This learning path is ideal developers who know the basics of Python and want to learn how to use the Flask framework to build powerful web solutions in Python.What You Will LearnBuild three web applications from the ground up using the powerful Python micro framework, Flask.Extend your applications to build advanced functionality, such as a user account control system using Flask-LoginLearn about web application security and defend against common attacks, such as SQL injection and XSSIntegrate with technologies like Redis, Sentry, MongoDB and so onBuild applications with integrations to most of the login mechanisms availableDon't just stop at development. Learn about deployment and post-deploymentUse SQLAlchemy to programmatically query a databaseDevelop a custom Flask extensionIn Detail
Are you a fan of Python? Want to use it to create powerful web applications? Then Flask is the perfect choice for you. This course will take you through the intricacies of the Flask Microframework, covering all it's components and elements and how to integrate it with useful third party libraries. Dive deep into what Flask has to offer and then you will create multiple Python apps from scratch on your own.
The first module will introduce you to web development using Flask to building fully functional web applications. Hands-on and pragmatic, this tutorial goes right to the crux of Flask by showing you how to build challenging real-world applications.
The second module introduces you to a number of recipes that will help you understand the power of Flask and its extensions. Start by seeing the different configurations that a Flask application can make use of. By the end of this module, you will have gained all the knowledge required to write Flask applications in the best possible way, and scale them with best practices.
The final module will walk you through advanced Flask topics while providing practical examples of for all your lessons learned. The module closes with a discussion of the different platforms that are available to deploy a Flask app on, the pros and cons of each one, and how to deploy on each one.
This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:Flask By-Example: Gareth DwyerFlask Framework Cookbook: Shalabh AggarwalMastering Flask: Jack StoufferStyle and approach
Filled with practical examples and recipes, this course is a great combination of example-driven learning complemented by exciting techniques to build powerful Python web applications with the Flask framework
Rather than impose development guidelines as other frameworks do, Flask leaves the business of extensions up to you. If you have Python experience, this book shows you how to take advantage of that creative freedom.Learn Flask’s basic application structure and write an example appWork with must-have components—templates, databases, web forms, and email supportUse packages and modules to structure a large application that scalesImplement user authentication, roles, and profilesBuild a blogging feature by reusing templates, paginating item lists, and working with rich textUse a Flask-based RESTful API to expose app functionality to smartphones, tablets, and other third-party clientsLearn how to run unit tests and enhance application performanceExplore options for deploying your web app to a production server
If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.What You Will LearnExplore how to use different machine learning models to ask different questions of your dataLearn how to build neural networks using Keras and TheanoFind out how to write clean and elegant Python code that will optimize the strength of your algorithmsDiscover how to embed your machine learning model in a web application for increased accessibilityPredict continuous target outcomes using regression analysisUncover hidden patterns and structures in data with clusteringOrganize data using effective pre-processing techniquesGet to grips with sentiment analysis to delve deeper into textual and social media dataIn Detail
Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.
Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization.Style and approach
Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow, self-paced tutorial gets you started with both Python 2.7 and 3.3— the latest releases in the 3.X and 2.X lines—plus all other releases in common use today. You’ll also learn some advanced language features that recently have become more common in Python code.Explore Python’s major built-in object types such as numbers, lists, and dictionariesCreate and process objects with Python statements, and learn Python’s general syntax modelUse functions to avoid code redundancy and package code for reuseOrganize statements, functions, and other tools into larger components with modulesDive into classes: Python’s object-oriented programming tool for structuring codeWrite large programs with Python’s exception-handling model and development toolsLearn advanced Python tools, including decorators, descriptors, metaclasses, and Unicode processing
Almost anyone can learn to write working script and create high quality code but they might lack a structured understanding of what it means to be 'Pythonic'. If you are a Python programmer who wants to code efficiently by getting the syntax and usage of a few intricate Python techniques exactly right, this book is for you.What You Will LearnCreate a virtualenv and start a new projectUnderstand how and when to use the functional programming paradigmGet familiar with the different ways the decorators can be written inUnderstand the power of generators and coroutines without digressing into lambda calculusCreate metaclasses and how it makes working with Python far easierGenerate HTML documentation out of documents and code using SphinxLearn how to track and optimize application performance, both memory and cpuUse the multiprocessing library, not just locally but also across multiple machinesGet a basic understanding of packaging and creating your own libraries/applicationsIn Detail
Python is a dynamic programming language. It is known for its high readability and hence it is often the first language learned by new programmers. Python being multi-paradigm, it can be used to achieve the same thing in different ways and it is compatible across different platforms. Even if you find writing Python code easy, writing code that is efficient, easy to maintain, and reuse is not so straightforward.
This book is an authoritative guide that will help you learn new advanced methods in a clear and contextualised way. It starts off by creating a project-specific environment using venv, introducing you to different Pythonic syntax and common pitfalls before moving on to cover the functional features in Python. It covers how to create different decorators, generators, and metaclasses. It also introduces you to functools.wraps and coroutines and how they work. Later on you will learn to use asyncio module for asynchronous clients and servers. You will also get familiar with different testing systems such as py.test, doctest, and unittest, and debugging tools such as Python debugger and faulthandler. You will learn to optimize application performance so that it works efficiently across multiple machines and Python versions. Finally, it will teach you how to access C functions with a simple Python call. By the end of the book, you will be able to write more advanced scripts and take on bigger challenges.Style and Approach
This book is a comprehensive guide that covers advanced features of the Python language, and communicate them with an authoritative understanding of the underlying rationale for how, when, and why to use them.
Have you looked at PHP and hated the clunky bloated syntax? Or looked at .Net and wished it was more open and flexible? Maybe you've tried your hand at GUI libraries in Python and found them hard to use? If your answer to any one of these questions is a yes, then this is just the book for you.
This book will take you on a journey from learning about web development using Flask to building fully functional web applications. In the first major project, we develop a dynamic Headlines application that displays the latest news headlines along with up-to-date currency and weather information. In project two, we build a Crime Map application that is backed by a MySQL database, allowing users to submit information on and the location of crimes in order to plot danger zones and other crime trends within an area. In the final project, we combine Flask with more modern technologies, such as Twitter's Bootstrap and the NoSQL database MongoDB, to create a Waiter Caller application that allows restaurant patrons to easily call a waiter to their table. This pragmatic tutorial will keep you engaged as you learn the crux of Flask by working on challenging real-world applications.Style and approach
This book will provide you with rich, practical experience of Flask. Every technology, that is employed along with Flask is comprehensively introduced, while the book focusses on developing web applications. Pointers to educational material are always given if you want to gain in-depth knowledge of the various technologies used.
Flask is a small but powerful web development framework for Python. Though Flask is termed a micro-framework, it is no way lacking in functionality; there are many extensions available to Flask which helps it to function at the same level as other large frameworks such as Django and Ruby on Rails.
This book will demonstrate how to develop a series of web application projects with the Python web micro-framework, and leverage extensions and external Python libraries and APIs to extend the development of a variety of larger and more complex web applications.
The book will start by explaining Python's Virtualenv library and how to create and switch between multiple virtual environments. You'll first build an SQL database-backed application, which will use Flask-WTF, Flask-SQLAlchemy, Jinja templates, and other methods. Next you'll move on to a timeline application, built using concepts including pytest-Flask, the Blinker package, data modelling for user timelines, exception handling, and creating and organizing CLI tools.
Moving on, you'll discover how to implement a photo timeline application where you'll explore topics such as writing and running celery tasks, API error handling and testing, and Werkzeug middlewares.
Finally, the book walks you through creating an application which fetches data from GitHub and stores it locally. You will also learn how to install and configure Flask-Click extension.Style and approach
This book covers how to effectively use the Flask micro-framework to develop a series of web applications. Each chapter focusses on the development of an application increasing in complexity with easy steps to follow.
This book is for anyone who wants to develop their knowledge of Python into something that can be used on the web. Flask follows the Python design principles and can be easily understood by anyone who knows Python, and even by those who do not.What You Will LearnCreate your web pages to add modularity and flexibility to your web app using templatesStore and retrieve relational data using SQLAlchemyDevelop schema migrations with AlembicProduce an admin section using flask-adminBuild RESTful APIs using Flask-RestlessSimulate requests and sessions using the Flask test clientMake Ajax requests from Jinja2 templatesIn Detail
Flask is a small and powerful web development framework for Python. It does not presume or force a developer to use a particular tool or library. Flask supports extensions that can add application features as if they were implemented in Flask itself. Flask's main task is to build web applications quickly and with less code. With its lightweight and efficient web development framework, Flask combines rapid development and clean, simple design.
This book will take you through the basics of learning how to apply your knowledge of Python to the web.
Starting with the creation of a “Hello world” Flask app, you will be introduced to the most common Flask APIs and Flask's interactive debugger. You will learn how to store and retrieve blog posts from a relational database using an ORM and also to map URLs to views. Furthermore, you will walk through template blocks, inheritance, file uploads, and static assets.
You will learn to authenticate users, build log in/log out functionality, and add an administrative dashboard for the blog. Moving on, you will discover how to make Ajax requests from the template and see how the Mock library can simplify testing complex interactions.
Finally, you will learn to deploy Flask applications securely and in an automated, repeatable manner, and explore some of the most popular Flask resources on the web.Style and approach
A comprehensive guide packed with real-world examples and popular use cases; starting with basic overviews and diving into the practical aspects of Flask Framework.
Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3.
This book covers:Python data model: understand how special methods are the key to the consistent behavior of objectsData structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode ageFunctions as objects: view Python functions as first-class objects, and understand how this affects popular design patternsObject-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritanceControl flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packagesMetaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work
You’ll gain a strong foundation in the language, including best practices for testing, debugging, code reuse, and other development tips. This book also shows you how to use Python for applications in business, science, and the arts, using various Python tools and open source packages.Learn simple data types, and basic math and text operationsUse data-wrangling techniques with Python’s built-in data structuresExplore Python code structure, including the use of functionsWrite large programs in Python, with modules and packagesDive into objects, classes, and other object-oriented featuresExamine storage from flat files to relational databases and NoSQLUse Python to build web clients, servers, APIs, and servicesManage system tasks such as programs, processes, and threadsUnderstand the basics of concurrency and network programming
—Andrew Hedges, Tapulous
This book takes you step-by-step through many fun and educational possibilities. Take advantage of several preloaded programming languages. Use the Raspberry Pi with Arduino. Create Internet-connected projects. Play with multimedia. With Raspberry Pi, you can do all of this and more.Get acquainted with hardware features on the Pi’s board Learn enough Linux to move around the operating system Pick up the basics of Python and Scratch—and start programming Draw graphics, play sounds, and handle mouse events with the Pygame framework Use the Pi’s input and output pins to do some hardware hacking Discover how Arduino and the Raspberry Pi complement each other Integrate USB webcams and other peripherals into your projects Create your own Pi-based web server with Python
Inside, you’ll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of application domains. Each recipe contains code samples you can use in your projects right away, along with a discussion about how and why the solution works.
Topics include:Data Structures and AlgorithmsStrings and TextNumbers, Dates, and TimesIterators and GeneratorsFiles and I/OData Encoding and ProcessingFunctionsClasses and ObjectsMetaprogrammingModules and PackagesNetwork and Web ProgrammingConcurrencyUtility Scripting and System AdministrationTesting, Debugging, and ExceptionsC Extensions
Ideal for enthusiasts, from students in robotics clubs to professional robotics scientists and engineers, each recipe describes a complete solution using ROS open source libraries and tools. You’ll learn how to complete tasks described in the recipes, as well as how to configure and recombine components for other tasks. If you’re familiar with Python, you’re ready to go.Learn fundamentals, including key ROS concepts, tools, and patternsProgram robots that perform an increasingly complex set of behaviors, using the powerful packages in ROSSee how to easily add perception and navigation abilities to your robotsIntegrate your own sensors, actuators, software libraries, and even a whole robot into the ROS ecosystemLearn tips and tricks for using ROS tools and community resources, debugging robot behavior, and using C++ in ROS
Packed with examples and exercises, Natural Language Processing with Python will help you:
Extract information from unstructured text, either to guess the topic or identify "named entities"Analyze linguistic structure in text, including parsing and semantic analysisAccess popular linguistic databases, including WordNet and treebanksIntegrate techniques drawn from fields as diverse as linguistics and artificial intelligence
This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.
While the Photon--and its accompanying cloud platform--is designed as a ready-to-go foundation for product developers and manufacturers, it's great for Maker projects, as you'll see in this book. You'll learn how to get started with the free development tools, deploy your sketches over WiFi, and build electronic projects that take advantage of the Photon's processing power, cloud platform, and input/output pins. What's more, the Photon is backward-compatible with its predecessor, the Spark Core.
Python in easy steps begins by explaining how to install the free Python interpreter so you can quickly begin to create your own executable programs by copying the book's examples. It demonstrates all the Python language basics before moving on to provide examples of Object Oriented Programming (OOP) and CGI scripting to handle web form data. The book concludes by demonstrating how you can use your acquired knowledge to create and deploy graphical windowed applications.
Python in easy steps makes no assumption you have previous knowledge of any programming language so it's ideal for the newcomer to computer programming. It has an easy-to-follow style that will appeal to programmers moving from another programming language, and to the student who is studying Python programming at school or college, and to those seeking a career in computing who need a fundamental understanding of computer programming.
Python is the language used to program the Raspberry Pi - covered by Raspberry Pi in easy steps.
Projects and tutorials include:Controlling devices over BluetoothUsing Python and Arduino programming environments on EdisonTracking objects with a webcam and OpenCVResponding to voice commands and talking backUsing and configuring Linux on Edison
By working with a single case study throughout this thoroughly revised book, you’ll learn the entire process of exploratory data analysis—from collecting data and generating statistics to identifying patterns and testing hypotheses. You’ll explore distributions, rules of probability, visualization, and many other tools and concepts.
New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries.Develop an understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyImport data from most sources with Python, rather than rely on data that’s cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data
Written by Mark Lutz—widely recognized as the world’s leading Python trainer—Python Pocket Reference is an ideal companion to O’Reilly’s classic Python tutorials, Learning Python and Programming Python, also written by Mark.
This fifth edition covers:Built-in object types, including numbers, lists, dictionaries, and moreStatements and syntax for creating and processing objectsFunctions and modules for structuring and reusing codePython’s object-oriented programming toolsBuilt-in functions, exceptions, and attributesSpecial operator overloading methodsWidely used standard library modules and extensionsCommand-line options and development toolsPython idioms and hintsThe Python SQL Database API
Inside, you'll learn about:
Interaction design and physical computingThe Arduino hardware and software development environmentBasics of electricity and electronicsPrototyping on a solderless breadboardDrawing a schematic diagram
And more. With inexpensive hardware and open-source software components that you can download free, getting started with Arduino is a snap. To use the introductory examples in this book, all you need is a USB Arduino, USB A-B cable, and an LED.
Join the tens of thousands of hobbyists who have discovered this incredible (and educational) platform. Written by the co-founder of the Arduino project, with illustrations by Elisa Canducci, Getting Started with Arduino gets you in on the fun! This 128-page book is a greatly expanded follow-up to the author's original short PDF that's available on the Arduino website.
Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming.
Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.
The example code for this unique data science book is maintained in a public GitHub repository. It’s designed to be easily accessible through a turnkey virtual machine that facilitates interactive learning with an easy-to-use collection of IPython Notebooks.
Through clear and concise instructions, you’ll learn how to get the most out of App Engine’s nearly unlimited computing power. This second edition is fully updated and expanded to cover Python 2.7 and Java 6 support, multithreading, asynchronous service APIs, and the use of frameworks such as Django 1.3 and webapp2.Understand how App Engine handles web requests and executes application codeLearn about new datastore features for queries and indexes, transactions, and data modelingCreate, manipulate, and serve large data files with the BlobstoreUse task queues to parallelize and distribute computation across the infrastructureEmploy scalable services for email, instant messaging, and communicating with web servicesTrack resource consumption, and optimize your application for speed and cost effectiveness
Python Projects is the ultimate resource for the Python programmer with basic skills who is ready to move beyond tutorials and start building projects.
The preeminent guide to bridge the gap between learning and doing, this book walks readers through the "where" and "how" of real-world Python programming with practical, actionable instruction. With a focus on real-world functionality, Python Projects details the ways that Python can be used to complete daily tasks and bring efficiency to businesses and individuals alike.
Python Projects is written specifically for those who know the Python syntax and lay of the land, but may still be intimidated by larger, more complex projects. The book provides a walk-through of the basic set-up for an application and the building and packaging for a library, and explains in detail the functionalities related to the projects. Topics include:
*How to maximize the power of the standard library modules
*Where to get third party libraries, and the best practices for utilization
*Creating, packaging, and reusing libraries within and across projects
*Building multi-layered functionality including networks, data, and user interfaces
*Setting up development environments and using virtualenv, pip, and more
Written by veteran Python trainers, the book is structured for easy navigation and logical progression that makes it ideal for individual, classroom, or corporate training.
For Python developers looking to apply their skills to real-world challenges, Python Projects is a goldmine of information and expert insight.
Bioinformatics Programming Using Python is perfect for anyone involved with bioinformatics -- researchers, support staff, students, and software developers interested in writing bioinformatics applications. You'll find it useful whether you already use Python, write code in another language, or have no programming experience at all. It's an excellent self-instruction tool, as well as a handy reference when facing the challenges of real-life programming tasks.Become familiar with Python's fundamentals, including ways to develop simple applicationsLearn how to use Python modules for pattern matching, structured text processing, online data retrieval, and database accessDiscover generalized patterns that cover a large proportion of how Python code is used in bioinformaticsLearn how to apply the principles and techniques of object-oriented programmingBenefit from the "tips and traps" section in each chapter
The Arduino is a simple microcontroller with an easy-to-learn programming environment, while the Raspberry Pi is a tiny Linux-based computer. This book clearly explains the differences between the Arduino and Raspberry Pi, when to use them, and to which purposes each are best suited.
Using these widely available and inexpensive platforms, you'll learn to control LEDs, motors of various types, solenoids, AC (alternating current) devices, heaters, coolers, displays, and sound. You'll even discover how to monitor and control these devices over the Internet. Working with solderless breadboards, you'll get up and running quickly, learning how to make projects that are as fun as they are informative. In Make: Action, you'll learn to:Build a can crusher using a linear actuator with your ArduinoHave an Arduino water your plantsBuild a personal traffic signal using LEDsMake a random balloon popper with ArduinoCool down your beverages with a thermostatic drink cooler you build yourselfUnderstand and use the PID control algorithmUse Raspberry Pi to create a puppet dance party that moves to your tweets!
If you are a software developer, data scientist, NLP or machine-learning enthusiast or just need to migrate your company's wiki from a legacy platform, then this book is for you. It is perfect for someone , who needs instant access to large amounts of semi-structured data effortlessly.What You Will LearnUnderstand HTML pages and write XPath to extract the data you needWrite Scrapy spiders with simple Python and do web crawlsPush your data into any database, search engine or analytics systemConfigure your spider to download files, images and use proxiesCreate efficient pipelines that shape data in precisely the form you wantUse Twisted Asynchronous API to process hundreds of items concurrentlyMake your crawler super-fast by learning how to tune Scrapy's performancePerform large scale distributed crawls with scrapyd and scrapinghubIn Detail
This book covers the long awaited Scrapy v 1.0 that empowers you to extract useful data from virtually any source with very little effort. It starts off by explaining the fundamentals of Scrapy framework, followed by a thorough description of how to extract data from any source, clean it up, shape it as per your requirement using Python and 3rd party APIs. Next you will be familiarised with the process of storing the scrapped data in databases as well as search engines and performing real time analytics on them with Spark Streaming. By the end of this book, you will perfect the art of scarping data for your applications with easeStyle and approach
It is a hands on guide, with first few chapters written as a tutorial, aiming to motivate you and get you started quickly. As the book progresses, more advanced features are explained with real world examples that can be reffered while developing your own web applications.
In a twelve-lesson progression, you’ll be exposed to this and more:Basic file input and output operations, incuding exceptionsUsing functions to compute and return multiple valuesBasic elements of a class definition and how to call methodsLists, dictionaries, sets, and other collectionsIteration through collections, files, sorted setsSearching strings with regular expressions (regex)Client and server programs for REST methodsUsing threads in Python for multiple tasksCGI-BIN programming for simple HTML Forms processingSix most common Python pitfalls
Take the One Hour challenge and see if you too can pick up 90% of syntax and semantics in less time than you probably spend commuting each day.
About the Author Victor R. Volkman graduated cum laude from Michigan Technological University with a BS in Computer Science in 1986. Since then, he has written for numerous publications, including The C Gazette, C++ Users Journal, Windows Developers Journal, and many others. He has taught college-level programming courses at Washtenaw Community College and has served on its Computer Information Science (CIS) Faculty Advisory Board for more than a decade. Volkman says Python helped him "rediscover the joy of programming again."
From Modern Software Press
This book is an in-depth guide to the use of pandas for data analysis, for either the seasoned data analysis practitioner or the novice user. It provides a basic introduction to the pandas framework, and takes users through the installation of the library and the IPython interactive environment. Thereafter, you will learn basic as well as advanced features, such as MultiIndexing, modifying data structures, and sampling data, which provide powerful capabilities for data analysis.
This book introduces the Kivy language and the necessary components so you can implement a graphical user interface (GUI) and learn techniques to handle events, detect gestures, and control multi-touch actions. You will learn strategies to animate your applications, and obtain interactive, professional-looking, and responsive results. You will be applying this knowledge throughout the book by developing three applications and tackling their diverse programming challenges.
Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.Use the IPython shell and Jupyter notebook for exploratory computingLearn basic and advanced features in NumPy (Numerical Python)Get started with data analysis tools in the pandas libraryUse flexible tools to load, clean, transform, merge, and reshape dataCreate informative visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, detailed examples
Each chapter includes exercises, using examples that run on Python 3 and Python 2.7. Learn how Kivy simplifies mobile development with its cross-platform API and domain-specific Kv language, and why this free and open source toolkit is ideal for commercial products.Design custom widgets with the Kv languageDelve into Kivy events, event handlers, and propertiesDynamically change which Kivy widgets are displayedUnderstand and apply iterative development principlesCreate basic animations, using Canvas and graphics primitivesStore local data with Kivy’s powerful key value storeAdd basic gestures to switch between app viewsImprove your app’s usability with Kivy’s built-in widgetsDeploy the app to your Android or iOS device, using Buildozer
The book deals with some of the most important and challenging areas of programming and computer science, but in a highly pedagogic and readable manner. The book covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others himself.
You won't find jargon, bloated samples, case studies, or history of Hello World and computer theory in this handy reference. This Python syntax reference is packed with useful information and is a must-have for any Python developer.
Fully updated for Java SE 8, Java: The Complete Reference, Ninth Edition explains how to develop, compile, debug, and run Java programs. Bestselling programming author Herb Schildt covers the entire Java language, including its syntax, keywords, and fundamental programming principles, as well as significant portions of the Java API library. JavaBeans, servlets, applets, and Swing are examined and real-world examples demonstrate Java in action. New Java SE 8 features such as lambda expressions, the stream library, and the default interface method are discussed in detail. This Oracle Press resource also offers a solid introduction to JavaFX.
Coverage includes:Data types, variables, arrays, and operators Control statements Classes, objects, and methods Method overloading and overriding Inheritance Interfaces and packages Exception handling Multithreaded programming Enumerations, autoboxing, and annotations The I/O classes Generics Lambda expressions String handling The Collections Framework Networking Event handling AWT and Swing The Concurrent API The Stream API Regular expressions JavaFX JavaBeans Applets and servlets Much, much more
If you are a Python developer, researcher, or analyst who wants to perform Geospatial, modeling, and GIS analysis with Python, then this book is for you. Familarity with digital mapping and analysis using Python or another scripting language for automation or crunching data manually is appreciated.What You Will LearnAutomate Geospatial analysis workflows using PythonCode the simplest possible GIS in 60 lines of PythonMold thematic maps with Python toolsGet hold of the various forms that geospatial data comes inProduce elevation contours using Python toolsCreate flood inundation modelsApply Geospatial analysis to find out about real-time data tracking and for storm chasingIn Detail
Geospatial Analysis is used in almost every field you can think of from medicine, to defense, to farming. This book will guide you gently into this exciting and complex field. It walks you through the building blocks of geospatial analysis and how to apply them to influence decision making using the latest Python software.
Learning Geospatial Analysis with Python, 2nd Edition uses the expressive and powerful Python 3 programming language to guide you through geographic information systems, remote sensing, topography, and more, while providing a framework for you to approach geospatial analysis effectively, but on your own terms. We start by giving you a little background on the field, and a survey of the techniques and technology used. We then split the field into its component specialty areas: GIS, remote sensing, elevation data, advanced modeling, and real-time data.
This book will teach you everything you need to know about, Geospatial Analysis from using a particular software package or API to using generic algorithms that can be applied. This book focuses on pure Python whenever possible to minimize compiling platform-dependent binaries, so that you don't become bogged down in just getting ready to do analysis. This book will round out your technical library through handy recipes that will give you a good understanding of a field that supplements many a modern day human endeavors.Style and approach
This is a practical, hands-on tutorial that teaches you all about Geospatial analysis interactively using Python.