I Completed 45 Lambda Function Exercises (And I'm Still a Beginner!)

Source: Dev.to

What I Worked Through

This wasn’t just about lambda functions – it was a deep dive into functional‑programming concepts in pure Python. The workbook covered:

📚 The 7 Main Topics

• Lambda Functions – Anonymous functions with map, filter, and sorted
• Closures and Freezing Variables – The tricky late‑binding trap and how to fix it
• Conditional/Ternary Expressions – Writing concise if‑else logic in one line
• List Comprehensions – Single, nested, and filtered comprehensions
• Higher‑Order Functions (HOF) – Functions as first‑class citizens
• Mixed Advanced Exercises – Combining multiple concepts
• Scenario‑Based Problems – Real‑world application challenges

🎯 Difficulty Progression

The exercises were organized into difficulty levels:

New Concepts I Discovered

While working through these exercises I stumbled upon many things beyond the core material. For example, I discovered the walrus operator (:=) introduced in Python 3.8. It wasn’t required for the exercises, but my curiosity (“what else?” / “why does this work?”) led me to explore it.

Takeaway: If you approach the workbook with curiosity—asking questions, experimenting, and trying “what if?”—you’ll uncover many extra operators, patterns, and techniques. Each exercise taught me something new, but my curiosity taught me even more!

The Reality Check ⚠️

After completing all 45 exercises, I’m still a beginner.

That’s completely okay! Learning programming isn’t a race to expertise. The workbook gave me a solid introduction to functional programming and lambda syntax, but I’m still mastering the basics.

Why These Exercises Helped

My gains depended heavily on my curiosity, interest, and engagement. The workbook helped because:

• Progressive difficulty – Starts simple, then ramps up
• Complete solutions – Detailed explanations for every problem
• Practical examples – Real‑world scenarios, not just toy problems
• Concept combination – Later exercises blend multiple ideas
• Tricky parts highlighted – Pitfalls are called out in solutions
• Hands‑on practice – 45 chances to write actual code

For Other Beginners

If you’re starting with Python and want to level up your functional‑programming skills, I’ve uploaded the complete workbook to a public repository.

Repository:

The repo contains:

• lambda.pdf – Full workbook with all 45 exercises
• Complete solutions with detailed explanations
• Progressive difficulty from Simple → Medium → Hard → Scenarios
• Coverage of advanced Python concepts

What to Expect

Structure

• 45 total exercises organized by topic
• 3 difficulty levels (Simple, Medium, Hard) plus scenario‑based problems
• Solutions included with explanations of tricky parts
• New operators & patterns you probably haven’t seen

Time Investment

Note: Times are estimates for a beginner starting from scratch and also learning the underlying concepts.

• Total estimated time: 20–30 hours of focused practice
• My experience: ~6–10 hours total (spread over 3–4 days, not continuous)

The total includes preliminary preparation—learning lambda theory (using ChatGPT) and picking up extra concepts while solving the exercises.

Important: Before diving into the PDF, learn basic lambda theory first. If you only know regular def functions, you’ll need to understand lambda syntax, as the workbook assumes that foundational knowledge. Your pace will vary based on curiosity and engagement.

What You’ll Learn

• Lambda functions
• Functional‑programming patterns
• List & dictionary comprehensions
• Closures
• Function composition
• Various Python operators & techniques

How much you learn ultimately depends on your curiosity, interest, and approach to the exercises. Happy coding!

My Advice After Completing It

• Start with simple exercises – Don’t jump to hard ones.
• Try before looking – Attempt each problem before checking solutions.
• Type the code yourself – Don’t just read the solutions.
• Understand the “why” – Not just the “how”.
• Experiment freely – Modify examples and see what breaks.
• Take breaks – Some concepts need time to sink in.
• Revisit difficult ones – Come back to exercises you struggled with.
• Stay humble – Remember you’re learning, not competing.
• Keep a notebook – Write down patterns and tricks you discover.
• Move sequentially – Exercises build on previous concepts.

The Learning Curve

Here’s how my progress felt:

• Exercises 1‑10 (Simple) – “This is making sense!”
• Exercises 11‑20 (Medium starts) – “Wait, this is getting complex…”
• Exercises 21‑30 (Hard begins) – “I need to slow down and think…”
• Exercises 31‑40 (Mixed/Advanced) – “Okay, this is challenging but doable!”
• Exercises 41‑45 (Scenarios) – “I can actually solve real problems now!”

The difficulty ramp is real, but it’s manageable if you take your time.

The Bottom Line

Completing these 45 exercises doesn’t make you an expert. It doesn’t even make you intermediate. You’ll still be a beginner, and that’s the reality of learning programming.

What you gain from these exercises depends on your curiosity, interest, and how you work through them. The more you engage and explore, the more you’ll learn. How much you benefit is entirely up to your approach.

Conclusion

If you’re a beginner looking to understand lambda functions and functional programming in Python, I highly recommend checking out this workbook. Work through the 45 exercises at your own pace—don’t rush, and don’t compare yourself to others.

The workbook will give you solid foundations in functional programming. Remember: after completing it you’ll still be a beginner, but you’ll gain valuable knowledge and patterns that will serve you well on your Python journey.

🤖 About This PDF & Getting Help

This PDF was generated using Gemini AI. If you have doubts or don’t understand something while working through the exercises:

• Ask Gemini or ChatGPT with specific examples from the exercises.
• Be curious! Ask “why does this work?” or “what happens if I change this?”
• Ask in different ways – if you don’t get the answer you need, rephrase your question.
• Request examples – ask for more examples to deepen your understanding.
• Don’t stop at one answer – if something isn’t clear, keep asking until it clicks.

Important: I used the free versions of these AI services—no paid accounts required. You can learn using free resources too!

The more curious you are and the more questions you ask, the deeper your understanding will become. AI assistants like Gemini and ChatGPT are there to help you learn—use them! If you don’t get what you want the first time, ask the same thing in different ways until the concept becomes clear.

Keep learning, keep coding, and embrace being a beginner. We all start somewhere, and every expert was once where you are now.

• Repository: (link omitted)
• PDF Link (Google Drive): (link omitted)

Content: 45 exercises | 7 topics | 3 difficulty levels | Complete solutions

Topics: Lambda Functions, Closures, Ternary Expressions, Comprehensions, HOF, Mixed Exercises, Scenarios

Status: Beginner‑friendly | Pure Python | Detailed explanations included

Happy Learning! 🐍

P.S. – Don’t skip the “tricky parts” in the solutions. Those explanations will help reduce confusion!

Note: This article was written with the help of Claude AI.