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Python 2.6 Text Processing: Beginners Guide
by Jeff McneilThis book is part of the Beginner's Guide series. Each chapter covers the steps for various tasks to process data followed by brief explanation of what is happening in each task. The explanation is followed by a few questions on the topic under discussion that will serve as a refresher course for you. This book is for people who have text in one format, and need it in another, as quickly as possible. You don't need any experience with text processing, but you will need some basic knowledge of Python.
Python 3 - Intensivkurs
by Mark Pilgrim Florian WollenscheinPython ist eine vollwertige Programmiersprache, mit der sich auch größere Anwendungen entwickeln lassen. In den letzten Jahren hat sie an Beliebtheit gewonnen, und mit Python 3 steht eine stark erweiterte Version zur Verfügung. In dem Band werden die Werkzeuge und Programmiermöglichkeiten praxisorientiert vorgestellt. Jedes Kapitel beginnt mit einem vollwertigen, lauffähigen Codebeispiel, das jeweils ausführlich analysiert wird. Im Vordergrund stehen die unmittelbare praktische Anwendung und die Realisierung von Projekten mit Python 3.
Python 3 Object Oriented Programming
by Dusty PhillipsThe book begins with the very foundations of OOP and then uses practical examples to show how to correctly implement Object Oriented Programming in Python. Many examples are taken from real-world projects. The book focuses on high-level design as well as the gritty details of the Python syntax. The provided exercises inspire the reader to think about his or her own code, rather than providing solved problems. If you're new to Object Oriented Programming techniques, or if you have basic Python skills and wish to learn in depth how and when to correctly apply Object Oriented Programming in Python, this is the book for you. If you are an object-oriented programmer for other languages, you too will find this book a useful introduction to Python, as it uses terminology you are already familiar with. Python 2 programmers seeking a leg up in the new world of Python 3 will also find the book beneficial, and you need not necessarily know Python 2.
Python 3 Object-Oriented Programming: Build robust and maintainable software with object-oriented design patterns in Python 3.8, 3rd Edition
by null Dusty PhillipsUncover modern Python with this guide to Python data structures, design patterns, and effective object-oriented techniquesKey FeaturesIn-depth analysis of many common object-oriented design patterns that are more suitable to Python's unique styleLearn the latest Python syntax and librariesExplore abstract design patterns and implement them in Python 3.8Book DescriptionObject-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. This third edition of Python 3 Object-Oriented Programming fully explains classes, data encapsulation, and exceptions with an emphasis on when you can use each principle to develop well-designed software. Starting with a detailed analysis of object-oriented programming, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. You will learn how to create maintainable applications by studying higher level design patterns. The book will show you the complexities of string and file manipulation, and how Python distinguishes between binary and textual data. Not one, but two very powerful automated testing systems, unittest and pytest, will be introduced in this book. You'll get a comprehensive introduction to Python's concurrent programming ecosystem. By the end of the book, you will have thoroughly learned object-oriented principles using Python syntax and be able to create robust and reliable programs confidently.What you will learnImplement objects in Python by creating classes and defining methodsGrasp common concurrency techniques and pitfalls in Python 3Extend class functionality using inheritanceUnderstand when to use object-oriented features, and more importantly when not to use themDiscover what design patterns are and why they are different in PythonUncover the simplicity of unit testing and why it's so important in PythonExplore concurrent object-oriented programmingWho this book is forIf you're new to object-oriented programming techniques, or if you have basic Python skills and wish to learn in depth how and when to correctly apply OOP in Python, this is the book for you. If you are an object-oriented programmer for other languages or seeking a leg up in the new world of Python 3.8, you too will find this book a useful introduction to Python. Previous experience with Python 3 is not necessary.
Python 3 Object-oriented Programming - Second Edition
by Dusty PhillipsUnleash the power of Python 3 objects About This Book Stop writing scripts and start architecting programs Learn the latest Python syntax and libraries A practical, hands-on tutorial that teaches you all about abstract design patterns and how to implement them in Python 3 Who This Book Is For If you're new to object-oriented programming techniques, or if you have basic Python skills and wish to learn in depth how and when to correctly apply object-oriented programming in Python to design software, this is the book for you. What You Will Learn Implement objects in Python by creating classes and defining methods Separate related objects into a taxonomy of classes and describe the properties and behaviors of those objects via the class interface Extend class functionality using inheritance Understand when to use object-oriented features, and more importantly when not to use them Discover what design patterns are and why they are different in Python Uncover the simplicity of unit testing and why it's so important in Python Grasp common concurrency techniques and pitfalls in Python 3 Exploit object-oriented programming in key Python technologies such as Kivy and Django. Object-oriented programming concurrently with asyncio In Detail Python 3 is more versatile and easier to use than ever. It runs on all major platforms in a huge array of use cases. Coding in Python minimizes development time and increases productivity in comparison to other languages. Clean, maintainable code is easy to both read and write using Python's clear, concise syntax. Object-oriented programming is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Many modern programming languages utilize the powerful concepts behind object-oriented programming and Python is no exception. Starting with a detailed analysis of object-oriented analysis and design, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. This book 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. You'll get an in-depth analysis of many common object-oriented design patterns that are more suitable to Python's unique style. This book will not just teach Python syntax, but will also build your confidence in how to program. You will also learn how to create maintainable applications by studying higher level design patterns. Following this, you'll learn the complexities of string and file manipulation, and how Python distinguishes between binary and textual data. Not one, but two very powerful automated testing systems will be introduced in the book. After you discover the joy of unit testing and just how easy it can be, you'll study higher level libraries such as database connectors and GUI toolkits and learn how they uniquely apply object-oriented principles. You'll learn how these principles will allow you to make greater use of key members of the Python eco-system such as Django and Kivy. This new edition includes all the topics that made Python 3 Object-oriented Programming an instant Packt classic. It's also packed with updated content to reflect recent changes in the core Python library and covers modern third-party packages that were not available on the Python 3 platform when the book was first published. Style and approach Throughout the book you will learn key object-oriented programming techniques demonstrated by comprehensive case studies in the context of a larger project.
Python 3 Text Processing with NLTK 3 Cookbook
by Jacob PerkinsThis book is intended for Python programmers interested in learning how to do natural language processing. Maybe you've learned the limits of regular expressions the hard way, or you've realized that human language cannot be deterministically parsed like a computer language. Perhaps you have more text than you know what to do with, and need automated ways to analyze and structure that text. This Cookbook will show you how to train and use statistical language models to process text in ways that are practically impossible with standard programming tools. A basic knowledge of Python and the basic text processing concepts is expected. Some experience with regular expressions will also be helpful.
Python 3 Web Development Beginner's Guide
by Michel AndersPart of Packt's Beginner's Guide Series, this book follows a sample application, with lots of screenshots, to help you get to grips with the techniques as quickly as possible. Moderately experienced Python programmers who want to learn how to create fairly complex, database-driven, cross browser compatible web apps that are maintainable and look good will find this book of most use. All key technologies except for Python 3 are explained in detail.
Python Algorithmic Trading Cookbook: All The Recipes You Need To Implement Your Own Trading Strategies In Python
by Pushpak DagadeIf you are a financial analyst, financial trader, data analyst, or algorithmic trader who wants to learn algorithmic trading techniques to address challenges faced in the finance domain, then this book is for you. Basic knowledge of financial terminologies and working knowledge of the Python programming language are expected.
Python Algorithms
by Magnus Lie HetlandPython Algorithms, Second Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science in a highly readable manner. It 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.
Python All-in-One For Dummies
by John C. Shovic Alan SimpsonEverything you need to know to get into Python coding, with 7 books in one Python All-in-One For Dummies is your one-stop source for answers to all your Python questions. From creating apps to building complex web sites to sorting big data, Python provides a way to get the work done. This book is great as a starting point for those new to coding, and it also makes a perfect reference for experienced coders looking for more than the basics. Apply your Python skills to data analysis, learn to write AI-assisted code using GitHub CoPilot, and discover many more exciting uses for this top programming language. Get started coding in Python—even if you’re new to computer programming Reference all the essentials and the latest updates, so your code is air-tight Learn how Python can be a solution for large-scale projects and big datasets Accelerate your career path with this comprehensive guide to learning PythonExperienced and would-be coders alike will love this easy-to-follow guide to learning and applying Python.
Python All-in-One For Dummies
by John C. Shovic Alan SimpsonThe one-stop resource for all your Python queries Powerful and flexible, Python is one of the most popular programming languages in the world. It’s got all the right stuff for the software driving the cutting-edge of the development world—machine learning, robotics, artificial intelligence, data science, etc. The good news is that it’s also pretty straightforward to learn, with a simplified syntax, natural-language flow, and an amazingly supportive user community. The latest edition of Python All-in-One For Dummies gives you an inside look at the exciting possibilities offered in the Python world and provides a springboard to launch yourself into wherever you want your coding career to take you. These 7 straightforward and friendly mini-books assume the reader is a beginning programmer, and cover everything from the basic elements of Python code to introductions to the specific applications where you’ll use it. Intended as a hands-on reference, the focus is on practice over theory, providing you with examples to follow as well as code for you to copy and start modifying in the “real world”—helping you get up and running in your area of interest almost right away. This means you’ll be finishing off your first app or building and remote-controlling your own robot much faster than you can believe. Get a thorough grounding in the language basics Learn how the syntax is applied in high-profile industries Apply Python to projects in enterprise Find out how Python can get you into hot careers in AI, big data, and more Whether you’re a newbie coder or just want to add Python to your magic box of tricks, this is the perfect, practical introduction—and one you’ll return to as you grow your career.
Python All-in-One For Dummies
by Alan Simpson John ShovicYour one-stop resource on all things Python Thanks to its flexibility, Python has grown to become one of the most popular programming languages in the world. Developers use Python in app development, web development, data science, machine learning, and even in coding education classes. There's almost no type of project that Python can't make better. From creating apps to building complex websites to sorting big data, Python provides a way to get the work done. Python All-in-One For Dummies offers a starting point for those new to coding by explaining the basics of Python and demonstrating how it’s used in a variety of applications. Covers the basics of the language Explains its syntax through application in high-profile industries Shows how Python can be applied to projects in enterprise Delves into major undertakings including artificial intelligence, physical computing, machine learning, robotics and data analysis This book is perfect for anyone new to coding as well as experienced coders interested in adding Python to their toolbox.
Python and AWS Cookbook
by Mitch GarnaatIf you intend to use Amazon Web Services (AWS) for remote computing and storage, Python is an ideal programming language for developing applications and controlling your cloud-based infrastructure. This cookbook gets you started with more than two dozen recipes for using Python with AWS, based on the author's boto library. You'll find detailed recipes for working with the S3 storage service as well as EC2, the service that lets you design and build cloud applications. Each recipe includes a code solution you can use immediately, along with a discussion of why and how the recipe works. You also get detailed advice for using boto with AWS and other cloud services. This book's recipes include methods to help you: Launch instances on EC2, and keep track of them with tags Associate an Elastic IP address with an instance Restore a failed Elastic Block Store volume from a snapshot Store and monitor your own custom metrics in CloudWatch Create a bucket in S3 to contain your data objects Reduce the cost of storing noncritical data Prevent accidental deletion of data in S3
Python and AWS Cookbook: Managing Your Cloud with Python and Boto
by Mitch GarnaatIf you intend to use Amazon Web Services (AWS) for remote computing and storage, Python is an ideal programming language for developing applications and controlling your cloud-based infrastructure. This cookbook gets you started with more than two dozen recipes for using Python with AWS, based on the author’s boto library.You’ll find detailed recipes for working with the S3 storage service as well as EC2, the service that lets you design and build cloud applications. Each recipe includes a code solution you can use immediately, along with a discussion of why and how the recipe works. You also get detailed advice for using boto with AWS and other cloud services.This book’s recipes include methods to help you:Launch instances on EC2, and keep track of them with tagsAssociate an Elastic IP address with an instanceRestore a failed Elastic Block Store volume from a snapshotStore and monitor your own custom metrics in CloudWatchCreate a bucket in S3 to contain your data objectsReduce the cost of storing noncritical dataPrevent accidental deletion of data in S3
Python and HDF5: Unlocking Scientific Data
by Andrew ColletteGain hands-on experience with HDF5 for storing scientific data in Python. This practical guide quickly gets you up to speed on the details, best practices, and pitfalls of using HDF5 to archive and share numerical datasets ranging in size from gigabytes to terabytes.Through real-world examples and practical exercises, you’ll explore topics such as scientific datasets, hierarchically organized groups, user-defined metadata, and interoperable files. Examples are applicable for users of both Python 2 and Python 3. If you’re familiar with the basics of Python data analysis, this is an ideal introduction to HDF5.Get set up with HDF5 tools and create your first HDF5 fileWork with datasets by learning the HDF5 Dataset objectUnderstand advanced features like dataset chunking and compressionLearn how to work with HDF5’s hierarchical structure, using groupsCreate self-describing files by adding metadata with HDF5 attributesTake advantage of HDF5’s type system to create interoperable filesExpress relationships among data with references, named types, and dimension scalesDiscover how Python mechanisms for writing parallel code interact with HDF5
Python and R for the Modern Data Scientist
by Rick J. Scavetta Boyan AngelovSuccess in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. This book guides data scientists from the Python and R communities along the path to becoming bilingual. By recognizing the strengths of both languages, you'll discover new ways to accomplish data science tasks and expand your skill set.Authors Rick Scavetta and Boyan Angelov explain the parallel structures of these languages and highlight where each one excels, whether it's their linguistic features or the powers of their open source ecosystems. You'll learn how to use Python and R together in real-world settings and broaden your job opportunities as a bilingual data scientist.Learn Python and R from the perspective of your current languageUnderstand the strengths and weaknesses of each languageIdentify use cases where one language is better suited than the otherUnderstand the modern open source ecosystem available for both, including packages, frameworks, and workflowsLearn how to integrate R and Python in a single workflowFollow a case study that demonstrates ways to use these languages together
Python API Development Fundamentals: Develop a full-stack web application with Python and Flask
by Jack Chan Ray Chung Jack HuangLearn all that's needed to build a fully functional web application from scratch. Key Features Delve deep into the principle behind RESTful API Learn how to build a scalable web application with the RESTful API architecture and Flask framework Know what are the exact tools and methodology to test your applications and how to use them Book 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 learn Understand the concept of a RESTful API Build a RESTful API using Flask and the Flask-Restful extension Manipulate a database using Flask-SQLAlchemy and Flask-Migrate Send out plaintext and HTML format emails using the Mailgun API Implement a pagination function using Flask-SQLAlchemy Use caching to improve API performance and efficiently obtain the latest information Deploy an application to Heroku and test it using Postman Who 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.
The Python Apprentice
by Austin Bingham Robert SmallshireLearn the Python skills and culture you need to become a productive member of any Python project. About This Book • Taking a practical approach to studying Python • A clear appreciation of the sequence-oriented parts of Python • Emphasis on the way in which Python code is structured • Learn how to produce bug-free code by using testing tools Who This Book Is For The Python Apprentice is for anyone who wants to start building, creating and contributing towards a Python project. No previous knowledge of Python is required, although at least some familiarity with programming in another language is helpful. What You Will Learn • Learn the language of Python itself • Get a start on the Python standard library • Learn how to integrate 3rd party libraries • Develop libraries on your own • Become familiar with the basics of Python testing In Detail Experienced programmers want to know how to enhance their craft and we want to help them start as apprentices with Python. We know that before mastering Python you need to learn the culture and the tools to become a productive member of any Python project. Our goal with this book is to give you a practical and thorough introduction to Python programming, providing you with the insight and technical craftsmanship you need to be a productive member of any Python project. Python is a big language, and it's not our intention with this book to cover everything there is to know. We just want to make sure that you, as the developer, know the tools, basic idioms and of course the ins and outs of the language, the standard library and other modules to be able to jump into most projects. Style and approach We introduce topics gently and then revisit them on multiple occasions to add the depth required to support your progression as a Python developer. We've worked hard to structure the syllabus to avoid forward references. On only a few occasions do we require you to accept techniques on trust, before explaining them later; where we do, it's to deliberately establish good habits.
Python Architecture Patterns: Master API design, event-driven structures, and package management in Python
by Jaime BueltaMake the best of your test suites by using cutting-edge software architecture patterns in PythonKey FeaturesLearn how to create scalable and maintainable applicationsBuild a web system for micro messaging using concepts in the bookUse profiling to find bottlenecks and improve the speed of the systemBook DescriptionDeveloping large-scale systems that continuously grow in scale and complexity requires a thorough understanding of how software projects should be implemented. Software developers, architects, and technical management teams rely on high-level software design patterns such as microservices architecture, event-driven architecture, and the strategic patterns prescribed by domain-driven design (DDD) to make their work easier. This book covers these proven architecture design patterns with a forward-looking approach to help Python developers manage application complexity—and get the most value out of their test suites. Starting with the initial stages of design, you will learn about the main blocks and mental flow to use at the start of a project. The book covers various architectural patterns like microservices, web services, and event-driven structures and how to choose the one best suited to your project. Establishing a foundation of required concepts, you will progress into development, debugging, and testing to produce high-quality code that is ready for deployment. You will learn about ongoing operations on how to continue the task after the system is deployed to end users, as the software development lifecycle is never finished. By the end of this Python book, you will have developed "architectural thinking": a different way of approaching software design, including making changes to ongoing systems.What you will learnThink like an architect, analyzing software architecture patternsExplore API design, data storage, and data representation methodsInvestigate the nuances of common architectural structuresUtilize and interoperate elements of patterns such as microservicesImplement test-driven development to perform quality code testingRecognize chunks of code that can be restructured as packagesMaintain backward compatibility and deploy iterative changesWho this book is forThis book will help software developers and architects understand the structure of large complex systems and adopt architectural patterns that are scalable. Examples in the book are implemented in Python so a fair grasp of basic Python concepts is expected. Proficiency in any programming languages such as Java or JavaScript is sufficient.
Python Arithmetic: The Informational Nature of Numbers (Studies in Big Data #153)
by Vincenzo MancaThe book is a gentle introduction to Python using arithmetic, and vice versa, with a historical perspective encompassing programming languages within the wider process of development of mathematical notation. The revisitation of typical algorithms that are the core of elementary mathematical knowledge helps to grasp their essence and to clarify some assumptions that are often taken for granted but are very profound and of a very general nature. The first mathematician to define a systematic system for generating numbers was Archimedes of Syracuse in the third century B.C. The Archimedean system, which was defined in a book with the Latin title Arenarius, was not intended to define all numbers, but only very large numbers [13, 22, 23]. However, it can be considered the first system with the three main characteristics of a counting system that have the most important properties for complete arithmetic adequacy: creativity, infinity, and recursion. Creativity means that each numeral is new for numerals that precede it; infinity means that after any numeral there is always another numeral; recursion means that after an initial sequence of numerals coinciding with the digits of the system, digits repeat regularly in all subsequent numerals. Since the numerals are finite expressions of digits, their lengths increase along their generation. In the next chapter, Python is briefly introduced by linking this language to standard mathematical notation, which took its current form throughout a long process that extends from the introduction of decimal numerals to the eighteenth century, particularly within Euler’s notational and conceptual framework. The third chapter is devoted to counting algorithms, showing that something that is usually taken for granted has intriguing aspects that deserve a very subtle analysis: the authors will show that the Python representation of counting algorithms is very informative and demonstrates the informational nature of numbers.
Python Artificial Intelligence Projects: 9 real-world AI projects leveraging machine learning and deep learning with TensorFlow and Keras
by Santanu PattanayakThis book is intended for data scientists, machine learning professionals, and deep learning practitioners who are ready to extend their knowledge and possibilities in AI. If you want to build real-life smart systems to play a crucial role in every complex domain, then this book is what you need. Knowledge of Python programming and deep learning concepts are expected to get the most out of the book.
Python Artificial Intelligence Projects for Beginners: Get up and running with Artificial Intelligence using 8 smart and exciting AI applications
by Joshua EckrothBuild smart applications by implementing real-world artificial intelligence projectsKey FeaturesExplore a variety of AI projects with PythonGet well-versed with different types of neural networks and popular deep learning algorithmsLeverage popular Python deep learning libraries for your AI projectsBook DescriptionArtificial Intelligence (AI) is the newest technology that’s being employed among varied businesses, industries, and sectors. Python Artificial Intelligence Projects for Beginners demonstrates AI projects in Python, covering modern techniques that make up the world of Artificial Intelligence.This book begins with helping you to build your first prediction model using the popular Python library, scikit-learn. You will understand how to build a classifier using an effective machine learning technique, random forest, and decision trees. With exciting projects on predicting bird species, analyzing student performance data, song genre identification, and spam detection, you will learn the fundamentals and various algorithms and techniques that foster the development of these smart applications. In the concluding chapters, you will also understand deep learning and neural network mechanisms through these projects with the help of the Keras library.By the end of this book, you will be confident in building your own AI projects with Python and be ready to take on more advanced projects as you progressWhat you will learnBuild a prediction model using decision trees and random forestUse neural networks, decision trees, and random forests for classificationDetect YouTube comment spam with a bag-of-words and random forestsIdentify handwritten mathematical symbols with convolutional neural networksRevise the bird species identifier to use imagesLearn to detect positive and negative sentiment in user reviewsWho this book is forPython Artificial Intelligence Projects for Beginners is for Python developers who want to take their first step into the world of Artificial Intelligence using easy-to-follow projects. Basic working knowledge of Python programming is expected so that you’re able to play around with code
The Python Audio Cookbook: Recipes for Audio Scripting with Python
by Alexandros DrymonitisThe Python Audio Cookbook offers an introduction to Python for sound and multimedia applications, with chapters that cover writing your first Python programs, controlling Pyo with physical computing, and writing your own GUI, among many other topics. Guiding the reader through a variety of audio synthesis techniques, the book empowers readers to combine their projects with popular platforms, from the Arduino to Twitter, and state-of-the-art practices such as AI. The Python Audio Cookbook balances accessible explanations for theoretical concepts, including Python syntax, audio processing and machine learning, with practical applications. This book is an essential introductory guide to Python for sound and multimedia practitioners, as well as programmers interested in audio applications.
Python Automation Cookbook: 75 Python automation ideas for web scraping, data wrangling, and processing Excel, reports, emails, and more, 2nd Edition
by Jaime BueltaGet a firm grip on the core processes including browser automation, web scraping, Word, Excel, and GUI automation with Python 3.8 and higher Key Features Automate integral business processes such as report generation, email marketing, and lead generation Explore automated code testing and Python's growth in data science and AI automation in three new chapters Understand techniques to extract information and generate appealing graphs, and reports with Matplotlib Book Description In this updated and extended version of Python Automation Cookbook, each chapter now comprises the newest recipes and is revised to align with Python 3.8 and higher. The book includes three new chapters that focus on using Python for test automation, machine learning projects, and for working with messy data. This edition will enable you to develop a sharp understanding of the fundamentals required to automate business processes through real-world tasks, such as developing your first web scraping application, analyzing information to generate spreadsheet reports with graphs, and communicating with automatically generated emails. Once you grasp the basics, you will acquire the practical knowledge to create stunning graphs and charts using Matplotlib, generate rich graphics with relevant information, automate marketing campaigns, build machine learning projects, and execute debugging techniques. By the end of this book, you will be proficient in identifying monotonous tasks and resolving process inefficiencies to produce superior and reliable systems. What you will learn Learn data wrangling with Python and Pandas for your data science and AI projects Automate tasks such as text classification, email filtering, and web scraping with Python Use Matplotlib to generate a variety of stunning graphs, charts, and maps Automate a range of report generation tasks, from sending SMS and email campaigns to creating templates, adding images in Word, and even encrypting PDFs Master web scraping and web crawling of popular file formats and directories with tools like Beautiful Soup Build cool projects such as a Telegram bot for your marketing campaign, a reader from a news RSS feed, and a machine learning model to classify emails to the correct department based on their content Create fire-and-forget automation tasks by writing cron jobs, log files, and regexes with Python scripting Who this book is for Python Automation Cookbook - Second Edition is for developers, data enthusiasts or anyone who wants to automate monotonous manual tasks related to business processes such as finance, sales, and HR, among others. Working knowledge of Python is all you need to get started with this book.
Python Automation Cookbook: Explore the world of automation using Python recipes that will enhance your skills
by Jaime BueltaStep-by-step instructions which take you through each program to automate monotonous tasks with Python 3.7Key FeaturesAutomate integral business processes such as report generation, email marketing, and lead generationBuild your first web application that scrapes data and accesses websites' APIsCreate graphic-rich charts, graphs, and maps using MatplotlibBook DescriptionHave you been doing the same old monotonous office work over and over again? Or have you been trying to find an easy way to make your life better by automating some of your repetitive tasks? Through a tried and tested approach, understand how to automate all the boring stuff using Python. The Python Automation Cookbook helps you develop a clear understanding of how to automate your business processes using Python, including detecting opportunities by scraping the web, analyzing information to generate automatic spreadsheets reports with graphs, and communicating with automatically generated emails. You’ll learn how to get notifications via text messages and run tasks while your mind is focused on other important activities, followed by understanding how to scan documents such as résumés. Once you’ve gotten familiar with the fundamentals, you’ll be introduced to the world of graphs, along with studying how to produce organized charts using Matplotlib. In addition to this, you’ll gain in-depth knowledge of how to generate rich graphics showing relevant information. By the end of this book, you’ll have refined your skills by attaining a sound understanding of how to identify and correct problems to produce superior and reliable systems.What you will learnGet to grips with scraping a website to detect changesSearch and process raw sales files to aggregate information in spreadsheetsExplore techniques to extract information from an Excel spreadsheet and generate exciting reports with graphsDiscover the techniques required to generate random, print-friendly codes to be used as single-use couponsAutomatically generate a marketing campaign, contacting the recipients over different channelsIdentify and implement precise solutionsWho this book is forThe Python Automation Cookbook is for you if you are a developer or anyone who wants to automate monotonous manual tasks related to fields such as finance, sales, and HR, among others.