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refactor: unify qlib experiment configs, runners, and templates (#1320)

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* refactor: unify qlib experiment configs, runners, and templates

* fix: use PropSetting instances instead of class attributes in qlib runners

* docs: add configurable train/valid/test time segments for fintech scenarios
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Linlang
2026-01-07 12:49:15 +08:00
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commit 19dbeb93e9
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docs/installation_and_configuration.rst
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@@ -201,6 +201,90 @@ The execution environment is determined by the ``DS_CODER_COSTEER_ENV_TYPE`` var
DS_CODER_COSTEER_ENV_TYPE=conda
Custom Time Segment Configuration (Train / Valid / Test)
=========================================================
RD-Agent now supports user-defined time segments for training, validation,
and testing (backtesting). Users can customize these segments via environment
variables in the ``.env`` file, depending on the scenario being executed.
This feature allows greater flexibility when running experiments on different
time ranges without modifying code or YAML configurations.
Fin-Factor Scenario
-------------------
When running the **fin_factor** scenario, you can configure the time segments
using the following environment variables. These variables are read by the
Factor-related PropSettings and directly affect the execution process.
Add the following entries to your ``.env`` file as needed:
.. code-block:: properties
QLIB_FACTOR_TRAIN_START=<train start date, default is 2008-01-01>
QLIB_FACTOR_TRAIN_END=<train end date, default is 2014-12-31>
QLIB_FACTOR_VALID_START=<valid start date, default is 2015-01-01>
QLIB_FACTOR_VALID_END=<valid end date, default is 2016-12-31>
QLIB_FACTOR_TEST_START=<test / backtest start date, default is 2017-01-01>
QLIB_FACTOR_TEST_END=<test / backtest end date, default is 2020-12-31>
Fin-Model Scenario
------------------
When running the **fin_model** scenario, the model training, validation, and
testing time segments can be configured independently via the following
environment variables:
.. code-block:: properties
QLIB_MODEL_TRAIN_START=<train start date, default is 2008-01-01>
QLIB_MODEL_TRAIN_END=<train end date, default is 2014-12-31>
QLIB_MODEL_VALID_START=<valid start date, default is 2015-01-01>
QLIB_MODEL_VALID_END=<valid end date, default is 2016-12-31>
QLIB_MODEL_TEST_START=<test / backtest start date, default is 2017-01-01>
QLIB_MODEL_TEST_END=<test / backtest end date, default is 2020-12-31>
These settings are used during model training and evaluation and directly
impact the execution workflow.
Fin-Quant Scenario
------------------
When running the **fin_quant** scenario, RD-Agent supports configuring time
segments for factor, model, and quant stages simultaneously.
**Note:** The ``QLIB_QUANT_*`` variables are only used for front-end UI display
purposes and do **not** affect the actual execution process.
You may configure the following variables in your ``.env`` file:
.. code-block:: properties
QLIB_FACTOR_TRAIN_START=<train start date, default is 2008-01-01>
QLIB_FACTOR_TRAIN_END=<train end date, default is 2014-12-31>
QLIB_FACTOR_VALID_START=<valid start date, default is 2015-01-01>
QLIB_FACTOR_VALID_END=<valid end date, default is 2016-12-31>
QLIB_FACTOR_TEST_START=<test / backtest start date, default is 2017-01-01>
QLIB_FACTOR_TEST_END=<test / backtest end date, default is 2020-12-31>
QLIB_MODEL_TRAIN_START=<train start date, default is 2008-01-01>
QLIB_MODEL_TRAIN_END=<train end date, default is 2014-12-31>
QLIB_MODEL_VALID_START=<valid start date, default is 2015-01-01>
QLIB_MODEL_VALID_END=<valid end date, default is 2016-12-31>
QLIB_MODEL_TEST_START=<test / backtest start date, default is 2017-01-01>
QLIB_MODEL_TEST_END=<test / backtest end date, default is 2020-12-31>
QLIB_QUANT_TRAIN_START=<train start date, default is 2008-01-01>
QLIB_QUANT_TRAIN_END=<train end date, default is 2014-12-31>
QLIB_QUANT_VALID_START=<valid start date, default is 2015-01-01>
QLIB_QUANT_VALID_END=<valid end date, default is 2016-12-31>
QLIB_QUANT_TEST_START=<test / backtest start date, default is 2017-01-01>
QLIB_QUANT_TEST_END=<test / backtest end date, default is 2020-12-31>
This setup allows the front-end to display consistent segment information
across different stages while keeping execution logic unchanged.
Configuration(deprecated)
=========================