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Python Practice: 93 Unique Online Coding Exercises

Whether you're just starting your learning journey or looking to brush up before a job interview, getting the right kind of Python practice can make a big difference.

Research shows that hands-on practice is the most effective way to learn, * and luckily there are so many different ways to practice that you're bound to find one that works best for you.

In this post, we'll share 93 ways to practice Python online by writing actual code, broken down into different practice methods.

Table of Contents

Core python programming (great for beginners), intermediate python programming, data handling and manipulation with numpy, data handling and manipulation with pandas, data analysis, complexity and algorithms, python introduction (great for beginners), data analysis and visualization, data cleaning.

• Machine Learning

AI and Deep Learning

Probability and statistics, beginner projects, data analysis projects, data engineering projects, machine learning and ai projects, core python concepts (great for beginners), intermediate techniques, data analysis and data science, frequently asked questions, where can i practice python programming.

• How can I practice Python programming?

Can I learn Python in 30 days?

Can i practice python on mobile, how quickly can i learn python, ai is advancing so quickly - should i still learn python, practice with free python coding exercises.

Exercises are a great way to practice a specific topic with targeted efficiency. For example, do you have an upcoming job interview where you know you'll be asked about Python dictionaries? Completing exercises about dictionaries will help refresh your skills and ensure you can confidently speak to this Pythonic datatype.

• Basic Mathematical Operators (free) — Use Python to perform calculations and printing results to the screen.
• Variables and data types (free) — Work with variables and doing calculations with variables.
• Lists and loops (free) — Practice using Python lists and for loops.
• Dictionaries 1 (free) — Use dictionaries in Python.
• Dictionaries 2 (free) — More practice with dictionaries and frequency tables.
• Lists (free) — Practice using lists in Python.
• Conditional statements (if-else) — Use conditional statements in Python.
• Sets — Practice using sets in Python.
• Python functions — Define and call functions.
• Intermediate Python functions — Practice more advanced usage of functions like returning multiple values.
• Object oriented programming (OOP) — Define classes, methods, and attributes.
• NumPy index selection (free) — Select values from ndarrays.
• NumPy creating ndarrays — Create ndarrays with specific values and shapes.
• NumPy ndarray methods — Use ndarray methods to perform calculations.
• NumPy broadcasting — Work with ndarrays with different shapes and using broadcasting to create ndarrays.
• NumPy boolean masks — Select data from ndarrays use boolean masks
• NumPy datatypes — Work with NumPy datatypes
• NumPy sorting — Practice sorting ndarrays
• NumPy stacking and splitting — Stack and split ndarrays
• Pandas series (free) — Use and build pandas series.
• Creating and manipulating dataframes — Create and manipulate pandas dataframes.
• Selecting data with Pandas — Select data from dataframes.
• Loading and exploring data — Load data into dataframes and explore it.
• Pandas boolean masks — Use boolean masks to select data from dataframes.
• Pandas Data Cleaning — Clean data in a dataframe.
• Cleaning and preparing data (free) — Write functions to remove incorrect characters and fill missing values.
• Data analysis basics — Manipulate data from CSV files using Python dictionaries and functions.
• Working with dates and times — Practice with the datetime module in Python.
• Time complexity of algorithms (free) — Identify the type of time complexity of Python functions.
• Constant time complexity — Find the constant time complexity of functions.
• Logarithmic complexity — Practice finding the logarithmic time complexity of functions.
• Sorting algorithms — Create and work with sorting algorithms in Python.
• Space complexity — Practice space complexity by writing Python functions.

Explore our full library of Python practice problems to continue improving your skills.

Practice with Online Python Courses

If you're looking for more structure, then practicing with Python courses online may resonate with you. Courses guide you through a topic, so if you want to gain a new skill or you're rusty on an old one, completing a course is an excellent way to go.

Throughout these courses, you'll be given questions and assignments to test your skills. Additionally, some of these courses contain a guided project that allows you to apply everything you've learned.

See below for some recommended courses.

• Introduction to Python — Write code using Python syntax; work with different types of data; and perform basic Python operations such as working with variables, processing numerical and text data, and manipulating lists.
• Basic Operators and Data Structures in Python — Learn the fundamentals of Python for loops, dictionaries, and conditional logic (if-else).
• Python Functions and Jupyter Notebook — Write Python functions, build functions that employ multiple return statements and return multiple variables, and install and use Jupyter Notebook.
• Python for Data Science: Intermediate — Manipulate text, clean messy data, work with object-oriented programming concepts, and use dates and times in Python.
• Pandas and NumPy Fundamentals — Use NumPy and pandas for data exploration, preparation, and analysis.
• Data Visualization Fundamentals — Balance graph creation and statistics in your visualizations using tools such as Matplotlib and Seaborn.
• Storytelling Data Visualization and Information Design — Use information design and data visualization to tell compelling stories.
• Data Cleaning and Analysis — Manipulate, combine, transform, and merge data; manipulate strings; and work with missing values in Python.
• Data Cleaning in Python: Advanced — Clean and manipulate text data using basic and advanced regular expressions, how to resolve missing data, and how to employ lambda functions and list comprehension with pandas.
• Data Cleaning Project Walkthrough — Combine multiple datasets and prepare them for analysis.
• Intro to Supervised Machine Learning — Build a supervised machine learning model in Python, and train and improve it for better performance and accuracy.
• Intro to Unsupervised Machine Learning — Learn about unsupervised machine learning models in Python, when to apply them, and what differentiates them from supervised machine learning models.
• Linear Regression Modeling — Build, evaluate, and interpret the results of a linear regression model, as well as using linear regression models for inference and prediction.
• Gradient Descent Modeling — Learn the fundamentals of gradient descent and how to implement this algorithm in Python.
• Logistic Regression Modeling — Build and evaluate logistic regression models, both from scratch and using scikit-learn.
• Decision Tree and Random Forest Modeling — Learn the foundations of Decision Trees including identifying the key components of trees, interpreting them, classifying new observations using decision trees and calculating optimal thresholds for both classification and regression trees.
• Optimizing Machine Learning Models — Explore the most common methods and techniques that will enable you to optimize your machine learning models for better efficiency.
• APIs for AI Applications — Use Python for retrieving, analyzing, and manipulating real-world data from various sources including the World Development Indicators database.
• Prompting Large Language Models (LLMs) — Create an AI-powered chatbot using Python, that incorporates key concepts like prompt engineering, managing conversation histories, and efficiently regulating token usage within an AI framework.
• Intro to Deep Learning in Tensorflow — Learn the fundamentals of deep learning, as well as how to build, train, and evaluate models using the TensorFlow framework.
• Introduction to Statistics in Python — Work with techniques for sampling data, concepts such as discrete variables and random variables, and the different types of charts and graphs you might use to visualize frequency distributions.
• Intermediate Statistics in Python — Summarize distributions using mean, median, and mode. You’ll also learn to measure variability using variance or standard deviation and how to locate and compare values using z-scores.
• Introduction to Probability in Python — Estimate probabilities, work with the addition and multiplication rules, and define permutations and combinations.
• Introduction to Conditional Probability in Python — Assign probabilities to events based on certain conditions, evaluate whether they are in a relationship of statistical independence or not, and on prior knowledge by using Bayes’s theorem.
• Hypothesis Testing in Python — Learn advanced statistical concepts like significance testing and multi-category chi-square testing,

These courses are a great way to practice Python online, and they're all free to start. If you're looking for more courses, you can find them on Dataquest's course page .

Practice with Python Projects

One of the most effective ways to practice Python online is with projects. When I was learning Python, it was easy to forget newly acquired skills. When I discovered that I could do projects to practice my newfound knowledge, it helped me remember new syntax. Additionally, I built a great portfolio of work to show potential employers.

Here are a few projects you can use to start practicing right now.

• Profitable App Profiles for the App Store and Google Play Markets (free) — Assume the role of a data analyst at a company that builds apps for Android and iOS. Since the company’s revenue depends on in-app ads, your task is analyzing historical data from app markets to determine which apps attract the most users.
• Learn and Install Jupyter Notebook (free) — Run Python code in a Jupyter Notebook and learn how to install Jupyter locally.
• Build a Word Guessing Game (free) — Have some fun, and create a functional and interactive word-guessing game using Python.
• Build a Garden Simulator Text Based Game (free) — Create an interactive text-based “Garden Simulator” using object-oriented programming, error handling, and randomness.
• Build a Food Ordering App — Create a functional and interactive food ordering application using Python.
• Investigating Fandango Movie Ratings (free) — Step into the role of a data journalist to analyze movie ratings data and determine if there’s evidence of bias in Fandango’s rating system.
• Exploring Hacker News Posts (free) — Analyze a dataset from Hacker News and apply your Python skills in string handling, object-oriented programming, and data management to uncover trends in user submissions.
• Exploring eBay Car Sales Data — Use Python to work with a scraped dataset of used cars from eBay Kleinanzeigen, a classifieds section of the German eBay website.
• Finding Heavy Traffic Indicators on I-94 — Explore how using the pandas plotting functionality along with the Jupyter Notebook interface allows us to explore data quickly using visualizations.
• Storytelling Data Visualization on Exchange Rates — Quickly create multiple subsetted plots using one or more conditions.
• Clean and Analyze Employee Exit Surveys — Work with exit surveys from employees of the Department of Education in Queensland, Australia. Play the role of a data analyst and pretend the stakeholders want answers to important data questions.
• Analyzing NYC High School Data — Discover the SAT performance of different demographics using scatter plots and maps.
• Building Fast Queries on a CSV (free) — Act as a Python developer to build an inventory system for a laptop store. You’ll apply efficient data structures and algorithms to enable fast queries.
• Analyzing Wikipedia Pages (free) — Process over 54 MB of Wikipedia articles to find specific text matches. Using Python and MapReduce, you’ll build a parallel solution to search the dataset and return match details efficiently.
• Building a database for crime reports — Use PostgreSQL to build a database with proper schemas, tables, and user roles to store and manage crime report data efficiently.
• Predicting Heart Disease (free) — Act as a data scientist at a healthcare solutions company to build a model that predicts a patient’s risk of developing heart disease based on their medical data.
• Predicting Insurance Costs — Use linear regession modeling to predict insurance costs.
• Developing a Dynamic AI Chatbot — Create an AI chatbot that can take on different personas and keep track of conversation history.

If these didn't spark your interest, here are plenty of other online Python projects you can try.

Practice with Online Python Tutorials

If online practice exercises, courses, and projects don't appeal to you, here are a few blog-style tutorials to help you learn Python. I like to use this type of resource when I'm on my phone to get some productive reading done, even when I can't code on my computer!

• Python strings — See how to declare the string data type, the relationship between the string data type and the ASCII table, the properties of the string data type, and some important string methods and operations.
• Python dictionaries — Learn how to create a Python dictionary, how to use its methods, and dictionary comprehension.
• Python data structures — Read about what data structures exist in Python, when to apply them, and their pros and cons.
• Python classes — Learn how to create and work with Python classes. See what Python classes are, why we use them, what types of classes exist, how to define a class in Python and declare/adjust class objects,
• Python lists — Read how to define, create, and slice lists, as well as how to add/remove items and use a for loop to iterate over a list.
• If statements — Use conditional logic with if, elif, and else to streamline your code's efficiency.
• Python datetime — Learn the uses of the datetime module, extract dates, and work with timestamps.
• Python ternary — Understand what a Python ternary operator is and when it's useful.
• Python subprocess — See how to use the subprocess module in Python to run different subprocesses during the course of a regular python script.
• Python math module — Read about the common constants and functions implemented in the math module — and how to use them.
• Read files in Python — Learn how to open files, use the with context manager, read text, CSV, and JSON files, and understand different file modes.
• Lambda functions — Define lambda functions in Python and explore the advantages and limitations of employing them.
• Reset index in pandas — Discusses the reset_index() pandas method, why we may need to reset the index of a DataFrame in pandas, and how we can apply and tune this method.
• GroupBy in pandas — Explore how to create a GroupBy object in pandas library of Python and how this object works.
• Getting Started with APIs — Understand how to retrieve data for AI and data science projects using APIs (Application Programming Interfaces).
• Introduction to Keras — Learn how to install and start using Keras; the Sequential API; and the steps for building, compiling, and training a model..
• Implement Support Vector Machines (SVMs) — Read about support vector machines, one of the most popular classification algorithms. Learn how to implement SVMs for a classification task in Python.

The web is also full of thousands of other beginner Python tutorials. As long as you've got a solid foundation in the Python basics, you can find great practice through many of them.

Dataquest.io has dozens of free interactive practice questions, as well as free interactive lessons, project ideas and walkthroughs, tutorials, and more.

HackerRank is a great site for practice that’s also interactive.

CodingGame is a fun platform for practice that supports Python.

Edabit has Python challenges that can be good for practicing or self-testing.

You can also practice Python using all of the interactive lessons listed above

How can I practice Python at home?

Install Python on your machine. You can download it directly here , or download a program like Anaconda Individual Edition that makes the process easier. Or you can find an interactive online platform like Dataquest and write code in your browser without installing anything.

Find a good Python project or some practice problems to work on.

Make detailed plans. Scheduling your practice sessions will make you more likely to follow through.

Join an online community. It's always great to get help from a real person. Reddit has great Python communities, and Dataquest's community is great if you're learning Python data skills.

In 30 days, you can definitely learn enough Python to be able to build some cool things. You won't be able to master Python that quickly, but you could learn to complete a specific project or do things like automate some aspects of your job.

Read more about how long it takes to learn Python .

Yes, there are many apps that allow you to practice Python on both iOS and Android. However, this shouldn't be your primary form of practice if you aspire to use Python in your career— it's good to practice installing and working with Python on desktops and laptops since that's how most professional programming work is done.

You can learn the fundamentals of Python in a weekend. If you're diligent, you can learn enough to complete small projects and genuinely impact your work within a month or so. Mastering Python takes much longer, but you don't need to become a master to get things done!

Absolutely, Python remains essential in the AI field. It's foundational for developing AI technologies and continuously updated to integrate with the latest AI advancements. Python libraries like TensorFlow and Keras facilitate efficient building and training of complex AI models. Learning Python also ensures you understand the underlying mechanisms of AI tools, making you a more proficient developer.

More learning resources

Tutorial: time series analysis with pandas, tutorial: using if statements in python.

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Python Programming Challenges

Practice your Python skills with these programming challenges. The tasks are meant to be challenging for beginners. If you find them too difficult, try completing our lessons for beginners first.

All challenges have hints and curated example solutions. They also work on your phone, so you can practice Python on the go.

Click a challenge to start.

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Python Coding Challenges

Write code online and get instant feedback on your progress with automated tests

Fix the error in Python code #1

Fix the error in python code #2, fix the error in python code #3, fix the error in python code #4, fix the error in python code #5, fix the error in python code #6, fix the error in python code #7, fix the error in python code #8, fix the error in python code #9, count the number of odd numbers in a given list, count the number of vowels in a given string, find numbers that are divisible by 3 but not a multiple of 7, drop the first n elements from a sequence, check voting eligibility based on the given age, exclude the first and last items in a list, fix the error in python code #10, fix the error in python code #11, fix the error in python code #12, generate a dictionary of squared numbers, double each number in a list, order a list of strings in alphabetical order, classify the given number, split a string into a list, reverse characters in a string, take the first n elements from a sequence, add an arbitrary number of arguments together and return the sum, count the frequency of each element in the given list, filter a dictionary to include only the key-value pairs where the value is an even number, create a dictionary where the values are the squares of the original values, validate an email addresses, calculate the exponential power of the given number, calculate the factorial of the given number, fix the error in python code #13, group elements by applying a function to each element, interleave an arbitrary number of lists, combine two lists by summing corresponding elements, find common elements between two lists, filter a list to include only the positive numbers, filter a list using the given function, map a function to each element in a list, reduce a list to a single value, sort students by age, square the even numbers in a list, multiply each element in a list by its index, partition a sequence into sublists, extract phone numbers from a string, calculate the product of all elements in the given list, calculate the square root of each element in the given list, subtract all the arguments from the first argument to the function, calculate the sum of squares of all elements in the given list, find unique elements in a given list, count the frequency of words in a file, create a dictionary from two lists, zip an arbitrary number of lists together, apply a function to corresponding elements of multiple lists, check for balanced parentheses, brackets, and braces, function composition by taking two functions as input and returning a composed function, read a csv file and extracts data from specific columns, extract email addresses, find common elements across multiple lists, flatten a tree, transpose a matrix, partial function application, validate a password, calculate the sum of all the numbers in a tree structure, calculate the depth of a tree, find the largest value in a tree.

Logical Python

Effective Python Tutorials

Python Practice Exercises and Challenges with Solutions

Practice exercise.

Welcome to our Python Exercise collection, these exercises are designed for all levels of learners. Whether you are a Beginner, an intermittent developer, or an expert. We have everything for you.

These are the curated set of exercises, each customized to reinforce essential concepts such as loops, functions, and conditionals. These bite-sized challenges are perfect for quick practice sessions, making learning Python a breeze.

Simply choose an exercise, read the instructions, and start coding! Solutions are available to keep you on the right track.

Here are the exercises:

• Python Basics Exercise with Solutions
• Python Input/Output Exercise with Solutions
• Python String Exercise with Solutions
• Python Loop Exercise with Solutions
• Python List Exercise with Solutions
• Python Tuple Exercise with Solutions
• Python Set Exercise with Solutions
• Python Dictionary Exercise with Solutions
• Python Functions Exercise with Solutions
• Python OOPS Exercise with Solutions

Practice Python

Beginner Python exercises

• Why Practice Python?
• Why Chilis?
• Resources for learners

All Exercises

All Solutions

• 1: Character Input Solutions
• 2: Odd Or Even Solutions
• 3: List Less Than Ten Solutions
• 4: Divisors Solutions
• 5: List Overlap Solutions
• 6: String Lists Solutions
• 7: List Comprehensions Solutions
• 8: Rock Paper Scissors Solutions
• 9: Guessing Game One Solutions
• 10: List Overlap Comprehensions Solutions
• 11: Check Primality Functions Solutions
• 12: List Ends Solutions
• 13: Fibonacci Solutions
• 14: List Remove Duplicates Solutions
• 15: Reverse Word Order Solutions
• 16: Password Generator Solutions
• 17: Decode A Web Page Solutions
• 18: Cows And Bulls Solutions
• 19: Decode A Web Page Two Solutions
• 20: Element Search Solutions
• 21: Write To A File Solutions
• 22: Read From File Solutions
• 23: File Overlap Solutions
• 24: Draw A Game Board Solutions
• 25: Guessing Game Two Solutions
• 26: Check Tic Tac Toe Solutions
• 27: Tic Tac Toe Draw Solutions
• 28: Max Of Three Solutions
• 29: Tic Tac Toe Game Solutions
• 30: Pick Word Solutions
• 31: Guess Letters Solutions
• 32: Hangman Solutions
• 33: Birthday Dictionaries Solutions
• 34: Birthday Json Solutions
• 35: Birthday Months Solutions
• 36: Birthday Plots Solutions
• 37: Functions Refactor Solution
• 38: f Strings Solution
• 39: Character Input Datetime Solution
• 40: Error Checking Solution

Python Practice for Beginners: 15 Hands-On Problems

• online practice

Want to put your Python skills to the test? Challenge yourself with these 15 Python practice exercises taken directly from our Python courses!

There’s no denying that solving Python exercises is one of the best ways to practice and improve your Python skills . Hands-on engagement with the language is essential for effective learning. This is exactly what this article will help you with: we've curated a diverse set of Python practice exercises tailored specifically for beginners seeking to test their programming skills.

These Python practice exercises cover a spectrum of fundamental concepts, all of which are covered in our Python Data Structures in Practice and Built-in Algorithms in Python courses. Together, both courses add up to 39 hours of content. They contain over 180 exercises for you to hone your Python skills. In fact, the exercises in this article were taken directly from these courses!

In these Python practice exercises, we will use a variety of data structures, including lists, dictionaries, and sets. We’ll also practice basic programming features like functions, loops, and conditionals. Every exercise is followed by a solution and explanation. The proposed solution is not necessarily the only possible answer, so try to find your own alternative solutions. Let’s get right into it!

Python Practice Problem 1: Average Expenses for Each Semester

John has a list of his monthly expenses from last year:

He wants to know his average expenses for each semester. Using a for loop, calculate John’s average expenses for the first semester (January to June) and the second semester (July to December).

Explanation

We initialize two variables, first_semester_total and second_semester_total , to store the total expenses for each semester. Then, we iterate through the monthly_spending list using enumerate() , which provides both the index and the corresponding value in each iteration. If you have never heard of enumerate() before – or if you are unsure about how for loops in Python work – take a look at our article How to Write a for Loop in Python .

Within the loop, we check if the index is less than 6 (January to June); if so, we add the expense to first_semester_total . If the index is greater than 6, we add the expense to second_semester_total .

After iterating through all the months, we calculate the average expenses for each semester by dividing the total expenses by 6 (the number of months in each semester). Finally, we print out the average expenses for each semester.

Python Practice Problem 2: Who Spent More?

John has a friend, Sam, who also kept a list of his expenses from last year:

They want to find out how many months John spent more money than Sam. Use a for loop to compare their expenses for each month. Keep track of the number of months where John spent more money.

We initialize the variable months_john_spent_more with the value zero. Then we use a for loop with range(len()) to iterate over the indices of the john_monthly_spending list.

Within the loop, we compare John's expenses with Sam's expenses for the corresponding month using the index i . If John's expenses are greater than Sam's for a particular month, we increment the months_john_spent_more variable. Finally, we print out the total number of months where John spent more money than Sam.

Python Practice Problem 3: All of Our Friends

Paul and Tina each have a list of their respective friends:

Combine both lists into a single list that contains all of their friends. Don’t include duplicate entries in the resulting list.

There are a few different ways to solve this problem. One option is to use the + operator to concatenate Paul and Tina's friend lists ( paul_friends and tina_friends ). Afterwards, we convert the combined list to a set using set() , and then convert it back to a list using list() . Since sets cannot have duplicate entries, this process guarantees that the resulting list does not hold any duplicates. Finally, we print the resulting combined list of friends.

If you need a refresher on Python sets, check out our in-depth guide to working with sets in Python or find out the difference between Python sets, lists, and tuples .

Python Practice Problem 4: Find the Common Friends

Now, let’s try a different operation. We will start from the same lists of Paul’s and Tina’s friends:

In this exercise, we’ll use a for loop to get a list of their common friends.

For this problem, we use a for loop to iterate through each friend in Paul's list ( paul_friends ). Inside the loop, we check if the current friend is also present in Tina's list ( tina_friends ). If it is, it is added to the common_friends list. This approach guarantees that we test each one of Paul’s friends against each one of Tina’s friends. Finally, we print the resulting list of friends that are common to both Paul and Tina.

Python Practice Problem 5: Find the Basketball Players

You work at a sports club. The following sets contain the names of players registered to play different sports:

How can you obtain a set that includes the players that are only registered to play basketball (i.e. not registered for football or volleyball)?

This type of scenario is exactly where set operations shine. Don’t worry if you never heard about them: we have an article on Python set operations with examples to help get you up to speed.

First, we use the | (union) operator to combine the sets of football and volleyball players into a single set. In the same line, we use the - (difference) operator to subtract this combined set from the set of basketball players. The result is a set containing only the players registered for basketball and not for football or volleyball.

If you prefer, you can also reach the same answer using set methods instead of the operators:

It’s essentially the same operation, so use whichever you think is more readable.

Python Practice Problem 6: Count the Votes

Let’s try counting the number of occurrences in a list. The list below represent the results of a poll where students were asked for their favorite programming language:

Use a dictionary to tally up the votes in the poll.

In this exercise, we utilize a dictionary ( vote_tally ) to count the occurrences of each programming language in the poll results. We iterate through the poll_results list using a for loop; for each language, we check if it already is in the dictionary. If it is, we increment the count; otherwise, we add the language to the dictionary with a starting count of 1. This approach effectively tallies up the votes for each programming language.

If you want to learn more about other ways to work with dictionaries in Python, check out our article on 13 dictionary examples for beginners .

Python Practice Problem 7: Sum the Scores

Three friends are playing a game, where each player has three rounds to score. At the end, the player whose total score (i.e. the sum of each round) is the highest wins. Consider the scores below (formatted as a list of tuples):

Create a dictionary where each player is represented by the dictionary key and the corresponding total score is the dictionary value.

This solution is similar to the previous one. We use a dictionary ( total_scores ) to store the total scores for each player in the game. We iterate through the list of scores using a for loop, extracting the player's name and score from each tuple. For each player, we check if they already exist as a key in the dictionary. If they do, we add the current score to the existing total; otherwise, we create a new key in the dictionary with the initial score. At the end of the for loop, the total score of each player will be stored in the total_scores dictionary, which we at last print.

Python Practice Problem 8: Calculate the Statistics

Given any list of numbers in Python, such as …

 … write a function that returns a tuple containing the list’s maximum value, sum of values, and mean value.

We create a function called calculate_statistics to calculate the required statistics from a list of numbers. This function utilizes a combination of max() , sum() , and len() to obtain these statistics. The results are then returned as a tuple containing the maximum value, the sum of values, and the mean value.

The function is called with the provided list and the results are printed individually.

Python Practice Problem 9: Longest and Shortest Words

Given the list of words below ..

… find the longest and the shortest word in the list.

To find the longest and shortest word in the list, we initialize the variables longest_word and shortest_word as the first word in the list. Then we use a for loop to iterate through the word list. Within the loop, we compare the length of each word with the length of the current longest and shortest words. If a word is longer than the current longest word, it becomes the new longest word; on the other hand, if it's shorter than the current shortest word, it becomes the new shortest word. After iterating through the entire list, the variables longest_word and shortest_word will hold the corresponding words.

There’s a catch, though: what happens if two or more words are the shortest? In that case, since the logic used is to overwrite the shortest_word only if the current word is shorter – but not of equal length – then shortest_word is set to whichever shortest word appears first. The same logic applies to longest_word , too. If you want to set these variables to the shortest/longest word that appears last in the list, you only need to change the comparisons to <= (less or equal than) and >= (greater or equal than), respectively.

If you want to learn more about Python strings and what you can do with them, be sure to check out this overview on Python string methods .

Python Practice Problem 10: Filter a List by Frequency

Given a list of numbers …

… create a new list containing only the numbers that occur at least three times in the list.

Here, we use a for loop to iterate through the number_list . In the loop, we use the count() method to check if the current number occurs at least three times in the number_list . If the condition is met, the number is appended to the filtered_list .

After the loop, the filtered_list contains only numbers that appear three or more times in the original list.

Python Practice Problem 11: The Second-Best Score

You’re given a list of students’ scores in no particular order:

Find the second-highest score in the list.

This one is a breeze if we know about the sort() method for Python lists – we use it here to sort the list of exam results in ascending order. This way, the highest scores come last. Then we only need to access the second to last element in the list (using the index -2 ) to get the second-highest score.

Python Practice Problem 12: Check If a List Is Symmetrical

Given the lists of numbers below …

… create a function that returns whether a list is symmetrical. In this case, a symmetrical list is a list that remains the same after it is reversed – i.e. it’s the same backwards and forwards.

Reversing a list can be achieved by using the reverse() method. In this solution, this is done inside the is_symmetrical function.

To avoid modifying the original list, a copy is created using the copy() method before using reverse() . The reversed list is then compared with the original list to determine if it’s symmetrical.

The remaining code is responsible for passing each list to the is_symmetrical function and printing out the result.

Python Practice Problem 13: Sort By Number of Vowels

Given this list of strings …

… sort the list by the number of vowels in each word. Words with fewer vowels should come first.

Whenever we need to sort values in a custom order, the easiest approach is to create a helper function. In this approach, we pass the helper function to Python’s sorted() function using the key parameter. The sorting logic is defined in the helper function.

In the solution above, the custom function count_vowels uses a for loop to iterate through each character in the word, checking if it is a vowel in a case-insensitive manner. The loop increments the count variable for each vowel found and then returns it. We then simply pass the list of fruits to sorted() , along with the key=count_vowels argument.

Python Practice Problem 14: Sorting a Mixed List

Imagine you have a list with mixed data types: strings, integers, and floats:

Typically, you wouldn’t be able to sort this list, since Python cannot compare strings to numbers. However, writing a custom sorting function can help you sort this list.

Create a function that sorts the mixed list above using the following logic:

• If the element is a string, the length of the string is used for sorting.
• If the element is a number, the number itself is used.

As proposed in the exercise, a custom sorting function named custom_sort is defined to handle the sorting logic. The function checks whether each element is a string or a number using the isinstance() function. If the element is a string, it returns the length of the string for sorting; if it's a number (integer or float), it returns the number itself.

The sorted() function is then used to sort the mixed_list using the logic defined in the custom sorting function.

If you’re having a hard time wrapping your head around custom sort functions, check out this article that details how to write a custom sort function in Python .

Python Practice Problem 15: Filter and Reorder

Given another list of strings, such as the one below ..

.. create a function that does two things: filters out any words with three or fewer characters and sorts the resulting list alphabetically.

Here, we define filter_and_sort , a function that does both proposed tasks.

First, it uses a for loop to filter out words with three or fewer characters, creating a filtered_list . Then, it sorts the filtered list alphabetically using the sorted() function, producing the final sorted_list .

The function returns this sorted list, which we print out.

Want Even More Python Practice Problems?

We hope these exercises have given you a bit of a coding workout. If you’re after more Python practice content, head straight for our courses on Python Data Structures in Practice and Built-in Algorithms in Python , where you can work on exciting practice exercises similar to the ones in this article.

Additionally, you can check out our articles on Python loop practice exercises , Python list exercises , and Python dictionary exercises . Much like this article, they are all targeted towards beginners, so you should feel right at home!

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Python Programming

Python Basic Exercise for Beginners

Updated on:  August 29, 2024 | 498 Comments

This essential Python exercise helps Python beginners learn necessary Python skills quickly.

Immerse yourself in the practice of Python’s foundational concepts, such as loops, control flow, data types, operators, list, strings, input-output, and built-in functions. This beginner’s exercise is sure to elevate your understanding of Python.

Also, See :

• Python Quizzes : Solve quizzes to test your knowledge of fundamental concepts.
• Python Basics : Learn the basics to solve this exercise.

What questions are included in this Python fundamental exercise?

• The exercise contains  15 Python programs to solve , ranging from beginner to intermediate difficulty.
• The hints and solutions are provided for each question.
• Tips and essential learning resources accompany each question . These will assist you in solving the exercise and empower you with the knowledge to tackle similar problems in the future, boosting your confidence and capability. As you progress, you’ll become more familiar with the basics of Python.

Use Online Code Editor to solve exercises.

This Python exercise covers questions on the following topics :

• Python for loop and while loop
• Python list , set , tuple , dictionary , input, and output

Also, try to solve the basic Python Quiz for beginners

Exercise 1: Calculate the multiplication and sum of two numbers

Given two integer numbers, write a Python code to return their product only if the product is equal to or lower than 1000. Otherwise, return their sum.

Expected Output :

• Accept user input in Python
• Calculate an Average in Python
• Create a function that will take two numbers as parameters
• Next, Inside a function, multiply two numbers and save their product in a product variable
• Next, use the if condition to check if the product >1000 . If yes, return the product
• Otherwise, use the else block to calculate the sum of two numbers and return it.

Exercise 2: Print the Sum of a Current Number and a Previous number

Write a Python code to iterate the first 10 numbers, and in each iteration, print the sum of the current and previous number.

Reference article for help :

• Python range() function
• Calculate sum and average in Python
• Create a  variable  called  previous_num  and assigning it to 0
• Next, iterate through the first 10 numbers using the for loop  and  range()  function
• Next, display the current number ( i ), the previous number, and the addition of both numbers in each iteration of a loop
• Finally, you need to update the previous_num for the next iteration. To do this, assign the value of the current number to the previous number ( previous_num = i).

Exercise 3: Print characters present at an even index number

Write a Python code to accept a string from the user and display characters present at an even index number.

For example, str = "PYnative" . so your code should display ‘P’, ‘n’, ‘t’, ‘v’.

Reference article for help: Python Input and Output

• Use the Python input() function to accept a string from a user.
• Calculate the length of the string using the len() function
• Next, iterate characters of a string using the loop and range() function.
• Use start = 0, stop = len(s)-1, and step =2. the step is 2 because we want only even index numbers
• In each iteration of a loop, use s[i] to print characters present at the current even index number

Solution 1 :

Solution 2 : Using list slicing

Exercise 4: Remove first n characters from a string

Write a Python code to remove characters from a string from 0 to n and return a new string.

For Example:

• remove_chars("PYnative", 4) so output must be tive . Here, you need to remove the first four characters from a string.
• remove_chars("PYnative", 2) so output must be native . Here, you need to remove the first two characters from a string.

Note : n must be less than the length of the string.

Use string slicing to get a substring. For example, remove the first four characters using s[4:] .

Also, try to solve  Python string exercises

Exercise 5: Check if the first and last numbers of a list are the same

Write a code to return True if the list’s first and last numbers are the same. If the numbers are different, return False .

Exercise 6: Display numbers divisible by 5

Write a Python code to display numbers from a list divisible by 5

Also, try to solve  Python list Exercise

Exercise 7: Find the number of occurrences of a substring in a string

Write a Python code to find how often the substring “ Emma ” appears in the given string.

Use string method count() .

Solution 1 : Use the count() method

Solution 2 : Without the string method

Exercise 8: Print the following pattern

Hint : Print Pattern using for loop

Exercise 9: Check Palindrome Number

Write a Python code to check if the given number is palindrome. A palindrome number is a number that is the same after reverse. For example, 545 is the palindrome number .

• Reverse the given number and save it in a different variable
• Use the if condition to check if the original and reverse numbers are identical. If yes, return True .

Exercise 10: Merge two lists using the following condition

Given two lists of numbers, write a Python code to create a new list such that the latest list should contain odd numbers from the first list and even numbers from the second list .

• Create an empty list named result_list
• Iterate the first list using a for loop
• In each iteration check if the current number is odd using the num % 2 != 0 formula. If the current number is odd, add it to the result list
• Now, Iterate the second list using a loop.
• In each iteration check if the current number is even using the num % 2 == 0 formula. If the current number is even, add it to the result list.
• Print the result list.

Note: Try to solve the Python list exercises

Exercise 11: Get each digit from a number in the reverse order.

For example, If the given integer number is 7536 , the output shall be “ 6 3 5 7 “, with a space separating the digits.

Use while loop

Exercise 12: Calculate income tax

Calculate income tax for the given income by adhering to the rules below

For example, suppose the income is 45000, and the income tax payable is

10000*0% + 10000*10%  + 25000*20% = $6000.

Exercise 13: Print multiplication table from 1 to 10

See : How to use nested loops in Python

• Create the outer for loop to iterate numbers from 1 to 10. Thus, the outer loop’s total number of iterations is 10.
• Create an inner loop to iterate 10 times.
• For each outer loop iteration, the inner loop will execute 10 times.
• The number is 1 in the first iteration of the outer loop. In the next, it is 2, and so on until it reaches 10.
• In each iteration of an inner loop, we perform a simple calculation: the multiplication of two numbers. (current outer number and current inner number)

Exercise 14: Print a downward half-pyramid pattern of stars

Exercise 15: get an int value of base raises to the power of exponent.

Write a function called exponent(base, exp) that returns an int value of base raises to the power of exp.

Note here exp is a non-negative integer, and the base is an integer.

Expected output

I want to hear from you. What do you think of this essential exercise? If you have better alternative answers to the above questions, please help others by commenting on this exercise.

I have shown only 15 questions in this exercise because we have Topic-specific exercises to cover each topic exercise in detail. Please refer to all Python exercises .

Did you find this page helpful? Let others know about it. Sharing helps me continue to create free Python resources.

About Vishal

I’m  Vishal Hule , the Founder of PYnative.com. As a Python developer, I enjoy assisting students, developers, and learners. Follow me on  Twitter .

Related Tutorial Topics:

Python exercises and quizzes.

Free coding exercises and quizzes cover Python basics, data structure, data analytics, and more.

• 15+ Topic-specific Exercises and Quizzes
• Each Exercise contains 10 questions
• Each Quiz contains 12-15 MCQ

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Python Exercise with Practice Questions and Solutions

Python Exercise: Practice makes you perfect in everything. This proverb always proves itself correct. Just like this, if you are a Python learner, then regular practice of Python exercises makes you more confident and sharpens your skills. So, to test your skills, go through these Python exercises with solutions.

Python is a widely used general-purpose high-level language that can be used for many purposes like creating GUI, web Scraping, web development, etc. You might have seen various Python tutorials that explain the concepts in detail but that might not be enough to get hold of this language. The best way to learn is by practising it more and more.

The best thing about this Python practice exercise is that it helps you learn Python using sets of detailed programming questions from basic to advanced. It covers questions on core Python concepts as well as applications of Python in various domains. So if you are at any stage like beginner, intermediate or advanced this Python practice set will help you to boost your programming skills in Python.

• List of Python Programming Exercises

In the below section, we have gathered chapter-wise Python exercises with solutions. So, scroll down to the relevant topics and try to solve the Python program practice set.

Table of Content

Python List Exercises

Python string exercises, python tuple exercises, python dictionary exercises, python set exercises, python matrix exercises, python functions exercises, python lambda exercises.

• Python Pattern printing Exercises

Python DateTime Exercises

Python oops exercises, python regex exercises, python linkedlist exercises, python searching exercises, python sorting exercises, python dsa exercises, python file handling exercises, python csv exercises, python json exercises, python os module exercises, python tkinter exercises, numpy exercises, pandas exercises, python web scraping exercises, python selenium exercises.

In this section, we have compiled a variety of Python list exercises that range from basic to advanced levels. These exercises are designed to help you master the fundamentals of Python lists, including list creation, indexing, slicing, and common operations like appending, inserting, and removing elements.

• Python program to interchange first and last elements in a list
• Python program to swap two elements in a list
• Python | Ways to find length of list
• Maximum of two numbers in Python
• Minimum of two numbers in Python

>> More Programs on List

In this section, we provide a variety of Python string exercises designed to enhance your understanding of string manipulation and operations. Explore these exercises and upsacle your Python programming skills.

• Python program to check whether the string is Symmetrical or Palindrome
• Reverse words in a given String in Python
• Ways to remove i’th character from string in Python
• Find length of a string in python (4 ways)
• Python program to print even length words in a string

>> More Programs on String

Here, you’ll find a range of Python tuple exercises designed to help you understand and master this essential data structure. Tuples are immutable sequences used to store collections of items, and they’re a fundamental part of Python programming.

• Python program to Find the size of a Tuple
• Python – Maximum and Minimum K elements in Tuple
• Python – Sum of tuple elements
• Python – Row-wise element Addition in Tuple Matrix
• Create a list of tuples from given list having number and its cube in each tuple

>> More Programs on Tuple

In this section, you’ll find a variety of Python dictionary exercises designed to help you master the use of dictionaries, one of Python’s most powerful and versatile data structures.

• Python | Sort Python Dictionaries by Key or Value
• Handling missing keys in Python dictionaries
• Python dictionary with keys having multiple inputs
• Python program to find the sum of all items in a dictionary
• Python program to find the size of a Dictionary

>> More Programs on Dictionary

This section offers a range of Python set exercises that will help you build a strong understanding of set operations in Python. You’ll practice adding and removing elements, performing operations like union, intersection, and difference, and using set comprehensions.

• Find the size of a Set in Python
• Iterate over a set in Python
• Python – Maximum and Minimum in a Set
• Python – Remove items from Set
• Python – Check if two lists have atleast one element common

>> More Programs on Sets

Here, in this section you’ll find a collection of Python matrix exercises tailored for beginners and advanced Python programmers. These exercises focus on essential skills such as creating and manipulating matrices, performing operations like addition, subtraction, multiplication, and more.

• Python – Assigning Subsequent Rows to Matrix first row elements
• Adding and Subtracting Matrices in Python
• Python – Group similar elements into Matrix
• Create an n x n square matrix, where all the sub-matrix have the sum of opposite corner elements as even

>> More Programs on Matrices

This section offers a variety of exercises focused on Python functions to help you master this essential programming concept. You’ll learn how to define functions, work with parameters and return values, and explore advanced topics like lambda functions, decorators, and recursion.

• How to get list of parameters name from a function in Python?
• How to Print Multiple Arguments in Python?
• Python program to find the power of a number using recursion
• Sorting objects of user defined class in Python
• Functions that accept variable length key value pair as arguments

>> More Programs on Functions

In this section, we’ve compiled a series of exercises focused on Python’s lambda functions, which allow you to write small, anonymous functions with concise syntax. These exercises will help you understand how to use lambda functions for quick data manipulation, sorting, filtering, and mapping operations.

• Lambda with if but without else in Python
• Python | Sorting string using order defined by another string
• Python | Find fibonacci series upto n using lambda
• Python program to count Even and Odd numbers in a List
• Python | Find the Number Occurring Odd Number of Times using Lambda expression and reduce function

>> More Programs on Lambda

• Program to print half Diamond star pattern
• Programs for printing pyramid patterns in Python
• Program to print the diamond shape
• Python | Print an Inverted Star Pattern
• Python Program to print digit pattern

>> More Programs on Python Pattern Printing

Enhance your Python skills by diving into various DateTime exercises that focus on handling dates and times effectively. These exercises will teach you how to use the datetime module to format dates, calculate time differences, manage time zones, and build time-sensitive applications.

• Python program to get Current Time
• Get Yesterday’s date using Python
• Python program to print current year, month and day
• Python – Convert day number to date in particular year
• Get Current Time in different Timezone using Python

>> More Programs on DateTime

Here in this practice section, you’ll find exercises focused on Object-Oriented Programming (OOP) concepts in Python. These exercises are designed to help you understand and implement key OOP principles such as classes, objects, inheritance, polymorphism, encapsulation, and abstraction.

• Python program to build flashcard using class in Python
• Shuffle a deck of card with OOPS in Python
• How to create an empty class in Python?
• Student management system in Python

>> More Programs on Python OOPS

Python Regex exercises to help you master the art of pattern matching and text manipulation. Regular expressions, or Regex, are powerful tools used to search, match, and manipulate strings based on specific patterns.

• Python program to find the type of IP Address using Regex
• Python program to find Indices of Overlapping Substrings
• Python program to extract Strings between HTML Tags
• Python – Check if String Contain Only Defined Characters using Regex
• Python program to find files having a particular extension using RegEx

>> More Programs on Python Regex

In this section, we’ve compiled a series of exercises focused on implementing and manipulating linked lists using Python. These exercises cover various operations, such as inserting nodes, deleting nodes, reversing linked lists, and detecting cycles, allowing you to practice and master linked list concepts.

• Python program to Search an Element in a Circular Linked List
• Pretty print Linked List in Python
• Python | Stack using Doubly Linked List
• Python | Queue using Doubly Linked List
• Python program to find middle of a linked list using one traversal

>> More Programs on Linked Lists

This section offers a range of exercises designed to help you master searching algorithms in Python. You’ll learn how to implement techniques like linear search and binary search, as well as more advanced methods such as interpolation and exponential search.

• Python Program for Linear Search
• Python Program for Binary Search (Recursive and Iterative)
• Python Program for Anagram Substring Search (Or Search for all permutations)

>> More Programs on Python Searching

This section provides a collection of exercises to help you practice and understand sorting in Python. You’ll explore various sorting algorithms, like bubble sort, merge sort, quicksort, and others, each with its unique approach to arranging data.

• Python Program for Bubble Sort
• Python Program for QuickSort
• Python Program for Insertion Sort
• Python Program for Selection Sort
• Python Program for Heap Sort

>> More Programs on Python Sorting

Strengthen your Python skills with Data Structures and Algorithms (DSA) exercises tailored to help you master the fundamental concepts of programming. These exercises cover a wide range of topics, including arrays, linked lists, stacks, queues, trees, graphs, and sorting algorithms, providing a hands-on approach to learning.

• Python program to reverse a stack
• Multithreaded Priority Queue in Python
• Check whether the given string is Palindrome using Stack
• Program to Calculate the Edge Cover of a Graph
• Python Program for N Queen Problem

>> More Programs on Python DSA

In this section, you’ll find a variety of exercises focused on Python file handling to help you master reading from and writing to files. These exercises will guide you through the essentials, such as opening, reading, writing, closing files and more.

• Read content from one file and write it into another file
• Write a dictionary to a file in Python
• How to check file size in Python?
• Find the most repeated word in a text file
• How to read specific lines from a File in Python?

>> More Programs on Python File Handling

Working with CSV (Comma-Separated Values) files is a fundamental skill in data handling and analysis with Python. These exercises are designed to help you learn how to read, write, and manipulate CSV files using Python’s built-in csv module and libraries like pandas.

• Update column value of CSV in Python
• How to add a header to a CSV file in Python?
• Get column names from CSV using Python
• Writing data from a Python List to CSV row-wise
• Convert multiple JSON files to CSV Python

>> More Programs on Python CSV

In this section, we provide a variety of exercises to help you master JSON (JavaScript Object Notation) in Python. JSON is a popular data format used for exchanging information between web clients and servers.

• Convert class object to JSON in Python
• Convert JSON data Into a Custom Python Object
• Flattening JSON objects in Python
• Convert CSV to JSON using Python

>> More Programs on Python JSON

Here in this section, we have compiled a list of exercises that will help you practice using the Python OS module to create, delete, and navigate directories, manage files, and interact with system processes.

• How to get file creation and modification date or time in Python?
• Menu Driven Python program for opening the required software Application
• Python Script to change name of a file to its timestamp
• Kill a Process by name using Python
• Finding the largest file in a directory using Python

>> More Programs on OS Module

Python’s Tkinter library is a powerful tool for creating graphical user interfaces (GUIs). These exercises are designed to help you learn the basics of GUI development, such as creating buttons, labels, text boxes, and handling events.

• Python | Create a GUI Marksheet using Tkinter
• Python | ToDo GUI Application using Tkinter
• Python | GUI Calendar using Tkinter
• File Explorer in Python using Tkinter
• Visiting Card Scanner GUI Application using Python

>> More Programs on Python Tkinter

Enhance your Python programming skills by diving into NumPy exercises designed to teach you the fundamentals of this powerful library. NumPy is essential for numerical computing in Python, providing support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on them.

• How to create an empty and a full NumPy array?
• Create a Numpy array filled with all zeros
• Create a Numpy array filled with all ones
• Replace NumPy array elements that doesn’t satisfy the given condition
• Get the maximum value from given matrix

>> More Programs on NumPy

In this section, you’ll find a variety of exercises designed to help you master the Pandas library in Python, a powerful tool for data manipulation and analysis. These exercises range from basic operations like data filtering, sorting, and grouping.

• Make a Pandas DataFrame with two-dimensional list | Python
• How to iterate over rows in Pandas Dataframe
• Create a pandas column using for loop
• Create a Pandas Series from array
• Pandas | Basic of Time Series Manipulation

>> More Programs on Python Pandas

Explore a variety of Python web scraping exercises that will help you learn how to extract data from websites efficiently.

• How to extract youtube data in Python?
• How to Download All Images from a Web Page in Python?
• Test the given page is found or not on the server Using Python
• How to Extract Wikipedia Data in Python?
• How to extract paragraph from a website and save it as a text file?

>> More Programs on Web Scraping

Here you’ll find exercises that help you master web automation using Selenium, a powerful tool for controlling web browsers through Python scripts.

• Download File in Selenium Using Python
• Bulk Posting on Facebook Pages using Selenium
• Google Maps Selenium automation using Python
• Count total number of Links In Webpage Using Selenium In Python
• Extract Data From JustDial using Selenium

>> More Programs on Python Selenium

• Number guessing game in Python
• 2048 Game in Python
• Get Live Weather Desktop Notifications Using Python
• 8-bit game using pygame
• Tic Tac Toe GUI In Python using PyGame

>> More Projects in Python

In closing, we just want to say that the practice or solving Python problems always helps to clear your core concepts and programming logic. Hence, we have designed this Python exercises after deep research so that one can easily enhance their skills and logic abilities.

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Problem Solving with Algorithms and Data Structures using Python ¶

By Brad Miller and David Ranum, Luther College

There is a wonderful collection of YouTube videos recorded by Gerry Jenkins to support all of the chapters in this text.

• 1.1. Objectives
• 1.2. Getting Started
• 1.3. What Is Computer Science?
• 1.4. What Is Programming?
• 1.5. Why Study Data Structures and Abstract Data Types?
• 1.6. Why Study Algorithms?
• 1.7. Review of Basic Python
• 1.8.1. Built-in Atomic Data Types
• 1.8.2. Built-in Collection Data Types
• 1.9.1. String Formatting
• 1.10. Control Structures
• 1.11. Exception Handling
• 1.12. Defining Functions
• 1.13.1. A Fraction Class
• 1.13.2. Inheritance: Logic Gates and Circuits
• 1.14. Summary
• 1.15. Key Terms
• 1.16. Discussion Questions
• 1.17. Programming Exercises
• 2.1.1. A Basic implementation of the MSDie class
• 2.2. Making your Class Comparable
• 3.1. Objectives
• 3.2. What Is Algorithm Analysis?
• 3.3. Big-O Notation
• 3.4.1. Solution 1: Checking Off
• 3.4.2. Solution 2: Sort and Compare
• 3.4.3. Solution 3: Brute Force
• 3.4.4. Solution 4: Count and Compare
• 3.5. Performance of Python Data Structures
• 3.7. Dictionaries
• 3.8. Summary
• 3.9. Key Terms
• 3.10. Discussion Questions
• 3.11. Programming Exercises
• 4.1. Objectives
• 4.2. What Are Linear Structures?
• 4.3. What is a Stack?
• 4.4. The Stack Abstract Data Type
• 4.5. Implementing a Stack in Python
• 4.6. Simple Balanced Parentheses
• 4.7. Balanced Symbols (A General Case)
• 4.8. Converting Decimal Numbers to Binary Numbers
• 4.9.1. Conversion of Infix Expressions to Prefix and Postfix
• 4.9.2. General Infix-to-Postfix Conversion
• 4.9.3. Postfix Evaluation
• 4.10. What Is a Queue?
• 4.11. The Queue Abstract Data Type
• 4.12. Implementing a Queue in Python
• 4.13. Simulation: Hot Potato
• 4.14.1. Main Simulation Steps
• 4.14.2. Python Implementation
• 4.14.3. Discussion
• 4.15. What Is a Deque?
• 4.16. The Deque Abstract Data Type
• 4.17. Implementing a Deque in Python
• 4.18. Palindrome-Checker
• 4.19. Lists
• 4.20. The Unordered List Abstract Data Type
• 4.21.1. The Node Class
• 4.21.2. The Unordered List Class
• 4.22. The Ordered List Abstract Data Type
• 4.23.1. Analysis of Linked Lists
• 4.24. Summary
• 4.25. Key Terms
• 4.26. Discussion Questions
• 4.27. Programming Exercises
• 5.1. Objectives
• 5.2. What Is Recursion?
• 5.3. Calculating the Sum of a List of Numbers
• 5.4. The Three Laws of Recursion
• 5.5. Converting an Integer to a String in Any Base
• 5.6. Stack Frames: Implementing Recursion
• 5.7. Introduction: Visualizing Recursion
• 5.8. Sierpinski Triangle
• 5.9. Complex Recursive Problems
• 5.10. Tower of Hanoi
• 5.11. Exploring a Maze
• 5.12. Dynamic Programming
• 5.13. Summary
• 5.14. Key Terms
• 5.15. Discussion Questions
• 5.16. Glossary
• 5.17. Programming Exercises
• 6.1. Objectives
• 6.2. Searching
• 6.3.1. Analysis of Sequential Search
• 6.4.1. Analysis of Binary Search
• 6.5.1. Hash Functions
• 6.5.2. Collision Resolution
• 6.5.3. Implementing the Map Abstract Data Type
• 6.5.4. Analysis of Hashing
• 6.6. Sorting
• 6.7. The Bubble Sort
• 6.8. The Selection Sort
• 6.9. The Insertion Sort
• 6.10. The Shell Sort
• 6.11. The Merge Sort
• 6.12. The Quick Sort
• 6.13. Summary
• 6.14. Key Terms
• 6.15. Discussion Questions
• 6.16. Programming Exercises
• 7.1. Objectives
• 7.2. Examples of Trees
• 7.3. Vocabulary and Definitions
• 7.4. List of Lists Representation
• 7.5. Nodes and References
• 7.6. Parse Tree
• 7.7. Tree Traversals
• 7.8. Priority Queues with Binary Heaps
• 7.9. Binary Heap Operations
• 7.10.1. The Structure Property
• 7.10.2. The Heap Order Property
• 7.10.3. Heap Operations
• 7.11. Binary Search Trees
• 7.12. Search Tree Operations
• 7.13. Search Tree Implementation
• 7.14. Search Tree Analysis
• 7.15. Balanced Binary Search Trees
• 7.16. AVL Tree Performance
• 7.17. AVL Tree Implementation
• 7.18. Summary of Map ADT Implementations
• 7.19. Summary
• 7.20. Key Terms
• 7.21. Discussion Questions
• 7.22. Programming Exercises
• 8.1. Objectives
• 8.2. Vocabulary and Definitions
• 8.3. The Graph Abstract Data Type
• 8.4. An Adjacency Matrix
• 8.5. An Adjacency List
• 8.6. Implementation
• 8.7. The Word Ladder Problem
• 8.8. Building the Word Ladder Graph
• 8.9. Implementing Breadth First Search
• 8.10. Breadth First Search Analysis
• 8.11. The Knight’s Tour Problem
• 8.12. Building the Knight’s Tour Graph
• 8.13. Implementing Knight’s Tour
• 8.14. Knight’s Tour Analysis
• 8.15. General Depth First Search
• 8.16. Depth First Search Analysis
• 8.17. Topological Sorting
• 8.18. Strongly Connected Components
• 8.19. Shortest Path Problems
• 8.20. Dijkstra’s Algorithm
• 8.21. Analysis of Dijkstra’s Algorithm
• 8.22. Prim’s Spanning Tree Algorithm
• 8.23. Summary
• 8.24. Key Terms
• 8.25. Discussion Questions
• 8.26. Programming Exercises

Acknowledgements ¶

We are very grateful to Franklin Beedle Publishers for allowing us to make this interactive textbook freely available. This online version is dedicated to the memory of our first editor, Jim Leisy, who wanted us to “change the world.”

Indices and tables ¶

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Python Quizzes

Check your Python learning progress and take your skills to the next level with Real Python’s interactive quizzes.

We created these online Python quizzes as a fun way for you to check your learning progress and to test your skills.

Each quiz takes you through a series of questions. Some of them are multiple choice, some will ask you to type in an answer, and some will require you to write actual Python code. As you make your way through each quiz, it keeps score of which questions you answered correctly.

At the end of each quiz you receive a grade based on your result. If you don’t score 100% on your first try—don’t fret! These quizzes are meant to challenge you and it’s expected that you go through them several times, improving your score with each run.

Browse Python Quizzes : Ready to test your Python skills? Pick a quiz below and jump right in, or search and filter quizzes by topic and skill level .

Interactive Quiz

A Practical Introduction to Web Scraping in Python

In this quiz, you'll test your understanding of web scraping in Python. Web scraping is a powerful tool for data collection and analysis. By working through this quiz, you'll revisit how to parse website data using string methods, regular expressions, and HTML parsers, as well as how to interact with forms and other website components.

Asynchronous Iterators and Iterables in Python

Take this quiz to test your understanding of how to create and use Python async iterators and iterables in the context of asynchronous code.

Async IO in Python: A Complete Walkthrough

In this quiz, you'll test your understanding of async IO in Python. With this knowledge, you'll be able to understand the language-agnostic paradigm of asynchronous IO, use the async/await keywords to define coroutines, and use the asyncio package to run and manage coroutines.

Basic Data Types in Python: A Quick Exploration

Take this quiz to test your understanding of the basic data types that are built into Python, like numbers, strings, bytes, and Booleans.

Beautiful Soup: Build a Web Scraper With Python

In this quiz, you'll revisit the main steps of the web scraping process. You'll learn how to write a script that uses Python's Requests library to scrape data from a website. You'll also use Beautiful Soup to extract the specific pieces of information that you're interested in.

Build a Blog Using Django, GraphQL, and Vue

In this quiz, you'll test your understanding of building a Django blog back end and a Vue front end, using GraphQL to communicate between them. This will help you decouple your back end and front end, handle data persistence in the API, and display the data in a single-page app (SPA).

Build a Guitar Synthesizer

In this quiz, you'll test your understanding of what it takes to build a guitar synthesizer in Python. By working through this quiz, you'll revisit a few key concepts from music theory and sound synthesis.

Build Command-Line Interfaces With Python's argparse

In this quiz, you'll test your understanding of creating command-line interfaces (CLIs) in Python using the argparse module. This knowledge is essential for creating user-friendly command-line apps, which are common in development, data science, and systems administration.

Choosing the Best Font for Programming

In this quiz, you'll test your understanding of how to choose the best font for your daily programming. You'll get questions about the technicalities and features to consider when choosing a programming font and refresh your knowledge about how to spot a high-quality coding font.

Context Managers and Python's with Statement

In this quiz, you'll assess your understanding of the Python with statement and context managers. By mastering these concepts, you'll be able to write more expressive code and manage system resources more effectively, avoiding resource leaks and ensuring proper setup and teardown of external resources.

Creating Great README Files for Your Python Projects

Take this quiz to test your understanding of how a great README file can make your Python project stand out and how to create your own README files.

Data Classes in Python

In this quiz, you'll test your understanding of Python data classes. Data classes, a feature introduced in Python 3.7, are a type of class mainly used for storing data. They come with basic functionality already implemented, such as instance initialization, printing, and comparison.

In this quiz, you'll revisit the foundational concepts of what Python decorators are and how to create and use them.

Defining Main Functions in Python

In this quiz, you'll test your understanding of the Python main() function and the special __name__ variable. With this knowledge, you'll be able to understand the best practices for defining main() in Python.

Documenting Python Code: A Complete Guide

In this quiz, you'll test your understanding of documenting Python code. With this knowledge, you'll be able to effectively document your Python scripts and projects, making them more understandable and maintainable.

Effective Testing with Pytest

In this quiz, you'll test your understanding of pytest, a Python testing tool. With this knowledge, you'll be able to write more efficient and effective tests, ensuring your code behaves as expected.

Format Floats Within F-Strings

In this quiz, you'll test your understanding of how to format floats within f-strings in Python. This knowledge will let you control the precision and appearance of floating-point numbers when you incorporate them into formatted strings.

Functional Programming in Python: When and How to Use It

In this quiz, you'll test your understanding of functional programming in Python. You'll revisit concepts such as functions being first-class citizens in Python, the use of the lambda keyword, and the implementation of functional code using map(), filter(), and reduce().

Generate Images With DALL·E and the OpenAI API

In this quiz, you'll test your understanding of generating images with DALL·E by OpenAI using Python. You'll revisit concepts such as using the OpenAI Python library, making API calls for image generation, creating images from text prompts, and converting Base64 strings to PNG image files.

Get Started With Django: Build a Portfolio App

In this quiz, you'll test your understanding of Django, a fully featured Python web framework. By working through this quiz, you'll revisit the steps to create a fully functioning web application and learn about some of Django's most important features.

Getters and Setters: Manage Attributes in Python

In this quiz, you'll test your understanding of Python's getter and setter methods, as well as properties. You'll learn when to use these tools and how they can help maintain encapsulation in your classes.

Getting Started With Testing in Python

In this quiz, you'll test your understanding of Python testing. With this knowledge, you'll be able to create basic tests, execute them, and find bugs before your users do.

How Do You Choose Python Function Names?

In this quiz, you'll test your understanding of how to choose Python function names. By working through this quiz, you'll revisit the rules and conventions for naming Python functions and why they're important for writing Pythonic code.

How to Check if a Python String Contains a Substring

In this quiz, you'll check your understanding of the best way to check whether a Python string contains a substring. You'll also revisit idiomatic ways to inspect the substring further, match substrings with conditions using regular expressions, and search for substrings in pandas.

How to Create Pivot Tables With pandas

This quiz is designed to push your knowledge of pivot tables a little bit further. You won't find all the answers by reading the tutorial, so you'll need to do some investigating on your own. By finding all the answers, you're sure to learn some other interesting things along the way.

How to Flatten a List of Lists in Python

In this quiz, you'll test your understanding of how to flatten a list in Python. Flattening a list involves converting a multidimensional list, such as a matrix, into a one-dimensional list. This is a common operation when working with data stored as nested lists.

How to Run Your Python Scripts

One of the most important skills you need to build as a Python developer is to be able to run Python scripts and code. Test your understanding on how good you are with running your code.

How to Use Conditional Expressions With NumPy where()

This quiz aims to test your understanding of the np.where() function. You won't find all the answers in the tutorial, so you'll need to do additional research. It's recommended that you make sure you can do all the exercises in the tutorial before tackling this quiz. Enjoy!

How to Use Generators and yield in Python

In this quiz, you'll test your understanding of Python generators and the yield statement. With this knowledge, you'll be able to work with large datasets in a more Pythonic fashion, create generator functions and expressions, and build data pipelines.

How to Write Beautiful Python Code With PEP 8

In this quiz, you'll test your understanding of PEP 8, the Python Enhancement Proposal that provides guidelines and best practices on how to write Python code. By working through this quiz, you'll revisit the key guidelines laid out in PEP 8 and how to set up your development environment to write PEP 8 compliant Python code.

HTTP Requests With the "requests" Library

Test your understanding of the Python "requests" library for making HTTP requests and interacting with web services.

Hugging Face Transformers

In this quiz, you'll test your understanding of the Hugging Face Transformers library. This library is a popular choice for working with transformer models in natural language processing tasks, computer vision, and other machine learning applications.

Implementing an Interface in Python

In this quiz, you'll test your understanding of Python interfaces and their role in software engineering. You'll learn how interfaces can help manage complexity in a growing application and how to implement them in Python.

Inheritance and Composition: A Python OOP Guide

In this quiz, you'll test your understanding of inheritance and composition in Python. These are two major concepts in object-oriented programming that help model the relationship between two classes. By working through this quiz, you'll revisit how to use inheritance and composition in Python, model class hierarchies, and use multiple inheritance.

Install and Execute Python Applications Using pipx

In this quiz, you'll test your understanding of how Python apps are run from isolated virtual environments using the pipx tool. With this knowledge, you'll be able to safely run Python apps that are installed globally in your operating system.

Linear Regression in Python

In this quiz, you'll test your knowledge of linear regression in Python. Linear regression is one of the fundamental statistical and machine learning techniques, and Python is a popular choice for machine learning.

Lists vs Tuples in Python

Challenge yourself with this quiz to evaluate and deepen your understanding of Python lists and tuples. You'll explore key concepts, such as how to create, access, and manipulate these data types, while also learning best practices for using them efficiently in your code.

Logging in Python

In this quiz, you'll test your understanding of Python's logging module. With this knowledge, you'll be able to add logging to your applications, which can help you debug errors and analyze performance.

Managing Multiple Python Versions With pyenv

In this quiz, you'll test your understanding of how to use pyenv to manage multiple versions of Python. Pyenv allows you to try out new Python features without disrupting your development environment, and quickly switch between different Python versions.

Model-View-Controller (MVC) in Python Web Apps: Explained With Lego

In this quiz, you'll test your understanding of the Model-View-Controller (MVC) design pattern, a fundamental concept in many Python web frameworks. By working through this quiz, you'll revisit the concepts of Models, Views, and Controllers, and how they relate to concrete web development examples.

Object-Oriented Programming (OOP) in Python 3

Object-oriented programming (OOP) is a method of structuring a program by bundling related properties and behaviors into individual objects.

Practical Prompt Engineering

In this quiz, you'll test your understanding of prompt engineering techniques with large language models (LLMs) like GPT-3.5 and GPT-4. You'll revisit how to work with OpenAI's API, apply prompt engineering techniques to practical examples, and use various strategies to improve your results.

Primer on Jinja Templating

In this quiz, you'll test your understanding of Jinja templating. Jinja is a powerful tool for building rich templates in Python web applications, and it can also be used to create text files with programmatic content.

Python 3.13: Free-Threading and a JIT Compiler

In this quiz, you'll test your understanding of the new features in Python 3.13. You'll revisit how to compile a custom Python build, disable the Global Interpreter Lock (GIL), enable the Just-In-Time (JIT) compiler, and more.

Python and REST APIs: Interacting With Web Services

In this quiz, you'll test your understanding of REST APIs and how to interact with them using Python. With this knowledge, you'll be able to retrieve, parse, update, and manipulate data provided by any RESTful API that you're interested in.

Python args and kwargs: Demystified

In this quiz, you'll test your understanding of how to use *args and **kwargs in Python. With this knowledge, you'll be able to add more flexibility to your functions.

Python Basics: Building Systems With Classes

You can use classes to build complex systems in Python. By composing classes, inheriting from other classes, and overriding class behavior, you'll harness the power of object-oriented programming (OOP).

Python Basics: Code Your First Python Program

With Python installed, you're ready ready to start coding! It's time to write your first Python program.

Python Basics: Conditional Logic and Control Flow

With conditional logic, you can write programs that perform different actions based on different conditions. Paired with functions and loops, conditional logic allows you to write complex programs that can handle many different situations.

Python Basics: Dictionaries

Python dictionaries, like lists and tuples, store a collection of objects. However, instead of storing objects in a sequence, dictionaries hold information in pairs of data called key-value pairs.

Python Basics: File System Operations

The pathlib module allows you to carry out file path operations with Python. These operations include creating, iterating over, searching for, moving, and deleting files and folders.

Python Basics: Finding and Fixing Code Bugs

Logic errors occur when an otherwise valid program doesn't do what was intended. They cause unexpected behaviors called bugs. Removing bugs is called debugging, and a debugger is a tool that helps you hunt down bugs and understand why they're happening.

Python Basics: Functions and Loops

Functions break code into smaller chunks and are great for defining actions that a program will execute several times throughout your code. Instead of writing the same code each time the program needs to perform the same task, just call the function!

Python Basics: Installing Packages With pip Quiz

Even though Python is famous for coming with batteries included, you'll still find yourself in need of a third-party library from time to time. You can install such packages with pip.

Python Basics: Lists and Tuples

Lists and tuples are important sequence data structures in Python. Lists are mutable, while tuples are immutable. Combining your knowledge of control flow and loops with these sequences allows you to build complex logic.

Python Basics: Modules and Packages

You can build an application by putting related code into separate files called modules. Then, you can use the import statement to use modules in another file.

Python Basics: Numbers and Math

You don't need to be a math whiz to program well, but numbers are an integral part of any programming language. Python is no exception.

Python Basics: Object-Oriented Programming

OOP, or object-oriented programming, is a method of structuring a program by bundling related properties and behaviors into individual objects. In this quiz, you'll test your understanding of OOP.

Python Basics: Reading and Writing Files Quiz

By reading and writing files, you can move data back and forth between your Python programs and external software. The CSV file format is particularly useful, as it's one of the most widely supported file formats for transferring tabular data.

Python Basics: Scopes

To fully understand functions and loops in Python, you need to be familiar with the issue of scope, which determines where a name is visible within your program.

Python Basics: Strings and String Methods

Strings are a fundamental data type in Python. In simplified terms, strings are collections of text, and they show up in many contexts. For example, strings can come from user input, data read from a file, or messages sent by equipment talking over a network.

Python Classes - The Power of Object-Oriented Programming

In this quiz, you'll test your understanding of Python classes. With this knowledge, you'll be able to define reusable pieces of code that encapsulate data and behavior in a single entity, model real-world objects, and solve complex problems.

Python Concurrency

This is a quiz that will review topics covered in our Speed Up Your Python Program With Concurrency tutorial.

Python Conditional Statements

Test your understanding of Python conditional statements

Python Dictionaries

Test your understanding of Python dictionaries

Python Dictionary Iteration

Dictionaries are one of the most important and useful data structures in Python. Learning how to iterate through a Dictionary can help you solve a wide variety of programming problems in an efficient way. Test your understanding on how you can use them better!

Python Exceptions: An Introduction

In this quiz, you'll test your understanding of Python exceptions. You'll cover the difference between syntax errors and exceptions and learn how to raise exceptions, make assertions, and use the try and except block.

Python Folium: Create Web Maps From Your Data

Python’s Folium library gives you access to the mapping strengths of the Leaflet JavaScript library through a Python API. It allows you to create interactive geographic visualizations that you can share as a website.

Python F-Strings

In this quiz, you'll test your knowledge of Python f-strings. With this knowledge, you'll be able to include all sorts of Python expressions inside your strings.

Python GUI Programming With Tkinter

In this quiz, you'll test your understanding of Python GUI Programming With Tkinter, the de facto Python GUI framework. Check your knowledge of GUI programming concepts such as widgets, geometry managers, and event handlers.

Python Installation and Setup

In this quiz, you'll test your understanding of how to install or update Python on your computer. With this knowledge, you'll be able to set up Python on various operating systems, including Windows, macOS, and Linux.

Python Lambda Functions

Python lambdas are little, anonymous functions, subject to a more restrictive but more concise syntax than regular Python functions. Test your understanding on how you can use them better!

Python Mappings

In this quiz, you'll test your understanding of the basic characteristics and operations of Python mappings. By working through this quiz, you'll revisit the key concepts and techniques of creating a custom mapping.

Python Modules and Packages

In this quiz, you'll test your understanding of Python modules and packages, which are mechanisms that facilitate modular programming. Modular programming involves breaking a large programming task into smaller, more manageable subtasks or modules. This approach has several advantages, including simplicity, maintainability, and reusability.

Python Name-Main Idiom

Test your knowledge of Python's if __name__ == "__main__" idiom by answering a series of questions! You've probably encountered the name-main idiom and might have even used it in your own scripts. But did you use it correctly?

Python Operators and Expressions

Test your understanding of Python operators and expressions.

Python Program Structure

Test your understanding of Python program structure.

Python Protocols: Leveraging Structural Subtyping

Take this quiz to test your understanding of how to create and use Python protocols while providing type hints for your functions, variables, classes, and methods.

Python Raw Strings

In this quiz, you can practice your understanding of how to use raw string literals in Python. With this knowledge, you'll be able to write cleaner and more readable regular expressions, Windows file paths, and many other string literals that deal with escape character sequences.

Python's Built-in Exceptions: A Walkthrough With Examples

In this quiz, you'll test your understanding of Python's built-in exceptions. With this knowledge, you'll be able to effectively identify and handle these exceptions when they appear. Additionally, you'll be more familiar with how to raise some of these exceptions in your code.

Python's Built-in Functions: A Complete Exploration

Take this quiz to test your knowledge about the available built-in functions in Python. By taking this quiz, you'll deepen your understanding of how to use these functions and the common programming problems they cover, from mathematical computations to Python-specific features.

Python's enumerate()

Once you learn about for loops in Python, you know that using an index to access items in a sequence isn't very Pythonic. So what do you do when you need that index value? In this tutorial, you'll learn all about Python's built-in enumerate(), where it's used, and how you can emulate its behavior.

Python Sequences: A Comprehensive Guide

In this quiz, you'll test your understanding of sequences in Python. You'll revisit the basic characteristics of a sequence, operations common to most sequences, special methods associated with sequences, and how to create user-defined mutable and immutable sequences.

Python Sets

Test your understanding of sets in Python, a commonly used data structure.

Python's Magic Methods: Leverage Their Power in Your Classes

In this quiz, you'll test your understanding of Python's magic methods. These special methods are fundamental to object-oriented programming in Python, allowing you to customize the behavior of your classes.

Python's property(): Add Managed Attributes to Your Classes

In this quiz, you'll test your understanding of Python's property(). With this knowledge, you'll be able to create managed attributes in your classes, perform lazy attribute evaluation, provide computed attributes, and more.

Python's raise: Effectively Raising Exceptions in Your Code

In this quiz, you'll test your understanding of how to raise exceptions in Python using the raise statement. This knowledge will help you handle errors and exceptional situations in your code, leading to more robust programs and higher-quality code.

Python String Formatting: Available Tools and Their Features

You can take this quiz to test your understanding of the available tools for string formatting in Python, as well as their strengths and weaknesses. These tools include f-strings, the .format() method, and the modulo operator.

Python Strings and Character Data

This quiz will test your understanding of Python's string data type and your knowledge about manipulating textual data with string objects. You'll cover the basics of creating strings using literals and the str() function, applying string methods, using operators and built-in functions, and more!

Python's unittest: Writing Unit Tests for Your Code

In this quiz, you'll test your understanding of Python testing with the unittest framework from the standard library. With this knowledge, you'll be able to create basic tests, execute them, and find bugs before your users do.

Python Threading

This is a quiz that will review topics covered in our An Intro To Threading tutorial.

Python time.sleep()

In this quiz, you'll revisit how to add time delays to your Python programs.

Python Type Checking

In this quiz, you'll test your understanding of Python type checking. You'll revisit concepts such as type annotations, type hints, adding static types to code, running a static type checker, and enforcing types at runtime. This knowledge will help you develop your code more efficiently.

Python Variables

Test your understanding of Python variables and object references.

Python Virtual Environments: A Primer

In this quiz, you'll test your understanding of Python virtual environments. With this knowledge, you'll be able to avoid dependency conflicts and help other developers reproduce your development environment.

Python "while" Loops

Test your understanding of Python while loops

Reading and Writing CSV Files in Python

This quiz will check your understanding of what a CSV file is and the different ways to read and write to them in Python.

Reading and Writing Files in Python

A quiz used for testing the user's knowledge of the topics covered in the Reading and Writing Files in Python article.

Reading and Writing WAV Files in Python

In this quiz, you can test your knowledge of handling WAV audio files in Python with the wave module. By applying what you've learned, you'll demonstrate your ability to synthesize sounds, analyze and visualize waveforms, create dynamic spectrograms, and enhance audio with special effects.

Rounding Numbers in Python

Test your knowledge of rounding numbers in Python.

Ruff: A Modern Python Linter

In this quiz, you'll test your understanding of Ruff, a modern linter for Python. By working through this quiz, you'll revisit why you'd want to use Ruff to check your Python code and how it automatically fixes errors, formats your code, and provides optional configurations to enhance your linting.

Socket Programming in Python

In this quiz, you'll test your understanding of Python sockets. With this knowledge, you'll be able to create your own client-server applications, handle multiple connections simultaneously, and send messages and data between endpoints.

Splitting, Concatenating, and Joining Strings in Python

In this quiz, you can test your Python skills when it comes to the most fundamental string operations: splitting, concatenating, and joining.

Split Your Dataset With scikit-learn's train_test_split()

In this quiz, you'll test your understanding of how to use the train_test_split() function from the scikit-learn library to split your dataset into subsets for unbiased evaluation in machine learning.

String Interpolation in Python: Exploring Available Tools

Take this quiz to test your understanding of the available tools for string interpolation in Python, as well as their strengths and weaknesses. These tools include f-strings, the .format() method, and the modulo operator.

Supercharge Your Classes With Python super()

In this quiz, you'll test your understanding of inheritance and the `super()` function in Python. By working through this quiz, you'll revisit the concept of inheritance, multiple inheritance, and how the `super()` function works in both single and multiple inheritance scenarios.

The Python calendar Module

In this quiz, you'll test your understanding of the calendar module in Python. It'll evaluate your proficiency in manipulating, customizing, and displaying calendars directly within your terminal. By working through this quiz, you'll revisit the fundamental functions and methods provided by the calendar module.

The Python for Loop

In this quiz, you'll test your understanding of Python's `for` loop and the concepts of definite iteration, iterables, and iterators. With this knowledge, you'll be able to perform repetitive tasks in Python more efficiently.

The Python print() Function

In this interactive quiz, you can revisit what you know about Python's print() function. You'll also get to quiz yourself about some of its lesser-known features.

The Python return Statement

In this quiz, you can practice your understanding of how to use the Python return statement when writing functions. Additionally, you'll cover some good programming practices related to the use of return. With this knowledge, you'll be able to write readable, robust, and maintainable functions in Python.

The Walrus Operator: Python's Assignment Expressions

In this quiz, you'll test your understanding of the Python Walrus Operator. This operator was introduced in Python 3.8, and understanding it can help you write more concise and efficient code.

Understanding the Python Mock Object Library

In this quiz, you'll test your understanding of Python's unittest.mock library. With this knowledge, you'll be able to write robust tests, create mock objects, and ensure your code is reliable and efficient.

Using and Creating Global Variables in Your Python Functions

In this quiz, you'll test your understanding of how to use global variables in Python functions. With this knowledge, you'll be able to share data across an entire program, modify and create global variables within functions, and understand when to avoid using global variables.

Web Scraping With Scrapy and MongoDB

In this quiz, you'll test your understanding of web scraping with Scrapy and MongoDB. You'll revisit how to set up a Scrapy project, build a functional web scraper, extract data from websites, store scraped data in MongoDB, and test and debug your Scrapy web scraper.

What Are CRUD Operations?

In this quiz, you'll revisit the key concepts and techniques related to CRUD operations. These operations are fundamental to any system that interacts with a database, and understanding them is crucial for effective data management.

What Is the __pycache__ Folder in Python?

In this quiz, you'll have the opportunity to test your knowledge of the __pycache__ folder, including when, where, and why Python creates these folders.

What's Lazy Evaluation in Python?

In this quiz, you'll test your understanding of the differences between lazy and eager evaluation in Python. By working through this quiz, you'll revisit how Python optimizes memory use and computational overhead by deciding when to compute values.

Working With JSON Data in Python

In this quiz, you'll test your understanding of working with JSON in Python. By working through this quiz, you'll revisit key concepts related to JSON data manipulation and handling in Python.

Write Pythonic and Clean Code With namedtuple

In this quiz, you'll test your understanding of Python's namedtuple() function from the collections module. This function allows you to create immutable sequence types that you can access using descriptive field names and dot notation.

Got feedback on our quizzes?

Up for a challenge: New Deltona city manager wants to see city put its past behind

Taking on the top administrative role in a city known for government dysfunction and in-fighting wouldn't sound like the kind of career move many would relish.

But then, Dale "Doc" Dougherty — who became the city manager for Deltona on June 10 — isn't most people.

Dougherty, who has spent most of his professional life in local government, is the first to admit he did think twice before accepting the job offer from Deltona which, with a current population of nearly 100,000, is the largest municipality in Volusia County. Palm Coast in Flagler County recently overtook Deltona as the most populous in the two-county region.

"So coming down here, many people said, 'don't do it,' mostly because there's this reputation (for Deltona) of it not moving forward," Dougherty, 55, said in a recent sit-down interview with The News-Journal.

In the end, Dougherty not only accepted the challenge but said he looked forward to it, confident he might be more successful in moving Deltona forward where his predecessors could not.

"My personality, I think it just fits well; I like figuring my way around things and how to do them better," Dougherty said. "And I just keep going until I can try to hopefully fix it."

Problem-solving skills

That problem-solver approach could be seen even as Dougherty led The News-Journal into city council chambers, explaining how he has plans to lower the height of the dais where members meet and also rearrange their seating from a horizontal pattern into more of a horseshoe shape.

"That way, the audience feels more included and not like they're watching a show up there," he said.

In his first week in office, Dougherty also did away with the metal detector and bag-check process visitors had to go through before being admitted to City Hall.

Dougherty will be the 15th city manager to hold the position since Deltona was incorporated in 1996, as a string of administrators were fired, resigned or appointed on a temporary basis. Most recently, Glenn Whitcomb took over as interim city manager with the resignation of Jim Chisholm in August 2023.

Commissioner seats have also seen frequent turnover, with  two commissioners departing mid-term since the beginning of the year . Commissioner Troy Shimkus (since ousted by incoming Commissioner Emma Santiago in the Aug. 20 primary election) was appointed to represent District 2 in January, while Commissioner Davison Heriot was appointed to fill the District 1 seat.

And Deltona Mayor Santiago Avila Jr. has been embroiled in several public controversies, including a flap over his refusal to recognize Pride Month in June, fueled by criticism by fellow Commissioner Dana McCool .

'Ghosts of the past'

Dougherty calls these issues "ghosts of the past" and says he is focused on positivity going forward.

Nicknamed "Doc" since he was a child (his Irish surname is pronounced "doc-erty"), the new city manager grew up in Allentown, Pennsylvania and over his nearly 30 years in the governmental sector has served in administrative roles in Florida, Georgia, South Carolina, North Carolina, Indiana, and most recently as city manager in Garden City, Michigan, a community of 27,000, for the last six years. He also earned a master's in business administration at the University of Notre Dame.

Dougherty and his wife, Alexandrea, a schoolteacher, have five children ranging in age from 19 to 25, four of whom are in the military (three went to the United States Military Academy at West Point).

Even as the family moved around a lot throughout Dougherty's career, he said, "The plan was always to come back to Florida."

One daughter, Alexis, lives in nearby Melbourne.

Developing community camaraderie

In getting to know the Deltona community more since relocating earlier this summer, Dougherty said he can understand where some of the city's reputation as a bedroom community lacking a true identity and cultural core comes from.

"I think that through the years many, many houses were built but they forgot to build a community," he said.

Dougherty has some ideas to change that, beginning with several he hopes to put into action shortly, like movies in the park, a concert series and special events like a chili cookoff. He also thinks if the community shows it is on the rise it could attract more commercial development, especially new restaurants that would also provide a sense of character.

With an easygoing style, Dougherty said he is an "open-door" kind of manager and wants staff to be able to come to him with both problems and suggestions. He wants to hear more about their hopes and goals and to provide a sense of consistency and accountability that's been lacking in Deltona government.

If he could pull it off, well, Dougherty might be seen as a kind of magician, given the community's history. Not that he has those kinds of superpowers, but Dougherty does acknowledge that rumors of his side hustle (not as much in recent years) as a certified hypnotist are, in fact, true. He has taken to more than a few stages with his traveling show, bringing willing participants up to be put under the influence of what he says is really just a kind of guided imagery visioning.

But his "powers" only go so far, Dougherty is quick to add.

"I can't make you do something you normally wouldn't," he said with a laugh.