DataDocking 0.0.3

Data Docking package

Data Dock Package

Introduction

This framework is mainly used for data pair amount in big data.

Installation

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

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

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

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: [e-mail]