Writing to MySQL database with pandas using SQLAlchemy, to_sql

Question

trying to write pandas dataframe to MySQL table using to_sql. Previously been using flavor='mysql', however it will be depreciated in the future and wanted to start the transition to using SQLAlchemy engine.

sample code:

import pandas as pd
import mysql.connector
from sqlalchemy import create_engine

engine = create_engine('mysql+mysqlconnector://[user]:[pass]@[host]:[port]/[schema]', echo=False)
cnx = engine.raw_connection()
data = pd.read_sql('SELECT * FROM sample_table', cnx)
data.to_sql(name='sample_table2', con=cnx, if_exists = 'append', index=False)

The read works fine but the to_sql has an error:

DatabaseError: Execution failed on sql 'SELECT name FROM sqlite_master WHERE type='table' AND name=?;': Wrong number of arguments during string formatting

Why does it look like it is trying to use sqlite? What is the correct use of a sqlalchemy connection with mysql and specifically mysql.connector?

I also tried passing the engine in as the connection as well, and that gave me an error referencing no cursor object.

data.to_sql(name='sample_table2', con=engine, if_exists = 'append', index=False)
>>AttributeError: 'Engine' object has no attribute 'cursor'

Answer 1

Using the engine in place of the raw_connection() worked:

import pandas as pd
import mysql.connector
from sqlalchemy import create_engine

engine = create_engine('mysql+mysqlconnector://[user]:[pass]@[host]:[port]/[schema]', echo=False)
data.to_sql(name='sample_table2', con=engine, if_exists = 'append', index=False)

Not clear on why when I tried this yesterday it gave me the earlier error.

Answer 2

Alternatively, use pymysql package...

import pymysql
from sqlalchemy import create_engine
cnx = create_engine('mysql+pymysql://[user]:[pass]@[host]:[port]/[schema]', echo=False)

data = pd.read_sql('SELECT * FROM sample_table', cnx)
data.to_sql(name='sample_table2', con=cnx, if_exists = 'append', index=False)

Answer 3

Using pymysql and sqlalchemy, this works for Pandas v0.22:

import pandas as pd
import pymysql
from sqlalchemy import create_engine

user = 'yourUserName'
passw = 'password'
host =  'hostName'  # either localhost or ip e.g. '172.17.0.2' or hostname address 
port = 3306 
database = 'dataBaseName'

mydb = create_engine('mysql+pymysql://' + user + ':' + passw + '@' + host + ':' + str(port) + '/' + database , echo=False)

directory = r'directoryLocation'  # path of csv file
csvFileName = 'something.csv'

df = pd.read_csv(os.path.join(directory, csvFileName ))

df.to_sql(name=csvFileName[:-4], con=mydb, if_exists = 'replace', index=False)

"""
if_exists: {'fail', 'replace', 'append'}, default 'fail'
     fail: If table exists, do nothing.
     replace: If table exists, drop it, recreate it, and insert data.
     append: If table exists, insert data. Create if does not exist.
"""

Answer 4

I know in the title of the question is included the word SQLAlchemy, however I see in the questions and answers the need to import pymysql or mysql.connector, and also is possible to do the job with pymysql, withouth calling SQLAlchemy.

import pymysql
user = 'root'
passw = 'my-secret-pw-for-mysql-12ud' # In previous posts variable "pass"
host =  '172.17.0.2'
port = 3306

database = 'sample_table' # In previous posts similar to "schema"

conn = pymysql.connect(host=host,
                       port=port,
                       user=user, 
                       passwd=passw,  
                       db=database)

data.to_sql(name=database, con=conn, if_exists = 'append', index=False, flavor = 'mysql')

I think this solution could be good althought it is not using SQLAlchemy.