Coffee break python pdf free download

Do you see the importance of understanding the basics? The matrix is sorted as the integers in the rows and columns increase monotonically with the row and column number. Otherwise, it returns False. The function trix and an integer value. It skips whole rows and columns at a time using the sorted property. Because as long as the column value than the searched value column j value, row[j] is larger all following elements of j are larger than the searched value sorted prop- erty.

Thus, we are sure that our searched value is not in column decreasing j and j. Why can it skip the whole row? Because it currently checks the largest value in the row. If this value is smaller than the searched value, all other values are as well. In summary, the idea of this great algorithm from Keith Schwartz 2 is to skip either one row or one column in each step. Thus, for a quadratic matrix with n rows 2n 2 all n and columns, the algorithm inspects approximately cells.

This puzzle presents an algorithmic problem with practical value for stock market analysis. Suppose you are trading the cryptocurrency Ethereum. The algorithm works as follows. It iterates over all each is a possible buying point i. Next, the algorithm uses the index i of the current buying point to get all potential selling points after buying. We use slicing to get these, i. The bubble sort algorithm works exactly as its name suggests. It sorts an input list by treating each element as a bubble that climbs up the list.

Each bubble rises as long as it is greater than the list elements. If the bubble 5. The precise algorithm works as follows. Next, the second largest element will rise to the top and the procedure repeats. Study this basic algorithm carefully. Every great coder must know it.

String concatenation is the process of creating a string by appending string arguments. The parameter sep declares the sep- arator string to be used to glue together two strings. The separator string comes as a keyword argument. The keyword argument helps to differentiate whether the last parameter is part of the sep argument. It concatenates an arbitrary number of strings using the separator to glue them together.

So you may as well learn its proper use now. This puzzle has only one challenge. But this is a trap! The purpose of solving Python puzzles is to understand code in a precise and deep manner. So if you got this puzzle wrong, be grateful for the lesson and go on. For example, consider a list with The naive algorithm performs compar- isons in the worst case.

Hence, value in a sorted list. Bsearch uses the property that the list is already sorted. It checks only the element in the middle position between two indices lo and hi. If this middle element is smaller than the searched value, all left-hand elements will be smaller as well because of the sorted list.

The algorithm can skip all left-hand elements by setting the lower index lo to the position right of the middle element. If this middle element is larger than the searched value, all right-hand elements will be larger as well. Hence, we set the upper index left of the middle element.

In each loop iteration, we reduce the search space, i. How to modify a sequence while iterating over it? For example, you want to prepare a data set of house prices for a machine learning algorithm to predict the market prices of new houses. This problem is not as simple as removing elements from a sequence over which you iterate.

Before entering the for loop, the Python interpreter creates an iterator object. The iterator object provides 5. For example, if the number of elements changes at runtime, the iterator object may believe it is ready, while there are still objects in it.

The puzzle presents one solution to this problem. So how to copy the sequence? The most convenient way to achieve this is by using the slice notation as shown in the puzzle. This puzzle introduces an advanced language feature: lambda functions. Lambda functions are rooted in the mathematical area of lambda calculus.

One of the pi- oneers of this area was Alonzo Church. Lambda functions exist in a wide range of languages for functional programming.

They are not only at the heart of functional programming languages, they are also the basis of many advanced Python language features. So how do lambda functions work? After the lambda keyword, the function takes one or more arbitrary arguments. After the colon follows a single expression. The lambda function then returns the result of this expression.

Hence, lambda functions are syntactical shortcuts for a subclass of normal Python functions. For ex- ample, the incrementor function in the puzzle increments a value by We assign this function to the variable f.

What is going on in this puzzle? The second is a more concise way to write the same string. We specify the line breaks with the new line char- 5.

These two ways of breaking lines in Python strings are the basis for advanced features and code snippets. This puzzle introduces several Python language features about quotes in string literals. It requires a clear understanding of the concept of escaping. Escaping is an important concept in most programming languages. You are not an advanced coder without understanding at least the basic idea of escaping.

Recap, strings can be enclosed either with single quotes ' These two options are semantically equivalent, i. But what happens if you write, say, a small conversation with direct speech? Trying this ends the string prematurely. Here, the best case is that the interpreter complains about the strange syntax of the random character sequence after the premature ending of your string. You can avoid this problem by enclosing the string with single quotes: 'Alice said: "Hey Bob!

The opposite also works, i. So far so good. What if you want to put a single quote within a string enclosed by single quotes? When put before special characters like the single quote, it escapes them. In other words, it changes the meaning of these characters. Only when escaped, the interpreter changes its meaning to the normal single quote character. The fibo function in the puzzle calculates all Fibonacci numbers up to the function argument n.

We use the concise method of iterable unpacking to store the value of b in the variable a and to calculate the new value of b as the sum of both. We maintain the whole sequence in the list variable result by appending the sequence value a to the end of the list. The puzzle calculates the Fibonacci sequence up to and stores the whole list in the variable fib But to solve the puzzle, you do not have to calculate the whole sequence.

The print statement only compares whether the last element is equal to the sum of the second and third last element in the sequence. Humans can solve this puzzle easily using logic and strategic thinking.

The Python interpreter, however, must take the brute-force approach of calculating everything from scratch. This nicely demonstrates your role as a computer programmer. But you must use your power wisely because the computer will do exactly what you ask it to do. This puzzle introduces a recursive algorithm to sort lists. When executing the functions, you get the following results. But why? The algorithm is a variant of the popular quicksort algorithm. Quicksort selects a pivot element from the list.

Then, the algorithm moves all elements that are smaller than the pivot to the left side. Similarly, it moves elements that are larger or equal than the pivot to the right side. This is repeated in a recursive manner for the left and the right lists. Suppose you create a new list as follows. You put all elements that are smaller than the pivot on the left, then the pivot, then all elements that are larger or equal the pivot on the right.

The resulting list feels a bit more sorted, right? If the two sublists were already sorted, the list would be perfectly sorted. This is where the recursive call of qsort1 comes into play. It takes over the problem of sorting each sublist by applying the same scheme of pivoting and recursion to the sublist. In contrast, the qsort2 function appends both sub- lists to the right of the pivot element.

They not only train your language understanding but also your conceptual thinking which is even more important for coders at any level. Programming is about using lower-level functionality to create higher-level functionality. In general, any programming language is a collection of functions that in turn build upon functions provided by the operating system. You must master the art of building your own code with the help of existing functionality. Do not reinvent the wheel! Functions are generic code snippets that can be tailored to your needs via keyword arguments.

The puzzle 5. The puzzle introduces two concepts: dictionaries and unpacking keyword arguments. Python dictionaries work like real-world dictionaries: the keys are the words and the values are the explanations.

You access the explanation to a given word via the index table. Similarly, in a Python dictionary, you access the values using the method of indexing.

The indices or keys can be strings, integers, or any other immutable data type. As the second keyword argument val2 is not declared in the dictionary, it is initialized to its default value. The question in this puzzle is whether the second print statement will ever be executed. The body of the while loop consists of the pass statement. This state- Although the while loop does nothing, the interpreter is trapped forever because the while condition is True.

Thus, our pro- gram wastes scarce CPU cycles until the user interrupts the execution. Hence, no execution path will execute the second print statement.

Knowing the basics sets apart the great coders from the merely intermediate ones. You already know data structures like lists, sets, and dictionaries. A graph is just another complex data structure for relational data. Relational data consists of edges and vertices. Each vertex stands in one or more relations with other vertices. An example for relational data is the Facebook social graph. Facebook represents users as vertices and friendship relations as edges.

Two users are connected via an edge in the graph if they are Facebook friends. The puzzle uses an adjacency matrix as graph data struc- G. Each row i in the matrix stores the out-neighbors of vertex i. And each column j stores the in-neighbors of vertex j. To check this, the algorithm uses a recursive approach. We increment it in each recursion level as the current path length increases by one.

In other words, at least one vertex is visited twice and a cycle exists in this recursion instance. This puzzle asks whether there is a path between 3 and 0. There is a direct path from vertex 3 to vertices 1 and 2 and to itself.

But neither vertex 1 nor 2 has any out-neighbors. Therefore, there is no path from vertex 3 to any other vertex besides vertices 1 and 2. The high Elo indicates that only experienced Python coders can solve this puzzle.

There are two barriers to overcome. First, the lambda function seems to be an abstract concept. Yet, it is only old wine in a new bottle. A lambda function is nothing but an anonymous function with a special syntax. In the puzzle, we use the lambda function as a key for the sorting function.

Second, we are not sorting by ascending integers, i. You will use or have already used the concepts introduced in this puzzle. They are elementary pieces of knowledge for any Python programmer. There are three basic concepts in the puzzle. First, we have the two dictionaries mapping an account name to the number of followers. Cristiano Ronaldo key: " cristiano" For example, has million Instagram followers. In contrast to lists, dictionaries allow fast data access.

You can retrieve each item with only one operation without having to iterate over the whole data structure. In the words of a computer scientist: the dictionary access has constant runtime complexity. The second argument is the sequence to be 5. After executing the code puzzle, both res1 and res2 5. The default split function divides the in the string along the whitespaces. Finally, we check whether one of them is True.

You already know that computers only operate on 0s and 1s. Every single character in a string is encoded as a sequence of 0s and 1s. The Unicode table assigns one binary or decimal value to each character. For example, the Unicode value 41 encodes the value 'A' and the Unicode value 42 the value 'B'.

With Unicode, we create our own secret language via encryption and decryption functions. The functions encrypt and decrypt operate on a string literal s1. To encrypt or decrypt a string, we shift each character by encrypt function shifts decrypt function shifts it to two Unicode positions. The the string to the right, the the left. We use the map function to implement this shift for each character in the string tion ord , s1. Using the built-in func- shifting a character is as simple as adding a bias value to the Unicode value of the respective character.

The result of both encryption and decryption is a sequence type. Hence, the result of a double encryption plus a single decryption is the same as a single decryption, i. The algorithm is simple, parallelizable to thousands of cores, and well established in theory.

The runtime of the algorithm can often be analyzed statistically. For example, Bitcoin miners guess the solution to a complex problem. When generating the solution, it is common to use randomization.

The guess method generates y between 0 and x. It is not informed. This book is all about push- ing you from beginner to intermediate coding level. If you feel that solving code puzzles has advanced your skills, make it a daily habit to solve a Python puzzle and watch the related video that is given on the Finxter web app.

Where to go from here? I am publishing a fresh code puzzle every couple of days on our website finxter. All puzzles are available for free. For any feedback, question, or problem you struggle and need help with, please send me an email to finxter. Finally, I would like to express my deep gratitude that you have spent your time solving code puzzles and reading this book. Above everything else, I value your time. The ultimate goal of any good textbook should be to save, not take, your time.

By working through this textbook, you have gained insights about your coding skill level and I hope that you have experienced a positive return on invested time and money. Now, please keep investing in yourself and stay active within the Finxter community. Home current Upload. Words: 25, Pages: Preview Full text Loading documents preview If you are reading this book, you are an aspiring coder and you seek ways to advance your coding skills.

You already have some experience in writing code, but you feel that there is a lot to be learned before you become a master coder. You want to read and understand code better. You want to challenge the status quo that some of your peers understand code faster than you. Either way, you have already proven your ambition to learn and, therefore, this book is for you.

To join the league of the great code masters, you only have to do one thing: stay in the game. Mastery comes from intense, struc- tured training. Bill Gates, the founder of Microsoft, reached mastery at a young age as a result of coding for more than 10, hours. He was committed and passionate about coding and worked long nights to develop his skills.

He was anything but an overnight success. There is one thing that will empower you to invest the 10, hours of hard, focused work to reach mastery. What do you think it is? As for the code masters, it's your ambition to learn that will drive you through the valleys of desperation on your path to mastery: complex code, nasty bugs, and project managers pushing tight deadlines.

Nurturing your ambition to learn will pay a rich stream of dividends to you and your family as long as you live. It will make you a respectable member of the society providing unique value to information technology, automation, and digitalization. So keeping your ambition to learn intact is the one thing you must place above all else. It helps you to learn faster by making use of the established principles of good teaching.

Investing this time will kickstart your skills to write, read, and understand Python source code. The idea is that you solve code puzzles that start out simple but become more and more complex as you read the book.

In essence, you play Python interpreter and compute the output of a code snippet in your head. To make this idea a reality, I developed the online coding academy Finxter. The next section explains and motivates the advantages of the Finxter method of puzzle-based learning. There is robust evidence in psychological science for each of these reasons. Instead, they are mostly focused on one-directional teaching. This book attempts to change that.

In brief, the 10 reasons for puzzle-based learning are the following. Overcome the Knowledge Gap Section 2. Embrace the Eureka Moment Section 2.

Divide and Conquer Section 2. Improve From Immediate Feedback Section 2. Measure Your Skills Section 2. Individualized Learning Section 2. Small is Beautiful Section 2. Active Beats Passive Learning Section 2. Each question built on answers to previous questions provided by the student. This more than year old teaching technique is still in widespread use today.

A good teacher opens a gap between their knowledge and the learner's. This creates a tension in the learner's mind. To close this gap, the learner awaits the missing piece of knowledge from the teacher. Better yet, the learner starts developing their own answers. The learner craves knowledge. Code puzzles open an immediate knowledge gap. The puzzle's semantics are hidden.

But only you can transform the unsolved puzzle into a solved one. Bad teachers open a knowledge gap that is too large. The learner feels frustrated because they cannot overcome the gap.

Suppose you are standing before a river that you must cross. But you have not learned to swim, yet. Now, consider two rivers. The second is Rattlesnake Creek. The fact that you have never heard of this river indicates that it is not too big of an obstacle. Most likely, you will not even attempt to swim through the big Colorado River. But you could swim over the Rattlesnake if you stretch your abilities just a little bit.

You must stretch yourself to solve them, but you can do it, if you go all-out. Constantly feeling a small but non-trivial knowledge gap creates a healthy learning environment. Fast and thorough learning has always increased our chances of survival. Thus, evolution created a brilliant biological reaction to reinforce learning in your body.

Your brain is wired to seek new information; it is wired to always process data, to always learn. Did you ever feel the sudden burst of happiness after experiencing a eureka moment? Your brain releases endorphins, the moment you close a knowledge gap.

Easy puzzles open small, hard puzzles, which open large knowledge gaps. You must learn a myriad of new concepts and language features. Many aspiring coders are overwhelmed by the complexity.

They seek a clear path to mastery. Most aspiring coders think they have a goal: becoming a better coder. As any productivity expert will tell you: break a big task or goal into a series of smaller steps.

Finishing each tiny step brings you one step closer to your big goal. Divide and conquer makes you feel in control, pushing you one step closer toward mastery. You want to become a master coder? Code puzzles do this for you. They break up the huge task of learning to code into a series of smaller learning 2. The student experiences laser focus on one learning task such as recursion, the for loop, or keyword ar- guments. A good code puzzle delivers a single idea from the author's into the student's head.

You can digest one puzzle at a time. Learn how this impacts day-to-day programming, to benefit in practice, to combine new features, and to avoid all new traps. Ansible is a simple, but powerful, server and configuration management tool.

Learn to use Ansible effectively, whether you manage one server—or thousands. All rights reserved. That's the premise of the "Coffee Break Python" textbook series. What will you get out of the book? Improve your level of deep Python code understanding. Surprise your peers with your newly acquired code speed reading skills. Enjoy the small daily doses of intellectual challenges.

A Finxter once called it "Sudoku for coders"! Learn all the basic Python syntax elements. Discover your own skill level by tracking your puzzle-solving performance. Compare your skill level against other coders: are you a grandmaster of code? Enjoy the fun of rushing over Python -- from "hello world" to "recursive Quicksort".

Get your dream job and rock future code interviews! Share this book Feedback Email the Author s. His research interests include graph theory and distributed systems.

Python Superpower. Python Mastery. Your Path to Python Mastery. Coffee Break Python - Extended Edition. Thank you. I love it : I enjoy reading this book! Keep up the good work. The Blockchain Economy - A Primer. Christian Mayer. Coffee Break NumPy. Leaving the Rat Race with Python. Christian Mayer and Lukas Rieger. Coffee Break Python.

Coffee Break Python Slicing. Brain Games Python. In addition, the two first chapters of the previous edition have been extended and split up into five new chapte Each chapter gives you the complete source code for a new game, and then teaches the programming concepts from the examples. This book also has an introduction to making games with 2D graph How To Code in Python 3. Extremely versatile and popular among developers, Python is a good general-purpose language that can be used in a variety of applications.

For those with an understanding of English, Python is a very humanreadable programming language, allowing for quick comprehension. Because Python supports multiple styles including scripting and object-oriented Smooth CoffeeScript.