Usage

To use Ivy workflow engine in a project:

from ivy.workflow_manager import WorkflowManager
args = ["--size-x=100",
        "--size-y=100",
        "ufig.config.random"]

mgr = WorkflowManager(args)
mgr.launch()

alternatively ivy can also be used from the command line:

$ ivy --size-x=100 --size-y=100 ufig.config.random

A configuration can range form very simple to arbitrarily complex.

In the simplest case the configuration file would look something like:

from ivy.config import base_config

plugins = ["test.plugin.simple_plugin",
        "test.plugin.simple_plugin"
        ]

Importing basic functionality from base_config and defining a list of plugins.

A slightly more complex use case would look something like:

from ivy.config import base_config
from ivy.loop import Loop
from ivy.utils.stop_criteria import RangeStopCriteria

context_provider = "ivy.context_provider.PickleContextProvider"
ctx_file_name = "ivy_cxt.dump"

plugins = Loop(["test.plugin.simple_plugin",
                Loop(["test.plugin.simple_plugin",
                      "test.plugin.simple_plugin"],
                      stop=RangeStopCriteria(maxIter=5)),
                "test.plugin.simple_plugin"],
                stop=RangeStopCriteria(maxIter=2))

a=1.5
b=["omega", "lambda", "gamma"]
c=None

Configures the ‘PickleContextProvider’ as context provider which ensures that the context is persisted to the file “ivy_ctx.dump” after every execution of a plugin

The list of plugins consists of two nested loops. Each having two plugins. The inner lopp will be executed 5 times and the outer loop twice.

Furthermore the config defines the attributes ‘a’, ‘b’ and c where ‘a’ is a float and ‘b’ a list of strings and c is a NoneType. The type of c will automatically be inferred from the given value from the command line.

Calling this config and overriding the attributes from the command line would look something like this:

$ ivy --a=1.75 --b=zeta,beta,gamma --c=False package.subpackage.module