pydantic
for ai founders
Why this scored 0
every term, weightedIts fastest-moving item, measured against the pace of its own source
Whether that velocity is itself speeding up, as a per-hour rate
How many independent communities its own items come from
Decays to zero over 14 days, counted from when we first saw it
Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it
Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On an entity's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology
Outlook
medium confidence · estimate, not a guarantee7-day
~0
range 0–12
14-day
~0
range 0–14
30-day
~0
range 0–19
Signal history
7-day window (free)projected trajectory (estimate, not a guarantee)
The evidence
The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.
- 131
Python dataclasses - intercept field assignment
intercept field assignment · for python devs
stackoverflowSteady 3 · pythondevtools82d ago - 221
How to express a conditionally required parameter in a Pydantic-validated tool/API schema, without losing the upfront schema validation?
Shows how to enforce conditional required fields without breaking schema validation. · for python backend developers
stackoverflowSteadydevtools11d ago - 319
The time I screwed up a conference talk (And the talk on Pydantic I would have given)
Missed Pydantic talk underscores need for clear preparation when presenting Python libraries. · for python developers, devrel teams
devtoSteadydevtools21d ago - 40
@pydantic/genai-prices — Calculate prices for calling LLM inference APIs
LLM price calculator · for ai founders
npmSteadyai−23 saturated102d ago