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6 Commits

Author SHA1 Message Date
you-n-g
f48bf813e3 chore(main): release 0.9.8 2025-11-06 21:52:22 +08:00
Linlang
66c36226aa fix(macd): remove extra division by close in DEA calculation to ensure dimension consistency (#2046) 2025-11-06 21:49:15 +08:00
shauryaMi12
bb7ab1cf14 docs: fix spelling mistake: exmaple to example (#2033)
Co-authored-by: Linlang <Lv.Linlang@hotmail.com>
2025-10-17 13:20:16 +08:00
shauryaMi12
3dc5a7d299 fix: typo in integration documentation: 'userd' -> 'used' (#2034)
* Fix typo in integration docs: 'userd' -> 'used'

* fix: pylint error in CI

---------

Co-authored-by: Linlang <Lv.Linlang@hotmail.com>
2025-10-16 11:07:55 +08:00
Kei YAMAZAKI
7d66e4b788 docs: update Docker run command in README.md to specify the correct image name (#2010) 2025-09-15 17:09:36 +08:00
Linlang
213eb6c2cd fix: the bug when auto_mount=True (#2009)
* fix: the bug when auto_mount=True

* fix: the bug when auto_mount=True
2025-09-11 20:05:17 +08:00
8 changed files with 34 additions and 22 deletions

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@@ -0,0 +1,13 @@
# Changelog
## [0.9.8](https://github.com/microsoft/qlib/compare/v0.9.7...v0.9.8) (2025-11-06)
### Bug Fixes
* download orderbook data error ([#1990](https://github.com/microsoft/qlib/issues/1990)) ([136b2dd](https://github.com/microsoft/qlib/commit/136b2ddf9a16e4106d62b8d1336a56273a8abef0))
* **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' -&gt; 'used' ([#2034](https://github.com/microsoft/qlib/issues/2034)) ([3dc5a7d](https://github.com/microsoft/qlib/commit/3dc5a7d299074f0fa45a4b7bb50ab446a8824a32))

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@@ -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 qlib_image_stable
docker run -it --name <container name> -v <Mounted local directory>:/app pyqlib/qlib_image_stable:stable
```
3. At this point you are in the docker environment and can run the qlib scripts. An example:
```bash

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@@ -42,7 +42,7 @@ Example
.. math::
DEA = \frac{EMA(DIF, 9)}{CLOSE}
DEA = EMA(DIF, 9)
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 = '(EMA($close, 12) - EMA($close, 26))/$close - EMA((EMA($close, 12) - EMA($close, 26))/$close, 9)/$close'
>> MACD_EXP = '2 * ((EMA($close, 12) - EMA($close, 26))/$close - EMA((EMA($close, 12) - EMA($close, 26))/$close, 9))'
>> fields = [MACD_EXP] # MACD
>> names = ['MACD']
>> labels = ['Ref($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 -0.011547 -0.019672
SH600004 0.002745 -0.014721
SH600006 0.010133 0.002911
SH600008 -0.001113 0.009818
SH600009 0.025878 -0.017758
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
... ... ...
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
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
Reference
=========

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@@ -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 exmaple which does the same thing as above examples.
Here is an example which does the same thing as above examples.
.. code-block:: python

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@@ -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 userd to get the test dataset.
- The parameters must include the parameter `dataset`, which will be used 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.

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@@ -140,7 +140,10 @@ 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:
_temp_mount = _c.decode("utf-8").split(" ")[2]
if isinstance(_c, str):
_temp_mount = _c.split(" ")[2]
else:
_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

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@@ -82,7 +82,7 @@ def get_calendar_list(bench_code="CSI300") -> List[pd.Timestamp]:
if bench_code.upper() == "ALL":
@deco_retry
def _get_calendar(month):
def _get_calendar_from_month(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(_m.strftime("%Y-%m"))
cal = _get_calendar_from_month(_m.strftime("%Y-%m"))
if cal:
calendar += cal
calendar = list(filter(lambda x: x <= pd.Timestamp.now(), calendar))

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@@ -613,10 +613,6 @@ 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]: