pyTooling 2.5.0

pyTooling is a powerful collection of arbitrary useful classes, decorators, meta-classes and exceptions.

pyTooling

pyTooling is a powerful collection of arbitrary useful abstract data models, classes, decorators, meta-classes and exceptions. It also provides lots of helper functions e.g. to ease the handling of package descriptions.

It's useful for any Python-base project independent if it's a library, framework or CLI tool.

Introduction

pyTooling is a basic collection of powerful helpers needed by almost any Python project. More specialized helpers can be found in sub-namespaces like:

• pyTooling.CLIAbstraction
• pyTooling.TerminalUI

In addition, pyTooling provides a collection of CI job templates for GitHub Actions. This drastically simplifies GHA-based CI pipelines for Python projects.

Package Details

Common Helper Functions

This is a set of useful helper functions:

• getsizeof calculates the "real" size of a data structure.
• isnestedclass checks if a class is nested inside another class.
• mergedicts merges multiple dictionaries into a new dictionary.
• zipdicts iterate multiple dictionaries simultaneously.

Common Classes

• pyTooling.CallByRef.*
  Emulation of call-by-reference parameters.
• pyTooling.Versioning.*
  Class representations of semantic version (SemVer) and calendar version (CalVer) numbers.

Data Structures

pyTooling also provides fast and powerful data structures offering object-oriented APIs:

• Trees
  • Tree data structure
    → A fast and simple implementation using a single Node class.

Decorators

• Documentation
  • @InheritDocString
    → Copy the doc-string from given base-class.
• Visibility
  • @export
    → Register the given function or class as publicly accessible in a module.

Exceptions

• EnvironmentException
  ... is raised when an expected environment variable is missing.
• PlatformNotSupportedException
  ... is raise if the platform is not supported.
• NotConfiguredException
  ... is raise if the requested setting is not configured.

Meta-Classes

• Overloading
  → Overloading allows method overloading in Python classes. It dispatches method calls based on method signatures (type annotations).
• Singleton
  → A class created from meta-class Singleton allows only a single instance to exist. If a further instance is tried to be created, a cached instance will be returned.
• SlottedType
  → All type-annotated fields in a class get stored in a slot rather than in __dict__. This improves the memory footprint as well as the field access performance of all class instances. The behavior is automatically inherited to all derived classes.

Packaging

tbd

Examples

@export Decorator

from pyTooling.Decorators import export

@export
class MyClass:
  pass

CallByRefIntParam

from pyTooling.CallByRef import CallByRefIntParam

# define a call-by-reference parameter for integer values
myInt = CallByRefIntParam(3)

# a function using a call-by-reference parameter
def func(param: CallByRefIntParam):
  param <<= param * 4

# call the function and pass the wrapper object
func(myInt)

print(myInt.Value)

Contributors

• Patrick Lehmann (Maintainer)
• Sven Köhler
• and more...

License

This Python package (source code) licensed under Apache License 2.0.
The accompanying documentation is licensed under Creative Commons - Attribution 4.0 (CC-BY 4.0).

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SPDX-License-Identifier: Apache-2.0