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riggerlib 1.1.4

An event hook framework

Latest Version: 3.1.2


Rigger is an event handling framwork. It allows for an arbitrary number of plugins to be setup to respond to events, with a namspacing system to allow data to be passed to and from these plugins. It is extensible and customizable enough that it can be used for a variety of purposes.


The main guts of Rigger is around the plugins. Before Rigger can do anything it must have a configured plugin. This plugin is then configured to bind certain functions inside itself to certain events. When Rigger is triggered to handle a certain event, it will tell the plugin that that particular event has happened and the plugin will respond accordingly.

In addition to the plugins, Rigger can also run certain callback functions before and after the hook function itself. These are call pre and post hook callbacks. Rigger allows multiple pre and post hook callbacks to be defined per event, but does not guarantee the order that they are executed in.

Let’s take the example of using the unit testing suite py.test as an example for Rigger. Suppose we have a number of tests that run as part of a test suite and we wish to store a text file that holds the time the test was run and its result. This information is required to reside in a folder that is relevant to the test itself. This type of job is what Rigger was designed for.

To begin with, we need to create a plugin for Rigger. Consider the following piece of code:

from riggerlib import RiggerBasePlugin
import time

class Test(RiggerBasePlugin):

    def plugin_initialize(self):
        self.register_plugin_hook('start_test', self.start_test)
        self.register_plugin_hook('finish_test', self.finish_test)

    def start_test(self, test_name, test_location, artifact_path):
        filename = artifact_path + "-" + self.ident + ".log"
        with open(filename, "w") as f:
            f.write(test_name + "\n")
            f.write(str(time.time()) + "\n")

    def finish_test(self, test_name, artifact_path, test_result):
        filename = artifact_path + "-" + self.ident + ".log"
        with open(filename, "w+") as f:

This is a typical plugin in Rigger, it consists of 2 things. The first item is the special function called plugin_initialize(). This is important and is equivilent to the __init__() that would usually be found in a class definition. Rigger calls plugin_initialize() for each plugin as it loads it. Inside this section we register the hook functions to their associated events. Each event can only have a single function associated with it. Event names are able to be freely assigned so you can customize plugins to work to specific events for your use case. The register_plugin_hook() takes an event name as a string and a function to callback when that event is experienced.

Next we have the hook functions themselves, start_test() and finish_test(). These have arguments in their prototypes and these arguments are supplied by Rigger and are created either as arguments to the fire_hook() function, which is responsible for actually telling Rigger that an even has occured, or they are created in the pre hook script.

Local and Global Namespaces

To allow data to be passed to and from hooks, Rigger has the idea of global and event local namespaces. The global values persist in the Rigger instance for its lifetime, but the event local values are destroyed at the end of each event.

Rigger uses the global and local values referenced earlier to store these argument values. When a pre, post or hook callback finishes, it has the opportunity to supply updates to both the global and local values dictionaries. In doing this, a pre-hook script can prepare data, which will could be stored in the locals dictionary and then passed to the actual plugin hook as a keyword argument. When a hook function is called, the local values override global values to provide a single set of keyword arguments that are passed to the hook or callback.

In the example above would probably fire the hook with something like this:

rigger.fire_hook('start_test', test_name="my_test", test_location="var/test/")

Notice that we don’t specify what the artifact_path value is. In the concept of testing, we may want to store multiple artifacts and so we would not want each plugin to have to compute the artifact path for itself. Rather, we would create this path during a pre-hook callback and update the local namespace with the key. So the process of events would follow like so.

  1. Local namespace has {test_name: “my_test”, test_location: “var/test”}
  2. Prehook callback fires with the arguments [test_name, test_location]
  3. Prehook exits and updates the local namespace with artifact_path
  4. Local namespace has {test_name: “my_test”, test_location: “var/test”, artifact_path: “var/test/my_test”}
  5. Hook ‘start_test’ is called for the ‘test’ plugin with the arguments [test_name, test_location, artifact_path]
  6. Hook exits with no updates
  7. Posthook callback fires with the arguments [test_name, test_location, artifact_path]
  8. Posthook exits

See how the prehook sets up a key value which is the made available to all the other plugin hooks.

TCP Server

Rigger comes with a TCP server which can be started up to allow either non-Python or remote machines to still communicate with the Rigger process. Rigger has a client that can be imported to use within Python projects, called RiggerClient. An instance of the RiggerClient is initialised with a server address and port like so:

from riggerlib import RiggerClient

rig_client = RiggerClient('', 21212)

Events can then be fired off in exactly the same way as before with the fire_hook method, which emulates the same API as the in-object Rigger instance. Internally the data is converted to JSON before being piped across the TCP connection. In this way data sent over the TCP link must be JSON serializable. The format is as follows:

{'hook_name': 'start_session',
    {'arg1': 'value1',
     'arg2': 'value2'

Queues and Backgrounding Instances

Rigger has two queues that it uses to stack up hooks. In the first instance, all hooks are delivered into the _global_queue. This queue is continually polled in a separate thread and once an item is discovered, it is processed. During processing, after the pre-hook callback, if it is discovered that the plugin instance has the background flag set, then the hook is passed into the _background_queue to be processed as and when in a separate thread. In this way tasks like archiving can be dealt with in the background without affecting the main thread.


There are three main threads running in Rigger. The main thread, which will be part of the main loop of the importing script, the background thread, and the global queue thread. During hook processing an option is available to thread and parallelise the instance hooks. Since Rigger doesn’t guarantee the order of plugin instances processing anyway, this is not an issue. If order is a concern, then please use a second event signal.


Rigger takes few options to start, it, an example is shown below:

squash_exceptions: True
threaded: True
server_port: 21212
server_enabled: True
        enabled: True
        plugin: test
  • squash_exceptions option tells Rigger whether to ignore exceptions that happen inside the fire_hook() call and just log them, or if it should raise them.
  • threaded option tells Rigger to run the fire_hook plugins as threads or sequentially.
  • server_address option tells Rigger which ip to bind the TCP server to.
  • server_port option tells Rigger which port to bind the TCP server to.
  • server_enabled option tells Rigger if it should run up the TCP server.
File Type Py Version Uploaded on Size
riggerlib-1.1.4.tar.gz (md5) Source 2014-07-15 10KB