How long does it take to learn Python?

Learning Python basics takes 1-2 months, focusing on syntax, loops, and simple scripts. Becoming proficient with libraries and real-world applications takes 3-6 months. Advanced topics like machine learning or backend development may take 6-12 months with consistent practice.

Best practices

Set realistic goals based on your prior programming experience, as complete beginners might need several months to become comfortable with Python.
Practice regularly, ideally daily, to reinforce concepts and improve your coding skills more quickly.
Utilize a variety of resources such as books, online tutorials, and interactive platforms to cater to different learning styles and enhance understanding.
Engage with the community through forums, meetups, or GitHub to gain insights, get feedback, and stay motivated throughout your learning journey.

import requests
from bs4 import BeautifulSoup
# Fetch webpage
response = requests.get('https://sandbox.oxylabs.io/')
soup = BeautifulSoup(response.text, 'html.parser')
# Find and print all links
for link in soup.find_all('a'):
    print(link.get('href'))

Common issues

Focus on mastering the basics like variables, loops, and functions before diving into more complex topics such as data structures or web development.
Break down the learning process into manageable projects that can be completed in a few weeks or months to provide a sense of accomplishment and practical experience.
Incorporate error handling early in your learning to develop good programming habits and understand how to manage common issues in Python.
Reflect on your progress periodically by reviewing past code to identify areas for improvement and consolidate your knowledge.

# Incorrect: Not using error handling which might crash the program if the URL is wrong or the server is down
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')

# Correct: Using try-except to handle potential HTTP request errors
try:
response = requests.get(url)
response.raise_for_status() # Raises an HTTPError for bad responses
soup = BeautifulSoup(response.text, 'html.parser')
except requests.exceptions.HTTPError as e:
print(f"HTTP error occurred: {e}")
except requests.exceptions.RequestException as e:
print(f"Error during requests to {url}: {e}")

# Incorrect: Diving directly into complex scraping without understanding basic HTML parsing
soup = BeautifulSoup(response.text, 'html.parser')
complex_data = soup.find_all('div', {'class': 'complex-class'})

# Correct: Start with simple tasks to understand basic parsing and gradually increase complexity
simple_data = soup.find('title').text
print(simple_data) # Understanding how to extract simple text

# Incorrect: Not breaking down the project into smaller, manageable parts
for faq in soup.find_all('div', class_='complex-section'):
process_complex_logic(faq)

# Correct: Break down the scraping into smaller functions or sections
def extract_questions(soup):
return [faq.text.strip() for faq in soup.find_all('div', class_='faq-question')]

questions = extract_questions(soup)
for question in questions:
print(question)

# Incorrect: Not reviewing or refactoring code which can lead to inefficient or hard-to-maintain scripts
data = [faq.text for faq in soup.find_all('div', class_='faq-question') if "python" in faq.text.lower()]

# Correct: Regularly review and refactor code to improve efficiency and readability
def filter_python_questions(faqs):
return [faq.text.strip() for faq in faqs if "learn python" in faq.text.lower()]

python_faqs = filter_python_questions(soup.find_all('div', class_='faq-question'))
for faq in python_faqs:
print(faq)