Python at Scale: Architecting for Speed: Beyond Simple Fixes: A Guide to Building Truly Performant, Data-Intensive Systems - Softcover
Synopsis
Let's be honest: your Python application is slow.
You’ve already done the "simple fixes." You've added a database index, optimized a loop, and maybe even pip install-ed a new library that promised magic. And yet, your P99 latency is climbing, your pandas script just OOM-killed another server, and your users are starting to notice.
Here’s the hard truth: your problem isn't your code; it's your architecture.
Python at Scale: Architecting for Speed is not another book of clever "hacks." It's a hands-on guide to thinking like a systems architect, for Python developers who have hit the performance wall. We're going "beyond simple fixes" to build truly performant, data-intensive systems that are fast by design.
In this book, we'll stop tweaking and start re-architecting. You will learn to:
- Identify the Real Villain: Stop guessing. Learn to use the right profiler (cProfile, Py-Spy, Scalene) to find your actual bottleneck—whether it's I/O wait, CPU (the GIL), or memory.
- Conquer Concurrency: Go beyond a simple await. Master the asyncio event loop, understand its "blocking" traps, and learn to build systems that can actually handle thousands of concurrent requests.
- Shatter the GIL: Stop fighting the Global Interpreter Lock. Learn to identify CPU-bound problems and use multiprocessing to shatter the "one-core" barrier and use your hardware's full power.
- Build an Impenetrable Data Layer: Your database is the bottleneck. Learn to protect it with advanced caching (Redis), denormalization, and the bulletproof "Outbox Pattern" to decouple your writes.
- Decouple Everything: Your app shouldn't do things "right now." Learn to use message queues like RabbitMQ and Kafka to build resilient, asynchronous, and blazing-fast services.
- Kill Your pandas Script (Before It Kills Your Server): That in-memory script is a time bomb. We'll show you how to move to out-of-core, parallel tools like Dask and Polars to process 500GB of data as easily as 5MB.
- Achieve True Observability: Learn to deploy and monitor with confidence. We'll cover everything from Docker and Kubernetes to the metrics that actually matter (hint: it's not "average latency").
"synopsis" may belong to another edition of this title.
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Python at Scale (Paperback)
Print on DemandSeller: Grand Eagle Retail, Bensenville, IL, U.S.A.
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Paperback. Condition: new. Paperback. Let's be honest: your Python application is slow.You've already done the "simple fixes." You've added a database index, optimized a loop, and maybe even pip install-ed a new library that promised magic. And yet, your P99 latency is climbing, your pandas script just OOM-killed another server, and your users are starting to notice.Here's the hard truth: your problem isn't your code; it's your architecture.Python at Scale: Architecting for Speed is not another book of clever "hacks." It's a hands-on guide to thinking like a systems architect, for Python developers who have hit the performance wall. We're going "beyond simple fixes" to build truly performant, data-intensive systems that are fast by design.In this book, we'll stop tweaking and start re-architecting. You will learn to: Identify the Real Villain: Stop guessing. Learn to use the right profiler (cProfile, Py-Spy, Scalene) to find your actual bottleneck-whether it's I/O wait, CPU (the GIL), or memory.Conquer Concurrency: Go beyond a simple await. Master the asyncio event loop, understand its "blocking" traps, and learn to build systems that can actually handle thousands of concurrent requests.Shatter the GIL: Stop fighting the Global Interpreter Lock. Learn to identify CPU-bound problems and use multiprocessing to shatter the "one-core" barrier and use your hardware's full power.Build an Impenetrable Data Layer: Your database is the bottleneck. Learn to protect it with advanced caching (Redis), denormalization, and the bulletproof "Outbox Pattern" to decouple your writes.Decouple Everything: Your app shouldn't do things "right now." Learn to use message queues like RabbitMQ and Kafka to build resilient, asynchronous, and blazing-fast services.Kill Your pandas Script (Before It Kills Your Server): That in-memory script is a time bomb. We'll show you how to move to out-of-core, parallel tools like Dask and Polars to process 500GB of data as easily as 5MB.Achieve True Observability: Learn to deploy and monitor with confidence. We'll cover everything from Docker and Kubernetes to the metrics that actually matter (hint: it's not "average latency").This book is your guide to moving from a developer who fights fires to an architect who prevents them. Stop "fixing" your code and start building systems that scale. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798273157453
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Python at Scale: Architecting for Speed: Beyond Simple Fixes: A Guide to Building Truly Performant, Data-Intensive Systems
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Python at Scale
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Python at Scale
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Python at Scale (Paperback)
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Paperback. Condition: new. Paperback. Let's be honest: your Python application is slow.You've already done the "simple fixes." You've added a database index, optimized a loop, and maybe even pip install-ed a new library that promised magic. And yet, your P99 latency is climbing, your pandas script just OOM-killed another server, and your users are starting to notice.Here's the hard truth: your problem isn't your code; it's your architecture.Python at Scale: Architecting for Speed is not another book of clever "hacks." It's a hands-on guide to thinking like a systems architect, for Python developers who have hit the performance wall. We're going "beyond simple fixes" to build truly performant, data-intensive systems that are fast by design.In this book, we'll stop tweaking and start re-architecting. You will learn to: Identify the Real Villain: Stop guessing. Learn to use the right profiler (cProfile, Py-Spy, Scalene) to find your actual bottleneck-whether it's I/O wait, CPU (the GIL), or memory.Conquer Concurrency: Go beyond a simple await. Master the asyncio event loop, understand its "blocking" traps, and learn to build systems that can actually handle thousands of concurrent requests.Shatter the GIL: Stop fighting the Global Interpreter Lock. Learn to identify CPU-bound problems and use multiprocessing to shatter the "one-core" barrier and use your hardware's full power.Build an Impenetrable Data Layer: Your database is the bottleneck. Learn to protect it with advanced caching (Redis), denormalization, and the bulletproof "Outbox Pattern" to decouple your writes.Decouple Everything: Your app shouldn't do things "right now." Learn to use message queues like RabbitMQ and Kafka to build resilient, asynchronous, and blazing-fast services.Kill Your pandas Script (Before It Kills Your Server): That in-memory script is a time bomb. We'll show you how to move to out-of-core, parallel tools like Dask and Polars to process 500GB of data as easily as 5MB.Achieve True Observability: Learn to deploy and monitor with confidence. We'll cover everything from Docker and Kubernetes to the metrics that actually matter (hint: it's not "average latency").This book is your guide to moving from a developer who fights fires to an architect who prevents them. Stop "fixing" your code and start building systems that scale. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798273157453
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