Each deployment of an application written using Pyramid implies a specific configuration of the framework itself. For example, an application which serves up MP3 files for your listening enjoyment might plug code into the framework that manages song files, while an application that manages corporate data might plug in code that manages accounting information. The way in which code is plugged in to Pyramid for a specific application is referred to as “configuration”.
Most people understand “configuration” as coarse settings that inform the high-level operation of a specific application deployment. For instance, it’s easy to think of the values implied by a .ini file parsed at application startup time as “configuration”. Pyramid extends this pattern to application development, using the term “configuration” to express standardized ways that code gets plugged into a deployment of the framework itself. When you plug code into the Pyramid framework, you are “configuring” Pyramid to create a particular application.
Here’s one of the simplest Pyramid applications, configured imperatively:
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from paste.httpserver import serve from pyramid.config import Configurator from pyramid.response import Response def hello_world(request): return Response('Hello world!') if __name__ == '__main__': config = Configurator() config.add_view(hello_world) app = config.make_wsgi_app() serve(app, host='0.0.0.0')
We won’t talk much about what this application does yet. Just note that the “configuration’ statements take place underneath the if __name__ == '__main__': stanza in the form of method calls on a Configurator object (e.g. config.add_view(...)). These statements take place one after the other, and are executed in order, so the full power of Python, including conditionals, can be employed in this mode of configuration.
A different mode of configuration gives more locality of reference to a configuration declaration. It’s sometimes painful to have all configuration done in imperative code, because often the code for a single application may live in many files. If the configuration is centralized in one place, you’ll need to have at least two files open at once to see the “big picture”: the file that represents the configuration, and the file that contains the implementation objects referenced by the configuration. To avoid this, Pyramid allows you to insert configuration decoration statements very close to code that is referred to by the declaration itself. For example:
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from pyramid.response import Response from pyramid.view import view_config @view_config(name='hello', request_method='GET') def hello(request): return Response('Hello')
The mere existence of configuration decoration doesn’t cause any configuration registration to be performed. Before it has any effect on the configuration of a Pyramid application, a configuration decoration within application code must be found through a process known as a scan.
A scan of a module or a package and its subpackages for decorations happens when the pyramid.config.Configurator.scan() method is invoked: scanning implies searching for configuration declarations in a package and its subpackages. For example:
Starting A Scan
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from paste.httpserver import serve from pyramid.response import Response from pyramid.view import view_config @view_config() def hello(request): return Response('Hello') if __name__ == '__main__': from pyramid.config import Configurator config = Configurator() config.scan() app = config.make_wsgi_app() serve(app, host='0.0.0.0')
The scanning machinery imports each module and subpackage in a package or module recursively, looking for special attributes attached to objects defined within a module. These special attributes are typically attached to code via the use of a decorator. For example, the view_config decorator can be attached to a function or instance method.
Once scanning is invoked, and configuration decoration is found by the scanner, a set of calls are made to a Configurator on your behalf: these calls replace the need to add imperative configuration statements that don’t live near the code being configured.
A third mode of configuration can be employed when you create a Pyramid application named declarative configuration. This mode uses an XML language known as ZCML to represent configuration statements rather than Python. ZCML is not built-in to Pyramid, but almost everything that can be configured imperatively can also be configured via ZCML if you install the pyramid_zcml package.