pymince 1.0.5

Python shredded utilities

pymince

About

pymince is a collection of useful tools that are "missing" from the Python standard library.

Installation (via pip)

pip install pymince

Tests

(env)$ pip install -r requirements.txt   # Ignore this command if it has already been executed
(env)$ pytest tests/

Usage

dictionary.py

DigestGetter

DigestGetter(include_keys=None, exclude_keys=None)

Calculate a digest of a "jsonified" python dictionary.

:param include_keys: dictionary keys to exclude
:param exclude_keys: dictionary keys to include
:rtype: str

Usage:
    from pymince.dictionary import DigestGetter

    getter = DigestGetter(include_keys=("a",))
    getter({"a": 1, "b": 1}) # --> bb6cb5c68df4652941caf652a366f2d8
    getter({"a": 1}) # --> bb6cb5c68df4652941caf652a366f2d8

all_true_values

all_true_values(dictionary, keys)

Check if an dictionary has all specified keys and
key-related values as True.

:param dict dictionary:
:param keys: keys sequence
:rtype: bool

Usage:
from pymince.dictionary import all_true_values

all_true_values({"a": 1, "b": 2}, ("a", "b")) # --> True
all_true_values({"a": 1, "b": 0}, ("a", "b")) # --> False
all_true_values({"a": 1, "b": 0}, ("a",)) # --> True

key_or_leaf_value

key_or_leaf_value(key, dictionary)

Find leaf key in dictionary.

:param str key: Key to find.
:param dict dictionary:

Usage:
    from pymince.dictionary import key_or_leaf_value

    key_or_leaf_value('a', {}) # --> 'a'
    key_or_leaf_value('a', {'a': 'b', 'b': 'c'}) # --> 'c'
    key_or_leaf_value('a', {'a': 'a'}) # --> 'a'

file.py

ensure_directory

ensure_directory(path, cleaning=False)

Make sure the given file path is an existing directory.
If it does not exist, a new directory will be created.

:param str path:
:param bool cleaning:
    If "cleaning" is True and the directory already exists,
    existing content will be deleted.

match_on_zip

match_on_zip(zip_file, pattern)

Make an iterator that returns file names in the zip file that
match the given pattern.

:param zip_file: instance of ZipFile class
:param pattern: Callable to filter filename list

open_on_zip

open_on_zip(zip_file, filename)

Open a file that is inside a zip file.

:param zip_file: instance of ZipFile class
:param str filename:

Usage:
-------------------------------------------------
import zipfile
from pymince.file import open_on_zip

with zipfile.ZipFile(zip_filename) as zf:
    # example1
    with open_on_zip(zf, "foo1.txt") as fd1:
        foo1_string = fd1.read()
    # example2
    with open_on_zip(zf, "foo2.txt") as fd2:
        foo2_string = fd2.read()
-------------------------------------------------

iterator.py

all_distinct

all_distinct(iterable, key=None)

Check if all the elements of a key-based iterable are distinct.

:param iterable:
:param key: None or "Callable" to compare if iterable items.
:rtype: bool

Usage:
    from pymince.iterator import all_distinct

    all_distinct([1, 1]) # --> False
    all_distinct([1, 2]) # --> True

all_equal

all_equal(iterable, key=None)

Check if all the elements of a key-based iterable are equals.

:param iterable:
:param key: None or "Callable" to compare if iterable items.
:rtype: bool

Usage:
    from pymince.iterator import all_equal

    all_equal([1, 1]) # --> True
    all_equal([1, 2]) # --> False

consume

consume(iterator)

Completely consume the given iterator.

grouper

grouper(iterable, size)

Make an iterator that returns each element being iterable
with "size" as the maximum number of elements.

:param iterable:
:param int size: maximum size of element groups.

Usage:
    from pymince.iterator import grouper

    groups = grouper([1, 2, 3, 4, 5], 2)
    list(list(g) for g in groups) # --> [[1, 2], [3, 4], [5]]

is_only_one

is_only_one(iterable)

Check if given iterable has only one element.

:param iterable:
:rtype: bool

non_empty_or_none

non_empty_or_none(iterator)

Returns an non-empty iterator or None according to given "iterator".

:param iterator:
:return: Iterator or None

Usage:
    from pymince.iterator import non_empty_or_none

    non_empty_or_none([]) # --> None
    non_empty_or_none([1,2]) # --> 1 2

replacer

replacer(iterable, matcher, new_value, count=-1)

Make an iterator that returns all occurrences of the old "iterable"
replaced by "new_value".

:param iterable:
:param matcher: Callable to find occurrences. It is an occurrence if the matcher returns True.
:param new_value: Any value to replace found occurrences.
:param int count:
    Maximum number of occurrences to replace.
    -1 (the default value) means replace all occurrences.

Usage:
    from pymince.iterator import replacer

    replacer([1,2,3,1,2,3], lambda n: n == 1, None) # --> None 2 3 None 2 3
    replacer([1,2,3,1,2,3], lambda n: n == 1, None, count=1) # --> None 2 3 1 2 3

splitter

splitter(iterable, sep, key=None, maxsplit=-1)

Split iterable into groups of iterators according
to given delimiter.

:param iterable:
:param sep: The delimiter to split the iterable.
:param key
    A function to compare the equality of each element with the given delimiter.
    If the key function is not specified or is None, the element itself is used for compare.

:param maxsplit:
    Maximum number of splits to do.
    -1 (the default value) means no limit.

:return: Generator with consecutive groups from "iterable" without the delimiter element.

Usage:
    from pymince.iterator import splitter

    data = ["a", "b", "c", "d", "b", "e"]

    undefined_split = splitter(data, "b")
    one_split = splitter(data, "b", maxsplit=1)
    list(list(s) for s in undefined_split) # --> [["a"], ["c", "d"], ["e"]]
    list(list(s) for s in one_split) # --> [["a"], ["c", "d", "b", "e"]]

uniquer

uniquer(iterable, key=None)

Make an iterator that returns each element from iterable only once
respecting the input order.

uniques

uniques(iterable, key=None)

Check if all the elements of a key-based iterable are unique.

:param iterable:
:param key: None or "Callable" to compare if iterable items.
:rtype: bool

Usage:
    from pymince.iterator import uniques

    uniques([1,2]) # --> True
    uniques([1,1]) # --> False

json.py

dump_into

dump_into(filename, payload, indent=2)

Dump JSON to a file.

Usage:
    from pymince.json import dump_into

    dump_into("foo.json", {"key": "value"})

load_from

load_from(filename)

Load JSON from a file.

Usage:
    from pymince.json import load_from

    dictionary = load_from("foo.json")

logging.py

timed_block

timed_block(name)

Logger the duration of the handled context.

Usage:
    from pymince.logging import timed_block

    logging.basicConfig(level=logging.DEBUG)
    with timed_block("sleeping"):
        time.sleep(1)

    >>Output<<
    INFO:root:Generating [sleeping]
    DEBUG:root:Finished [sleeping in 1.002 ms.]

retry.py

retry_if_none

retry_if_none(delay=0, tries=1)

Returns a retry decorator if the callback
returns None.

:param int delay: seconds delay between attempts. default: 0.
:param int tries: number of attempts. default: 1

Usage:
    @retry_if_none(delay=0, tries=1)
    def foo():
        return 1

std.py

bind_json_std

bind_json_std(encoding='utf-8')

Decorator to call "function" passing the json read from
"stdin" in the keyword parameter "data" and dump the json that the callback returns
to "stdout".

Upgrade README.md

Upgrade README.md Usage section according to current pymince code.

(env) python upgrade_readme_usage.py