ℹ️ About Codex in GitHub

\\n
\\n\\n[Your team has set up Codex to review pull requests in this repo](https://chatgpt.com/codex/cloud/settings/general). Reviews are triggered when you\\n- Open a pull request for review\\n- Mark a draft as ready\\n- Comment \\\"@codex review\\\".\\n\\nIf Codex has suggestions, it will comment; otherwise it will react with 👍.\\n\\n\\n\\n\\nCodex can also answer questions or update the PR. Try commenting \\\"@codex address that feedback\\\".\\n \\n

\",\"path\":null,\"side\":null,\"line\":null}","text_elements",[],{"_350":392,"_331":332,"_352":338},{"_353":393,"_355":-5,"_41":-5,"_356":-5,"_94":300,"_90":358},[394],{"_45":388,"_90":395},"input_text",{"_350":397,"_331":332,"_352":338},{"_353":398,"_355":-5,"_41":-5,"_356":-5,"_94":300,"_90":358},[399],{"_45":400,"_90":395},"\n /workspace/buckaroo\n bash\n 2026-05-24\n Etc/UTC\n",{"_350":402,"_331":332,"_352":338},{"_353":403,"_355":-5,"_41":-5,"_356":-5,"_94":404,"_90":358},[405,406],"developer",{"_45":408,"_90":395},{"_45":407,"_90":395},"\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- imagegen: Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas. (file: /opt/codex/skills/.system/imagegen/SKILL.md)\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or model upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /opt/codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /opt/codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /opt/codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /opt/codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.\n","\nFilesystem sandboxing defines which files can be read or written. `sandbox_mode` is `danger-full-access`: No filesystem sandboxing - all commands are permitted. Network access is enabled.\nApproval policy is currently never. Do not provide the `sandbox_permissions` for any reason, commands will be rejected.\n","turn/started",{"_331":332,"_85":411},{"_101":-5,"_41":338,"_339":412,"_341":342,"_343":413},[],"inProgress",{"_343":415,"_331":332},{"_416":417,"_90":418},"activeFlags",[],"active","thread/started",{"_421":422},"thread",{"_423":-5,"_424":-5,"_425":426,"_427":342,"_428":429,"_430":15,"_431":-5,"_432":-5,"_41":332,"_433":434,"_179":-5,"_159":435,"_436":197,"_437":438,"_343":439,"_75":440,"_441":342},"agentNickname","agentRole","cliVersion","0.124.0","createdAt","cwd","/workspace/buckaroo","ephemeral","forkedFromId","gitInfo","modelProvider","openai","/opt/codex/sessions/2026/05/24/rollout-2026-05-24T21-54-24-019e5bfb-6aad-79b1-aba9-2c4969e45661.jsonl","preview","source","vscode",{"_90":347},[],"updatedAt",[],"messages",[445],{"_41":446,"_447":448,"_449":450,"_451":450,"_353":452,"_343":453,"_355":-5,"_454":31,"_455":456,"_457":458,"_459":-5},"05cd37e1-4308-4329-8450-c80d4cd9ed8a","author",{"_94":300,"_179":-5,"_455":468},"create_time",1779659663.287977,"update_time",{"_464":45,"_465":466},"finished_successfully","weight","metadata",{"_460":461},"recipient","all","channel","l1239dk1",{"_462":463},"inline_comments",[],"content_type","parts",[467],"@codex thanks — both P1 and P2 were addressed in [34deb3c0](https://github.com/buckaroo-data/buckaroo/commit/34deb3c0):\n\n- **P1 (no string columns)** — `handle_infinite_request_buckaroo_polars` now uses `processed_df.clear()` to return an empty frame when `search_string` is non-empty and the frame has no `String` columns. Matches pandas `search_df_str` semantics (OR-accumulate from an all-False mask). Pinned by `test_search_with_no_string_columns_returns_empty`.\n- **P2 (.json vs ndjson)** — `.json` now dispatches to `pl.read_json` (standard JSON arrays, matching `pd.read_json` default `lines=False`); newline-delimited JSON moved to the explicit `.ndjson` extension. Pinned by `test_load_file_polars_json_array` + `test_load_file_polars_ndjson_still_works`.\n\nLint failure in the prior CI run was unrelated — `paddy_format` rejected the multi-line import block in the new test file. Fixed in [8eded229](https://github.com/buckaroo-data/buckaroo/commit/8eded229).\nfeat(server): /load accepts backend='polars' for buckaroo dataflow\n\n## Summary\n- `/load` was hardcoded to pandas (`load_file` → `create_dataflow`); the polars buckaroo dataflow was only reachable via the notebook widget. Demos that embed via the standalone server (iframe / `BuckarooServerView`) couldn't exercise it.\n- Adds `backend: 'polars'` to the POST body (default `'pandas'`, polars validated as `mode='buckaroo'`-only). New module `data_loading_polars.py` with `PolarsServerDataflow` (config lifted from `PolarsBuckarooInfiniteWidget`), eager polars file loader, and `handle_infinite_request_buckaroo_polars` (literal-substring `str.contains` across String columns to match pandas `search_df_str` semantics).\n- WS dispatch routes `session.backend == 'polars'` to the new handler; pandas / xorq branches untouched. Polars stays optional — `data_loading_polars` is lazy-imported.\n\nUsage:\n```python\nPOST /load { \"session\": \"demo\", \"path\": \"data.parquet\", \"mode\": \"buckaroo\", \"backend\": \"polars\" }\n```\n\n## Test plan\n- [ ] `pytest tests/unit/server/` — existing pandas-backend `/load` tests still pass (92 passed locally).\n- [ ] Manual: POST /load with backend=polars, then open the session — grid renders, sorting and search work end-to-end.\n\n🤖 Generated with [Claude Code](https://claude.com/claude-code)\n## :package: TestPyPI package published\n\n```bash\npip install --index-strategy unsafe-best-match --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ buckaroo==0.14.7.dev26373401136\n```\n\nor with uv:\n\n```bash\nuv pip install --index-strategy unsafe-best-match --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ buckaroo==0.14.7.dev26373401136\n```\n\n### MCP server for Claude Code\n\n```bash\nclaude mcp add buckaroo-table -- uvx --from \"buckaroo[mcp]==0.14.7.dev26373401136\" --index-strategy unsafe-best-match --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ buckaroo-table\n```\n\n### :book: [Docs preview](https://buckaroo-data--855.org.readthedocs.build/en/855/)\n\n### :art: [Storybook preview](https://buckaroo-data--855.org.readthedocs.build/en/855/storybook/)\n**_{_{![P1 Badge](https://img.shields.io/badge/P1-orange?style=flat)}} Return no rows when search term has no string columns**\n\nWhen `backend='polars'` and `search_string` is non-empty, this branch leaves `filtered_df` unchanged if the frame has no `String` columns, so the UI shows all rows as if no search was applied. That diverges from the existing pandas behavior (`search_df_str`), which returns an empty result for non-empty searches with no searchable text/object columns. This will make search appear broken on numeric-only datasets in buckaroo mode.\n\nUseful? React with 👍 / 👎.\n**_{_{![P2 Badge](https://img.shields.io/badge/P2-yellow?style=flat)}} Read standard .json files with the JSON loader**\n\nThe `.json` branch now calls `pl.read_ndjson`, which expects newline-delimited JSON; regular JSON arrays/objects that currently load through the pandas path (`pd.read_json` default `lines=False`) will fail under `backend='polars'`. Because `/load` advertises the same extension support and this is keyed only by file suffix, users can hit avoidable 400/500 load failures simply by switching backend.\n\nUseful? React with 👍 / 👎.\n\n### 💡 Codex Review\n\nHere are some automated review suggestions for this pull request.\n\n**Reviewed commit:** `5e0704546f`\n \n\n

ℹ️ About Codex in GitHub

\n
\n\n[Your team has set up Codex to review pull requests in this repo](https://chatgpt.com/codex/cloud/settings/general). Reviews are triggered when you\n- Open a pull request for review\n- Mark a draft as ready\n- Comment \"@codex review\".\n\nIf Codex has suggestions, it will comment; otherwise it will react with 👍.\n\n\n\n\nCodex can also answer questions or update the PR. Try commenting \"@codex address that feedback\".\n \n

",{},"created",1779659680.7008905,"Completing the task","event_type","info",{"_90":358,"_94":91,"_353":479},{"_90":476,"_477":478},"partial_repo_snapshot","files",[],[480],{"_464":45,"_45":360},{"_90":300,"_41":82,"_94":300,"_483":484,"_485":486,"_487":488,"_130":-5,"_117":489},[81],"input_items",[507,508,509,510,511,512],"external_post_config",{"_490":491,"_240":241,"_492":281,"_252":-5,"_493":235,"_494":-5,"_495":496,"_497":498,"_499":-5,"_500":-5,"_501":502,"_503":15,"_504":57,"_505":52,"_506":15},"user_model_slug","slug",1779659655.374603,"installation_id",112153683,"pr_number","repo_id","review_trigger","comment_id",4530065617,"comment_type","issue","pr_write_guard_token","pending_pr_reaction_id","pending_comment_reaction_id",361200384,"comment_if_no_findings","comment_on_error","share_url","is_parallel_review",{"_90":358,"_94":300,"_353":526},{"_288":289,"_290":291,"_523":295,"_524":127,"_297":-5,"_90":525},{"_90":513,"_290":522,"_159":-5,"_515":-5,"_516":-5},{"_90":513,"_290":521,"_159":518,"_515":519,"_516":-5},{"_90":513,"_290":517,"_159":518,"_515":519,"_516":520},{"_90":513,"_290":514,"_159":-5,"_515":-5,"_516":-5},"pull_request_comment","\n### 💡 Codex Review\n\nHere are some automated review suggestions for this pull request.\n\n**Reviewed commit:** `5e0704546f`\n \n\n

ℹ️ About Codex in GitHub

","side","line","**_{_{![P2 Badge](https://img.shields.io/badge/P2-yellow?style=flat)}} Read standard .json files with the JSON loader**\n\nThe `.json` branch now calls `pl.read_ndjson`, which expects newline-delimited JSON; regular JSON arrays/objects that currently load through the pandas path (`pd.read_json` default `lines=False`) will fail under `backend='polars'`. Because `/load` advertises the same extension support and this is keyed only by file suffix, users can hit avoidable 400/500 load failures simply by switching backend.\n\nUseful? React with 👍 / 👎.","buckaroo/server/data_loading_polars.py","RIGHT",79,"**_{_{![P1 Badge](https://img.shields.io/badge/P1-orange?style=flat)}} Return no rows when search term has no string columns**\n\nWhen `backend='polars'` and `search_string` is non-empty, this branch leaves `filtered_df` unchanged if the frame has no `String` columns, so the UI shows all rows as if no search was applied. That diverges from the existing pandas behavior (`search_df_str`), which returns an empty result for non-empty searches with no searchable text/object columns. This will make search appear broken on numeric-only datasets in buckaroo mode.\n\nUseful? React with 👍 / 👎.","## :package: TestPyPI package published\n\n```bash\npip install --index-strategy unsafe-best-match --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ buckaroo==0.14.7.dev26373401136\n```\n\nor with uv:\n\n```bash\nuv pip install --index-strategy unsafe-best-match --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ buckaroo==0.14.7.dev26373401136\n```\n\n### MCP server for Claude Code\n\n```bash\nclaude mcp add buckaroo-table -- uvx --from \"buckaroo[mcp]==0.14.7.dev26373401136\" --index-strategy unsafe-best-match --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ buckaroo-table\n```\n\n### :book: [Docs preview](https://buckaroo-data--855.org.readthedocs.build/en/855/)\n\n### :art: [Storybook preview](https://buckaroo-data--855.org.readthedocs.build/en/855/storybook/)","base_ref","head_ref","pull_request_info",[527],{"_464":45,"_45":528},"@codex thanks — both P1 and P2 were addressed in [34deb3c0](https://github.com/buckaroo-data/buckaroo/commit/34deb3c0):\n\n- **P1 (no string columns)** — `handle_infinite_request_buckaroo_polars` now uses `processed_df.clear()` to return an empty frame when `search_string` is non-empty and the frame has no `String` columns. Matches pandas `search_df_str` semantics (OR-accumulate from an all-False mask). Pinned by `test_search_with_no_string_columns_returns_empty`.\n- **P2 (.json vs ndjson)** — `.json` now dispatches to `pl.read_json` (standard JSON arrays, matching `pd.read_json` default `lines=False`); newline-delimited JSON moved to the explicit `.ndjson` extension. Pinned by `test_load_file_polars_json_array` + `test_load_file_polars_ndjson_still_works`.\n\nLint failure in the prior CI run was unrelated — `paddy_format` rejected the multi-line import block in the new test file. Fixed in [8eded229](https://github.com/buckaroo-data/buckaroo/commit/8eded229).",[635,636],[],{"_469":470,"_45":471,"_472":473},{"_443":626},{"_313":625},{"_313":564},{"_280":281,"_272":282,"_283":284,"_285":15,"_286":15,"_287":15,"_288":289,"_290":291,"_292":245,"_293":125,"_294":295,"_296":127,"_297":-5,"_298":-5,"_299":-5,"_300":563,"_302":303,"_304":303,"_305":306,"_307":308},{"_41":121,"_191":192,"_193":194,"_195":15,"_196":197,"_198":199,"_200":552,"_202":-5,"_203":-5,"_204":553,"_206":197,"_207":197,"_208":554,"_210":555,"_212":556,"_214":-5,"_215":216,"_217":218,"_219":220,"_221":557,"_53":-5,"_117":223,"_224":558,"_226":559,"_228":229,"_230":15,"_231":15},{"_131":545},[539,540,541,542,543,544],{"_146":169,"_148":163,"_150":164,"_152":161,"_154":170,"_156":157,"_158":31,"_159":-5},{"_146":168,"_148":163,"_150":164,"_152":161,"_154":165,"_156":157,"_158":31,"_159":-5},{"_146":166,"_148":163,"_150":164,"_152":161,"_154":167,"_156":157,"_158":31,"_159":-5},{"_146":162,"_148":163,"_150":164,"_152":161,"_154":165,"_156":157,"_158":31,"_159":-5},{"_146":160,"_148":149,"_150":151,"_152":161,"_154":155,"_156":157,"_158":31,"_159":-5},{"_146":147,"_148":149,"_150":151,"_152":153,"_154":155,"_156":157,"_158":31,"_159":-5},[546,547,548],{"_175":551,"_177":188},{"_175":550,"_177":184},{"_175":549,"_177":178},{"_179":180,"_90":181,"_117":182},{"_179":185,"_90":181,"_117":186},{"_179":189,"_90":181,"_117":190},{"_274":275,"_276":-5,"_277":-5,"_278":-5,"_279":-5},[235],{"_235":560},{},{},[],{"_234":57},{"_232":57,"_233":197},{"_41":237,"_179":194,"_238":561,"_240":241,"_242":243,"_244":245,"_246":247,"_248":249,"_250":251,"_252":62,"_253":15,"_254":-5,"_255":-5,"_256":-5,"_257":-5,"_258":-5,"_259":-5,"_158":260,"_261":-5,"_53":562},{"_266":267,"_41":268,"_90":269,"_270":271,"_272":273},{"_263":15,"_264":15,"_265":15},{"_266":309,"_179":309,"_310":-5,"_270":311,"_41":312},[565,566,567,568,569,570,571,572,573,574,575,576,577],{"_152":419,"_329":621},{"_152":344,"_329":618},{"_152":409,"_329":615},{"_152":348,"_329":610},{"_152":348,"_329":606},{"_152":348,"_329":602},{"_152":362,"_329":597},{"_152":362,"_329":593},{"_152":348,"_329":589},{"_152":362,"_329":587},{"_152":348,"_329":583},{"_152":344,"_329":581},{"_152":328,"_329":578},{"_331":332,"_85":579},{"_334":335,"_336":337,"_101":-5,"_41":338,"_339":580,"_341":342,"_343":111},[],{"_343":582,"_331":332},{"_90":347},{"_350":584,"_331":332,"_352":338},{"_353":585,"_355":-5,"_41":-5,"_356":357,"_94":91,"_90":358},[586],{"_45":360,"_90":361},{"_350":588,"_331":332,"_352":338},{"_41":365,"_356":357,"_45":360,"_90":366},{"_350":590,"_331":332,"_352":338},{"_353":-5,"_369":370,"_41":-5,"_371":591,"_90":373},[592],{"_45":375,"_90":376},{"_350":594,"_331":332,"_352":338},{"_353":595,"_41":380,"_371":596,"_90":373},[],[375],{"_350":598,"_331":332,"_352":338},{"_353":599,"_41":385,"_90":386},[600],{"_45":388,"_389":601,"_90":45},[],{"_350":603,"_331":332,"_352":338},{"_353":604,"_355":-5,"_41":-5,"_356":-5,"_94":300,"_90":358},[605],{"_45":388,"_90":395},{"_350":607,"_331":332,"_352":338},{"_353":608,"_355":-5,"_41":-5,"_356":-5,"_94":300,"_90":358},[609],{"_45":400,"_90":395},{"_350":611,"_331":332,"_352":338},{"_353":612,"_355":-5,"_41":-5,"_356":-5,"_94":404,"_90":358},[613,614],{"_45":408,"_90":395},{"_45":407,"_90":395},{"_331":332,"_85":616},{"_101":-5,"_41":338,"_339":617,"_341":342,"_343":413},[],{"_343":619,"_331":332},{"_416":620,"_90":418},[],{"_421":622},{"_423":-5,"_424":-5,"_425":426,"_427":342,"_428":429,"_430":15,"_431":-5,"_432":-5,"_41":332,"_433":434,"_179":-5,"_159":435,"_436":197,"_437":438,"_343":623,"_75":624,"_441":342},{"_90":347},[],[],[627],{"_41":446,"_447":628,"_449":450,"_451":450,"_353":629,"_343":453,"_355":-5,"_454":31,"_455":630,"_457":458,"_459":-5},{"_94":300,"_179":-5,"_455":634},{"_464":45,"_465":633},{"_460":631},{"_462":632},[],[467],{},{"_90":358,"_94":91,"_353":638},{"_90":476,"_477":637},[],[639],{"_464":45,"_45":360},[642,643,644,645,646,647],{"_490":491,"_240":241,"_492":281,"_252":-5,"_493":235,"_494":-5,"_495":496,"_497":498,"_499":-5,"_500":-5,"_501":502,"_503":15,"_504":57,"_505":52,"_506":15},{"_90":358,"_94":300,"_353":648},{"_288":289,"_290":291,"_523":295,"_524":127,"_297":-5,"_90":525},{"_90":513,"_290":522,"_159":-5,"_515":-5,"_516":-5},{"_90":513,"_290":521,"_159":518,"_515":519,"_516":-5},{"_90":513,"_290":517,"_159":518,"_515":519,"_516":520},{"_90":513,"_290":514,"_159":-5,"_515":-5,"_516":-5},[649],{"_464":45,"_45":528},"task_e_6a13738686d88321a988a36d6ffb15a0",1779659654.52696,"Github 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