Metadata-Version: 2.1
Name: DataDocking
Version: 0.0.3
Summary: Data Docking package
Home-page: https://github.com/AlitaIcon/DataDocking
Author: alita
Author-email: 1906321518@qq.com
License: MIT
Project-URL: Documentation, https://github.com/AlitaIcon/DataDocking
Project-URL: Source, https://pypi.org/project/DataDocking/
Description: # Data Dock Package
        
        #### Introduction
        This framework is mainly used for data pair amount in big data.
        
        #### Installation
        ```ini
        pip install DataDocking -i https://pypi.python.org/simple -U
        ```
        
        #### Uage
        1.DataLoadStatic
        - This is used to load static data variables, data variables cannot be modified
        ```python
        from DataDocking import DataLoadStatic
        class DataLoad(DataLoadStatic):
            temp = 20
            press = 30
            
        dl = DataLoad()
        # dl.temp.value --> 20
        # dl.all_fields --> {'temp': 20, 'press': 30}
        ```
        
        2.DataParse
        - Data analysis process, follow common framework usage: set_up() ->  process() -> teardown()
            - set_up: Data preprocessing
            - process: data processing
            - teardown: Data finishing process
        ```python
        from DataDocking import DataParse
        class TempDataParse(DataParse):
            def setup(self):
                pass
        
            def process(self):
                pass
        
            def teardown(self):
                pass
        ```
        
        3.DataSave
        - Data storage, incoming ```sql_url_con```, such as ```postgresql+psycopg2://root:123@127.0.0.1:5432/demo```
        ```python
        from DataDocking import DataSave
        class TempDataSave(DataSave):
            pass
        
        if __name__ == '__main__':
            sql_url_con = 'postgresql+psycopg2://root:123@127.0.0.1:5432/demo'
            tds = TempDataSave()
            db = tds.db(sql_url_con)
            db.query('your sql')
            tds.save('your save sql')
            
            sql_url_cons = [sql_url_con for _ in range(3)]
            dbs = tds.dbs(sql_url_cons) 
            index_db = dbs[0]
            index_db.query('your sql')
            index_db.save('your save sql')
            
        ```
        
        #### Connection
        - author github: https://github.com/AlitaIcon/DataDocking
        
        - more information: 1906321518@qq.com
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
