How to get SalesForce data to Python Panda dataframes - python-3.x

Question

Currently we are taking SalesForce data in to CSV file and reading this CSV file in Pandas using read_csv, to_csv methods. Do we have any other way to get data from SalesForce to pandas dataframe.

Answer 1

With Python - you can download a package called Simple Salesforce and write SOQL queries to return data
https://github.com/simple-salesforce/simple-salesforce
Here's an example of how to do this:
from simple_salesforce import Salesforce
sf = Salesforce(username='<enter username>', password='<enter password>',
security_token = '<enter your access token from your profile>')
a_query= pd.DataFrame(sf.query(
"SELECT Name, CreatedDate FROM User")['records'])

Answer 2

In my case, to display the information as a dataframe I had to use the following code:
# Import libraries
import simple_salesforce as ssf, pandas
# Create the connection
session_id, instance = ssf.SalesforceLogin(username='<username>', password='<password>', security_token='<token>', sandbox=False)
sf_ = ssf.Salesforce(instance=instance, session_id=session_id)
# Query to execute
sql_code = "SELECT id, name FROM main_table"
# Store query result as dataframe
information = sf_.query(query= sql_code)
table = pandas.DataFrame(information['records']).drop(columns='attributes')

Answer 3

Adding up to the original answer,
the function below is also suitable for simple joins.
def sf_results_to_dataframe(results, drop_index=True) -> pd.DataFrame:
df = pd.DataFrame(results['records'])
df.drop('attributes', axis=1, inplace=True) # clean up from technical info
df.set_index('Id', drop=drop_index, inplace=True)
for table in ['Account', 'Contact', 'Lead', 'Opportunity']:
if table in results['records'][0].keys(): # detect JOIN
local_keys = list(results['records'][0][table].keys()) # keys from the joined table
if 'attributes' in local_keys:
local_keys.remove('attributes')
global_keys = [table + key for key in local_keys] # name for the fields in the output table
# fields of the joined table and the record index
table_records = [{'Id': record['Id'],
**{global_key:record[table][local_key] for global_key, local_key in zip(global_keys, local_keys)}}
for record in results['records']]
df_extra = pd.DataFrame(table_records)
df_extra.set_index('Id', drop=True, inplace=True) # match index
df.drop(table, axis=1, inplace=True) # drop duplicated info
df = df.merge(df_extra, left_index=True, right_index=True) # merge on index
return df
Example:
import pandas as pd
from simple_salesforce import Salesforce
SALESFORCE_EMAIL = '...'
SALESFORCE_TOKEN = '...'
SALESFORCE_PASSWORD = '...'
sf = Salesforce(username=SALESFORCE_EMAIL, password=SALESFORCE_PASSWORD, security_token=SALESFORCE_TOKEN)
query = """SELECT Id, Name, Account.Name
FROM Contact
LIMIT 1
"""
results = sf.query(query)
df = sf_results_to_dataframe(results)