Ready to get started?

Download a free trial of the SurveyMonkey Connector to get started:

 Download Now

Learn more:

SurveyMonkey Icon SurveyMonkey Python Connector

Python Connector Libraries for SurveyMonkey Data Connectivity. Integrate SurveyMonkey with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

Use SQLAlchemy ORMs to Access SurveyMonkey Data in Python



The CData Python Connector for SurveyMonkey enables you to create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of SurveyMonkey data.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems effectively. With the CData Python Connector for SurveyMonkey and the SQLAlchemy toolkit, you can build SurveyMonkey-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to SurveyMonkey data to query SurveyMonkey data.

With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live SurveyMonkey data in Python. When you issue complex SQL queries from SurveyMonkey, the CData Connector pushes supported SQL operations, like filters and aggregations, directly to SurveyMonkey and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to SurveyMonkey Data

Connecting to SurveyMonkey data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

SurveyMonkey uses the OAuth 2 authentication standard. See the Getting Started section in the help documentation for a guide.

Follow the procedure below to install SQLAlchemy and start accessing SurveyMonkey through Python objects.

Install Required Modules

Use the pip utility to install the SQLAlchemy toolkit and SQLAlchemy ORM package:

pip install sqlalchemy pip install sqlalchemy.orm

Be sure to import the appropriate modules:

from sqlalchemy import create_engine, String, Column from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker

Model SurveyMonkey Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with SurveyMonkey data.

NOTE: Users should URL encode the any connection string properties that include special characters. For more information, refer to the SQL Alchemy documentation.

engine = create_engine("surveymonkey:///?OAuthClientId=MyOAuthClientId&OAuthClientSecret=MyOAuthClientSecret&CallbackURL=http://localhost:portNumber&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Declare a Mapping Class for SurveyMonkey Data

After establishing the connection, declare a mapping class for the table you wish to model in the ORM (in this article, we will model the MySurvey_Responses table). Use the sqlalchemy.ext.declarative.declarative_base function and create a new class with some or all of the fields (columns) defined.

base = declarative_base() class MySurvey_Responses(base): __tablename__ = "MySurvey_Responses" RespondentId = Column(String,primary_key=True) ChoiceId = Column(String) ...

Query SurveyMonkey Data

With the mapping class prepared, you can use a session object to query the data source. After binding the Engine to the session, provide the mapping class to the session query method.

Using the query Method

engine = create_engine("surveymonkey:///?OAuthClientId=MyOAuthClientId&OAuthClientSecret=MyOAuthClientSecret&CallbackURL=http://localhost:portNumber&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt") factory = sessionmaker(bind=engine) session = factory() for instance in session.query(MySurvey_Responses).filter_by(ChoiceText="blue"): print("RespondentId: ", instance.RespondentId) print("ChoiceId: ", instance.ChoiceId) print("---------")

Alternatively, you can use the execute method with the appropriate table object. The code below works with an active session.

Using the execute Method

MySurvey_Responses_table = MySurvey_Responses.metadata.tables["MySurvey_Responses"] for instance in session.execute(MySurvey_Responses_table.select().where(MySurvey_Responses_table.c.ChoiceText == "blue")): print("RespondentId: ", instance.RespondentId) print("ChoiceId: ", instance.ChoiceId) print("---------")

For examples of more complex querying, including JOINs, aggregations, limits, and more, refer to the Help documentation for the extension.

Free Trial & More Information

Download a free, 30-day trial of the SurveyMonkey Python Connector to start building Python apps and scripts with connectivity to SurveyMonkey data. Reach out to our Support Team if you have any questions.