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# 本代码由可视化策略环境自动生成 2018年8月3日 23:53
# 本代码单元只能在可视化模式下编辑。您也可以拷贝代码，粘贴到新建的代码单元或者策略，然后修改。


m4 = M.use_datasource.v1(
    datasource_id='bar1d_CN_STOCK_A',
    start_date='2018-01-01',
    end_date='2018-02-01'
)

# 修改数据列名
def m19_run_bigquant_run(input_ds, columns, keep_old_columns):
    # 解析列映射为dict, TODO: 验证输入是否有效
    columns = dict(c.split(':') for c in columns.split('|'))
    print('列名映射：', columns)
    # 输出数据源
    dataset_ds = DataSource()
    output_store = dataset_ds.open_df_store()

    for key, df in input_ds.iter_df():
        old_column_set = set(df.columns)
        for old_col, new_col in columns.items():
            if old_col not in old_column_set:
                print('警告：列 %s 不存在' % old_col)
        if keep_old_columns:
            for old_col, new_col in columns.items():
                if old_col in old_column_set:
                    df[new_col] = df[old_col]
        else:
            df.columns = [columns.get(c, c) for c in df.columns]
        df.to_hdf(output_store, key)
        row_count = len(df)
        print('%s: %s' % (key, len(df)))

    dataset_ds.close_df_store()
    return Outputs(data=dataset_ds)

# 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。
def m19_post_run_bigquant_run(outputs):
    return outputs

m19 = M.cached.v3(
    input_1=m4.data,
    run=m19_run_bigquant_run,
    post_run=m19_post_run_bigquant_run,
    input_ports='input_ds',
    params="""{
    'columns': 'deal_number:new_deal_number|close:new_close',
    'keep_old_columns': true
}
""",
    output_ports='data'
)

m2 = M.rename_columns.v5(
    input_ds=m4.data,
    columns='deal_number:new_deal_number|close:new_close',
    keep_old_columns=True
)

[2018-08-03 23:51:05.884144] INFO: bigquant: use_datasource.v1 开始运行..
[2018-08-03 23:51:06.072156] INFO: bigquant: 命中缓存
[2018-08-03 23:51:06.082901] INFO: bigquant: use_datasource.v1 运行完成[0.198757s].
[2018-08-03 23:51:06.097946] INFO: bigquant: rename_columns.v5 开始运行..
列名映射： {'close': 'new_close', 'deal_number': 'new_deal_number'}
/data: 80837
[2018-08-03 23:51:06.563193] INFO: bigquant: rename_columns.v5 运行完成[0.465224s].