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feat: automate semantic releases with release-please - #169
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Write down where and why we mean to publish jupyddl as citable research software (.docs/PUBLISHING.md): a Zenodo DOI per release, a JOSS paper, ICAPS workshops for the research results, with a readiness checklist, the paper outline, the AI-usage disclosure JOSS requires, and how contributors can be considered for authorship. The README states the project's aim and its Cite section now says which version the 2021 preprint describes. Add the community files an outside contributor expects: a security policy, a pull-request template, a "Propose an algorithm" issue template, and an "Adding an algorithm" section in CONTRIBUTING.md. Run tests and build on pull requests. They were `on: [push]`, which never fires for a fork, so a contributor's PR showed no checks at all. Fix AGENTS.md drift: the Python floor is 3.10 and Mergify is retired. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RbGtRHF8XhkiPQCDVHtV2
A package can now add planners, heuristics and generators by declaring `jupyddl.planners`, `jupyddl.heuristics` or `jupyddl.generators` entry points. Once installed, they work from the CLI, the benchmark harness and `jupyddl.solve` by name, without anyone importing the package. Discovery is lazy and defensive (jupyddl/plugins.py): the CLI runs it before building its parser, the library only on a registry miss, so importing jupyddl never scans installed packages. A built-in name always wins, a plugin that fails to import is skipped with a warning, and JUPYDDL_NO_PLUGINS=1 turns it off. `jupyddl plugins` lists what was found. The CLI now reads `requires_heuristic` from the registry at call time, since INFORMED_PLANNERS is fixed at import and cannot know about plugins. .docs/EXTENDING.md walks through a heuristic, a planner from a priority function, a planner from scratch with the budget/observer contract, a generator, testing the guarantees you claim, and shipping as a plugin. tests/test_extending.py runs every Python block in it, so it cannot drift. best_first now accepts a tuple priority for tie-breaking; observers get its first element as `f`, so traces stay numeric. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RbGtRHF8XhkiPQCDVHtV2
# Conflicts: # .docs/PUBLISHING.md # AGENTS.md # CHANGELOG.md
Each of these returned a plan, a cost or a value without complaint, and validate_plan accepted the plans because it replays them through the same Task.apply. tests/test_semantics.py now pins them on tiny hand-written tasks; 16 of its cases fail on the previous code. - Derived facts were never retracted, and (not <derived>) held from the start. close() now recomputes axioms from scratch and maintains negated derived facts; negation inside a rule body (needs stratification) is refused. The relaxation gets the complement for free, so it never calls a solvable state a dead end. - An atom both added and deleted left its complement true too; a `when` re-adding a deleted atom did the same. Complements: the delete wins. - Under a (total-cost) metric an action without a cost effect is free, as in IPC planners (pegsol/sokoban optimised the wrong objective). Cost inside `when` was charged unconditionally: refused, as are negative costs. - A never-defined numeric fluent read as 0; conditions reading one fail. - blind skipped zero-cost actions and overestimated. - h1/h2/hm crashed on numeric states; LM-cut crashed on an empty goal. - lmcut and h2 clear `admissible` on tasks with conditional effects. - Optimal planners default to lmcut, not hff; `-H none` means blind. - make_heuristic builds a heuristic class or partial instead of passing it through unbuilt. - Fact ids and id sets are built in sorted order, so LM-cut tie-breaks, expansions and plans no longer change with PYTHONHASHSEED. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RbGtRHF8XhkiPQCDVHtV2
- iddfs, idastar and ehc never read their budget, so --time-limit was ignored. They poll per expansion now; the recursive ones unwind with BudgetExhausted. beam polls per node, not per layer, and bnb stops evaluating siblings once the budget fires. - Hitting a depth cap (iddfs max_depth, bnb max_depth) or Python's recursion limit sets stats.truncated: it is not a proof of unsolvability, nor of optimality. - bfs and iddfs leave OPTIMAL_PLANNERS: they minimise plan length, and on errands return cost 16 where 10 is optimal. - Live dashboard: a budget stop no longer reads "no plan found"; lines are clipped to the stream's terminal width so repaints do not smear; the non-tty log writes at most every two seconds. - idastar/ehc/hc/beam without a heuristic raise a clear ValueError; MultiObserver forwards positional arguments; the SearchObserver and best_first docstrings say what actually happens. tests/test_search_contract.py runs every planner where the budget is the only thing that stops it, checks OPTIMAL_PLANNERS against dijkstra under action costs, and pins the dashboard behaviour. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RbGtRHF8XhkiPQCDVHtV2
- Exit codes say what happened: 0 solved, 1 no plan, 2 bad input, 3 stopped by a budget, 4 a plan that failed validation. Unsolvable, out of budget and a crash all used to exit 1. - Bad input (missing file, parse error, unknown planner or heuristic, a malformed --sizes) is one line on stderr, not a traceback; JUPYDDL_DEBUG=1 restores the traceback. --version exists. - `demo` and `benchmark demos` never finished. Both stop each search after 10 s by default (--time-limit 0 for none); animate and demo take the same budget flags as solve. - benchmark validates --planners/--heuristic/--metric up front, and chart options check for the viz extra before searching rather than after. - Dead ends (h = inf) crashed the progress chart and coloured the wavefront NaN; in the workbench they made the progress message invalid JSON and aborted the run. - A trace's plan is the visible plan, without compiler bookkeeping. - Packaging: the sdist's own suite failed because .github/ was dropped wholesale; only workflows are excluded now. build runs twine --strict. black is pinned to one major in dev and format.yml; Renovate pins third-party actions to digests. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RbGtRHF8XhkiPQCDVHtV2
PR titles become Conventional Commits (pr-title check, plain shell, no third-party action). On every push to main release-please keeps one release PR whose version follows from what was merged: fix -> patch, feat -> minor, feat!/BREAKING CHANGE -> major. tools/release_pr_fixup.py then files the hand-written [Unreleased] notes under the new section and rebuilds web/dist, which records the version. Merging the release PR tags the commit; release-please.yml then dispatches release.yml on the tag, because a tag made with the workflow token triggers no workflows. release.yml now also refuses a dispatch that would re-release an existing version. Renovate opens semantic titles so its PRs pass the check. tests/test_release.py pins the manifest, pyproject and __version__ together and checks the changelog fix-up, including the section release.yml extracts. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RbGtRHF8XhkiPQCDVHtV2
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What and why
Releases now follow semantic versioning, with the bump decided by what each merged PR contains. Nobody picks a number.
fix: …/fix(lmcut): …/perf: …feat: …feat!: …or aBREAKING CHANGE:footerdocs:chore:ci:test:refactor:…How it works
pr-title.ymlrequires a Conventional Commit title. It is plain shell with no third-party action, and reads the title from an env var so the title can't inject into the script.release-please.ymlruns on every push tomainand keeps one release PR up to date (chore: release X.Y.Z). That PR:pyproject.toml,jupyddl.__version__(via anx-release-please-versionmarker) and the manifest;tools/release_pr_fixup.py, which moves the hand-written## [Unreleased]notes under the new version and rebuildsweb/dist. The bundle records the version, andpagesrefuses to deploy a stale one.release.ymlon that tag: build → verify → PyPI (trusted publishing, unchanged) → attach artifacts.workflow_dispatchis the exception, so no personal token is needed.Also
release.ymlnow refuses a manual dispatch that would re-release an existing version. Before, PyPI silently skipped the upload while the GitHub Release had its assets replaced from a different commit (flagged in the review).chore(deps): …), so its PRs pass the check.pr-titleortestsrequired checks without an exception for the release PR. A PR opened with the workflow token starts no workflows, so those checks never report on it.release.ymlrepeats every check that matters before publishing.How it was checked
tests/test_release.py:pyproject.tomland__version__agree;release.ymlextracts for the release notes contains both the generated and the hand-written notes.flake8andblackare clean, andweb/distis rebuilt.feat:, so it should open a2.5.0release PR carrying all the Unreleased notes.Checklist
flake8 jupyddl tests toolsandpytestpass locallyweb/distrebuiltCHANGELOG.mdupdatedThe history has a
merge -s oursof the already-merged #167 tip so the push fast-forwards. Squash-merge, keeping the PR title as the commit message.Generated by Claude Code