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Essential SQLAlchemy introduces a high-level open-source code library that makes it easier for Python programmers to access relational databases such as Oracle, DB2, MySQL, PostgreSQL, and SQLite. SQLAlchemy has become increasingly popular since its release, but it still lacks good offline documentation. This practical book fills the gap, and because a developer wrote it, you get an objective look at SQLAlchemy's tools rather than an advocate's description of all the "cool" features. SQLAlchemy includes both a database server-independent SQL expression language and an object-relational mapper (ORM) that lets you map "plain old Python objects" (POPOs) to database tables without substantially changing your existing Python code. Essential SQLAlchemy demonstrates how to use the library to create a simple database application, walks you through simple queries, and explains how to use SQLAlchemy to connect to multiple databases simultaneously with the same Metadata. You also learn how to: Create custom types to be used in your schema, and when it's useful to use custom rather than built-in types Run queries, updates, and deletes with SQLAlchemy's SQL expression language Build an object mapper with SQLAlchemy, and understand the differences between this and active record patterns used in other ORMs Create objects, save them to a session, and flush them to the database Use SQLAlchemy to model object oriented inheritance Provide a declarative, active record pattern for use with SQLAlchemy using the Elixir extension Use the SQLSoup extension to provide an automatic metadata and object model based on database reflection In addition, you'll learn how and when to use other extensions to SQLAlchemy, including AssociationProxy, OrderingList, and more. Essential SQLAlchemy is the much-needed guide for every Python developer using this code library. Instead of a feature-by-feature documentation, this book takes an "essentials" approach that gives you exactly what you need to become productive with SQLAlchemy right away.
"Dive into SQLAlchemy, the popular, open-source code library that helps Python programmers work with relational databases such as Oracle, MySQL, PostgresSQL, and SQLite. Using real-world examples, this practical guide shows you how to build a simple database application with SQLAlchemy, and how to connect to multiple databases simultaneously with the same metadata. SQL is a powerful language for querying and manipulating data, but it's tough to integrate it with your application. SQLAlchemy helps you map Python objects to database tables without substantially changing your existing Python code. If you're an intermediate Python developer with knowledge of basic SQL syntax and relational theory, this book serves as both a learning tool and a handy reference. Essential SQLAlchemy includes several sections: SQLAlchemy Core: Provide database services to your applications in a Pythonic way with the SQL Expression Language; SQLAlchemy ORM: Use the object relational mapper to bind database schema and operations to data objects in your application; Alembic: Use this lightweight database migration tool to handle changes to the database as your application evolves; and Cookbook: Learn how to use SQLAlchemy with web frameworks like Flask and libraries like SQLAcodegen."--Publisher's description
Dive into SQLAlchemy, the popular, open-source code library that helps Python programmers work with relational databases such as Oracle, MySQL, PostgresSQL, and SQLite. Using real-world examples, this practical guide shows you how to build a simple database application with SQLAlchemy, and how to connect to multiple databases simultaneously with the same metadata. SQL is a powerful language for querying and manipulating data, but it’s tough to integrate it with your application. SQLAlchemy helps you map Python objects to database tables without substantially changing your existing Python code. If you’re an intermediate Python developer with knowledge of basic SQL syntax and relational theory, this book serves as both a learning tool and a handy reference. Essential SQLAlchemy includes several sections: SQLAlchemy Core: Provide database services to your applications in a Pythonic way with the SQL Expression Language SQLAlchemy ORM: Use the object relational mapper to bind database schema and operations to data objects in your application Alembic: Use this lightweight database migration tool to handle changes to the database as your application evolves Cookbook: Learn how to use SQLAlchemy with web frameworks like Flask and libraries like SQLAcodegen
Master the math needed to excel in data science, machine learning, and statistics. In this book author Thomas Nield guides you through areas like calculus, probability, linear algebra, and statistics and how they apply to techniques like linear regression, logistic regression, and neural networks. Along the way you'll also gain practical insights into the state of data science and how to use those insights to maximize your career. Learn how to: Use Python code and libraries like SymPy, NumPy, and scikit-learn to explore essential mathematical concepts like calculus, linear algebra, statistics, and machine learning Understand techniques like linear regression, logistic regression, and neural networks in plain English, with minimal mathematical notation and jargon Perform descriptive statistics and hypothesis testing on a dataset to interpret p-values and statistical significance Manipulate vectors and matrices and perform matrix decomposition Integrate and build upon incremental knowledge of calculus, probability, statistics, and linear algebra, and apply it to regression models including neural networks Navigate practically through a data science career and avoid common pitfalls, assumptions, and biases while tuning your skill set to stand out in the job market
Understanding SQL's underlying theory is the best way to guarantee that your SQL code is correct and your database schema is robust and maintainable. On the other hand, if you're not well versed in the theory, you can fall into several traps. In SQL and Relational Theory, author C.J. Date demonstrates how you can apply relational theory directly to your use of SQL. With numerous examples and clear explanations of the reasoning behind them, you'll learn how to deal with common SQL dilemmas, such as: Should database access granted be through views instead of base tables? Nulls in your database are causing you to get wrong answers. Why? What can you do about it? Could you write an SQL query to find employees who have never been in the same department for more than six months at a time? SQL supports "quantified comparisons," but they're better avoided. Why? How do you avoid them? Constraints are crucially important, but most SQL products don't support them properly. What can you do to resolve this situation? Database theory and practice have evolved since Edgar Codd originally defined the relational model back in 1969. Independent of any SQL products, SQL and Relational Theory draws on decades of research to present the most up-to-date treatment of the material available anywhere. Anyone with a modest to advanced background in SQL will benefit from the many insights in this book.
SQL is the ubiquitous language for software developers working with structured data. Most developers who rely on SQL are experts in their favorite language (such as Java, Python, or Go), but they're not experts in SQL. They often depend on antipatterns - solutions that look right but become increasingly painful to work with as you uncover their hidden costs. Learn to identify and avoid many of these common blunders. Refactor an inherited nightmare into a data model that really works. Updated for the current versions of MySQL and Python, this new edition adds a dozen brand new mini-antipatterns for quick wins. No matter which platform, framework, or language you use, the database is the foundation of your application, and the SQL database language is the standard for working with it. Antipatterns are solutions that look simple at the surface, but soon mire you down with needless work. Learn to identify these traps, and craft better solutions for the often-asked questions in this book. Avoid the mistakes that lead to poor performance and quality, and master the principles that make SQL a powerful and flexible tool for handling data and logic. Dive deep into SQL and database design, and learn to recognize the most common missteps made by software developers in database modeling, SQL query logic, and code design of data-driven applications. See practical examples of misconceptions about SQL that can lure software projects astray. Find the greatest value in each group of data. Understand why an intersection table may be your new best friend. Store passwords securely and don't reinvent the wheel. Handle NULL values like a pro. Defend your web applications against the security weakness of SQL injection. Use SQL the right way - it can save you from headaches and needless work, and let your application really shine! What You Need: The SQL examples use the MySQL 8.0 flavor, but other popular brands of RDBMS are mentioned. Other code examples use Python 3.9+ or Ruby 2.7+.
Updated for the latest database management systems -- including MySQL 6.0, Oracle 11g, and Microsoft's SQL Server 2008 -- this introductory guide will get you up and running with SQL quickly. Whether you need to write database applications, perform administrative tasks, or generate reports, Learning SQL, Second Edition, will help you easily master all the SQL fundamentals. Each chapter presents a self-contained lesson on a key SQL concept or technique, with numerous illustrations and annotated examples. Exercises at the end of each chapter let you practice the skills you learn. With this book, you will: Move quickly through SQL basics and learn several advanced features Use SQL data statements to generate, manipulate, and retrieve data Create database objects, such as tables, indexes, and constraints, using SQL schema statements Learn how data sets interact with queries, and understand the importance of subqueries Convert and manipulate data with SQL's built-in functions, and use conditional logic in data statements Knowledge of SQL is a must for interacting with data. With Learning SQL, you'll quickly learn how to put the power and flexibility of this language to work.
Take full creative control of your web applications with Flask, the Python-based microframework. With the second edition of this hands-on book, youâ??ll learn Flask from the ground up by developing a complete, real-world application created by author Miguel Grinberg. This refreshed edition accounts for important technology changes that have occurred in the past three years. Explore the frameworkâ??s core functionality, and learn how to extend applications with advanced web techniques such as database migrations and an application programming interface. The first part of each chapter provides you with reference and background for the topic in question, while the second part guides you through a hands-on implementation. If you have Python experience, youâ??re ready to take advantage of the creative freedom Flask provides. Three sections include: A thorough introduction to Flask: explore web application development basics with Flask and an application structure appropriate for medium and large applications Building Flasky: learn how to build an open source blogging application step-by-step by reusing templates, paginating item lists, and working with rich text Going the last mile: dive into unit testing strategies, performance analysis techniques, and deployment options for your Flask application
Discover "SYSTEMS INTEGRATION WITH PYTHON 2nd Edition 2024: A Quick and Practical Guide! Essential for Students and Professionals" – your definitive resource for mastering system integration in a practical and efficient way. Whether you are a beginner or an experienced professional, this book is designed to be the indispensable tool that will take your skills to the next level. Written by Diego Rodrigues, a best-selling author with over 1800 titles published in six languages, this manual offers a comprehensive approach that covers everything from the fundamentals of integration to the most advanced practices. With clear and direct language, each chapter is structured to provide deep learning and immediate application. You will learn how to connect systems through RESTful APIs, integrate cloud services like AWS, Google Cloud, and Azure, and manage both relational and non-relational databases with Python. Additionally, the book explores messaging techniques, process automation with CI/CD, and much more, all aimed at preparing you to face the technological challenges of today and tomorrow. Open the sample of this book and see how system integration can revolutionize your practices, optimizing processes, improving efficiency, and providing a strategic vision that will boost your projects and career. Tags: system integration python APIs RESTful integration databases cloud services Flask Django FastAPI CI/CD process automation continuous microservices messaging RabbitMQ Kafka SQLAlchemy Celery NoSQL MongoDB Redis Cassandra software development automation serverless DevOps infrastructure as code systems architecture cybersecurity monitoring testing data integration ETL data pipelines cloud storage MySQL PostgreSQL SQLite Docker Kubernetes Jenkins Ansible Terraform GitHub Bitbucket Jenkinsfile PySpark Hadoop Airflow Swagger OpenAPI YAML JSON XML REST SOAP MQTT WebSockets BLE edge computing machine learning artificial intelligence AWS Google Cloud Azure databricks Python Java Linux Kali Linux HTML ASP.NET Ada Assembly Language BASIC Borland Delphi C C# C++ CSS Cobol Compilers DHTML Fortran General HTML Java JavaScript LISP PHP Pascal Perl Prolog RPG Ruby SQL Swift UML Elixir Haskell VBScript Visual Basic XHTML XML XSL Django Flask Ruby on Rails Angular React Vue.js Node.js Laravel Spring Hibernate .NET Core Express.js TensorFlow PyTorch Jupyter Notebook Keras Bootstrap Foundation jQuery SASS LESS Scala Groovy MATLAB R Objective-C Rust Go Kotlin TypeScript Elixir Dart SwiftUI Xamarin React Native NumPy Pandas SciPy Matplotlib Seaborn D3.js OpenCV NLTK PySpark BeautifulSoup Scikit-learn XGBoost CatBoost LightGBM FastAPI Celery Tornado Redis RabbitMQ Kubernetes Docker Jenkins Terraform Ansible Vagrant GitHub GitLab CircleCI Travis CI Linear Regression Logistic Regression Decision Trees Random Forests FastAPI AI ML K-Means Clustering Support Vector Tornado Machines Gradient Boosting Neural Networks LSTMs CNNs GANs ANDROID IOS MACOS WINDOWS Nmap Metasploit Framework Wireshark Aircrack-ng John the Ripper Burp Suite SQLmap Maltego Autopsy Volatility IDA Pro OllyDbg YARA Snort ClamAV iOS Netcat Tcpdump Foremost Cuckoo Sandbox Fierce HTTrack Kismet Hydra Nikto OpenVAS Nessus ZAP Radare2 Binwalk GDB OWASP Amass Dnsenum Dirbuster Wpscan Responder Setoolkit Searchsploit Recon-ng BeEF aws google cloud ibm azure databricks nvidia meta x Power BI IoT CI/CD Hadoop Spark Pandas NumPy Dask SQLAlchemy web scraping mysql big data science openai chatgpt Handler RunOnUiThread()Qiskit Q# Cassandra Bigtable VIRUS MALWARE docker kubernetes Kali Linux Nmap Metasploit Wireshark information security pen test cybersecurity Linux distributions ethical hacking vulnerability analysis system exploration wireless attacks web application security malware analysis social engineering Android iOS Social Engineering Toolkit SET computer science IT professionals cybersecurity careers cybersecurity expertise cybersecurity library cybersecurity training Linux operating systems cybersecurity tools ethical hacking tools security testing penetration test cycle security concepts mobile security cybersecurity fundamentals cybersecurity techniques cybersecurity skills cybersecurity industry global cybersecurity trends Kali Linux tools cybersecurity education cybersecurity innovation penetration test tools cybersecurity best practices global cybersecurity companies cybersecurity solutions IBM Google Microsoft AWS Cisco Oracle cybersecurity consulting cybersecurity framework network security cybersecurity courses cybersecurity tutorials Linux security cybersecurity challenges cybersecurity landscape cloud security cybersecurity threats cybersecurity compliance cybersecurity research cybersecurity technology
A guide to using the Python computer language to handle a variety of tasks in both the Unix and Linux servers.