4 October 2023
Python is a high-level, general-purpose programming language that emphasizes code readability and speed of development. Created in 1991 by developer Guido van Rossum, Python has a clear, logical syntax that is easy for beginners to pick up yet powerful enough for experienced programmers. This guide will help you get started. If you are serious about Python you should consider training in one of our Python training courses listed at the end of this article.
Some of the key features and benefits of the Python language include:
With Python in high demand across many industries, it's a great time to start learning Python programming. The hands-on skills you gain will open up opportunities to build your own applications and analyze data, or pursue Python careers like web developer, data analyst, automation specialist, machine learning engineer and more.
Before you can start running Python programs and scripts, you need to set up your Python programming environment. This involves installing the Python interpreter on your operating system, and installing code editors and IDEs (Integrated Development Environments) to write your Python code.
To execute Python code, you need the Python interpreter (also called the Python execution environment) installed. Follow these steps to install Python:
python --version to verify that Python is installed correctly.You should see the installed Python version printed out.
While you can write Python code using a simple text editor, using a customized code editor or IDE provides a more streamlined workflow. Here are some top options:
Download and install your preferred Python code editor. For example, you can install VS Code, then install the Python extension to add Python language support.
It's recommended to isolate your Python projects in separate virtual environments, rather than installing packages globally. This prevents version conflicts between different projects. Python comes with the venv module to create virtual environments and the pip package installer.
To create a virtual environment called myenv:
python -m venv myenv
Activate the environment:
myenv\Scripts\activate
Install packages within that environment using pip install, such as:
pip install pandas
Other popular package/environment managers like Conda and Poetry also exist.
With your Python programming environment now set up, it's time to start learning the basics of the Python language.
Python is a relatively straightforward language to learn, especially if you have some programming experience. We'll cover fundamental Python concepts including data structures, statements and functions.
Like any programming language, Python has built-in data types that are used to define variables and data structures. The main data types include:
Here's an example assigning these data types to variables:
number = 10 #integer
price = 24.99 #float
name = "John" #string
items = ["Spam", "Eggs", "Beans"] #list
point = (10, 20) #tuple
person = {"name":"Mary", "age":23} #dictionary
= like num = 10+, -, *, / to generate new values==, !=, >, < to evaluate conditionsExamples:
total = num + 10 # Addition
diff = 20 - 10 # Subtraction
product = 5 * 2 # Multiplication
quotient = 100 / 20 # Division
flag = num > 10 # Greater than
is_equal = total == 20 # Equality check
Python uses typical control flow statements similar to other languages:
if, elif, else statements for conditional branchingfor loops for iterating over sequenceswhile loops for repeating execution until condition changesExample:
# If statement
if score >= 90:
print("A grade")
elif score >= 80:
print("B grade")
else:
print("No grade")
# For loop
for num in [1, 2, 3, 4, 5]:
print(num)
# While loop
count = 0
while count < 5:
print(count)
count += 1
Functions group code blocks for reuse and organize programs into logical modules. Functions are defined with def and called to execute the logic. Parameters allow passing data into functions.
# Function definition
def double(x):
return x * 2
# Call function
print(double(3)) # Returns 6
Python has many built-in functions like print(), len(), range() etc. You can also import functions from Python modules.
Python supports object-oriented programming (OOP) with classes and objects. A class defines attributes and behaviors while an object is an instance created from the class.
# Class definition
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
# Create object
person = Person("Mark", 23)
print(person.name) # Prints name attribute
print(person.age) # Prints age attribute
With this solid grounding of Python basics including key data structures, operators, control flow, functions and OOP, you can write simple Python scripts. Next let's level up your skills with some intermediate concepts.
Once you grasp Python basics, you can move on to more advanced Python programming concepts that will take your code to the next level:
Comprehensions provide an elegant way to create lists and dictionaries using a compact syntax.
values = [x*2 for x in range(10)] # List comprehension
squares = {x: x*x for x in range(5)} # Dictionary comprehension
These anonymous, inline functions are defined with lambda for simple one-line expressions.
double = lambda x: x * 2
print(double(7)) # Prints 14
Python ships with many standard libraries and modules like math, random, statistics, collections, datetime etc.
import math
print(math.factorial(6)) # Prints 720
from datetime import date
print(date.today()) # Prints today's date
open() function opens files and try/ except blocks handle exceptions.
# Open file
f = open("test.txt", "r")
try:
num = int(input("Enter a number: "))
print(100 / num)
except ZeroDivisionError:
print("Cannot divide by zero")
print() statements to inspect variables.With this knowledge of intermediate skills like comprehensions, built-in modules and debugging, you can write more powerful Python programs. Next let's explore some specific domains where Python excels.
One of Python's most popular uses is data analysis thanks to its powerful libraries like Pandas, NumPy and Matplotlib.
The NumPy library adds support for large, multi-dimensional arrays and matrices along with mathematical and statistical functions to operate on them.
import numpy as np
arr = np.array([1, 2, 3])
print(arr + 2) # Adds 2 to each array element
NumPy is great for performing complex matrix operations.
The Pandas library provides easy-to-use data structures and data analysis tools for loading, analyzing and manipulating datasets.
import pandas as pd
df = pd.DataFrame(data)
df.sort_values("Name") # Sorts table by Name column
Pandas makes importing, managing and analyzing tabular data much simpler.
Matplotlib is the most popular Python library for producing charts, graphs and plots to visualize data.
import matplotlib.pyplot as plt
plt.plot(x_data, y_data)
plt.show() # Displays plot
The Matplotlib visualizations like histograms, scatterplots, and bar charts help uncover insights from data.
Python's specialized libraries like Pandas, NumPy and Matplotlib are indispensable for doing meaningful data analysis and visualizations to derive actionable insights from data.
Another common use case for Python is building web applications and websites, for which Python has fantastic web frameworks.
The most popular Python web frameworks are Django and Flask.
Key steps for building web applications in Python include:
For example, a simple Flask app:
from flask import Flask
app = Flask(__name__)
@app.route("/")
def index():
return "<h1>Hello World!</h1>"
if __name__ == "__main__":
app.run()
This powerful yet simple template displays "Hello World!" at the website route.
Python enables building full-featured websites and web apps quickly with its web application frameworks.
You should now have a solid base of Python knowledge to start writing your own scripts and programs. Here are some recommendations for advancing your Python skills:
Python has seen immense growth in popularity and usage over the last decades. With this comprehensive guide, you now have an excellent foundation to launch your journey as a Python developer to expand your programming skills.
So go forth and build something awesome with Python!
Q: Is Python worth learning in 2023?
A: Absolutely - with growing demand across many industries, Python remains one of the top programming languages to learn in 2023 and beyond. The versatility, large community and abundance of resources make Python a great investment.
Q: What can I build with Python skills?
A: Some examples of what you can build with Python include web applications and sites, desktop GUI apps, data analysis and visualizations, machine learning models, web
Q: What can I build with Python skills?
A: Some examples of what you can build with Python include web applications and sites, desktop GUI apps, data analysis and visualizations, machine learning models, web scraping scripts, automation bots, and more. Python is incredibly versatile.
Q: Is Python easy for beginners to learn?
A: Yes - Python strikes an excellent balance between being simple for beginners yet also powerful for experienced programmers. The clean syntax, indentation structure and focus on readability make Python highly accessible for new programmers.
Q: Should I learn Python 2 or Python 3?
A: You should learn Python 3, which is the latest and recommended version. Python 2 is legacy and no longer supported. All modern Python courses and resources use Python 3.
Q: What IDE is best for Python programming?
A: Some top Python IDEs include PyCharm, Visual Studio Code, Jupyter Notebook and Spyder. Try out a few options to determine the best Python IDE for your needs and preferences.
We have Python courses for every area of your teams training or can design a bespoke course to meet your companies requirements
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