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Tags: Profiler

1.plasma-umass / scalene

Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals

python
profiling
performance-analysis
cpu-profiling
profiler
python-profilers
+8 more

Python APACHE-2.014K total446 forks

+14 stars

from 13,536 · score 2.71

2.alibaba / arthas

TranslatedAlibaba Java Diagnostic Tool Arthas

java
agent
trace
jvm
arthas
trouble-shooting
+3 more

Java APACHE-2.038K total7.6K forks

+12 stars

from 37,595 · score 2.56

3.async-profiler / async-profiler

Sampling CPU and HEAP profiler for Java featuring AsyncGetCallTrace + perf_events

C++APACHE-2.09.2K total994 forks

+11 stars

from 9,175 · score 2.48

4.bloomberg / memray

Memray is a memory profiler for Python

memory
memory-leak
memory-leak-detection
memory-profiler
profiler
python
+2 more

Python APACHE-2.015K total484 forks

+7 stars

from 15,399 · score 2.08

5.deepflowio / deepflow

eBPF Observability - Distributed Tracing and Profiling

opentelemetry
kubernetes
wasm
apm
gpu
llm
+1 more

Go APACHE-2.04.3K total492 forks

+7 stars

from 4,309 · score 2.08

6.didi / DoKit

TranslatedAn efficiency platform for the entire R&D lifecycle of products built with broad front-end technologies.

ios
tools
monitoring
performance
android
mockgps
+1 more

Java APACHE-2.020K total3.2K forks

+2 stars

from 20,413 · score 1.10

7.mgartner / pg_flame

A flamegraph generator for Postgres EXPLAIN ANALYZE output.

flamegraph
postgres
performance
performance-visualization
postgresql
postgresql-tool
+1 more

Go APACHE-2.01.6K total36 forks

+2 stars

from 1,620 · score 1.10

8.epickrram / grav

Performance visualisation tools

performance
monitoring
observability
ebpf
flamegraph

Python APACHE-2.0293 total21 forks

+1 stars

from 292 · score 0.69

Order: Attention Score

Most net stars gained in the window first. The score only puts this gain on a log scale, so the order is the order of the gain.

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Ranked by stars gained in the window. The score is the natural log of one plus that gain, so a repository's rank is exactly its star gain's rank.

score = log1p(net stars gained in the trailing T complete UTC days)

A repository is ranked only when its Star History covers every day of the window and its latest Observation is not missing.

The longest window is 180 days. Star History from the Repository Host goes back at most 180 days before the first daily record that AwesomeRepos made for the repository. A longer window needs more of these daily records first. A repository younger than the window does not rank in it.

The filters select from the same eligible repositories. A repository matches the topics when it has any of them. Total stars is the count now. Last push and creation on the Repository Host count back from the start of today (UTC). The counts beside the languages, licenses, and topics include all ranked repositories in the window. A Tag holds the repositories that have it. See Tags.

A new repository enters the index when it gains stars faster than the published admission threshold, whatever its size. A repository stays in the index after it enters. Thus an archived repository can still rank.

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