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#Crowdin #GitHub #Sphinx #Python #Litestar #Web #ASGI
A bar chart comparing the performance of LiteStar (orange bars) and FastAPI (green bars) in Requests Per Second (RPS) as the number of dependencies ('Num Deps') increases from 0 to 5. The data shows that LiteStar consistently maintains a higher throughput than FastAPI across all dependency counts. For example, at 0 dependencies, LiteStar reaches 45573 RPS versus FastAPI's 37004 RPS. At 5 dependencies, LiteStar holds 32877 RPS while FastAPI drops to 26463 RPS.
Testing #FastAPI vs #LiteStar with nested empty deps (0-5 levels).
Both show smooth perf degradation, unlike LiteStar's flat deps with TaskGroup.
Still, 5 deps = 28% drop for LiteStar — DI overhead is significant even when deps do nothing.
#Python
A bar chart comparing performance in Requests Per Second (RPS) between 'TaskGroup' (purple bars) and 'Await' (orange bars) based on the number of dependencies ('Num Deps'). For 1 dependency, TaskGroup achieves 4604 RPS and Await achieves 4628 RPS. For 2 dependencies, TaskGroup is at 4085 RPS while Await is at 4558 RPS. For 4 dependencies, TaskGroup drops to 3817 RPS, whereas Await maintains 4529 RPS, showing that Await scales better as dependency count increases.
Quick perf test: changed #LiteStar dependency resolution from TaskGroup to await.
RPS impact? Minimal vs 17% degradation with TaskGroup at 4 deps. Each request does 4 DB calls.
TaskGroup overhead matters more than expected.
More details in thread 👇
#Python #Backend
In the previous thread, Litestar's RPS dropped 36% with 2+ flat dependencies due to TaskGroup overhead. 📉
How do #Litestar and #FastAPI perform with real DB queries in dependencies? Let's figure it out in this thread 🧵
#Python
Summarized my findings and opened an issue. Hoping to help make #LiteStar just a little bit better.
github.com/litestar-org...
#Python #Backend #WebDev
A bar chart titled "LiteStar" showing Request Per Second (RPS) performance across different numbers of dependencies (0 to 5). The RPS drops from 41,451 with 1 dependency to 26,492 with 2 dependencies. A red arrow points to this 36% decrease with a handwritten caption asking "Why?".
Is #LiteStar faster than #FastAPI? Benchmarks say yes, but look at Dependency Injection. 📉
Adding just 2 flat dependencies significantly degrades the throughput. I dug into the source to find why.
Thread: TaskGroups, Kahn's algorithm & performance trade-offs. 🧵
#Python #Backend #WebDev
Глубокий обзор фреймворка Litestar от разработчика Django. Аж захотелось тоже попробовать!
https://www.b-list.org/weblog/2025/aug/06/litestar/
#try #python #webdev #litestar #programming
Litestar emerges as a strong FastAPI alternative. Users praise its robust design, speed, and built-in features like an event system. It's better suited for complex JSON/HTML serving, offering a more structured path for serious apps. #Litestar 3/6
New blog post: I've mentioned before that #litestar is by far my favorite of the new generation of #python web frameworks, and I've finally found time to write about why.
www.b-list.org/weblog/2025/...
LitestarCatsCV. Тренируемся на кошках. Расширяем возможност...
habr.com/ru/companies/ntechlab/ar...
#api #python #tutorial #backend #uv #fastapi #litestar #granian #jinja #keydb
Event Attributes
