hackytools 0.1.1

Tools that are hacky. Obviously.

hackytools

Hacky Tools, by Hackysack (I'll never get tired of that joke.)

Installation

You can install this package via the command:

pip install hackytools

To get the development version instead (where there may be unstable features) use one of the following:

pip install https://github.com/H4CKY54CK/hackytools/archive/main.zip
pip install https://github.com/H4CKY54CK/hackytools/archive/main.tar.gz

What do I get?

So far, not much. But I promise that I'm working hard at gathering a bunch of my homemade tools.

For right now, you get a couple of different hacky decorators, a spritesheet/stylesheet generator (mainly for subreddit CSS), and a command line tool (currently, only a single command).

Decorators

@timeit

A decorator to time how long a function takes, illustrated below.

from hackytools import timeit
import time

# We need the `time` module to delay our test functions just a little bit.

# Time how long a function takes.
@timeit
def main1():
    time.sleep(2)

# Same thing, but in case you're used to using parentheses
@timeit()
def main2():
    time.sleep(.5)

# Get an average elapsed time by running your function 5 times.
@timeit(repeat=5)
def main3():
    pass

if __name__ == '__main__':
    main1()
    main2()
    main3()


# main1 elapsed: 2.00 s
# main2 elapsed: 500.38 ms
# main3 average elapsed: 616.67 ns | best (of 5): 300.00 ns | worst (of 5): 1.90 µs

The timing decorator also automatically converts the time returned into a sensible unit, for optimal viewing pleasure.

Just be careful that you don't repeat 50 times, and your code takes 50 seconds each run. That would take forever. Be smart.

@timeable

This does nearly the same thing as @timeit. However, @timeable by default, does not time your function. In fact, it doesn't interfere with it at all, unless explicitly told to do so. What do I mean? I'll explain.

from hackytools import timeable

@timeable
def some_function():
    # do some stuff
    return # or whatever

some_function()

# Even though it is decorated, this function will act normally. However...
# If we were to pass in a specific (unlikely to already be in use) kwargs
# dict such as the following (and unpack it with **):

some_function(**{'_frequency': 1})

# some_function elapsed: 1.20 µs

# This WILL time the function, with a frequency of 1 time(s).

# "But that function doesn't take any arguments!", I hear you say.

# And you'd be right. Through the magic of decorators (and some pretty basic python)
# we can actually reach into the kwargs, get the value for this specific kwarg,
# and then remove the kwargs from the kwargs dict. ezpz

@logme

This is just a regular logging decorator. You decorate your function with @logme, and it logs some basic information about what just happened, to the file {your_filename}.log. So, if your filename was myproject.py, the logfile would literally be myproject.py.log. This is for several reasons, the most important being to not overwrite existing files. I should probably just add a file check.

# myproject.py

from hackytools import logme

@logme
def add(x, y):
    return x + y

add(5, 6)

# What was logged and where:
# (DEBUG) 10/09/20 01:54:33 PM: func: add | args: (5, 6) | kwargs: {} | returned: 11
# to file `myproject.py.log`

whatsmyip

Use this at the command line to get your public IP address. This is just a convenience command due to me getting tired of having to specifically search "whats my ip ipv4" on Google. If I'm going to do some of the legwork, I may as well make it easy on myself.

More

I have more planned. I have a changelog planned, so I don't clutter the README. I have docs planned, to also avoid cluttering the README. Some of these may already be in effect. I don't know, I'm not God. Jeez. (The changelog is in effect, though.)