MapProxy implements the Web Server Gateway Interface (WSGI) which is for Python what the Servlet API is for Java. There are different ways to deploy WSGI web applications.

MapProxy comes with a simple HTTP server that is easy to start and sufficient for local testing, see Testing. For production and load testing it is recommended to choose one of the production setups.


The serve-develop subcommand of mapproxy-util starts an HTTP server for local testing. It takes an existing MapProxy configuration file as an argument:

mapproxy-util serve-develop mapproxy.yaml

The server automatically reloads if the configuration or any code of MapProxy changes.

--bind, -b

Set the socket MapProxy should listen. Defaults to localhost:8080. Accepts either a port number or hostname:portnumber.


Start MapProxy in debug mode. If you have installed Werkzeug (recommended) or Paste, you will get an interactive traceback in the web browser on any unhandled exception (internal error).


This server is sufficient for local testing of the configuration, but it is not stable for production or load testing.

The serve-multiapp-develop subcommand of mapproxy-util works similar to serve-develop but takes a directory of MapProxy configurations. See MultiMapProxy.


There are two common ways to deploy MapProxy in production.

Embedded in HTTP server
You can directly integrate MapProxy into your web server. Apache can integrate Python web services with the mod_wsgi extension for example.
Behind an HTTP server or proxy
You can run MapProxy as a separate local HTTP server behind an existing web server (nginx, Apache, etc.) or an HTTP proxy (Varnish, squid, etc).

Both approaches require a configuration that maps your MapProxy configuration with the MapProxy application. You can write a small script file for that.

Running MapProxy as a FastCGI server behind HTTP server, a third option, is no longer advised for new setups since the FastCGI package (flup) is no longer maintained and the Python HTTP server improved significantly.

Server script

You need a script that makes the configured MapProxy available for the Python WSGI servers.

You can create a basic script with mapproxy-util:

mapproxy-util create -t wsgi-app -f mapproxy.yaml

The script contains the following lines and makes the configured MapProxy available as application:

from mapproxy.wsgiapp import make_wsgi_app
application = make_wsgi_app('examples/minimal/etc/mapproxy.yaml')

This is sufficient for embedding MapProxy with mod_wsgi or for starting it with Python HTTP servers like gunicorn (see further below). You can extend this script to setup logging or to set environment variables.

You can enable MapProxy to automatically reload the configuration if it changes:

from mapproxy.wsgiapp import make_wsgi_app
application = make_wsgi_app('examples/minimal/etc/mapproxy.yaml', reloader=True)

Apache mod_wsgi

The Apache HTTP server can directly integrate Python application with the mod_wsgi extension. The benefit is that you don’t have to start another server. Read mod_wsgi installation for detailed instructions.

mod_wsgi requires a server script that defines the configured WSGI function as application. See above.

You need to modify your Apache httpd.conf as follows:

# if not loaded elsewhere
LoadModule wsgi_module modules/

WSGIScriptAlias /mapproxy /path/to/mapproxy/

<Directory /path/to/mapproxy/>
  Order deny,allow
  Allow from all

mod_wsgi has a lot of options for more fine tuning. WSGIPythonHome or WSGIPythonPath lets you configure your virtualenv and WSGIDaemonProcess/WSGIProcessGroup allows you to start multiple processes. See the mod_wsgi configuration directives documentation. Using Mapnik also requires the WSGIApplicationGroup option.


On Windows only the WSGIPythonPath option is supported. Linux/Unix supports WSGIPythonPath and WSGIPythonHome. See also the mod_wsgi documentation for virtualenv for detailed information when using multiple virtualenvs.

A more complete configuration might look like:

# if not loaded elsewhere
LoadModule wsgi_module modules/

WSGIScriptAlias /mapproxy /path/to/mapproxy/
WSGIDaemonProcess mapproxy user=mapproxy group=mapproxy processes=8 threads=25
WSGIProcessGroup mapproxy
# WSGIPythonHome should contain the bin and lib dir of your virtualenv
WSGIPythonHome /path/to/mapproxy/venv
WSGIApplicationGroup %{GLOBAL}

<Directory /path/to/mapproxy/>
  Order deny,allow
  # For Apache 2.4:
  Require all granted
  # For Apache 2.2:
  # Allow from all

Behind HTTP server or proxy

There are Python HTTP servers available that can directly run MapProxy. Most of them are robust and efficient, but there are some odd HTTP clients out there that (mis)interpret the HTTP standard in various ways. It is therefor recommended to put a HTTP server or proxy in front that is mature and widely deployed (like Apache, Nginx, etc.).

Python HTTP Server

You need start these servers in the background on start up. It is recommended to create an init script for that or to use tools like upstart or supervisord.


Gunicorn is a Python WSGI HTTP server for UNIX. Gunicorn use multiple processes but the process number is fixed. The default worker is synchronous, meaning that a process is blocked while it requests data from another server for example. You need to choose an asynchronous worker like eventlet.

You need a server script that creates the MapProxy application (see above). The script needs to be in the directory from where you start gunicorn and it needs to end with .py.

To start MapProxy with the Gunicorn web server with four processes, the eventlet worker and our server script (without .py):

cd /path/of/
gunicorn -k eventlet -w 4 -b :8080 config:application

An example upstart script (/etc/init/mapproxy.conf) might look like:

start on runlevel [2345]
stop on runlevel [!2345]


setuid mapproxy
setgid mapproxy

chdir /etc/opt/mapproxy

exec /opt/mapproxy/bin/gunicorn -k eventlet -w 8 -b :8080 application \
    >>/var/log/mapproxy/gunicorn.log 2>&1


Spawning is another Python WSGI HTTP server for UNIX that supports multiple processes and multiple threads.

cd /path/of/
spawning config.application --threads=8 --processes=4 \

HTTP Proxy

You can either use a dedicated HTTP proxy like Varnish or a general HTTP web server with proxy capabilities like Apache with mod_proxy in front of MapProxy.

You need to set some HTTP headers so that MapProxy can generate capability documents with the URL of the proxy, instead of the local URL of the MapProxy application.

  • Host – is the hostname that clients use to acces MapProxy (i.e. the proxy)
  • X-Script-Name – path of MapProxy when the URL is not / (e.g. /mapproxy)
  • X-Forwarded-Host – alternative to HOST
  • X-Forwarded-Proto – should be https when the client connects with HTTPS


Here is an example for the Nginx webserver with the included proxy module. It forwards all requests to to localhost:8181/:

server {
  location /mapproxy {
    proxy_pass http://localhost:8181;
    proxy_set_header Host $http_host;
    proxy_set_header X-Script-Name /mapproxy;


Here is an example for the Apache webserver with the included mod_proxy and mod_headers modules. It forwards all requests to to localhost:8181/

<IfModule mod_proxy.c>
  <IfModule mod_headers.c>
        <Location /mapproxy>
                ProxyPass http://localhost:8181
                ProxyPassReverse  http://localhost:8181
                RequestHeader add X-Script-Name "/mapproxy"

You need to make sure that both modules are loaded. The Host is already set to the right value by default.

Other deployment options

Refer to for a list of some available WSGI servers.



Running MapProxy as a FastCGI server behind HTTP server is no longer advised for new setups since the used Python package (flup) is no longer maintained. Please refer to the MapProxy 1.5.0 deployment documentation for more information on FastCGI.


Because of the way Python handles threads in computing heavy applications (like MapProxy WMS is), you should choose a server that uses multiple processes (pre-forking based) for best performance.

The examples above are all minimal and you should read the documentation of your components to get the best performance with your setup.

Load Balancing and High Availablity

You can easily run multiple MapProxy instances in parallel and use a load balancer to distribute requests across all instances, but there are a few things to consider when the instances share the same tile cache with NFS or other network filesystems.

MapProxy uses file locks to prevent that multiple processes will request the same image twice from a source. This would typically happen when two or more requests for missing tiles are processed in parallel by MapProxy and these tiles belong to the same meta tile. Without locking MapProxy would request the meta tile for each request. With locking, only the first process will get the lock and request the meta tile. The other processes will wait till the the first process releases the lock and will then use the new created tile.

Since file locking doesn’t work well on most network filesystems you are likely to get errors when MapProxy writes these files on network filesystems. You should configure MapProxy to write all lock files on a local filesystem to prevent this. See globals.cache.lock_dir and globals.cache.tile_lock_dir.

With this setup the locking will only be effective when parallel requests for tiles of the same meta tile go to the same MapProxy instance. Since these requests are typically made from the same client you should enable sticky sessions in you load balancer when you offer tiled services (WMTS/TMS/KML).


MapProxy uses the Python logging library for the reporting of runtime information, errors and warnings. You can configure the logging with Python code or with an ini-style configuration. Read the logging documentation for more information.


MapProxy uses multiple loggers for different parts of the system. The loggers build a hierarchy and are named in dotted-notation. mapproxy is the logger for everything, mapproxy.source is the logger for all sources, mapproxy.source.wms is the logger for all WMS sources, etc. If you configure on logger (e.g. mapproxy) then all sub-loggers will also use this configuration.

Here are the most important loggers:

Logs information about the system and the installation (e.g. used projection library).
Logs information about the configuration.
Logs errors and warnings for service XXX.
Logs all requests to sources with URL, size in kB and duration in milliseconds. The duration is the time it took to receive the header of the response. The actual request duration might be longer, especially for larger images or when the network bandwith is limited.

Enabling logging

The test server is already configured to log all messages to the console (stdout). The other deployment options require a logging configuration.

Server Script

You can use the Python logging API or load an .ini configuration if you have a server script for deployment.

The example script created with mapproxy-util create -t wsgi-app already contains code to load an .ini file. You just need to uncomment these lines and create a log.ini file. You can create an example log.ini with:

mapproxy-util create -t log-ini log.ini


New in version 1.2.0.

You can run multiple MapProxy instances (configurations) within one process with the MultiMapProxy application.

MultiMapProxy can dynamically load configurations. You can put all configurations into one directory and MapProxy maps each file to a URL: conf/proj1.yaml is available at http://hostname/proj1/.

Each configuration will be loaded on demand and MapProxy caches each loaded instance. The configuration will be reloaded if the file changes.

MultiMapProxy as the following options:

The directory where MapProxy should look for configurations.
If set to true, MapProxy will list all available configurations at the root URL of your MapProxy. Defaults to false.

Server Script

There is a make_wsgi_app function in the mapproxy.multiapp package that creates configured MultiMapProxy WSGI application. Replace the application definition in your script as follows:

from mapproxy.multiapp import make_wsgi_app
application = make_wsgi_app('/path/to.projects', allow_listing=True)