kalib 0.17.20

A comprehensive set of advanced utilities for Python programming, e.g. HTTP communication, string handling, logging enhancements, introspection, dynamic importing, property caching descriptors, data class extensions, serialization, etc.

Advanced Python Utilities Module

This module provides a comprehensive set of utilities for advanced Python programming, including HTTP communication, string handling, logging enhancements, introspection, dynamic importing, property descriptors, data class extensions, and serialization. It is designed to facilitate complex application development by offering robust tools that extend Python's standard capabilities.

Table of Contents

• HTTP Communication Utilities
• String Handling Enhancements
• Advanced Logging System
• Introspection and Reflection Utilities
• Dynamic Importing Tools
• Advanced Property Descriptors
• Data Class Extensions and Configuration Handling
• Serialization and Deserialization Utilities

HTTP Communication Utilities

Overview

This component provides a robust toolkit for handling HTTP communication. It includes advanced features for error handling, response parsing, cookie management, and URL processing. The utilities streamline building HTTP clients and services by abstracting common patterns and offering flexible, extensible components.

Key Features

• HTTPException Hierarchy: A comprehensive set of exception classes for handling HTTP errors, based on status codes and error types.
• Response Handling: Utilities for parsing and processing HTTP responses, including automatic JSON decoding and error checking.
• Cookie Management: Tools for managing HTTP cookies, including parsing and formatting.
• URL Processing: Classes and functions for manipulating URLs, including query parameters and path components.
• Serialization Decorators: Decorators to facilitate serialization and deserialization of complex objects within the HTTP context.
• Namespace Augmentation: Enhancements to the HTTP namespace for convenient access to common utilities like HTTP.URL, HTTP.Agent, and HTTP.Exception.

String Handling Enhancements

Overview

Provides advanced string handling utilities focused on character encoding detection, conversion, and manipulation. It defines the Str class, acting as a wrapper around string or bytes objects, offering methods to handle various encoding scenarios and to facilitate text processing.

Key Features

• Encoding and Decoding: Convert between bytes and string representations, handling different character encodings.
• Charset Detection: Automatically detects the character encoding of input data using custom logic and libraries.
• Lazy Proxying: Proxies common string methods to the underlying string representation, allowing Str instances to behave like regular strings.
• Tokenization: Methods to split strings into tokens based on regular expression patterns.

Advanced Logging System

Overview

Enhances the standard Python logging system by introducing custom log levels, additional logging utilities, and a more flexible logger configuration. It provides advanced logging capabilities suitable for complex applications that require detailed logging and traceability.

Key Features

• Custom Log Levels: Defines additional log levels like NOTICE, DEPRECATE, and VERBOSE for finer-grained logging.
• Logger Configuration: Supports configuration from files (e.g., logging.toml), environment variables, or default settings.
• Logger Extensions: Provides a Logger class with enhanced methods for logging, including context-aware logging and deduplication of messages.
• Integration with Modules: Automatically injects the custom logger into modules, ensuring consistent logging behavior across the application.

Introspection and Reflection Utilities

Overview

Offers a collection of utility functions and classes for introspection, type checking, and reflection. It includes functions to analyze objects, their types, inheritance hierarchies, and modules.

Key Features

• Type Checking Functions: Utilities like is_callable, is_collection, and is_iterable for checking object types.
• Inheritance Utilities: Functions to iterate over an object's MRO, get attributes from superclasses, and analyze class hierarchies.
• Module and Object Inspection: Tools to get the module of an object, its fully qualified name, source file, and other metadata.
• Stack Inspection: Functions to analyze the call stack, filter stack traces, and determine stack frame offsets.

Dynamic Importing Tools

Overview

Provides utilities for dynamic importing of modules and objects, with support for caching, handling optional dependencies, and enhanced error reporting.

Key Features

• Dynamic Importing: Functions like import_object to import modules or objects by name at runtime.
• Caching Imports: cached_import function to memoize imports and improve performance.
• Optional Dependencies: optional function to handle optional imports gracefully, returning None or a default value if the module is not available.
• Error Handling: Detailed logging and error messages to aid in debugging import issues, including suggestions for missing packages.

Advanced Property Descriptors

Overview

Provides advanced property descriptors for Python classes, allowing the creation of instance, class, and mixed properties with optional caching capabilities. It includes decorators and base classes to facilitate the definition of properties that can behave differently depending on access context.

Key Features

• Custom Property Decorators: Decorators like @prop and @pin to define properties with custom behaviors.
• Caching Support: Ability to cache property results, optimizing performance for expensive computations.
• Context-Aware Properties: Properties that can differentiate between being accessed from an instance or a class.
• Async Support: Supports both synchronous and asynchronous property methods.

Data Class Extensions and Configuration Handling

Overview

Extends the standard dataclasses module with additional features such as validation, serialization, dynamic class creation, and integration with custom logging mechanisms.

Key Features

• Custom Data Classes: Enhanced dataclass decorator that supports extra parameters, memoization, and custom initialization.
• Validation: Automatic validation of field types and default values against the defined schema.
• Serialization Methods: Methods like as_dict, as_json, and as_sql for converting instances to different formats.
• Dynamic Class Creation: Utilities like autoclass and simple to generate classes dynamically based on configuration schemas.
• Operator Overloading: Overloaded operators (&, |, ^, -, +) for combining and comparing data class instances.

Serialization and Deserialization Utilities

Overview

Provides advanced serialization and deserialization utilities, supporting multiple serialization backends, compression algorithms, and encoding schemes. It allows custom serialization of complex objects, automatic detection of serialization formats, and flexible data encoding and decoding options.

Key Features

• Multiple Backends: Supports serialization backends like orjson and standard json, with automatic selection.
• Custom Serialization: Ability to register custom serialization functions for specific classes.
• Compression Support: Utilizes compression libraries like zstd or gzip to compress serialized data.
• Flexible Encoding: Supports multiple encoding schemes such as Base16, Base32, Base64, Base85, and Base2048.
• Automatic Backend Detection: Deserialization functions automatically detect the serialization backend used.
• Error Handling: Robust exception handling and context-aware suppression of errors.

Tasks

publish

Run: once Requires: environment

Input: mode Environment: mode=patch

Bumps project new version, build and publish the package to repository.

xc bump-version "$mode"

.venv/bin/poetry build
.venv/bin/poetry publish

bump-version

Run: once Requires: environment

Inputs: mode Environment: mode=patch

Prepare and commit a version update in a Git repository. Checks for uncommitted changes, ensures the current branch is master, verifies if there are any changes since the last tag, and bumps the version number.

After validating the readiness for an update, it prompts to proceed. Once confirmed, the script updates the pyproject.toml and .pre-commit-config.yaml files if necessary, commits the changes, tags the new version, and pushes the updates to the remote repository.

#!/bin/zsh

uncommited="$(git diff --cached --name-only | sort -u | tr '\n' ' ' | xargs)"
if [ -n "$uncommited" ]; then
    echo "uncommited changes found"
    exit 1
fi

#

branch="$(git rev-parse --quiet --abbrev-ref HEAD 2>/dev/null)"
if [ -z "$branch" ]; then
    exit 1
elif [ "$branch" == "master" ]; then
    echo "using main master mode"
else
    exit 1
fi

#

changes="$(git ls-files --deleted --modified --exclude-standard)"
changes="$(printf "$changes" | sort -u | tr '\n' ' ' | xargs)"

if [ "$changes" == "README.md" ]; then
    echo "pipeline development mode"
elif [ -n "$changes" ]; then
    echo "uncommited changes found"
    exit 1
fi

git fetch --tags --force
current="$(git describe --tags --abbrev=0)"
[ -z "$current" ] && exit 1

amount="$(git rev-list --count $current..HEAD)"
uncommited="$(git diff --cached --name-only | sort -u | tr '\n' ' ' | xargs)"

if [ "$amount" -eq 0 ] && [ -z "$uncommited" ]; then
    echo "no changes since $current"
    exit 1
fi

version="$(bump "$mode" "$current")"
[ -z "$version" ] && exit 1

revision="$(git rev-parse "$version" 2>/dev/null)" || retval="$?"

if [ "$retval" -eq 128 ]; then
    echo "future tag $revision not found, continue"

elif [ -z "$retval" ] && [ -n "$revision" ]; then

    echo "future tag $version already set to commit $revision, sync with remote branch!"
    exit 1

else
    echo "something went wrong, version: '$version' revision: '$revision', retval: '$retval'"
    exit 2
fi

# non destructive stop here

git push origin $branch
git-restore-mtime --skip-missing || echo "datetime restoration failed, return: $?, skip"
ls -la
echo "we ready for bump $current -> ${version}, press ENTER twice to proceed or ESC+ENTER to exit"

counter=0
while : ; do
    read -r key

    if [[ $key == $'\e' ]]; then
        exit 1

    elif [ -z "$key" ]; then
        counter=$((counter + 1))
        if [ "$counter" -eq 2 ]; then
            break
        fi
    fi
done

# actions starts here

xc update-pyproject "$current" "$version"

uncommited="$(git diff --cached --name-only | sort -u | tr '\n' ' ' | xargs)"
changes="$(git ls-files --deleted --modified --exclude-standard)"
changes="$(printf "$changes" | sort -u | tr '\n' ' ' | xargs)"

if [[ "$uncommited" =~ "\bpyproject\.toml\b" ]] || [[ "$changes" =~ "\bpyproject\.toml\b" ]]; then
    xc add-pyproject
fi

if [[ "$uncommited" =~ "\bci/\.pre-commit-config\.yaml\b" ]] || [[ "$changes" =~ "\bci/\.pre-commit-config\.yaml\b" ]]; then
    xc add-precommit
fi

uncommited="$(git diff --cached --name-only | sort -u | tr '\n' ' ' | xargs)"
if [ -n "$uncommited" ]; then
    git commit -m "$branch: $version"
fi

git tag -a "$version" -m "$version"
git push --tags

echo "version update to ${version}"

environment

Run: once

Make virtualenv for project build & test tools, install pre-push hook.

if [ ! -d ".venv" ]; then
    virtualenv --python python3.11 ".venv"
    .venv/bin/pip install --upgrade pip
    .venv/bin/pip install --upgrade poetry pre-commit tomli tomli_w docformatter rstcheck

else
    [ -f ".venv/bin/activate" ]

fi

.venv/bin/pre-commit install --config ci/.pre-commit-config.yaml --install-hooks --overwrite --color always --hook-type pre-push

autoupdate

Run: once

Autoupdate pre-commit hooks if the last update was more than 7 days ago.

ctime="$(date +%s)"
mtime="$(git log -1 --format=%ct ci/.pre-commit-config.yaml)"

result=$(((7*86400) - (ctime - mtime)))

if [ "$result" -le 0 ]; then
    update
fi

update

Run: once Requires: environment

Update all pre-commit hook versions to latest releases.

.venv/bin/pre-commit autoupdate --config ci/.pre-commit-config.yaml --color always

check

Requires: environment, autoupdate

Runs all defined pre-commit hooks.

.venv/bin/pre-commit run --config ci/.pre-commit-config.yaml --color always --all

clean

Run: once

Clean up the project working directory: remove build/, .venv/, and .ruff_cache/ directories, as well as all .pyc files and pycache directories.

rm -rf build/ || true
rm -rf .venv/ || true
rm -rf .ruff_cache/ || true

find . -name "*.pyc" -delete || true
find . -name "__pycache__" -type d -exec rm -rf {} + || true

update-pyproject

Run: once Requires: environment, autoupdate

Update version in pyproject.toml file based on provided old and new version tags. It validates the version format and ensures the current tag matches the project's version before writing the new version.

#!.venv/bin/python
from os import environ
from sys import argv, exit
from re import match
from pathlib import Path

import tomli_w
import tomllib

ROOT = Path(environ['PWD'])

def get_version(string):
    try:
        return match(r'^(\d+\.\d+\.\d+)$', string).group(1)
    except Exception:
        print(f'could not parse version from {string}')
        exit(3)

if __name__ == '__main__':
    try:
        current_tag = get_version(argv[1])
        version_tag = get_version(argv[2])
    except IndexError:
        print('usage: xc setver <old_tag> <new_tag>')
        exit(1)

    path = ROOT / 'pyproject.toml'
    try:
        with open(path, 'rb') as fd:
            data = tomllib.load(fd)

    except Exception:
        print(f'could not load {path}')
        exit(2)

    try:
        current_ver = get_version(data['tool']['poetry']['version'])
        print(f'project version: {current_ver}')

    except KeyError:
        print(f'could not find version in {data}')
        exit(2)

    if current_tag != current_ver:
        if current_ver == version_tag:
            print(f'current version {current_ver} == {version_tag}, no update needed')
            exit(0)

        print(f'current tag {current_tag} != {current_ver} current version')
        exit(4)

    data['tool']['poetry']['version'] = version_tag

    try:
        with open(path, 'wb') as fd:
            tomli_w.dump(data, fd)

        print(f'project version -> {version_tag}')

    except Exception:
        print(f'could not write {path} with {data=}')
        exit(5)

add-precommit

Requires: environment, autoupdate

Check and format ci/.pre-commit-config.yaml. If any changes are made, it stages the file for the next commit.

.venv/bin/pre-commit run check-yaml --config ci/.pre-commit-config.yaml --color always --file ci/.pre-commit-config.yaml || value="$?"

while true; do
    value="0"
    .venv/bin/pre-commit run yamlfix --config ci/.pre-commit-config.yaml --color always --file ci/.pre-commit-config.yaml || value="$?"

    if [ "$value" -eq 0 ]; then
        break

    elif [ "$value" -eq 1 ]; then
        continue

    else
        exit "$value"

    fi
done

changes="$(git diff pyproject.toml)" || exit "$?"
changes="$(printf "$changes" | wc -l)"
if [ "$changes" -ne 0 ]; then
    git add ci/.pre-commit-config.yaml
fi

add-pyproject

Requires: environment, autoupdate

Check and format pyproject.toml. If any changes are made, it stages the file for the next commit.

.venv/bin/pre-commit run check-toml --config ci/.pre-commit-config.yaml --color always --file pyproject.toml || value="$?"

while true; do
    value="0"
    .venv/bin/pre-commit run pretty-format-toml --config ci/.pre-commit-config.yaml --color always --file pyproject.toml || value="$?"

    if [ "$value" -eq 0 ]; then
        break

    elif [ "$value" -eq 1 ]; then
        continue

    else
        exit "$value"

    fi
done

changes="$(git diff pyproject.toml)" || exit "$?"
changes="$(printf "$changes" | wc -l)"
if [ "$changes" -ne 0 ]; then
    git add pyproject.toml
fi