release: spotforecast2 7.0.0 — spotoptim 1.0 (sequential), drop n_jobs_spotoptim#208
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…spotoptim spotoptim 1.0 is sequential-only: n_jobs / eval_batch_size were removed and passing them now raises TypeError. spotforecast2-safe 21.0.0 removed the dead n_jobs_spotoptim config field in lockstep. This change makes sf2 compatible with both and retires all parallel-SpotOptim scaffolding. Changes: - Bump pins: spotoptim[torch]>=1.0.0,<2 and spotforecast2-safe>=21.0.0,<22. spotoptim 1.0 made torch/tensorboard optional ([torch] extra); pin the extra so the TensorBoard tuning pass-through keeps working (was always available via spotoptim's old hard torch dependency). - Declare xgboost explicitly: it is imported at module top-level in spotforecast2.tasks.task_entsoe and the xgb forecaster model, previously satisfied transitively via spotoptim's dependency tree. - SpotOptimStrategy: stop forwarding config.n_jobs_spotoptim into SpotOptim; keep the TensorBoard kwargs pass-through. - spotoptim_search: remove the multiprocessing.Manager shared counter, the parallel-eval detection, the worker-side result-recovery block, and the config_counter/config_counter_lock objective parameters. The trial bar is now unconditional on show_progress; the "config k/N" label counts completed configs. Backtesting-level n_jobs (skforecast) is unchanged. - Tests: delete test_spotoptim_parallel.py; drop the shared-counter / parallel label tests; convert the TensorBoard pass-through test to a sequential run. - Docs: spotoptim_intro narrative updated to sequential-only. BREAKING CHANGE: spotforecast2 now requires spotoptim>=1.0 and spotforecast2-safe>=21. The n_jobs_spotoptim config field is gone and SpotOptim tuning is sequential-only; backtesting parallelism (n_jobs) is unaffected. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…or/spotoptim-1.0-sequential feat!: require spotoptim 1.0 (sequential) + sf2-safe 21, drop n_jobs_spotoptim
## [7.0.0-rc.1](v6.1.0...v7.0.0-rc.1) (2026-06-09) ### ⚠ BREAKING CHANGES * spotforecast2 now requires spotoptim>=1.0 and spotforecast2-safe>=21. The n_jobs_spotoptim config field is gone and SpotOptim tuning is sequential-only; backtesting parallelism (n_jobs) is unaffected. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> ### Features * require spotoptim 1.0 (sequential) + sf2-safe 21, drop n_jobs_spotoptim ([ce81d8f](ce81d8f))
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🎉 This PR is included in version 7.0.0-rc.1 🎉 The release is available on GitHub release Your semantic-release bot 📦🚀 |
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🎉 This PR is included in version 7.0.0 🎉 The release is available on GitHub release Your semantic-release bot 📦🚀 |
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Promotes the spotoptim 1.0 / sf2-safe 21 compatibility work from
developtomainto cut the final 7.0.0 release.See #207 for the full change set. Coordinated migration: sf2-safe 21.0.0 (released) → sf2 7.0.0 (this release) → bart26k-lecture.
spotoptim[torch]>=1.0(sequential-only) andspotforecast2-safe>=21.n_jobs_spotoptimforwarding and all parallel-SpotOptim scaffolding.xgboostexplicitly (exposed by spotoptim's dependency slimming).Verified: fast suite green against sf2-safe 21 + spotoptim 1.0; both bart26k-lecture team4 submission scripts run end-to-end on the new stack.
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