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Mahmoud Harmouch
Mahmoud Harmouch

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30 PyTricks I've Learned By Joining the Real Python Mailing List.

#python #beginners

I subscribed to the Real Python mailing list two years ago, and I learned a lot of tips and tricks during that time. Even though it might seem like an odd way to learn Python, I have found it to be extremely helpful. I have written down some notes about the most useful tips and tricks that I have learned over the last two years, and I wanted to share them with you today.

1. Merging two dictionaries.

Question: How to merge two dictionaries?

Answer: Using The unpack ** operator. 

>>> x = {'a': 10, 'b': 8}
>>> x = {'a': 1, 'b': 2}
>>> y = {'b': 3, 'c': 4}
>>> z = {**x, **y}
>>> z
{'a': 1, 'b': 3, 'c': 4}
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2. A way to test multiple conditions at once.

Question: How to test multiple flags at once?

Answer: Using any, in, all operators instead of or or and. 

>>> x, y, z = 0, 1, 0
>>> if x == 1 or y == 1 or z == 1:
...   print("Passed")
... 
Passed

>>> if 1 in (x, y, z):
...   print("Passed")
... 
Passed

>>> if any((x, y, z)):
...   print("Passed")
... 
Passed

>>> x, y, z = 1, 1, 1
>>> if x == 1 and y == 1 and z == 1:
...   print("Passed")
... 
Passed

>>> if all((x, y, z)):
...   print("Passed")
... 
Passed
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3. Sorting a dict by values.

Question: How to sort a dict by values?

Answer: Using the sorted method along with operator.itemgetter or any ordinary function as a key. 

>>> dict1 = {'a': 4, 'b': 3, 'c': 2, 'd': 1}
>>> dict1_sorted = dict(sorted(dict1.items(), key=lambda item:item[1]))
>>> dict1_sorted
{'d': 1, 'c': 2, 'b': 3, 'a': 4}

>>> import operator
>>> dict1_sorted = dict(sorted(dict1.items(), key=operator.itemgetter(1)))
>>> dict1_sorted
{'d': 1, 'c': 2, 'b': 3, 'a': 4}
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4. The get method on dicts and its "default" argument.

Question: How to fetch a dict value given a key?

Answer: Using the get method. 

>>> name_for_userid = {123: "Alice", 432: "Bob"}
>>> print(f"Hello {name_for_userid.get(123, 'there')}!")
Hello Alice!

>>> print(f"Hello {name_for_userid.get(999, 'there')}!")
Hello there!
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5. Namedtuples can be a great alternative to defining a class manually.

Question: What is another way to define a class?

Answer: Using collections.namedtuple. 

>>> from collections import namedtuple
>>> Car = namedtuple('Car', 'color mileage')
>>> my_car = Car('red', 312.4)
>>> my_car
Car(color='red', mileage=312.4)
>>> my_car.color
'red'
>>> my_car.mileage
312.4
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6. Cool python imports.

Question: Are there any easter eggs in python?

Answer: Yes. 

>>> import antigravity
>>> import this
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7. Pretty print a dict.

Question: How to print a dict with indentation?

Answer: Using json.dumps method. 

>>> import json
>>> dict1 = {'b': 2, 'a': 1, 'c': 4}
>>> print(json.dumps(dict1, indent=4, sort_keys=True))
{
    "a": 1,
    "b": 2,
    "c": 4
}
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8. Function argument unpacking in python.

Question: How to pass multiple arguments at once to a given function?

Answer: Using the unpack * operator. 

>>> def my_func(a, b, c):
...   print(a, b, c)
... 
>>> dict1 = {'a': 1, 'b': 3, 'c': 4}
>>> my_func(*dict1)
a b c
>>> my_func(**dict1)
1 3 4
>>>
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9. Using the built-in timeit module to measure the performance of your code.

Question: How to measure the execution time of your code?

Answer: Using the timeit module. 

>>> import timeit
>>> code_snippet = "for _ in range(1000): ..."
>>> timeit.timeit(code_snippet, number=10_000)
0.1994824110006448
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10. In-place value swapping.

Question: How to swap values in python?

Answer: Using the tuple notation ,. 

>>> a = 1
>>> b = 2
>>> a, b = b, a
>>> a, b
(2, 1)
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11. Use "is" instead of "==" to test for object identity.

Question: How to test identities of two objects?

Answer: Using the is operator. 

>>> a = [1, 2, 3]
>>> b = a
>>> b is a
True
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12. Python built-in HTTP server.

Question: How to preview a website?

Answer: Using the http.server method. 

➜  ~ python3 -m http.server          
Serving HTTP on 0.0.0.0 port 8000 (http://0.0.0.0:8000/) ...
127.0.0.1 - - [08/Sep/2022 21:46:01] "GET / HTTP/1.1" 200 -
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This will serve the current directory on http://localhost:8000 or http://127.0.0.1:8000.

server

13. Use list comprehensions. They're more concise and easier to read.

Question: How to filter values in python?

Answer: Using a list comprehension. 

# Filter odd values.
>>> a = [x * x for x in range(10) if not x % 2]
>>> a
[0, 4, 16, 36, 64]
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14. Type annotations.

Question: How to explicitly declare a type for a given variable?

Answer: Using type annotations. 

>>> def add(a: int, b: int) -> int:
...   return a + b
...
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15. Finding the most common elements in an iterable.

Question: How to find the n most frequent items in an iterable?

Answer: Using the collections.Counter.most_common method. 

>>> c = collections.Counter("HelloWorld")
>>> c
Counter({'l': 3, 'o': 2, 'H': 1, 'e': 1, 'W': 1, 'r': 1, 'd': 1})
>>> c.most_common(2)
[('l', 3), ('o', 2)]
# they have the most counts as n=2 in this case.
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16. Generate permutations for an iterable.

Question: How to generate permutations for a given iterable?

Answer: Using the itertools.permutations method. 

>>> import itertools
>>> for p in itertools.permutations('abc'):
...   print(p)
... 
('a', 'b', 'c')
('a', 'c', 'b')
('b', 'a', 'c')
('b', 'c', 'a')
('c', 'a', 'b')
('c', 'b', 'a')
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17. __str__ vs __repr__.

Question: When to use __str__ and __repr__?

Answer: __repr__ is for developers, __str__ is for customers. 

>>> import datetime
>>> today = datetime.datetime.utcnow()
>>> today
datetime.datetime(2022, 9, 8, 19, 5, 39, 446208)
>>> str(today)
'2022-09-08 19:05:39.446208'
>>> repr(today)
'datetime.datetime(2022, 9, 8, 19, 5, 39, 446208)'
>>> today
datetime.datetime(2022, 9, 8, 19, 5, 39, 446208)
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18. Use @classmethod and @staticmethod decorators on class methods as needed.

Question: What is the difference between classmethod and staticmethod? 

>>> class A:
...   def foo(self, x):
...     print(f"executing foo({self}, {x})")
...   @classmethod
...   def class_foo(cls, x):
...     print(f"executing class_foo({cls}, {x})")
...   @staticmethod
...   def static_foo(x):
...       print(f"executing static_foo({x})")
... 
>>> a = A()
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Answer: With classmethod, the class of the object instance is implicitly passed as the first argument instead of self. 

>>> a.foo(1)
executing foo(<__main__.A object at 0x7f90ff34cf70>, 1)
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staticmethod don't have access to cls (the class) nor self (the instance). They behave like plain functions except that you can call them from an instance or the class: 

>>> a.static_foo(1)
executing static_foo(1)
>>> A.static_foo('hi')
executing static_foo(hi)
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19. Lambda functions.

Question: When to use lambda functions?

Answer: To represent a mathematical function of some sort. 

>>> f = lambda x, y: x+y
>>> f(2,3)
5
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20. Working with IP addresses.

Question: How to store an IP address?

Answer: Using the ipaddress module. 

>>> import ipaddress
>>> ipaddress.ip_address('192.168.1.2')
IPv4Address('192.168.1.2')

>>> ipaddress.ip_address('::1')
IPv6Address('::1')
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21. Accessing class and function names at runtime.

Question: How to access class and function names at runtime?

Answer: Using the __name__ method. 

>>> from collections import namedtuple
>>> Car = namedtuple('Car', 'color mileage')
>>> car = Car(color='red', mileage=123.12)
>>> car.__class__.__name__
'Car'
>>>
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22. Class inheritance and the issubclass built-in function.

Question: How to check class inheritance?

Answer: Using the issubclass module. 

>>> class Parent:
...   ...
... 
>>> class Child(Parent):
...   ...
... 
>>> issubclass(Child, Parent)
True
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23. Unicode variable names.

Question: Is Unicode variable names allowed in python?

Answer: Yes. 

>>> á = 'a'
>>> ª = 1
>>> ❤️ = 'Python 2' #  not allowed
  File "<stdin>", line 1
    ❤️ = 'Python 2'
    ^
SyntaxError: invalid character '❤️' (U+1F4A9)
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24. globals and locals.

Question: What is the difference between globals and locals?

Answer: globals gets all global variables in the current scope. 

>>> globals()
{'__name__': '__main__', '__doc__': None, '__package__': None,
.
.
.
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locals gets all local variables in the current scope. 

>>> locals()
{'__name__': '__main__', '__doc__': None, '__package__': None,
.
.
.
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25. faulthandler module.

Question: What does faulthandler do?

Answer: Display tracebacks even when python crashes, segfault. 

>>> import faulthandler
>>> faulthandler.enable()
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26. else with for and while loops.

Question: What does else do with a loop?

Answer: Its scope runs only if the loop ran to completion without hitting a break statement. 

>>> for i in range(10):
...   print(i)
...   if i == 8:
...     break # termination, no else    
... else:
...   print("after for loop")
... 
0
1
2
3
4
5
6
7
8
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27. Pythonic way to check if all elements are equal in a list.

Question: How to check if all elements are equal in a list?

Answer: using the set method to check for unique values. 

>>> lst = [1, 1, 1]
>>> len(set(lst)) == 1
True
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28. contextlib.suppress.

Question: How to ignore specific exceptions?

Answer: using the contextlib module. 

>>> import contextlib, os
>>> with contextlib.suppress(FileNotFoundError):
...   os.remove('file_name.txt')
...
>>>
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29. Forced keyword-only parameters.

Question: How to force keyword-only arguments?

Answer: using the * operator. 

>>> def f(a, b, *, c='x', d='y'):
...   return "Hello"
... 
>>> f(1, 2, 'p', 'q')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: f() takes 2 positional arguments but 4 were given
>>> f(1, 2, c='p', d='q')
'Hello'
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30. Multiple sets of kwargs.

Question: How to pass multiple sets of keyword arguments?

Answer: using the unpack ** operator. 

>>> def f(a, b, c, d):
...   ...
... 
>>> x = {'a': 1, 'b': 2}
>>> y = {'c': 3, 'd': 4}

>>> f(**x, **y)
>>>
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These are all the things I've learned from subscribing to the Real Python mailing list. If you're looking for a more in-depth look at Python, I highly recommend checking out My repo; you might be surprised at what you learn!

GitHub logo wiseaidev / awesome-python

📚 Awesome Python Resources (mostly PyCon).

Awesome Python Awesome

📜 Summary

A curated list of python tutorials, notes, slides deck, files related to pycon talks, and a handful list of books that are worth reading. This repository can be used as a reference documentation for mastering the python programming language and other related content like frameworks and such.

This repository serves three primary roles:

  1. Sharing an opinionated list of python videos.

  2. Sharing notes driven by the awesome community.

  3. Sharing a handful list of books that can play a significant role in honing your python skills.

If you are looking for a way to contribute to the project, please refer to the Guideline.

Don't forget to slap that ⭐ button an odd number of times ;-)

Currently maintained by Mahmoud Harmouch.

👉 Table Of Content (TOC).

  1. Python Talks
    1.1. Novice Level - Core
    1.2. Intermediate Level - Core
    1.3. Generic
    1.4. Python 2 and Python 3…

View on GitHub

Cover Image by Gerd Altmann from Pixabay.

Top comments (8)

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geraldew profile image
geraldew •

By coincidence I recently encountered the reason why item 7 "Pretty print a dict." is not reliable.
i.e. Answer: Using json.dumps method.

This will fail when the items in the dictionary are not things that can be expressed as JSON. The two I encountered were enumerations and tuples.

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wiseai profile image
Mahmoud Harmouch •

Actually, I don't like to use this method, but rather engineer my own thing. For instance, at some point in the past, i created these handy functions:

def indent(string: str, num_spaces: int) -> str:
    indent_str: str = " " * num_spaces
    return "\n".join(indent_str + line for line in string.split("\n")[:-1]) + "\n"

def pretty_dict(dict_: dict[str, str], num_spaces: int) -> str:
  if not isinstance(dict_, dict):
    return repr(dict_)
  rep = []
  for key, val in dict_.items():
    rep.append(f"{key}: {pretty_dict(val, num_spaces)},\n")
  if rep:
    return f'{{\n{indent("".join(rep), num_spaces)}}}'
  else:
    return "{}"
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Usage:

>>> dict1 = {'b': 2, 'a': {'b': [1, 2, 3]}, 'c': list(enumerate(range(4)))}
>>> print(pretty_dict(dict1, 2))
{
  b: 2,
  a: {
    b: [1, 2, 3],
  },
  c: [(0, 0), (1, 1), (2, 2), (3, 3)],
}
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It seems like, over the years, I developed a hate relationship with the DRY principle. Anyways, I hope you find it useful. Cheers mate!

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tompollard61 profile image
Tom Pollard •

json.dumps() will represent tuples as JSON lists. But there are certainly other Python types that json.dumps() can't handle, like datetimes

The pprint ("pretty-print") module handles all of those. So, instead of json.dumps() you can use pprint.pprint()

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geraldew profile image
geraldew •

Well it simply didn't in the environment that I was using, instead it crashed on the tuple. To be clear, the tuple was being used as a key in the Python dictionary, something that Python allows but I'm guessing has no equivalence in JSON.

Thread Thread
 
tompollard61 profile image
Tom Pollard •

Yes, JSON keys need to be strings.

In any case, pprint was introduced to the stdlib specifically to handle pretty-printing of Python values, but I don't run across many people who seem to know about it.

Thread Thread
 
geraldew profile image
geraldew •

post script - as it happened I was curious enough about JSON versus data structures to try getting it to handle something more than just text keys. So I wrote an experiment about using enumerations - see:

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gdledsan profile image
Edmundo Sanchez •

Check orjson, faster and better json handling

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gdledsan profile image
Edmundo Sanchez •

There is a library to solve that, check orjson, its faster, it parses more types, check it out

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