Gud Boi
441358e2e7
Interrupted backfill can leave stored observations separated by missing trading time. Query dated IB sessions before prepending stored history and reserve synthetic samples only during covered open sessions. Keep venue closures compressed and preserve the indexes of already published rows. Deats, - Add `Client.history_schedule()` with UTC coverage, extended hours, bounded duration, timeout, and rejection of ambiguous DST times. - Keep schedule normalization in `venues` and allocation in `.tsp._reserve`, with the project AGPL headers. - Expose schedule and synthetic-range queries through `datad.ib`. - Bound reservations by available SHM capacity and inspect only the newest 32 gaps by default via `newest_gaps`. Zero disables queries; leave unknown and oversized ranges unresolved. - Record synthetic ranges separately from OHLCV. Automatic storage writes retain provider observations; placeholders copy close. - Group the new tests under `tests/providers`. - Cover request formatting, DST, failure and capacity cases, plus real SHM/NativeDB startup placement with a fake provider. - Document a common CLI/chart segment-repair interface and defer coordinated insertion, repair execution, and reader integration. Validation: 55 targeted tests passed in the working tree; live IB schedule coverage remains unqualified. After the module moves, 33 affected tests passed again; the local review follow-up passed 18 affected cases, including four new request-budget cases. The commit runner repeats lint and isolated regression checks against this exact boundary. Prompt-IO: ai/prompt-io/codex/20260924T185456Z_1da9b760_schedule_prompt_io.md (this patch was generated in some part by `codex` using `gpt-6` (`openai`)) |
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| 20260915T155229Z_fadab3d2_prompt_io.md | ||
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| 20260923T164656Z_efa72980_prompt_io.md | ||
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| 20260924T165757Z_1da9b760_prompt_io.md | ||
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| 20260924T185456Z_1da9b760_schedule_prompt_io.md | ||
| 20260924T185456Z_1da9b760_schedule_prompt_io.raw.md | ||
| README.md | ||
README.md
AI Prompt I/O Log — codex
This directory tracks prompts and outputs for AI-assisted development using Codex. Substantive contributions include model identification, prompt context, output records, and human contribution accounting.
Code output uses Git diff references; non-code output is retained in the paired .raw.md file. Human contributors remain responsible for review and acceptance. Entries follow the NLNet generative AI policy.