Python Codes

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Sorts one list based on another list containing the desired indexes. Use zip() and sorted() to combine and sort the two lists, based on the values of indexes. Use a list comprehension to get the first element of each pair from the result. Use the reverse parameter in sorted() to sort the dictionary in reverse order, based on the third argument. CODE: def sort_by_indexes(lst, indexes, reverse=False): return [val for (_, val) in sorted(zip(indexes, lst), key=lambda x: \ x[0], reverse=reverse)] Example: a = ['eggs', 'bread', 'oranges', 'jam', 'apples', 'milk'] b = [3, 2, 6, 4, 1, 5] sort_by_indexes(a, b) Output: ['apples', 'bread', 'eggs', 'jam', 'milk', 'oranges'] sort_by_indexes(a, b, True) Output: ['oranges', 'milk', 'jam', 'eggs', 'bread', 'apples'] Share and Support @Python_Codes

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Converts a string to kebab case. 👉Use re.sub() to replace any - or _ with a space, using the regexp r"(_|-)+". 👉Use re.sub() to match all words in the string, str.lower() to lowercase them. 👉Finally, use str.join() to combine all word using - as the separator. CODE: from re import sub def kebab(s): return '-'.join( sub(r"(\s|_|-)+"," ", 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(), s)).split()) Examples 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' Share and Support @Python_Codes

bifurcate_by Splits values into two groups, based on the result of the given filtering function. 👉Use a list comprehension to add elements to groups, based on the value returned by fn for each element. 👉If fn returns a truthy value for any element, add it to the first group, otherwise add it to the second group. CODE: def bifurcate_by(lst, fn): return [ [x for x in lst if fn(x)], [x for x in lst if not fn(x)] ] Examples Input: bifurcate_by(['beep', 'boop', 'foo', 'bar'], lambda x: x[0] == 'b') Output: [ ['beep', 'boop', 'bar'], ['foo'] ] Share and Support @Python_Codes

This is How Python Code Executed @Python_Codes

What are named tuples in Python? These are part of the collections module and act very similar to regular tuples The main difference being that values stored in a named tuple can be accessed using field names instead of indexes. For example, a point in the two-dimensional plane can be represented using two coordinates. In a regular tuple, these values would be accessed by index ([0] and [1]), but if we define a named tuple, Point, we can access them using x and y instead (although we can still use indexes, too, if we want): Example: from collections import namedtuple # Regular tuple p = (2, 4) # p[0] = 2, p[1] = 4 # Named tuple Point = namedtuple('Point', 'x y') q = Point(3, 5) # q.x = 3, q.y = 5 Example 2: from collections import namedtuple Point = namedtuple('Point', ['x', 'y', 'z'], defaults = [1]); a = Point(1, 1, 0); # a.x = 1, a.y = 1, a.z = 0 # Default value used for `z` b = Point(2, 2); # b.x = 2, b.y = 2, b.z = 1 (default) Share and Support @Python_Codes

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merge Python, List

Merges two or more lists into a list of lists, combining elements from each of the input lists based on their positions.

.👉🏻 Use max() combined with a list comprehension to get the length of the longest list in the arguments. .👉🏻 Use range() in combination with the max_length variable to loop as many times as there are elements in the longest list. .👉🏻If a list is shorter than max_length, use fill_value for the remaining items (defaults to None). .👉🏻zip() and itertools.zip_longest() provide similar functionality to this snippet. Code:

def merge(*args, fill_value = 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 fill_value for k in range(len(args))
    ])
  return result

Example: merge(['a', 'b'], [1, 2], [True, False]) Output: [['a', 1, True], ['b', 2, False]] Share and Support @Python_Codes

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What are named tuples in Python? Python's named tuples are a very simple yet interesting feature that can make a developer's life easier. They are part of the collections module and act very similar to regular tuples, the main difference being that values stored in a named tuple can be accessed using field names instead of indexes. For example, a point in the two-dimensional plane can be represented using two coordinates. In a regular tuple, these values would be accessed by index ([0] and [1]), but if we define a named tuple, Point, we can access them using x and y instead (although we can still use indexes, too, if we want): Example: from collections import namedtuple # Regular tuple p = (2, 4) # p[0] = 2, p[1] = 4 # Named tuple Point = namedtuple('Point', 'x y') q = Point(3, 5) # q.x = 3, q.y = 5 Apart from the increased readability of your code, named tuples provide a few other quality of life improvements. First and foremost, they allow for default values to be specified via the defaults iterable argument. Secondly, they have the ability to automatically rename duplicate or invalid fields via the rename boolean argument. And, finally, they even provide a convenient option to specify field names as a list or comma/space-separated string. from collections import namedtuple Point = namedtuple('Point', ['x', 'y', 'z'], defaults = [1]); a = Point(1, 1, 0); # a.x = 1, a.y = 1, a.z = 0 # Default value used for z b = Point(2, 2); # b.x = 2, b.y = 2, b.z = 1 (default) Where's the catch? you might ask. Well, it seems like there's none! The obvious parallel to dictionaries in terms of syntax doesn't seem to go any further, as named tuple instances do not have per-instance dictionaries, meaning they require as much memory as regular tuples. Share and Support @Python_Codes