Data Docking package
Project description
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 aspostgresql+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: 1906321518@qq.com
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