Python Amazon S3 JSON File Connector In this article you will learn how to integrate Amazon S3 JSON File data to Python (live / bi-directional connection to Amazon S3 JSON File). Amazon S3 JSON File Connector can be used to read JSON Files stored in AWS S3 Buckets. Using this you can easily integrate AWS S3 JSON File data. It's supports latest security standards, and optimized for large data files. It also supports reading compressed files (e.g. GZip /Zip).. Using Amazon S3 JSON File Connector you will be able to connect, read, and write data from within Python. Follow the steps below to see how we would accomplish that. Download  Help File  Buy  Driver mentioned in this article is part of ODBC PowerPack which is a collection of high-performance Drivers for various API data source (i.e. REST API, JSON, XML, CSV, Amazon S3 and many more). Using familiar SQL query language you can make live connections and read/write data from API sources or JSON / XML / CSV Files inside SQL Server (T-SQL) or your favorite Reporting (i.e. Power BI, Tableau, Qlik, SSRS, MicroStrategy, Excel, MS Access), ETL Tools (i.e. Informatica, Talend, Pentaho, SSIS). You can also call our drivers from programming languages such as JAVA, C#, Python, PowerShell etc. If you are new to ODBC and ZappySys ODBC PowerPack then check the following links to get started. ODBC PowerPack - System Requirements and Installation Getting Started - Using ODBC PowerPack ODBC API Driver Help File

See also Connect Amazon S3 JSON File in SSIS Connect Amazon S3 JSON File in SQL Server Connect Amazon S3 JSON File in Power BI Connect Amazon S3 JSON File in SSRS Connect Amazon S3 JSON File in Informatica Connect Amazon S3 JSON File in MS Access Connect Amazon S3 JSON File in MS Excel Connect Amazon S3 JSON File in SSAS Connect Amazon S3 JSON File in C# Connect Amazon S3 JSON File in JAVA Connect Amazon S3 JSON File in Tableau Connect Amazon S3 JSON File in SAP Crystal Reports Connect Amazon S3 JSON File in Azure Data Factory (ADF) Connect Amazon S3 JSON File in ODBC

Create ODBC Data Source (DSN) based on ZappySys Amazon S3 JSON Driver

To get data from AmazonS3JsonFile using Python we first need to create a DSN (Data Source) which will access data from AmazonS3JsonFile. We will later be able to read data using Python. Perform these steps:

1. Install ZappySys ODBC PowerPack.

2. Open ODBC Data Sources (x64):
   

3. Create a User Data Source (User DSN) based on ZappySys Amazon S3 JSON Driver

   ZappySys Amazon S3 JSON Driver

   
   You should create a System DSN (instead of a User DSN) if the client application is launched under a Windows System Account, e.g. as a Windows Service. If the client application is 32-bit (x86) running with a System DSN, use ODBC Data Sources (32-bit) instead of the 64-bit version.

4. Create and configure a connection for the Amazon S3 storage account.

   

5. You can use select your desired single file by clicking [...] path button.

   mybucket/dbo.tblNames.json

   dbo.tblNames.json

   
   
   
   ----------OR----------

   You can also read the multiple files stored in Amazon S3 Storage using wildcard pattern supported e.g. dbo.tblNames*.json.
   

   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)
   
   mybucket/dbo.tblNames.json (will read only single .JSON file)
   mybucket/dbo.tbl*.json (all files starting with file name)
   mybucket/*.json (all files with .json Extension and located under folder subfolder)
   

   mybucket/dbo.tblNames*.json

   
   
   
   ----------OR----------

   You can also read the zip and gzip compressed files also without extracting it in using Amazon S3 JSON Source File Task.

   mybucket/dbo.tblNames*.gz

   

6. Now select/enter Path expression in Path textbox to extract only specific part of JSON string 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.
   

7. Navigate to the Preview Tab and let's explore the different modes available to access the data.
   

   1. --- Using Direct Query ---

      Click on Preview Tab, Select Table from Tables Dropdown and select [value] and click Preview.
      

   2. --- Using Stored Procedure ---

      Note : For this you have to Save ODBC Driver configuration and then again reopen to configure same driver. For more information click here.
      

      Click on the Custom Objects Tab, Click on Add button and select Add Procedure and Enter an appropriate name and Click on OK button to create.
      

      1. --- Without Parameters ---

         Now Stored Procedure can be created with or without parameters (see example below). If you use parameters then Set default value otherwise it may fail to compilation)
         
         

      2. --- With Parameters ---

         Note : Here you can use Placeholder with Paramters in Stored Procedure.
         Example : SELECT * FROM $ WHERE OrderID = '<@OrderID, FUN_TRIM>' or CustId = '<@CustId>' and Total >= '<@Total>'
         

         

   3. --- Using Virtual Table ---

      Note : For this you have to Save ODBC Driver configuration and then again reopen to configure same driver. For more information click here.
      

      ZappySys APi Drivers support flexible Query language so you can override Default Properties you configured on Data Source such as URL, Body. This way you don't have to create multiple Data Sources if you like to read data from multiple EndPoints. However not every application support supplying custom SQL to driver so you can only select Table from list returned from driver.

      Many applications like MS Access, Informatica Designer wont give you option to specify custom SQL when you import Objects. In such case Virtual Table is very useful. You can create many Virtual Tables on the same Data Source (e.g. If you have 50 Buckets with slight variations you can create virtual tables with just URL as Parameter setting).

      vt__Customers
      DataPath=mybucket_1/customers.json
      
      vt__Orders
      DataPath=mybucket_2/orders.json
      
      vt__Products
      DataPath=mybucket_3/products.json
      

      1. Click on the Custom Objects Tab, Click on Add button and select Add Table and Enter an appropriate name and Click on OK button to create.
         
      2. Once you see Query Builder Window on screen Configure it.
         
      3. Click on Preview Tab, Select Virtual Table(prefix with vt__) from Tables Dropdown or write SQL query with Virtual Table name and click Preview.
         

8. Click OK to finish creating the data source

9. That's it; we are done. In a few clicks we configured the to Read the Amazon S3 JSON File data using ZappySys Amazon S3 JSON File Connector

Read data in Python from the DSN

1. Python code to get the data:
   

   AmazonS3JsonFileDSN')

   

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=AmazonS3JsonFileDSN')
   
       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)
   

4. If you want to avoid to be dependent on a DSN name 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 . Then in your Python code use Connection String when initializing OdbcConnection object, for example:

   conn = pyodbc.connect('DRIVER={ZappySys Amazon S3 JSON Driver};ServiceUrl=https://yourservices.provider.com/api/xxxx....;AuthName=Http;')

   How to get ZappySys Driver Connection String?

   Please follow the instructions below to retrieve the connection string for the ZappySys driver.

   1. Click on the Windows Start menu.

   2. In the search bar, type ODBC and press Enter.

   3. From the search results, choose ODBC Data Sources or ODBC Data Sources (32-bit) or a similar option depending on your system architecture and ODBC driver configuration.

   4. Choose your data source from the list, then click on the Configure button.
   5. After opening the Data Source UI, you should copy the connection string to a Notepad or text file for reference.
   6. Click on Copy Connection String button.
      When you click 'Copy Connection String,' you may encounter the following option:
      Choose the third option All Settings to copy everything and click on OK button.
      
      

   That's it connection string has been successfully copied.

How to install `pyodbc` in the Python?

Create Custom Store Procedure in ZappySys Driver

You can create procedures to encapsulate custom logic and then only pass handful parameters rather than long SQL to execute your API call.

Steps to create Custom Store Procedure in ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here

1. Go to Custom Objects Tab and Click on Add button and Select Add Procedure:
   

2. Enter the desired Procedure name and click on OK:
   

3. Select the created Store Procedure and write the your desired store procedure and Save it and it will create the custom store procedure in the ZappySys Driver:
   Here is an example stored procedure for ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here
   

   CREATE PROCEDURE [usp_get_orders]
       @fromdate = '<<yyyy-MM-dd,FUN_TODAY>>'
    AS
       SELECT * FROM Orders where OrderDate >= '<@fromdate>';
   

   
   

4. That's it now go to Preview Tab and Execute your Store Procedure using Exec Command. In this example it will extract the orders from the date 1996-01-01:
   

   Exec usp_get_orders '1996-01-01';

   
   

5. Let's generate the SQL Server Query Code to make the API call using store procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC usp_get_orders @fromdate=''1996-07-30''')

   
   

6. Now go to SQL served and execute that query and it will make the API call using store procedure and provide you the response.
   

Create Custom Virtual Table in ZappySys Driver

ZappySys API Drivers support flexible Query language so you can override Default Properties you configured on Data Source such as URL, Body. This way you don't have to create multiple Data Sources if you like to read data from multiple EndPoints. However not every application support supplying custom SQL to driver so you can only select Table from list returned from driver.

If you're dealing with Microsoft Access and need to import data from an SQL query, it's important to note that Access doesn't allow direct import of SQL queries. Instead, you can create custom objects (Virtual Tables) to handle the import process.

Many applications like MS Access, Informatica Designer wont give you option to specify custom SQL when you import Objects. In such case Virtual Table is very useful. You can create many Virtual Tables on the same Data Source (e.g. If you have 50 URLs with slight variations you can create virtual tables with just URL as Parameter setting.

1. Go to Custom Objects Tab and Click on Add button and Select Add Table:
   

2. Enter the desired Table name and click on OK:
   

3. And it will open the New Query Window Click on Cancel to close that window and go to Custom Objects Tab.

4. Select the created table, Select Text Type AS SQL and write the your desired SQL Query and Save it and it will create the custom table in the ZappySys Driver:
   Here is an example SQL query for ZappySys Driver. You can insert Placeholders also. Read more about placeholders here
   

   SELECT
     "ShipCountry",
     "OrderID",
     "CustomerID",
     "EmployeeID",
     "OrderDate",
     "RequiredDate",
     "ShippedDate",
     "ShipVia",
     "Freight",
     "ShipName",
     "ShipAddress",
     "ShipCity",
     "ShipRegion",
     "ShipPostalCode"
   FROM "Orders"
   Where "ShipCountry"='USA'

   
   

5. That's it now go to Preview Tab and Execute your custom virtual table query. In this example it will extract the orders for the USA Shipping Country only:
   

   SELECT * FROM "vt__usa_orders_only"

   
   

6. Let's generate the SQL Server Query Code to make the API call using store procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC [usp_get_orders] ''1996-01-01''')

   
   

7. Now go to SQL served and execute that query and it will make the API call using store procedure and provide you the response.
   

Conclusion

In this article we discussed how to connect to Amazon S3 JSON File in Python and integrate data without any coding. Click here to Download Amazon S3 JSON File Connector for Python and try yourself see how easy it is. If you still have any question(s) then ask here or simply click on live chat icon below and ask our expert (see bottom-right corner of this page).

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