* security: harden artifact serialization and loading
* ci: restore dependency and title lint compatibility
* fix: address artifact test and lint failures
* ci: handle current MLflow and Windows OSQP changes
* ci: use lxml release with cross-platform wheels
* fix: defer optional CVXPY solver imports
* docs: mark notebook model artifacts as trusted
* docs: mark position artifacts as trusted
* style: document intentional lazy import
* ci: skip broken released OSQP on Windows Python 3.8
* fix: mark online model artifacts as trusted
* test: make MLflow client timing check robust
* ci: retry nondeterministic benchmark smoke test
* fix: cap filelock before fork safety regression
* fix: use filelock release compatible with multiprocessing
* fix: preserve artifact loading compatibility after hardening
* fix(security): validate derived artifact paths and extend regressions
* fix(security): preserve extended data artifact round trips
* fix(security): retain legacy NumPy and pandas artifact classes
Allow the exact MaskedArray and SparseDtype module paths emitted by the older dependency versions in CI. Preserve restricted loading and cover both old and new paths.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix(data): avoid unused trading calendar lookup in PIT normalization
PIT normalization uses report dates and calendar-day offsets, so do not request an unused Baostock calendar. Cover annual and quarterly normalization without online calendar access.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix(security): require explicit trust in artifact workflows
Expose default-off artifact trust at online, delayed-training and meta-workflow entry points. Keep data loading restricted, preserve legacy default recorder calls and restored workflow defaults, and document migration and trust boundaries.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* test(workflow): cover complete DDG-DA and HIST artifact flows
Exercise real training, cache and recorder restoration, saved-task replay, signals and portfolio backtests. Fix the cache trust, grouping, relative-path, LightGBM early-stopping and HIST CPU blockers exposed by full execution.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix(security)!: unify artifact trust and publish upgrade guidance
Use trusted consistently across public APIs and CLI options. Migrate pre-release saved consent only at serialization boundaries, reject invalid or conflicting settings, and preserve restricted data reads. Add a canonical upgrade guide with README, installation, changelog and runtime-error entry points.
BREAKING CHANGE: executable artifact restoration requires explicit trusted=True. HIST mappings use JSON and high-frequency cache paths must remain within artifact_root. See docs/start/artifact_migration.rst for upgrading existing workflows.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix(security): remove trial-only trust compatibility
Target upgrades from pre-PR Qlib rather than artifacts generated by intermediate PR revisions. Retain restricted defaults for saved objects without consent, unify current APIs, and remove state/keyword migration branches and documentation.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* ci: avoid failed dataset probes and space download retries
Download the same existing v2 archives used by successful jobs without probing nonexistent package-version assets. Allow five download attempts 60 seconds apart; preserve the full matrix, datasets, noninteractive setup and failure propagation. Cover the exact archives and retry policy in offline CI tests.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* docs: add practical artifact migration examples
Show explicit consent for restored online components while preserving the original manager, schema-aware Arrow conversions, timezone-preserving ZoneInfo migration, and restricted round trips into a separate recorder. Explain shared-component scope, staging artifacts and trusted-source prerequisites.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix(workflow): preserve fresh artifact workflows with scoped trust
Keep immutable cache references intact at open rolling tails. Add explicit per-load record-template consent and per-artifact collector loading options without widening other reads. Restore the original template class after parent-load failures, and support audited business-frequency and NumPy record representations through exact pickle globals.
Document the scoped APIs and cover fresh trained-model reads, cache generation, numerical round trips and refusal paths.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Update detailed_workflow.ipynb
the result figure is empty
* Update detailed_workflow.ipynb
fix issue: the plotly figure is empty
* The error message indicated that my code did not
comply with the code style guidelines.
Specifically, I had used double quotes "notebook"
for the string, whereas the required format was
single quotes 'notebook'.
This has now been corrected.
* comply with the code style guidelines.
Specifically, I had used double quotes "notebook"
for the string, whereas the required format was
single quotes 'notebook'.
This has now been corrected.
* I didn't use nbqa black to reformat my code. Now
is done!
* recover_code
---------
Co-authored-by: Linlang <Lv.Linlang@hotmail.com>
* fixed a problem with multi index caused by the default value of groupkey
* modify group_key default value
* limit pandas verion
* format with black
* fix docs error
* fix docs error
* fixed bugs caused by pandas upgrade
* remove needless code
* reformat with black
* limit version & add docs
* Init model for both dataset
* Remove some deprecated code
* Add model template;
* We must align with previous results
* We choose another mode as the initial version
* Almost success to run GRU
* Successfully run training
* Passed general_nn test
* gru test
* Alignment test passed
* comment
* fix readme & minor errors
* general nn updates & benchmarks
* Update examples/benchmarks/GeneralPtNN/workflow_config_gru2mlp.yaml
---------
Co-authored-by: Young <afe.young@gmail.com>
Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>
* download orderbook data
* fix CI error
* fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* test fix CI error
* optimize get_data code
* optimize get_data code
* optimize get_data code
* optimize README
---------
Co-authored-by: Linlang <v-linlanglv@microsoft.com>
* Add multi pass port ana record
* Add list function
* Add documentation and support <MODEL> tag
* Add drop in replacement example
* reformat
* Change according to comments
* update format
* Update record_temp.py
Fix type hint
* Update record_temp.py
* Intermediate version
* Fix yaml template & Successfully run rolling
* Be compatible with benchmark
* Get same results with previous linear model
* Black formatting
* Update black
* Update the placeholder mechanism
* Update CI
* Update CI
* Upgrade Black
* Fix CI and simplify code
* Fix CI
* Move the data processing caching mechanism into utils.
* Adjusting DDG-DA
* Organize import
* move config file to benchmark_dynamic & switch default sim task model to GBDT
* Update benchmark_dynamic results
* Change the default value of alpha of DDG-DA
* transpose dimension 1 and 2 to match nn.Conv1d input
* 1.update TCN benchmarks;
2.Emphasize updating the benchmark table;
* replace specific version with main
---------
Co-authored-by: lijinhui <362237642@qq.com>
* 1.specify group_keys=False to avoid FutureWarning;
2.fix get train_start from dict unexpected problem;
* fix black
* Add comments
* Add make file
---------
Co-authored-by: Young <afe.young@gmail.com>
* Remove lr_decay and lr_decay_steps params
More flexible way to pass a scheduler (via callable function) is already
supported
* remove lr_decay and lr_decay_steps from mlp workflow configs
* wip
* wip
* wip
* Fix naming errors
* Backtest test passed
* Why training stuck?
* Minor
* Refine train configs
* Use dummy in training
* Remove pickle_dataframe
* CI
* CI
* Add more strict condition to filter orders
* Pass test
* Add TODO in example
---------
Co-authored-by: Young <afe.young@gmail.com>
* Waiting for bin data
* Complete readme
* CI
* Add inst filter by time
* Update qlib/data/dataset/processor.py
* typo
* Fix time filter bug
* Add Filter and set Universe
* Complete data pipeline
* Fix Provider Logger Info Args
* Add DQN; a minor bugfix in ppo reward.
* update readme. modify assertion logic in strategy check.
* Fix Doc issues and fix black
* Fix pylint Error
---------
Co-authored-by: Young <afe.young@gmail.com>
Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>
* Update test_qlib_from_source.yml
* add ipynb format check to workflow
* test ipynb CI
* modify nbqa check path
* add pylint flake8 mypy check to ipynb
* check ipynb with black and pylint
* reformat .ipynb files
* format line length
nbqa black . -l 120
* update nbqa .ipynb format CI
* format old ipynb files
* add nbconvert check to CI
* adjust CI order to avoid repeating download data
* add missing parameters to doc string in order_generate
* fix some typos in doc strings
* reformat base on code style standard
* Update qlib/backtest/__init__.py
* Update examples/run_all_model.py
* Update examples/run_all_model.py
Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>
Linlang
you-n-gandLinlang
DiandLinlang
zipheiandLinlang
codecnotsupported
Lee YuntongandLeeYuntong
Fivele-LiandCadenza-Li
Wendi Li
yaxuan999andYoung
Huoran Li
Maksim Zayakin
qianyun210603andyou-n-g
aprilpearandyou-n-g
huajunzh-msftandyou-n-g
Ning Tangandyou-n-g
lcrunandcanl@microsoft.com
EricChangMSR
