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Collection of generic-purpose and stand-alone functions

Project description

Collection of generic-purpose and stand-alone functions

python pypi license build & test codecov pylint black

This package provides a collection of generic-purpose and stand-alone functions that are of common use. A characteristic of the package is to be lightweight and dependencies-free. Please, consider its installation if any of the following function can be of use in your project. Any addition to the list is very welcome!

Installation

The package can be installed via pip:

pip install [--user] lyncs_utils

Documentation

Here the list of functions implemented with a short description. Use help(lyncs_utils) for more details.

Class Utils

Functions and decorator for classes. See lyncs_utils.class_utils.

  • @add_to: Decorator for adding a function to a class
  • @add_kwargs_of(fnc): Decorator for adding kwargs of a function to another
  • @compute_property: Decorator for computing a property once and cache the result
  • @static_property: Decorator for a static property (like staticmethod)
  • @class_property: Decorator for a class property (like classmethod)
  • call_method(obj, fnc, *args, **kwargs): Calls a method of the obj.
  • default_repr_pretty: Default method to use for repr_pretty
  • default(value, type=None, doc=None): Attribute with default value and optional type checking
  • methodof(self, func): Returns the class where method has been defined
  • @before_super: Decorator that call method from super before executing for self
  • @after_super: Decorator that call method from super after executing for self

Extensions

Extensions of Python standard functions. See lyncs_utils.extensions.

  • count: See itertools.count. Adds call method
  • redirect_stdout: See contextlib.redirect_stdout. Now, it redirects stdout also from C
  • keydefaultdict: A defaultdict that passes the key to the factory
  • FreezableDict: Extension of dict. A dictionary that can be frozen at any moment.
  • cache: Enables functools.cache for all versions of Python
  • lazy_import(module): Lazy import for modules
  • setitems(arr, vals): Sets items of an iterable object
  • commonsuffix(words): Finds common suffix in words
  • @raiseif(fail, error): Decorator that raises error if fail is True
  • RaiseOnUse(error): Class instance that raises error when used
  • ndict: A dictionally that supports numerical operations

Math

Math utils. See lyncs_utils.math.

  • prod(arr): Enables math.prod for all versions of Python
  • sign(n): Sign of a number
  • iscomplex(n): If n is complex
  • isclose(a,b,warn_tol=None,**): math.isclose with support for complex and warning tol
  • factors(n): Returns the list of factors of n
  • prime_factors(n): Returns the list of prime factors of n

Functools

Tools for functions. See lyncs_utils.functools.

  • is_keyword(key): Whether key can be used as a function keyword
  • get_docstring(fnc): Returns the docstring of a function or class
  • get_varnames(fnc): Returns the list of varnames of the function
  • has_args(fnc): Whether the function uses *args
  • has_kwargs(fnc): Whether the function uses **kwargs
  • get_defaults(fnc): Returns the dict of default values of the function
  • get_annotations(fnc): Returns the dict of annotations of the function
  • apply_annotations(fnc, *args, **kwargs): Applies the annotations of fnc to the respective *args, **kwargs
  • select_kwargs(fnc, *args, **kwargs): Calls fnc passing *args and ONLY the applicable **kwargs
  • @spy: Decorator that will log debug information when the function is called
  • @clickit: Decorator that adds click.option for any function argument

Context Managers

Functionalities using contextmanager by contextlib meant to be called within a with-statement. See lyncs_utils.contextlib.

  • setting(obj, attr, value, default=None): Context manager that temporaly sets an attribute of an object.
  • updating(obj, attr, value, default=None): Context manager that temporaly sets an item of an object.

I/O

Tools for I/O. See lyncs_utils.io.

  • @open_file: Decorator that opens the file (if needed) before calling the function
  • read(fname/fp): Reads data from file
  • write(fname/fp): Writes data into the file
  • read_struct(fname/fp, format): Reads a structure from file
  • write_struct(fname/fp, format, *data): Writes a structure from file
  • file_size(fname/fp): Returns the file size
  • to_path(fname/fp): Returns a Path object to the file
  • dbdict: Dictionary-like class for storing dictionaries in a database

Logical

Functions returning or manipulating logical values (boolean). See lyncs_utils.logical.

  • single_true(iter): Whether one and only one element of the list is True
  • isiterable(obj): Whether the object is iteragle or not
  • interactive(): Whether Python has been run in interactive mode
  • version(num, pkg): Compares the version number to the one of a package

Numpy

Functions returning or manipulating Numpy arrays (available with lyncs[numpy])

  • outer(A,B): outer product, alias of numpy.kron.
  • gamma_matrices(dim, euclidean=True): returns n-dimensional gamma matrices
  • su_generators(N): returns NxN generators of su(N)

Itertools

Functions for iterable objects

  • first(it): first element of an iterable
  • last(it): last element of an iterable
  • indexes(it,val): indexes of occurances of a value in an iterable
  • keys(dict): calls keys, if available, or dict.keys
  • values(dict): calls values, if available, or dict.values
  • items(dict): calls items, if available, or dict.items
  • dictmap(fnc, dict): map for dictionaries
  • dictzip(*dicts, fill=True, default=None): zip for dictionaries
  • flat_dict(dict, sep=None, base=()): flat nested dictionaries into a single dict
  • nest_dict(dict, sep=None): turns a flat dictionaries into a nested dict
  • allclose(left, right, **): applies isclose recursively to iterable objects
  • compact_indexes(ids): compats list of integers into ranges where possible

Pytest

Functions tu use within pytest, to be impoted from lyncs_utils.pytest

  • DynParam(fnc): Dynamic params based on the test function
  • GetMark(map, def): Dynamic params based on the marks of the test function
  • lazy_fixture(str): Use a fixture as one of the values passed in @pytest.mark.parametrize

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