TA-Lib，全称“Technical Analysis Library”, 即技术分析库，是 Python 金融量化的高级库，涵盖了 150 多种股票、期货交易软件中常用的技术分析指标，如 MACD、RSI、KDJ、动量指标、布林带等等。
TA-Lib 可分为 10 个子板块：
- Overlap Studies(重叠指标)
- Momentum Indicators(动量指标)
- Volume Indicators(交易量指标)
- Cycle Indicators(周期指标)
- Price Transform(价格变换)
- Volatility Indicators(波动率指标)
- Pattern Recognition(模式识别)
- Statistic Functions(统计函数)
- Math Transform(数学变换)
- Math Operators(数学运算)
本文介绍通过 Funcraft 的模板将 Python 量化交易库 TA-lib 移植到函数计算。
依赖工具
本项目是在 MacOS 下开发的，涉及到的工具是平台无关的，对于 Linux 和 Windows 桌面系统应该也同样适用。在开始本例之前请确保如下工具已经正确的安装，更新到最新版本，并进行正确的配置。
对于 MacOS 用户可以使用 homebrew 进行安装：
brew cask install docker
brew tap vangie/formula
brew install fun
Windows 和 Linux 用户安装请参考：
https://github.com/aliyun/fun/blob/master/docs/usage/installation.md
安装好后，记得先执行 fun config 初始化一下配置。
初始化
使用 fun init 命令可以快捷地将本模板项目初始化到本地。
fun init vangie/ta-lib-example
安装依赖
$ fun install
using template: template.yml
start installing function dependencies without docker
building ta-lib-example/ta-lib-example
Funfile exist, Fun will use container to build forcely
Step 1/5 : FROM registry.cn-beijing.aliyuncs.com/aliyunfc/runtime-python3.6:build-1.7.7
---> 373f5819463b
Step 2/5 : COPY ta-lib-0.4.0-src.tar.gz /tmp
---> Using cache
---> 64f9f85112b4
Step 3/5 : RUN cd /tmp; tar -xzf ta-lib-0.4.0-src.tar.gz
---> Using cache
---> 9f2d3f836de9
Step 4/5 : RUN cd /tmp/ta-lib/ ; ./configure --prefix=/code/.fun/root/usr ; make ; make install
---> Using cache
---> 7725836973d4
Step 5/5 : RUN TA_LIBRARY_PATH=/code/.fun/root/usr/lib TA_INCLUDE_PATH=/code/.fun/root/usr/include fun-install pip install TA-Lib
---> Using cache
---> a338e71895b7
sha256:a338e71895b74a0be98278f35da38c48545f04a54e19ec9e689bab976265350b
Successfully built a338e71895b7
Successfully tagged fun-cache-d4ac1d89-5b75-4429-933a-2260e2f7fbec:latest
copying function artifact to /Users/vangie/Workspace/ta-lib-example/{{ projectName }}
Install Success
Tips for next step
======================
* Invoke Event Function: fun local invoke
* Invoke Http Function: fun local start
* Build Http Function: fun build
* Deploy Resources: fun deploy
本地调用
$ fun local invoke
using template: template.yml
Missing invokeName argument, Fun will use the first function ta-lib-example/ta-lib-example as invokeName
skip pulling image aliyunfc/runtime-python3.6:1.7.7...
FunctionCompute python3 runtime inited.
FC Invoke Start RequestId: dc1495b2-13ec-4ecf-a2dc-a0026d82651a
FC Invoke End RequestId: dc1495b2-13ec-4ecf-a2dc-a0026d82651a
[
"HT_DCPERIOD",
"HT_DCPHASE",
"HT_PHASOR",
"HT_SINE",
"HT_TRENDMODE"
]
RequestId: dc1495b2-13ec-4ecf-a2dc-a0026d82651a Billed Duration: 350 ms Memory Size: 1998 MB Max Memory Used: 34 MB
部署
$ fun deploy
using template: template.yml
using region: cn-shanghai
using accountId: ***********4733
using accessKeyId: ***********EUz3
using timeout: 600
Waiting for service ta-lib-example to be deployed...
Waiting for function ta-lib-example to be deployed...
Waiting for packaging function ta-lib-example code...
The function ta-lib-example has been packaged. A total of 39 files files were compressed and the final size was 3.23 MB
function ta-lib-example deploy success
service ta-lib-example deploy success
执行
$ fun invoke
using template: template.yml
Missing invokeName argument, Fun will use the first function ta-lib-example/ta-lib-example as invokeName
========= FC invoke Logs begin =========
FC Invoke Start RequestId: 83e23eba-02b4-4380-bbca-daec6856bf4a
FC Invoke End RequestId: 83e23eba-02b4-4380-bbca-daec6856bf4a
Duration: 213.86 ms, Billed Duration: 300 ms, Memory Size: 128 MB, Max Memory Used: 43.50 MB
========= FC invoke Logs end =========
FC Invoke Result:
[
"HT_DCPERIOD",
"HT_DCPHASE",
"HT_PHASOR",
"HT_SINE",
"HT_TRENDMODE"
]
参考阅读
“阿里巴巴云原生关注微服务、Serverless、容器、Service Mesh 等技术领域、聚焦云原生流行技术趋势、云原生大规模的落地实践，做最懂云原生开发者的技术圈。”