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Writing to PostgreSQL¶
- Insure PostgreSQL is actually installed on the system,
- There is a database called demo created on the said system
The cell below creates a dataframe that will be stored within postgreSQL
In [8]:
# # Writing to PostgreSQL database # import transport from transport import providers import pandas as pd _data = pd.DataFrame({"name":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]}) pgw = transport.factory.instance(provider=providers.POSTGRESQL,database='demo',table='friends',context='write') pgw.write(_data,if_exists='replace') #-- default is append print (transport.__version__)
2.0.0
Reading from PostgreSQL¶
The cell below reads the data that has been written by the cell above and computes the average age within a PostreSQL (simple query).
- Basic read of the designated table (friends) created above
- Execute an aggregate SQL against the table
NOTE
It is possible to use transport.factory.instance or transport.instance they are the same. It allows the maintainers to know that we used a factory design pattern.
In [6]:
import transport from transport import providers pgr = transport.instance(provider=providers.POSTGRESQL,database='demo',table='friends') _df = pgr.read() _query = 'SELECT COUNT(*) _counts, AVG(age) from friends' _sdf = pgr.read(sql=_query) print (_df) print ('--------- STATISTICS ------------') print (_sdf)
name age 0 James Bond 55 1 Steve Rogers 150 2 Steve Nyemba 44 --------- STATISTICS ------------ _counts avg 0 3 83.0
The cell bellow show the content of an auth_file, in this case if the dataset/table in question is not to be shared then you can use auth_file with information associated with the parameters.
NOTE:
The auth_file is intended to be JSON formatted
In [1]:
{ "host":"klingon.io","port":5432,"username":"me","password":"foobar", "database":"demo","table":"friends" }
Out[1]:
{'host': 'klingon.io',
'port': 5432,
'username': 'me',
'password': 'foobar',
'database': 'demo',
'table': 'friends'}
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