Merge branch 'master' into syntax-and-numerical-operators

CHANGELOG.md

@@ -63,6 +63,17 @@ Types of change:
 - [Html - Link Relative Paths - Change part of PQ as it wasn't worder properly](https://github.com/enkidevs/curriculum/pull/2985)
 - [Python - Format Text Paragraphs With Textwrap - Make the fill method more clear](https://github.com/enkidevs/curriculum/pull/2981)
 - [Python - Syntax And Numerical Operators - Move single-line commands to a single line, update indentation in codeblocks from 4 to 2 spaces](https://github.com/enkidevs/curriculum/pull/3014)
+- [Python - Testing - Move single-line commands to a single line, update indentation in codeblocks from 4 to 2 spaces](https://github.com/enkidevs/curriculum/pull/3015)
+- [Python - Unordered Data Types - Move single-line commands to a single line, update indentation in codeblocks from 4 to 2 spaces](https://github.com/enkidevs/curriculum/pull/3016)
+- [Python - Utilities I - Move single-line commands to a single line, update indentation in codeblocks from 4 to 2 spaces](https://github.com/enkidevs/curriculum/pull/3017)
+- [Python - Utilities II - Move single-line commands to a single line, update indentation in codeblocks from 4 to 2 spaces](https://github.com/enkidevs/curriculum/pull/3018)
+- [Python - Working With Strings - Move single-line commands to a single line, update indentation in codeblocks from 4 to 2 spaces](https://github.com/enkidevs/curriculum/pull/3019)
+- [Python - Arrays I - Move single-line commands to a single line, update indentation in codeblocks from 4 to 2 spaces](https://github.com/enkidevs/curriculum/pull/3020)
+- [Python - Arrays II - Move single-line commands to a single line, update indentation in codeblocks from 4 to 2 spaces](https://github.com/enkidevs/curriculum/pull/3021)
+- [Python - Comprehension - Move single-line commands to a single line, update indentation in codeblocks from 4 to 2 spaces](https://github.com/enkidevs/curriculum/pull/3022)
+- [Python - Functional Programming - Move single-line commands to a single line, update indentation in codeblocks from 4 to 2 spaces](https://github.com/enkidevs/curriculum/pull/3024)
+- [Python - Generators - Move single-line commands to a single line, update indentation in codeblocks from 4 to 2 spaces](https://github.com/enkidevs/curriculum/pull/3026)
+- [Python - Python Immutability - Move single-line commands to a single line, update indentation in codeblocks from 4 to 2 spaces](https://github.com/enkidevs/curriculum/pull/3028)
 - [Python - Iterators - Move single-line commands to a single line, update indentation in codeblocks from 4 to 2 spaces](https://github.com/enkidevs/curriculum/pull/3027)
 
 ## January 4th 2022

python/functional-programming/arrays-i/the-reversed-built-in-function.md

@@ -31,15 +31,15 @@ The `reversed` built-in allows us to create an iterator for an iterable sequence
 reversed(seq)
 ```
 
-Where `seq` is an iterable sequence such as a tuple, list, string or range. This returns an iterator which accesses the elements in the sequence in the reverse order. For example, we may use `reversed` to reverse the order of characters in a string.
+Where `seq` is an iterable sequence such as a tuple, list, string, or range. This returns an iterator, which accesses the elements in the sequence in the reverse order. For example, we may use `reversed` to reverse the order of characters in a string.
 
 ```python
 ourString = 'enki'
 print(list(reversed(ourString)))
 # Result: ['i', 'k', 'n', 'e']
 ```
 
-Notice how we could create custom classes that implement the `__reversed__()` method and then use `reversed` on them to quickly and efficiently reverse their ordering. In this way we can begin to see how often the `reversed` function might be useful in day-to-day programming tasks.
+Notice how we could create custom classes that implement the `__reversed__()` method and then use `reversed` on them to quickly and efficiently reverse their ordering. In this way, we can begin to see how often the `reversed` function might be useful in day-to-day programming tasks.
 
 
 ---

python/functional-programming/arrays-i/the-slice-built-in-function.md

@@ -105,8 +105,7 @@ print(ourString[sObject])
 Use `slice` to remove every second number in the list of numbers.
 
 ```python
-nList = ['1', '2', '3', '4', '5',
-         '6', '7', '8']
+nList = ['1', '2', '3', '4', '5', '6', '7', '8']
 
 sObject = ???(???, ???, ???)
 print(nList[sObject])

python/functional-programming/arrays-i/the-zip-built-in-function.md

@@ -105,18 +105,9 @@ We have three lists, `fnames`, `lnames`, `locations`, which are ordered so that
 Fill in the gaps in the code below to achieve this.
 
 ```python
-locations = ['IT',
-             'FR',
-             'FR',
-             'RU']
-fnames = ['italo',
-          'jean',
-          'emily',
-          'katya']
-lnames = ['calvino',
-          'micheal',
-          'rambert',
-          'sokolov']
+locations = ['IT', 'FR', 'FR', 'RU']
+fnames = ['italo', 'jean', 'emily', 'katya']
+lnames = ['calvino', 'micheal', 'rambert', 'sokolov']
 
 result = zip(???, ???)
 result2 = zip(???, ???)

python/functional-programming/arrays-ii/the-map-built-in-function.md

@@ -29,7 +29,7 @@ revisionQuestion:
 
 ## Content
 
-The `map` function is built in to the Python language. Together with the other built-in functions `filter` and `reduce`, `map` allows us to take a functional approach to programming in Python.
+The `map` function is built into the Python language. Together with the other built-in functions `filter` and `reduce`, `map` allows us to take a functional approach to programming in Python.
 
 `map` applies a given function—`function_here` in the case below—iteratively to all items in a given `input_list`[1]. The basic syntax looks like this:
 
@@ -68,8 +68,7 @@ Finally, it's good to know that we can pass more than one iterable `input_list`
 Let's say we have a list, called `promises`. We want to `make_good` on all our promises, where `make_good` is a previously-defined function that takes a string. Fill in the blanks in the code below to apply `make_good` to all elements in `promises`.  
 
 ```python
-promises = ['learn css', 'learn js',
-  'buy milk', 'be excellent to each other']
+promises = ['learn css', 'learn js', 'buy milk', 'be excellent to each other']
 promises = ???(???, ???)
 ```
 

python/functional-programming/arrays-ii/the-sorted-built-in-function.md

@@ -105,8 +105,7 @@ print(sorted([4, 0, 2, 3, 1, 5]))
 What is the result of the execution of the following code snippet?
 
 ```python
-print(sorted([0, 2, 3, 1,
-'a', 'b', 'A', 'B']))
+print(sorted([0, 2, 3, 1, 'a', 'b', 'A', 'B']))
 ```
 
 ???

python/functional-programming/comprehension/dictionary-comprehension.md

@@ -34,11 +34,11 @@ cube_dict = {x: x ** 3 for x in num_list}
 
 ```
 
-Now if we print cube_dict, we get:
+Now, if we print `cube_dict`, we get:
 
 ```python
 for k, v in cube_dict.items():
-    print(k, v)
+  print(k, v)
 # output
 # 1 1
 # 2 8
@@ -58,17 +58,18 @@ print(lcase_freqs)
 # partial output ...
 
 {'u': 0, 'q': 0, 'w': 0, 'o': 0, \
-'b': 0,  'c': 0, 't': 0, 'h': 0, \
+ 'b': 0,  'c': 0, 't': 0, 'h': 0, \
 ...
-'g': 0, 'a': 0, 'n': 0}
+ 'g': 0, 'a': 0, 'n': 0}
+
 # Check it is correct:
 lfk = list(lcase_freqs.keys())
 lfk.sort()
 print(lfk)
 ['a', 'b', 'c', 'd', 'e', 'f', \
-'g', 'h', 'i', 'j', 'k', 'l', \
-'m', 'n', 'o', 'p','q', 'r', \
-'s', 't', 'u', 'v', 'w', 'x', \
-'y', 'z']
+ 'g', 'h', 'i', 'j', 'k', 'l', \
+ 'm', 'n', 'o', 'p','q', 'r', \
+ 's', 't', 'u', 'v', 'w', 'x', \
+ 'y', 'z']
 
 ```

python/functional-programming/comprehension/list-comprehension.md

@@ -97,8 +97,7 @@ Use list comprehension to add one and divide by two [(x + 1) / 2] for all elemen
 
 ```python
 l = [1,2,3,4,5]
-x = [((x+1)/2) ??? x % 2 \
-    ??? x ??? x in ???]
+x = [((x+1)/2) ??? x % 2 ??? x ??? x in ???]
 ```
 
 - if

python/functional-programming/comprehension/nested-lists-comprehension.md

@@ -27,27 +27,23 @@ Since a list comprehension can take any **expression** as its initial expression
 These are often useful, but are often used to work with matrices.
 
 ```python
-matrix = [[1, 2, 3], [4, 5, 6], \
-[7, 8, 9]]
-
+matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
 ```
 
 Say we want to create another matrix with values equal to the squares of each element in the original matrix:
 
 ```python
-matrix2 = [[x**2 for x in row] for \
-row in matrix]
-#matrix2 = [[1, 4, 9], [16, 25, 36],\
-# [49, 64, 81]]
+matrix2 = [[x**2 for x in row] for row in matrix]
+#matrix2 = [[1, 4, 9], [16, 25, 36], [49, 64, 81]]
 ```
 
 A more advanced list comprehension with two for clauses and two if clauses:
 
 ```python
 lc = [ (x, y) for x in \
-range(10) if x % 2 == 0 \
-for y in range(20) if \
-y % 3 == 0 ]
+     range(10) if x % 2 == 0 \
+     for y in range(20) if \
+     y % 3 == 0 ]
 # lc
 # [(0, 0), (0, 3), (0, 6), \
 # (0, 9), (0, 12), (0, 15), (0, 18),\
@@ -70,7 +66,6 @@ Use nested list comprehension to generate a list of tuples, where the first elem
 Ex: (1,1),(1,2),(1,3),...(9,7),(9,8),(9,9).
 
 ```python
-
 l = [??? for x in range(10)\
     if ??? for y in ???]
 ```

python/functional-programming/comprehension/set-comprehension.md

@@ -33,22 +33,19 @@ Imagine we have the following list:
 
 ```python
 my_list = [1, 2, 3, 4, 5, 6, 7, 8]
-
 ```
 
 And we need a set containing only even numbers in the list. This can be easily achieved with **set comprehension**:
 
 ```python
 even_set = {x for x in my_list if x%2 == 0}
-
 ```
 
 We can now check the result:
 
 ```python
 print(even_set)
 # {8, 2, 4, 6}
-
 ```
 
 Note that the above operation would work even if my_list contained some duplicate values, e.g:
@@ -67,10 +64,8 @@ since sets by definition do not allow duplicates.
 Fill in the following code snippet. It creates a new set that contains elements of list `l` that are even and adds one and divides by two the odd numbers:
 
 ```python
-
 l = [10, 11, 13, 14, 18, 19]
-new_set = {x ??? x % 2 == 0 else/
-          ??? for x ??? l}
+new_set = {x ??? x % 2 == 0 else ??? for x ??? l}
 ```
 
 - if
@@ -88,7 +83,6 @@ new_set = {x ??? x % 2 == 0 else/
 What will the `odd_set` look like after we run the following code snippet?
 
 ```python
-
 l = [1,3,3,2,4,5,5,8,9]
 odd_set = {x for x in l if x % 2}
 ```

python/functional-programming/comprehension/speed-up-your-for-loop-using-map-or-list-comprehensions.md

@@ -35,7 +35,7 @@ If you need to lowercase all the input strings:
 ```python
 lower_list = []
 for word in input_list:
-    lower_list.append(word.lower())
+  lower_list.append(word.lower())
 ```
 
 Instead, you can use `map()` to push the loop into compiled C code:
@@ -47,8 +47,7 @@ lower_list = map(str.lower, input_list)
 Also, in Python 2.0 or above, there are list comprehensions. List comprehension are the "pythonic" way to approach this situation. `map()` is more often used in JavaScript. We recommend usage of list comprehension:
 
 ```python
-lower_list = [word.lower() \
-  for word in input_list]
+lower_list = [word.lower() for word in input_list]
 ```
 
 They are both more efficient than simple `for` loop statement.
@@ -63,8 +62,7 @@ Use list comprehension to modify a list of characters such that all its elements
 ```python
 strings = ['a', 'e', 'i', 'o', 'u']
 
-lower_list = [word.??? \
-  for word in ???]
+lower_list = [word.??? for word in ???]
 ```
 
 - upper()

python/functional-programming/functional-programming/what-is-functional-programming.md

@@ -40,9 +40,9 @@ This is a way to define functions in a one-line fashion. Functions defined with
 
 ```py
 foo = [1, 2, 3, 4, 5, 6]
-print(list(filter(
-      lambda x: x % 2 == 0,foo))
-      )
+print(list(filter( \
+  lambda x: x % 2 == 0,foo
+)))
 
 # Output: [2, 4, 6]
 ```
@@ -108,10 +108,9 @@ Can you predict what the output will be?
 ```py
 foo = list(range(1,10))
 
-result = list(
-       filter(
-       lambda x: x / 2 == 1 ,foo
-       ))
+result = list(filter( \
+  lambda x: x / 2 == 1 ,foo
+))
 
 print(result)
 

python/functional-programming/generators/generator-of-generators.md

@@ -27,7 +27,7 @@ Last insight, we've seen how **recursion** and **generators** can work together.
 
 Consider the following example:
 
-```plain-text
+```python
 def fibonacci():
     #Generating fibonacci sequence
     a, b = 0, 1
@@ -51,7 +51,7 @@ This is why we define the second **generator** called `firstn` which accepts two
 
 Finally, we print a list containing the first 10 *elements* of the *Fibonacci sequence*:
 
-```plain-text
+```python
 # Output:
 # [0, 1, 1, 2, 3, 5, 8, 13, 21, 34]
 ```
@@ -99,8 +99,7 @@ def n_power(g,n):
     for i in range(n):
       yield next(g)
 
-print(list(n_power(
-  power_of_two(), 4)))
+print(list(n_power(power_of_two(), 4)))
 ```
 
 ???

python/functional-programming/generators/recursive-generator.md

@@ -30,9 +30,9 @@ Consider the following example:
 
 ```python
 def infinity(start):
-    yield start
-    for x in infinity(start + 1)
-      yield x
+  yield start
+  for x in infinity(start + 1)
+    yield x
 ```
 
 We defined a **generator** that counts up to infinity. During the first evaluation, the starting value will be **returned**. Then we loop on the new **generators** created in the `for`'s body.
@@ -43,8 +43,8 @@ Let's check out the example above implemented using `yield from`:
 
 ```python
 def infinity(start):
-    yield start
-    yield from infinity(start + 1)
+  yield start
+  yield from infinity(start + 1)
 
 gen = infinity(20)
 print(next(gen)) # 20
@@ -64,9 +64,9 @@ Can you spot which of the following generators are recursive?
 
 ```python
 def list_gen(l):
-    if l:
-        yield l[0]
-        yield from list_gen(l[1:])
+  if l:
+    yield l[0]
+    yield from list_gen(l[1:])
 
 def cubic_generator(n):
 	for i in range(n):

python/functional-programming/generators/yield-and-next.md

@@ -42,10 +42,10 @@ Consider the following generator:
 
 ```py
 def range_gen(n):
-    i = 0
-    while i < n:
-        yield i
-        i += 1
+  i = 0
+  while i < n:
+    yield i
+    i += 1
 ```
 
 This **function** generates all natural numbers up to `n`. Let's use the `next()` method now:
@@ -73,9 +73,9 @@ What is the output of the following snippet?
 
 ```py
 def countdown(num):
-    while num > 0:
-        yield num
-        num -= 1
+  while num > 0:
+    yield num
+    num -= 1
 
 >>> gen = countdown(5)
 >>> print(next(gen))