Python Quick Tips

Efficient, pythonic code nicely packaged for consumption.

Python and many of its packages have incredible official documentation, but it can be hard to get through it. Meet Python Quick Tips! For elegant, generalizable solutions to data science problems, see Python Deep Tips (forthcoming).

Why take my word on it?
Don’t. Explore for yourself. Each tip has links to documentation and each block of code runs in a Jupyter Notebook.

Python Resources

1. W3 Schools. W3 Schools documentation and tutorials are very light. They are a great primer to get you mind around a topic before trying out the official documentation.
2. Real Python. Real Python articles are incredibly detailed and very good. I try to use the official documentation, but when it is too dense to digest, I turn to Real Python.
3. Python Guide. The world of Python resource is immense. If you find that the options I presented don’t work for you, then look through the resources listed by Python Guide.

Python Core

1. Use sets to do membership checking.
   Sets are unordered and contain only unique values. When checking if a value exists in a set, python uses hashing which is dramatically faster than checking each element. However, there is overhead to cast from a list to the set, so its best to plan to use a set if the variable’s purpose is membership testing.

# Best. Plan ahead.  
members_set = {1, 2, 3, 4, 1, 2}
print(0 in members_set)
# => False
# Slow, but best you can do if only testing once and must use a list
# due to other constraints.
members_list = [1, 2, 3, 4, 1, 2]
print(0 in members_list)
# => False
# Better, but only pays off if doing membership testing multiple 
# times. 
members_from_cast = set(members_list)
other_list = ['a', 'b', 'c']
for other in other_list:
    print(other in members_from_cast)
# => False 
# => False 
# => False

2. Use dictionary comprehensions and set comprehensions.
Dictionary and set comprehensions offer the same readability, compact representation and speed advantages that list comprehensions do.

prime_numbers = [2, 3, 5, 7, 11, 13] 

# Less compact.
primes_squared = {} 
for prime_number in prime_numbers: 
    primes_squared.update({prime_number: prime_number**2})
print(primes_squared)
# => {2: 4, 3: 9, 5: 25, 7: 49, 11: 121, 13: 169}
# Compact, faster, pythonic. 
primes_better = {x : x**2 for x in prime_numbers}
print(primes_better)
# => {2: 4, 3: 9, 5: 25, 7: 49, 11: 121, 13: 169}
# Less compact.
primes_squared_set = set({}) 
for prime_number in prime_numbers: 
    primes_squared_set.add(prime_number**2)
print(primes_squared_set)
# => {4, 9, 169, 49, 121, 25}
# Compact, faster, pythonic. 
primes_better_set = {x**2 for x in prime_numbers}
print(primes_better_set)
# => {4, 9, 169, 49, 121, 25}

This article gets updated whenever I think something is worthy. Check back for updates. Last updated: 3 March 2021.