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Yape - Yet another pipeline executor

Yape is a general-purpose pipeline/workflow executor written in Python. It provides ways to construct and run an execution graph.

Yape's features:

  • Ergonomics of Python: The execution graph is created via Python code, providing great flexibility on how you create and configure your execution nodes. The API tries its best to provide an syntax-sugary way of creating and using nodes.
  • Graph Execution: Graph execution can be done via CLI or a Python API. You can execute the whole graph or selected a set of target nodes for execution.
  • Node dependencies: A node can use as dependencies a mixture of regular python values, other nodes and file system paths. When nodes are used as dependencies, Yape will know how to execute them in the correct order and to provide the results to the dependent nodes.
  • Caching: By default, if Yape sees that an execution node did not change from its last run, it does not re-execute it and just return the cached result. This behavior can be turned off if necessary.
  • Minimal execution sub-graph: Yape is capable of generating and exporting a minimal sub-graph with only the nodes/data necessary to fulfill a selected set of target nodes. This is specially useful for machine learning pipelines into production, where one is only interested in the execution path for the "test phase".

Install

Yape can be installed via pip:

pip install yape

Quickstart

Creating the execution graph

By default, the yape command looks for and load the file yp.py, which is the entry point for creating the execution graph. In general, that file would be at the root directory of your project. In the Python code examples provided here, unless explicitly noted, the content is expected to be in the yp.py file.

The most common way of creating a node is by wrapping a function responsible for the execution of such a node. There are multiple ways you can create functional nodes:

  1. Using the yp.node decorator:

    import yape as yp

@yp.node
def hello(who="world"):
    print(f"Hello, {who}!")

    When using @yp.node, hello is transformed into a yape.Node object, which will execute the original function.

  2. Using the yp.fn decorator:

    import yape as yp

@yp.fn
def hello(who):
    print(f"Hello, {who}!")

def nodegen():
    hello("world")

    In this example, hello is transformed into a special kind of function called a node generator and we use it inside nodegen().

    When a node generator is called, it creates a new node object that will call the wrapped function with the same arguments passed to the generator.

    The function nodegen() is a special function that Yape looks for when loading the yp.py file and is understood as the function responsible for creating the node objects for yp.py [1].

  3. Using yp.fn decorator directly for node creation:

    import yape as yp

def hello(who):
    print(f"Hello, {who}!")

def nodegen():
    yp.fn(hello)("world")

    This has the same effect achieved with example (2), but with the difference that hello is left untouched, which could be useful if you want to keep your functions unmodified for other uses. This is also useful when using functions provided by other libraries.

[1]Note that in example (1) we did not create a nodegen() function as the node is already created by @yp.node, but you could have a nodegen() there as well (in case you use a mixture of node creation styles).

Running

You can use the command yape to run your execution graph. Using the example from the above:

$ yape
Hello, world!

Ignoring the cache

If you try running it again, you will see that there will be no output:

$ yape

That's because the node hasn't changed, so Yape knows it does not have to execute it. If we change the node definition or arguments, then Yape will detect the change. For example, let's change the argument for our node:

import yape as yp

def hello(who):
    print(f"Hello, {who}!")

def nodegen():
    yp.fn(hello)("my friend")

And then run yape:

$ yape
Hello, my friend!

The command yape without positional arguments is actually a shortcut for yape run, which is the sub-command responsible for running the execution graph. If you want to force the execution of nodes and ignore the cache, you can use the -f option (short for --force):

$ yape run -f
Hello, my friend!

Selecting target nodes

The yape run sub-command also allows us to select which nodes we want to execute. Let's increment our example by defining extra nodes:

import yape as yp

def hello(who):
    print(f"Hello, {who}!")

def hi(who):
    print(f"Hi, {who}!")

def nodegen():
    yp.fn(hello)("my friend")
    yp.fn(hello, name="hello_world")("world")
    yp.fn(hi)("John Doe")

We created two extra nodes. By default, a functional node will be named after the name of the wrapped function. Since the first node already will be named "hello", we explicitly define a different name ("hello_world") for the second one.

We can select nodes to be run by passing their names (or paths when they belong to sub-graphs) as positional arguments:

$ yape run hello_world
Hello, world!

$ yape run -f hello hi # Using -f because hello is cached
Hi, John Doe!
Hello, my friend!