This library is used to read or write data in Postgres, MongoDB (Only read) or Google Sheets
Project description
Overview
Justogres is a connector to comunicate pandas.DataFrame objects with postgres database
Quick start
for more details review documentation
Install or upgrade package
install:
pip install justogres
upgrade:
pip install justogres --upgrade
Init module
from justogres import clientPsql
psql = clientPsql(
host = "<your host>",
user = "<your user>",
password = "<your password>",
db_name = "<your database name>",
)
Insert data into postgres
import pandas as pd
example_df = pd.DataFrame(data=example_data)
psql.insert(
example_df,
table_name=<your table name>, #if doesn't exist table, will be created
schema=<your schema name>, #should be created previously
#optional
chunksize=<your chunksize to load (default: 1000)>,
column_types={<name_column_df>:<data_type postgres>})# if not declare column types, will be assigned automatically
Read table of postgres
we have 2 ways to read DB, both return pandas.DataFrame object but its main difference is the type of data that is assigned to the columns of the dataframe
1. use exec_query() -> all columns are defines as object (string datatype in pandas)
query_example_to_read="""SELECT *
FROM schema_name.table_name;"""
df = psql.exec_query(
query_example_to_read,
#optional
chunksize=<your chunksize to load (default: 1000)>
)
2. use read_with_pandas() -> columns are defined with datatype declare for each column into DB
query_example_to_read="""SELECT *
FROM schema_name.table_name;"""
df = psql.read_with_pandas(
query_example_to_read,
#optional
**kwargs=<all attributes we can use with pandas.read_sql()>
)
for more info of pandas.read_sql()
Execute sql queries
this method doesn't return anything
query_example="""DELETE
FROM schema_name.table_name
WHERE column_name='value';"""
psql.exec_query(
query_example,
#optional
chunksize=<your chunksize to load (default: 1000)>
)
SpreadSheets Module
Write DataFrame in Worksheet
from justogres import SpreadSheets
spread_sheet_client = SpreadSheets("credentials.json")
spreadsheet_id = '1SVZDYBw17S1XeRNBW08YA7i29mOfFlGmmF6EWKH84bk'
worksheet_name = 'Result'
spread_sheet_client.append_dataframe(data_frame ,spreadsheet_id, worksheet_name)
Read DataFrame in Worksheet
from justogres import SpreadSheets
spread_sheet_client = SpreadSheets("credentials.json")
spreadsheet_id = '1SVZDYBw17S1XeRNBW08YA7i29mOfFlGmmF6EWKH84bk'
worksheet_name = 'Result'
spread_sheet_client.worksheet_to_dataframe(spreadsheet_id, worksheet_name)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
justogres-3.0.11.tar.gz
(7.4 kB
view details)
Built Distribution
File details
Details for the file justogres-3.0.11.tar.gz
.
File metadata
- Download URL: justogres-3.0.11.tar.gz
- Upload date:
- Size: 7.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.9.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3a2e8dc821346939968b002eaf3f02467201f6300c0472313bfcd50e858d9905 |
|
MD5 | 0e50e674738aa09bfc5b0f53d6d24106 |
|
BLAKE2b-256 | edf5cf6f7589a13d357a4c6b03545f8257184e4d8610799127e9016109cb2e14 |
File details
Details for the file justogres-3.0.11-py3-none-any.whl
.
File metadata
- Download URL: justogres-3.0.11-py3-none-any.whl
- Upload date:
- Size: 7.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.9.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 790cc0874dd171221e181da0a1b67a81b5656f0c24e25462cbae4d1c6816df9c |
|
MD5 | d5712e4dda7489542c45d319d2e632fa |
|
BLAKE2b-256 | 073435245d705707711bbfd9c845a942a9e9d0982f02ffda62788976c49b377a |