Python CSV Connector In this article you will learn how to integrate CSV data to Python (live / bi-directional connection to CSV). CSV Connector can be used to extract and output CSV data from Web URL/REST API web service calls (Web URL) or direct CSV String (variables or DB columns) or local CSV files data.. Using CSV 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 CSV in SSIS Connect CSV in SQL Server Connect CSV in Power BI Connect CSV in SSRS Connect CSV in Informatica Connect CSV in MS Access Connect CSV in MS Excel Connect CSV in SSAS Connect CSV in C# Connect CSV in JAVA Connect CSV in Tableau Connect CSV in SAP Crystal Reports Connect CSV in Azure Data Factory (ADF) Connect CSV in ODBC

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

To get data from Csv using Python we first need to create a DSN (Data Source) which will access data from Csv. 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 CSV Driver

   ZappySys CSV 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. 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 from the DSN

1. Python code to get the data:
   

   CsvDSN')

   

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=CsvDSN')
   
   cursor = conn.cursor() 
   
   #execute query to fetch data from API service
   cursor.execute("SELECT * FROM value") 
   row = cursor.fetchone() 
   while row: 
   print (row[1]) 
   row = cursor.fetchone()
   

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 API Driver};ServiceUrl=https://services.odata.org/V3/Northwind/Northwind.svc;Provider=OData;AuthName=Http;')
   

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';

   
   

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.

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"

   
   

Conclusion

In this article we discussed how to connect to CSV in Python and integrate data without any coding. Click here to Download CSV 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).

Download CSV Connector for Python Documentation 

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