Python Data Visualization Cookbook. As a developer with knowledge of Python you are already in a great position to start using data visualization. This superb cookbook shows you how in plain language and practical recipes, culminating with 3D animations

Igor Milovanovic

Today, data visualization is a hot topic as a direct result of the vast amount of data created every second. Transforming that data into information is a complex task for data visualization professionals, who, at the same time, try to understand the data and objectively transfer that understanding to others. This book is a set of practical recipes that strive to help the reader get a firm grasp of the area of data visualization using Python and its popular visualization and data libraries.Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts.Python Data Visualization Cookbook starts by showing you how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. During the book, we go from simple plots and charts to more advanced ones, thoroughly explaining why we used them and how not to use them. As we go through the book, we will also discuss 3D diagrams. We will peep into animations just to show you what it takes to go into that area. Maps are irreplaceable for displaying geo-spatial data, so we also show you how to build them. In the last chapter, we show you how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python.This book will help those who already know how to program in Python to explore a new field – one of data visualization. As this book is all about recipes that explain how to do something, code samples are abundant, and they are followed by visual diagrams and charts to help you understand the logic and compare your own results with what is explained in the book.

Python Deep Learning. Understand how deep neural networks work and apply them to real-world tasks - Third Edition

Ivan Vasilev

The field of deep learning has developed rapidly recently and today covers a broad range of applications. This makes it challenging to navigate and hard to understand without solid foundations. This book will guide you from the basics of neural networks to the state-of-the-art large language models in use today.The first part of the book introduces the main machine learning concepts and paradigms. It covers the mathematical foundations, the structure, and the training algorithms of neural networks and dives into the essence of deep learning.The second part of the book introduces convolutional networks for computer vision. We’ll learn how to solve image classification, object detection, instance segmentation, and image generation tasks.The third part focuses on the attention mechanism and transformers – the core network architecture of large language models. We’ll discuss new types of advanced tasks they can solve, such as chatbots and text-to-image generation.By the end of this book, you’ll have a thorough understanding of the inner workings of deep neural networks. You'll have the ability to develop new models and adapt existing ones to solve your tasks. You’ll also have sufficient understanding to continue your research and stay up to date with the latest advancements in the field.

Python for Secret Agents - Volume II. Gather, analyze, and decode data to reveal hidden facts using Python, the perfect tool for all aspiring secret agents - Second Edition

Steven F. Lott

Python is easy to learn and extensible programming language that allows any manner of secret agent to work with a variety of data. Agents from beginners to seasoned veterans will benefit from Python's simplicity and sophistication. The standard library provides numerous packages that move beyond simple beginner missions. The Python ecosystem of related packages and libraries supports deep information processing.This book will guide you through the process of upgrading your Python-based toolset for intelligence gathering, analysis, and communication. You'll explore the ways Python is used to analyze web logs to discover the trails of activities that can be found in web and database servers. We'll also look at how we can use Python to discover details of the social network by looking at the data available from social networking websites.Finally, you'll see how to extract history from PDF files, which opens up new sources of data, and you’ll learn about the ways you can gather data using an Arduino-based sensor device.

Python Geospatial Development. If you're experienced in Python here's an opportunity to get deep into Geospatial development, linking data to global locations. No prior knowledge required – this book takes you through it all, step by step. - Second Edition

Erik Westra

Geospatial development links your data to places on the Earth's surface. Writing geospatial programs involves tasks such as grouping data by location, storing and analyzing large amounts of spatial information, performing complex geospatial calculations, and drawing colorful interactive maps. In order to do this well, you'll need appropriate tools and techniques, as well as a thorough understanding of geospatial concepts such as map projections, datums and coordinate systems.Python Geospatial Development - Second Edition teaches you everything you need to know about writing geospatial applications using Python. No prior knowledge of geospatial concepts, tools or techniques is required. The book guides you through the process of installing and using various toolkits, obtaining geospatial data for use in your programs, and building complete and sophisticated geospatial applications in Python.Python Geospatial Development teaches you everything you need to know about writing geospatial applications using Python. No prior knowledge of geospatial concepts, tools or techniques is required. The book guides you through the process of installing and using various toolkits, obtaining geospatial data for use in your programs, and building complete and sophisticated geospatial applications in Python.This book provides an overview of the major geospatial concepts, data sources and toolkits. It teaches you how to store and access spatial data using Python, how to perform a range of spatial calculations, and how to store spatial data in a database. Because maps are such an important aspect of geospatial programming, the book teaches you how to build your own “slippy map” interface within a web application, and finishes with the detailed construction of a geospatial data editor using Geodjango.Whether you want to write quick utilities to solve spatial problems, or develop sophisticated web applications based around maps and geospatial data, this book includes everything you need to know.

Python i Asyncio. Programowanie asynchroniczne

Caleb Hattingh

Programowanie współbieżne jest ważną techniką w tworzeniu nowoczesnych rozwiązań sieciowych. Programiści Pythona często w tym celu korzystają z wątków i mechanizmu wywłaszczania. Z tym że nie jest to optymalne rozwiązanie - z uwagi na ryzyko naruszenia bezpieczeństwa. Istnieje też możliwość programowania asynchronicznego z wykorzystaniem biblioteki asyncio, która została dodana w Pythonie 3.4. Złożoność API Asyncio budzi jednak obawy programistów Pythona, również biegle posługujących się tym językiem. Mimo to wysiłek włożony w zrozumienie działania Asyncio jest opłacalny, gdyż biblioteka ta pozwala na skuteczne rozwiązywanie problemów ze współbieżnym programowaniem sieciowym. Lektura tej książki ułatwi Ci pozbycie się obaw przed biblioteką asyncio. Zrozumiesz jej podstawowe elementy, co pozwoli Ci na rozpoczęcie programowania sterowanego zdarzeniami i prostą obsługę tysięcy jednoczesnych połączeń sieciowych. Dowiesz się, dlaczego Asyncio stanowi bezpieczniejszą alternatywę dla wielozadaniowości z wywłaszczaniem wątków, i dogłębnie zrozumiesz koncepcję programowania asynchronicznego. Następnie przeanalizujesz wprowadzone w Pythonie zmiany, dzięki którym możliwe jest programowanie asynchroniczne. Dowiesz się także, w jakich konkretnie sytuacjach biblioteka asyncio jest wyjątkowo użyteczna i których narzędzi należy wtedy używać. W książce pokazano najlepsze sposoby wykorzystania nowych możliwości Asyncio. W tej książce: porównanie programowania współbieżnego z wykorzystaniem Asyncio i wątków podstawy programowania bazującego na zdarzeniach możliwości Asyncio ważne dla programistów końcowych oraz twórców frameworków składnia async/await, w tym API koprocedur i klasy Future szczegółowe przypadki użycia kilku bibliotek zgodnych z Asyncio Programowanie asynchroniczne: nowa wizja bezpieczeństwa kodu Pythona!

Python: Journey from Novice to Expert. Journey from Novice to Expert

Fabrizio Romano, Dusty Phillips, Rick van Hattem

Python is a dynamic and powerful programming language, having its application in a wide range of domains. It has an easy-to-use, simple syntax, and a powerful library, which includes hundreds of modules to provide routines for a wide range of applications, thus making it a popular language among programing enthusiasts.This course will take you on a journey from basic programming practices to high-end tools and techniques giving you an edge over your peers. It follows an interesting learning path, divided into three modules. As you complete each one, you’ll have gained key skills and get ready for the material in the next module.The first module will begin with exploring all the essentials of Python programming in an easy-to-understand way. This will lay a good foundation for those who are interested in digging deeper. It has a practical and example-oriented approach through which both the introductory and the advanced topics are explained. Starting with the fundamentals of programming and Python, it ends by exploring topics, like GUIs, web apps, and data science.In the second module you will learn about object oriented programming techniques in Python. Starting with a detailed analysis of object-oriented technique and design, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. This module fully explains classes, data encapsulation, inheritance, polymorphism, abstraction, and exceptions with an emphasis on when you can use each principle to develop well-designed software.With a good foundation of Python you will move onto the third module which is a comprehensive tutorial covering advanced features of the Python language. Start by creating a project-specific environment using venv. This will introduce you to various Pythonic syntax and common pitfalls before moving onto functional features and advanced concepts, thereby gaining an expert level knowledge in programming and teaching how to script highest quality Python programs.

Python Parallel Programming Cookbook. Master efficient parallel programming to build powerful applications using Python

Giancarlo Zaccone

This book will teach you parallel programming techniques using examples in Python and will help you explore the many ways in which you can write code that allows more than one process to happen at once. Starting with introducing you to the world of parallel computing, it moves on to cover the fundamentals in Python. This is followed by exploring the thread-based parallelism model using the Python threading module by synchronizing threads and using locks, mutex, semaphores queues, GIL, and the thread pool. Next you will be taught about process-based parallelism where you will synchronize processes using message passing along with learning about the performance of MPI Python Modules. You will then go on to learn the asynchronous parallel programming model using the Python asyncio module along with handling exceptions. Moving on, you will discover distributed computing with Python, and learn how to install a broker, use Celery Python Module, and create a worker. You will understand anche Pycsp, the Scoop framework, and disk modules in Python. Further on, you will learnGPU programming withPython using the PyCUDA module along with evaluating performance limitations.

Python. Programowanie funkcyjne

Steven F. Lott

Zgodnie z paradygmatem programowania funkcyjnego największy nacisk należy kłaść na stałe i funkcje. Polega to na konstruowaniu funkcji oraz na obliczaniu wartości wyrażeń. W ten sposób otrzymuje się kod odporny na błędy. Python nie jest w pełni funkcyjnym językiem programowania, jednak pozwala na taki sposób pisania programów. Dzięki temu umożliwia tworzenie zwięzłego i eleganckiego kodu. Na przykład stosowanie wyrażeń generatorowych w Pythonie sprawia, że tworzone programy działają szybciej, ponieważ zużywają mniej zasobów. Niezależnie więc od stosowanego paradygmatu warto zapożyczyć pewne elementy programowania funkcyjnego i wykorzystać je do tworzenia ekspresyjnych i zwięzłych aplikacji w Pythonie. To znakomity podręcznik dla programistów, którzy chcą wykorzystać techniki i wzorce projektowe z funkcyjnych języków programowania, aby tworzyć w Pythonie zwięzłe, eleganckie i ekspresyjne programy - z czytelnym i łatwym w utrzymaniu kodem. Zawiera ogólny przegląd koncepcji funkcyjnych oraz wyjaśnia tak istotne pojęcia jak funkcje pierwszej klasy, funkcje wyższego rzędu, funkcje czyste, leniwe wartościowanie i wiele innych. Wnikliwie omawia sposób korzystania z tych funkcji w Pythonie 3.6, a także techniki przygotowywania i eksploracji danych. Ponadto pokazuje, w jaki sposób standardowa biblioteka Pythona pasuje do funkcyjnego modelu programowania. Co ważne, w książce znalazło się kilka przykładów prezentujących w praktyce opisane koncepcje. W książce między innymi: podstawy modelu programowania funkcyjnego działania na kolekcjach danych i przetwarzanie krotek projektowanie dekoratorów biblioteka PyMonad usługi sieciowe a programowanie funkcyjne Python: kod funkcyjny i funkcjonalny!