At first glance, integrating Python with Salesforce looks simple—install a library, connect to an API, and start querying data. But the reality is far more complex. Salesforce’s API structure presents challenges that aren’t immediately obvious.
Developers must navigate polymorphic fields, hierarchical relationships, and varying data formats—such as numeric fields, date/time values, nested JSON, and binary objects—which often require careful transformations for compatibility. On top of that, you’ll need to manage tokens, batch API calls, and optimize workflows for both real-time queries and bulk data migrations. Add in strict rate limits and the complexity of handling both real-time queries and bulk data migrations, and what seemed straightforward can quickly become a time sink.
The Devart Python Connector for Salesforce makes your integration process easier. It simplifies setting up secure, high-performance connections using direct TCP/IP connectivity. With full support for Python DB API 2.0, you can stick to workflows you already know, avoiding unnecessary compatibility issues. Plus, it handles diverse data types seamlessly, so you spend less time fixing errors and more time building something meaningful.
Whether you’re syncing millions of records with the Bulk API or fetching real-time updates via the REST API, this tool helps you handle even the most complex workflows. Instead of struggling with API quirks, you’ll have the confidence to focus on creating smarter, more scalable solutions.”
Table of contents
- Benefits of using Devart Python Connector for Salesforce
- What sets Devart Python Connector apart
- Prerequisites for connecting Python to Salesforce
- How to authenticate Python with Salesforce API
- Querying Salesforce data with Devart Connector
Benefits of using Devart Python Connector for Salesforce
Traditional Python Salesforce integration tools often complicate things with clunky client libraries, tricky API setups, and endless configuration steps that slow everything down. The Devart Python Connector changes the equation, giving developers a straightforward and reliable way to connect Python and Salesforce.
Here’s how the Devart Python Connector makes integration faster, easier, and more effective.
Establish direct TCP/IP connectivity for streamlined performance
Traditional integrations rely on client libraries that add layers of complexity, increase configuration time, and risk version conflicts. The Devart Python Connector eliminates this bottleneck by establishing a direct Python simple Salesforce connection.
- Faster Performance: With no unnecessary dependencies, queries and transactions are processed with minimal latency.
- Enhanced reliability: Fewer components mean fewer points of failure, reducing errors and downtime.
- Quick setup: Skip installing additional software—get started in minutes.
For developers, this means less troubleshooting and more time to focus on solutions. For businesses, it’s about faster deployments and smoother operations without the usual roadblocks.
Use Python DB API 2.0 for familiar workflows
For a developer, learning a new tool shouldn’t feel like starting from scratch. You need something that fits into your workflow, not something that forces you to relearn everything. The Devart Python Salesforce connector keeps things simple by fully adhering to the Python DB API 2.0 standard so you can hit the ground running.
Here’s how it makes your life easier:
- Familiar syntax: Use the Python commands you already know to interact with Salesforce, like creating cursors, running queries, and fetching results.
cursor.execute("SELECT Name, Email FROM Contact")
results = cursor.fetchall()In this example, cursor.execute() runs a SQL-like query to retrieve “Name” and “Email” from Salesforce contacts, and cursor.fetchall() stores the resulting records.
- Easy integration: Work seamlessly with tools like Pandas and SQLAlchemy to manipulate and analyze your data without extra steps.
With the Devart Python Connector, you skip the frustration of unfamiliar syntax and jump straight into building solutions. It’s built to keep you productive, so you can spend less time figuring things out and more time getting things done.
Simplify integration with REST and Bulk APIs for any use case
Integrating with Salesforce isn’t one-size-fits-all. Sometimes you need real-time data for live updates, and other times you’re dealing with massive datasets that require efficiency at scale. The Devart Python Connector lets Python connect to Salesforce, offering seamless support for both REST and Bulk APIs so you can choose the best approach for your needs.
- Bulk API: Perfect for heavy lifting, like migrating millions of records or syncing large datasets without overloading the system. Developers can use the Salesforce bulk API Python setup to reduce API calls, boosting performance for high-volume operations.
- REST API: Ideal for quick, dynamic tasks like updating dashboards, retrieving customer details during a live chat, or running on-the-fly data queries.
This dual compatibility ensures that the Devart Salesforce Python connector delivers the performance and scalability required, regardless of the complexity or size of your project,
Secure your data with enterprise-grade protection
When working with sensitive customer data, security is non-negotiable. A single breach can result in regulatory fines, reputational damage, and lost trust. The Devart Python Connector is designed with enterprise-grade security features to keep your Salesforce integrations safe and compliant with data protection standards and Salesforce’s security protocols.
- SSL encryption: Protects data during transmission, preventing unauthorized access or interception.
- SSH tunneling: Adds an extra layer of protection, ideal for environments with higher network vulnerabilities.
- Regular updates: Ensures compliance with Salesforce’s latest security protocols so your integration stays robust over time.
With these safeguards in place, you can focus on innovation without worrying about vulnerabilities. The Devart Python Connector gives you the confidence to handle sensitive data securely, whether you’re scaling operations or running everyday workflows.
Scale efficiently with growth-focused features
High-demand scenarios like Black Friday or massive data migrations can push your systems to the limit. To keep up with growth and rising workloads, you need a tool that not only handles the load but supports seamless scaling. The Devart Python Connector is designed for growing enterprises, delivering consistent performance and reliability when it matters most.
- Bulk data handling: Insert, update, or delete thousands of records in a single operation, significantly reducing processing time and minimizing errors.
- Smart error management: Advanced error detection ensures smooth operations, even during complex workflows.
- Continuous optimization: Nightly builds and updates keep the connector ready for evolving enterprise needs.
Whether you’re managing millions of transactions or syncing critical datasets, the Devart Python Connector enables growth with confidence. It’s built to handle demanding environments, helping you scale seamlessly and avoid bottlenecks.
What sets Devart Python connector apart
While there are other tools for Salesforce Python integration, the Devart Python Connector distinguishes itself with a unique combination of features:
- Direct connectivity: Faster and more reliable than traditional client libraries.
- Developer-centric design: Familiar Python syntax means less time spent learning and more time building.
- Enterprise-grade features: Built-in security, bulk data handling, and error management meet the demands of high-volume workflows.
- Flexibility: Full support for both REST and Python Salesforce Bulk API enables seamless integration, making it suitable for projects of any scale.
By solving common integration pain points, the Devart Python Connector turns a traditionally challenging process into a smooth, efficient workflow.
Prerequisites for connecting Python to Salesforce
Before integrating Python with Salesforce using the Devart Python Connector, you must ensure that both your Salesforce account and Python environment are appropriately configured. This section provides step-by-step instructions for setting up a Salesforce account for API access and installing the Devart Python Connector in your Python environment.
Setting up a Salesforce Account
To access Salesforce data programmatically, you need to configure your Salesforce account for API access. This involves creating a Salesforce developer account, enabling API access, and setting up a connected app. Follow these steps to get started.
Step 1: Create a Salesforce developer account
If you don’t have one, sign up at Salesforce Developer to access the tools needed for integration.
Step 2: Enable API access
- Log in to Salesforce and go to Setup > Users > Profiles.
- Select your user profile (e.g., System Administrator).
- Ensure the API Enabled checkbox is selected under Administrative Permissions and save the changes.
Step 3: Set up a connected app
This step allows your Python application to securely authenticate with Salesforce:
- Navigate to Setup > App Manager, and click New Connected App.
- Enter the App Name, for Example: PythonIntegrationApp.
- Configure OAuth Settings, enable OAuth, set the callback URL to http://localhost:8000/callback, and add relevant scopes (e.g., Access and manage your data (api)). This configuration is an essential step when using Python for Salesforce. It ensures secure and efficient integration.
- Save the app. Salesforce may take a few minutes to process your configuration.
Step 4: Obtain API credentials
- After saving, note the Consumer Key and Consumer Secret from your connected app’s settings.
- If your account is using username-password authentication, generate a security token by going to Setup > My Personal Information > Reset My Security Token. Salesforce will email the token to you.
With these steps completed, your Salesforce account is ready for integration.
Installing Devart Python Connector
Installing the connector is a straightforward process. Follow the steps described below to proceed with the installation.
Step 1: Verify your environment
Before installing the connector, ensure your Python environment is ready:
- Check Python version:
Make sure Python 3.x is installed by running the following commands:
python --version - Ensure pip is installed:
Verify pip (Python’s package manager) is available.
python -m ensurepip --upgrade If Python or pip isn’t installed, refer to the official Python installation guide.
Step 2: Download and install the Devart Python Connector
Use pip to install the connector or download it directly from the Devart website.
Step 3: Test the installation
A simple test ensures the connector is properly installed and functional. Use the following script to validate the setup by connecting to Salesforce and running a query.
This script verifies that the connector is installed, API credentials are correct, and your Salesforce account is accessible.
import devart
# Replace with your Salesforce credentials
conn = devart.connect(
consumer_key="your_consumer_key",
consumer_secret="your_consumer_secret",
username="your_username",
password="your_password" + "your_security_token"
)
cursor = conn.cursor()
cursor.execute("SELECT Name FROM Account LIMIT 5")
for row in cursor.fetchall():
print(row) How to authenticate Python with Salesforce API
Authentication is a critical step in integrating Python with Salesforce. Primarily, there are two Python Salesforce API authentication methods: OAuth for secure, scalable integrations and security tokens for simpler setups.
Authentication using OAuth
OAuth is the recommended method for production environments. It ensures security and scalability, making it ideal for enterprise-grade integrations where exposing credentials isn’t an option.
Steps for OAuth authentication
Step 1: Set up a connected app in salesforce
Ensure that you’ve already created a connected app as outlined in the Setting up a Salesforce Account section. The connected app will provide you with the Consumer Key, Consumer Secret, and Callback URL, which are required for OAuth authentication.
Step 2: Generate an access token
Use Python to generate an access token by sending a POST request to Salesforce’s OAuth token endpoint.
import requests
# Salesforce OAuth token endpoint
oauth_url = "https://login.salesforce.com/services/oauth2/token"
# Define your credentials
payload = {
"grant_type": "password",
"client_id": "your_consumer_key", # Consumer Key from Connected App
"client_secret": "your_consumer_secret", # Consumer Secret from Connected App
"username": "your_salesforce_username", # Your Salesforce username
"password": "your_password_and_token" # Password + Security Token
}
# Send the request
response = requests.post(oauth_url, data=payload)
# Parse the response
if response.status_code == 200:
access_token = response.json().get("access_token")
instance_url = response.json().get("instance_url")
print("Access Token:", access_token)
print("Instance URL:", instance_url)
else:
print("Error:", response.json()) Replace the placeholders with your actual credentials. The access_token and instance_url will be used for subsequent salesforce API python calls.
Step 3. Use the access token
Include the access token in the Authorization header for every API request. The following example demonstrates how to use it with the Devart Python Connector.
connection_params = {
"host": "your_instance_url", # Instance URL from the OAuth response
"access_token": access_token, # Access Token from the OAuth response
"database": "salesforce"
}
connection = devart.connect(**connection_params)
print("Authenticated via OAuth successfully!") Considerations for OAuth
- Security: Store your Consumer Key, Consumer Secret, and access tokens securely (e.g., in environment variables or a secrets manager).
- Token expiry: Access tokens have a limited lifespan. Use Salesforce’s refresh token mechanism to obtain new tokens without re-authenticating.
Using security tokens for authentication
For simpler setups or development environments, you can authenticate using Salesforce’s security tokens.
Steps for security token authentication
Step 1: Obtain a security token
- Log in to Salesforce.
- Navigate to Setup > My Personal Information > Reset My Security Token.
- Click Reset Security Token, and Salesforce will email a new token to your registered email address.
Step 2: Authenticate using username and security token
When using the Devart Python Connector, append the security token to your Salesforce password.
connection_params = {
"host": "your_salesforce_instance.salesforce.com",
"user": "your_username",
"password": "your_password" + "your_security_token",
"database": "salesforce"
}
connection = devart.connect(**connection_params)
print("Authenticated using security token successfully!") Step 3: Test the connection
Verify the connection by running a simple query.
cursor = connection.cursor()
cursor.execute("SELECT Id, Name FROM Account")
for row in cursor.fetchall():
print(row) Considerations for security tokens
- Development-Only Use: Security token-based authentication is ideal for testing or small-scale projects but should not be used in production environments due to its lower security level.
- Token Reset: Resetting your security token invalidates the previous one, so ensure you update your scripts or configuration when this happens.
For better security, store your security tokens in an encrypted format and update configurations immediately after token resets.
Summary of authentication methods
| Feature | OAuth | Security Token |
|---|---|---|
| Security Level | High (recommended for production) | Moderate (suitable for development) |
| Ease of Use | Requires connected app setup | Quick setup, no app required |
| Best use Case | Large-scale, secure integrations | Quick testing and small-scale projects |
| Credential Expiry | Tokens expire but can be refreshed | Token resets need manual updates |
With authentication configured, you’re now ready to query Salesforce data using the Devart Python Connector.
Querying Salesforce data with Devart Connector
Once authenticated, the Devart Python Connector makes querying Salesforce data as simple and efficient as querying any relational database. By combining the flexibility of Python with the structured capabilities of Salesforce Object Query Language (SOQL), developers can extract valuable insights and manipulate data directly within their Python applications.
Basic queries to fetch data
With its SQL-like syntax, the Devart Python Connector allows you to query Salesforce objects easily. Whether you need real-time data for dashboards or filtered results for analytics, SOQL makes it straightforward to extract and manipulate Salesforce records.
Example: Fetching data from the contact object
import devart
# Define connection parameters
connection_params = {
"host": "your_salesforce_instance.salesforce.com",
"user": "your_username",
"password": "your_password_with_security_token",
"database": "salesforce"
}
# Establish connection
connection = devart.connect(**connection_params)
# Create a cursor for executing queries
cursor = connection.cursor()
# Simple SELECT query
cursor.execute("SELECT Id, FirstName, LastName, Email FROM Contact")
# Fetch and display results
for record in cursor.fetchall():
print(record) Key points:
- SQL-like syntax: The connector allows you to query Salesforce objects using familiar SQL commands like SELECT, WHERE, and ORDER BY.
- Data fetching: The fetchall() method retrieves all results as a list of tuples for easy manipulation in Python.
Example: Filtering results with a WHERE clause
You can filter data to retrieve specific records.
cursor.execute("""
SELECT Id, Name, Phone
FROM Account
WHERE Industry = 'Technology'
""")
# Print filtered accounts
for account in cursor.fetchall():
print(account) Here, the query fetches accounts belonging to the “Technology” industry, helping you drill down into specific data subsets.
Example: Sorting and limiting results
For better performance or specific use cases, you can limit the number of results and sort data.
cursor.execute("""
SELECT Name, AnnualRevenue
FROM Account
ORDER BY AnnualRevenue DESC
LIMIT 10
""")
# Top 10 accounts by revenue
for account in cursor.fetchall():
print(account) This query retrieves the top 10 accounts with the highest annual revenue.
Advanced querying techniques
For more complex queries, Salesforce Object Query Language (SOQL) offers powerful features such as relationship queries, grouping, and aggregate functions. SOQL queries are executed directly on Salesforce servers, minimizing latency and optimizing performance for complex data operations. The Devart Python Connector fully supports SOQL, enabling advanced data interactions.
Example: querying related objects
SOQL allows you to query related objects in a single statement. For instance, retrieving accounts and their associated contacts.
cursor.execute("""
SELECT Id, Name,
(SELECT FirstName, LastName
FROM Contacts)
FROM Account
WHERE Industry = 'Finance'
""")
# Print account names with their contacts
for account in cursor.fetchall():
print(account) This query fetches accounts in the “Finance” industry along with their associated contacts, demonstrating SOQL’s ability to handle hierarchical relationships.
Example: aggregating data with SOQL
Aggregate functions like COUNT, SUM, and AVG enable you to summarize data directly in Salesforce.
cursor.execute("""
SELECT Industry, COUNT(Id)
FROM Account
GROUP BY Industry
""")
# Print industry count
for industry in cursor.fetchall():
print(industry) This query groups accounts by industry and counts the number of accounts in each category.
Example: Combining filters and aggregates
For more refined queries, combine filters and aggregate functions.
cursor.execute("""
SELECT Owner.Name, SUM(Amount)
FROM Opportunity
WHERE StageName = 'Closed Won'
GROUP BY Owner.Name
ORDER BY SUM(Amount) DESC
""")
# Print total sales by owner
for owner in cursor.fetchall():
print(owner) This query retrieves the total sales amount for each opportunity owner, sorted in descending order.
Example: Querying data with date fields
SOQL also allows querying using date functions and fields.
cursor.execute("""
SELECT Name, CloseDate, Amount
FROM Opportunity
WHERE CloseDate >= LAST_N_DAYS:30
""")
# Print opportunities closed in the last 30 days
for opportunity in cursor.fetchall():
print(opportunity) This query fetches opportunities that closed within the last 30 days, making it useful for time-sensitive reports.
Key advantages of querying with Devart Connector
- Efficiency: SOQL queries are executed directly on Salesforce servers, reducing the overhead on your local application.
- Flexibility: The connector supports a wide range of SOQL features, enabling both simple and complex queries.
- Integration with Python: Results are returned in Python-friendly formats, making it easy to process and analyze data using libraries like Pandas.
The Takeaway
Salesforce Python integration has never been easier or more efficient than with the Devart Python Connector. By providing a direct, secure, and seamless connection between Python applications and Salesforce databases, this tool eliminates the complexities traditionally associated with data integration.
The Devart Python Connector bridges the gap between Salesforce’s robust capabilities and Python’s versatility, empowering you to streamline workflows, automate tasks, and unlock new possibilities in data analysis, AI, and seamless integration with other platforms. Whether you’re a data scientist, developer, or enterprise architect, our Python connector simplifies your complex processes, boosts efficiency, and drives innovation, helping you focus on achieving your goals and growing your business.
Ready to simplify your Salesforce-Python workflows? Order your Devart Python Connector today and unlock the power of streamlined data integration.
