Update Python Content

CHANGELOG.md

@@ -57,6 +57,7 @@ Types of change:
 ### Changed
 - [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 - All Applicable Insights - Move single-line commands to a single line, update indentation in codeblocks from 4 to 2 spaces](https://github.com/enkidevs/curriculum/pull/2979)
 
 ## January 4th 2022
 

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

@@ -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

@@ -38,7 +38,7 @@ 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 +58,17 @@ 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}
 # 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/decorators/decorators-methods.md

@@ -32,8 +32,7 @@ def get_fahrenheit(method):
   # methods, pass self as a parameter
   def wrapper(self):
     # "self" argument is passed
-    return "{0} F"
-      .format(method(self) * 1.8 + 32)
+    return "{0} F".format(method(self) * 1.8 + 32)
   return wrapper
 
 class Temperature(object):
@@ -55,8 +54,7 @@ We got it now working for methods. But what if we are looking to decorate method
 def get_fahrenheit(method):
   # exepect any number of args/named args
   def wrapper(*args, **kwargs):
-    return "{0} F"
-     .format(method(*args,**kwargs)*1.8+32)
+    return "{0} F".format(method(*args,**kwargs)*1.8+32)
   return wrapper
 
 class Temperature(object):
@@ -65,10 +63,8 @@ class Temperature(object):
 
   @get_fahrenheit
   #two extra arguments expected here
-  def get_temp(self, extra1, extra2 = 0,
-   extra3 = 0):
-    return self.degrees + extra1 + extra2
-     + extra3
+  def get_temp(self, extra1, extra2 = 0, extra3 = 0):
+    return self.degrees + extra1 + extra2 + extra3
 temp = Temperature(15)
 # self is passed by default
 print(temp.get_temp(3, extra2 = 1))

python/functional-programming/decorators/decorators-syntax.md

@@ -26,8 +26,7 @@ def say_hello(name):
   return "Hello, {0}!".format(name)
 def h2_decorate(string_function):
   def func_wrapper(name):
-    return "<h2>{0}</h2>"
-      .format(string_function(name))
+    return "<h2>{0}</h2>".format(string_function(name))
   return func_wrapper
 hello_wrapper = h2_decorate(say_hello)
 ```
@@ -37,8 +36,7 @@ We can shorten the code and get rid of the variable assignment by introducing th
 ```python
 def h2_decorate(string_function):
   def func_wrapper(name):
-    return "<h2>{0}</h2>"
-      .format(string_function(name))
+    return "<h2>{0}</h2>".format(string_function(name))
   return func_wrapper
 
 @h2_decorate
@@ -55,8 +53,7 @@ As you can see, the function is decorated, without the need of an explicit `h2_d
 # variable assignment
 def say_hello(name):
   return "Hello, {0}!".format(name)
-long_wrap =
-  div_decorate(h2_decorate(say_hello))
+long_wrap = div_decorate(h2_decorate(say_hello))
 print(long_wrap("Mike"))
 
 # @ notation
@@ -83,8 +80,7 @@ However, this syntax requires an additional enclosing function, as the **decorat
 def tags_wrapper(tag):
   def func_decorator(string_function):
     def name_wrapper(name):
-      return "<{0}>{1}</{0}>"
-        .format(tag, string_function(name))
+      return "<{0}>{1}</{0}>".format(tag, string_function(name))
     return name_wrapper
   return func_decorator
 

python/functional-programming/decorators/functools-wraps.md

@@ -26,8 +26,7 @@ For example, for the code below:
 ```python
 def h2_decorate(string_function):
   def func_wrapper(name):
-    return "<h2>{0}</h2>" \
-    .format(string_function(name))
+    return "<h2>{0}</h2>".format(string_function(name))
   return func_wrapper
 
 @h2_decorate
@@ -53,8 +52,7 @@ from functools import wraps
 def h2_decorate(string_function):
   @wraps(string_function)
   def func_wrapper(name):
-    return "<h2>{0}</h2>"
-      .format(string_function(name))
+    return "<h2>{0}</h2>".format(string_function(name))
   return func_wrapper
 
 print(say_hello.__name__)

python/functional-programming/decorators/what-are-decorators.md

@@ -43,8 +43,7 @@ You could always define another function that makes use of `say_hello`:
 
 ```python
 def hello_heading(name):
-  return "<h2>{0}</h2>"
-    .format(say_hello(name))
+  return "<h2>{0}</h2>".format(say_hello(name))
 ```
 
 Which is perfectly acceptable, but you'd be giving away the opportunity of making your code extensible. What if you are going to need a `say_goodbye` function, formatted in the same way? You'd have to create two more functions:
@@ -53,17 +52,15 @@ Which is perfectly acceptable, but you'd be giving away the opportunity of makin
 def say_goodbye(name):
   return "Goodbye, {0}!".format(name)
 def goodbye_heading(name):
-  return "<h2>{0}</h2>"
-    .format(say_goodbye(name))
+  return "<h2>{0}</h2>".format(say_goodbye(name))
 ```
 
 This is not ideal, since all you had done, for each function, was to **decorate** (enhance, manipulate or extend) their output. What if you could write a function that wraps any function's output in `<h2>` tags?
 
 ```python
 def h2_decorate(string_function):
   def func_wrapper(name):
-    return "<h2>{0}</h2>"
-      .format(string_function(name))
+    return "<h2>{0}</h2>".format(string_function(name))
   return func_wrapper
 ```
 
@@ -87,7 +84,7 @@ If you couldn't figure it out, consider that `h2_decorate`'s references to the `
 
 ## Practice
 
-The number of similar looking functions that can be decorated using the same decorator is
+The number of similar-looking functions that can be decorated using the same decorator is
 
 ???
 
@@ -108,13 +105,11 @@ def say_hello(name):
   return "Hello, {0}!".format(name)
 # A
 def hello_heading(name):
-  return "<h2>{0}</h2>"
-    .format(say_hello(name))
+  return "<h2>{0}</h2>".format(say_hello(name))
 # B
 def hello_heading(func):
   def func_wrapper(name):
-    return "<h2>{0}</h2>"
-      .format(func(name))
+    return "<h2>{0}</h2>".format(func(name))
   return func_wrapper
 ```
 

python/functional-programming/functional-programming-ii/functional-particularities-of-python.md

@@ -47,17 +47,14 @@ A comprehension is an expression where the same flow control keywords used in lo
 ```python
 # without comprehension
 for element in list:
-  if condition1(element) and
-    condition2(element):
+  if condition1(element) and condition2(element):
     collection.append(element)
   else:
     new = mutate(element)
     collection.append(element)
 
 # with comprehension
-collection = [e if condition1(e) and
-              condition2(e) else
-              modify(e) for e in list]
+collection = [e if condition1(e) and condition2(e) else modify(e) for e in list]
 ```
 
 As you can clearly see, our code instantly becomes much more legible and comprehensible.