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locustio
locust
Python2015–2024
locustio / locust

locust

Write scalable load tests in plain Python 🚗💨

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5Distinct people
5Mentions
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28.3KGitHub stars
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What it is

Write scalable load tests in plain Python 🚗💨

GitHub

Where it is used

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What people are saying

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year5 dated mentions

Observed mentions: 2015-07-01 13:38:24 UTC to 2024-11-13 06:05:37 UTC.

012015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20152016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC101
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC000
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC110
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC110
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC110
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101

What Hacker News says

5 sources
dhx·Nov 13, 2024
This account was spamming Python repositories with the same type of low value obvious backdoor spam.[1] Full list of attempted pull requests (all deleted seemingly by GitHub): 1 https://www.github.com/KurtBestor/Hitomi-Downloader/pull/7638 2 https://www.github.com/home-assistant/core/pull/130423 3 https://www.github.com/celery/celery/pull/9407 4 https://www.github.com/chriskiehl/Gooey/pull/921 5 https://www.github.com/crewAIInc/crewAI/pull/1582 6 https://www.github.com/cumulo-autumn/StreamDiffusion/pull/177 7 https://www.github.com/AUTOMATIC1111/stable-diffusion-webui/pull/16646 8 https://www.github.com/Aider-AI/aider/pull/2343 9 https://www.github.com/aboul3la/Sublist3r/pull/383 10 https://www.github.com/plotly/dash/pull/3073 11 https://www.github.com/soimort/you-get/pull/3034 12 https://www.github.com/streamlink/
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streamlink/pull/6290 13 https://www.github.com/jumpserver/jumpserver/pull/14440 14 https://www.github.com/junyanz/pytorch-CycleGAN-and-pix2pix/pull/1684 15 https://www.github.com/kornia/kornia/pull/3069 16 https://www.github.com/langflow-ai/langflow/pull/4520 17 https://www.github.com/exo-explore/exo/pull/432 18 https://www.github.com/PostHog/posthog/pull/26144 19 https://www.github.com/PrefectHQ/prefect/pull/15987 20 https://www.github.com/pydantic/pydantic/pull/10822 21 https://www.github.com/pyg-team/pytorch_geometric/pull/9777 22 https://www.github.com/qutebrowser/qutebrowser/pull/8379 23 https://www.github.com/tornadoweb/tornado/pull/3441 24 https://www.github.com/ungoogled-software/ungoogled-chromium/pull/3092 25 https://www.github.com/locustio/locust/pull/2980 26 https://www.github.com/matterport/Mask_RCNN/pull/3057 27 https://www.github.com/Stability-AI/generative-models/pull/425 28 https://www.github.com/yt-dlp/yt-dlp/pull/11520 [1] https://play.clickhouse.com/play?user=play#U0VMRUNUICogRlJPT...
In Backdoor attempt on Exolabs GitHub repo through an innocent looking PR
unclefester90·Jan 20, 2019Submission

Show HN: An HTTP server version of the vegeta load-testing tool

https://github.com/nitishm/vegeta-server/ I am looking for contributors to help me out with my latest project. I am creating an HTTP server implementation, driven by a REST API, for the https://github.com/tsenart/vegeta load testing tool. Currently it is only available as a CLI tool. However, there is an excellent library provided by the author, which is used by the CLI tool. The idea is to create a tool, using vegeta, which is similar to https://github.com/loadimpact/k6 or https://github.com/locustio/locust complete with a UI (frontend). This makes it possible to use this tool in a more distributed manner, and possibly introduce it as a kubernetes native load-testing tool. The project currently supports submitting/viewing/canceling `attack`s (all options are not implemented, yet) and viewing the attack `report`s. Issues are tagged with a
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ppropriate labels.
2 points · Open discussion
rdsubhas·Jul 1, 2015
I used Locust for a good long time around a year back, and here are some observations. Locust is awesome to start with, and has master/slave for spawning multiple servers, great for testing real concurrency with large loads. Gatling doesn't have master/slave mode yet. Main problems with Locust are: * Lack of good presentation of results (compare Gatling and Locust results, and Locust is very primitive) * Lack of Pipelines/Scenarios. This IMO was a big deal breaker for me. You can't say: "100% users hit the home screen, out of which 70% add a product, out of which 25% actually pay" etc. This is easily modeled with Gatling, and the same request session with same data falls through each scenario. I'm still following https://github.com/locustio/locust/issues/171 though, but I don't think they have any idea of implementing it.
In Locust – A modern load testing framework

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