JSON File Connector for Python

JSON File Connector can be used to extract and output JSON data stored in local files or direct JSON String (variables or DB columns). JSON Connector also supports JSONPath to filter data from nested array/sub-documents. This Connector is optimized to work with very large files.

In this article you will learn how to quickly and efficiently integrate JSON File data in Python. We will use high-performance JSON File Connector to easily connect to JSON File and then access the data inside Python.

Let's follow the steps below to see how we can accomplish that!

Download Documentation

JSON File Connector for Python is based on ZappySys JSON Driver which is part of ODBC PowerPack. It is a collection of high-performance ODBC drivers that enable you to integrate data in SQL Server, SSIS, a programming language, or any other ODBC-compatible application. ODBC PowerPack supports various file formats, sources and destinations, including REST/SOAP API, SFTP/FTP, storage services, and plain files, to mention a few.

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

Step-by-step instructions

To get data from JSON File using Python we first need to create a DSN (Data Source) which will access data from JSON File. We will later be able to read data using Python. Perform these steps:

Download and install ODBC PowerPack.
Open ODBC Data Sources (x64):
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.

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.json (will read only single reponse.json file)
C:\SSIS\Test\j*.json (all files starting with file name)
C:\SSIS\Test\*.json (all files with .json Extension and located under folder subfolder)

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[*]
Once you configured a data source, you can preview data. Hit Preview tab, and use similar settings to preview data:
Click OK to finish creating the data source
That's it; we are done. In a few clicks we configured the call to JSON File using ZappySys JSON File Connector

Video Tutorial

Read data in Python

Using ODBC DSN

Use this code snippet to read the data using JsonFileDSN data source:

JsonFileDSN')
When you run the code it will make the API call and read the data:

Here is Python program's code in text format:


    import pyodbc
    conn = pyodbc.connect('DSN=JsonFileDSN')

    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:

Open ODBC data source configuration and click Copy settings:

ZappySys JSON Driver - Configuration [Version: 2.0.1.10418]

ZappySys JSON Driver - JSON File

JSON File Connector can be used to extract and output JSON data stored in local files or direct JSON String (variables or DB columns). JSON Connector also supports JSONPath to filter data from nested array/sub-documents. This Connector is optimized to work with very large files.

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

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

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

How to install `pyodbc` in the Python?

You would need to install pyodbc in Python if you intend to establish connections to databases that support ODBC (Open Database Connectivity). This module facilitates communication between Python applications and various database management systems, enabling you to perform operations such as querying, retrieving data, and managing databases. Here's how you can install pyodbc in Python:

Installation Steps:

Ensure you have Python installed on your system. If not, download it from the official Python website and follow the installation instructions.
Open your terminal or command prompt.
Use the following command to install pyodbc using pip, the Python package installer:
```
python -m pip install "pyodbc"
```
Make sure you have a stable internet connection and the necessary permissions to install Python packages.

Reasons to Install:

If pyodbc is not installed, your Python script will generate the following error:
```
"ModuleNotFoundError: No module named 'pyodbc'"
```
.
Database Connectivity: pyodbc allows Python to connect to various databases that support ODBC, such as Microsoft SQL Server, PostgreSQL, MySQL, and more.
Data Operations: It facilitates the execution of SQL queries, retrieval of data, and other database operations from within Python scripts.
Cross-Platform Support: pyodbc is designed to work across different operating systems, including Windows, macOS, and various Linux distributions.
Simplicity and Efficiency: The module provides an intuitive interface for managing database transactions and connections, simplifying the process of working with databases in Python.

By installing pyodbc, you can seamlessly integrate your Python applications with a wide range of ODBC-supported databases, enabling efficient and effective data management and analysis.

Centralized data access via Data Gateway

In some situations, you may need to provide JSON File 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.

	Data Gateway	Local ODBC data source
Simple configuration
Installation	Single machine	Per machine
Connectivity	Local and remote	Local only
Connections limit	Limited by License	Unlimited
Central data access
Central access control
More flexible cost

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

Let's not wait and get going!

Creating JSON File data source in Gateway

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

Search for gateway in Windows Start Menu and open ZappySys Data Gateway Configuration:
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
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 Driver
- Finally, click OK
JsonFileDSN

ZappySys JSON Driver
When the ZappySys JSON 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.
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:

Open ODBC Data Sources (x64):
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.
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.
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
Then set the default database property to JsonFileDSN (the one we used in Data Gateway):

JsonFileDSN
Continue by checking Trust server certificate option:
Once you do that, test the connection:
If connection is successful, everything is good:
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 JSON File in Python via Data Gateway. Follow these final steps:

Go back to Python.
Use this code snippet to read the data using GatewayDSN data source:

GatewayDSN')
Read the data the same way we discussed at the beginning of this article.
That's it!

Now you can connect to JSON File data in Python via the Data Gateway.

If you are asked for authentication details, use Database authentication or SQL Authentication option and enter credentials you used when configuring Data Gateway, e.g. john and your password.