To help you get started, we've collected the most common ways that toolz is being used within popular public projects.

dask / dask / dask / array / core.py View on Github

>>> blockdims_from_blockshape((10, 0), (4, 0))
    ((4, 4, 2), (0,))
    """
    if chunks is None:
        raise TypeError("Must supply chunks= keyword argument")
    if shape is None:
        raise TypeError("Must supply shape= keyword argument")
    if np.isnan(sum(shape)) or np.isnan(sum(chunks)):
        raise ValueError("Array chunk sizes are unknown. shape: %s, chunks: %s"
                         % (shape, chunks))
    if not all(map(is_integer, chunks)):
        raise ValueError("chunks can only contain integers.")
    if not all(map(is_integer, shape)):
        raise ValueError("shape can only contain integers.")
    shape = tuple(map(int, shape))
    chunks = tuple(map(int, chunks))
    return tuple(((bd,) * (d // bd) + ((d % bd,) if d % bd else ())
                 if d else (0,))
                 for d, bd in zip(shape, chunks))

View more ways to use toolz

Toolz

A set of utility functions for iterators, functions, and dictionaries.

See the PyToolz documentation at

LICENSE

New BSD. See License File.

Install

toolz is on the Python Package Index (PyPI):

pip install toolz

Structure and Heritage

toolz is implemented in three parts:

itertoolz_, for operations on iterables. Examples: groupby, unique, interpose,

functoolz_, for higher-order functions. Examples: memoize, curry, compose,

dicttoolz_, for operations on dictionaries. Examples: assoc, update-in, merge.

These functions come from the legacy of functional languages for list processing. They interoperate well to accomplish common complex tasks.

Read our API Documentation for more details.

Example

This builds a standard wordcount function from pieces within toolz:

>>> def stem(word):
...     """ Stem word to primitive form """
...     return word.lower().rstrip(",.!:;'-\"").lstrip("'\"")

>>> from toolz import compose, frequencies
>>> from toolz.curried import map
>>> wordcount = compose(frequencies, map(stem), str.split)

>>> sentence = "This cat jumped over this other cat!"
>>> wordcount(sentence)
{'this': 2, 'cat': 2, 'jumped': 1, 'over': 1, 'other': 1}

Dependencies

toolz supports Python 3.7+ with a common codebase. It is pure Python and requires no dependencies beyond the standard library.

It is, in short, a lightweight dependency.

CyToolz

The toolz project has been reimplemented in Cython. The cytoolz project is a drop-in replacement for the Pure Python implementation. See CyToolz GitHub Page for more details.

See Also

• Underscore.js: A similar library for JavaScript
• Enumerable: A similar library for Ruby
• Clojure: A functional language whose standard library has several counterparts in toolz
• itertools: The Python standard library for iterator tools
• functools: The Python standard library for function tools

Contributions Welcome

toolz aims to be a repository for utility functions, particularly those that come from the functional programming and list processing traditions. We welcome contributions that fall within this scope.

We also try to keep the API small to keep toolz manageable. The ideal contribution is significantly different from existing functions and has precedent in a few other functional systems.

Please take a look at our issue page for contribution ideas.

Community

See our mailing list. We're friendly.