions can access the configuration when calling ``init_app``.
.. _config-dev-prod:
Development / Production
------------------------
Most applications need more than one configuration. There should be at
least separate configurations for the production server and the one used
during development. The easiest way to handle this is to use a default
configuration that is always loaded and part of the version control, and a
separate configuration that overrides the values as necessary as mentioned
in the example above::
app = Flask(__name__)
app.config.from_object('yourapplication.default_settings')
app.config.from_envvar('YOURAPPLICATION_SETTINGS')
Then you just have to add a separate :file:`config.py` file and export
``YOURAPPLICATION_SETTINGS=/path/to/config.py`` and you are done. However
there are alternative ways as well. For example you could use imports or
subclassing.
What is very popular in the Django world is to make the import explicit in
the config file by adding ``from yourapplication.default_settings
import *`` to the top of the file and then overriding the changes by hand.
You could also inspect an environment variable like
``YOURAPPLICATION_MODE`` and set that to `production`, `development` etc
and import different hard-coded files based on that.
An interesting pattern is also to use classes and inheritance for
configuration::
class Config(object):
TESTING = False
class ProductionConfig(Config):
DATABASE_URI = 'mysql://user@localhost/foo'
class DevelopmentConfig(Config):
DATABASE_URI = "sqlite:////tmp/foo.db"
class TestingConfig(Config):
DATABASE_URI = 'sqlite:///:memory:'
TESTING = True
To enable such a config you just have to call into
:meth:`~flask.Config.from_object`::
app.config.from_object('configmodule.ProductionConfig')
Note that :meth:`~flask.Config.from_object` does not instantiate the class
object. If you need to instantiate the class, such as to access a property,
then you must do so before calling :meth:`~flask.Config.from_object`::
from configmodule import ProductionConfig
app.config.from_object(ProductionConfig())
# Alternatively, import via string:
from werkzeug.utils import import_string
cfg = import_string('configmodule.ProductionConfig')()
app.config.from_object(cfg)
Instantiating the configuration object allows you to use ``@property`` in
your configuration classes::
class Config(object):
"""Base config, uses staging database server."""
TESTING = False
DB_SERVER = '192.168.1.56'
@property
def DATABASE_URI(self): # Note: all caps
return f"mysql://user@{self.DB_SERVER}/foo"
class ProductionConfig(Config):
"""Uses production database server."""
DB_SERVER = '192.168.19.32'
class DevelopmentConfig(Config):
DB_SERVER = 'localhost'
class TestingConfig(Config):
DB_SERVER = 'localhost'
DATABASE_URI = 'sqlite:///:memory:'
There are many different ways and it's up to you how you want to manage
your configuration files. However here a list of good recommendations:
- Keep a default configuration in version control. Either populate the
config with this default configuration or import it in your own
configuration files before overriding values.
- Use an environment variable to switch between the configurations.
This can be done from outside the Python interpreter and makes
development and deployment much easier because you can quickly and
easily switch between different configs without having to touch the
code at all. If you are working often on different projects you can
even create your own script for sourcing that activates a virtualenv
and exports the development configuration for you.
- Use a tool like `fabric`_ to push code and configuration separately
to the production server(s).
.. _fabric: https://www.fabfile.org/
.. _instance-folders:
Instance Folders
----------------
.. versionadded:: 0.8
Flask 0.8 introduces instance folders. Flask for a long time made it
possible to refer to paths relative to the application's folder directly
(via :attr:`Flask.root_path`). This was also how many developers loaded
configurations stored next to the application. Unfortunately however this
only works well if applications are not packages in which case the root
path refers to the contents of the package.
With Flask 0.8 a new attribute was introduced:
:attr:`Flask.instance_path`. It refers to a new concept called the
“instance folder”. The instance folder is designed to not be under
version control and be deployment specific. It's the perfect place to
drop things that either change at runtime or configuration files.
You can either explicitly provide the path of the instance folder when
creating the Flask application or you can let Flask autodetect the
instance folder. For explicit configuration use the `instance_path`
parameter::
app = Flask(__name__, instance_path='/path/to/instance/folder')
Please keep in mind that this path *must* be absolute when provided.
If the `instance_path` parameter is not provided the following default
locations are used:
- Uninstalled module::
/myapp.py
/instance
- Uninstalled package::
/myapp
/__init__.py
/instance
- Installed module or package::
$PREFIX/lib/pythonX.Y/site-packages/myapp
$PREFIX/var/myapp-instance
``$PREFIX`` is the prefix of your Python installation. This can be
``/usr`` or the path to your virtualenv. You can print the value of
``sys.prefix`` to see what the prefix is set to.
Since the config object provided loading of configuration files from
relative filenames we made it possible to change the loading via filenames
to be relative to the instance path if wanted. The behavior of relative
paths in config files can be flipped between “relative to the application
root” (the default) to “relative to instance folder” via the
`instance_relative_config` switch to the application constructor::
app = Flask(__name__, instance_relative_config=True)
Here is a full example of how to configure Flask to preload the config
from a module and then override the config from a file in the instance
folder if it exists::
app = Flask(__name__, instance_relative_config=True)
app.config.from_object('yourapplication.default_settings')
app.config.from_pyfile('application.cfg', silent=True)
The path to the instance folder can be found via the
:attr:`Flask.instance_path`. Flask also provides a shortcut to open a
file from the instance folder with :meth:`Flask.open_instance_resource`.
Example usage for both::
filename = os.path.join(app.instance_path, 'application.cfg')
with open(filename) as f:
config = f.read()
# or via open_instance_resource:
with app.open_instance_resource('application.cfg') as f:
config = f.read()

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Contributing
============
See the Pallets `detailed contributing documentation <_contrib>`_ for many ways
to contribute, including reporting issues, requesting features, asking or
answering questions, and making PRs.
.. _contrib: https://palletsprojects.com/contributing/

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Debugging Application Errors
============================
In Production
-------------
**Do not run the development server, or enable the built-in debugger, in
a production environment.** The debugger allows executing arbitrary
Python code from the browser. It's protected by a pin, but that should
not be relied on for security.
Use an error logging tool, such as Sentry, as described in
:ref:`error-logging-tools`, or enable logging and notifications as
described in :doc:`/logging`.
If you have access to the server, you could add some code to start an
external debugger if ``request.remote_addr`` matches your IP. Some IDE
debuggers also have a remote mode so breakpoints on the server can be
interacted with locally. Only enable a debugger temporarily.
The Built-In Debugger
---------------------
The built-in Werkzeug development server provides a debugger which shows
an interactive traceback in the browser when an unhandled error occurs
during a request. This debugger should only be used during development.
.. image:: _static/debugger.png
:align: center
:class: screenshot
:alt: screenshot of debugger in action
.. warning::
The debugger allows executing arbitrary Python code from the
browser. It is protected by a pin, but still represents a major
security risk. Do not run the development server or debugger in a
production environment.
The debugger is enabled by default when the development server is run in debug mode.
.. code-block:: text
$ flask --app hello run --debug
When running from Python code, passing ``debug=True`` enables debug mode, which is
mostly equivalent.
.. code-block:: python
app.run(debug=True)
:doc:`/server` and :doc:`/cli` have more information about running the debugger and
debug mode. More information about the debugger can be found in the `Werkzeug
documentation <https://werkzeug.palletsprojects.com/debug/>`__.
External Debuggers
------------------
External debuggers, such as those provided by IDEs, can offer a more
powerful debugging experience than the built-in debugger. They can also
be used to step through code during a request before an error is raised,
or if no error is raised. Some even have a remote mode so you can debug
code running on another machine.
When using an external debugger, the app should still be in debug mode, otherwise Flask
turns unhandled errors into generic 500 error pages. However, the built-in debugger and
reloader should be disabled so they don't interfere with the external debugger.
.. code-block:: text
$ flask --app hello run --debug --no-debugger --no-reload
When running from Python:
.. code-block:: python
app.run(debug=True, use_debugger=False, use_reloader=False)
Disabling these isn't required, an external debugger will continue to work with the
following caveats.
- If the built-in debugger is not disabled, it will catch unhandled exceptions before
the external debugger can.
- If the reloader is not disabled, it could cause an unexpected reload if code changes
during a breakpoint.
- The development server will still catch unhandled exceptions if the built-in
debugger is disabled, otherwise it would crash on any error. If you want that (and
usually you don't) pass ``passthrough_errors=True`` to ``app.run``.
.. code-block:: python
app.run(
debug=True, passthrough_errors=True,
use_debugger=False, use_reloader=False
)

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Apache httpd
============
`Apache httpd`_ is a fast, production level HTTP server. When serving
your application with one of the WSGI servers listed in :doc:`index`, it
is often good or necessary to put a dedicated HTTP server in front of
it. This "reverse proxy" can handle incoming requests, TLS, and other
security and performance concerns better than the WSGI server.
httpd can be installed using your system package manager, or a pre-built
executable for Windows. Installing and running httpd itself is outside
the scope of this doc. This page outlines the basics of configuring
httpd to proxy your application. Be sure to read its documentation to
understand what features are available.
.. _Apache httpd: https://httpd.apache.org/
Domain Name
-----------
Acquiring and configuring a domain name is outside the scope of this
doc. In general, you will buy a domain name from a registrar, pay for
server space with a hosting provider, and then point your registrar
at the hosting provider's name servers.
To simulate this, you can also edit your ``hosts`` file, located at
``/etc/hosts`` on Linux. Add a line that associates a name with the
local IP.
Modern Linux systems may be configured to treat any domain name that
ends with ``.localhost`` like this without adding it to the ``hosts``
file.
.. code-block:: python
:caption: ``/etc/hosts``
127.0.0.1 hello.localhost
Configuration
-------------
The httpd configuration is located at ``/etc/httpd/conf/httpd.conf`` on
Linux. It may be different depending on your operating system. Check the
docs and look for ``httpd.conf``.
Remove or comment out any existing ``DocumentRoot`` directive. Add the
config lines below. We'll assume the WSGI server is listening locally at
``http://127.0.0.1:8000``.
.. code-block:: apache
:caption: ``/etc/httpd/conf/httpd.conf``
LoadModule proxy_module modules/mod_proxy.so
LoadModule proxy_http_module modules/mod_proxy_http.so
ProxyPass / http://127.0.0.1:8000/
RequestHeader set X-Forwarded-Proto http
RequestHeader set X-Forwarded-Prefix /
The ``LoadModule`` lines might already exist. If so, make sure they are
uncommented instead of adding them manually.
Then :doc:`proxy_fix` so that your application uses the ``X-Forwarded``
headers. ``X-Forwarded-For`` and ``X-Forwarded-Host`` are automatically
set by ``ProxyPass``.

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ASGI
====
If you'd like to use an ASGI server you will need to utilise WSGI to
ASGI middleware. The asgiref
`WsgiToAsgi <https://github.com/django/asgiref#wsgi-to-asgi-adapter>`_
adapter is recommended as it integrates with the event loop used for
Flask's :ref:`async_await` support. You can use the adapter by
wrapping the Flask app,
.. code-block:: python
from asgiref.wsgi import WsgiToAsgi
from flask import Flask
app = Flask(__name__)
...
asgi_app = WsgiToAsgi(app)
and then serving the ``asgi_app`` with the ASGI server, e.g. using
`Hypercorn <https://github.com/pgjones/hypercorn>`_,
.. sourcecode:: text
$ hypercorn module:asgi_app

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eventlet
========
Prefer using :doc:`gunicorn` with eventlet workers rather than using
`eventlet`_ directly. Gunicorn provides a much more configurable and
production-tested server.
`eventlet`_ allows writing asynchronous, coroutine-based code that looks
like standard synchronous Python. It uses `greenlet`_ to enable task
switching without writing ``async/await`` or using ``asyncio``.
:doc:`gevent` is another library that does the same thing. Certain
dependencies you have, or other considerations, may affect which of the
two you choose to use.
eventlet provides a WSGI server that can handle many connections at once
instead of one per worker process. You must actually use eventlet in
your own code to see any benefit to using the server.
.. _eventlet: https://eventlet.net/
.. _greenlet: https://greenlet.readthedocs.io/en/latest/
Installing
----------
When using eventlet, greenlet>=1.0 is required, otherwise context locals
such as ``request`` will not work as expected. When using PyPy,
PyPy>=7.3.7 is required.
Create a virtualenv, install your application, then install
``eventlet``.
.. code-block:: text
$ cd hello-app
$ python -m venv .venv
$ . .venv/bin/activate
$ pip install . # install your application
$ pip install eventlet
Running
-------
To use eventlet to serve your application, write a script that imports
its ``wsgi.server``, as well as your app or app factory.
.. code-block:: python
:caption: ``wsgi.py``
import eventlet
from eventlet import wsgi
from hello import create_app
app = create_app()
wsgi.server(eventlet.listen(("127.0.0.1", 8000)), app)
.. code-block:: text
$ python wsgi.py
(x) wsgi starting up on http://127.0.0.1:8000
Binding Externally
------------------
eventlet should not be run as root because it would cause your
application code to run as root, which is not secure. However, this
means it will not be possible to bind to port 80 or 443. Instead, a
reverse proxy such as :doc:`nginx` or :doc:`apache-httpd` should be used
in front of eventlet.
You can bind to all external IPs on a non-privileged port by using
``0.0.0.0`` in the server arguments shown in the previous section.
Don't do this when using a reverse proxy setup, otherwise it will be
possible to bypass the proxy.
``0.0.0.0`` is not a valid address to navigate to, you'd use a specific
IP address in your browser.

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gevent
======
Prefer using :doc:`gunicorn` or :doc:`uwsgi` with gevent workers rather
than using `gevent`_ directly. Gunicorn and uWSGI provide much more
configurable and production-tested servers.
`gevent`_ allows writing asynchronous, coroutine-based code that looks
like standard synchronous Python. It uses `greenlet`_ to enable task
switching without writing ``async/await`` or using ``asyncio``.
:doc:`eventlet` is another library that does the same thing. Certain
dependencies you have, or other considerations, may affect which of the
two you choose to use.
gevent provides a WSGI server that can handle many connections at once
instead of one per worker process. You must actually use gevent in your
own code to see any benefit to using the server.
.. _gevent: https://www.gevent.org/
.. _greenlet: https://greenlet.readthedocs.io/en/latest/
Installing
----------
When using gevent, greenlet>=1.0 is required, otherwise context locals
such as ``request`` will not work as expected. When using PyPy,
PyPy>=7.3.7 is required.
Create a virtualenv, install your application, then install ``gevent``.
.. code-block:: text
$ cd hello-app
$ python -m venv .venv
$ . .venv/bin/activate
$ pip install . # install your application
$ pip install gevent
Running
-------
To use gevent to serve your application, write a script that imports its
``WSGIServer``, as well as your app or app factory.
.. code-block:: python
:caption: ``wsgi.py``
from gevent.pywsgi import WSGIServer
from hello import create_app
app = create_app()
http_server = WSGIServer(("127.0.0.1", 8000), app)
http_server.serve_forever()
.. code-block:: text
$ python wsgi.py
No output is shown when the server starts.
Binding Externally
------------------
gevent should not be run as root because it would cause your
application code to run as root, which is not secure. However, this
means it will not be possible to bind to port 80 or 443. Instead, a
reverse proxy such as :doc:`nginx` or :doc:`apache-httpd` should be used
in front of gevent.
You can bind to all external IPs on a non-privileged port by using
``0.0.0.0`` in the server arguments shown in the previous section. Don't
do this when using a reverse proxy setup, otherwise it will be possible
to bypass the proxy.
``0.0.0.0`` is not a valid address to navigate to, you'd use a specific
IP address in your browser.

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Gunicorn
========
`Gunicorn`_ is a pure Python WSGI server with simple configuration and
multiple worker implementations for performance tuning.
* It tends to integrate easily with hosting platforms.
* It does not support Windows (but does run on WSL).
* It is easy to install as it does not require additional dependencies
or compilation.
* It has built-in async worker support using gevent or eventlet.
This page outlines the basics of running Gunicorn. Be sure to read its
`documentation`_ and use ``gunicorn --help`` to understand what features
are available.
.. _Gunicorn: https://gunicorn.org/
.. _documentation: https://docs.gunicorn.org/
Installing
----------
Gunicorn is easy to install, as it does not require external
dependencies or compilation. It runs on Windows only under WSL.
Create a virtualenv, install your application, then install
``gunicorn``.
.. code-block:: text
$ cd hello-app
$ python -m venv .venv
$ . .venv/bin/activate
$ pip install . # install your application
$ pip install gunicorn
Running
-------
The only required argument to Gunicorn tells it how to load your Flask
application. The syntax is ``{module_import}:{app_variable}``.
``module_import`` is the dotted import name to the module with your
application. ``app_variable`` is the variable with the application. It
can also be a function call (with any arguments) if you're using the
app factory pattern.
.. code-block:: text
# equivalent to 'from hello import app'
$ gunicorn -w 4 'hello:app'
# equivalent to 'from hello import create_app; create_app()'
$ gunicorn -w 4 'hello:create_app()'
Starting gunicorn 20.1.0
Listening at: http://127.0.0.1:8000 (x)
Using worker: sync
Booting worker with pid: x
Booting worker with pid: x
Booting worker with pid: x
Booting worker with pid: x
The ``-w`` option specifies the number of processes to run; a starting
value could be ``CPU * 2``. The default is only 1 worker, which is
probably not what you want for the default worker type.
Logs for each request aren't shown by default, only worker info and
errors are shown. To show access logs on stdout, use the
``--access-logfile=-`` option.
Binding Externally
------------------
Gunicorn should not be run as root because it would cause your
application code to run as root, which is not secure. However, this
means it will not be possible to bind to port 80 or 443. Instead, a
reverse proxy such as :doc:`nginx` or :doc:`apache-httpd` should be used
in front of Gunicorn.
You can bind to all external IPs on a non-privileged port using the
``-b 0.0.0.0`` option. Don't do this when using a reverse proxy setup,
otherwise it will be possible to bypass the proxy.
.. code-block:: text
$ gunicorn -w 4 -b 0.0.0.0 'hello:create_app()'
Listening at: http://0.0.0.0:8000 (x)
``0.0.0.0`` is not a valid address to navigate to, you'd use a specific
IP address in your browser.
Async with gevent or eventlet
-----------------------------
The default sync worker is appropriate for many use cases. If you need
asynchronous support, Gunicorn provides workers using either `gevent`_
or `eventlet`_. This is not the same as Python's ``async/await``, or the
ASGI server spec. You must actually use gevent/eventlet in your own code
to see any benefit to using the workers.
When using either gevent or eventlet, greenlet>=1.0 is required,
otherwise context locals such as ``request`` will not work as expected.
When using PyPy, PyPy>=7.3.7 is required.
To use gevent:
.. code-block:: text
$ gunicorn -k gevent 'hello:create_app()'
Starting gunicorn 20.1.0
Listening at: http://127.0.0.1:8000 (x)
Using worker: gevent
Booting worker with pid: x
To use eventlet:
.. code-block:: text
$ gunicorn -k eventlet 'hello:create_app()'
Starting gunicorn 20.1.0
Listening at: http://127.0.0.1:8000 (x)
Using worker: eventlet
Booting worker with pid: x
.. _gevent: https://www.gevent.org/
.. _eventlet: https://eventlet.net/

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Deploying to Production
=======================
After developing your application, you'll want to make it available
publicly to other users. When you're developing locally, you're probably
using the built-in development server, debugger, and reloader. These
should not be used in production. Instead, you should use a dedicated
WSGI server or hosting platform, some of which will be described here.
"Production" means "not development", which applies whether you're
serving your application publicly to millions of users or privately /
locally to a single user. **Do not use the development server when
deploying to production. It is intended for use only during local
development. It is not designed to be particularly secure, stable, or
efficient.**
Self-Hosted Options
-------------------
Flask is a WSGI *application*. A WSGI *server* is used to run the
application, converting incoming HTTP requests to the standard WSGI
environ, and converting outgoing WSGI responses to HTTP responses.
The primary goal of these docs is to familiarize you with the concepts
involved in running a WSGI application using a production WSGI server
and HTTP server. There are many WSGI servers and HTTP servers, with many
configuration possibilities. The pages below discuss the most common
servers, and show the basics of running each one. The next section
discusses platforms that can manage this for you.
.. toctree::
:maxdepth: 1
gunicorn
waitress
mod_wsgi
uwsgi
gevent
eventlet
asgi
WSGI servers have HTTP servers built-in. However, a dedicated HTTP
server may be safer, more efficient, or more capable. Putting an HTTP
server in front of the WSGI server is called a "reverse proxy."
.. toctree::
:maxdepth: 1
proxy_fix
nginx
apache-httpd
This list is not exhaustive, and you should evaluate these and other
servers based on your application's needs. Different servers will have
different capabilities, configuration, and support.
Hosting Platforms
-----------------
There are many services available for hosting web applications without
needing to maintain your own server, networking, domain, etc. Some
services may have a free tier up to a certain time or bandwidth. Many of
these services use one of the WSGI servers described above, or a similar
interface. The links below are for some of the most common platforms,
which have instructions for Flask, WSGI, or Python.
- `PythonAnywhere <https://help.pythonanywhere.com/pages/Flask/>`_
- `Google App Engine <https://cloud.google.com/appengine/docs/standard/python3/building-app>`_
- `Google Cloud Run <https://cloud.google.com/run/docs/quickstarts/build-and-deploy/deploy-python-service>`_
- `AWS Elastic Beanstalk <https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/create-deploy-python-flask.html>`_
- `Microsoft Azure <https://docs.microsoft.com/en-us/azure/app-service/quickstart-python>`_
This list is not exhaustive, and you should evaluate these and other
services based on your application's needs. Different services will have
different capabilities, configuration, pricing, and support.
You'll probably need to :doc:`proxy_fix` when using most hosting
platforms.

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mod_wsgi
========
`mod_wsgi`_ is a WSGI server integrated with the `Apache httpd`_ server.
The modern `mod_wsgi-express`_ command makes it easy to configure and
start the server without needing to write Apache httpd configuration.
* Tightly integrated with Apache httpd.
* Supports Windows directly.
* Requires a compiler and the Apache development headers to install.
* Does not require a reverse proxy setup.
This page outlines the basics of running mod_wsgi-express, not the more
complex installation and configuration with httpd. Be sure to read the
`mod_wsgi-express`_, `mod_wsgi`_, and `Apache httpd`_ documentation to
understand what features are available.
.. _mod_wsgi-express: https://pypi.org/project/mod-wsgi/
.. _mod_wsgi: https://modwsgi.readthedocs.io/
.. _Apache httpd: https://httpd.apache.org/
Installing
----------
Installing mod_wsgi requires a compiler and the Apache server and
development headers installed. You will get an error if they are not.
How to install them depends on the OS and package manager that you use.
Create a virtualenv, install your application, then install
``mod_wsgi``.
.. code-block:: text
$ cd hello-app
$ python -m venv .venv
$ . .venv/bin/activate
$ pip install . # install your application
$ pip install mod_wsgi
Running
-------
The only argument to ``mod_wsgi-express`` specifies a script containing
your Flask application, which must be called ``application``. You can
write a small script to import your app with this name, or to create it
if using the app factory pattern.
.. code-block:: python
:caption: ``wsgi.py``
from hello import app
application = app
.. code-block:: python
:caption: ``wsgi.py``
from hello import create_app
application = create_app()
Now run the ``mod_wsgi-express start-server`` command.
.. code-block:: text
$ mod_wsgi-express start-server wsgi.py --processes 4
The ``--processes`` option specifies the number of worker processes to
run; a starting value could be ``CPU * 2``.
Logs for each request aren't show in the terminal. If an error occurs,
its information is written to the error log file shown when starting the
server.
Binding Externally
------------------
Unlike the other WSGI servers in these docs, mod_wsgi can be run as
root to bind to privileged ports like 80 and 443. However, it must be
configured to drop permissions to a different user and group for the
worker processes.
For example, if you created a ``hello`` user and group, you should
install your virtualenv and application as that user, then tell
mod_wsgi to drop to that user after starting.
.. code-block:: text
$ sudo /home/hello/.venv/bin/mod_wsgi-express start-server \
/home/hello/wsgi.py \
--user hello --group hello --port 80 --processes 4

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