Skip to content

HiCiChlid/link2postgresql

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

9 Commits
 
 
 
 
 
 
 
 

Repository files navigation

link2postgresql

This is a collection of methods for uploading or downloading data with different formats.

  1. Using SQL to manage DB
  2. Spark DataFrame <-> DB
  3. Pandas DataFrame <-> DB
  4. Excel/csv/json -->DB
  • Automatically add an ID column when uploading

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

What things you need to install the software and how to install them

spark
jdk
hadoop
PostgreSQL

# python package
pip install psycopg2
pip install pandas
pip install numpy
pip install findspark
pip install pyspark
pip install pyarrow
pip install geoalchemy2
pip install geopandas

Installing

A step by step series of examples that tell you how to get a development env running

Say what the step will be Step1:

copy 'link2postgresql' folder and paste it into 'python/Lib/site-packages'

Step2: open a terminal or command to open a python having a test.

from link2postgresql import Link2postgresql as link

End with an example of getting some data out of the system or using it for a little demo

Running the tests

Explain how to run the automated tests for this system.

initialization

aim_link=link(user="postgres", password="1234", ip="localhost", port="5432",database="sample_database")

table2spark_df

Download table from PostgreSQL database as spark dataframe (transformation).

cmd="select * from sample_table where id=1"
pandas_df=aim_link.table2spark_df(table_name="sample_table",cmd=cmd)

table2spark_df_slow

Download table from PostgreSQL database as spark dataframe (action). All the data in the table are stored in the memory.

cmd="select * from sample_table where id=1"
pandas_df=aim_link.table2spark_df_slow(table_name="sample_table",cmd=cmd)

spark_df2table

Upload spark dataframe into PostgreSQL database. mode is the same as in JDBC

aim_link.spark_df2table(df=spark_df,table_name='sample_table',mode="append"):

execute

Using sql to control the database. eg: delete the records with id equal to 1 in sample_table.

aim_link.execute("delete from sample_table where id=1;")

fetch_execute

Download the data (String) from DB

cmd="select * from sample_table;"
temp=aim_link.fetch_execute(cmd=cmd)

Download the data and title (Tuple) from DB

cmd="select * from sample_table;"
temp=aim_link.fetch_execute(cmd=cmd,title=True)
data=temp[0]
title=temp[1]

tablemaxcount

Inner-class function. Getting the max value of id from the defined table and columns.

def tablemaxcount(self,id_name,table_name):
    ......

table2pandas_df

Download table from PostgreSQL database as spark dataframe. All the data in the table are stored in the memory.

cmd="select * from sample_table where id=1"
pandas_df=aim_link.table2pandas_df(table_name='sample_table',cmd=cmd)

table2pandas_df_slow

Using JDBC to download to spark dataframe and then transform it into pandas dataframe. Pyarrow is used to accelerate the action.

cmd="select * from sample_table where id=1"
pandas_df=aim_link.table2pandas_df_slow(table_name='sample_table',cmd=cmd)

emptytable

Create a new empty table in PostgreSQL database

schema="(a bigint,b real,c text)"
aim_link.emptytable(table_name='sample_table', schema)

insert_s

Insert values into an extant table. Supporting multiline. the schema is different from the above.

schema="a,b,c"
values="(1,1.0,'1.0'),(2,2.0,'2.0'),(3,3.0,'3.0')"
aim_link.insert_s(table_name='sample_table', schema=schema, values=values)

addgeocolumn

Manually transform a column about wkt1 into geometry.

aim_link.addgeocolumn(table_name='sample_table',wkt_column='wkt_column',geo_type='POINT')

pandas_df2table

upload pandas dataframe to PostgreSQL database.

  1. table_name should not contian uppercase letters!!

  2. if_exists='append': Continuoulsy insert table without wawrnings.

  3. id='True': create a ID column in the first. At the same time, a creasing sequence and a primary key constraint will be created.

  4. clean="True":Special marks in title may casue some errors with a high risk!! So I use 'clean' to fix it.

  5. check="True":single quota marks in the content will also cause error. So set check="True".

aim_link.pandas_df2table(df=pandas_df, table_name='sample_table', if_exists='append', id='True', check="True", clean="True")

pandas_df2table_slow

Using emptytable and insert_s to realize uploading pandas dataframe to Postgresql database. The best advantage: it supports postgis that is geo-information. The coordinate system is 4326. geo_schema:the column label of cooridinate information. It must be in the format of WKT, eg: POINT(113.1 22.3)

aim_link.pandas_df2table_slow(df=pandas_df, table_name='sample_table', geo_schema="geometry", check="Yes"):

pandas_df2table_lite

Inner-class function. it suits for building a lightweight form in DB. The machine will in a high probability be stuck when big data.

def pandas_df2table_lite(self, df, table_name,if_exists='append',clean='False', *args, **kwargs): 
    ......

excel2table

if your original data are clean enough, you can choose it! otherwise, do data clean first

aim_link.excel2table(excelpath='./sample_table.xls',table_name='sample_table', if_exists='fail')

csv2table

if your original data are clean enough, you can choose it! otherwise, do data clean first

aim_link.csv2table(csvpath='./sample_table.csv',table_name='sample_table', if_exists='fail')

json2table

if your original data are clean enough, you can choose it! otherwise, do data clean first

aim_link.json2table(jsonpath='./sample_table.json',table_name='sample_table', if_exists='fail')

Authors

  • GUO Zijian

License

MIT License

Copyright (c) 2018-present GUO ZIJIAN from PolyU

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

Footnotes

  1. https://en.wikipedia.org/wiki/Well-known_text_representation_of_geometry

About

A Python model for linking to PostgreSQL database

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages