.. _running: Running ======= Since pygeoapi is a Python API at its core, it can be served via numerous web server scenarios. So far, pygeoapi can be served via Flask `WSGI`_, Starlette `ASGI`_, and `Django`_. This section covers how pygeoapi can be run in development environments and in production environments. For running pygeoapi using Docker, refer to the :ref:`docker` section. Running in development ---------------------- The ``pygeoapi serve`` is the easiest way to run pygeoapi in your own machine. This command starts a pygeoapi server instance. By default, a Flask server is started, but Starlette and Django are available as well. Using the ``--starlette`` or ``--django`` flags will start pygeoapi using the specified server technology. It is also advisable to install the development dependencies (contained in the requirements-dev.txt file) for running pygeoapi for development. To do so, run the following command: .. code-block:: bash pip3 install -r requirements-dev.txt .. note:: * Changes to the configuration files of pygeoapi or OpenAPI requires a server restart (configurations are loaded once at server startup for performance). * Changes to the codebase require a rebuild (i.e., re-running the ``pip3 install .`` command). For instructions for running pygeoapi with hot-reloading, refer to the "Hot-reloading" section. Flask WSGI ^^^^^^^^^^ Web Server Gateway Interface (WSGI) is a standard for how web servers communicate with Python applications. By having a WSGI server, HTTP requests are processed into threads/processes for better performance. Flask is a WSGI implementation which pygeoapi utilizes to communicate with the core API. .. code-block:: bash HTTP request <--> Flask (pygeoapi/flask_app.py) <--> pygeoapi API (pygeoapi/api.py) The Flask WSGI server can be run as follows: .. code-block:: bash pygeoapi serve --flask pygeoapi serve # uses Flask by default To integrate pygeoapi as part of another Flask application, use Flask blueprints: .. code-block:: python from flask import Flask from pygeoapi.flask_app import BLUEPRINT as pygeoapi_blueprint app = Flask(__name__) app.register_blueprint(pygeoapi_blueprint, url_prefix='/oapi') @app.route('/') def hello_world(): return 'Hello, World!' As a result, your application will be available at http://localhost:5000/ and pygeoapi will be available at http://localhost:5000/oapi Starlette ASGI ^^^^^^^^^^^^^^ Asynchronous Server Gateway Interface (ASGI) is standard interface between async-capable web servers, frameworks, and applications written in Python. ASGI provides the benefits of WSGI as well as asynchronous capabilities. Starlette is an ASGI implementation which pygeoapi utilizes to communicate with the core API in asynchronous mode. .. code-block:: bash HTTP request <--> Starlette (pygeoapi/starlette_app.py) <--> pygeoapi API (pygeoapi/api.py) To use Starlette as the web server it is necessary to install its dependencies running the following command: .. code-block:: bash pip3 install -r requirements-starlette.txt Then, the Starlette ASGI server can be run as follows: .. code-block:: bash pygeoapi serve --starlette To integrate pygeoapi as part of another Starlette application: .. code-block:: python from starlette.applications import Starlette from starlette.responses import PlainTextResponse from starlette.routing import Route from pygeoapi.starlette_app import APP as pygeoapi_app async def homepage(request): return PlainTextResponse('Hello, World!') app = Starlette(debug=True, routes=[ Route('/', homepage), ]) app.mount('/oapi', pygeoapi_app) As a result, your application will be available at http://localhost:5000/ and pygeoapi will be available at http://localhost:5000/oapi Django ^^^^^^ `Django`_ is a Python web framework that encourages rapid development and clean, pragmatic design. Similarly to Flask and Starlette, Django can be used by pygeoapi to communicate with the core API. .. code-block:: bash HTTP request <--> Django (pygeoapi/django_app.py) <--> pygeoapi API (pygeoapi/api.py) To use Django as a web server it is necessary to install its dependencies running the following command: .. code-block:: bash pip3 install -r requirements-django.txt After Django rependencies is installed, pygeoapi can be run as follows: .. code-block:: bash pygeoapi serve --django As a result, your Django application will be available at http://localhost:5000/. To integrate pygeoapi as part of another Django project in a pluggable it is necessary to add the pygeoapi urls to the main Django application urls: .. code-block:: python from django.contrib import admin from django.urls import path, include from pygeoapi.django_pygeoapi import urls as pygeoapi_urls urlpatterns = [ path('admin/', admin.site.urls), path('sample-project/', include(pygeoapi_urls)), ] This integration can be seen in the provided example Django project. Refer to the `Django example in the pygeoapi-examples repository`_ for the integration of pygeoapi with an already existing Django application. .. note:: To enable HTTP POST/PUT/PATCH/DELETE functionality, `django.middleware.csrf.CsrfViewMiddleware` must not be set. Note that this enables create/replace/update/delete functionality against resources in your application. Hot-reloading ^^^^^^^^^^^^^ The ``pygeoapi serve`` uses the current pygeoapi installation. If the installation was performed using the setup command provided in the :ref:`install` section (``pip3 install .``), changes made to the codebase of pygeoapi are not going to be reflected in the application until a rebuild (i.e., re-running ``pip3 install .``). By hot-reloading we mean to be able to directly see changes reflected in the application without reinstalling the pygeoapi package or resetting the server. This is useful for development, as the changes made by developers are easily and rapidly reflected and they can take advantage of the hot-reloading capabilities that offer each of the web servers available. To enable hot-reloading, install the pygeoapi package using pip (instead of `setup.py`) with the following command: .. code-block:: bash pip3 install -e . .. note:: This command must be run from the root directory of pygeoapi. After the local package is built, run ``pygeoapi serve`` again and the changes to the codebase will be reflected live on the running instance. Running in production --------------------- Running ``pygeoapi serve`` in production is not recommended or advisable. Preferred options are described below. .. seealso:: :ref:`docker` for container-based production installations. Apache and mod_wsgi ^^^^^^^^^^^^^^^^^^^ Deploying pygeoapi via `mod_wsgi`_ provides a simple approach to enabling within Apache. To deploy with mod_wsgi, your Apache instance must have mod_wsgi enabled within Apache. At this point, set up the following Python WSGI script: .. code-block:: python import os os.environ['PYGEOAPI_CONFIG'] = '/path/to/my-pygeoapi-config.yml' os.environ['PYGEOAPI_OPENAPI'] = '/path/to/my-pygeoapi-openapi.yml' from pygeoapi.flask_app import APP as application Now configure in Apache: .. code-block:: apache WSGIDaemonProcess pygeoapi processes=1 threads=1 WSGIScriptAlias /pygeoapi /path/to/pygeoapi.wsgi process-group=pygeoapi application-group=%{GLOBAL} Header set Access-Control-Allow-Origin "*" When running pygeoapi in a Python virtual environment, use directives similar to the below: .. code-block:: apache WSGIDaemonProcess pygeoapi processes=1 threads=1 python-home=/path/to/venv/pygeoapi WSGIScriptAlias /pygeoapi /path/to/pygeoapi.wsgi process-group=pygeoapi application-group=%{RESOURCE} Gunicorn ^^^^^^^^ `Gunicorn`_ (for UNIX) is one of several Python WSGI HTTP servers that can be used for production environments. .. code-block:: bash HTTP request --> WSGI or ASGI server (gunicorn) <--> Flask or Starlette (pygeoapi/flask_app.py or pygeoapi/starlette_app.py) <--> pygeoapi API .. note:: Gunicorn is as easy to install as ``pip3 install gunicorn`` .. note:: For a complete list of WSGI server implementations, see the `WSGI server list`_. Gunicorn and Flask ^^^^^^^^^^^^^^^^^^ Gunicorn and Flask is simple to run: .. code-block:: bash gunicorn pygeoapi.flask_app:APP .. note:: For extra configuration parameters like port binding, workers, and logging please consult the `Gunicorn settings`_. Gunicorn and Starlette ^^^^^^^^^^^^^^^^^^^^^^ Running Gunicorn with Starlette requires the `Uvicorn`_ library, which provides async capabilities along with Gunicorn. Uvicorn includes a Gunicorn worker class allowing you to run ASGI applications, with all of Uvicorn's performance benefits, while also giving you Gunicorn's fully-featured process management. It is simple to run using the following command: .. code-block:: bash gunicorn pygeoapi.starlette_app:APP -w 4 -k uvicorn.workers.UvicornH11Worker .. note:: Uvicorn is as easy to install as ``pip3 install uvicorn`` Summary ------- pygeoapi has many approaches for deploying depending on your requirements. Choose one that works for you and modify accordingly. .. note:: Additional approaches are welcome and encouraged; see :ref:`contributing` for more information on how to contribute to and improve the documentation .. _`WSGI`: https://en.wikipedia.org/wiki/Web_Server_Gateway_Interface .. _`ASGI`: https://asgi.readthedocs.io/en/latest .. _`Gunicorn`: https://gunicorn.org .. _`WSGI server list`: https://wsgi.readthedocs.io/en/latest/servers.html .. _`Gunicorn settings`: https://docs.gunicorn.org/en/stable/settings.html .. _`Uvicorn`: https://www.uvicorn.org .. _`mod_wsgi`: https://modwsgi.readthedocs.io/en/master .. _`Django`: https://www.djangoproject.com .. _`Django example in the pygeoapi-examples repository`: https://github.com/geopython/pygeoapi-examples/blob/main/django/sample_project/README.md