Profiling-Tools
Profiling tools are essential utilities in software development that help developers analyze the performance of their applications. By measuring various metrics such as execution time, memory usage, and CPU load, these tools identify bottlenecks and inefficiencies in code. Profiling allows developers to optimize their applications, ensuring they run smoothly and efficiently. Different programming languages offer various profiling tools, each with unique features tailored to specific needs. For instance, Python has profilers like cProfile and line_profiler, while Go provides pprof. Utilizing these tools can significantly enhance application performance and resource management.
Unveiling Bottlenecks (Part 2): A Deep Dive into Profiling Tools
In our previous blog post, we introduced the concept of profiling for optimizing Shiny app performance. Today, we’ll take a deep dive into three powerful tools in this arsenal: reactlog, profvis and s...
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Debugging and Profiling
Debugging and Profiling These libraries help you with Python development: the debugger enables you to step through code, analyze stack frames and set breakpoints etc., and the profilers run code and ...
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Continuous Profiling for Python Applications
In computer programming, the meaning of “profiling” is “finding and optimizing those resources that can decrease the response time, cache time, interruptions, and usage of individual instructions in…
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Profiling in Go
A brief guide to explain your app’s connection with your CPU or memory Photo by Kai Dahms on Unsplash What Is Profiling, and Why Is It Useful? Have you ever wanted to dig deeper for explanations as t...
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Chapter 27 - Code Profiling
Code profiling is an attempt to find bottlenecks in your code. Profiling is supposed to find what parts of your code take the longest. Once you know that, then you can look at those pieces of your co...
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The Python Profilers
The Python Profilers Source code: Lib/profile.py and Lib/pstats.py Introduction to the profilers cProfile and profile provide deterministic profiling of Python programs. A profile is a set of statist...
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YData Profiling: The New Standard for Data Profiling
YData Profiling is a new open-source data profiling tool that has quickly become the standard for data scientists and data analysts. It offers a wide range of features and benefits that make it the…
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Top Tools for Profiling Your Python Code and How to Use Them
Do you know how to Profile your Python code? Continue reading on Python in Plain English
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Data Scientists, Start Using Profilers
A profiler can show you exactly which parts are taking the most time, allowing you to see which sections to spend time optimizing to speed up your code.
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-XXcallProfiling
This option enables the use of call profiling for code optimizations. Profiling records useful runtime statistics specific to the application and can—in many cases—increase performance because JVM can...
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Profiling Python Code
Last Updated on June 21, 2022 Profiling is a technique to figure out how time is spent in a program. With these statistics, we can find the “hot spot” of a program and think about ways of improvement....
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Performance Profiling During Development
Performance profiling isn’t just an activity reserved for Ops teams monitoring an application in production. In my view, it’s a skill that should become part of every decent software…
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