The applied python library (12 resultados)

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Condición: Neu. Neuware.

Taschenbuch. Condición: Neu. Neuware.

Condición: New. Print on Demand.

Paperback. Condición: new. Paperback. Build the Data Pipelines That Power Modern Businesses.Behind every dashboard, machine learning model, business report, or real-time analytics platform lies a data pipeline responsible for collecting, validating, transforming, and delivering trustworthy data. Building those pipelines requires far more than writing Python scripts, it requires engineering systems that are reliable, scalable, and capable of running unattended in production.Python for Data Engineering is a practical guide for Python developers who want to master the discipline of modern data engineering. Rather than focusing on isolated code examples, this book teaches you how to design complete data pipelines the way professional engineering teams build them: one reliable component at a time.Throughout the book, you'll build Conduit, a production-grade data pipeline that evolves chapter after chapter. Starting with structured data formats and database connectivity, you'll progressively develop a complete system capable of extracting data from multiple sources, validating data quality, transforming datasets efficiently, orchestrating workflows, monitoring pipeline health, and loading information into modern data warehouses.Unlike many books that concentrate only on ETL code, this guide emphasizes one of the most overlooked realities of data engineering: silent failures. A pipeline that finishes successfully can still produce incorrect data. Learning how to detect, prevent, and monitor these failures is one of the core engineering skills you'll develop throughout the book.Inside you'll learn how to: Build reliable ETL and ELT pipelines using PythonRead and process CSV, JSON, Parquet, APIs, and databasesDesign robust data validation and quality checksAutomate incremental loading and Change Data Capture (CDC)Work with SQL, SQLAlchemy, and modern database workflowsProcess large datasets efficiently using PySparkDesign dimensional models and production-ready data warehousesOrganize scalable Data Lakes using modern storage formatsTest, monitor, and deploy production-grade data pipelinesBuild complete end-to-end engineering projects from extraction to analyticsEvery chapter combines clear explanations, practical Python code, engineering best practices, and realistic business scenarios. Instead of memorizing isolated techniques, you'll understand why production pipelines fail, how experienced engineers prevent data corruption, and what separates experimental scripts from systems businesses can trust.Whether you're preparing for a career in data engineering, expanding your Python expertise, or transitioning from data analysis into large-scale data infrastructure, this book provides the practical knowledge needed to build reliable data systems with confidence.By the end of the journey, you won't simply know how to manipulate data.You'll know how to engineer the pipelines that deliver it. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

Condición: New. Print on Demand.

Paperback. Condición: new. Paperback. Stop Repeating Tasks. Start Building Automation That Works.Every developer has experienced it.Renaming hundreds of files. Cleaning spreadsheets. Downloading reports. Managing servers. Monitoring logs. Running the same commands every day. Updating cloud resources. Creating backups. Checking system health.Most of these tasks shouldn't be done manually.They should be automated.Python for Automation & Scripting is a practical guide for Python developers who want to move beyond simple scripts and build reliable automation systems that can run safely, efficiently, and unattended in real-world environments. Instead of focusing on isolated examples, this book teaches you how professional engineers design automation tools that are secure, maintainable, and production-ready.Throughout the book, you'll build Foreman, a complete automation platform that grows chapter by chapter. Beginning with filesystem operations and command-line tools, you'll progressively develop a professional automation toolkit capable of managing files, interacting with APIs, automating cloud resources, administering remote servers, scheduling recurring jobs, monitoring systems, handling failures, and deploying automation services that can be trusted to run without constant supervision.Unlike many automation books that simply show how to make scripts work, this guide focuses on something even more important: making automation safe. Automation amplifies everything it does-including mistakes. That's why you'll learn how to write defensive code, build idempotent workflows, implement structured logging, recover gracefully from failures, and create automation systems that remain reliable long after they leave your laptop.Inside you'll learn how to: Automate repetitive tasks using modern PythonBuild professional command-line applicationsWork safely with files, directories, and operating systemsConsume REST APIs and automate web-based workflowsPerform responsible web scrapingSchedule recurring jobs and background servicesManage remote servers using SSH and FabricAutomate AWS cloud infrastructure with PythonBuild Docker and infrastructure automation workflowsImplement logging, monitoring, error handling, and resilient automationPackage, distribute, and deploy production-ready automation toolsEvery chapter combines practical projects, fully explained Python code, engineering best practices, and realistic scenarios inspired by the daily work of developers, DevOps engineers, system administrators, and IT professionals.Whether your goal is to eliminate repetitive work, automate infrastructure, improve operational efficiency, or build powerful internal tools, this book provides the practical knowledge required to transform Python into one of your most valuable productivity tools.By the end of the book, you won't simply know how to write scripts.You'll know how to engineer automation systems that are reliable, scalable, and trusted to run in production.Build once.Automate forever. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condición: new. Paperback. Build the Data Pipelines That Power Modern Businesses.Behind every dashboard, machine learning model, business report, or real-time analytics platform lies a data pipeline responsible for collecting, validating, transforming, and delivering trustworthy data. Building those pipelines requires far more than writing Python scripts, it requires engineering systems that are reliable, scalable, and capable of running unattended in production.Python for Data Engineering is a practical guide for Python developers who want to master the discipline of modern data engineering. Rather than focusing on isolated code examples, this book teaches you how to design complete data pipelines the way professional engineering teams build them: one reliable component at a time.Throughout the book, you'll build Conduit, a production-grade data pipeline that evolves chapter after chapter. Starting with structured data formats and database connectivity, you'll progressively develop a complete system capable of extracting data from multiple sources, validating data quality, transforming datasets efficiently, orchestrating workflows, monitoring pipeline health, and loading information into modern data warehouses.Unlike many books that concentrate only on ETL code, this guide emphasizes one of the most overlooked realities of data engineering: silent failures. A pipeline that finishes successfully can still produce incorrect data. Learning how to detect, prevent, and monitor these failures is one of the core engineering skills you'll develop throughout the book.Inside you'll learn how to: Build reliable ETL and ELT pipelines using PythonRead and process CSV, JSON, Parquet, APIs, and databasesDesign robust data validation and quality checksAutomate incremental loading and Change Data Capture (CDC)Work with SQL, SQLAlchemy, and modern database workflowsProcess large datasets efficiently using PySparkDesign dimensional models and production-ready data warehousesOrganize scalable Data Lakes using modern storage formatsTest, monitor, and deploy production-grade data pipelinesBuild complete end-to-end engineering projects from extraction to analyticsEvery chapter combines clear explanations, practical Python code, engineering best practices, and realistic business scenarios. Instead of memorizing isolated techniques, you'll understand why production pipelines fail, how experienced engineers prevent data corruption, and what separates experimental scripts from systems businesses can trust.Whether you're preparing for a career in data engineering, expanding your Python expertise, or transitioning from data analysis into large-scale data infrastructure, this book provides the practical knowledge needed to build reliable data systems with confidence.By the end of the journey, you won't simply know how to manipulate data.You'll know how to engineer the pipelines that deliver it. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …

Paperback. Condición: new. Paperback. Stop Repeating Tasks. Start Building Automation That Works.Every developer has experienced it.Renaming hundreds of files. Cleaning spreadsheets. Downloading reports. Managing servers. Monitoring logs. Running the same commands every day. Updating cloud resources. Creating backups. Checking system health.Most of these tasks shouldn't be done manually.They should be automated.Python for Automation & Scripting is a practical guide for Python developers who want to move beyond simple scripts and build reliable automation systems that can run safely, efficiently, and unattended in real-world environments. Instead of focusing on isolated examples, this book teaches you how professional engineers design automation tools that are secure, maintainable, and production-ready.Throughout the book, you'll build Foreman, a complete automation platform that grows chapter by chapter. Beginning with filesystem operations and command-line tools, you'll progressively develop a professional automation toolkit capable of managing files, interacting with APIs, automating cloud resources, administering remote servers, scheduling recurring jobs, monitoring systems, handling failures, and deploying automation services that can be trusted to run without constant supervision.Unlike many automation books that simply show how to make scripts work, this guide focuses on something even more important: making automation safe. Automation amplifies everything it does-including mistakes. That's why you'll learn how to write defensive code, build idempotent workflows, implement structured logging, recover gracefully from failures, and create automation systems that remain reliable long after they leave your laptop.Inside you'll learn how to: Automate repetitive tasks using modern PythonBuild professional command-line applicationsWork safely with files, directories, and operating systemsConsume REST APIs and automate web-based workflowsPerform responsible web scrapingSchedule recurring jobs and background servicesManage remote servers using SSH and FabricAutomate AWS cloud infrastructure with PythonBuild Docker and infrastructure automation workflowsImplement logging, monitoring, error handling, and resilient automationPackage, distribute, and deploy production-ready automation toolsEvery chapter combines practical projects, fully explained Python code, engineering best practices, and realistic scenarios inspired by the daily work of developers, DevOps engineers, system administrators, and IT professionals.Whether your goal is to eliminate repetitive work, automate infrastructure, improve operational efficiency, or build powerful internal tools, this book provides the practical knowledge required to transform Python into one of your most valuable productivity tools.By the end of the book, you won't simply know how to write scripts.You'll know how to engineer automation systems that are reliable, scalable, and trusted to run in production.Build once.Automate forever. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…