Reputation: 1691
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'
Upvotes: 59
Views: 106920
Reputation: 1691
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.
Upvotes: 81
Reputation: 3479
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.
"""
Upvotes: 8
Reputation: 2816
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.
Upvotes: 0
Reputation: 15537
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)
Upvotes: 15