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Angelos Chalaris c0d36df01c [CHORE] Cleanup scripts, setup most of Travis 
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## 30-seconds-of-python-code
> Curated collection of useful Python snippets that you can understand in 30 seconds or less.
* Use <kbd>Ctrl</kbd> + <kbd>F</kbd> or <kbd>command</kbd> + <kbd>F</kbd> to search for a snippet.
* Contributions welcome, please read the [contribution guide](CONTRIBUTING.md).
* If you want to follow 30-seconds-of-code on social media, you can find us on [Facebook](https://www.facebook.com/30secondsofcode), [Instagram](https://www.instagram.com/30secondsofcode) and [Twitter](https://twitter.com/30secondsofcode).
#### Related projects
* [30 Seconds of code](https://github.com/30-seconds/30-seconds-of-code)
* [30 Seconds of CSS](https://30-seconds.github.io/30-seconds-of-css/)
* [30 Seconds of Interviews](https://30secondsofinterviews.org/)
* [30 Seconds of React](https://github.com/30-seconds/30-seconds-of-react)
* [30 Seconds of PHP](https://github.com/30-seconds/30-seconds-of-php-code)
* [30 Seconds of Knowledge](https://chrome.google.com/webstore/detail/30-seconds-of-knowledge/mmgplondnjekobonklacmemikcnhklla)
* [30 Seconds of Kotlin](https://github.com/IvanMwiruki/30-seconds-of-kotlin) _(unofficial)_
## Contents
### List
<details>
<summary>View contents</summary>
* [`all_equal`](#all_equal)
* [`all_unique`](#all_unique)
* [`bifurcate`](#bifurcate)
* [`bifurcate_by`](#bifurcate_by)
* [`chunk`](#chunk)
* [`compact`](#compact)
* [`count_by`](#count_by)
* [`count_occurences`](#count_occurences)
* [`deep_flatten`](#deep_flatten)
* [`difference`](#difference)
* [`difference_by`](#difference_by)
* [`every`](#every)
* [`every_nth`](#every_nth)
* [`filter_non_unique`](#filter_non_unique)
* [`group_by`](#group_by)
* [`has_duplicates`](#has_duplicates)
* [`head`](#head)
* [`initial`](#initial)
* [`initialize_2d_list`](#initialize_2d_list)
* [`initialize_list_with_range`](#initialize_list_with_range)
* [`initialize_list_with_values`](#initialize_list_with_values)
* [`intersection`](#intersection)
* [`intersection_by`](#intersection_by)
* [`last`](#last)
* [`longest_item`](#longest_item)
* [`max_n`](#max_n)
* [`min_n`](#min_n)
* [`none`](#none)
* [`offset`](#offset)
* [`sample`](#sample)
* [`shuffle`](#shuffle)
* [`similarity`](#similarity)
* [`some`](#some)
* [`spread`](#spread)
* [`symmetric_difference`](#symmetric_difference)
* [`symmetric_difference_by`](#symmetric_difference_by)
* [`tail`](#tail)
* [`union`](#union)
* [`union_by`](#union_by)
* [`unique_elements`](#unique_elements)
* [`zip`](#zip)
</details>
### Math
<details>
<summary>View contents</summary>
* [`average`](#average)
* [`average_by`](#average_by)
* [`clamp_number`](#clamp_number)
* [`digitize`](#digitize)
* [`factorial`](#factorial)
* [`fibonacci`](#fibonacci)
* [`gcd`](#gcd)
* [`in_range`](#in_range)
* [`is_divisible`](#is_divisible)
* [`is_even`](#is_even)
* [`is_odd`](#is_odd)
* [`lcm`](#lcm-)
* [`max_by`](#max_by)
* [`min_by`](#min_by)
* [`rads_to_degrees`](#rads_to_degrees)
* [`sum_by`](#sum_by)
</details>
### Object
<details>
<summary>View contents</summary>
* [`keys_only`](#keys_only)
* [`map_values`](#map_values)
* [`values_only`](#values_only)
</details>
### String
<details>
<summary>View contents</summary>
* [`byte_size`](#byte_size)
* [`camel`](#camel)
* [`capitalize`](#capitalize)
* [`capitalize_every_word`](#capitalize_every_word)
* [`decapitalize`](#decapitalize)
* [`is_anagram`](#is_anagram)
* [`is_lower_case`](#is_lower_case)
* [`is_upper_case`](#is_upper_case)
* [`kebab`](#kebab)
* [`palindrome`](#palindrome)
* [`snake`](#snake)
* [`split_lines`](#split_lines)
</details>
### Utility
<details>
<summary>View contents</summary>
* [`cast_list`](#cast_list)
</details>
---
## List
### all_equal
Check if all elements in a list are equal.
Use `[1:]` and `[:-1]` to compare all the values in the given list.
```py
def all_equal(lst):
return lst[1:] == lst[:-1]
```
<details>
<summary>Examples</summary>
```py
all_equal([1, 2, 3, 4, 5, 6]) # False
all_equal([1, 1, 1, 1]) # True
```
</details>
<br>[⬆ Back to top](#contents)
### all_unique
Returns `True` if all the values in a flat list are unique, `False` otherwise.
Use `set()` on the given list to remove duplicates, compare its length with the length of the list.
```py
def all_unique(lst):
return len(lst) == len(set(lst))
```
<details>
<summary>Examples</summary>
```py
x = [1,2,3,4,5,6]
y = [1,2,2,3,4,5]
all_unique(x) # True
all_unique(y) # False
```
</details>
<br>[⬆ Back to top](#contents)
### bifurcate
Splits values into two groups.
If an element in `filter` is `True`, the corresponding element in the collection belongs to the first group; otherwise, it belongs to the second group.
Use list comprehension and `enumerate()` to add elements to groups, based on `filter`.
```py
def bifurcate(lst, filter):
return [
[x for i,x in enumerate(lst) if filter[i] == True],
[x for i,x in enumerate(lst) if filter[i] == False]
]
```
<details>
<summary>Examples</summary>
```py
bifurcate(['beep', 'boop', 'foo', 'bar'], [True, True, False, True]) # [ ['beep', 'boop', 'bar'], ['foo'] ]
```
</details>
<br>[⬆ Back to top](#contents)
### bifurcate_by
Splits values into two groups according to a function, which specifies which group an element in the input list belongs to.
If the function returns `True`, the element belongs to the first group; otherwise, it belongs to the second group.
Use list comprehension to add elements to groups, based on `fn`.
```py
def bifurcate_by(lst, fn):
return [
[x for x in lst if fn(x)],
[x for x in lst if not fn(x)]
]
```
<details>
<summary>Examples</summary>
```py
bifurcate_by(['beep', 'boop', 'foo', 'bar'], lambda x: x[0] == 'b') # [ ['beep', 'boop', 'bar'], ['foo'] ]
```
</details>
<br>[⬆ Back to top](#contents)
### chunk
Chunks a list into smaller lists of a specified size.
Use `list()` and `range()` to create a list of the desired `size`.
Use `map()` on the list and fill it with splices of the given list.
Finally, return use created list.
```py
from math import ceil
def chunk(lst, size):
return list(
map(lambda x: lst[x * size:x * size + size],
list(range(0, ceil(len(lst) / size)))))
```
<details>
<summary>Examples</summary>
```py
chunk([1,2,3,4,5],2) # [[1,2],[3,4],5]
```
</details>
<br>[⬆ Back to top](#contents)
### compact
Removes falsey values from a list.
Use `filter()` to filter out falsey values (`False`, `None`, `0`, and `""`).
```py
def compact(lst):
return list(filter(bool, lst))
```
<details>
<summary>Examples</summary>
```py
compact([0, 1, False, 2, '', 3, 'a', 's', 34]) # [ 1, 2, 3, 'a', 's', 34 ]
```
</details>
<br>[⬆ Back to top](#contents)
### count_by
Groups the elements of a list based on the given function and returns the count of elements in each group.
Use `map()` to map the values of the given list using the given function.
Iterate over the map and increase the element count each time it occurs.
```py
def count_by(arr, fn=lambda x: x):
key = {}
for el in map(fn, arr):
key[el] = 0 if el not in key else key[el]
key[el] += 1
return key
```
<details>
<summary>Examples</summary>
```py
from math import floor
count_by([6.1, 4.2, 6.3], floor) # {4: 1, 6: 2}
count_by(['one', 'two', 'three'], len) # {3: 2, 5: 1}
```
</details>
<br>[⬆ Back to top](#contents)
### count_occurences
Counts the occurrences of a value in a list.
Increment a counter for every item in the list that has the given value and is of the same type.
```py
def count_occurrences(lst, val):
return len([x for x in lst if x == val and type(x) == type(val)])
```
<details>
<summary>Examples</summary>
```py
count_occurrences([1, 1, 2, 1, 2, 3], 1) # 3
```
</details>
<br>[⬆ Back to top](#contents)
### deep_flatten
Deep flattens a list.
Use recursion.
Define a function, `spread`, that uses either `list.extend()` or `list.append()` on each element in a list to flatten it.
Use `list.extend()` with an empty list and the `spread` function to flatten a list.
Recursively flatten each element that is a list.
```py
def spread(arg):
ret = []
for i in arg:
if isinstance(i, list):
ret.extend(i)
else:
ret.append(i)
return ret
def deep_flatten(lst):
result = []
result.extend(
spread(list(map(lambda x: deep_flatten(x) if type(x) == list else x, lst))))
return result
```
<details>
<summary>Examples</summary>
```py
deep_flatten([1, [2], [[3], 4], 5]) # [1,2,3,4,5]
```
</details>
<br>[⬆ Back to top](#contents)
### difference
Returns the difference between two iterables.
Create a `set` from `b`, then use list comprehension on `a` to only keep values not contained in the previously created set, `_b`.
```py
def difference(a, b):
_b = set(b)
return [item for item in a if item not in _b]
```
<details>
<summary>Examples</summary>
```py
difference([1, 2, 3], [1, 2, 4]) # [3]
```
</details>
<br>[⬆ Back to top](#contents)
### difference_by
Returns the difference between two lists, after applying the provided function to each list element of both.
Create a `set` by applying `fn` to each element in `b`, then use list comprehension in combination with `fn` on `a` to only keep values not contained in the previously created set, `_b`.
```py
def difference_by(a, b, fn):
_b = set(map(fn, b))
return [item for item in a if fn(item) not in _b]
```
<details>
<summary>Examples</summary>
```py
from math import floor
difference_by([2.1, 1.2], [2.3, 3.4],floor) # [1.2]
difference_by([{ 'x': 2 }, { 'x': 1 }], [{ 'x': 1 }], lambda v : v['x']) # [ { x: 2 } ]
```
</details>
<br>[⬆ Back to top](#contents)
### every
Returns `True` if the provided function returns `True` for every element in the list, `False` otherwise.
Iterate over the elements of the list to test if every element in the list returns `True` based on `fn`.
Omit the seconds argument, `fn`, to check if all elements are `True`.
```py
def every(lst, fn=lambda x: not not x):
for el in lst:
if not fn(el):
return False
return True
```
<details>
<summary>Examples</summary>
```py
every([4, 2, 3], lambda x: x > 1) # True
every([1, 2, 3]) # True
```
</details>
<br>[⬆ Back to top](#contents)
### every_nth
Returns every nth element in a list.
Use `[1::nth]` to create a new list that contains every nth element of the given list.
```py
def every_nth(lst, nth):
return lst[1::nth]
```
<details>
<summary>Examples</summary>
```py
every_nth([1, 2, 3, 4, 5, 6], 2) # [ 2, 4, 6 ]
```
</details>
<br>[⬆ Back to top](#contents)
### filter_non_unique
Filters out the non-unique values in a list.
Use list comprehension and `list.count()` to create a list containing only the unique values.
```py
def filter_non_unique(lst):
return [item for item in lst if lst.count(item) == 1]
```
<details>
<summary>Examples</summary>
```py
filter_non_unique([1, 2, 2, 3, 4, 4, 5]) # [1, 3, 5]
```
</details>
<br>[⬆ Back to top](#contents)
### group_by
Groups the elements of a list based on the given function.
Use `list()` in combination with `map()` and `fn` to map the values of the list to the keys of an object.
Use list comprehension to map each element to the appropriate `key`.
```py
def group_by(lst, fn):
groups = {}
for key in list(map(fn,lst)):
groups[key] = [item for item in lst if fn(item) == key]
return groups
```
<details>
<summary>Examples</summary>
```py
import math
group_by([6.1, 4.2, 6.3], math.floor); # {4: [4.2], 6: [6.1, 6.3]}
group_by(['one', 'two', 'three'], 'length'); # {3: ['one', 'two'], 5: ['three']}
```
</details>
<br>[⬆ Back to top](#contents)
### has_duplicates
Returns `True` if there are duplicate values in a flast list, `False` otherwise.
Use `set()` on the given list to remove duplicates, compare its length with the length of the list.
```py
def has_duplicates(lst):
return len(lst) != len(set(lst))
```
<details>
<summary>Examples</summary>
```py
x = [1,2,3,4,5,5]
y = [1,2,3,4,5]
has_duplicates(x) # True
has_duplicates(y) # False
```
</details>
<br>[⬆ Back to top](#contents)
### head
Returns the head of a list.
use `lst[0]` to return the first element of the passed list.
```py
def head(lst):
return lst[0]
```
<details>
<summary>Examples</summary>
```py
head([1, 2, 3]); # 1
```
</details>
<br>[⬆ Back to top](#contents)
### initial
Returns all the elements of a list except the last one.
Use `lst[0:-1]` to return all but the last element of the list.
```py
def initial(lst):
return lst[0:-1]
```
<details>
<summary>Examples</summary>
```py
initial([1, 2, 3]); # [1,2]
```
</details>
<br>[⬆ Back to top](#contents)
### initialize_2d_list
Initializes a 2D list of given width and height and value.
Use list comprehension and `range()` to generate `h` rows where each is a list with length `h`, initialized with `val`.
If `val` is not provided, default to `None`.
Explain briefly how the snippet works.
```py
def initialize_2d_list(w,h, val = None):
return [[val for x in range(w)] for y in range(h)]
```
<details>
<summary>Examples</summary>
```py
initialize_2d_list(2, 2, 0) # [[0,0], [0,0]]
```
</details>
<br>[⬆ Back to top](#contents)
### initialize_list_with_range
Initializes a list containing the numbers in the specified range where `start` and `end` are inclusive with their common difference `step`.
Use list comprehension and `range()` to generate a list of the appropriate length, filled with the desired values in the given range.
Omit `start` to use the default value of `0`.
Omit `step` to use the default value of `1`.
```py
def initialize_list_with_range(end, start = 0, step = 1):
return [x for x in range(start, end + 1, step)]
```
<details>
<summary>Examples</summary>
```py
initialize_list_with_range(5) # [0, 1, 2, 3, 4, 5]
initialize_list_with_range(7,3) # [3, 4, 5, 6, 7]
initialize_list_with_range(9,0,2) # [0, 2, 4, 6, 8]
```
</details>
<br>[⬆ Back to top](#contents)
### initialize_list_with_values
Initializes and fills a list with the specified value.
Use list comprehension and `range()` to generate a list of length equal to `n`, filled with the desired values.
Omit `val` to use the default value of `0`.
```py
def initialize_list_with_values(n, val = 0):
return [val for x in range(n)]
```
<details>
<summary>Examples</summary>
```py
initialize_list_with_values(5, 2) # [2, 2, 2, 2, 2]
```
</details>
<br>[⬆ Back to top](#contents)
### intersection
Returns a list of elements that exist in both lists.
Create a `set` from `b`, then use list comprehension on `a` to only keep values contained in both lists.
```py
def intersection(a, b):
_b = set(b)
return [item for item in a if item in _b]
```
<details>
<summary>Examples</summary>
```py
intersection([1, 2, 3], [4, 3, 2]) # [2, 3]
```
</details>
<br>[⬆ Back to top](#contents)
### intersection_by
Returns a list of elements that exist in both lists, after applying the provided function to each list element of both.
Create a `set` by applying `fn` to each element in `b`, then use list comprehension in combination with `fn` on `a` to only keep values contained in both lists.
```py
def intersection_by(a, b, fn):
_b = set(map(fn, b))
return [item for item in a if fn(item) in _b]
```
<details>
<summary>Examples</summary>
```py
from math import floor
intersection_by([2.1, 1.2], [2.3, 3.4],floor) # [2.1]
```
</details>
<br>[⬆ Back to top](#contents)
### last
Returns the last element in a list.
use `lst[-1]` to return the last element of the passed list.
```py
def last(lst):
return lst[-1]
```
<details>
<summary>Examples</summary>
```py
last([1, 2, 3]) # 3
```
</details>
<br>[⬆ Back to top](#contents)
### longest_item
Takes any number of iterable objects or objects with a length property and returns the longest one.
If multiple objects have the same length, the first one will be returned.
Use `max()` with `len` as the `key` to return the item with the greatest length.
```py
def longest_item(*args):
return max(args, key = len)
```
<details>
<summary>Examples</summary>
```py
longest_item('this', 'is', 'a', 'testcase') # 'testcase'
longest_item([1, 2, 3], [1, 2], [1, 2, 3, 4, 5]) # [1, 2, 3, 4, 5]
longest_item([1, 2, 3], 'foobar') # 'foobar'
```
</details>
<br>[⬆ Back to top](#contents)
### max_n
Returns the `n` maximum elements from the provided list.
If `n` is greater than or equal to the provided list's length, then return the original list (sorted in descending order).
Use `sorted() to sort the list, `[:n]` to get the specified number of elements.
Omit the second argument, `n`, to get a one-element list.
```py
def max_n(lst, n=1):
return sorted(lst, reverse=True)[:n]
```
<details>
<summary>Examples</summary>
```py
max_n([1, 2, 3]) # [3]
max_n([1, 2, 3], 2) # [3,2]
```
</details>
<br>[⬆ Back to top](#contents)
### min_n
Returns the `n` minimum elements from the provided list.
If `n` is greater than or equal to the provided list's length, then return the original list (sorted in ascending order).
Use `sorted() to sort the list, `[:n]` to get the specified number of elements.
Omit the second argument, `n`, to get a one-element list.
```py
def min_n(lst, n=1):
return sorted(lst, reverse=False)[:n]
```
<details>
<summary>Examples</summary>
```py
min_n([1, 2, 3]) # [1]
min_n([1, 2, 3], 2) # [1,2]
```
</details>
<br>[⬆ Back to top](#contents)
### none
Returns `False` if the provided function returns `True` for at least one element in the list, `True` otherwise.
Iterate over the elements of the list to test if every element in the list returns `False` based on `fn`.
Omit the seconds argument, `fn`, to check if all elements are `False`.
```py
def none(lst, fn=lambda x: not not x):
for el in lst:
if fn(el):
return False
return True
```
<details>
<summary>Examples</summary>
```py
none([0, 1, 2, 0], lambda x: x >= 2 ) # False
none([0, 0, 0]) # True
```
</details>
<br>[⬆ Back to top](#contents)
### offset
Moves the specified amount of elements to the end of the list.
Use `lst[offset:]` and `lst[:offset]` to get the two slices of the list and combine them before returning.
Explain briefly how the snippet works.
```py
def offset(lst, offset):
return lst[offset:] + lst[:offset]
```
<details>
<summary>Examples</summary>
```py
offset([1, 2, 3, 4, 5], 2) # [3, 4, 5, 1, 2]
offset([1, 2, 3, 4, 5], -2) # [4, 5, 1, 2, 3]
```
</details>
<br>[⬆ Back to top](#contents)
### sample
Returns a random element from an array.
Use `randint()` to generate a random number that corresponds to an index in the list, return the element at that index.
```py
from random import randint
def sample(lst):
return lst[randint(0, len(lst) - 1)]
```
<details>
<summary>Examples</summary>
```py
sample([3, 7, 9, 11]) # 9
```
</details>
<br>[⬆ Back to top](#contents)
### shuffle
Randomizes the order of the values of an list, returning a new list.
Uses the [Fisher-Yates algorithm](https://en.wikipedia.org/wiki/Fisher%E2%80%93Yates_shuffle) to reorder the elements of the list.
```py
from copy import deepcopy
from random import randint
def shuffle(lst):
temp_lst = deepcopy(lst)
m = len(temp_lst)
while (m):
m -= 1
i = randint(0, m)
temp_lst[m], temp_lst[i] = temp_lst[i], temp_lst[m]
return temp_lst
```
<details>
<summary>Examples</summary>
```py
foo = [1,2,3]
shuffle(foo) # [2,3,1] , foo = [1,2,3]
```
</details>
<br>[⬆ Back to top](#contents)
### similarity
Returns a list of elements that exist in both lists.
Use list comprehension on `a` to only keep values contained in both lists.
```py
def similarity(a, b):
return [item for item in a if item in b]
```
<details>
<summary>Examples</summary>
```py
similarity([1, 2, 3], [1, 2, 4]) # [1, 2]
```
</details>
<br>[⬆ Back to top](#contents)
### some
Returns `True` if the provided function returns `True` for at least one element in the list, `False` otherwise.
Iterate over the elements of the list to test if every element in the list returns `True` based on `fn`.
Omit the seconds argument, `fn`, to check if all elements are `True`.
```py
def some(lst, fn=lambda x: not not x):
for el in lst:
if fn(el):
return True
return False
```
<details>
<summary>Examples</summary>
```py
some([0, 1, 2, 0], lambda x: x >= 2 ) # True
some([0, 0, 1, 0]) # True
```
</details>
<br>[⬆ Back to top](#contents)
### spread
Flattens a list, by spreading its elements into a new list.
Loop over elements, use `list.extend()` if the element is a list, `list.append()` otherwise.
```py
def spread(arg):
ret = []
for i in arg:
if isinstance(i, list):
ret.extend(i)
else:
ret.append(i)
return ret
```
<details>
<summary>Examples</summary>
```py
spread([1,2,3,[4,5,6],[7],8,9]) # [1,2,3,4,5,6,7,8,9]
```
</details>
<br>[⬆ Back to top](#contents)
### symmetric_difference
Returns the symmetric difference between two iterables, without filtering out duplicate values.
Create a `set` from each list, then use list comprehension on each one to only keep values not contained in the previously created set of the other.
```py
def symmetric_difference(a, b):
_a, _b = set(a), set(b)
return [item for item in a if item not in _b] + [item for item in b if item not in _a]
```
<details>
<summary>Examples</summary>
```py
symmetric_difference([1, 2, 3], [1, 2, 4]) # [3, 4]
```
</details>
<br>[⬆ Back to top](#contents)
### symmetric_difference_by
Returns the symmetric difference between two lists, after applying the provided function to each list element of both.
Create a `set` by applying `fn` to each element in every list, then use list comprehension in combination with `fn` on each one to only keep values not contained in the previously created set of the other.
```py
def symmetric_difference_by(a, b, fn):
_a, _b = set(map(fn, a)), set(map(fn, b))
return [item for item in a if fn(item) not in _b] + [item for item in b if fn(item) not in _a]
```
<details>
<summary>Examples</summary>
```py
from math import floor
symmetric_difference_by([2.1, 1.2], [2.3, 3.4],floor) # [1.2, 3.4]
```
</details>
<br>[⬆ Back to top](#contents)
### tail
Returns all elements in a list except for the first one.
Return `lst[1:]` if the list's length is more than `1`, otherwise, return the whole list.
```py
def tail(lst):
return lst[1:] if len(lst) > 1 else lst
```
<details>
<summary>Examples</summary>
```py
tail([1, 2, 3]); # [2,3]
tail([1]); # [1]
```
</details>
<br>[⬆ Back to top](#contents)
### union
Returns every element that exists in any of the two lists once.
Create a `set` with all values of `a` and `b` and convert to a `list`.
```py
def union(a,b):
return list(set(a + b))
```
<details>
<summary>Examples</summary>
```py
union([1, 2, 3], [4, 3, 2]) # [1,2,3,4]
```
</details>
<br>[⬆ Back to top](#contents)
### union_by
Returns every element that exists in any of the two lists once, after applying the provided function to each element of both.
Create a `set` by applying `fn` to each element in `a`, then use list comprehension in combination with `fn` on `b` to only keep values not contained in the previously created set, `_a`.
Finally, create a `set` from the previous result and `a` and transform it into a `list`
```py
def union_by(a,b,fn):
_a = set(map(fn, a))
return list(set(a + [item for item in b if fn(item) not in _a]))
```
<details>
<summary>Examples</summary>
```py
from math import floor
union_by([2.1], [1.2, 2.3], floor) # [2.1, 1.2]
```
</details>
<br>[⬆ Back to top](#contents)
### unique_elements
Returns the unique elements in a given list.
Create a `set` from the list to discard duplicated values, then return a `list` from it.
```py
def unique_elements(li):
return list(set(li))
```
<details>
<summary>Examples</summary>
```py
unique_elements([1, 2, 2, 3, 4, 3]) # [1, 2, 3, 4]
```
</details>
<br>[⬆ Back to top](#contents)
### zip
Creates a list of elements, grouped based on the position in the original lists.
Use `max` combined with `list comprehension` to get the length of the longest list in the arguments.
Loop for `max_length` times grouping elements.
If lengths of `lists` vary, use `fill_value` (defaults to `None`).
```py
def zip(*args, fillvalue=None):
max_length = max([len(lst) for lst in args])
result = []
for i in range(max_length):
result.append([
args[k][i] if i < len(args[k]) else fillvalue for k in range(len(args))
])
return result
```
<details>
<summary>Examples</summary>
```py
zip(['a', 'b'], [1, 2], [True, False]) # [['a', 1, True], ['b', 2, False]]
zip(['a'], [1, 2], [True, False]) # [['a', 1, True], [None, 2, False]]
zip(['a'], [1, 2], [True, False], fill_value = '_') # [['a', 1, True], ['_', 2, False]]
```
</details>
<br>[⬆ Back to top](#contents)
---
## Math
### average
Returns the average of two or more numbers.
Use `sum()` to sum all of the `args` provided, divide by `len(args)`.
```py
def average(*args):
return sum(args, 0.0) / len(args)
```
<details>
<summary>Examples</summary>
```py
average(*[1, 2, 3]) # 2.0
average(1, 2, 3) # 2.0
```
</details>
<br>[⬆ Back to top](#contents)
### average_by
Returns the average of a list, after mapping each element to a value using the provided function.
Use `map()` to map each element to the value returned by `fn`.
Use `sum()` to sum all of the mapped values, divide by `len(lst)`.
```py
def average_by(lst, fn=lambda x: x):
return sum(map(fn, lst), 0.0) / len(lst)
```
<details>
<summary>Examples</summary>
```py
average_by([{ 'n': 4 }, { 'n': 2 }, { 'n': 8 }, { 'n': 6 }], lambda x: x['n']) # 5.0
```
</details>
<br>[⬆ Back to top](#contents)
### clamp_number
Clamps `num` within the inclusive range specified by the boundary values `a` and `b`.
If `num` falls within the range, return `num`.
Otherwise, return the nearest number in the range.
```py
def clamp_number(num,a,b):
return max(min(num, max(a,b)),min(a,b))
```
<details>
<summary>Examples</summary>
```py
clamp_number(2, 3, 5) # 3
clamp_number(1, -1, -5) # -1
```
</details>
<br>[⬆ Back to top](#contents)
### digitize
Converts a number to an array of digits.
Use `map()` combined with `int` on the string representation of `n` and return a list from the result.
```py
def digitize(n):
return list(map(int, str(n)))
```
<details>
<summary>Examples</summary>
```py
digitize(123) # [1, 2, 3]
```
</details>
<br>[⬆ Back to top](#contents)
### factorial
Calculates the factorial of a number.
Use recursion.
If `num` is less than or equal to `1`, return `1`.
Otherwise, return the product of `num` and the factorial of `num - 1`.
Throws an exception if `num` is a negative or a floating point number.
```py
def factorial(num):
if not ((num >= 0) & (num % 1 == 0)):
raise Exception(
f"Number( {num} ) can't be floating point or negative ")
return 1 if num == 0 else num * factorial(num - 1)
```
<details>
<summary>Examples</summary>
```py
factorial(6) # 720
```
</details>
<br>[⬆ Back to top](#contents)
### fibonacci
Generates an array, containing the Fibonacci sequence, up until the nth term.
Starting with `0` and `1`, use `list.apoend() to add the sum of the last two numbers of the list to the end of the list, until the length of the list reaches `n`.
If `n` is less or equal to `0`, return a list containing `0`.
```py
def fibonacci(n):
if n <= 0:
return [0]
sequence = [0, 1]
while len(sequence) <= n:
next_value = sequence[len(sequence) - 1] + sequence[len(sequence) - 2]
sequence.append(next_value)
return sequence
```
<details>
<summary>Examples</summary>
```py
fibonacci(7) # [0, 1, 1, 2, 3, 5, 8, 13]
```
</details>
<br>[⬆ Back to top](#contents)
### gcd
Calculates the greatest common divisor of a list of numbers.
Use `reduce()` and `math.gcd` over the given list.
```py
from functools import reduce
import math
def gcd(numbers):
return reduce(math.gcd, numbers)
```
<details>
<summary>Examples</summary>
```py
gcd([8,36,28]) # 4
```
</details>
<br>[⬆ Back to top](#contents)
### in_range
Checks if the given number falls within the given range.
Use arithmetic comparison to check if the given number is in the specified range.
If the second parameter, `end`, is not specified, the range is considered to be from `0` to `start`.
```py
def in_range(n, start, end = 0):
if (start > end):
end, start = start, end
return start <= n <= end
```
<details>
<summary>Examples</summary>
```py
in_range(3, 2, 5); # True
in_range(3, 4); # True
in_range(2, 3, 5); # False
in_range(3, 2); # False
```
</details>
<br>[⬆ Back to top](#contents)
### is_divisible
Checks if the first numeric argument is divisible by the second one.
Use the modulo operator (`%`) to check if the remainder is equal to `0`.
```py
def is_divisible(dividend, divisor):
return dividend % divisor == 0
```
<details>
<summary>Examples</summary>
```py
is_divisible(6, 3) # True
```
</details>
<br>[⬆ Back to top](#contents)
### is_even
Returns `True` if the given number is even, `False` otherwise.
Checks whether a number is odd or even using the modulo (`%`) operator.
Returns `True` if the number is even, `False` if the number is odd.
```py
def is_even(num):
return num % 2 == 0
```
<details>
<summary>Examples</summary>
```py
is_even(3) # False
```
</details>
<br>[⬆ Back to top](#contents)
### is_odd
Returns `True` if the given number is odd, `False` otherwise.
Checks whether a number is even or odd using the modulo (`%`) operator.
Returns `True` if the number is odd, `False` if the number is even.
```py
def is_odd(num):
return num % 2 == `0`
```
<details>
<summary>Examples</summary>
```py
is_odd(3) # True
```
</details>
<br>[⬆ Back to top](#contents)
### lcm ![advanced](/advanced.svg)
Returns the least common multiple of two or more numbers.
Define a function, `spread`, that uses either `list.extend()` or `list.append()` on each element in a list to flatten it.
Use `math.gcd()` and `lcm(x,y) = x * y / gcd(x,y)` to determine the least common multiple.
```py
from functools import reduce
import math
def spread(arg):
ret = []
for i in arg:
if isinstance(i, list):
ret.extend(i)
else:
ret.append(i)
return ret
def lcm(*args):
numbers = []
numbers.extend(spread(list(args)))
def _lcm(x, y):
return int(x * y / math.gcd(x, y))
return reduce((lambda x, y: _lcm(x, y)), numbers)
```
<details>
<summary>Examples</summary>
```py
lcm(12, 7) # 84
lcm([1, 3, 4], 5) # 60
```
</details>
<br>[⬆ Back to top](#contents)
### max_by
Returns the maximum value of a list, after mapping each element to a value using the provided function.
Use `map()` with `fn` to map each element to a value using the provided function, convert to a `list` and use `max()` to return the maximum value.
```py
def max_by(lst, fn):
return max(list(map(fn,lst)))
```
<details>
<summary>Examples</summary>
```py
max_by([{ 'n': 4 }, { 'n': 2 }, { 'n': 8 }, { 'n': 6 }], lambda v : v['n']) # 8
```
</details>
<br>[⬆ Back to top](#contents)
### min_by
Returns the minimum value of a list, after mapping each element to a value using the provided function.
Use `map()` with `fn` to map each element to a value using the provided function, convert to a `list` and use `min()` to return the minimum value.
```py
def min_by(lst, fn):
return min(list(map(fn,lst)))
```
<details>
<summary>Examples</summary>
```py
min_by([{ 'n': 4 }, { 'n': 2 }, { 'n': 8 }, { 'n': 6 }], lambda v : v['n']) # 2
```
</details>
<br>[⬆ Back to top](#contents)
### rads_to_degrees
Converts an angle from radians to degrees.
Use `math.pi` and the radian to degree formula to convert the angle from radians to degrees.
```py
import math
def rads_to_degrees(rad):
return (rad * 180.0) / math.pi
```
<details>
<summary>Examples</summary>
```py
import math
rads_to_degrees(math.pi / 2) # 90.0
```
</details>
<br>[⬆ Back to top](#contents)
### sum_by
Returns the sum of a list, after mapping each element to a value using the provided function.
Use `map()` with `fn` to map each element to a value using the provided function, convert to a `list` and use `sum()` to return the sum of the values.
```py
def sum_by(lst, fn):
return sum(list(map(fn,lst)))
```
<details>
<summary>Examples</summary>
```py
sum_by([{ 'n': 4 }, { 'n': 2 }, { 'n': 8 }, { 'n': 6 }], lambda v : v['n']) # 20
```
</details>
<br>[⬆ Back to top](#contents)
---
## Object
### keys_only
Returns a flat list of all the keys in a flat dictionary.
Use `dict.keys()` to return the keys in the given dictionary.
Return a `list()` of the previous result.
```py
def keys_only(flat_dict):
return list(flat_dict.keys())
```
<details>
<summary>Examples</summary>
```py
ages = {
"Peter": 10,
"Isabel": 11,
"Anna": 9,
}
keys_only(ages) # ['Peter', 'Isabel', 'Anna']
```
</details>
<br>[⬆ Back to top](#contents)
### map_values
Creates an object with the same keys as the provided object and values generated by running the provided function for each value.
Use `dict.keys()` to iterate over the object's keys, assigning the values produced by `fn` to each key of a new object.
```py
def map_values(obj, fn):
ret = {}
for key in obj.keys():
ret[key] = fn(obj[key])
return ret
```
<details>
<summary>Examples</summary>
```py
users = {
'fred': { 'user': 'fred', 'age': 40 },
'pebbles': { 'user': 'pebbles', 'age': 1 }
}
map_values(users, lambda u : u['age']) # {'fred': 40, 'pebbles': 1}
```
</details>
<br>[⬆ Back to top](#contents)
### values_only
Returns a flat list of all the values in a flat dictionary.
Use `dict.values()` to return the values in the given dictionary.
Return a `list()` of the previous result.
```py
def values_only(dict):
return list(flat_dict.values())
```
<details>
<summary>Examples</summary>
```py
ages = {
"Peter": 10,
"Isabel": 11,
"Anna": 9,
}
values_only(ages) # [10, 11, 9]
```
</details>
<br>[⬆ Back to top](#contents)
---
## String
### byte_size
Returns the length of a string in bytes.
Use `string.encode('utf-8')` to encode the given string and return its length.
```py
def byte_size(string):
return len(string.encode('utf-8'))
```
<details>
<summary>Examples</summary>
```py
byte_size('😀') # 4
byte_size('Hello World') # 11
```
</details>
<br>[⬆ Back to top](#contents)
### camel
Converts a string to camelcase.
Break the string into words and combine them capitalizing the first letter of each word, using a regexp.
```py
import re
def camel(str):
s = re.sub(r"(\s|_|-)+","",
re.sub(r"[A-Z]{2,}(?=[A-Z][a-z]+[0-9]*|\b)|[A-Z]?[a-z]+[0-9]*|[A-Z]|[0-9]+",
lambda mo: mo.group(0)[0].upper() + mo.group(0)[1:].lower(),str)
)
return s[0].lower() + s[1:]
```
<details>
<summary>Examples</summary>
```py
camel('some_database_field_name'); # 'someDatabaseFieldName'
camel('Some label that needs to be camelized'); # 'someLabelThatNeedsToBeCamelized'
camel('some-javascript-property'); # 'someJavascriptProperty'
camel('some-mixed_string with spaces_underscores-and-hyphens'); # 'someMixedStringWithSpacesUnderscoresAndHyphens'
```
</details>
<br>[⬆ Back to top](#contents)
### capitalize
Capitalizes the first letter of a string.
Capitalize the first letter of the string and then add it with rest of the string.
Omit the `lower_rest` parameter to keep the rest of the string intact, or set it to `True` to convert to lowercase.
```py
def capitalize(string, lower_rest=False):
return string[:1].upper() + (string[1:].lower() if lower_rest else string[1:])
```
<details>
<summary>Examples</summary>
```py
capitalize('fooBar') # 'FooBar'
capitalize('fooBar', True) # 'Foobar'
```
</details>
<br>[⬆ Back to top](#contents)
### capitalize_every_word
Capitalizes the first letter of every word in a string.
Use `string.title()` to capitalize first letter of every word in the string.
```py
def capitalize_every_word(string):
return string.title()
```
<details>
<summary>Examples</summary>
```py
capitalize_every_word('hello world!') # 'Hello World!'
```
</details>
<br>[⬆ Back to top](#contents)
### decapitalize
Decapitalizes the first letter of a string.
Decapitalize the first letter of the string and then add it with rest of the string.
Omit the `upper_rest` parameter to keep the rest of the string intact, or set it to `True` to convert to uppercase.
```py
def decapitalize(string, upper_rest=False):
return str[:1].lower() + (str[1:].upper() if upper_rest else str[1:])
```
<details>
<summary>Examples</summary>
```py
decapitalize('FooBar') # 'fooBar'
decapitalize('FooBar', True) # 'fOOBAR'
```
</details>
<br>[⬆ Back to top](#contents)
### is_anagram
Checks if a string is an anagram of another string (case-insensitive, ignores spaces, punctuation and special characters).
Use `str.replace()` to remove spaces from both strings.
Compare the lengths of the two strings, return `False` if they are not equal.
Use `sorted()` on both strings and compare the results.
```py
def is_anagram(str1, str2):
_str1, _str2 = str1.replace(" ", ""), str2.replace(" ", "")
if len(_str1) != len(_str2):
return False
else:
return sorted(_str1.lower()) == sorted(_str2.lower())
```
<details>
<summary>Examples</summary>
```py
is_anagram("anagram", "Nag a ram") # True
```
</details>
<br>[⬆ Back to top](#contents)
### is_lower_case
Checks if a string is lower case.
Convert the given string to lower case, using `str.lower()` and compare it to the original.
```py
def is_lower_case(string):
return string == string.lower()
```
<details>
<summary>Examples</summary>
```py
is_lower_case('abc') # True
is_lower_case('a3@$') # True
is_lower_case('Ab4') # False
```
</details>
<br>[⬆ Back to top](#contents)
### is_upper_case
Checks if a string is upper case.
Convert the given string to upper case, using `str.upper()` and compare it to the original.
```py
def is_upper_case(string):
return string == string.upper()
```
<details>
<summary>Examples</summary>
```py
is_upper_case('ABC') # True
is_upper_case('a3@$') # False
is_upper_case('aB4') # False
```
</details>
<br>[⬆ Back to top](#contents)
### kebab
Converts a string to kebab case.
Break the string into words and combine them adding `-` as a separator, using a regexp.
```py
import re
def kebab(str):
return re.sub(r"(\s|_|-)+","-",
re.sub(r"[A-Z]{2,}(?=[A-Z][a-z]+[0-9]*|\b)|[A-Z]?[a-z]+[0-9]*|[A-Z]|[0-9]+",
lambda mo: mo.group(0).lower(),str)
)
```
<details>
<summary>Examples</summary>
```py
kebab('camelCase'); # 'camel-case'
kebab('some text'); # 'some-text'
kebab('some-mixed_string With spaces_underscores-and-hyphens'); # 'some-mixed-string-with-spaces-underscores-and-hyphens'
kebab('AllThe-small Things'); # "all-the-small-things"
```
</details>
<br>[⬆ Back to top](#contents)
### palindrome
Returns `True` if the given string is a palindrome, `False` otherwise.
Use `str.lower()` and `re.sub()` to convert to lowercase and remove non-alphanumeric characters from the given string.
Then, compare the new string with its reverse.
```py
from re import sub
def palindrome(string):
s = sub('[\W_]', '', string.lower())
return s == s[::-1]
```
<details>
<summary>Examples</summary>
```py
palindrome('taco cat') # True
```
</details>
<br>[⬆ Back to top](#contents)
### snake
Converts a string to snake case.
Break the string into words and combine them adding `_-_` as a separator, using a regexp.
```py
import re
def snake(str):
return re.sub(r"(\s|_|-)+","-",
re.sub(r"[A-Z]{2,}(?=[A-Z][a-z]+[0-9]*|\b)|[A-Z]?[a-z]+[0-9]*|[A-Z]|[0-9]+",
lambda mo: mo.group(0).lower(),str)
)
```
<details>
<summary>Examples</summary>
```py
snake('camelCase'); # 'camel_case'
snake('some text'); # 'some_text'
snake('some-mixed_string With spaces_underscores-and-hyphens'); # 'some_mixed_string_with_spaces_underscores_and_hyphens'
snake('AllThe-small Things'); # "all_the_smal_things"
```
</details>
<br>[⬆ Back to top](#contents)
### split_lines
Splits a multiline string into a list of lines.
Use `str.split()` and `'\n'` to match line breaks and create a list.
```py
def split_lines(str):
str.split('\n')
```
<details>
<summary>Examples</summary>
```py
split_lines('This\nis a\nmultiline\nstring.\n') # 'This\nis a\nmultiline\nstring.\n'
```
</details>
<br>[⬆ Back to top](#contents)
---
## Utility
### cast_list
Casts the provided value as an array if it's not one.
Use `isinstance()` to check if the given value is a list and return it as-is or encapsulated in a list accordingly.
```py
def cast_list(val):
return val if isinstance(val, list) else [val]
```
<details>
<summary>Examples</summary>
```py
cast_list('foo'); # ['foo']
cast_list([1]); # [1]
```
</details>
<br>[⬆ Back to top](#contents)
## Collaborators
| [<img src="https://github.com/Chalarangelo.png" width="100px;"/>](https://github.com/Chalarangelo)<br/> [<sub>Angelos Chalaris</sub>](https://github.com/Chalarangelo) | [<img src="https://github.com/fejes713.png" width="100px;"/>](https://github.com/fejes713)<br/> [<sub>Stefan Feješ</sub>](https://github.com/fejes713) | [<img src="https://github.com/kriadmin.png" width="100px;"/>](https://github.com/kriadmin)<br/> [<sub>Rohit Tanwar</sub>](https://github.com/kriadmin) |
| --- | --- | --- |
## Credits
*This README is built using [markdown-builder](https://github.com/30-seconds/markdown-builder).*
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