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Introduction

ggpyjobs is the replay-processing engine for the GGTracker site.

Requests for replay processing are queued in Redis by the 'esdb' codebase; ggpyjobs retrieves these from queue, and performs the requested parsing work.

This codebase is useful to read if you're wondering how GGTracker extracts information from replay files. See the 'Plugins' section below.

If you want GGTracker to show a new piece of information, the steps to do that include:

  • add the necessary processing code here, in ggpyjobs
  • modify the other parts of GGTracker to work correctly with the new piece of information

The other codebases used in GGTracker are:

Plugins

ggpyjobs uses the sc2reader library to parse replays.

In sc2parse/plugins.py there are various 'plugins' to sc2reader that compute additional things from each replay file.

The plugins are:

  • EngagementTracker -- identifies major combat engagements and measures total value of things lost by each player
  • ZergMacroTracker -- measures inject efficiency, and active inject time per base; distinguishes 'macro hatches'
  • ProtossTerranMacroTracker -- tracks energy for each nexus and orbital, measures time spent at max energy
  • MiningBaseIdentifier -- identifies which bases are in mining locations (as opposed to, for example, macro hatches)
  • ScoutingTracker -- detects when the first scout command was issued to a worker
  • UpgradesTracker -- retrieves the list of upgrades and timings per player
  • ArmyTracker -- retrieves total and per-minute unit counts
  • WWPMTracker -- measures 'worker waves per minute', no longer displayed on GGTracker
  • BaseTracker -- no longer used since 2.0.8
  • TrainingTracker -- no longer used since 2.0.8
  • ActivityTracker -- no longer used since 2.0.8
  • OwnershipTracker -- no longer used since 2.0.8
  • LifeSpanTracker -- no longer used since 2.0.8

Requirements

  • MySQL
  • Python 2.X
  • Redis (when running as part of GGTracker)

Installation

I'm probably missing some steps here; if you run into problems, please let me know so I can improve this README.

  • create MySQL databases called esdb_development and esdb_test
  • sign up for an Amazon AWS account
  • mkdir config
  • cp config_example/s3.yml config
  • customize config/s3.yml, putting your AWS details in
  • cp config_example/database.yml config
  • mkdir testcache

Install the various requirements. PIL may require external libraries to be installed.

  • pip install -r requirements.txt

Run the tests to verify a successful setup:

GGFACTORY_CACHE_DIR=testcache GGPYJOBS_CONFIG_PATH=config PYTHONPATH=src/sc2reader DJANGO_SECRETKEY=foo ./manage.py test sc2parse

There will be some output; at the end, if all is well, it will say something like:

Ran 26 tests in 41.357s

OK

Run specific tests like this:

GGFACTORY_CACHE_DIR=testcache GGPYJOBS_CONFIG_PATH=config PYTHONPATH=src/sc2reader DJANGO_SECRETKEY=foo ./manage.py test sc2parse.SC2ReaderToEsdbTestCase.test_close_replays

Parsing a replay with the extra ggpyjobs plugins

GGFACTORY_CACHE_DIR=testcache python
from sc2parse import ggfactory
replay = ggfactory.load_replay('/path/to/a/replay.SC2Replay')
print replay.players[0].upgrades
print replay.eblob

Environment Variables

As you may have noticed in the test-running commands above, ggpyjobs uses the following environment variables:

  • GGFACTORY_CACHE_DIR (required): Sets a directory to cache remote files used to load SC2 resources. Use full path.
  • DJANGO_SECRETKEY (required): Sets the SECRETKEY in the django settings.py file.
  • GGPYJOBS_CONFIG_PATH (required in testing): The directory where the config files s3.yml and database.yml are found for test runs.

Keeping up to Date

If there are changes to the requirements.txt file, run this:

$ pip install --upgrade -r requirements.txt

Working on sc2reader

If you want ggpyjobs to use a customized version of sc2reader:

$ pip uninstall sc2reader $ cd path/to/ggtracker/sc2reader $ python setup.py develop

When installed in this 'develop mode', sc2reader will automatically reflect changes to the code base it was installed from. Please note that a worker running as a daemon will not automatically reflect changes to the code made since the process began running. The worker must be shut down and restarted to pick up the code changes.

I don't understand XXXX

Just ask, I'll add questions and answers to a FAQ here.