pyapp-flow 0.16

Description:

pyappflow 0.16

pyapp-flow
A simple application level workflow library.
Allows complex processes to be broken into smaller specific steps, greatly
simplifying testing and re-use.




Installation
pip install pyapp-flow

Usage
from pathlib import Path
from typing import Sequence
import pyapp_flow as flow

# Define steps:

@flow.step(name="Load Names", output="names")
def load_names(root_path: Path) -> Sequence[str]:
"""
Read a sequence of names from a file
"""
with (root_path / "names.txt").open() as f_in:
return [name.strip() for name in f_in.readlines()]

@flow.step(name="Say hello")
def say_hi(name: str):
print(f"Hello {name}")

# Define a workflow:

great_everybody = (
flow.Workflow(name="Great everybody in names file")
.nodes(
load_names,
flow.ForEach("name", in_var="names").loop(say_hi)
)
)

# Execute workflow:

context = flow.WorkflowContext(root_path=Path())
great_everybody(context)

All nodes within the workflow follow a simple interface of:
def node_function(context: flow.WorkflowContext):
...

or using typing
NodeFunction = Callable[[flow.WorkflowContext], Any]

The step decorator simplifies definition of a step by handling loading and saving
of state variables from the WorkflowContext.
Reference
Workflow
At the basic level a workflow is an object that holds a series of nodes to be called
in sequence. The workflow object also includes helper methods to generate and append
the nodes defined in the Builtin Nodes section of the documentation.
Just like every node in pyApp-Flow a workflow is called with an WorkflowContext
object, this means workflows can be nested in workflows, or called from a for-each
node.
The one key aspect with a workflow object is related to context variable scope.
When a workflow is triggered the context scope is copied and any changes made
to the variables are discarded when the workflow ends. However, just like Python
scoping only the reference to the variable is copied meaning mutable objects can
be modified (eg list/dicts).
workflow = (
flow.Workflow(name="My Workflow")
.nodes(...)
)

WorkflowContext
The workflow context object holds the state of the workflow including handling
variable scoping and helper methods for logging progress.
Properties


state
Direct access to state variables in the current scope.


depth
Current scope depth


indent
Helper that returns a string indent for use formatting messages


Methods


format
Format a string using values from the context state. Most name
values for nodes/workflows use this method to allow values to be included
from scope eg:
context.format("Current path {working_path}")



push_state/pop_state
Used to step into or out of a lower state scope. Typically these methods are
not called directly but are called via using a with block eg:
with context:
pass # Separate variable scope



Logging wrappers
Wrappers around an internal workflow logger that handle indentation to make
reading the log easier.

log
debug
info
warning
error
exception



Builtin Nodes
Modify context variables


SetVar
Set one or more variables into the context
SetVar(my_var="foo")



Append
Append a value to a list in the context object (will create the list if it
does not exist).
Append("messages", "Operation failed to add {my_var}")



CaptureErrors
Capture and store any errors raised by node(s) within the capture block to a
variable within the context.
CaptureErrors("errors").nodes(my_flaky_step)

This node also has a try_all argument that controls the behaviour when an
error is captured, if True every node is called even if they all raise errors,
this is useful for running a number of separate tests that may fail.
CaptureErrors(
"errors",
try_all=True
).nodes(
my_first_check,
my_second_check,
)



Provide feedback


LogMessage
Insert a message within optional values from the context into the runtime
log with an optional level.
LogMessage("State of my_var is {my_var}", level=logging.INFO)



Branching
Branching nodes utilise a fluent interface for defining the nodes within each
branch.


Conditional / If
Analogous with an if statement, it can accept either a context variable
that can be interpreted as a bool or a function/lamba that accepts a
WorkflowContext object and returns a bool.
# With context variable
(
If("is_successful")
.true(log_message("Process successful :)"))
.false(log_message("Process failed :("))
)

# With Lambda
(
If(lambda context: len(context.state.errors) == 0)
.true(log_message("Process successful :)"))
.false(log_message("Process failed :("))
)



Switch
Analogous with a switch statement found in many languages or with Python
a dict lookup with a default fallback.
Like the conditional node switch can accept a context variable or a
function/lambda that accepts a WorkflowContext, except returns any hashable
object.
# With context variable
(
Switch("my_var")
.case("foo", log_message("Found foo!"))
.case("bar", log_message("Found bar!"))
.default(log_message("Found neither."))
)

# With Lambda
(
Switch(lambda context: context.state["my_var"])
.case("foo", log_message("Found foo!"))
.case("bar", log_message("Found bar!"))
)



Iteration


ForEach
Analogous with a for loop this node will iterate through a sequence and
call each of the child nodes.
All nodes within a for-each loop are in a nested context scope.
# With a single target variable
(
ForEach("message", in_var="messages")
.loop(log_message("- {message}"))
)

# With multiple target variables
(
ForEach("name, age", in_var="students")
.loop(log_message("- {name} is {age} years old."))
)