taskr-cli 0.0.2

A language agnostic make-like tool meant for python projects

Taskr

A simple task runner meant for python projects. I mostly use bash scripts, but those aren't always cross platform. Semi-inspired by (Mage)[https://github.com/magefile/mage], a task runner for go.

This is also an excuse to have a project that involves packaging so I can learn more about it and mess around, and end up writing more boilerplate/tooling than actual code :)

This project uses itself, so it should always work.. in theory.

Developing

This project uses pipenv. Make sure it's installed. Then call

python -m pipenv shell
pipenv install --dev

You should now be in an virtual environment where you can run tests/dev tools

Installing

On PYPI

pip install taskr_cli

You can confirm it works by running

taskr --version

Using

Ensure you have a tasks.py file defined in the root of your repo. To generate a template, run taskr --init. From there you can modify and add tasks.

CLI:

[master●] » taskr -h
usage: taskr [-h] [-v] [-l] [-i]

A small utility to run tasks

optional arguments:
  -h, --help     show this help message and exit
  -v, --version  Prints the version number
  -l, --list     Show tasks
  -i, --init     Generate a task file

When listing tasks, taskr will attempt to grab the docblock and show it, or use a single # comment above the task function

[master●] » taskr -l

Tasks:
 all      : Runs all static analysis tools
 build    : Builds the wheel
 clean    : Remove build artifacts, cache, etc.
 flake    : Check flake8
 format   : Run black
 mypy     : Checks types
 reinstall: Reinstalls taskr
 sort     : Sort imports
 *test    : Run tests

* = default

Default tasks are run when taskr is run without any arguments. You can set this by setting a variable DEFAULT to the name of a task in tasks.py

DEFAULT = "test"

# Run tests
def test
  taskr.run("python -m pytest tests/")

To run a task, just pass the name. Output from a task will be displayed

[master●] » taskr format
All done! ✨ 🍰 ✨
11 files left unchanged.

You can also define "internal" functions that taskr will ignore when listing by pre-pending the name with an underscore.

import taskr

# Tasker will not list this
def _get_system():
  return os.environ.get("build_system")

def build():
  env = _get_system()
  taskr.run_env("python setup.py install", env={"BUILD_SYSTEM": build_ststem})

Task runners

A few utility methods are provided for system running tasks. Taskr expects task functions to return either True (The task was successful) for False it failed. To determine if a task was successful or not, taskr looks at the return code of the called program. 0 is success, anything else fails.

Taskr will auto copy your existing environment variables when running tasks, so running tasks with programs installed in a virual environment (i.e. dev tools though pip) will work

run

run's argument can be either a list, or a string.

import taskr

def flake() -> bool:
    return taskr.run(["python", "-m", "flake8", "taskr/*.py"])

# Runs flake8
def flake() -> bool:
    return taskr.run("python -m flake8 taskr/*.py")

run_env

run_env is the exact same as run, but takes in a dictionary of environment variables to use when running the task.

import taskr

# Runs a production build
def build():
  vars = {
    "PRODUCTION": "true"
  }
  return taskr.run_env("python setup.py install", vars)

run_conditional

run_conditional is a way to run tasks (functions) in order, as long as the previous task returns a non failure return code (False). You can throw normal python functions in here to

import taskr
import some_package as sp

# Run black
def fmt():
    return taskr.run("python -m black .")

# Check flake8
def flake():
    return taskr.run(["python", "-m", "flake8", "taskr/*.py"])

# Run all static tools
def all():
    return taskr.run_conditional(flake, fmt, sp.function)

run_output

run_output' will run a command and return the output

import taskr

# Get the number of env variables
def _get_count():
    ret = taskr.run_output("env | wc -l")
    print(ret.status) # True 
    print(ret.stdout) # "90"
    print(ret.sterr)  # ""

You're also able to pass an environment dict to this function, the same way as run_env