Python shredded utilities
Project description
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/
(env)$ pytest --cov pymince # Tests with coverge
Usage
algorithm.py
fibonacci
fibonacci(n=None)
Returns a generator with fibonacci series up to n.
Runs indefinitely if n is specified as None.
:param Optional[int] n: Must be None or number.
:rtype: Generator[int]
luhn
luhn(value: str) -> bool
The Luhn algorithm or Luhn formula, also known as the "modulus 10" or "mod 10" algorithm,
named after its creator, IBM scientist Hans Peter Luhn,
is a simple checksum formula used to validate a variety of
identification numbers, such as credit card numbers, IMEI numbers, National Provider Identifier numbers
Based on: https://en.wikipedia.org/wiki/Luhn_algorithm
sieve_of_eratosthenes
sieve_of_eratosthenes(n)
Primes less than n.
Based on: https://en.wikipedia.org/wiki/Sieve_of_Eratosthenes
:param int n: n an integer n > 1
:rtype: Generator[int]. All prime numbers from 2 through n.
Examples:
from pymince.algorithm import sieve_of_eratosthenes as primes
primes(30) # --> 2, 3, 5, 7, 11, 13, 17, 19, 23, 29
boolean.py
string2bool
string2bool(value, ignorecase=False)
Function to convert a string representation of
truth to True or False.
:param str value: value to convert.
:param bool ignorecase: Uppercase/lowercase letters of given "value" are ignored.
:raise: "ValueError" if "value" is anything else.
:rtype: bool
Examples:
from pymince.boolean import string2bool
string2bool("true") # --> True
string2bool("false") # --> False
string2bool("TRUE") # --> ValueError
string2bool("TRUE", ignorecase=True) # --> True
string2bool("FALSE") # --> ValueError
string2bool("FALSE", ignorecase=True) # --> False
dates.py
IsoWeekDay
IsoWeekDay(value, names=None, *, module=None, qualname=None, type=None, start=1)
Python Enum containing Days of the Week, according to ISO,
where Monday == 1 ... Sunday == 7.
Provides a 'of' method can be used to verbalize a datetime.datetime.isoweekday
return value.
Example:
from pymince.dates import IsoWeekDay
friday = datetime.datetime(2023, 2, 17)
IsoWeekDay.of(friday) # pymince.dates.IsoWeekDay.FRIDAY
WeekDay
WeekDay(value, names=None, *, module=None, qualname=None, type=None, start=1)
Python Enum containing Days of the Week,
where Monday == 0 ... Sunday == 6.
Provides a 'of' method can be used to verbalize a datetime.datetime.weekday
return value.
Example:
from pymince.dates import WeekDay
friday = datetime.datetime(2023, 2, 17)
WeekDay.of(friday) # pymince.dates.WeekDay.FRIDAY
irange
irange(start_date, stop_date=None, time_step=None)
Returns a generator that produces a sequence of datetime's from "start_date" (inclusive)
to "stop_date" (exclusive) by "time_step".
:param datetime.datetime start_date: Inclusive.
:param datetime.datetime stop_date: Exclusive. `utcnow` is used by default.
:param datetime.delta time_step: one-day `timedelta` is used by default.
Examples:
import datetime
from pymince.dates import irange
ini = datetime.datetime.fromisoformat("2022-10-31")
end = datetime.datetime.fromisoformat("2022-11-02")
day = datetime.timedelta(days=1)
it = irange(ini, stop_date=end, time_step=day)
next(it) # --> datetime.datetime(2022, 10, 31, 0, 0)
next(it) # --> datetime.datetime(2022, 11, 1, 0, 0)
next(it) # --> raise StopIteration
string2year
string2year(value, gte=None, lte=None, shift=None)
Function to convert a string year representation to integer year.
:param str value: Value to convert.
:param Optional[int] gte: if it is specified is required that: year >= gte
:param Optional[int] lte: if it is specified is required that: year <= lte
:param Optional[int] shift: use a two-digit year on shift
:raise: "ValueError" if "value" cannot be converted.
:rtype: int
Examples:
from pymince.dates import string2year
string2year("53", shift=None) # --> 2053
string2year("53", shift=1953) # --> 1953
string2year("52", shift=1953) # --> 2052
string2year("54", shift=1953) # --> 1954
string2year("1954") # --> 1954
string2year("123") # --> ValueError
string2year("1955", gte=1956) # --> ValueError
string2year("1955", lte=1954) # --> ValueError
dictionary.py
Useful functions that use dictionaries.
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
Examples:
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 a dictionary has all the specified keys and if all its
evaluated key-related values are True.
:param dict dictionary:
:param keys: keys sequence
:rtype: bool
Examples:
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
find_leaf_value
find_leaf_value(key, dictionary)
Find leaf value in mapping.
:param Any key: key to find
:param dict dictionary:
Examples:
from pymince.dictionary import find_leaf_value
find_leaf_value('a', {}) # --> 'a'
find_leaf_value('a', {'a': 'b', 'b': 'c'}) # --> 'c'
find_leaf_value('a', {'a': 'a'}) # --> 'a'
from_objects
from_objects(iterable, key_getter, value_getter)
Create a new dictionary with elements generated from
the "key_getter" and "value_getter" callbacks applied to each element of the iterable.
:param Iterable[any] iterable:
:param Callable key_getter:
Dictionary keys getter.
It is called with each element of "iterable" passing it as an argument.
:param Callable value_getter:
Dictionary values getter.
It is called with each element of "iterable" passing it as an argument.
:raise: ValueError if any generated key is duplicate.
:rtype: dict
Examples:
from pymince.dictionary import from_objects
keygetter = operator.itemgetter(0)
valgetter = operator.itemgetter(1, 2)
values = iter([(1, "a", "b"), (2, "a", "b")])
from_objects(values, keygetter, valgetter) # --> {1: ('a', 'b'), 2: ('a', 'b')}
frozendict
frozendict(*args, **kwargs)
Returns a "MappingProxyType" from a dictionary built according to given parameters.
Add immutability only on a first level.
Examples:
from pymince.dictionary import frozendict
my_dict = frozendict(a=1, b=2)
my_dict["a"] # --> 1
list(my_dict.items()) # --> [("a", 1), ("b", 2)]
my_dict["c"] = 3 # --> TypeError
tree
tree()
Returns a dict whose defaults are dicts.
As suggested here: https://gist.github.com/2012250
Examples:
import json
from pymince.dictionary import tree
users = tree()
users['user1']['username'] = 'foo'
users['user2']['username'] = 'bar'
print(json.dumps(users)) # {"user1": {"username": "foo"}, "user2": {"username": "bar"}}
file.py
decompress
decompress(src_path, dst_path, size=65536)
Decompress given file in blocks using gzip.
:param str src_path: source file path
:param str dst_path: destination file(unzipped) path
:param int size: Read up to size bytes from src_path for each block.
:return: dst_path
Examples:
from pymince.file import decompress
decompress("/foo/src.txt.gz", "/baz/dst.txt") # --> "/baz/dst.txt"
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 a directory already exists,
this directory and the files contained in it will be deleted.
If "cleaning" is True and a file already exists,
this file will be deleted.
get_valid_filename
get_valid_filename(s)
Returns a valid filename for the given string.
- Remove leading/trailing spaces
- Change spaces to underscores
- Remove anything that is not an alphanumeric, dash, underscore, or dot
is_empty_directory
is_empty_directory(path)
Check if the given path is an empty directory.
match_from_zip
match_from_zip(zip_file, pattern)
Make an iterator that returns file names in the zip file that
match the given pattern.
Uppercase/lowercase letters are ignored.
:param zip_file: ZipFile object or zip path.
:param pattern: "re.Pattern" to filter filename list
:return: Iterator with the filenames found
Examples:
import pymince.file
pymince.file.match_from_zip("archive.zip", "^file") # --> file1.log file2.txt
pymince.file.match_from_zip(zipfile.ZipFile("archive.zip"), "^file") # --> file1.log file2.txt
replace_extension
replace_extension(filename, old_ext=None, new_ext=None)
Replace filename "old_ext" with "new_ext".
:param str filename:
:param Optional[str] old_ext:
:param Optional[str] new_ext:
Examples:
from pymince.file import replace_extension
# remove extensions
replace_extension("/home/user/file.old") # --> "/home/user/file"
replace_extension("/home/user/file.old", old_ext=".old") # --> "/home/user/file"
replace_extension("/home/user/file.old", old_ext=".new") # --> "/home/user/file.old"
# replace extensions
replace_extension("/home/user/file.old", new_ext=".new") # --> "/home/user/file.new"
replace_extension("/home/user/file.old", old_ext=".old", new_ext=".new") # --> "/home/user/file.new"
replace_extension("/home/user/file.old", old_ext=".new", new_ext=".new") # --> "/home/user/file.old"
functional.py
caller
caller(*args, **kwargs)
Return a callable that calls with given params.
Examples:
import pymince.functional
caller = pymince.functional.caller(range(5))
caller(len) # 5
caller(list) # [0, 1, 2, 3, 4]
classproperty
classproperty(method=None)
Decorator that converts a method with a single cls argument into a property
that can be accessed directly from the class.
Examples:
from pymince.functional import classproperty
class MyClass:
__foo = "var"
@classproperty
def foo(cls):
return cls.__foo
identity
identity(x)
Takes a single argument and returns it unchanged.
Identity function, as defined in https://en.wikipedia.org/wiki/Identity_function.
once
once(fn)
Decorator to execute a function only once.
Examples:
from pymince.functional import once
@once
def inc_once():
global n
n += 1
return 'anything'
n = 0
inc_once() # --> 'anything'
inc_once() # --> 'anything'
inc_once() # --> 'anything'
print(n) # --> 1
pipe
pipe(*fns)
Compose functions from left to right.
:param fns: Functions to compose.
:rtype: Callable[[Any], Any]
Examples:
from pymince.functional import pipe
addtwo = lambda n: n + 2
double = lambda n: n * 2
square = lambda n: n * n
fn = pipe(addtwo, double, square)
fn(1) # --> 36
retry_if_errors
retry_if_errors(*exceptions, delay=0, tries=1)
Decorator that retries to call the wrapped function
if any of given exceptions are thrown.
:param exceptions: Lists of exceptions that trigger a retry attempt.
:param int delay: seconds delay between attempts. default: 0.
:param int tries: number of attempts. default: 1
Examples:
@retry_if_errors(ValueError, TypeError, delay=0, tries=1)
def foo():
return 1
retry_if_none
retry_if_none(delay=0, tries=1)
Decorator that retries to call the wrapped function
if it returns None.
:param int delay: seconds delay between attempts. default: 0.
:param int tries: number of attempts. default: 1
Examples:
@retry_if_none(delay=0, tries=1)
def foo():
return 1
set_attributes
set_attributes(**kwargs)
Decorator to set attributes on functions and classes.
Examples:
from pymince.functional import set_attributes
@set_attributes(short_description="dummy function")
def foo():
pass
print(foo.short_description) # "dummy function"
Based on: https://github.com/wolph/python-utils/ (set_attributes)
suppress
suppress(*exceptions, default=None)
Decorator to suppress the specified exceptions and return the
default value instead.
Examples:
from pymince.functional import suppress
@suppress(FileNotFoundError, default=False)
def remove(somefile):
os.remove(somefile)
remove("no_found.txt") # False
iterator.py
Functions that use iterators for efficient loops.
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
Examples:
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
Examples:
from pymince.iterator import all_equal
all_equal([1, 1]) # --> True
all_equal([1, 2]) # --> False
all_equals
all_equals(*iterables, key=None)
Check if the iterables are equal.
If the "iterables" are empty, it returns True.
:param iterables:
:param key: None or "Callable" to compare if iterable items.
:rtype: bool
Examples:
from pymince.iterator import all_equals
all_equals() # --> True
all_equals(range(1, 4), (1, 2, 3), {1, 2, 3}) # --> True
all_equals((1, 2), (1, 2, 3)) # --> False
all_identical
all_identical(left, right)
Check that the items of `left` are the same objects
as those in `right`.
:param Iterable[Any] left:
:param Iterable[Any] right:
:rtype: bool
Examples:
from pymince.iterator import all_identical
a, b = object(), object()
all_identical([a, b, a], [a, b, a]) # --> True
all_identical([a, b, [a]], [a, b, [a]]) # --> False *new list object, while "equal" is not "identical"*
centroid
centroid(coordinates)
Calculate the centroid of a set of n-dimensional coordinates.
In Cartesian coordinates, the centroid is
just the mean of the components.
:param Iterable[Iterable[int]] coordinates: Iterable of n-dimensional coordinates.
:rtype: Generator[int]
Examples:
from pymince.iterator import centroid
coord = (((2, 2), (4, 4)))
tuple(centroid(coord)) # --> (3, 3)
consume
consume(iterator, n=None)
Advance *iterator* by *n* steps. If *n* is ``None``, consume it
entirely.
Examples:
from pymince.iterator import consume
it = iter([1, 2])
consume(it)
next(it) # --> StopIteration
grouper
grouper(iterable, size)
Make a generator that returns each element being iterable
with "size" as the maximum number of elements.
:param iterable:
:param int size: maximum size of element groups.
:rtype: Generator
Examples:
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]]
ibool
ibool(iterable)
Iterator class supporting ´__bool__´.
Examples:
from pymince.iterator import ibool
it = ibool((1, 2, 3))
bool(it) # --> True
list(it) # --> [1, 2, 3]
in_all
in_all(obj, iterables)
Check if the object is contained in all the given iterables.
If the "iterables" are empty, return True.
:param Any obj:
:param iterables: iterable of iterables
:rtype: bool
Examples:
from pymince.iterator import in_all
in_all("a", (("a", "b"), "bcd")) # --> False
in_all("a", (("a", "b"), "abc")) # --> True
in_all("a", ()) # --> True
in_any
in_any(obj, iterables)
Check if the object is contained in any of the given iterables.
:param Any obj:
:param iterables: iterable of iterables
:rtype: bool
Examples:
from pymince.iterator import in_any
in_any("a", (("a", "b"), "bcd")) # --> True
in_any("a", (("b", "b"), "def")) # --> False
in_any("a", ()) # --> False
ipush
ipush(iterable)
Iterator class supporting ´append´ and ´prepend´.
Examples:
from pymince.iterator import ipush
it = ipush(iter([2, 3])
it.append(4)
it.append(5)
it.prepend(1)
it.prepend(0)
list(it) # --> [0, 1, 2, 3, 4, 5]
mul
mul(iterable, start=1)
Return the multiplication of a 'start' value (default: 1)
plus an iterable of numbers.
When the iterable is empty, return the start value.
only_one
only_one(iterable)
Check if given iterable has only one element.
:param iterable:
:rtype: bool
Examples:
from pymince.iterator import only_one
only_one([1]) # --> True
only_one([1, 2]) # --> False
only_one([]) # --> False
pad_end
pad_end(iterable, length, fill_value=None)
The function adds "fill_value" at the finishing of the iterable,
until it reaches the specified length.
If the value of the "length" param is less than the length of
the given "iterable", no filling is done.
:param iterable:
:param int length: A number specifying the desired length of the resulting iterable.
:param Any fill_value: Any value to fill the given iterable.
:rtype: Generator
Examples:
from pymince.iterator import pad_end
pad_end(("a", "b"), 3, fill_value="1") # --> "a" "b" "1"
pad_end(("a", "b"), 3) # --> "a" "b" None
pad_end(("a", "b", "c"), 3) # --> "a" "b" "c"
pad_start
pad_start(iterable, length, fill_value=None)
The function adds "fill_value" at the beginning of the iterable,
until it reaches the specified length.
If the value of the "length" param is less than the length of
the given "iterable", no filling is done.
:param iterable:
:param int length: A number specifying the desired length of the resulting iterable.
:param Any fill_value: Any value to fill the given iterable.
:rtype: Generator
Examples:
from pymince.iterator import pad_start
pad_start(("a", "b"), 3, fill_value="1") # --> "1" "a" "b"
pad_start(("a", "b"), 3) # --> None "a" "b"
pad_start(("a", "b", "c"), 3) # --> "a" "b" "c"
partition
partition(predicate, iterable)
Split the iterable into two lists, based on the boolean return-value
of the predicate.
- (1): items that have predicate(item) == False.
- (2): items that have predicate(item) == True.
Examples:
from pymince.iterator import partition
is_odd = lambda x: x % 2 != 0
even_items, odd_items = partition(is_odd, range(10)) # ([0, 2, 4, 6, 8], [1, 3, 5, 7, 9])
replacer
replacer(iterable, matcher, new_value, count=-1)
Make a generator that yields 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.
:rtype: Generator
Examples:
from pymince.iterator import replacer
is_one = lambda n: n == 1
replacer([1,2,3,1,2,3], is_one, None) # --> None 2 3 None 2 3
replacer([1,2,3,1,2,3], is_one, None, count=1) # --> None 2 3 1 2 3
splitter
splitter(iterable, sep, key=None, maxsplit=-1, container=None)
Splits an iterable based on a separator.
A separator will never appear in the output.
: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.
:param container: Callable to save the splits. By default tuple is used.
:return: Generator with consecutive splits of "iterable" without the delimiter item.
Examples:
from pymince.iterator import splitter
data = ("a", "b", "c", "d", "b", "e")
split_n = splitter(data, "b") # --> ("a",) ("c", "d") ("e",)
split_1 = splitter(data, "b", maxsplit=1) # --> ("a",) ("c", "d", "b", "e")
sub
sub(iterable)
Return the subtraction of a non-empty iterable of numbers and sets.
truediv
truediv(iterable)
Return the division of an non-empty iterable of numbers.
uniquer
uniquer(iterable, key=None)
Make a generator that returns each element from iterable only once
respecting the input order.
Examples:
from pymince.iterator import uniquer
uniquer([1, 2, 3, 2]) # --> 1 2 3
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
Examples:
from pymince.iterator import uniques
uniques([1,2]) # --> True
uniques([1,1]) # --> False
json.py
Useful functions for working with JSONs.
JSONEncoder
JSONEncoder(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, sort_keys=False, indent=None, separators=None, default=None)
JSON encoder that handles additional types compared
to `json.JSONEncoder`
- `datetime` and `date` are serialized to strings according to the isoformat.
- `decimal.Decimal` is serialized to a string.
- `uuid.UUID` is serialized to a string.
- `dataclasses.dataclass` is passed to `dataclasses.asdict`.
- `frozenset` and `set` are serialized by ordering their values.
dump_from_csv
dump_from_csv(csv_path, json_path, /, *, fieldnames=None, start=0, stop=None, strip=True, encoding='utf-8', **kwargs)
Dump CSV file to a JSON file using "utf-8" encoding.
:param str csv_path:
:param str json_path:
:param fieldnames: list of keys for the JSON
:param int start:
If start is specified, will skip all preceding elements;
otherwise, start defaults to zero.
:param int stop:
:param bool strip:
Whether or not white space should be removed from the
beginning and end of field values.
:param str encoding: utf-8 is used by default.
dump_into
dump_into(filename, payload, encoding='utf-8', **kwargs)
Dump JSON to a file using "utf-8" encoding.
Examples:
from pymince.json import dump_into
dump_into("foo.json", {"key": "value"})
dump_into_zip
dump_into_zip(zip_path, arcname, payload, **kwargs)
Dump JSON into the zip archive under the name arcname.
Examples:
from pymince.json import dump_into_zip
dump_into_zip("archive.zip", "foo.json", {"key": "value"})
idump_fork
idump_fork(path_items, encoding='utf-8', dump_if_empty=True, **dumps_kwargs)
Incrementally dumps different groups of elements into
the indicated JSON file.
*** Useful to reduce memory consumption ***
:param Iterable[file_path, Iterable[dict]] path_items: group items by file path
:param encoding: 'utf-8' by default.
:param bool dump_if_empty: If false, don't create an empty file.
:param dumps_kwargs: json.dumps kwargs.
Examples:
from pymince.json import idump_fork
path_items = (
("num.json", ({"value": 1}, {"value": 2})),
("num.json", ({"value": 3},)),
("foo.json", ({"a": "1"}, {"b": 2})),
("baz.json", ()),
)
idump_fork(iter(path_items))
idump_into
idump_into(filename, iterable, encoding='utf-8', **kwargs)
Dump an iterable incrementally into a JSON file
using the "utf-8" encoding.
The result will always be an array with the elements of the iterable.
*** Useful to reduce memory consumption ***
Examples:
from pymince.json import idump_into
it = iter([{"key": "foo"}, {"key": "bar"}])
dump_into("foo.json", it)
idump_lines
idump_lines(iterable, **dumps_kwargs)
Generator yielding string lines that form a JSON array
with the serialized elements of given iterable.
*** Useful to reduce memory consumption ***
:param iterable: Iterable[dict]
:rtype: Iterable[str]
load_from
load_from(filename, encoding='utf-8')
Load JSON from a file using "utf-8" encoding.
Examples:
from pymince.json import load_from
dictionary = load_from("foo.json")
load_from_zip
load_from_zip(zip_path, arcname)
Load JSON from a file named "arcname" inside a zip archive.
Examples:
from pymince.json import load_from_zip
dictionary = load_from_zip("archive.zip", "foo.json")
jsonlines.py
Useful functions for working with JSON lines data as described:
dump
dump(iterable, fp, **kwargs)
Serialize iterable as a `jsonlines` formatted stream to file.
:param iterable: Iterable[Any]
:param fp: file-like object
:param kwargs: `json.dumps` kwargs
Example:
from pymince.jsonlines import dump
data = ({'foo': 1}, {'bar': 2})
with open('myfile.jsonl', mode='w', encoding ='utf-8') as file:
dump(iter(data), file)
dump_fork
dump_fork(path_items, encoding='utf-8', dump_if_empty=True, **kwargs)
Incrementally dumps different groups of elements into
the indicated `jsonlines` file.
*** Useful to reduce memory consumption ***
:param Iterable[file_path, Iterable[dict]] path_items: group items by file path
:param encoding: 'utf-8' by default.
:param bool dump_if_empty: If false, don't create an empty `jsonlines` file.
:param kwargs: json.dumps kwargs.
Examples:
from pymince.jsonlines import dump_fork
path_items = (
("num.jsonl", ({"value": 1}, {"value": 2})),
("num.jsonl", ({"value": 3},)),
("foo.jsonl", ({"a": "1"}, {"b": 2})),
("baz.jsonl", ()),
)
dump_fork(iter(path_items))
dump_into
dump_into(filename, iterable, encoding='utf-8', **kwargs)
Dump iterable to a `jsonlines` file.
Example:
from pymince.jsonlines import dump_into
data = ({'foo': 1}, {'bar': 2})
dump_into("myfile.jsonl", iter(data))
dumper
dumper(iterable, **kwargs)
Generator yielding JSON lines.
dumps
dumps(iterable, **kwargs)
Serialize iterable to a `jsonlines` formatted string.
:param iterable: Iterable[Any]
:param kwargs: `json.dumps` kwargs
:rtype: str
load
load(fp, **kwargs)
Returns iterable from a file formatted as JSON lines.
:param fp: file-like object
:param kwargs: `json.loads` kwargs
:rtype: Iterable[str]
load_from
load_from(filename, encoding='utf-8', **kwargs)
Returns iterable from a filename formatted as JSON lines.
:param filename: path
:param encoding: file encoding. 'utf-8' used by default
:param kwargs: `json.loads` kwargs
:rtype: Iterable[str]
Examples:
from pymince.jsonlines import load_from
it = load_from("myfile.jsonl")
next(it)
logging.py
ColoredFormatter
ColoredFormatter(fmt=None, datefmt=None, style='%', validate=True)
A class for formatting colored logs.
Default colors:
- DEBUG: blue
- INFO: green
- WARNING: yellow
- ERROR: red
- CRITICAL: red
Examples:
import logging
from pymince.logging import ColoredFormatter
# Config
logger = logging.getLogger('mylog')
logger.setLevel('DEBUG')
stream_handler = logging.StreamHandler()
stream_handler.setFormatter(ColoredFormatter(logging.BASIC_FORMAT))
logger.addHandler(stream_handler)
# Use default colors
logger.debug("This is debug") # blue color
# Use custom colors
import colorama
logger.debug("This is debug", extra={"color": colorama.Fore.BLACK})
ColoredLogger
ColoredLogger(name=None, level=10, **fmt_kwargs)
Custom logger to generate color logs.
Examples:
from pymince.logging import ColoredLogger
logger = ColoredLogger()
# Use default colors
logger.debug("This is debug") # blue color
# Use custom colors
import colorama
logger.debug("This is debug", extra={"color": colorama.Fore.BLACK})
StructuredFormatter
StructuredFormatter(fmt=None, datefmt=None, style='%', validate=True)
Implementation of JSON structured logging that works
for most handlers.
Examples:
import logging
import sys
from pymince.logging import StructuredFormatter
# Config
logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
formatter = StructuredFormatter('%(message)s')
handler = logging.StreamHandler(sys.stdout)
handler.setLevel(logging.DEBUG)
handler.setFormatter(formatter)
logger.addHandler(handler)
# Usage
logger.debug('', {"string": "value1", "number": 1})
logger.debug('', {"string": "value2", "number": 2})
>>Output<<
{"timestamp":"2022-06-17 18:37:48,789","level":"DEBUG","payload":{"string":"value1","number":1}}
{"timestamp":"2022-06-17 18:37:48,789","level":"DEBUG","payload":{"string":"value2","number":2}}
timed_block
timed_block(name, logger=None)
Log the duration of the handled context.
Examples:
import logging
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 s]
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".
Examples:
from pymince.std import bind_json_std
@bind_json_std()
def foo(data=None):
print("Processing data from sys.stdin", data)
result = data and {**data, "new": "value"}
print("Result to write in sys.stdout", result)
return result
text.py
Useful functions for working with strings.
are_anagram
are_anagram(text1, text2)
Check if two strings are anagram.
Examples:
from pymince.text import are_anagram
are_anagram("listen", "silent") # --> True
are_anagram("they see", "the eyes") # --> True
fullstr
fullstr()
Custom string inheriting from "str" which adds
the following methods:
- is_url(self, schemes=None, hostnames=None)
- is_int(self)
- is_positive_int(self)
- is_negative_int(self)
- is_payment_card(self)
- is_binary(self)
- is_percentage(self)
- is_palindrome(self)
- is_email_address(self)
- is_roman(self)
- are_anagram(self, other)
get_random_secret
get_random_secret(length, alphabet='abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ')
Generate a cryptographically secure random string.
Useful for creating temporary passwords.
get_random_string
get_random_string(length, alphabet='abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ')
Generate random string.
is_binary
is_binary(text)
Check if the string is binary or not.
is_email_address
is_email_address(text)
Check if the string is an email address.
This solution does a very simple check. It only validates that the string contains an at sign (@)
that is preceded and followed by one or more non whitespace characters.
is_int
is_int(text)
Check if the string is the representation of
a integer number.
True:
"10", "10.", "10.0",
"+10", "+10.", "+10.0",
"-10", "-10.", "-10.0"
is_negative_int
is_negative_int(text)
Check if the string is the representation of
negative integer number.
True:
"-10", "-10.", "-10.0"
is_palindrome
is_palindrome(text)
Check if the string is palindrome or not.
A string is said to be palindrome if the reverse of the string is the same as string
is_payment_card
is_payment_card(text)
Check if the string is a valid payment
card number.
https://en.wikipedia.org/wiki/Payment_card_number#Issuer_identification_number_(IIN)
is_percentage
is_percentage(text)
Check if the string is a valid percentage
True: "100%", "100 %", "100 %", 100.0 %",
is_positive_int
is_positive_int(text)
Check if the string is the representation of
positive integer number.
True:
"10", "10.", "10.0",
"+10", "+10.", "+10.0",
is_roman
is_roman(text)
Check if the string is a valid roman numeral.
is_url
is_url(text, schemes=None, hostnames=None)
Check if the string is a URL according to the
given schemes and host-names.
:param str text:
:param Optional[Container[str]] schemes: ("http", "https")
:param Optional[Container[str]] hostnames: ("www.python.org", "github.com", "localhost")
:rtype: bool
Examples:
from pymince.text import is_url
# True
is_url("https://github.com/")
is_url("https://github.com/", hostnames=("github.com",))
is_url("https://github.com/", hostnames=("github.com",), schemes=("https",))
# False
is_url("https://github.com/", schemes=("http",))
is_url("https://github.com/", hostnames=("www.python.org", "localhost"))
multireplace
multireplace(text, replacements)
Given a string and a replacement map, it returns the replaced string.
:param str text: string to execute replacements on.
:param Union[dict[str, str], tuple[tuple[str, str], ...] replacements:
2-dict or 2-tuples with value to find and value to replace
:rtype: str
Examples:
from pymince.text import multireplace
mapping = {",": "", "cry": "smile"}
multireplace("No, woman, no cry", mapping) # --> "No woman no smile"
multireplacer
multireplacer(replacements)
Given a replacement map, returns a function that can be reused to replace any string.
:param Union[dict[str, str], tuple[tuple[str, str], ...] replacements:
2-dict or 2-tuples with value to find and value to replace
:rtype: Callable[[str], str]
Examples:
from pymince.text import multireplacer
mapping = (("abc", "123"), ("def", "456"))
replace = multireplacer(mapping)
replace("...def...") # --> "...456..."
replace("...abc...") # --> "...123..."
replace("...abc...def...") # --> "...123...456..."
normalize_newlines
normalize_newlines(s)
Normalize CRLF and CR newlines to just LF.
remove_decimal_zeros
remove_decimal_zeros(value, decimal_sep='.', min_decimals=None)
Removes non-significant decimal zeros from a formatted text number.
Examples:
from pymince.text import remove_decimal_zeros
remove_decimal_zeros("2.000100", ".") # --> "2.0001"
remove_decimal_zeros("2.000000", ".") # --> "2"
remove_decimal_zeros("2.000000", ".", min_decimals=2) # --> "2.00"
remove_number_commas
remove_number_commas(s)
Removes commas from a formatted text number having commas
as group separator.
:param str s:
:rtype str
Examples:
from pymince.text import remove_number_commas
remove_number_commas('1,234,567.8') # --> '1234567.8'
replace
replace(value, old_values, new_value, count=-1)
Replace matching values in the given string with new_value.
:param str value:
:param old_values: iterable of values to replace.
:param str new_value: replacement value.
:param int count:
Maximum number of occurrences to replace.
-1 (the default value) means replace all occurrences.
:rtype: str
Examples:
from pymince.text import replace
replace("No, woman, no cry", [","], ";") # --> "No; woman; no cry"
replace("No, woman, no cry", [","], ";", count=1) # --> "No; woman, no cry"
slugify
slugify(value, allow_unicode=False)
Convert to ASCII if 'allow_unicode' is False. Convert spaces or repeated
dashes to single dashes. Remove characters that aren't alphanumerics,
underscores, or hyphens. Convert to lowercase. Also strip leading and
trailing whitespace, dashes, and underscores.
https://github.com/django/django/blob/main/django/utils/text.py
warnings.py
deprecated
deprecated(fn)
This is a decorator which can be used to mark functions
as deprecated. It will result in a warning being emitted
when the function is used.
http://code.activestate.com/recipes/391367-deprecated/?in=lang-python
Examples:
from pymince.warnings import deprecated
@deprecated
def check_function():
pass
class SomeClass:
@deprecated
def check_method(self):
pass
@deprecated
class CheckClass:
pass
>> check_function() # DeprecationWarning --> 'Deprecated "check_function".'
>> SomeClass().check_method() # DeprecationWarning --> 'Deprecated "check_method".'
>> CheckClass() # DeprecationWarning --> 'Deprecated "CheckClass".'
xml.py
iterparse
iterparse(filename)
Incrementally parse XML document into ElementTree.
This function is based on: https://github.com/python/cpython/issues/93618
'Fix misleading hint for original ElementTree.iterparse.'
'''
The code below deletes a root child once it is completed, then processes and removes
it from the memory (if nothing more references to it ofc).
This allows to process 7GB XML with with a memory usage up to 10MB (in case of great number of root children).
'''
:param str filename: XML filename
:rtype: Generator
Examples:
from pymince.xml import iterparse
for event, obj in iterparse("countries.xml")
if event == 'start'
print(obj, obj.tag, obj.attrib, obj.text)
>>Output<<
<Element 'country' at 0x0000018ADF9D0CC0> country {'code': 'as', 'iso': '16'} American Samoa
<Element 'country' at 0x0000018ADF9D0C70> country {'code': 'ad', 'iso': '20'} Andorra
Upgrade README.md
Upgrade README.md Usage section according to current pymince code.
(env) python upgrade_readme_usage.py
Release history Release notifications | RSS feed
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