This post originally appeared on Mario Pabon’s blog.
So recently I began working at a little startup in New York City by the name of Underdog.io, where I discovered that they had a back-end written primarily in Python, a language that I had very little previous exposure to.
While I was hired primarily for my experience with JavaScript and React, the small size of our team means that I frequently have to delve into all parts of the codebase in order to ship a feature. So I had to get well acquainted with Python, very fast.
Unfortunately, I had a hard time finding good resources for learning Python that weren’t targeted to people who haven’t programmed before. I already knew how to program and am familiar with other languages, I just needed to learn the syntax and paradigms of this one specific programming language, Python.
That’s where this blog post comes in. To serve as a quick guide for JavaScript developers who want to get up to speed quickly with Python, but without having to learn what declaring a variable means or what a function is.
This post is assuming you are using Python 3.0.1, so some of the examples might not work with older versions of Python.
Syntax
Declaring variables
Declaring a variable in Python is super simple. Like JavaScript, you don’t have to set the type of the variable when declaring it. And you don’t have to declare the scope of the variable either (let vs var):
x = 5
You can change the type of a variable by assigning a value of a different type to it:
x = 5 # x has a type of Integer
x = 'Hewwo' # x is now a String!
Unlike JavaScript, variables in Python are always block scoped.
Blocks
Python is a bit more strict than JavaScript when it comes to syntax. In Python, getting indentation off by a single space can prevent your programming from even running (!). This is because Python uses indentation to create blocks instead of braces. For example, this is how you would define a block in JavaScript vs. Python:
Creating a block in JavaScript
function exampleFunction () {
// This is a block
var a = 5;
}
{
// This is also a block
}
Creating a block in Python
# This is a block with its own scope
def example_function():
# This is also a block with its own scope
x = 5
print(x)
If the line containing print(x) had one or more extra spaces, the Python interpreter would throw an IndentationError, because those extra spaces would have created an invalid block.
def example_function():
x = 5
# IndentationError!
print(x)
If that same line had one or more less spaces in it, like this:
def example_function():
x = 5
print(x)
The Python interpreter would throw this error:
NameError: name 'x' is not defined
Because print(x) is in a block that is out of scope of the one that x is declared in.
Control flow
if...else, while, and for blocks in Python are very similar to JavaScript:
if…else
if x > 2:
print('hai!')
elif x > 3:
print('bye!')
else:
print('hey now')
if not x:
print('x is falsy!')
while loop
while x > 0:
print('hey now')
for loop
For loops are like JavaScript foreach loops:
ex_list = [1, 2, 3]
for x in ex_list:
print(x)
Types
Python’s type system is a lot like JavaScript’s; it’s there, but it’s not as strict as in other languages like Java or C#.
Practically speaking, variables have types, but you don’t have to declare the types of your variables like you would in a statically typed language such as Java.
Here’s a quick overview of Python’s built in data types:
Numbers
Unlike JavaScript, Python has more than one number type:
- Integers:
1, 2, 3 - Floats:
4.20, 4e420 - Complex numbers:
4 + 20j - Booleans:
True, False
You can perform the same operations on numbers in Python as you can in JavaScript. There’s also an exponentiation operator (**):
# a = 4
a = 2 ** 2
Lists
Lists in Python are similar to arrays in JavaScript. Lists can contain a mixture of types:
[4, "2", [0, "zero"]]
There’s also a special syntax for slicing elements from lists:
a_list = [1, 2, 3, 4, 5]
# 1, 2, 3
a_list[0:2]
# 4, 5
a_list[3:]
# 3, 4
a_list[2, -2]
And some handy built-in methods for operating on lists:
# 3
len([1, 2, 3])
# 3, 2, 1
[1, 2, 3].reverse()
# 1, 2, 3
[1, 2].append(3)
You can even concatenate two lists with the + operator:
# 1, 2, 3, 4
[1, 2] + [3, 4]
Strings
Strings in Python are a lot like strings in JavaScript. They are immutable, and individual characters can be accessed like elements in an array:
name = 'Mario'
# M
print(name[0])
# Nope, name is still 'Mario'
name[0] = 'W'
Dictionaries
Dictionaries are associative arrays, similar to objects in JavaScript. In fact, dictionaries can be declared with a JSON-like syntax:
# Dictionaries in python
person = {
'name': 'Mario',
'age': 24
}
# Mario
print(person['name'])
Dictionaries have a handy method for returning a default value when trying to get the value of a non-existent key:
# Because `gender` is not defined, non-binary will be returned
person.get('gender', 'non-binary')
None
None is equivalent to null in JavaScript. It signifies the absence of a value, and is considered “falsy”.
x = None
if not x:
print('x is falsy!')
Functions
Like JavaScript, functions are objects in Python. That means you can pass functions as arguments, or even assign properties to functions:
def func(a, fn):
print(a)
fn()
func.x = 'meep'
# 'meep'
print(func.x)
def another_func():
print('hey')
# 5
# 'hey'
func(5, another_func)
Modules
Modules in Python aren’t that far off from modules in ES6.
Defining a module
A module in Python is simply a file that contains some Python code.
# my_module.py
hey = 'heyyy'
def say_hey():
print(hey)
Unlike JavaScript, you don’t have to declare what is being exported; everything is exported by default.
Importing a module
You can import an entire module in Python:
# importing my_module.py from another_module.py; both files are in the same
# directory
import my_module
# Do things
my_module.say_hey()
print(my_module.hey)
Or import individual items from a module:
# another_module.py
from my_module import hey, say_hey
# Do things
say_hey()
print(hey)
You can also install modules other people have written with pip, a package manager for Python.
pip install simplejson
Object Oriented Programming
Python has support for object oriented programming with classes and classical inheritance, unlike JavaScript which has prototypes with prototypal inheritance.
Classes
# Defining a class
class Animal:
# Variable that is shared by all instances of the Animal class
default_age = 1
# Constructor
def __init__(self, name):
# Defining a publicly available variable
self.name = name
# You can define private variables and methods by prepending the variable
# name with 2 underscores (__):
self.__age = default_age
# Public method
def get_age(self):
return self.__age
# Private method
def __meow():
print('meowwww')
# Defining a static method with the `staticmethod` decorator
@staticmethod
def moo():
print('moooo')
# Creating an Animal object
animal = Animal()
# Accessing public variables and methods
print(animal.name)
print(animal.default_age)
print(animal.get_age())
# Accessing a static method
Animal.moo()
# ERR!!!! .__age is private, so this won't work:
print(animal.__age)
Inheritance
Classes can inherit from other classes:
# Inheriting from the Animal class
class Human(Animal):
def __init__(self, name, ssn):
# Must call the __init__ method of the base class
super().__init__(name)
self.__ssn = ssn
def get_ssn(self):
return self.__ssn
# Using the Human class
human = Human('Mario', 123456789)
# Human objects have access to methods defined in the Animal base class
human.get_age()
human.get_ssn()
Resources
There is a lot more to Python than what’s in this guide. I highly recommend you check out the Python docs for tutorials and details about other language features.
And remember, the best way to learn a language is to write it, a lot. So get to coding!
P.S.: If you need an idea for a project, maybe try creating a simple API with Flask?
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