Dev tools · alternatives · 2026

24 alternatives to StackImpact – Python Production Profiler: CPU, Memory, Exceptions

DEPRECATED StackImpact Python Profiler - Production-Grade Performance Profiler: CPU, memory allocations, blocking calls, exceptions, metrics, and more - stackimpact/stackimpact-python

StackImpact is a Python profiler designed for production environments that tracks CPU usage, memory consumption, and exceptions. It helps developers identify performance bottlenecks and errors in live applications. The… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. StackImpact – Python Production Profiler: CPU, Memory, Exceptions launched in 2017; newer entries below may have overtaken it.

1
StackImpact – Go Production Profiler: CPU, Memory, Blocking Calls▲7
DEPRECATED StackImpact Go Profiler - Production-Grade Performance Profiler: CPU, memory allocations, blocking calls, errors, metrics, and more - stackimpact/stackimpact-go
2017 · github.com · its alternatives →
2
Py-spy – A new sampling profiler for Python programs▲286
Sampling profiler for Python programs. Contribute to benfred/py-spy development by creating an account on GitHub.
2018 · github.com · its alternatives →
3
Pyper – Concurrent Python Made Simple▲156
Hello and happy new year! We're excited to introduce the Pyper package for concurrency & parallelism in Python. Pyper is a flexible framework for concurrent / parallel data processing, following the functional paradigm. Source code can be found on [github](https://github.com/pyper-dev/pyper) Key features: Intuitive API: Easy to learn, easy to think about. Implements clean abstractions to seamlessly unify threaded, multiprocessed, and asynchronous work. Functional Paradigm: Python functions are the building blocks of data pipelines. Let's you write clean, reusable…
2025 · github.com · its alternatives →
4
Debugging-Friendly Tracebacks for Python▲123
Debugging-friendly exceptions for Python. Contribute to cknd/stackprinter development by creating an account on GitHub.
2019 · github.com · its alternatives →
5
GitHired▲360
Hey HN - today I’m launching GitHired. A hiring platform that ranks developers based on what they actually build — not what they claim on a PDF. It’s called GitHired, and here’s the core idea: GitHub > Resumes Instead of trusting “proficient in React” bullet points, we analyze a candidate’s actual GitHub: their real tech stack their most complex projects how active they are what kinds of contributions they make which skills match your job description and yes, we detect fake “green square farming.” Why we built this Because engineering hiring is broken. Resumes are inflated. Activity charts…
Dec 2025 · githired.tech · its alternatives →
6
Refurb – A tool for refurbishing and modernizing Python codebases▲123
A tool for refurbishing and modernizing Python codebases - dosisod/refurb
2022 · github.com · its alternatives →
7
Weave▲237
Hey HN, We’re building Weave: an ML-powered tool to measure engineering output, that actually understands engineering output! Why? Here’s the thing: almost every eng leader already measures output - either openly or behind closed doors. But they rely on metrics like lines of code (correlation with effort: ~0.3), number of PRs, or story points (slightly better at ~0.35). These metrics are, frankly, terrible proxies for productivity. We’ve developed a custom model that analyzes code and its impact directly, with a far better 0.94 correlation. The result? A standardized engineering output…
2025 · app.workweave.ai · its alternatives →
8
Debugger that generates video visualizations for algorithm learning▲102
A simple Python debugger and profiler that generates animated visualizations of program flow, useful for algorithm learning. - CCExtractor/vardbg
2020 · github.com · its alternatives →
9
Timep – A next-gen profiler and flamegraph-generator for bash code▲53
Note: this is an update to [this](https://news.ycombinator.com/item?id=44568529) "Show HN" post. timep is a state-of-the-art [debug-]trap-based bash profiler that is efficient and extremely accurate. Unlike other profilers, timep records: 1. per-command wall-clock time 2. per-command CPU time, and 3. the hierarchy of parent function calls /subshells for each command the wall-clock + CPU time combination allows you to determine if a particular command is CPU-bound or IO-bound, and the hierarchical logging gives you a map of how the code actually executed. The standout…
2025 · github.com · its alternatives →
10RA
Rbkit – a low-pause profiler for ruby▲67
2015 · rbkit.codemancers.com · its alternatives →
11
Whole-fleet continuous profiler for C/C++/Rust/Go/JVM/Python/Ruby/PHP▲33
2021 · prodfiler.com · its alternatives →
12SA
Sping – An HTTP/TCP latency tool that's easy on the eye▲178
I've frequently found myself using [nvitop](https://github.com/XuehaiPan/nvitop) to diagnose GPU/CPU contention issues. The two best things about it are: - It's easy to install if I can access pip in the container - It makes a compelling screenshot (which helps me communicate with coworkers.) With those two lessons in mind: Here is Sping! Purpose: Help observe and diagnose latency issues at layer 4+ (TCP/HTTP/HTTPS) Two good things about it: - It's easy to install if you have pip. (Available at…
2025 · dseltzer.gitlab.io · its alternatives →
13
Single-Header Profiler for C++17▲68
Morning HN. I often found myself wondering "how much does this code segment take in terms of total runtime" and it's often quite annoying to figure out with optimizations enabled, especially when working on something new or testing someone else's implementation without the proper tooling set up. Wanted to have a single include lib that would allow us to write something like: ``` PROFILE("Loop 1") for (...) // some work ``` and have the next expression automatically record time & dump results to a table. Wrote a few macros to do exactly that a few months back, but they were…
2025 · github.com · its alternatives →
14
G-Profiler by Granulate▲69
Production code profiling made easy
2021 · its alternatives →
15
I wrote a tool in Rust for tracking all allocations in a Linux process▲113
allocscope - a memory tracking tool. Contribute to matt-kimball/allocscope development by creating an account on GitHub.
2023 · github.com · its alternatives →
16GC
Gitalytics.com - Quicker Way to check someone's github profile▲83
Since everyone seems to be making a github application, I thought I'd share mine. It's an aggregated view of all of a given person's github projects, as well as easyish lookups for linkedin/stackoverflow/hackernews. It attempts to determine both productivity (how much code did this person write?) as well as impact (did anyone care?) I'd love any feedback, but go easy on the number of simultaneous searches as I'm trying to play nice by github's api limits. check it -- http://www.gitalytics.com
2011 · gitalytics.com · its alternatives →
17
I developed the most user-friendly Python profiling tool available▲6
Hello, I have several years of experience as a Python developer, and during that time, I've worked on intricate applications dealing with large volumes of data. One frequent challenge I faced was benchmarking the application and identifying performance bottlenecks. While there are some excellent Python profiling tools available, they can be quite daunting for beginners. The utility I have developed simplifies this process, making it as straightforward as possible to transition from slow code to a detailed flame chart. I would greatly appreciate your feedback!
2023 · github.com · its alternatives →
18
Bench – A generic latency benchmarking library▲37
A generic latency benchmarking library. Contribute to tylertreat/bench development by creating an account on GitHub.
2015 · github.com · its alternatives →
19
Goroutine-analyzer: A visual goroutine stack dump debugging tool▲73
Helps analyze goroutines. Inspired by TDA for Java and goroutine-inspect for golang. - openziti/goroutine-analyzer
2022 · github.com · its alternatives →
20
Spall – WASM-based profiler for JavaScript and C and Odin▲83
[I'm the author] Spall is a web-accessible profiler that I made to help my web-dev friends load gigabyte+ JSON traces without lunch-break-long load times. Recently, Spall got experimental support for auto-tracing with binary traces (along with an in-progress native-port, to give it more memory headroom), which was used to help track down and fix some hard-to-spot lock contention issues in the Odin-language compiler. I demoed it at the Handmade Seattle conference in October, https://guide.handmade-seattle.com/c/2022/spall/, with a head-to-head against Perfetto,…
2023 · gravitymoth.com · its alternatives →
21
Prometeo – a Python-to-C transpiler for high-performance computing▲166
An experimental Python-to-C transpiler and domain specific language for embedded high-performance computing - zanellia/prometeo
2021 · github.com · its alternatives →
22
Benchi – A benchmarking tool written in Go▲58
Benchi is a CLI tool for running benchmarks and collecting metrics. It's using Docker Compose to orchestrate the infrastructure and tools being benchmarked, making it repeatable and runnable on different machines. It allows you to run the same benchmark for different tools and compare the collected results. The repository contains a simple example. For a more elaborate example see how we use Benchi to compare data pipelines running on Conduit and Kafka Connect, two data streaming tools (still work in progress): https://github.com/ConduitIO/streaming-benchmarks
2025 · github.com · its alternatives →
23
A simple lazy Python calculation engine, with spreadsheet demo▲123
Simple Python Calculation Engine. Contribute to bsdz/calcengine development by creating an account on GitHub.
2021 · github.com · its alternatives →
24
Utilyze – an open source GPU monitoring tool more accurate than nvtop▲128
The standard GPU utilization metric reported by nvidia-smi, nvtop, Weights & Biases, Amazon CloudWatch, Google Cloud Monitoring, and Azure Monitor is highly misleading. It reports the fraction of time that any kernel is running on the GPU, which means a GPU can report 100% utilization even if only a small portion of its compute capacity is actually being used. In practice, we've seen workloads with ~1–10% real compute throughput while dashboards show 100%. This becomes a problem when teams rely on that metric for capacity planning or optimization decisions, it can make underutilized systems…
Apr 2026 · systalyze.com · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →