fix: trying to fix the error in github action by limiting the version of gymnasium

CHANGELOG.md

@@ -1,14 +0,0 @@
-# Changelog
-
-## [0.9.8](https://github.com/microsoft/qlib/compare/v0.9.7...v0.9.8) (2025-11-13)
-
-
-### Bug Fixes
-
-* download orderbook data error ([#1990](https://github.com/microsoft/qlib/issues/1990)) ([136b2dd](https://github.com/microsoft/qlib/commit/136b2ddf9a16e4106d62b8d1336a56273a8abef0))
-* **gbdt:** correct dtrain assignment in finetune() to use Dataset instead of tuple ([#2049](https://github.com/microsoft/qlib/issues/2049)) ([2b41782](https://github.com/microsoft/qlib/commit/2b41782f0cfb81e8cc065f2915b215758a7838ef))
-* **macd:** remove extra division by close in DEA calculation to ensure dimension consistency ([#2046](https://github.com/microsoft/qlib/issues/2046)) ([66c3622](https://github.com/microsoft/qlib/commit/66c36226aafceabe497e5967f67921e5d3c9d497))
-* replace deprecated pandas fillna(method=) with ffill()/bfill() ([#1987](https://github.com/microsoft/qlib/issues/1987)) ([7095e75](https://github.com/microsoft/qlib/commit/7095e755fa57e011f0483d24b45fc5bd5a4deaf8))
-* spelling errors ([#1996](https://github.com/microsoft/qlib/issues/1996)) ([f26b341](https://github.com/microsoft/qlib/commit/f26b3417363410531dbbb39e425bce6cf05528a1))
-* the bug when auto_mount=True ([#2009](https://github.com/microsoft/qlib/issues/2009)) ([213eb6c](https://github.com/microsoft/qlib/commit/213eb6c2cd12342b6ec98f21300217e1659f3d58))
-* typo in integration documentation: 'userd' -> 'used' ([#2034](https://github.com/microsoft/qlib/issues/2034)) ([3dc5a7d](https://github.com/microsoft/qlib/commit/3dc5a7d299074f0fa45a4b7bb50ab446a8824a32))

Makefile

@@ -113,7 +113,7 @@ dev: prerequisite all
 
 # Check lint with black.
 black:
-	black . -l 120 --check --diff --exclude qlib/_version.py
+	black . -l 120 --check --diff
 
 # Check code folder with pylint.
 # TODO: These problems we will solve in the future. Important among them are: W0221, W0223, W0237, E1102

README.md

@@ -324,7 +324,7 @@ We recommend users to prepare their own data if they have a high-quality dataset
     ```
 2. Start a new Docker container
     ```bash
-    docker run -it --name <container name> -v <Mounted local directory>:/app pyqlib/qlib_image_stable:stable
+    docker run -it --name <container name> -v <Mounted local directory>:/app qlib_image_stable
     ```
 3. At this point you are in the docker environment and can run the qlib scripts. An example:
     ```bash

docs/advanced/alpha.rst

@@ -42,7 +42,7 @@ Example
 
     .. math::
 
-        DEA = EMA(DIF, 9)
+        DEA = \frac{EMA(DIF, 9)}{CLOSE}
 
 Users can use ``Data Handler`` to build formulaic alphas `MACD` in qlib:
 
@@ -51,7 +51,7 @@ Users can use ``Data Handler`` to build formulaic alphas `MACD` in qlib:
 .. code-block:: python
 
     >> from qlib.data.dataset.loader import QlibDataLoader
-    >> MACD_EXP = '2 * ((EMA($close, 12) - EMA($close, 26))/$close - EMA((EMA($close, 12) - EMA($close, 26))/$close, 9))'
+    >> MACD_EXP = '(EMA($close, 12) - EMA($close, 26))/$close - EMA((EMA($close, 12) - EMA($close, 26))/$close, 9)/$close'
     >> fields = [MACD_EXP] # MACD
     >> names = ['MACD']
     >> labels = ['Ref($close, -2)/Ref($close, -1) - 1'] # label
@@ -66,17 +66,17 @@ Users can use ``Data Handler`` to build formulaic alphas `MACD` in qlib:
                             feature     label
                                MACD     LABEL
     datetime   instrument
-    2010-01-04 SH600000    0.008781 -0.019672
-               SH600004    0.006699 -0.014721
-               SH600006    0.005714  0.002911
-               SH600008    0.000798  0.009818
-               SH600009    0.017015 -0.017758
+    2010-01-04 SH600000   -0.011547 -0.019672
+               SH600004    0.002745 -0.014721
+               SH600006    0.010133  0.002911
+               SH600008   -0.001113  0.009818
+               SH600009    0.025878 -0.017758
     ...                         ...       ...
-    2017-12-29 SZ300124    0.015071 -0.005074
-               SZ300136   -0.015466  0.056352
-               SZ300144    0.013082  0.011853
-               SZ300251   -0.001026  0.021739
-               SZ300315   -0.007559  0.012455
+    2017-12-29 SZ300124    0.007306 -0.005074
+               SZ300136   -0.013492  0.056352
+               SZ300144   -0.000966  0.011853
+               SZ300251    0.004383  0.021739
+               SZ300315   -0.030557  0.012455
 
 Reference
 =========

docs/start/getdata.rst

@@ -129,7 +129,7 @@ For example, it looks quite long and complicated:
 
 
 But using string is not the only way to implement the expression. You can also implement expression by code.
-Here is an example which does the same thing as above examples.
+Here is an exmaple which does the same thing as above examples.
 
 
 .. code-block:: python

docs/start/integration.rst

@@ -71,7 +71,7 @@ The Custom models need to inherit `qlib.model.base.Model <../reference/api.html#
                 )
 
 - Override the `predict` method
-    - The parameters must include the parameter `dataset`, which will be used to get the test dataset.
+    - The parameters must include the parameter `dataset`, which will be userd to get the test dataset.
     - Return the `prediction score`.
     - Please refer to `Model API <../reference/api.html#module-qlib.model.base>`_ for the parameter types of the fit method.
     - Code Example: In the following example, users need to use `LightGBM` to predict the label(such as `preds`) of test data `x_test` and return it.

pyproject.toml

@@ -45,7 +45,7 @@ dependencies = [
   "pymongo",
   "loguru",
   "lightgbm",
-  "gym",
+  "gymnasium<=0.26.2",
   "cvxpy",
   "joblib",
   "matplotlib",
@@ -117,4 +117,3 @@ qrun = "qlib.cli.run:run"
 [tool.setuptools_scm]
 local_scheme = "no-local-version"
 version_scheme = "guess-next-dev"
-write_to = "qlib/_version.py"

qlib/__init__.py

@@ -4,10 +4,7 @@ from pathlib import Path
 
 from setuptools_scm import get_version
 
-try:
-    from ._version import version as __version__
-except ImportError:
-    __version__ = get_version(root="..", relative_to=__file__)
+__version__ = get_version(root="..", relative_to=__file__)
 __version__bak = __version__  # This version is backup for QlibConfig.reset_qlib_version
 import logging
 import os
@@ -143,10 +140,7 @@ def _mount_nfs_uri(provider_uri, mount_path, auto_mount: bool = False):
                     _command_log = [line for line in _command_log if _remote_uri in line]
                 if len(_command_log) > 0:
                     for _c in _command_log:
-                        if isinstance(_c, str):
-                            _temp_mount = _c.split(" ")[2]
-                        else:
-                            _temp_mount = _c.decode("utf-8").split(" ")[2]
+                        _temp_mount = _c.decode("utf-8").split(" ")[2]
                         _temp_mount = _temp_mount[:-1] if _temp_mount.endswith("/") else _temp_mount
                         if _temp_mount == _mount_path:
                             _is_mount = True

qlib/contrib/model/gbdt.py

@@ -51,7 +51,7 @@ class LGBModel(ModelFT, LightGBMFInt):
                     w = reweighter.reweight(df)
                 else:
                     raise ValueError("Unsupported reweighter type.")
-                ds_l.append((lgb.Dataset(x.values, label=y, weight=w, free_raw_data=False), key))
+                ds_l.append((lgb.Dataset(x.values, label=y, weight=w), key))
         return ds_l
 
     def fit(
@@ -109,10 +109,8 @@ class LGBModel(ModelFT, LightGBMFInt):
             verbose level
         """
         # Based on existing model and finetune by train more rounds
-        ds_l = self._prepare_data(dataset, reweighter)
-        dtrain, _ = ds_l[0]
-
-        if dtrain.construct().num_data() == 0:
+        dtrain, _ = self._prepare_data(dataset, reweighter)  # pylint: disable=W0632
+        if dtrain.empty:
             raise ValueError("Empty data from dataset, please check your dataset config.")
         verbose_eval_callback = lgb.log_evaluation(period=verbose_eval)
         self.model = lgb.train(

qlib/rl/interpreter.py

@@ -5,9 +5,9 @@ from __future__ import annotations
 
 from typing import Any, Generic, TypeVar
 
-import gym
+import gymnasium as gym
 import numpy as np
-from gym import spaces
+from gymnasium import spaces
 
 from qlib.typehint import final
 from .simulator import ActType, StateType

qlib/rl/order_execution/interpreter.py

@@ -8,7 +8,7 @@ from typing import Any, List, Optional, cast
 
 import numpy as np
 import pandas as pd
-from gym import spaces
+from gymnasium import spaces
 
 from qlib.constant import EPS
 from qlib.rl.data.base import ProcessedDataProvider

qlib/rl/order_execution/policy.py

@@ -6,11 +6,11 @@ from __future__ import annotations
 from pathlib import Path
 from typing import Any, Dict, Generator, Iterable, Optional, OrderedDict, Tuple, cast
 
-import gym
+import gymnasium as gym
 import numpy as np
 import torch
 import torch.nn as nn
-from gym.spaces import Discrete
+from gymnasium.spaces import Discrete
 from tianshou.data import Batch, ReplayBuffer, to_torch
 from tianshou.policy import BasePolicy, PPOPolicy, DQNPolicy
 

qlib/rl/utils/env_wrapper.py

@@ -6,8 +6,8 @@ from __future__ import annotations
 import weakref
 from typing import Any, Callable, cast, Dict, Generic, Iterable, Iterator, Optional, Tuple
 
-import gym
-from gym import Space
+import gymnasium as gym
+from gymnasium import Space
 
 from qlib.rl.aux_info import AuxiliaryInfoCollector
 from qlib.rl.interpreter import ActionInterpreter, ObsType, PolicyActType, StateInterpreter

qlib/rl/utils/finite_env.py

@@ -13,7 +13,7 @@ import warnings
 from contextlib import contextmanager
 from typing import Any, Callable, Dict, Generator, List, Optional, Set, Tuple, Type, Union, cast
 
-import gym
+import gymnasium as gym
 import numpy as np
 from tianshou.env import BaseVectorEnv, DummyVectorEnv, ShmemVectorEnv, SubprocVectorEnv
 

scripts/collect_info.py

@@ -45,7 +45,7 @@ class InfoCollector:
             "pymongo",
             "loguru",
             "lightgbm",
-            "gym",
+            "gymnasium",
             "cvxpy",
             "joblib",
             "matplotlib",

scripts/data_collector/utils.py

@@ -82,7 +82,7 @@ def get_calendar_list(bench_code="CSI300") -> List[pd.Timestamp]:
             if bench_code.upper() == "ALL":
 
                 @deco_retry
-                def _get_calendar_from_month(month):
+                def _get_calendar(month):
                     _cal = []
                     try:
                         resp = requests.get(
@@ -98,7 +98,7 @@ def get_calendar_list(bench_code="CSI300") -> List[pd.Timestamp]:
                 month_range = pd.date_range(start="2000-01", end=pd.Timestamp.now() + pd.Timedelta(days=31), freq="M")
                 calendar = []
                 for _m in month_range:
-                    cal = _get_calendar_from_month(_m.strftime("%Y-%m"))
+                    cal = _get_calendar(_m.strftime("%Y-%m"))
                     if cal:
                         calendar += cal
                 calendar = list(filter(lambda x: x <= pd.Timestamp.now(), calendar))

scripts/data_collector/yahoo/collector.py

@@ -613,6 +613,10 @@ class YahooNormalize1min(YahooNormalize, ABC):
     def symbol_to_yahoo(self, symbol):
         raise NotImplementedError("rewrite symbol_to_yahoo")
 
+    @abc.abstractmethod
+    def _get_1d_calendar_list(self) -> Iterable[pd.Timestamp]:
+        raise NotImplementedError("rewrite _get_1d_calendar_list")
+
 
 class YahooNormalizeUS:
     def _get_calendar_list(self) -> Iterable[pd.Timestamp]:

setup.py

@@ -2,12 +2,22 @@ import os
 
 import numpy
 from setuptools import Extension, setup
+from setuptools_scm import get_version
+
+
+def read(rel_path: str) -> str:
+    here = os.path.abspath(os.path.dirname(__file__))
+    with open(os.path.join(here, rel_path), encoding="utf-8") as fp:
+        return fp.read()
 
 
 NUMPY_INCLUDE = numpy.get_include()
 
 
+VERSION = get_version(root=".", relative_to=__file__)
+
 setup(
+    version=VERSION,
     ext_modules=[
         Extension(
             "qlib.data._libs.rolling",

tests/rl/test_finite_env.py

@@ -3,7 +3,7 @@
 
 from collections import Counter
 
-import gym
+import gymnasium as gym
 import numpy as np
 from tianshou.data import Batch, Collector
 from tianshou.policy import BasePolicy

tests/rl/test_logger.py

@@ -7,10 +7,10 @@ import logging
 import re
 from typing import Any, Tuple
 
-import gym
+import gymnasium as gym
 import numpy as np
 import pandas as pd
-from gym import spaces
+from gymnasium import spaces
 from tianshou.data import Collector, Batch
 from tianshou.policy import BasePolicy
 

tests/rl/test_trainer.py

@@ -7,7 +7,7 @@ import pytest
 
 import torch
 import torch.nn as nn
-from gym import spaces
+from gymnasium import spaces
 from tianshou.policy import PPOPolicy
 
 from qlib.config import C