Develop Reference

How to Implement Natural Join in Python without using Pandas

Should be done using single function
Shouldn't use Pandas or merge function or any other inbuilt database libraries

You can use native driver like psycopg2 for postgres https://www.psycopg.org/docs/usage.html
import psycopg2
# Connect to an existing database
conn = psycopg2.connect("dbname=test user=postgres")
cur = conn.cursor()
# Query the database and obtain data as Python objects
cur.execute("""
SELECT * FROM test t
left join test1 t1 on (t.t1_id = t1.id);
""")
fetched_rows = cur.fetchall()
# Make the changes to the database persistent
conn.commit()
# Close communication with the database
cur.close()
conn.close()

MySQL connector with Python: getting data by field name

I have to retrieve data from a database. Right now i am using the following code:
import mysql.connector
connection = mysql.connector.connect(user, password, host, database)
cursor = connection.cursor()
cursor.execute(*Query*)
data = cursor.fetchall()
name = data[0][0]
surname = data[0][1]
I would need to access the data by field name instead of raw indexes. For instance something like that
name = data[0]['name']
surname = data[0]['surname']
Thanks

One option is to use MySQLdb. Then you can change:
cursor = connection.cursor()
To:
cursor = connection.cursor(MySQLdb.cursors.DictCursor)
and access the values by field names instead indexes.

According to mysql-connector-python documentation, there are two ways to achieve this.
Manually:
cursor = cnx.cursor()
cursor.execute(...)
row = dict(zip(cursor.column_names, cursor.fetchone()))
With MySQLCursorDict class:
cursor = cnx.cursor(dictionary=True)

Insert into with condition

I'm working with python and using pymysql library and i want to write a query that insert an array in a line where a column has some special value.
For example insert 'hi' into a column where user_id is 22
for that query i write this code
from pymysql import *
chat_id = 22
user_first_name = "hi"
db = connect(host="localhost", port=3306, user="root", passwd="",
db='support',charset='utf8')
cursor = db.cursor()
cursor.execute("""INSERT INTO users user_firstname VALUE %s WHERE user_id is
%s""",(user_first_name, chat_id))
db.commit()
how should i write this query in correct form?

If I'm undertanding, correctly, rather than an INSERT INTO, it seems you need an UPDATE:
cursor.execute("""UPDATE users SET user_firstname='%s' WHERE user_id=%s""",(user_first_name, chat_id))

Francisco is right though. If you have a user_id already, then an UPDATE should be used to change the value of and existing record. The INSERT command, creates a new record.

SQLite Python Blaze - Attempting to create a table after dropping a table of same name returns old schema

I am trying to work out why the schema of a dropped table returns when I attempt to create a table using a different set of column names?
After dropping the table, I can confirm in an SQLite explorer that the table has disappeared. Once trying to load the new file via ODO it then returns an error "Column names of incoming data don't match column names of existing SQL table names in SQL table". Then I can see the same table is re-created in the database, using the previously dropped schema! I attempted a VACUUM statement after dropping the table but still same issue.
I can create the table fine using a different table name, however totally confused as to why I can't use the previously dropped table name I want to use?
import sqlite3
import pandas as pd
from odo import odo, discover, resource, dshape
conn = sqlite3.connect(dbfile)
c = conn.cursor()
c.execute("DROP TABLE <table1>")
c.execute("VACUUM")
importfile = pd.read_csv(csvfile)
odo(importfile,'sqlite:///<db_path>::<table1'>)
ValueError: Column names of incoming data don't match column names of existing SQL table Names in SQL table:

import sqlite3
import pandas as pd
from odo import odo, discover, resource, dshape
conn = sqlite3.connect('test.db')
cursor = conn.cursor();
table = """ CREATE TABLE IF NOT EXISTS TABLE1 (
id integer PRIMARY KEY,
name text NOT NULL
); """;
cursor.execute(table);
conn.commit(); # Save table into database.
cursor.execute(''' DROP TABLE TABLE1 ''');
conn.commit(); # Save that table has been dropped.
cursor.execute(table);
conn.commit(); # Save that table has been created.
conn.close();

List names of all available MS SQL databases on server using python

Trying to list the names of the databases on a remote MS SQL server using Python (Just like the Object Explorer in MS SQL Server Management Studio).
Current solution: The required query is SELECT name FROM sys.databases;. So current solution is using SQLAlchemy and Pandas, which works fine as below.
import pandas
from sqlalchemy import create_engine
#database='master'
engine = create_engine('mssql+pymssql://user:password#server:port/master')
query = "select name FROM sys.databases;"
data = pandas.read_sql(query, engine)
output:
name
0 master
1 tempdb
2 model
3 msdb
Question: How to list the names of the databases on the server using
SQLAlchemy's inspect(engine) similar to listing table names under a database? Or any simpler way without importing Pandas?
from sqlalchemy import inspect
#trial 1: with no database name
engine = create_engine('mssql+pymssql://user:password#server:port')
#this engine not have DB name
inspector = inspect(engine)
inspector.get_table_names() #returns []
inspector.get_schema_names() #returns [u'dbo', u'guest',...,u'INFORMATION_SCHEMA']
#trial 2: with database name 'master', same result
engine = create_engine('mssql+pymssql://user:password#server:port/master')
inspector = inspect(engine)
inspector.get_table_names() #returns []
inspector.get_schema_names() #returns [u'dbo', u'guest',...,u'INFORMATION_SCHEMA']

If all you really want to do is avoid importing pandas then the following works fine for me:
from sqlalchemy import create_engine
engine = create_engine('mssql+pymssql://sa:saPassword#localhost:52865/myDb')
conn = engine.connect()
rows = conn.execute("select name FROM sys.databases;")
for row in rows:
print(row["name"])
producing
master
tempdb
model
msdb
myDb

It is also possible to obtain tables from a specific scheme with execute the single query with the driver below: DB-API interface to Microsoft SQL Server for Python.
pip install pymssql
import pymssql
# Connect to the database
conn =
pymssql.connect(server='127.0.0.1',user='root',password='root',database='my_database')
# Create a Cursor object
cur = conn.cursor()
# Execute the query: To get the name of the tables from my_database
cur.execute("select table_name from information_schema.tables") # where table_schema = 'tableowner'
for row in cur.fetchall():
# Read and print tables
for row in cur.fetchall():
print(row[0])
output:
my_table_name_1
my_table_name_2
my_table_name_3
...
my_table_name_x

I believe the following snippet will list the names of the available databases on whatever server you choose to connect to. This will return a JSON object that will be displayed in your browser. This question is a bit old, but I hope this helps anyone curious who stops by.
from flask import Flask, request
from flask_restful import Resource, Api
from sqlalchemy import create_engine, inspect
from flask_jsonpify import jsonify
engine = create_engine('mssql+pymssql://user:password#server:port/master')
class AllTables(Resource):
def get(self):
conn = engine.connect()
inspector = inspect(conn)
tableList = [item for item in inspector.get_table_names()]
result = {'data': tableList}
return jsonify(result)
api.add_resource(AllTables, '/alltables')
app.run(port='8080')

here is another solution which fetch row by row:
import pymssql
connect = pymssql.connect(server, user, password, database)
cursor = connect.cursor(as_dict=True)
row = cursor.fetchone()
while row:
for r in row.items():
print r[0], r[1]
row = cursor.fetchone()