Welcome to mpu’s documentation!¶

This package contains various small functions and classes. All of the functionality is not offered by any mayor package.

Core design principles are:

Lightweight:
- No dependencies
- Small file size
Documentation: Every parameter is properly documented. For each opened issue or question I will think about adding the information to the docs
Testing: >90% test coverage. For each issue found I will think about creating a test which could have shown the issue.

Please note that this is not in version 1.0 yet. So there will likely be breaking changes.

Contents:

mpu¶

mpu: Martins Python Utilities.

class mpu.Location(latitude: float, longitude: float)[source]¶

Bases: object

Define a single point.

Parameters

latitude (float) – in [-90, 90] - from North to South
longitude (float) – in [-180, 180] - from West to East

distance(there: mpu.Location) → float[source]¶

Calculate the distance from this location to there.

Parameters: there (Location) –
Returns: distance_in_m
Return type: float

get_google_maps_link()[source]¶: Get a Google Maps link to this location.

property latitude¶: Getter for latiutde.

property longitude¶: Getter for longitude.

mpu.clip(number: Union[int, float], lowest: Union[None, int, float] = None, highest: Union[None, int, float] = None) → Union[int, float][source]¶

Clip a number to a given lowest / highest value.

Parameters

number (number) –
lowest (number, optional) –
highest (number, optional) –

Returns

clipped_number

Return type

number

Examples

>>> clip(42, lowest=0, highest=10)
10

mpu.consistent_shuffle(*lists: List[List[Any]]) → Tuple[List[Any], …][source]¶

Shuffle lists consistently.

Parameters: *lists – Variable length number of lists
Returns: shuffled_lists – All of the lists are shuffled consistently
Return type: tuple of lists

Examples

>>> import mpu, random; random.seed(8)
>>> mpu.consistent_shuffle([1,2,3], ['a', 'b', 'c'], ['A', 'B', 'C'])
([3, 2, 1], ['c', 'b', 'a'], ['C', 'B', 'A'])

mpu.exception_logging(exctype, value, tb)[source]¶

Log exception by using the root logger.

Use it as sys.excepthook = exception_logging.

Parameters

exctype (type) –
value (NameError) –
tb (traceback) –

mpu.haversine_distance(origin: Tuple[float, float], destination: Tuple[float, float]) → float[source]¶

Calculate the Haversine distance.

Parameters

origin (Tuple[float, float]) – (lat, long)
destination (Tuple[float, float]) – (lat, long)

Returns

distance_in_km

Return type

float

Examples

>>> munich = (48.1372, 11.5756)
>>> berlin = (52.5186, 13.4083)
>>> round(haversine_distance(munich, berlin), 1)
504.2

>>> new_york_city = (40.712777777778, -74.005833333333)  # NYC
>>> round(haversine_distance(berlin, new_york_city), 1)
6385.3

mpu.is_in_intervall(value, min_value, max_value, name='variable')[source]¶

Raise an exception if value is not in an interval.

Parameters

value (orderable) –
min_value (orderable) –
max_value (orderable) –
name (str) – Name of the variable to print in exception.

mpu.parallel_for(loop_function: Callable[Any, Any], parameters: List[Tuple[Any, …]], nb_threads: int = 100) → List[Any][source]¶

Execute the loop body in parallel.

Note

Race-Conditions Executing code in parallel can cause an error class called “race-condition”.

Parameters

loop_function (Callable) – Python function which takes a tuple as input
parameters (List[Tuple]) – Each element here should be executed in parallel.

Returns

return_values

Return type

list of return values

mpu.aws¶

Convenience functions for AWS interactions.

class mpu.aws.ExistsStrategy[source]¶

Bases: enum.Enum

Strategies what to do when a file already exists.

ABORT = 'abort'¶

RAISE = 'raise'¶

REPLACE = 'replace'¶

class mpu.aws.S3Path(bucket_name, key)¶

Bases: tuple

property bucket_name¶: Alias for field number 0

property key¶: Alias for field number 1

mpu.aws.list_files(bucket, prefix='', profile_name=None)[source]¶

List up to 1000 files in a bucket.

Parameters

bucket (str) –
profile_name (str, optional) – AWS profile

Returns

s3_paths

Return type

List[str]

mpu.aws.s3_download(source, destination=None, exists_strategy=<ExistsStrategy.RAISE: 'raise'>, profile_name=None)[source]¶

Copy a file from an S3 source to a local destination.

Parameters

source (str) – Path starting with s3://, e.g. ‘s3://bucket-name/key/foo.bar’
destination (str, optional) – If none is given, a temporary file is created
exists_strategy ({'raise', 'replace', 'abort'}) – What is done when the destination already exists? * ExistsStrategy.RAISE means a RuntimeError is raised, * ExistsStrategy.REPLACE means the local file is replaced, * ExistsStrategy.ABORT means the download is not done.
profile_name (str, optional) – AWS profile

Returns

download_path – Path of the downloaded file.

Return type

str

Raises

botocore.exceptions.NoCredentialsError – Botocore is not able to find your credentials. Either specify profile_name or add the environment variables AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY and AWS_SESSION_TOKEN. See https://boto3.readthedocs.io/en/latest/guide/configuration.html

mpu.aws.s3_read(source, profile_name=None)[source]¶

Read a file from an S3 source.

Parameters

source (str) – Path starting with s3://, e.g. ‘s3://bucket-name/key/foo.bar’
profile_name (str, optional) – AWS profile

Returns

content

Return type

bytes

Raises

botocore.exceptions.NoCredentialsError – Botocore is not able to find your credentials. Either specify profile_name or add the environment variables AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY and AWS_SESSION_TOKEN. See https://boto3.readthedocs.io/en/latest/guide/configuration.html

mpu.aws.s3_upload(source, destination, profile_name=None)[source]¶

Copy a file from a local source to an S3 destination.

Parameters

source (str) –
destination (str) – Path starting with s3://, e.g. ‘s3://bucket-name/key/foo.bar’
profile_name (str, optional) – AWS profile

mpu.datastructures¶

Utility datastructures.

class mpu.datastructures.EList(*args)[source]¶

Bases: list

Enhanced List.

This class supports every operation a normal list supports. Additionally, you can call it with a list as an argument.

Examples

>>> l = EList([2, 1, 0])
>>> l[2]
0
>>> l[[2, 0]]
[0, 2]
>>> l[l]
[0, 1, 2]

remove_indices(indices)[source]¶

Remove rows by which have the given indices.

Parameters: indices (list) –
Returns: filtered_list
Return type: EList

class mpu.datastructures.Interval(left=None, right=None)[source]¶

Bases: mpu.datastructures.IntervalLike

Representation of an interval.

The empty interval is represented as left=None, right=None. Left and right have to be comparable. Typically, it would be numbers or dates.

Parameters

left (object) –
right (object) –

intersection(other)[source]¶

Intersect two IntervalLike objects.

Parameters: other (IntervalLike) –
Returns: intersected
Return type: IntervalLike

is_empty()[source]¶: Return if the interval is empty.

issubset(other)[source]¶

Check if the interval “self” is completely inside of other.

Parameters: other (IntervalLike) –
Returns: is_inside
Return type: bool

union(other)[source]¶

Combine two Intervals.

Parameters: other (IntervalLike) –
Returns: interval_union
Return type: IntervalLike

class mpu.datastructures.IntervalLike[source]¶

Bases: object

Anything like an interval or a union of an interval.

As mpu supports Python 2.7 until 2020 and does not want to include extra dependencies, ABC cannot be used.

intersection(other)[source]¶

Intersect two IntervalLike objects.

Parameters: other (IntervalLike) –
Returns: intersected
Return type: IntervalLike

is_empty()[source]¶: Return if the IntervalLike is empty.

issubset(other)[source]¶

Check if the interval “self” is completely inside of other.

Parameters: other (IntervalLike) –
Returns: is_inside
Return type: bool

union(other)[source]¶

Combine two Intervals.

Parameters: other (IntervalLike) –
Returns: interval_union
Return type: IntervalLike

class mpu.datastructures.IntervalUnion(intervals)[source]¶

Bases: mpu.datastructures.IntervalLike

A union of Intervals.

intersection(other)[source]¶

Return the intersection between this IntervalUnion and another object.

This changes the object itself!

Parameters: other (Interval or IntervalUnion) –
Returns: intersection
Return type: Interval or IntervalUnion

is_empty()[source]¶: Return if the IntervalUnion is empty.

issubset(other)[source]¶

Check if this IntervalUnion is completely inside of other.

Parameters: other (Interval or IntervalUnion) –
Returns: is_inside
Return type: bool

union(other)[source]¶

Return the union between this IntervalUnion and another object.

Parameters: other (Interval or IntervalUnion) –
Returns: union
Return type: Interval or IntervalUnion

mpu.datastructures.dict_merge(dict_left, dict_right, merge_method='take_left_shallow')[source]¶

Merge two dictionaries.

This method does NOT modify dict_left or dict_right!

Apply this method multiple times if the dictionary is nested.

Parameters

dict_left (dict) –
dict_right (dict) –
merge_method ({'take_left_shallow', 'take_left_deep', ) –

‘take_right_shallow’, ‘take_right_deep’,
‘sum’}
- take_left_shallow: Use both dictinaries. If both have the same key, take the value of dict_left
- take_left_deep : If both dictionaries have the same key and the value is a dict for both again, then merge those sub-dictionaries
- take_right_shallow : See take_left_shallow
- take_right_deep : See take_left_deep
- sum : sum up both dictionaries. If one does not have a value for a key of the other, assume the missing value to be zero.

Returns

merged_dict

Return type

dict

Examples

>>> dict_merge({'a': 1, 'b': 2}, {'c': 3}) == {'a': 1, 'b': 2, 'c': 3}
True

>>> out = dict_merge({'a': {'A': 1}},
...                  {'a': {'A': 2, 'B': 3}}, 'take_left_deep')
>>> expected = {'a': {'A': 1, 'B': 3}}
>>> out == expected
True

>>> out = dict_merge({'a': {'A': 1}},
...                  {'a': {'A': 2, 'B': 3}}, 'take_left_shallow')
>>> expected = {'a': {'A': 1}}
>>> out == expected
True

>>> out = dict_merge({'a': 1, 'b': {'c': 2}},
...                  {'b': {'c': 3, 'd': 4}},
...                  'sum')
>>> expected = {'a': 1, 'b': {'c': 5, 'd': 4}}
>>> out == expected
True

mpu.datastructures.does_keychain_exist(dict_, list_)[source]¶

Check if a sequence of keys exist in a nested dictionary.

Parameters

dict_ (Dict[str/int/tuple, Any]) –
list_ (List[str/int/tuple]) –

Returns

keychain_exists

Return type

bool

Examples

>>> d = {'a': {'b': {'c': 'd'}}}
>>> l_exists = ['a', 'b']
>>> does_keychain_exist(d, l_exists)
True

>>> l_no_existant = ['a', 'c']
>>> does_keychain_exist(d, l_no_existant)
False

mpu.datastructures.flatten(iterable, string_flattening=False)[source]¶

Flatten an given iterable of iterables into one list.

Parameters

iterable (iterable) –
string_flattening (bool) – If this is False, then strings are NOT flattened

Returns

flat_list

Return type

List

Examples

>>> flatten([1, [2, [3]]])
[1, 2, 3]

>>> flatten(((1, 2), (3, 4), (5, 6)))
[1, 2, 3, 4, 5, 6]

>>> flatten(EList([EList([1, 2]), (3, [4, [[5]]])]))
[1, 2, 3, 4, 5]

mpu.datastructures.set_dict_value(dictionary, keys, value)[source]¶

Set a value in a (nested) dictionary by defining a list of keys.

Note

Side-effects This function does not make a copy of dictionary, but directly edits it.

Parameters

dictionary (dict) –
keys (List[Any]) –
value (object) –

Returns

dictionary

Return type

dict

Examples

>>> d = {'a': {'b': {'c': 'x', 'f': 'g'}, 'd': 'e'}}
>>> expected = {'a': {'b': {'c': 'foobar', 'f': 'g'}, 'd': 'e'}}
>>> set_dict_value(d, ['a', 'b', 'c'], 'foobar') == expected
True

mpu.datetime¶

Datetime related utility functions.

mpu.datetime.add_time(datetime_obj, days=0, hours=0, minutes=0, seconds=0)[source]¶

Add time to a timezone-aware datetime object.

This keeps the timezone correct, even if it changes due to daylight saving time (DST).

Parameters

datetime_obj (datetime.datetime) –
days (int) –
hours (int) –
minutes (int) –
seconds (int) –

Returns

datetime

Return type

datetime.datetime

mpu.datetime.generate(minimum, maximum, local_random=<random.Random object>)[source]¶

Generate a random date.

The generated dates are uniformly distributed.

Parameters

minimum (datetime object) –
maximum (datetime object) –
local_random (random.Random) –

Returns

generated_date

Return type

datetime object

Examples

>>> import random; r = random.Random(); r.seed(0)
>>> from datetime import datetime

>>> generate(datetime(2018, 1, 1), datetime(2018, 1, 2), local_random=r)
datetime.datetime(2018, 1, 1, 20, 15, 58, 47972)

>>> generate(datetime(2018, 1, 1), datetime(2018, 1, 2), local_random=r)
datetime.datetime(2018, 1, 1, 18, 11, 27, 260414)

mpu.decorators¶

Decorators which are not in functools.

mpu.decorators.deprecated(func)[source]¶

Mark functions as deprecated.

It will result in a warning being emitted when the function is used.

mpu.decorators.timing(func)[source]¶: Measure the execution time of a function call and print the result.

mpu.geometry¶

Create and manipulate two-dimensional geometrical entities such as lines.

For more advanced use cases, see:

class mpu.geometry.LineSegment(p1: mpu.geometry.Point, p2: mpu.geometry.Point, name: str = 'LineSegment')[source]¶

Bases: object

A line segment a a 2-dimensional Euclidean space.

Parameters

p1 (Point) –
p2 (Point) –

angle() → float[source]¶: Get the angle of this line.

bounding_box() → Tuple[mpu.geometry.Point, mpu.geometry.Point][source]¶

Get the bounding box of this line represented by two points.

The p1 point is in the lower left corner, the p2 one at the upper right corner.

intersect(other) → Union[None, mpu.geometry.LineSegment, mpu.geometry.Point][source]¶

Get the intersection between this LineSegment and another LineSegment.

Parameters: other (LineSegment) –
Returns: intersection
Return type: Union[None, LineSegment, Point]

is_point()[source]¶: Check if this LineSegment is a point.

length() → float[source]¶: Get the length of this line segment.

simplify()[source]¶: Simplify this line segment to a point, if possible.

class mpu.geometry.Point(x: float, y: float)[source]¶

Bases: object

A point in a 2-dimensional Euclidean space.

Parameters

x (float) –
y (float) –

mpu.geometry.crossproduct(a: mpu.geometry.Point, b: mpu.geometry.Point) → float[source]¶: Get the cross product of two points.

mpu.geometry.do_bounding_boxes_intersect(a: Tuple[mpu.geometry.Point, mpu.geometry.Point], b: Tuple[mpu.geometry.Point, mpu.geometry.Point]) → bool[source]¶

Check if bounding boxes do intersect.

If one bounding box touches the other, they do intersect.

mpu.geometry.do_lines_intersect(a: mpu.geometry.LineSegment, b: mpu.geometry.LineSegment) → bool[source]¶: Check if LineSegments a and b intersect.

mpu.geometry.get_all_intersecting_lines_by_brute_force(lines: List[mpu.geometry.LineSegment]) → Set[FrozenSet[mpu.geometry.LineSegment]][source]¶

Get all interectionLines by applying a brute force algorithm.

Parameters: lines (all lines you want to check, in no order) –
Returns
Return type: a list that contains all pairs of intersecting lines

mpu.geometry.is_point_on_line(a: mpu.geometry.LineSegment, b: mpu.geometry.Point) → bool[source]¶: Check if point b is on LineSegment a.

mpu.geometry.is_point_right_of_line(a: mpu.geometry.LineSegment, b: mpu.geometry.Point) → bool[source]¶: Check if point b is right of line a.

mpu.geometry.line_segment_touches_or_crosses_line(a: mpu.geometry.LineSegment, b: mpu.geometry.LineSegment) → bool[source]¶: Check if line segment a touches or crosses line segment b.

mpu.image¶

Image manipulation.

mpu.image.get_meta(filepath)[source]¶

Get meta-information of an image.

Parameters: filepath (str) –
Returns: meta
Return type: dict

mpu.io¶

Reading and writing common file formats.

mpu.io.download(source: str, sink=None)[source]¶

Download a file.

Parameters

source (str) – Where the file comes from. Some URL.
sink (str or None (default: same filename in current directory)) – Where the file gets stored. Some filepath in the local file system.

mpu.io.get_access_datetime(filepath: str)[source]¶

Get the last time filepath was accessed.

Parameters: filepath (str) –
Returns: access_datetime
Return type: datetime.datetime

mpu.io.get_creation_datetime(filepath: str)[source]¶

Get the date that a file was created.

Parameters: filepath (str) –
Returns: creation_datetime
Return type: datetime.datetime or None

mpu.io.get_file_meta(filepath: str)[source]¶

Get meta-information about a file.

Parameters: filepath (str) –
Returns: meta
Return type: dict

mpu.io.get_modification_datetime(filepath: str)[source]¶

Get the datetime that a file was last modified.

Parameters: filepath (str) –
Returns: modification_datetime
Return type: datetime.datetime

mpu.io.gzip_file(source: str, sink: str)[source]¶

Create a GZIP file from a source file.

Parameters

source (str) – Filepath
sink (str) – Filepath

mpu.io.hash(filepath: str, method='sha1', buffer_size=65536)[source]¶

Calculate a hash of a local file.

Parameters

filepath (str) –
method ({'sha1', 'md5'}) –
buffer_size (int, optional (default: 65536 byte = 64 KiB)) – in byte

Returns

hash

Return type

str

mpu.io.read(filepath: str, **kwargs)[source]¶

Read a file.

Supported formats:

CSV
JSON, JSONL
pickle

Parameters

filepath (str) – Path to the file that should be read. This methods action depends mainly on the file extension.
kwargs (dict) – Any keywords for the specific file format. For CSV, this is ‘delimiter’, ‘quotechar’, ‘skiprows’, ‘format’

Returns

data

Return type

Union[str, bytes] or other (e.g. format=dicts)

mpu.io.urlread(url: str, encoding='utf8')[source]¶

Read the content of an URL.

Parameters: url (str) –
Returns: content
Return type: str

mpu.io.write(filepath: str, data, **kwargs)[source]¶

Write a file.

Supported formats:

CSV
JSON, JSONL
pickle

Parameters

filepath (str) – Path to the file that should be read. This methods action depends mainly on the file extension.
data (dict or list) – Content that should be written
kwargs (dict) – Any keywords for the specific file format.

Returns

data

Return type

str or bytes

mpu.math¶

Mathematical functions which are not adequately covered by standard libraries.

Standard libraries are:

mpu.math.argmax(iterable)[source]¶

Find the first index of the biggest value in the iterable.

Parameters: iterable (iterable) –
Returns: argmax
Return type: int

Examples

>>> argmax([0, 0, 0])
0
>>> argmax([1, 0, 0])
0
>>> argmax([0, 1, 0])
1
>>> argmax([])

mpu.math.factorize(number)[source]¶

Get the prime factors of an integer except for 1.

Parameters: number (int) –
Returns: primes
Return type: iterable

Examples

>>> factorize(-17)
[-1, 17]
>>> factorize(8)
[2, 2, 2]
>>> factorize(3**25)
[3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3]
>>> factorize(1)
[1]

mpu.math.gcd(a: int, b: int) → int[source]¶

Calculate the greatest common divisor.

Currently, this uses the Euclidean algorithm.

Parameters

a (int) – Non-zero
b (int) –

Returns

greatest_common_divisor

Return type

int

Examples

>>> gcd(1, 7)
1
>>> gcd(-1, -1)
1
>>> gcd(1337, 42)
7
>>> gcd(-1337, -42)
7
>>> gcd(120, 364)
4
>>> gcd(273, 1870)
1

mpu.math.generate_primes()[source]¶

Generate an infinite sequence of prime numbers.

The algorithm was originally written by David Eppstein, UC Irvine. See: http://code.activestate.com/recipes/117119/

Examples

>>> g = generate_primes()
>>> next(g)
2
>>> next(g)
3
>>> next(g)
5

mpu.math.is_prime(number)[source]¶

Check if a number is prime.

Parameters: number (int) –
Returns: is_prime_number
Return type: bool

Examples

>>> is_prime(-17)
False
>>> is_prime(17)
True
>>> is_prime(47055833459)
True

mpu.math.product(iterable, start=1)[source]¶

Calculate the product of the iterables.

Parameters

iterable (iterable) – List, tuple or similar which contains numbers
start (number, optional (default: 1)) –

Returns

product

Return type

number

Examples

>>> product([1, 2, 3, 4, 5])
120
>>> product([])
1

mpu.math.round_down(x, decimal_places)[source]¶

Round a float down to decimal_places.

Parameters

x (float) –
decimal_places (int) –

Returns

rounded_float

Return type

float

Examples

>>> round_down(1.23456, 3)
1.234
>>> round_down(1.23456, 2)
1.23

mpu.math.round_up(x, decimal_places)[source]¶

Round a float up to decimal_places.

Parameters

x (float) –
decimal_places (int) –

Returns

rounded_float

Return type

float

Examples

>>> round_up(1.2344, 3)
1.235
>>> round_up(1.234, 3)
1.234
>>> round_up(1.23456, 3)
1.235
>>> round_up(1.23456, 2)
1.24

mpu.ml¶

Machine Learning functions.

mpu.ml.indices2one_hot(indices, nb_classes)[source]¶

Convert an iterable of indices to one-hot encoded list.

You might also be interested in sklearn.preprocessing.OneHotEncoder

Parameters

indices (iterable) – iterable of indices
nb_classes (int) – Number of classes
dtype (type) –

Returns

one_hot

Return type

list

Examples

>>> indices2one_hot([0, 1, 1], 3)
[[1, 0, 0], [0, 1, 0], [0, 1, 0]]
>>> indices2one_hot([0, 1, 1], 2)
[[1, 0], [0, 1], [0, 1]]

mpu.ml.one_hot2indices(one_hots)[source]¶

Convert an iterable of one-hot encoded targets to a list of indices.

Parameters: one_hot (list) –
Returns: indices
Return type: list

Examples

>>> one_hot2indices([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
[0, 1, 2]

>>> one_hot2indices([[1, 0], [1, 0], [0, 1]])
[0, 0, 1]

mpu.path¶

Functions for path manipultion and retrival of files.

mpu.path.get_all_files(root, followlinks=False)[source]¶

Get all files within the given root directory.

Note that this list is not ordered.

Parameters

root (str) – Path to a directory
followlinks (bool, optional (default: False)) –

Returns

filepaths – List of absolute paths to files

Return type

list

mpu.path.get_from_package(package_name, path)[source]¶

Get the absolute path to a file in a package.

Parameters

package_name (str) – e.g. ‘mpu’
path (str) – Path within a package

Returns

filepath

Return type

str

mpu.pd¶

Pandas utility functions.

mpu.pd.describe(df, dtype=None)[source]¶

Print a description of a Pandas dataframe.

Parameters

df (Pandas.DataFrame) –
dtype (dict) – Maps column names to types

mpu.pd.example_df()[source]¶: Create an example dataframe.

mpu.shell¶

Enhancing printed terminal output.

class mpu.shell.Codes[source]¶

Bases: object

Escape sequences for enhanced shell output.

BACKGROUND_BLACK = '\x1b[40m'¶

BACKGROUND_BLUE = '\x1b[44m'¶

BACKGROUND_CYAN = '\x1b[46m'¶

BACKGROUND_DARK_GRAY = '\x1b[100m'¶

BACKGROUND_DEFAULT = '\x1b[49m'¶

BACKGROUND_GREEN = '\x1b[42m'¶

BACKGROUND_LIGHT_BLUE = '\x1b[104m'¶

BACKGROUND_LIGHT_CYAN = '\x1b[106m'¶

BACKGROUND_LIGHT_GRAY = '\x1b[47m'¶

BACKGROUND_LIGHT_GREEN = '\x1b[102m'¶

BACKGROUND_LIGHT_MAGENTA = '\x1b[105m'¶

BACKGROUND_LIGHT_RED = '\x1b[101m'¶

BACKGROUND_LIGHT_YELLOW = '\x1b[103m'¶

BACKGROUND_MAGENTA = '\x1b[45m'¶

BACKGROUND_RED = '\x1b[41m'¶

BACKGROUND_WHITE = '\x1b[107m'¶

BACKGROUND_YELLOW = '\x1b[43m'¶

BLACK = '\x1b[30m'¶

BLINK = '\x1b[5m'¶

BLUE = '\x1b[34m'¶

BOLD = '\x1b[1m'¶

CYAN = '\x1b[36m'¶

DARK_GRAY = '\x1b[90m'¶

DEFAULT = '\x1b[39m'¶

DIM = '\x1b[2m'¶

GREEN = '\x1b[32m'¶

HIDDEN = '\x1b[8m'¶

LIGHT_BLUE = '\x1b[94m'¶

LIGHT_CYAN = '\x1b[96m'¶

LIGHT_GRAY = '\x1b[37m'¶

LIGHT_GREEN = '\x1b[92m'¶

LIGHT_MAGENTA = '\x1b[95m'¶

LIGHT_RED = '\x1b[91m'¶

LIGHT_YELLOW = '\x1b[93m'¶

MAGENTA = '\x1b[35m'¶

RED = '\x1b[31m'¶

RESET_ALL = '\x1b[0m'¶

RESET_BLINK = '\x1b[25m'¶

RESET_BOLD = '\x1b[21m'¶

RESET_DIM = '\x1b[22m'¶

RESET_HIDDEN = '\x1b[28m'¶

RESET_REVERSE = '\x1b[27m'¶

RESET_UNDERLINED = '\x1b[24m'¶

REVERSE = '\x1b[7m'¶

UNDERLINED = '\x1b[4m'¶

WHITE = '\x1b[97m'¶

YELLOW = '\x1b[33m'¶

mpu.shell.print_table(table)[source]¶

Print as a table.

I recommend looking at [tabulate](https://pypi.org/project/tabulate/).

Parameters: table (list) –

Examples

>>> print_table([[1, 2, 3], [41, 0, 1]])
 1  2  3
41  0  1

mpu.shell.text_input(text)[source]¶

Ask the user for textual input.

Parameters: text (str) – What the user sees.
Returns: inputed_text – What the user wrote.
Return type: str

mpu.string¶

String manipulation, verification and formatting.

For more complex checks, you might want to use the [validators](http://validators.readthedocs.io) package.

mpu.string.human_readable_bytes(nb_bytes: Union[int, float], suffix: str = 'B') → str[source]¶

Convert a byte number into a human readable format.

Parameters

nb_bytes (Union[int, float]) –
suffix (str, optional (default: "B")) –

Returns

size_str

Return type

str

Examples

>>> human_readable_bytes(123)
'123.0 B'

>>> human_readable_bytes(1025)
'1.0 KiB'

>>> human_readable_bytes(9671406556917033397649423)
'8.0 YiB'

mpu.string.is_email(potential_email_address: str) → bool[source]¶

Check if potential_email_address is a valid e-mail address.

Please note that this function has no false-negatives but many false-positives. So if it returns that the input is not a valid e-mail adress, it certainly isn’t. If it returns True, it might still be invalid. For example, the domain could not be registered.

Parameters: potential_email_address (str) –
Returns: is_email
Return type: bool

Examples

>>> is_email('')
False
>>> is_email('info@martin-thoma.de')
True
>>> is_email('info@math.martin-thoma.de')
True
>>> is_email('Martin Thoma <info@martin-thoma.de>')
False
>>> is_email('info@martin-thoma')
False
>>> is_email('Martin <>')
False

mpu.string.is_float(potential_float: str) → bool[source]¶

Check if potential_float is a valid float.

Returns: is_float
Return type: bool

Examples

>>> is_float('123')
True
>>> is_float('1234567890123456789')
True
>>> is_float('0')
True
>>> is_float('-123')
True
>>> is_float('123.45')
True
>>> is_float('a')
False
>>> is_float('0x8')
False

mpu.string.is_iban(potential_iban: str) → bool[source]¶

Check if a string is a valid IBAN number.

IBAN is described in ISO 13616-1:2007 Part 1.

Spaces are ignored.

# CODE 0 = always zero b = BIC or National Bank code c = Account number i = holder’s kennitala (national identification number) k = IBAN check digits n = Branch number t = Account type x = National check digit or character

Examples

>>> is_iban('DE89 3704 0044 0532 0130 00')
True
>>> is_iban('DE89 3704 0044 0532 0130 01')
False

mpu.string.is_int(potential_int: str) → bool[source]¶

Check if potential_int is a valid integer.

Parameters: potential_int (str) –
Returns: is_int
Return type: bool

Examples

>>> is_int('123')
True
>>> is_int('1234567890123456789')
True
>>> is_int('0')
True
>>> is_int('-123')
True
>>> is_int('123.45')
False
>>> is_int('a')
False
>>> is_int('0x8')
False

mpu.string.is_ipv4(potential_ipv4: str, allow_leading_zeros: bool = False, allow_shortened_addresses=False) → bool[source]¶

Check if a string is a valid IPv4 address.

Parameters: potential_ipv4 (str) –
Returns: is_valid
Return type: bool

Examples

>>> is_ipv4("192.168.0.4")
True
>>> is_ipv4("192.168..4")
False
>>> is_ipv4("192.168.01.4", allow_leading_zeros=True)
True
>>> is_ipv4("192.168.01.4", allow_leading_zeros=False)
False
>>> is_ipv4("256.168.01.4")
False
>>> is_ipv4("4", allow_shortened_addresses=True)
True
>>> is_ipv4("4", allow_shortened_addresses=False)
False

mpu.string.is_none(string_: str, default='raise') → bool[source]¶

Check if a string is equivalent to None.

Parameters

string_ (str) –
default ({'raise', False}) – Default behaviour if none of the “None” strings is detected.

Returns

is_none

Return type

bool

Examples

>>> is_none('2', default=False)
False
>>> is_none('undefined', default=False)
True

mpu.string.str2bool(string_: str, default='raise') → bool[source]¶

Convert a string to a bool.

Parameters

string_ (str) –
default ({'raise', False}) – Default behaviour if none of the “true” strings is detected.

Returns

boolean

Return type

bool

Examples

>>> str2bool('True')
True
>>> str2bool('1')
True
>>> str2bool('0')
False

mpu.string.str2bool_or_none(string_: str, default='raise') → Optional[bool][source]¶

Convert a string to a bool or to None.

Parameters

string_ (str) –
default ({'raise', False}) – Default behaviour if none of the “true” or “none” strings is detected.

Returns

bool_or_none

Return type

bool or None

Examples

>>> str2bool_or_none('True')
True
>>> str2bool_or_none('1')
True
>>> str2bool_or_none('0')
False
>>> str2bool_or_none('undefined')

mpu.string.str2float_or_none(string_: str) → Optional[float][source]¶

Convert a string to a float or to None.

Parameters: string_ (str) –
Returns: float_or_none
Return type: float or None

Examples

>>> str2float_or_none('1')
1.0
>>> str2float_or_none('1.2')
1.2
>>> str2float_or_none('undefined')

mpu.string.str2int_or_none(string_: str) → Optional[int][source]¶

Convert a string to a int or to None.

Parameters: string_ (str) –
Returns: int_or_none
Return type: int or None

Examples

>>> str2int_or_none('2')
2
>>> str2int_or_none('undefined')

mpu.string.str2str_or_none(string_: str) → Optional[str][source]¶

Convert a string to a str or to None.

Parameters: string_ (str) –
Returns: str_or_none
Return type: bool or None

Examples

>>> str2str_or_none('True')
'True'
>>> str2str_or_none('1')
'1'
>>> str2str_or_none('0')
'0'
>>> str2str_or_none('undefined')

mpu.units¶

Module contents¶

Handle units - currently only currencies.

class mpu.units.Currency(name, code, numeric_code, symbol, exponent, entities, withdrawal_date, subunits)[source]¶

Bases: object

Currency base class which contains information similar to ISO 4217.

for_json()¶: Return a JSON-serializable object.

classmethod from_json(json)[source]¶: Create a Currency object from a JSON dump.

class mpu.units.Money(value: Union[str, fractions.Fraction, int, Tuple], currency: Union[str, mpu.units.Currency])[source]¶

Bases: object

Unit of account.

Parameters

value (Union[str, fractions.Fraction, int, Tuple]) –
currency (Currency or str) –

Examples

>>> rent = Money(500, 'USD')
>>> '{:.2f,shortcode}'.format(rent)
'USD 500.00'
>>> '{:.2f,postshortcode}'.format(rent)
'500.00 USD'
>>> '{:.2f,symbol}'.format(rent)
'$500.00'
>>> '{:.2f,postsymbol}'.format(rent)
'500.00$'
>>> '{:.2f}'.format(rent)
'500.00 USD'

for_json()¶: Return a JSON-serializable object.

classmethod from_json(json)[source]¶: Create a Money object from a JSON dump.

mpu.units.get_currency(currency_str)[source]¶

Convert an identifier for a currency into a currency object.

Parameters: currency_str (str) –
Returns: currency
Return type: Currency

Allowed operations with Money¶

Here you can see which operations are allowed by two Money objects of currencies (A and B):

Operator	Money A	Money B	int, Fraction
+ , -	Money A	N/A	N/A
*	N/A	N/A	Money A
/	N/A	N/A	N/A
//	Fraction	N/A	Money A
>, >=, <, <=	Bool	N/A	N/A
==	Bool	False	False

Welcome to mpu’s documentation!¶

mpu¶

mpu.aws¶

mpu.datastructures¶

mpu.datetime¶

mpu.decorators¶

mpu.geometry¶

mpu.image¶

mpu.io¶

mpu.math¶

mpu.ml¶

mpu.path¶

mpu.pd¶

mpu.shell¶

mpu.string¶

mpu.units¶

Module contents¶

Allowed operations with Money¶

Indices and tables¶