diff --git a/src/python/__init__.py b/src/python/__init__.py index 0461de7..f4ff59e 100644 --- a/src/python/__init__.py +++ b/src/python/__init__.py @@ -1,6 +1,6 @@ """python package. -Python 代码 +Python code """ from functools import partial @@ -9,21 +9,21 @@ from bigmodule import I # metadata -# 模块作者 -author = "BigQuant" -# 模块分类 -category = "通用" -# 模块显示名 -friendly_name = "Python函数" -# 文档地址, optional -doc_url = "https://bigquant.com/wiki/" -# 是否自动缓存结果 +# Module author +author = "AFE" +# Module category +category = "General" +# Module display name +friendly_name = "Python function" +# Documentation URL, optional +doc_url = "wiki/" +# Whether to automatically cache results cacheable = True DEFAULT_RUN = """def bigquant_run(input_1, input_2, input_3): - # Python 代码入口函数,input_1/2/3 对应三个输入端,data_1/2/3 对应三个输出端 - # 示例代码如下。在这里编写您的代码 + # Python code entry function, input_1/2/3 correspond to three input ports, data_1/2/3 correspond to three output ports + # Sample code is as follows. Write your code here import dai @@ -34,27 +34,27 @@ """ DEFAULT_POST_RUN = """def bigquant_run(outputs): - # 后处理函数,可选。输入是主函数的输出,可以在这里对数据做处理,或者返回更友好的outputs数据格式。此函数输出不会被缓存。 + # Post-processing function, optional. The input is the output of the main function, and you can process the data here or return a more user-friendly outputs data format. The output of this function will not be cached. return outputs """ def run( - run: I.code("主函数,返回dict对象", I.code_python, default=DEFAULT_RUN, specific_type_name="函数", auto_complete_type="python"), - do_run: I.bool("运行主函数,如果不运行主函数,将通过 data_1 返回函数 partial(run, input_*=input_*)") = True, + run: I.code("Main function, returns a dict object", I.code_python, default=DEFAULT_RUN, specific_type_name="function", auto_complete_type="python"), + do_run: I.bool("Run the main function, if not running the main function, it will return the function partial(run, input_*=input_*)") = True, post_run_outputs_: I.code( - "后处理函数,输入是主函数的输出,此函数输出不会被缓存", I.code_python, default=DEFAULT_POST_RUN, specific_type_name="函数", auto_complete_type="python" + "Post-processing function, input is the output of the main function, this function's output will not be cached", I.code_python, default=DEFAULT_POST_RUN, specific_type_name="function", auto_complete_type="python" ) = None, - input_1: I.port("输入1,传入到函数的参数 input_1", optional=True) = None, - input_2: I.port("输入2,传入到函数的参数 input_2", optional=True) = None, - input_3: I.port("输入3,传入到函数的参数 input_3", optional=True) = None, + input_1: I.port("Input 1, passed as parameter input_1 to the function", optional=True) = None, + input_2: I.port("Input 2, passed as parameter input_2 to the function", optional=True) = None, + input_3: I.port("Input 3, passed as parameter input_3 to the function", optional=True) = None, m_meta_kwargs=None, ) -> [ - I.port("输出1,对应函数输出的 data_1", "data_1", optional=True), - I.port("输出2,对应函数输出的 data_2", "data_2", optional=True), - I.port("输出3,对应函数输出的 data_3", "data_3", optional=True), + I.port("Output 1, corresponding to the function's output data_1", "data_1", optional=True), + I.port("Output 2, corresponding to the function's output data_2", "data_2", optional=True), + I.port("Output 3, corresponding to the function's output data_3", "data_3", optional=True), ]: - """执行任意Python代码,支持缓存加速。""" + """Execute arbitrary Python code with support for cache acceleration.""" if do_run: result = run(input_1, input_2, input_3)

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