https://github.com/wukan1986/polars_ta
Technical Analysis Indicators for polars
https://github.com/wukan1986/polars_ta
expression polars ta talib
Last synced: 3 months ago
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Technical Analysis Indicators for polars
- Host: GitHub
- URL: https://github.com/wukan1986/polars_ta
- Owner: wukan1986
- License: mit
- Created: 2023-12-12T11:44:52.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2025-08-02T17:13:15.000Z (3 months ago)
- Last Synced: 2025-08-02T19:34:06.413Z (3 months ago)
- Topics: expression, polars, ta, talib
- Language: Python
- Homepage: https://polars-ta.readthedocs.io
- Size: 330 KB
- Stars: 183
- Watchers: 6
- Forks: 44
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-polars - polars_ta - Python package that provides technical indicator operators rewritten in Polars by [@wukan1986](https://github.com/wukan1986). (Libraries/Packages/Scripts / Polars plugins)
README
# polars_ta
Technical Indicator Operators Rewritten in `polars`.
We provide wrappers for some functions (like `TA-Lib`) that are not `pl.Expr` alike.
## How to Install
### Using `pip`
```commandline
pip install -i https://pypi.org/simple --upgrade polars_ta
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple --upgrade polars_ta # Mirror in China
```
### Build from Source
```commandline
git clone --depth=1 https://github.com/wukan1986/polars_ta.git
cd polars_ta
python -m build
cd dist
pip install polars_ta-0.1.2-py3-none-any.whl
```
### How to Install TA-Lib
Non-official `TA-Lib` wheels can be downloaded from `https://github.com/cgohlke/talib-build/releases`
## Usage
See `examples` folder.
```python
# We need to modify the function name by prefixing `ts_` before using them in `expr_coodegen`
from polars_ta.prefix.tdx import *
# Import functions from `wq`
from polars_ta.prefix.wq import *
# Example
df = df.with_columns([
# Load from `wq`
*[ts_returns(CLOSE, i).alias(f'ROCP_{i:03d}') for i in (1, 3, 5, 10, 20, 60, 120)],
*[ts_mean(CLOSE, i).alias(f'SMA_{i:03d}') for i in (5, 10, 20, 60, 120)],
*[ts_std_dev(CLOSE, i).alias(f'STD_{i:03d}') for i in (5, 10, 20, 60, 120)],
*[ts_max(HIGH, i).alias(f'HHV_{i:03d}') for i in (5, 10, 20, 60, 120)],
*[ts_min(LOW, i).alias(f'LLV_{i:03d}') for i in (5, 10, 20, 60, 120)],
# Load from `tdx`
*[ts_RSI(CLOSE, i).alias(f'RSI_{i:03d}') for i in (6, 12, 24)],
])
```
When both `min_samples` and `MIN_SAMPLES` are set, `min_samples` takes precedence. default value is `None`.
```python
import polars_ta
# Global settings. Priority Low
polars_ta.MIN_SAMPLES = 1
# High priority
ts_mean(CLOSE, 10, min_samples=1)
```
## How We Designed This
1. We use `Expr` instead of `Series` to avoid using `Series` in the calculation. Functions are no longer methods of class.
2. Use `wq` first. It mimics `WorldQuant Alpha` and strives to be consistent with them.
3. Use `ta` otherwise. It is a `polars`-style version of `TA-Lib`. It tries to reuse functions from `wq`.
4. Use `tdx` last. It also tries to import functions from `wq` and `ta`.
5. We keep the same signature and parameters as the original `TA-Lib` in `talib`.
6. If there is a naming conflict, we suggest calling `wq`, `ta`, `tdx`, `talib` in order. The higher the priority, the closer the implementation is to `Expr`.
## Comparison of Our Indicators and Others
See [compare](compare.md)
## Handling Null/NaN Values
See [nan_to_null](nan_to_null.md)
## Debugging
```commandline
git clone --depth=1 https://github.com/wukan1986/polars_ta.git
cd polars_ta
pip install -e .
```
Notice:
If you have added some functions in `ta` or `tdx`, please run `prefix_ta.py` or `prefix_tdx.py` inside the `tools` folder to generate the corrected Python script (with the prefix added).
This is required to use in `expr_codegen`.
## Reference
- https://github.com/pola-rs/polars
- https://github.com/TA-Lib/ta-lib
- https://github.com/twopirllc/pandas-ta
- https://github.com/bukosabino/ta
- https://github.com/peerchemist/finta
- https://github.com/wukan1986/ta_cn
- https://support.worldquantbrain.com/hc/en-us/community/posts/20278408956439-从价量看技术指标总结-Technical-Indicator-
- https://platform.worldquantbrain.com/learn/operators/operators
# polars_ta
基于`polars`的算子库。实现量化投研中常用的技术指标、数据处理等函数。对于不易翻译成`Expr`的库（如：`TA-Lib`）也提供了函数式调用的封装
## 安装
### 在线安装
```commandline
pip install -i https://pypi.org/simple --upgrade polars_ta # 官方源
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple --upgrade polars_ta # 国内镜像源
```
### 源码安装
```commandline
git clone --depth=1 https://github.com/wukan1986/polars_ta.git
cd polars_ta
python -m build
cd dist
pip install polars_ta-0.1.2-py3-none-any.whl
```
### TA-Lib安装
Windows用户不会安装可从`https://github.com/cgohlke/talib-build/releases` 下载对应版本whl文件
## 使用方法
参考`examples`目录即可，例如：
```python
# 如果需要在`expr_codegen`中使用，需要有`ts_`等前权，这里导入提供了前缀
from polars_ta.prefix.tdx import *
# 导入wq公式
from polars_ta.prefix.wq import *
# 演示生成大量指标
df = df.with_columns([
# 从wq中导入指标
*[ts_returns(CLOSE, i).alias(f'ROCP_{i:03d}') for i in (1, 3, 5, 10, 20, 60, 120)],
*[ts_mean(CLOSE, i).alias(f'SMA_{i:03d}') for i in (5, 10, 20, 60, 120)],
*[ts_std_dev(CLOSE, i).alias(f'STD_{i:03d}') for i in (5, 10, 20, 60, 120)],
*[ts_max(HIGH, i).alias(f'HHV_{i:03d}') for i in (5, 10, 20, 60, 120)],
*[ts_min(LOW, i).alias(f'LLV_{i:03d}') for i in (5, 10, 20, 60, 120)],
# 从tdx中导入指标
*[ts_RSI(CLOSE, i).alias(f'RSI_{i:03d}') for i in (6, 12, 24)],
])
```
当`min_samples`和`MIN_SAMPLES`都设置时，以`min_samples`为准，默认值为`None`
```python
import polars_ta
# 全局设置。优先级低
polars_ta.MIN_SAMPLES = 1
# 指定函数。优先级高
ts_mean(CLOSE, 10, min_samples=1)
```
## 设计原则
1. 调用方法由`成员函数`换成`独立函数`。输入输出使用`Expr`，避免使用`Series`
2. 优先实现`wq`公式，它仿`WorldQuant Alpha`公式，与官网尽量保持一致。如果部分功能实现在此更合适将放在此处
3. 其次实现`ta`公式，它相当于`TA-Lib`的`polars`风格的版本。优先从`wq`中导入更名
4. 最后实现`tdx`公式，它也是优先从`wq`和`ta`中导入
5. `talib`的函数名与参数与原版`TA-Lib`完全一致
6. 如果出现了命名冲突，建议调用优先级为`wq`、`ta`、`tdx`、`talib`。因为优先级越高，实现方案越接近于`Expr`
## 指标区别
请参考[compare](compare.md)
## 空值处理
请参考[nan_to_null](nan_to_null.md)
## 开发调试
```commandline
git clone --depth=1 https://github.com/wukan1986/polars_ta.git
cd polars_ta
pip install -e .
```
注意：如果你在`ta`或`tdx`中添加了新的函数，请再运行`tools`下的`prefix_ta.py`或`prefix_tdx.py`，用于生成对应的前缀文件。前缀文件方便在`expr_codegen`中使用
## 文档生成
```commandline
pip install -r requirements-docs.txt
mkdocs build
```
文档生成在`site`目录下，其中的`llms-full.txt`可以作为大语言模型的知识库导入。
也可以通过以下链接导入：
https://polars-ta.readthedocs.io/en/latest/llms-full.txt
## 提示词
由于`llms-full.txt`信息不适合做提示词，所以`tools/prompt.py`提供了生成更简洁算子清单的功能。
用户也可以直接使用`prompt.txt`(欢迎提示词工程专家帮忙改进，做的更准确)
## 参考
- https://github.com/pola-rs/polars
- https://github.com/TA-Lib/ta-lib
- https://github.com/twopirllc/pandas-ta
- https://github.com/bukosabino/ta
- https://github.com/peerchemist/finta
- https://github.com/wukan1986/ta_cn
- https://support.worldquantbrain.com/hc/en-us/community/posts/20278408956439-从价量看技术指标总结-Technical-Indicator-