Python and Snowflake appending new data into an existing table using SQL Alchemy engine is returning current session does not have a current database

Question

I need to append some new data into an existing table on snowflake. I am using sqlalchemy as the engine along with pandas data frame to_sql(). Here is the imports and the script:

import pandas as pd
import os
import snowflake.connector as snowCtx
import getpass
import json
import numpy as np
from datetime import date, datetime
import time
from sqlalchemy import create_engine
from sqlalchemy.dialects import registry
import snowflake.sqlalchemy
from snowflake.connector.pandas_tools import pd_writer
from sqlalchemy.ext.declarative import declarative_base

registry.register('snowflake', 'snowflake.sqlalchemy', 'dialect')

columns_df = pd.DataFrame(data.columns.to_list(), columns={'survey_column_name'})
                        columns_df['survey_id'] = nextval
                        columns_df = columns_df[['survey_id', 'survey_column_name']]
                        columns_df.to_sql('SURVEY_METADATA_COLUMN_NAMES', 
                                         index = False,  
                                         index_label = None, 
                                         con = engine, 
                                         schema = 'PUBLIC', 
                                         if_exists = 'append', 
                                         chunksize = 300,
                                         method = pd_writer)

The error I am getting is as follows:

ProgrammingError: (snowflake.connector.errors.ProgrammingError) 090105 (22000): Cannot perform CREATE

TABLE. This session does not have a current database. Call 'USE DATABASE', or use a qualified name. [SQL:

CREATE TABLE "PUBLIC"."SURVEY_METADATA_COLUMN_NAMES" (

survey_id INTEGER,

survey_column_name TEXT )

]

The connections are as follows:

user = input('Your Snowflake username: ')
password = getpass.getpass('Your Snowflake Password: ')
account = 'MY_ACCOUNT'
conn = snowCtx.connect(
    user=user,
    password=password,
    account=account,
    database='MY_DB',
    schema='PUBLIC',
    warehouse='COMPUTE_WH',
    role='SYSADMIN'
)

engine = create_engine(
    'snowflake://{user}:{password}@{account}/'.format(
        user=user,
        password=password,
        account=account,
        database='MY_DB',
        schema = 'PUBLIC',
        warehouse='COMPUTE_WH',
        role='SYSADMIN',
        cache_column_metadata=True
    )
)

alim1990 · Accepted Answer · 2020-11-24 17:29:09Z

2

I switched into using write_pandas() instead:

success, nchunks, nrows, _ = write_pandas(conn, 
                                          columns_df, 
                                          'SURVEY_METADATA_COLUMN_NAMES', 
                                          chunk_size = 300, 
                                          schema = 'PUBLIC')
                        print(success, nchunks, nrows)
if(success):
   print(filename+' columns uploaded')
else:
   print(filename+' columns were not uploaded')

Which needs pyarrow library, so I installed it using:

pip install pyarrow

I removed all imports related to sqlalchemy and kept the following:

import pandas as pd
import os
import snowflake.connector as snowCtx
import getpass
import json
import numpy as np
from datetime import date, datetime
import time
from snowflake.connector.pandas_tools import write_pandas

answered Nov 24, 2020 at 17:29

alim1990

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1 Comment

Long Luu Over a year ago

A difference between them I think is write_pandas writes to an existing table, while df.to_sql() creates the table on the fly.

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