groupie 0.2.1

Exception group utilities for exceptional code

groupie is a module for useful ExceptionGroups

Exceptions in Python can be a very neat way of controling program flow. ExceptionGroups (with an assist from groupie) simplify more complex control flow.

It's features include:

• Collect exceptions using a context, like contextlib.suppress - but collect them up
• accumulate exceptions into one big ExceptionGroup to be raised at once
• downgrade exceptions to warnings presented via logging
• Static analysis (eg. ruff) compatability notices when you're supressing errors

Think of using this when:

• Parsing configuration files / objects
• Parsing code
• Building a bunch of targets

Useful Patterns

Surface as many user-facing issues as possible at once

It's super annoying as a user to get drip-fed one issue at a time, especially when there's some intensive process leading up to the failure (imagine if pytest stopped at the first failed test each time it was run).

Raise these exceptions for any branch of logic that will individually stop execution, but accumulating these before raising them means that all possible branches are explored as deeply as possible before surfacing the issue.

eg.

time_consuming_setup()

with accumulate(ValueError) as accumulator:
    with accumulator.collector:
        do_one()  # <-- say this fails, we'd usually never know if two and three were going to work!
    with accumulator.collector:
        do_two()
    with accumulator.collector:
        do_three()  # <-- this fails as well!

This will yield an ExceptionGroup showing both do_one and do_three failed at the same time!

Accumulating exceptions in a loop

Because it's so common, there are special methods to condense the boilerplate of accumulating exceptions in a loop.

for collector, item in accumulate(range(10), ValueError):
    with collector:
        do_something(item)

Then the exception group will contain all the exceptions raised in the loop.

downgradeing Exceptions

Say you've deprecated something, but you want to surface it as a warning, later to be promoted to an error:

def do_something():
    with downgrade(DeprecationException):
        raise DeprecationException("This is deprecated - to the other thing.")

    # but, for now, do it anyway...

Attempting to do something a few ways, failing only if none succeed

A common pattern for a user-facing application is to attempt to do something - perhaps load a configuration file - a few different ways, and only fail if none succeed.

Say you allow the configuration file for a tool to exist in a few places.

def load_config():
    possible_locations = [
        "~/.config/my-tool/config.json",
        "./config.json",
        "/etc/my-tool/config.json",
    ]
    collector = Collector(FileNotFoundError)
    for location in possible_locations:
        with collector:
            return load_config_from_file(location)

    # If we haven't already returned, raise an exception describing
    # all the failures we encountered while trying.
    collector.raise_all()

NOTE: the difference accumulate and Collector:

• accumulate is a context manager that accumulates the exceptions into a single one, and then raises it when exiting the context. It's useful to ensure you definately raise the exception and makes it really hard to miss a check on whether there were any.
• The Collector is a context manager that collects the exceptions, but it's up to you to handle them (possibly raise them) when you're done with it.

Custom UserException tree

One very useful pattern is to create a tree of Exception types under the standard included types and use them to represent user-facing issues.

class UserException(Exception):
    """Represents a user-facing exception"""

class UserResourceException(UserException):
    """You have a file missing!"""

# etc...

This is particulaly useful because you can pass the UserException type to all the accumulate calls around your code.

You can also add pretty printing to these exceptions (check out rich!) with something like:

class UserException(Exception):
    """Represents a user-facing exception"""

    def __str__(self):
        return f"{self.__class__.__name__}: {self.__doc__}"

Attribution

These utils and patternsstarted life as part of atopile, a compiler to design PCBAs with code