Picks in a "How to choose" list were plain text, so a reader had to hunt for the tool's row in the table.
Co-Authored-By: Claude <noreply@anthropic.com>
Replacing framework-independent dogpile.cache with Django-only django-redis removed the shared Redis and Memcached cache use case, and a single Caching group conflated distinct jobs.
Co-Authored-By: Codex <noreply@openai.com>
Parking a project during a full review left its previous screen-out or rejection active, so incremental scans hid it instead of revisiting it.
Co-Authored-By: Codex <noreply@openai.com>
Seeding an uncertain addition or listed entry as park erased its row kind, so review offered structure actions and exported the wrong verdict.
Co-Authored-By: Codex <noreply@openai.com>
Faiss indexes vectors and integer IDs rather than storing documents and metadata, so its Database placement contradicted the category definition.
Co-Authored-By: Codex <noreply@openai.com>
The guide claimed DiskCache required less effort than every other Python caching library without comparative evidence.
Co-Authored-By: Codex <noreply@openai.com>
The guide claimed Magika never loads a complete file into memory, but the documented guarantee applies to large files.
Co-Authored-By: Codex <noreply@openai.com>
Calling report() and should_prune() alone did not stop an unpromising trial because should_prune() only returns a boolean.
Co-Authored-By: Codex <noreply@openai.com>
The intro recommended jev-ultrafast, which was removed from the list, and missed Scrapling, which took its slot.
Co-Authored-By: Claude <noreply@anthropic.com>
The README split LLM Inference and Serving into Local LLM Inference and LLM Serving, but the intro still grouped MLX LM with vLLM and SGLang and said nothing about Ollama or llama-cpp-python.
Co-Authored-By: Claude <noreply@anthropic.com>
The intro's lead and guide recommended dogpile.cache, which the list no longer carries, and never covered django-redis, which replaced it.
Co-Authored-By: Claude <noreply@anthropic.com>
The scanner recognizes a star only when README links that exact repo, so a starred engine listed through its Python binding (llama.cpp as llama-cpp-python) came back as a new candidate every scan. The Record step now writes a ledger row for such stars. Also drops the last 'drop' verdict wording from preview-verdicts.
Co-Authored-By: Claude <noreply@anthropic.com>
Leaked secrets are a supply chain risk that dependency audits don't cover, so Supply Chain Security splits into Dependency Audits and Secret Scanning.
Co-Authored-By: Claude <noreply@anthropic.com>
Pickling arbitrary Python objects is a different job from data formats, so Serialization splits into Data Formats and Object Pickling.
Co-Authored-By: Claude <noreply@anthropic.com>
File type detection is a different job from paths and file watching, and splitting them leaves room for a challenger in each without passing the cap.
Co-Authored-By: Claude <noreply@anthropic.com>
Removed: jev-ultrafast (no PyPI download signal; not published on PyPI): its README calls it an MVP and it needs a hosted API key, so the challenger slot goes to scrapling in the next commit. This overrides the Challenger Exception recorded 2026-10-02.
Co-Authored-By: Claude <noreply@anthropic.com>
Removed: dogpile.cache (about 1.9M downloads/month on ClickPy, 2026-10-16, down from 2.67M a year earlier): falling demand, and its slot goes to django-redis in the next commit.
Co-Authored-By: Claude <noreply@anthropic.com>
Local runners (ollama, llama-cpp-python, mlx-lm) and production serving engines (vllm, sglang) answer different needs, and one use case could not hold both at the cap. The old page redirects to LLM Serving.
Co-Authored-By: Claude <noreply@anthropic.com>
Each line keeps the ClickPy downloads and the reason at decision time, so later PR reviews and star scans don't propose these projects again without new evidence.
Co-Authored-By: Claude <noreply@anthropic.com>
Vinta ChenandClaude
