Web App Development and Real-Time Web Analytics with Python

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Publisher :
ISBN 13 : 9781484277843
Total Pages : 0 pages
Book Rating : 4.2/5 (778 download)

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Book Synopsis Web App Development and Real-Time Web Analytics with Python by : Tshepo Chris Nokeri

Download or read book Web App Development and Real-Time Web Analytics with Python written by Tshepo Chris Nokeri and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to develop and deploy dashboards as web apps using the Python programming language, and how to integrate algorithms into web apps. Author Tshepo Chris Nokeri begins by introducing you to the basics of constructing and styling static and interactive charts and tables before exploring the basics of HTML, CSS, and Bootstrap, including an approach to building web pages with HTML. From there, he'll show you the key Python web frameworks and techniques for building web apps with them. You'll then see how to style web apps and incorporate themes, including interactive charts and tables to build dashboards, followed by a walkthrough of creating URL routes and securing web apps. You'll then progress to more advanced topics, like building machine learning algorithms and integrating them into a web app. The book concludes with a demonstration of how to deploy web apps in prevalent cloud platforms. Web App Development and Real-Time Web Analytics with Python is ideal for intermediate data scientists, machine learning engineers, and web developers, who have little or no knowledge about building web apps that implement bootstrap technologies. After completing this book, you will have the knowledge necessary to create added value for your organization, as you will understand how to link front-end and back-end development, including machine learning. You will: Create interactive graphs and render static graphs into interactive ones Understand the essentials of HTML, CSS, and Bootstrap Gain insight into the key Python web frameworks, and how to develop web applications using them Develop machine learning algorithms and integrate them into web apps Secure web apps and deploy them to cloud platforms.

Web App Development and Real-Time Web Analytics with Python

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Author :
Publisher : Apress
ISBN 13 : 9781484277829
Total Pages : 226 pages
Book Rating : 4.2/5 (778 download)

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Book Synopsis Web App Development and Real-Time Web Analytics with Python by : Tshepo Chris Nokeri

Download or read book Web App Development and Real-Time Web Analytics with Python written by Tshepo Chris Nokeri and published by Apress. This book was released on 2021-11-20 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to develop and deploy dashboards as web apps using the Python programming language, and how to integrate algorithms into web apps. Author Tshepo Chris Nokeri begins by introducing you to the basics of constructing and styling static and interactive charts and tables before exploring the basics of HTML, CSS, and Bootstrap, including an approach to building web pages with HTML. From there, he’ll show you the key Python web frameworks and techniques for building web apps with them. You’ll then see how to style web apps and incorporate themes, including interactive charts and tables to build dashboards, followed by a walkthrough of creating URL routes and securing web apps. You’ll then progress to more advanced topics, like building machine learning algorithms and integrating them into a web app. The book concludes with a demonstration of how to deploy web apps in prevalent cloud platforms. Web App Development and Real-Time Web Analytics with Python is ideal for intermediate data scientists, machine learning engineers, and web developers, who have little or no knowledge about building web apps that implement bootstrap technologies. After completing this book, you will have the knowledge necessary to create added value for your organization, as you will understand how to link front-end and back-end development, including machine learning. What You Will Learn Create interactive graphs and render static graphs into interactive ones Understand the essentials of HTML, CSS, and Bootstrap Gain insight into the key Python web frameworks, and how to develop web applications using them Develop machine learning algorithms and integrate them into web apps Secure web apps and deploy them to cloud platforms Who This Book Is For Intermediate data scientists, machine learning engineers, and web developers.

Learn Web Development with Python

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Publisher : Packt Publishing Ltd
ISBN 13 : 1789950880
Total Pages : 779 pages
Book Rating : 4.7/5 (899 download)

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Book Synopsis Learn Web Development with Python by : Fabrizio Romano

Download or read book Learn Web Development with Python written by Fabrizio Romano and published by Packt Publishing Ltd. This book was released on 2018-12-21 with total page 779 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to Python programming for web development using the most popular Python web framework - Django Key FeaturesLearn the fundamentals of programming with Python and building web appsBuild web applications from scratch with DjangoCreate real-world RESTful web services with the latest Django frameworkBook Description If you want to develop complete Python web apps with Django, this Learning Path is for you. It will walk you through Python programming techniques and guide you in implementing them when creating 4 professional Django projects, teaching you how to solve common problems and develop RESTful web services with Django and Python. You will learn how to build a blog application, a social image bookmarking website, an online shop, and an e-learning platform. Learn Web Development with Python will get you started with Python programming techniques, show you how to enhance your applications with AJAX, create RESTful APIs, and set up a production environment for your Django projects. Last but not least, you’ll learn the best practices for creating real-world applications. By the end of this Learning Path, you will have a full understanding of how Django works and how to use it to build web applications from scratch. This Learning Path includes content from the following Packt products: Learn Python Programming by Fabrizio RomanoDjango RESTful Web Services by Gastón C. HillarDjango Design Patterns and Best Practices by Arun RavindranWhat you will learnExplore the fundamentals of Python programming with interactive projectsGrasp essential coding concepts along with the basics of data structures and control flowDevelop RESTful APIs from scratch with Django and the Django REST FrameworkCreate automated tests for RESTful web servicesDebug, test, and profile RESTful web services with Django and the Django REST FrameworkUse Django with other technologies such as Redis and CeleryWho this book is for If you have little experience in coding or Python and want to learn how to build full-fledged web apps, this Learning Path is for you. No prior experience with RESTful web services, Python, or Django is required, but basic Python programming experience is needed to understand the concepts covered.

Python Data Analytics

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Publisher : Apress
ISBN 13 : 1484209583
Total Pages : 350 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Python Data Analytics by : Fabio Nelli

Download or read book Python Data Analytics written by Fabio Nelli and published by Apress. This book was released on 2015-08-25 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python Data Analytics will help you tackle the world of data acquisition and analysis using the power of the Python language. At the heart of this book lies the coverage of pandas, an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. Author Fabio Nelli expertly shows the strength of the Python programming language when applied to processing, managing and retrieving information. Inside, you will see how intuitive and flexible it is to discover and communicate meaningful patterns of data using Python scripts, reporting systems, and data export. This book examines how to go about obtaining, processing, storing, managing and analyzing data using the Python programming language. You will use Python and other open source tools to wrangle data and tease out interesting and important trends in that data that will allow you to predict future patterns. Whether you are dealing with sales data, investment data (stocks, bonds, etc.), medical data, web page usage, or any other type of data set, Python can be used to interpret, analyze, and glean information from a pile of numbers and statistics. This book is an invaluable reference with its examples of storing and accessing data in a database; it walks you through the process of report generation; it provides three real world case studies or examples that you can take with you for your everyday analysis needs.

Building Web Applications with Python and Neo4j

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Publisher : Packt Publishing Ltd
ISBN 13 : 178398399X
Total Pages : 184 pages
Book Rating : 4.7/5 (839 download)

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Book Synopsis Building Web Applications with Python and Neo4j by : Sumit Gupta

Download or read book Building Web Applications with Python and Neo4j written by Sumit Gupta and published by Packt Publishing Ltd. This book was released on 2015-07-16 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Py2neo is a simple and pragmatic Python library that provides access to the popular graph database Neo4j via its RESTful web service interface. This brings with it a heavily refactored core, a cleaner API, better performance, and some new idioms. You will begin with licensing and installing Neo4j, learning the fundamentals of Cypher as a graph query language, and exploring Cypher optimizations. You will discover how to integrate with various Python frameworks such as Flask and its extensions: Py2neo, Neomodel, and Django. Finally, the deployment aspects of your Python-based Neo4j applications in a production environment is also covered. By sequentially working through the steps in each chapter, you will quickly learn and master the various implementation details and integrations of Python and Neo4j, helping you to develop your use cases more quickly.

Monetizing Machine Learning

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Publisher : Apress
ISBN 13 : 1484238737
Total Pages : 510 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Monetizing Machine Learning by : Manuel Amunategui

Download or read book Monetizing Machine Learning written by Manuel Amunategui and published by Apress. This book was released on 2018-09-12 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take your Python machine learning ideas and create serverless web applications accessible by anyone with an Internet connection. Some of the most popular serverless cloud providers are covered in this book—Amazon, Microsoft, Google, and PythonAnywhere. You will work through a series of common Python data science problems in an increasing order of complexity. The practical projects presented in this book are simple, clear, and can be used as templates to jump-start many other types of projects. You will learn to create a web application around numerical or categorical predictions, understand the analysis of text, create powerful and interactive presentations, serve restricted access to data, and leverage web plugins to accept credit card payments and donations. You will get your projects into the hands of the world in no time. Each chapter follows three steps: modeling the right way, designing and developing a local web application, and deploying onto a popular and reliable serverless cloud provider. You can easily jump to or skip particular topics in the book. You also will have access to Jupyter notebooks and code repositories for complete versions of the code covered in the book. What You’ll Learn Extend your machine learning models using simple techniques to create compelling and interactive web dashboards Leverage the Flask web framework for rapid prototyping of your Python models and ideasCreate dynamic content powered by regression coefficients, logistic regressions, gradient boosting machines, Bayesian classifications, and more Harness the power of TensorFlow by exporting saved models into web applications Create rich web dashboards to handle complex real-time user input with JavaScript and Ajax to yield interactive and tailored contentCreate dashboards with paywalls to offer subscription-based accessAccess API data such as Google Maps, OpenWeather, etc.Apply different approaches to make sense of text data and return customized intelligence Build an intuitive and useful recommendation site to add value to users and entice them to keep coming back Utilize the freemium offerings of Google Analytics and analyze the results Take your ideas all the way to your customer's plate using the top serverless cloud providers Who This Book Is For Those with some programming experience with Python, code editing, and access to an interpreter in working order. The book is geared toward entrepreneurs who want to get their ideas onto the web without breaking the bank, small companies without an IT staff, students wanting exposure and training, and for all data science professionals ready to take things to the next level.

Getting Started with Streamlit for Data Science

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Publisher : Packt Publishing Ltd
ISBN 13 : 1800563205
Total Pages : 282 pages
Book Rating : 4.8/5 (5 download)

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Book Synopsis Getting Started with Streamlit for Data Science by : Tyler Richards

Download or read book Getting Started with Streamlit for Data Science written by Tyler Richards and published by Packt Publishing Ltd. This book was released on 2021-08-20 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create, deploy, and test your Python applications, analyses, and models with ease using Streamlit Key Features Learn how to showcase machine learning models in a Streamlit application effectively and efficiently Become an expert Streamlit creator by getting hands-on with complex application creation Discover how Streamlit enables you to create and deploy apps effortlessly Book DescriptionStreamlit shortens the development time for the creation of data-focused web applications, allowing data scientists to create web app prototypes using Python in hours instead of days. Getting Started with Streamlit for Data Science takes a hands-on approach to helping you learn the tips and tricks that will have you up and running with Streamlit in no time. You'll start with the fundamentals of Streamlit by creating a basic app and gradually build on the foundation by producing high-quality graphics with data visualization and testing machine learning models. As you advance through the chapters, you’ll walk through practical examples of both personal data projects and work-related data-focused web applications, and get to grips with more challenging topics such as using Streamlit Components, beautifying your apps, and quick deployment of your new apps. By the end of this book, you’ll be able to create dynamic web apps in Streamlit quickly and effortlessly using the power of Python.What you will learn Set up your first development environment and create a basic Streamlit app from scratch Explore methods for uploading, downloading, and manipulating data in Streamlit apps Create dynamic visualizations in Streamlit using built-in and imported Python libraries Discover strategies for creating and deploying machine learning models in Streamlit Use Streamlit sharing for one-click deployment Beautify Streamlit apps using themes, Streamlit Components, and Streamlit sidebar Implement best practices for prototyping your data science work with Streamlit Who this book is for This book is for data scientists and machine learning enthusiasts who want to create web apps using Streamlit. Whether you’re a junior data scientist looking to deploy your first machine learning project in Python to improve your resume or a senior data scientist who wants to use Streamlit to make convincing and dynamic data analyses, this book will help you get there! Prior knowledge of Python programming will assist with understanding the concepts covered.

Web Application Development with Streamlit

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Publisher :
ISBN 13 : 9781484281123
Total Pages : 0 pages
Book Rating : 4.2/5 (811 download)

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Book Synopsis Web Application Development with Streamlit by : Mohammad Khorasani

Download or read book Web Application Development with Streamlit written by Mohammad Khorasani and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transition from a back-end developer to a full-stack developer with knowledge of all the dimensions of web application development, namely, front-end, back-end and server-side software. This book provides a comprehensive overview of Streamlit, allowing developers and programmers of all backgrounds to get up to speed in as little time as possible. Streamlit is a pure Python web framework that will bridge the skills gap and shorten development time from weeks to hours. This book walks you through the complete cycle of web application development, from an introductory to advanced level with accompanying source code and resources. You will be exposed to developing basic, intermediate, and sophisticated user interfaces and subsequently you will be acquainted with data visualization, database systems, application security, and cloud deployment in Streamlit. In a market with a surplus demand for full stack developers, this skill set could not possibly come at a better time. In one sentence, Streamlit is a means for the empowerment of developers everywhere and all stand to gain from it. You will: Mutate big data in real-time Visualize big data interactively Implement web application security and privacy protocols Deploy Streamlit web applications to the cloud using Streamlit, Linux and Windows servers.

Network Data Analytics

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Publisher : Springer
ISBN 13 : 3319778005
Total Pages : 406 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Network Data Analytics by : K. G. Srinivasa

Download or read book Network Data Analytics written by K. G. Srinivasa and published by Springer. This book was released on 2018-04-26 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts. Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics.

Building Data Science Applications with FastAPI

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Publisher : Packt Publishing Ltd
ISBN 13 : 1801074186
Total Pages : 426 pages
Book Rating : 4.8/5 (1 download)

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Book Synopsis Building Data Science Applications with FastAPI by : Francois Voron

Download or read book Building Data Science Applications with FastAPI written by Francois Voron and published by Packt Publishing Ltd. This book was released on 2021-10-08 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get well-versed with FastAPI features and best practices for testing, monitoring, and deployment to run high-quality and robust data science applications Key FeaturesCover the concepts of the FastAPI framework, including aspects relating to asynchronous programming, type hinting, and dependency injectionDevelop efficient RESTful APIs for data science with modern PythonBuild, test, and deploy high performing data science and machine learning systems with FastAPIBook Description FastAPI is a web framework for building APIs with Python 3.6 and its later versions based on standard Python-type hints. With this book, you'll be able to create fast and reliable data science API backends using practical examples. This book starts with the basics of the FastAPI framework and associated modern Python programming language concepts. You'll be taken through all the aspects of the framework, including its powerful dependency injection system and how you can use it to communicate with databases, implement authentication and integrate machine learning models. Later, you'll cover best practices relating to testing and deployment to run a high-quality and robust application. You'll also be introduced to the extensive ecosystem of Python data science packages. As you progress, you'll learn how to build data science applications in Python using FastAPI. The book also demonstrates how to develop fast and efficient machine learning prediction backends and test them to achieve the best performance. Finally, you'll see how to implement a real-time face detection system using WebSockets and a web browser as a client. By the end of this FastAPI book, you'll have not only learned how to implement Python in data science projects but also how to maintain and design them to meet high programming standards with the help of FastAPI. What you will learnExplore the basics of modern Python and async I/O programmingGet to grips with basic and advanced concepts of the FastAPI frameworkImplement a FastAPI dependency to efficiently run a machine learning modelIntegrate a simple face detection algorithm in a FastAPI backendIntegrate common Python data science libraries in a web backendDeploy a performant and reliable web backend for a data science applicationWho this book is for This Python data science book is for data scientists and software developers interested in gaining knowledge of FastAPI and its ecosystem to build data science applications. Basic knowledge of data science and machine learning concepts and how to apply them in Python is recommended.

Ultimate Django for Web App Development Using Python

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Publisher : Orange Education Pvt Ltd
ISBN 13 : 8196815115
Total Pages : 360 pages
Book Rating : 4.1/5 (968 download)

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Book Synopsis Ultimate Django for Web App Development Using Python by : Leonardo Luis Lazzaro

Download or read book Ultimate Django for Web App Development Using Python written by Leonardo Luis Lazzaro and published by Orange Education Pvt Ltd. This book was released on 2024-01-22 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Craft Scalable and Dynamic Web Apps using Django and Python KEY FEATURES ● Real-World Practices and Solutions for Crafting Dynamic and Scalable Django Solutions. ● Build a Comprehensive Task Management System Hands-On. ● Explore Advanced API, Testing, and Deployment Techniques with Real-World Applications. DESCRIPTION This comprehensive guide is an indispensable resource for developers seeking to elevate their web development skills in Django and Python. The book begins by establishing a strong foundation and understanding of Django's architecture, emphasizing the Model-View-Template (MVT) pattern and a pivotal service layer for creating scalable web applications. The book then progresses to practical aspects, guiding readers through the development of a Task Management App. This hands-on approach reinforces fundamental concepts and showcases Django's flexibility and efficiency in real-world scenarios. The advanced sections of the book will help you tackle complex challenges, covering topics like preventing double-form submissions, implementing offline pessimistic and optimistic locking techniques, mastering API development with Django Ninja, and ensuring application reliability through exhaustive testing with pytest. The book culminates in practical insights for deploying Django applications with Docker and Kubernetes, this guide equips you to tackle real-world challenges effectively. WHAT WILL YOU LEARN ● Unlock the potential of Django 4.2 and Python for robust web development expertise. ● Seamlessly build and deploy a complete Django project, implementing essential features like authentication, authorization, and multi-tenant capabilities. ● Develop and secure APIs with Django Ninja, following best practices for a streamlined process. ● Gain mastery in testing with pytest, ensuring the creation of reliable, bug-free Django applications. ● Elevate your skills and create web solutions with confidence using the latest tools and techniques in Django development. WHO IS THIS BOOK FOR? This book caters to web development enthusiasts, Python developers and experienced programmers looking to build scalable web apps with Django. Whether you're new to programming or seeking advanced insights, this guide offers a progressive approach. Beginners establish a strong foundation, while seasoned developers delve into advanced topics like preventing double-form submissions and implementing locking techniques. TABLE OF CONTENTS 1. Introduction to Django and Python 2. Setting Up Your Development Environment 3. Getting Started with Django Projects and Apps 4. Django Models and PostgreSQL 5. Django Views and URL Handling 6. Using the Django Template Engine 7. Forms in Django 8. User Authentication and Authorization in Django 9. Django Ninja and APIs 10. Testing with pytest 11. Deploying Django Applications with Gunicorn and Docker 12. Final Thoughts and Future Directions Index

Practical Python Backend Programming

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Author :
Publisher : GitforGits
ISBN 13 : 8119177614
Total Pages : 254 pages
Book Rating : 4.1/5 (191 download)

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Book Synopsis Practical Python Backend Programming by : Tim Peters

Download or read book Practical Python Backend Programming written by Tim Peters and published by GitforGits. This book was released on 2024-01-31 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Practical Python Backend Programming" is a quick pragmatic book that teaches both new and experienced developers the fundamentals of backend development with Python. All sorts of developers, from Python programmers to non-Python programmers, full stack developers, and web developers, will find what they need to know to become experts in backend programming in this entire book. The book covers key topics in backend development, including how to set up stable development environments and how to use virtual environments for better dependency management. With this book, readers will have a firm grasp of Python programming with an emphasis on backend tasks by learning the language's syntax, data structures, and functions. The book teaches you to create and launch dynamic web apps by providing an in-depth look at web frameworks such as Flask and FastAPI. It teaches SQLAlchemy for efficient data handling and advanced database integration, and it shows to improve applications with databases like PostgreSQL, MySQL, and MongoDB. Strategies for managing concurrent operations and improving performance are also covered in the book, along with asynchronous programming in Python. This book delves into various authentication methods, secure communication protocols such as HTTPS, and techniques to secure REST APIs. For efficient management of asynchronous tasks and real-time data processing, it also introduces message brokers such as RabbitMQ and Kafka. The book teaches its readers how to containerize apps and manage them on a large scale by integrating technologies like Docker and Kubernetes. It goes on to talk about how to use serverless architectures, how to use modern tools for continuous integration and deployment, and how to deploy apps to cloud platforms like AWS. Key Learnings Build dynamic web apps with strong backend logic using Flask and FastAPI. Write efficient, well-structured backend code by learning Python's syntax, functions, and best practices. Make your apps more efficient and scalable by using asynchronous programming techniques. Investigate Kubernetes and Docker to orchestrate and containerize apps for improved deployment and scalability. Use AWS's cloud services to deploy apps with guaranteed uptime and lightning-fast performance. Improve efficiency and compatibility by setting up and managing Python development environments. Enhance your data handling capabilities by learning to integrate and manipulate databases using SQLAlchemy. Protect online apps with OAuth and JWT's sophisticated authorization and authentication features. Efficiently process data in real-time and broker messages with RabbitMQ and Kafka. Streamline processes, cut down on mistakes, and implement continuous integration and deployment by following best practices. Table of Content Fundamentals of Backend Development Building Your First Web Application with Flask Advanced Flask Development Introduction to FastAPI Working with Databases Asynchronous Programming in Python User Management and Security Deploying Python Backend Applications Microservices and Cloud Integration Message Brokers and Asynchronous Task Processing

Web Development with Django

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1839213779
Total Pages : 827 pages
Book Rating : 4.8/5 (392 download)

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Book Synopsis Web Development with Django by : Ben Shaw

Download or read book Web Development with Django written by Ben Shaw and published by Packt Publishing Ltd. This book was released on 2021-02-25 with total page 827 pages. Available in PDF, EPUB and Kindle. Book excerpt: Django is a popular Python-based framework for web application development. Like Python, Django is easy for beginners to learn and enables constant progress. This book will help aspiring web developers gain the skills to use Django to develop robust web apps.

Real-Time Analytics

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 1118838025
Total Pages : 432 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Real-Time Analytics by : Byron Ellis

Download or read book Real-Time Analytics written by Byron Ellis and published by John Wiley & Sons. This book was released on 2014-06-23 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Construct a robust end-to-end solution for analyzing and visualizing streaming data Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Byron Ellis teaches data analysts technologies to build an effective real-time analytics platform. This platform can then be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms. The author is among a very few leading experts in the field. He has a prestigious background in research, development, analytics, real-time visualization, and Big Data streaming and is uniquely qualified to help you explore this revolutionary field. Moving from a description of the overall analytic architecture of real-time analytics to using specific tools to obtain targeted results, Real-Time Analytics leverages open source and modern commercial tools to construct robust, efficient systems that can provide real-time analysis in a cost-effective manner. The book includes: A deep discussion of streaming data systems and architectures Instructions for analyzing, storing, and delivering streaming data Tips on aggregating data and working with sets Information on data warehousing options and techniques Real-Time Analytics includes in-depth case studies for website analytics, Big Data, visualizing streaming and mobile data, and mining and visualizing operational data flows. The book's "recipe" layout lets readers quickly learn and implement different techniques. All of the code examples presented in the book, along with their related data sets, are available on the companion website.

Practical Data Analysis

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Author :
Publisher : Dhiraj Bhuyan
ISBN 13 :
Total Pages : 323 pages
Book Rating : 4./5 ( download)

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Book Synopsis Practical Data Analysis by : Dhiraj Bhuyan

Download or read book Practical Data Analysis written by Dhiraj Bhuyan and published by Dhiraj Bhuyan. This book was released on 2019-11-30 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Practical Data Analysis – Using Python & Open Source Technology” uses a case-study based approach to explore some of the real-world applications of open source data analysis tools and techniques. Specifically, the following topics are covered in this book: 1. Open Source Data Analysis Tools and Techniques. 2. A Beginner’s Guide to “Python” for Data Analysis. 3. Implementing Custom Search Engines On The Fly. 4. Visualising Missing Data. 5. Sentiment Analysis and Named Entity Recognition. 6. Automatic Document Classification, Clustering and Summarisation. 7. Fraud Detection Using Machine Learning Techniques. 8. Forecasting - Using Data to Map the Future. 9. Continuous Monitoring and Real-Time Analytics. 10. Creating a Robot for Interacting with Web Applications. Free samples of the book is available at - http://timesofdatascience.com

Python API Development Fundamentals

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1838981101
Total Pages : 372 pages
Book Rating : 4.8/5 (389 download)

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Book Synopsis Python API Development Fundamentals by : Jack Chan

Download or read book Python API Development Fundamentals written by Jack Chan and published by Packt Publishing Ltd. This book was released on 2019-11-22 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn all that’s needed to build a fully functional web application from scratch. Key FeaturesDelve deep into the principle behind RESTful APILearn how to build a scalable web application with the RESTful API architecture and Flask frameworkKnow what are the exact tools and methodology to test your applications and how to use themBook Description Python is a flexible language that can be used for much more than just script development. By knowing the Python RESTful APIs work, you can build a powerful backend for web applications and mobile applications using Python. You'll take your first steps by building a simple API and learning how the frontend web interface can communicate with the backend. You'll also learn how to serialize and deserialize objects using the marshmallow library. Then, you'll learn how to authenticate and authorize users using Flask-JWT. You'll also learn how to enhance your APIs by adding useful features, such as email, image upload, searching, and pagination. You'll wrap up the whole book by deploying your APIs to the cloud. By the end of this book, you'll have the confidence and skill to leverage the power of RESTful APIs and Python to build efficient web applications. What you will learnUnderstand the concept of a RESTful APIBuild a RESTful API using Flask and the Flask-Restful extensionManipulate a database using Flask-SQLAlchemy and Flask-MigrateSend out plaintext and HTML format emails using the Mailgun APIImplement a pagination function using Flask-SQLAlchemyUse caching to improve API performance and efficiently obtain the latest informationDeploy an application to Heroku and test it using PostmanWho this book is for This book is ideal for aspiring software developers who have a basic-to-intermediate knowledge of Python programming and who want to develop web applications using Python. Knowledge of how web applications work will be beneficial but is not essential.

Real-Time Big Data Analytics

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1784397407
Total Pages : 326 pages
Book Rating : 4.7/5 (843 download)

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Book Synopsis Real-Time Big Data Analytics by : Sumit Gupta

Download or read book Real-Time Big Data Analytics written by Sumit Gupta and published by Packt Publishing Ltd. This book was released on 2016-02-26 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design, process, and analyze large sets of complex data in real time About This Book Get acquainted with transformations and database-level interactions, and ensure the reliability of messages processed using Storm Implement strategies to solve the challenges of real-time data processing Load datasets, build queries, and make recommendations using Spark SQL Who This Book Is For If you are a Big Data architect, developer, or a programmer who wants to develop applications/frameworks to implement real-time analytics using open source technologies, then this book is for you. What You Will Learn Explore big data technologies and frameworks Work through practical challenges and use cases of real-time analytics versus batch analytics Develop real-word use cases for processing and analyzing data in real-time using the programming paradigm of Apache Storm Handle and process real-time transactional data Optimize and tune Apache Storm for varied workloads and production deployments Process and stream data with Amazon Kinesis and Elastic MapReduce Perform interactive and exploratory data analytics using Spark SQL Develop common enterprise architectures/applications for real-time and batch analytics In Detail Enterprise has been striving hard to deal with the challenges of data arriving in real time or near real time. Although there are technologies such as Storm and Spark (and many more) that solve the challenges of real-time data, using the appropriate technology/framework for the right business use case is the key to success. This book provides you with the skills required to quickly design, implement and deploy your real-time analytics using real-world examples of big data use cases. From the beginning of the book, we will cover the basics of varied real-time data processing frameworks and technologies. We will discuss and explain the differences between batch and real-time processing in detail, and will also explore the techniques and programming concepts using Apache Storm. Moving on, we'll familiarize you with “Amazon Kinesis” for real-time data processing on cloud. We will further develop your understanding of real-time analytics through a comprehensive review of Apache Spark along with the high-level architecture and the building blocks of a Spark program. You will learn how to transform your data, get an output from transformations, and persist your results using Spark RDDs, using an interface called Spark SQL to work with Spark. At the end of this book, we will introduce Spark Streaming, the streaming library of Spark, and will walk you through the emerging Lambda Architecture (LA), which provides a hybrid platform for big data processing by combining real-time and precomputed batch data to provide a near real-time view of incoming data. Style and approach This step-by-step is an easy-to-follow, detailed tutorial, filled with practical examples of basic and advanced features. Each topic is explained sequentially and supported by real-world examples and executable code snippets.