iskm/learnxinyminutes-docs
1
0
Fork 0
mirror of https://github.com/adambard/learnxinyminutes-docs.git synced 2025-01-14 13:15:59 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity

Merge pull request #4537 from nbehrnd/python_en_linelimit

Browse Source 
[python/en] stricter restraint of 80 characters/line maximum
This commit is contained in:
Marcel Ribeiro Dantas 2022-11-09 01:54:26 -03:00 committed by GitHub
commit 8afc5e6ceb
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 37 additions and 34 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

71
python.html.markdown
View File

@ -13,11 +13,13 @@ contributors:
filename: learnpython.py
---
Python was created by Guido van Rossum in the early 90s. It is now one of the most popular
languages in existence. I fell in love with Python for its syntactic clarity. It's basically
executable pseudocode.
Python was created by Guido van Rossum in the early 90s. It is now one of the
most popular languages in existence. I fell in love with Python for its
syntactic clarity. It's basically executable pseudocode.
Note: This article applies to Python 3 specifically. Check out [here](http://learnxinyminutes.com/docs/pythonlegacy/) if you want to learn the old Python 2.7
Note: This article applies to Python 3 specifically. Check out
[here](http://learnxinyminutes.com/docs/pythonlegacy/) if you want to learn the
old Python 2.7
```python
@ -97,8 +99,9 @@ bool(set()) # => False
bool(4) # => True
bool(-6) # => True
# Using boolean logical operators on ints casts them to booleans for evaluation, but their non-cast value is returned
# Don't mix up with bool(ints) and bitwise and/or (&,|)
# Using boolean logical operators on ints casts them to booleans for evaluation,
# but their non-cast value is returned. Don't mix up with bool(ints) and bitwise
# and/or (&,|)
bool(0) # => False
bool(2) # => True
0 and 2 # => 0
@ -152,10 +155,10 @@ b == a # => True, a's and b's objects are equal
# You can find the length of a string
len("This is a string") # => 16
# You can also format using f-strings or formatted string literals (in Python 3.6+)
# Since Python 3.6, you can use f-strings or formatted string literals.
name = "Reiko"
f"She said her name is {name}." # => "She said her name is Reiko"
# You can basically put any Python expression inside the braces and it will be output in the string.
# Any valid Python expression inside these braces is returned to the string.
f"{name} is {len(name)} characters long." # => "Reiko is 5 characters long."
# None is an object
@ -294,7 +297,7 @@ filled_dict = {"one": 1, "two": 2, "three": 3}
# Note keys for dictionaries have to be immutable types. This is to ensure that
# the key can be converted to a constant hash value for quick look-ups.
# Immutable types include ints, floats, strings, tuples.
invalid_dict = {[1,2,3]: "123"} # => Raises a TypeError: unhashable type: 'list'
invalid_dict = {[1,2,3]: "123"} # => Yield a TypeError: unhashable type: 'list'
valid_dict = {(1,2,3):[1,2,3]} # Values can be of any type, however.
# Look up values with []
@ -348,7 +351,7 @@ del filled_dict["one"] # Removes the key "one" from filled dict
# Sets store ... well sets
empty_set = set()
# Initialize a set with a bunch of values. Yeah, it looks a bit like a dict. Sorry.
# Initialize a set with a bunch of values.
some_set = {1, 1, 2, 2, 3, 4} # some_set is now {1, 2, 3, 4}
# Similar to keys of a dictionary, elements of a set have to be immutable.
@ -454,8 +457,7 @@ for i in range(4, 8, 2):
print(i)
"""
To loop over a list, and retrieve both the index and the value of each item in the list
prints:
Loop over a list to retrieve both the index and the value of each list item:
0 dog
1 cat
2 mouse
@ -482,10 +484,11 @@ try:
# Use "raise" to raise an error
raise IndexError("This is an index error")
except IndexError as e:
pass # Pass is just a no-op. Usually you would do recovery here.
pass # Refrain from this, provide a recovery (next example).
except (TypeError, NameError):
pass # Multiple exceptions can be handled together, if required.
else: # Optional clause to the try/except block. Must follow all except blocks
pass # Multiple exceptions can be processed jointly.
else: # Optional clause to the try/except block. Must follow
# all except blocks.
print("All good!") # Runs only if the code in try raises no exceptions
finally: # Execute under all circumstances
print("We can clean up resources here")
@ -521,7 +524,8 @@ print(contents)
filled_dict = {"one": 1, "two": 2, "three": 3}
our_iterable = filled_dict.keys()
print(our_iterable) # => dict_keys(['one', 'two', 'three']). This is an object that implements our Iterable interface.
print(our_iterable) # => dict_keys(['one', 'two', 'three']). This is an object
# that implements our Iterable interface.
# We can loop over it.
for i in our_iterable:
@ -533,15 +537,16 @@ our_iterable[1] # Raises a TypeError
# An iterable is an object that knows how to create an iterator.
our_iterator = iter(our_iterable)
# Our iterator is an object that can remember the state as we traverse through it.
# We get the next object with "next()".
# Our iterator is an object that can remember the state as we traverse through
# it. We get the next object with "next()".
next(our_iterator) # => "one"
# It maintains state as we iterate.
next(our_iterator) # => "two"
next(our_iterator) # => "three"
# After the iterator has returned all of its data, it raises a StopIteration exception
# After the iterator has returned all of its data, it raises a
# StopIteration exception
next(our_iterator) # Raises StopIteration
# We can also loop over it, in fact, "for" does this implicitly!
@ -549,7 +554,7 @@ our_iterator = iter(our_iterable)
for i in our_iterator:
print(i) # Prints one, two, three
# You can grab all the elements of an iterable or iterator by calling list() on it.
# You can grab all the elements of an iterable or iterator by call of list().
list(our_iterable) # => Returns ["one", "two", "three"]
list(our_iterator) # => Returns [] because state is saved
@ -599,9 +604,9 @@ all_the_args(1, 2, a=3, b=4) prints:
# Use * to expand tuples and use ** to expand kwargs.
args = (1, 2, 3, 4)
kwargs = {"a": 3, "b": 4}
all_the_args(*args) # equivalent to all_the_args(1, 2, 3, 4)
all_the_args(**kwargs) # equivalent to all_the_args(a=3, b=4)
all_the_args(*args, **kwargs) # equivalent to all_the_args(1, 2, 3, 4, a=3, b=4)
all_the_args(*args) # equivalent: all_the_args(1, 2, 3, 4)
all_the_args(**kwargs) # equivalent: all_the_args(a=3, b=4)
all_the_args(*args, **kwargs) # equivalent: all_the_args(1, 2, 3, 4, a=3, b=4)
# Returning multiple values (with tuple assignments)
def swap(x, y):
@ -611,7 +616,7 @@ def swap(x, y):
x = 1
y = 2
x, y = swap(x, y) # => x = 2, y = 1
# (x, y) = swap(x,y) # Again parenthesis have been excluded but can be included.
# (x, y) = swap(x,y) # Again the use of parenthesis is optional.
# global scope
x = 5
@ -659,7 +664,7 @@ list(map(max, [1, 2, 3], [4, 2, 1])) # => [4, 2, 3]
list(filter(lambda x: x > 5, [3, 4, 5, 6, 7])) # => [6, 7]
# We can use list comprehensions for nice maps and filters
# List comprehension stores the output as a list which can itself be a nested list
# List comprehension stores the output as a list (which itself may be nested).
[add_10(i) for i in [1, 2, 3]] # => [11, 12, 13]
[x for x in [3, 4, 5, 6, 7] if x > 5] # => [6, 7]
@ -719,8 +724,8 @@ class Human:
# Note that the double leading and trailing underscores denote objects
# or attributes that are used by Python but that live in user-controlled
# namespaces. Methods(or objects or attributes) like: __init__, __str__,
# __repr__ etc. are called special methods (or sometimes called dunder methods)
# You should not invent such names on your own.
# __repr__ etc. are called special methods (or sometimes called dunder
# methods). You should not invent such names on your own.
def __init__(self, name):
# Assign the argument to the instance's name attribute
self.name = name
@ -774,7 +779,7 @@ if __name__ == '__main__':
i.say("hi") # "Ian: hi"
j = Human("Joel")
j.say("hello") # "Joel: hello"
# i and j are instances of type Human, or in other words: they are Human objects
# i and j are instances of type Human; i.e., they are Human objects.
# Call our class method
i.say(i.get_species()) # "Ian: H. sapiens"
@ -811,8 +816,8 @@ if __name__ == '__main__':
# "species", "name", and "age", as well as methods, like "sing" and "grunt"
# from the Human class, but can also have its own unique properties.
# To take advantage of modularization by file you could place the classes above in their own files,
# say, human.py
# To take advantage of modularization by file you could place the classes above
# in their own files, say, human.py
# To import functions from other files use the following format
# from "filename-without-extension" import "function-or-class"
@ -936,8 +941,8 @@ class Batman(Superhero, Bat):
# However we are dealing with multiple inheritance here, and super()
# only works with the next base class in the MRO list.
# So instead we explicitly call __init__ for all ancestors.
# The use of *args and **kwargs allows for a clean way to pass arguments,
# with each parent "peeling a layer of the onion".
# The use of *args and **kwargs allows for a clean way to pass
# arguments, with each parent "peeling a layer of the onion".
Superhero.__init__(self, 'anonymous', movie=True,
superpowers=['Wealthy'], *args, **kwargs)
Bat.__init__(self, *args, can_fly=False, **kwargs)
@ -1036,8 +1041,6 @@ print(say()) # Can you buy me a beer?
print(say(say_please=True)) # Can you buy me a beer? Please! I am poor :(
```
## Ready For More?
### Free Online
* [Automate the Boring Stuff with Python](https://automatetheboringstuff.com)