Библиотека Python разработчика | Книги по питону

Django for APIs: Build Web APIs with Python & Django William S. Vincent Take a modern API-first approach to creating 3 different Django back-ends: a Library API, Todo API, and a Blog API with user authentication, permissions, proper documentation, and more. You'll even learn how to connect them to a React front-end for a truly full-stack web application.

Introducing Python: Modern Computing in Simple Packages Bill Lubanovic Easy to understand and fun to read, this updated edition of Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you’ve learned.

Forging Python: Best practices and life lessons developing Python Miki Tebeka Life lessons and best practices developing Python and programming in general brought in unique and old way.

Machine Learning with Spark and Python: Essential Techniques for Predictive Analytic Michael Bowles Machine Learning with Spark and Python Essential Techniques for Predictive Analytics, Second Edition simplifies ML for practical uses by focusing on two key algorithms. This new second edition improves with the addition of Spark―a ML framework from the Apache foundation. By implementing Spark, machine learning students can easily process much large data sets and call the spark algorithms using ordinary Python code.

Fundamentals Of Python: Data Structures Kenneth A. Lambert Whether you are a computer programming student, hobbyist or professional, Lambert's FUNDAMENTALS OF PYTHON DATA STRUCTURES, 2E offers the perfect introduction to object-oriented design and data structures using the popular Python(TM) programming language. The level of instruction is ideal if you've had at least one semester of programming experience in an object-oriented language, such as Java(TM), C++ or Python(TM). Step-by-step explanations and focused exercises clearly explain the design of collection classes with polymorphism and inheritance and multiple implementations of collection interfaces. This edition also addresses the analysis of the space/time tradeoffs of different collection implementations and, specifically, array-based implementations and link-based implementations. You learn to work with collections, including sets, lists, stacks, queues, trees, dictionaries and graphs.

Effective Python Penetration Testing Robert Moreno Moving on, you will find out how to write basic attack scripts, and will develop debugging and reverse engineering skills with Python libraries. Toward the end of the book, you will discover how to utilize cryptography toolkits in Python and how to automate Python tools and libraries.We will begin by providing you with an overview of Python scripting and penetration testing. You will learn to analyze network traffic by writing Scapy scripts and will see how to fingerprint web applications with Python libraries such as ProxMon and Spynner.Penetration testing is a practice of testing a computer system, network, or web application to find weaknesses in security that an attacker can exploit. will help you utilize your Python scripting skills to safeguard your networks from cyberattacks.

Mastering Machine Learning with Python in Six Steps: A Practical Implementation Guide to Predictive Data Analytics Using Python Manohar Swamynathan Explore fundamental to advanced Python 3 topics in six steps, all designed to make you a worthy practitioner. This updated version's approach is based on the "six degrees of separation" theory, which states that everyone and everything is a maximum of six steps away and presents each topic in two parts: theoretical concepts and practical implementation using suitable Python 3 packages.

Python for civil and structural engineers Vittorio Lora Python for civil and structural engineers Are you interested in python and its applications in structural engineering? Are you a professional or a student looking for a way to speed up your work? Then this book was written exactly for you. No prior knowledge of the language is required: the book goes from basic programming concepts to writing useful real-world applications.

Text Analytics with Python: A Practitioner's Guide to Natural Language Processing Dipanjan Sarkar Leverage Natural Language Processing (NLP) in Python and learn how to set up your own robust environment for performing text analytics. This second edition has gone through a major revamp and introduces several significant changes and new topics based on the recent trends in NLP.

Machine Learning Pocket Reference: Working with Structured Data in Python Matt Harrison With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project.