A comprehensive collection of Python utilities for developers and audio processing enthusiasts. "Z0Z_" indicates a prototype package where individual components may eventually evolve into focused standalone packages.
Z0Z_tools solves common development challenges with clean, well-documented functions that emphasize self-explanatory code and robust error handling.
Convert string representations like "TRUE" or "false" to proper Python boolean values:
from Z0Z_tools import oopsieKwargsie
def my_function(verbose="true"):
# Converts "true", "True", "TRUE", etc. to Python's True
is_verbose = oopsieKwargsie(verbose)
if is_verbose:
print("Detailed information follows...")Fine-tune CPU usage with intuitive syntax:
from Z0Z_tools import defineConcurrencyLimit
# Use 75% of available CPUs
workers = defineConcurrencyLimit(0.75)
# Use all CPUs except 2
workers = defineConcurrencyLimit(-2)
# Use exactly 8 CPUs
workers = defineConcurrencyLimit(8)Convert and validate inputs to integers with clear error messages:
from Z0Z_tools import intInnit
# Handles mixed input types with precise validation
validated_ids = intInnit(['1', 2, '3.0'], 'user_ids')
# Rejects non-integer values with helpful errors
try:
intInnit([1.5, '2'], 'dimensions')
except ValueError as e:
print(e) # "I received 1.5, but dimensions must be an integer number."Recursively extract and convert values from nested data structures:
from Z0Z_tools import stringItUp
mixed_data = [1, {'user': 'Alice'}, {3.14, 'math'}, b'bytes']
strings = stringItUp(mixed_data) # ['1', 'user', 'Alice', '3.14', 'math', 'bytes']Combine and clean dictionary data with control over duplicates and ordering:
from Z0Z_tools import updateExtendPolishDictionaryLists
dict1 = {'colors': ['red', 'blue'], 'sizes': [1, 2]}
dict2 = {'colors': ['blue', 'green'], 'materials': ['wood']}
# Merge with duplicate removal and sorting
merged = updateExtendPolishDictionaryLists(
dict1, dict2,
destroyDuplicates=True,
reorderLists=True
)
# Result: {'colors': ['blue', 'green', 'red'], 'sizes': [1, 2], 'materials': ['wood']}Generate efficient string representations of large arrays:
from Z0Z_tools import autoDecodingRLE
import numpy as np
array = np.array([1, 2, 3, 3, 3, 4, 5, 6])
encoded = autoDecodingRLE(array) # '[1,2,[3]*3,4,5,6]'
# The string can be evaluated directly to recreate the data
import ast
decoded = ast.literal_eval(encoded) # [1, 2, 3, 3, 3, 4, 5, 6]Read audio files with automatic stereo conversion and sample rate control:
from Z0Z_tools import readAudioFile, writeWAV
# Load audio with sample rate conversion
waveform = readAudioFile('input.wav', sampleRate=44100)
# Save in WAV format (always 32-bit float)
writeWAV('output.wav', waveform)Load and process batches of audio files:
from Z0Z_tools import loadWaveforms
# Load multiple files with consistent formatting
array_waveforms = loadWaveforms(['file1.wav', 'file2.wav', 'file3.wav'])
# The result is a unified array with shape (channels, samples, file_count)Convert between waveforms and spectrograms:
from Z0Z_tools import stft, halfsine
# Create a spectrogram with a half-sine window
spectrogram = stft(waveform, windowingFunction=halfsine(1024))
# Convert back to a waveform
reconstructed = stft(spectrogram, inverse=True, lengthWaveform=original_length)Create functions that operate on spectrograms:
from Z0Z_tools import waveformSpectrogramWaveform
def boost_low_frequencies(spectrogram):
# Boost frequencies below 500 Hz
spectrogram[:, :10, :] *= 2.0
return spectrogram
# Create a processor that handles the STFT/ISTFT automatically
processor = waveformSpectrogramWaveform(boost_low_frequencies)
# Apply the processor to a waveform
processed_waveform = processor(original_waveform)Generate platform-independent relative paths:
from Z0Z_tools import findRelativePath
# Works with files or directories on different branches
rel_path = findRelativePath('/path/to/source', '/path/to/different/target')
# Result: '../../different/target'Install unpackaged Python code with a simple command:
# From your terminal or command prompt
python -m Z0Z_tools.pipAnything /path/to/unpackaged/codeValidate your implementations with ready-to-use test suites:
from Z0Z_tools import PytestFor_intInnit
import pytest
# Test your custom integer validation function
@pytest.mark.parametrize("test_name,test_func",
PytestFor_intInnit(your_integer_validator))
def test_validator(test_name, test_func):
test_func() # Runs a comprehensive test suitepip install Z0Z_tools
Coding One Step at a Time:
- WRITE CODE.
- Don't write stupid code that's hard to revise.
- Write good code.
- When revising, write better code.
