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Reproducible Example

import dask.dataframe as dd

engine = create_engine("mssql+pyodbc://{user}:{pw}@{sv}:1433/{db}?driver=ODBC+DRIVER+17+for+SQL+Server"
                       .format(user="sa",
                               pw="sa",
                               db="table",
                               sv='server.com'), pool_pre_ping=True)

# Get the list of CSV files in the folder
csv_files = [f for f in os.listdir(dir_folder) if f.endswith('.csv')]

# Loop through the CSV files in the folder
for file in csv_files:
    # Read the CSV file into a Dask DataFrame
    df = dd.read_csv(f'{dir_folder}/{file}', usecols = cols, dtype = converters)

    # Fill empty rows with 0
    df = df.fillna(0)

    # Rename the columns
    df = df.rename(columns = new_column_names)

    # Write the DataFrame to the SQL table
    df.to_sql(table, engine, if_exists='append', index=False)

Issue Description

Issue related to connection, but as far as I know, I need t create the connection and send it through to_sql.

Pandas BUG: Cannot connect to sql

Expected Behavior

It supposed to connect the database and load the dataframe

Installed Versions

python : 3.10.4.final.0 pandas : 1.4.2

Comment From: phofl

Can you post in #40686?

Comment From: jbrockmendel

isnt this a dask issue?

Comment From: leo-schick

@jbrockmendel no, it is a issue with pandas not supporting SQLAlchemy>=2.0 yet

Comment From: jlonge4

@Edimo05 @phofl does this still exist?

Comment From: phofl

Dask only supports strings as uri, no engines. So this works as expected

Comment From: jlonge4

@phofl thanks! I dug through and couldn't think of a single reason why not so that works 😂