REST API Connector for Python

Create ODBC Data Source (DSN) based on ZappySys JSON Driver

If your API is JSON Type and responding the json string response, in that case using ZappySys JSON Driver we can make the JSON API call and parse the json string. Let's configure the API call in the JSON Driver

1. Download and install ODBC PowerPack.

2. Open ODBC Data Sources (x64):

   

3. Create a User data source (User DSN) based on ZappySys JSON Driver:

   ZappySys JSON Driver

   
   • Create and use User DSN if the client application is run under a User Account. This is an ideal option in design-time, when developing a solution, e.g. in Visual Studio 2019. Use it for both type of applications - 64-bit and 32-bit.
   • Create and use System DSN if the client application is launched under a System Account, e.g. as a Windows Service. Usually, this is an ideal option to use in a production environment. Use ODBC Data Source Administrator (32-bit), instead of 64-bit version, if Windows Service is a 32-bit application.

4. Select Url or File and paste the following Url for this example OR you can load existing connection string as per this article.
   

   NOTE: Here for demo, We are using odata API, but you need to refer your own API documentation and based on that you need to use your own API URL and need to configure connection based on API Authentication type

   https://services.odata.org/V3/Northwind/Northwind.svc/Customers?$format=json

5. Now enter JSONPath expression in Array Filter textbox to extract only specific part of JSON file as below ($.value[*] will get content of value attribute from JSON document. Value attribute is array of JSON documents so we have to use [*] to indicate we want all records of that array)
   

   NOTE: Here, We are using our desired filter, but you need to select your desired filter based on your requirement.

   
   Click on Test Connection button to view whether the Test Connection is SUCCESSFUL or Not.
   $.value[*]
   

6. Once you configured a data source, you can preview data. Hit Preview tab, and use similar settings to preview data:
   

7. Click OK to finish creating the data source

8. That's it; we are done. In a few clicks we configured the call to JSON API using ZappySys JSON Connector.

Create ODBC Data Source (DSN) based on ZappySys XML Driver

In upper section we check how to make the JSON API call using JSON Driver and parse the json string response. Same way if your API is XML/SOAP Type and responding the xml string response, in that case using ZappySys XML Driver we can make the XML/SOAP API call and parse the xml string. Let's configure the API call in the XML Driver.

1. Download and install ODBC PowerPack.

2. Open ODBC Data Sources (x64):

   

3. Create a User data source (User DSN) based on ZappySys XML Driver:

   ZappySys XML Driver

   
   • Create and use User DSN if the client application is run under a User Account. This is an ideal option in design-time, when developing a solution, e.g. in Visual Studio 2019. Use it for both type of applications - 64-bit and 32-bit.
   • Create and use System DSN if the client application is launched under a System Account, e.g. as a Windows Service. Usually, this is an ideal option to use in a production environment. Use ODBC Data Source Administrator (32-bit), instead of 64-bit version, if Windows Service is a 32-bit application.

4. Select Url or File and paste the following Url for this example OR you can load existing connection string as per this article.
   

   NOTE: Here for demo, We are using odata API, but you need to refer your own API documentation and based on that you need to use your own API URL and need to configure connection based on API Authentication type

   https://services.odata.org/V3/Northwind/Northwind.svc/Customers

5. Now enter Path expression in Array Filter textbox to extract only specific part of XML file as below ($.feed.entry[*] will get content of entry attribute from XML document. Entry attribute is array of XML documents so we have to use [*] to indicate we want all records of that array)
   

   NOTE: Here, We are using our desired filter, but you need to select your desired filter based on your requirement.

   
   Click on Test Connection button to view whether the Test Connection is SUCCESSFUL or Not.
   $.feed.entry[*]
   

6. Once you configured a data source, you can preview data. Hit Preview tab, and use similar settings to preview data:
   

7. Click OK to finish creating the data source.

8. That's it; we are done. In a few clicks we configured the call to XML API using ZappySys XML Connector.

Create ODBC Data Source (DSN) based on ZappySys CSV Driver

In upper section we check how to make the XML/Soap API call using XML Driver and parse the xml string response. Same way if your API is CSV Type or want to parse the CSV file data, in that case using ZappySys CSV Driver we can make the API call or read the CSV file data.

1. Download and install ODBC PowerPack.

2. Open ODBC Data Sources (x64):

   

3. Create a User data source (User DSN) based on ZappySys CSV Driver:

   ZappySys CSV Driver

   
   • Create and use User DSN if the client application is run under a User Account. This is an ideal option in design-time, when developing a solution, e.g. in Visual Studio 2019. Use it for both type of applications - 64-bit and 32-bit.
   • Create and use System DSN if the client application is launched under a System Account, e.g. as a Windows Service. Usually, this is an ideal option to use in a production environment. Use ODBC Data Source Administrator (32-bit), instead of 64-bit version, if Windows Service is a 32-bit application.

4. Select Url or File.
   

   Read CSV API in Python

   • Paste the following Url. In this example, We are using Zip format CSV File URL, but you need to refer your CSV File/URL.

     https://zappysys.com/downloads/files/test/cust-1.csv.zip
     Click on Test Connection button to view whether the Test Connection is SUCCESSFUL or Not.

   Read CSV File in Python

   • You can use pass single file or multiple file path using wildcard pattern in path and you can use select single file by clicking [...] path button or multiple file using wildcard pattern in path.
     

     Note: If you want to operation with multiple files then use wild card pattern as below
     (when you use wild card pattern in source path then system will treat target path as folder regardless you end with slash)
     
     C:\SSIS\Test\reponse.csv (will read only single reponse.csv file)
     C:\SSIS\Test\j*.csv (all files starting with file name j)
     C:\SSIS\Test\*.csv (all files with .csv Extension and located under folder subfolder)
     

     Click on Test Connection button to view whether the Test Connection is SUCCESSFUL or Not.

5. Once you configured a data source, you can preview data. Hit Preview tab, and use similar settings to preview data:
   

6. Click OK to finish creating the data source

7. That's it; we are done. In a few clicks we configured the read the CSV data using ZappySys CSV Connector.

Read data in Python

Using ODBC DSN

1. Use this code snippet to read the data using RestApiDSN data source:

   RestApiDSN')

   

2. When you run the code it will make the API call and read the data:

   

3. Here is Python program's code in text format:

   
       import pyodbc
       conn = pyodbc.connect('DSN=RestApiDSN')
   
       cursor = conn.cursor()
   
       #execute query to fetch data from API service
       cursor.execute("SELECT id,title FROM products")
   
       row = cursor.fetchone()
       while row:
           print(row)
           row = cursor.fetchone()
   
       ##For loop example
       #for row in cursor:
       #    print(row)
   

Using a full ODBC connection string

If you want to avoid being dependent on a DSN and creating multiple DSNs for each platform (x86, x64), then you can use a fully qualified connection string. Simply go to your DSN and copy the Connection String:

1. Open ODBC data source configuration and click Copy settings:
   

   ZappySys JSON, XML or CSV Driver - Configuration [Version: 2.0.1.10418]

   ZappySys JSON, XML or CSV Driver - REST API

   REST API Connector can be used to extract and output JSON/XML/CSV/String data coming from REST API web service calls (Web URL).

   RestApiDSN

   
2. The window opens, telling us the connection string was successfully copied to the clipboard:

3. Then in your Python code use Connection String when initializing OdbcConnection object, for example:

   conn = pyodbc.connect('DRIVER={ZappySys JSON, XML or CSV Driver};ServiceUrl=https://yourservices.provider.com/api/xxxx....;AuthName=Http;')

How to install `pyodbc` in the Python?

Centralized data access via Data Gateway

In some situations, you may need to provide REST API data access to multiple users or services. Configuring the data source on a Data Gateway creates a single, centralized connection point for this purpose.

This configuration provides two primary advantages:

• Centralized data access
  The data source is configured once on the gateway, eliminating the need to set it up individually on each user's machine or application. This significantly simplifies the management process.
• Centralized access control
  Since all connections route through the gateway, access can be governed or revoked from a single location for all users.

If you need any of these requirements, you will have to create a data source in Data Gateway to connect to REST API, and to create an ODBC data source to connect to Data Gateway in Python.

Let's not wait and get going!

Creating REST API data source in Gateway

In this section we will create a data source for REST API in Data Gateway. Let's follow these steps to accomplish that:

1. Search for gateway in Windows Start Menu and open ZappySys Data Gateway Configuration:

   

2. Go to Users tab and follow these steps to add a Data Gateway user:

   • Click Add button
   • In Login field enter username, e.g., john
   • Then enter a Password
   • Check Is Administrator checkbox
   • Click OK to save
   

3. Now we are ready to add a data source:

   • Click Add button
   • Give Datasource a name (have it handy for later)
   • Then select Native - ZappySys JSON, XML or CSV Driver
   • Finally, click OK
   RestApiDSN

   ZappySys JSON, XML or CSV Driver

   

4. When the ZappySys JSON, XML or CSV Driver configuration window opens, configure the Data Source the same way you configured it in ODBC Data Sources (64-bit), in the beginning of this article.

5. Very important step. Now, after creating or modifying the data source make sure you:

   • Click the Save button to persist your changes.
   • Hit Yes, once asked if you want to restart the Data Gateway service.

   This will ensure all changes are properly applied:

   
   Skipping this step may result in the new settings not taking effect and, therefore you will not be able to connect to the data source.

Creating ODBC data source for Data Gateway

In this part we will create ODBC data source to connect to Data Gateway from Python. To achieve that, let's perform these steps:

1. Open ODBC Data Sources (x64):

   

2. Create a User data source (User DSN) based on ODBC Driver 17 for SQL Server:

   ODBC Driver 17 for SQL Server

   
   If you don't see ODBC Driver 17 for SQL Server driver in the list, choose a similar version driver.

3. Then set a Name of the data source (e.g. Gateway) and the address of the Data Gateway:

   GatewayDSN

   localhost,5000

   
   Make sure you separate the hostname and port with a comma, e.g. localhost,5000.

4. Proceed with authentication part:

   • Select SQL Server authentication
   • In Login ID field enter the user name you used in Data Gateway, e.g., john
   • Set Password to the one you configured in Data Gateway
   

5. Then set the default database property to RestApiDSN (the one we used in Data Gateway):

   RestApiDSN

   

6. Continue by checking Trust server certificate option:

   

7. Once you do that, test the connection:

   

8. If connection is successful, everything is good:

   

9. Done!

We are ready to move to the final step. Let's do it!

Accessing data in Python via Data Gateway

Finally, we are ready to read data from REST API in Python via Data Gateway. Follow these final steps:

1. Go back to Python.

2. Use this code snippet to read the data using GatewayDSN data source:

   GatewayDSN')

   

3. Read the data the same way we discussed at the beginning of this article.

4. That's it!

Now you can connect to REST API data in Python via the Data Gateway.

Configuring pagination in the REST API Driver

ZappySys REST API Driver equips users with powerful tools for seamless data extraction and management from REST APIs, leveraging advanced pagination methods for enhanced efficiency. These options are designed to handle various types of pagination structures commonly used in APIs. Below are the detailed descriptions of these options:

1. Page-based Pagination: This method works by retrieving data in fixed-size pages from the Rest API. It allows you to specify the page size and navigate through the results by requesting different page numbers, ensuring that you can access all the data in a structured manner.

2. Offset-based Pagination: With this approach, you can extract data by specifying the starting point or offset from which to begin retrieving data. It allows you to define the number of records to skip and fetch subsequent data accordingly, providing precise control over the data extraction process.

3. Cursor-based Pagination: This technique involves using a cursor or a marker that points to a specific position in the dataset. It enables you to retrieve data starting from the position indicated by the cursor and proceed to subsequent segments, ensuring that you capture all the relevant information without missing any records.

4. Token-based Pagination: In this method, a token serves as a unique identifier for a specific data segment. It allows you to access the next set of data by using the token provided in the response from the previous request. This ensures that you can systematically retrieve all the data segments without duplication or omission.

Utilizing these comprehensive pagination features in the ZappySys REST API Driver facilitates efficient data management and extraction from REST APIs, optimizing the integration and analysis of extensive datasets.

For more detailed steps, please refer to this link: How to do REST API Pagination in SSIS / ODBC Drivers

Authentication

ZappySys offers various authentication methods to securely access data from various sources. These authentication methods include OAuth, Basic Authentication, Token-based Authentication, and more, allowing users to connect to a wide range of data sources securely.

ZappySys Authentication is a robust system that facilitates secure access to data from a diverse range of sources. It includes a variety of authentication methods tailored to meet the specific requirements of different data platforms and services. These authentication methods may involve:

1. OAuth: ZappySys supports OAuth for authentication, which allows users to grant limited access to their data without revealing their credentials. It's commonly used for applications that require access to user account information.

2. Basic Authentication: This method involves sending a username and password with every request. ZappySys allows users to securely access data using this traditional authentication approach.

3. Token-based Authentication: ZappySys enables users to utilize tokens for authentication. This method involves exchanging a unique token with each request to authenticate the user's identity without revealing sensitive information.

By implementing these authentication methods, ZappySys ensures the secure and reliable retrieval of data from various sources, providing users with the necessary tools to access and integrate data securely and efficiently. For more comprehensive details on the authentication process, please refer to the official ZappySys documentation or reach out to their support team for further assistance.

For more details, please refer to this link: ZappySys Connections

Conclusion

In this article we showed you how to connect to REST API in Python and integrate data without any coding, saving you time and effort.

We encourage you to download REST API Connector for Python and see how easy it is to use it for yourself or your team.

If you have any questions, feel free to contact ZappySys support team. You can also open a live chat immediately by clicking on the chat icon below.

Download REST API Connector for Python Documentation

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