Humble Tech Book Bundle: Python, Rust, and Data by O'Reilly
Creativity meets data with Python and Rust
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Python for Data Analysis
Wes McKinney, O'Reilly
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3rd Edition
Learning Python
Mark Lutz, O'Reilly
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6th Edition
Think Python
Allen B. Downey, O'Reilly
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3rd Edition
Programming Rust
Jim Blandy, Jason Orendorff, Leonora F. S. Tindall, O'Reilly
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2nd Edition
Introducing Python
Bill Lubanovic, O'Reilly
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3rd Edition
Causal Inference in Python
Matheus Facure, O'Reilly
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How many buyers will an additional dollar of online marketing bring in? Which customers will only buy when given a discount coupon? How do you… How many buyers will an additional dollar of online marketing bring in? Which customers will only buy when given a discount coupon? How do you establish an optimal pricing strategy? The best way to determine how the levers at our disposal affect the business metrics we want to drive is through causal inference. In this book, author Matheus Facure, senior data scientist at Nubank, explains the largely untapped potential of causal inference for estimating impacts and effects. Managers, data scientists, and business analysts will learn classical causal inference methods like randomized control trials (A/B tests), linear regression, propensity score, synthetic controls, and difference-in-differences. Each method is accompanied by an application in the industry to serve as a grounding example. With this book, you will: Learn how to use basic concepts of causal inference Frame a business problem as a causal inference problem Understand how bias gets in the way of causal inference Learn how causal effects can differ from person to person Use repeated observations of the same customers across time to adjust for biases Understand how causal effects differ across geographic locations Examine noncompliance bias and effect dilution
Rust Atomics and Locks
Mara Bos, O'Reilly
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The Rust programming language is extremely well suited for concurrency, and its ecosystem has many libraries that include lots of concurrent data… The Rust programming language is extremely well suited for concurrency, and its ecosystem has many libraries that include lots of concurrent data structures, locks, and more. But implementing those structures correctly can be very difficult. Even in the most well-used libraries, memory ordering bugs are not uncommon. In this practical book, Mara Bos, leader of the Rust library team, helps Rust programmers of all levels gain a clear understanding of low-level concurrency. You'll learn everything about atomics and memory ordering and how they're combined with basic operating system APIs to build common primitives like mutexes and condition variables. Once you're done, you'll have a firm grasp of how Rust's memory model, the processor, and the role of the operating system all fit together. With this guide, you'll learn: How Rust's type system works exceptionally well for programming concurrency correctly All about mutexes, condition variables, atomics, and memory ordering What happens in practice with atomic operations on Intel and ARM processors How locks are implemented with support from the operating system How to write correct code that includes concurrency, atomics, and locks How to build your own locking and synchronization primitives correctly
High Performance Python
Micha Gorelick, Ian Ozsvald, O'Reilly
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3rd Edition
Effective Rust
David Drysdale, O'Reilly
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Rust's popularity is growing, due in part to features like memory safety, type safety, and thread safety. But these same elements can also make… Rust's popularity is growing, due in part to features like memory safety, type safety, and thread safety. But these same elements can also make learning Rust a challenge, even for experienced programmers. This practical guide helps you make the transition to writing idiomatic Rust—while also making full use of Rust's type system, safety guarantees, and burgeoning ecosystem. If you're a software engineer who has experience with an existing compiled language, or if you've struggled to convert a basic understanding of Rust syntax into working programs, this book is for you. By focusing on the conceptual differences between Rust and other compiled languages, and by providing specific recommendations that programmers can easily follow, Effective Rust will soon have you writing fluent Rust, not just badly translated C++. Understand the structure of Rust's type system Learn Rust idioms for error handling, iteration, and more Discover how to work with Rust's crate ecosystem Use Rust's type system to express your design Win fights with the borrow checker Build a robust project that takes full advantage of the Rust tooling ecosystem
Python for Excel
Felix Zumstein, O'Reilly
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2nd Edition
Python Polars: The Definitive Guide
Jeroen Janssens, Thijs Nieuwdorp, O'Reilly
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Unlock the power of Polars, a Python package for transforming, analyzing, and visualizing data. In this hands-on guide, Jeroen Janssens and Thijs… Unlock the power of Polars, a Python package for transforming, analyzing, and visualizing data. In this hands-on guide, Jeroen Janssens and Thijs Nieuwdorp walk you through every feature of Polars, showing you how to use it for real-world tasks like data wrangling, exploratory data analysis, building pipelines, and more. Whether you're a seasoned data professional or new to data science, you'll quickly master Polars' expressive API and its underlying concepts. You don't need to have experience with pandas, but if you do, this book will help you make a seamless transition. The many practical examples and real-world datasets are available on GitHub, so you can easily follow along. Process data from CSV, Parquet, spreadsheets, databases, and the cloud Get a solid understanding of Expressions, the building blocks of every query Handle complex data types, including text, time, and nested structures Use both eager and lazy APIs, and know when to use each Visualize your data with Altair, hvPlot, plotnine, and Great Tables Extend Polars with your own Python functions and Rust plugins Leverage GPU acceleration to boost performance even further
Command-Line Rust
Ken Youens-Clark, O'Reilly
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2026 Updated Edition
Python in a Nutshell
Alex Martelli, Anna Martelli Ravenscroft, Steve Holden, Paul McGuire, O'Reilly
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4th Edition
Test-Driven Development with Python
Harry Percival, O'Reilly
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3rd Edition
Async Rust
Maxwell Flitton, Caroline Morton, O'Reilly
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Already popular among programmers for its memory safety and speed, the Rust programming language is also valuable for asynchrony. This practical book… Already popular among programmers for its memory safety and speed, the Rust programming language is also valuable for asynchrony. This practical book shows you how asynchronous Rust can help you solve problems that require multitasking. You'll learn how to apply async programming to solve problems with an async approach. You will also dive deeper into async runtimes, implementing your own ways in which async runtimes handle incoming tasks. Authors Maxwell Flitton and Caroline Morton also show you how to implement the Tokio software library to help you with incoming traffic, communicate between threads with shared memory and channels, and design a range of complex solutions using actors. You'll also learn to perform unit and end-to-end tests on a Rust async system. With this book, you'll learn: How Rust approaches async programming How coroutines relate to async Rust Reactive programming and how to implement pub sub in async rust How to solve problems using actors How to customize Tokio to gain control over how tasks are processed Async Rust design patterns How to build an async TCP server just using the standard library How to unit test async Rust By the end of the book, you'll be able to implement your own async TCP server completely from the standard library with zero external dependencies, and unit test your async code.
Python for DevOps
Noah Gift, Kennedy Behrman, Alfredo Deza, Grig Gheorghiu, O'Reilly
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Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation.… Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout these transformations, Python has become one of the most popular languages in the world. This practical resource shows you how to use Python for everyday Linux systems administration tasks with today‚Äôs most useful DevOps tools, including Docker, Kubernetes, and Terraform. Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you‚Äôll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to "get stuff done" in Python? This is your guide. Python foundations, including a brief introduction to the language How to automate text, write command-line tools, and automate the filesystem Linux utilities, package management, build systems, monitoring and instrumentation, and automated testing Cloud computing, infrastructure as code, Kubernetes, and serverless Machine learning operations and data engineering from a DevOps perspective Building, deploying, and operationalizing a machine learning project
Machine Learning with Python Cookbook
Kyle Gallatin, Chris Albon, O'Reilly
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2nd Edition
Practical Python Data Wrangling and Data Quality
Susan E. McGregor, O'Reilly
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The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already… The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations. Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data. Use Python 3.8+ to read, write, and transform data from a variety of sources Understand and use programming basics in Python to wrangle data at scale Organize, document, and structure your code using best practices Collect data from structured data files, web pages, and APIs Perform basic statistical analyses to make meaning from datasets Visualize and present data in clear and compelling ways
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Python for DevOps
Noah Gift, Kennedy Behrman, Alfredo Deza, Grig Gheorghiu, O'Reilly
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Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation.… Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout these transformations, Python has become one of the most popular languages in the world. This practical resource shows you how to use Python for everyday Linux systems administration tasks with today‚Äôs most useful DevOps tools, including Docker, Kubernetes, and Terraform. Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you‚Äôll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to "get stuff done" in Python? This is your guide. Python foundations, including a brief introduction to the language How to automate text, write command-line tools, and automate the filesystem Linux utilities, package management, build systems, monitoring and instrumentation, and automated testing Cloud computing, infrastructure as code, Kubernetes, and serverless Machine learning operations and data engineering from a DevOps perspective Building, deploying, and operationalizing a machine learning project
Machine Learning with Python Cookbook
Kyle Gallatin, Chris Albon, O'Reilly
download, pdf, epub
2nd Edition
Practical Python Data Wrangling and Data Quality
Susan E. McGregor, O'Reilly
download, pdf, epub
The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already… The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations. Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data. Use Python 3.8+ to read, write, and transform data from a variety of sources Understand and use programming basics in Python to wrangle data at scale Organize, document, and structure your code using best practices Collect data from structured data files, web pages, and APIs Perform basic statistical analyses to make meaning from datasets Visualize and present data in clear and compelling ways