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Examples

You can find these examples in the examples directory (surprise!) of the Sacred sources or in the Github Repository. Look at them for the sourcecode, it is an important part of the examples. It can also be very helpful to run them yourself and play with the command-line interface.

The following is just their documentation from their docstring which you can also get by running them with the -h, --help or help flags.

Hello World

examples/01_hello_world.py

examples.01_hello_world

Hello Config Dict

examples/02_hello_config_dict.py

examples.02_hello_config_dict

Hello Config Scope

examples/03_hello_config_scope.py

examples.03_hello_config_scope

Captured Functions

examples/04_captured_functions.py

examples.04_captured_functions

My Commands

examples/05_my_commands.py

examples.05_my_commands

Randomness

examples/06_randomness.py

examples.06_randomness

Less magic

If you are new to Sacred, you might be surprised by the amount of new idioms it introduces compared to standard Python. But don't worry, you don't have to use any of the magic if you don't want to and still benefit from the excellent tracking capabilities.

examples/07_magic.py shows a standard machine learning task, that uses a lot of possible Sacred idioms:

  • configuration definition through local variables
  • parameter injection through captured functions
  • command line interface integration through the ex.automain decorator

examples/08_less_magic.py shows the same task without any of those idioms. The recipe for replacing Sacred magic with standard Python is simple.

  • define your configuration in a dictionary, alternatively you can use an external JSON or YAML file
  • avoid the ex.capture decorator. Instead only pass _config to the main function and access all parameters explicitly through the configuration dictionary
  • just use ex.main instead of ex.automain and call ex.run() explicitly. This avoids the parsing of command line parameters you did not define yourself.

While we believe that using sacred idioms makes things easier by hard-wiring parameters and giving you a flexible command line interface, we do not enforce its usage if you feel more comfortable with classical Python. At its core Sacred is about tracking computatonal experiments, not about any particular coding style.

Docker Setup

examples/docker

To use Sacred to its full potential you probably want to use it together with MongoDB and dashboards like Omniboard that have been developed for it. To ease getting started with these services you find an exemplary docker-compose configuration in examples/docker. After installing Docker Engine and Docker Compose (only necessary for Linux) go to the directory and run:

docker-compose up

This will pull the necessary containers from the internet and build them. This may take several minutes. Afterwards mongoDB should be up and running. mongo-express, an admin interface for MongoDB, should now be available on port 8081, accessible by the user and password set in the .env file (ME_CONFIG_BASICAUTH_USERNAME and ME_CONFIG_BASICAUTH_PASSWORD). Sacredboardshould be available on port 5000. Omniboard should be available on port 9000. They will both listen to the the database name set in the .env file (MONGO_DATABASE) which will allow the boards to listen to the appropriated mongo database name set when creating the MongoObserver with the db_name arg. All services will by default only be exposed to localhost. If you want to expose them on all interfaces, e.g. for the use on a server, you need to change the port mappings in docker-compose.yml from 127.0.0.1:XXXX:XXXX to XXXX:XXXX. However, in this case you should change the authentication information in .env to something more secure.