I am having trouble uploading a CSV file into a table in MS SQL Server, The CSV file has 25 columns and the header has the same name as table in SQL which also has 25 columns. When I run the script it throws an error
params arg (<class 'list'>) can be only a tuple or a dictionary
What is the best way to import this data into MS SQL? Both the CSV and SQL table have the exact same column names.
Here is the code:
import csv
import pymssql
conn = pymssql.connect(
server="xx.xxx.xx.90",
port = 2433,
user='SQLAdmin',
password='xxxxxxxx',
database='NasrWeb'
)
cursor = conn.cursor()
customer_data = csv.reader('cleanNVG.csv') #25 columns with same header as SQL
for row in customer_data:
cursor.execute('INSERT INTO zzzOracle_Extract([Customer Name]\
,[Customer #]\
,[Account Name]\
,[Identifying Address Flag]\
,[Address1]\
,[Address2]\
,[Address3]\
,[Address4]\
,[City]\
,[County]\
,[State]\
,[Postal Code]\
,[Country]\
,[Category ]\
,[Class]\
,[Reference]\
,[Party Status]\
,[Address Status]\
,[Site Status]\
,[Ship To or Bill To]\
,[Default Warehouse]\
,[Default Order Type]\
,[Default Shipping Method]\
,[Optifacts Customer Number]\
,[Salesperson])''VALUES(%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,)',row)
conn.commit()
cursor.close()
print("Done")
conn.close()
This is what the first rows of the CSV file looks like
You are using csv.reader
incorrectly. The first argument to .reader
is not the path to the CSV file, it is
[an] object which supports the iterator protocol and returns a string each time its __next__()
method is called — file objects and list objects are both suitable.
Hence, according to the example in the documentation, you should be doing something like this:
import csv
with open('cleanNVG.csv', newline='') as csvfile:
customer_data = csv.reader(csvfile)
for row in customer_data:
cursor.execute(sql, tuple(row))
Try d6tstack which has fast pandas to SQL functionality because it uses native DB import commands. It works for Postgres and MYSQL, MS SQL is experimental. Comment or raise an issue if it doesn't work.
import pandas as pd
df = pd.read_csv('cleanNVG.csv')
uri_mssql = 'mssql+pymssql://usr:pwd@localhost/db'
d6tstack.utils.pd_to_mssql(df, uri_mssql, 'table', 'schema') # experimental
It is also useful for importing multiple CSV with data schema changes and/or preprocess with pandas before writing to db, see further down in examples notebook
d6tstack.combine_csv.CombinerCSV(glob.glob('*.csv'),
apply_after_read=apply_fun).to_mssql_combine(uri_psql, 'table')
Check the data types on the table, and the sizes of each field as well. If it is varchar(10) and your data is 20 characters long, it will throw an error.
Also,
Consider building the query dynamically to ensure the number of placeholders matches your table and CSV file format. Then it's just a matter of ensuring your table and CSV file are correct, instead of checking that you typed enough ? placeholders in your code.
The following example assumes
CSV file contains column names in the first line
Connection is already built
File name is test.csv
Table name is MyTable
Python 3
...
with open ('test.csv', 'r') as f:
reader = csv.reader(f)
columns = next(reader)
query = 'insert into MyTable({0}) values ({1})'
query = query.format(','.join(columns), ','.join('?' * len(columns)))
cursor = connection.cursor()
for data in reader:
cursor.execute(query, data)
cursor.commit()
If column names are not included in the file:
...
with open ('test.csv', 'r') as f:
reader = csv.reader(f)
data = next(reader)
query = 'insert into dbo.Test values ({0})'
query = query.format(','.join('?' * len(data)))
cursor = connection.cursor()
cursor.execute(query, data)
for data in reader:
cursor.execute(query, data)
cursor.commit()
Basically, though, your code looks fine. Here is a generic sample.
cur=cnxn.cursor() # Get the cursor
csv_data = csv.reader(file(Samplefile.csv')) # Read the csv
for rows in csv_data: # Iterate through csv
cur.execute("INSERT INTO MyTable(Col1,Col2,Col3,Col4) VALUES (?,?,?,?)",rows)
cnxn.commit()