XML File Connector for PythonIn this article you will learn how to quickly and efficiently integrate XML File data in Python. We will use high-performance XML File Connector to easily connect to XML File and then access the data inside Python. XML File Connector can be used to extract and output XML data stored in local XML files or direct XML String (variables or DB columns). XML Connector also supports Path expression to extract data from any level. This Connector is optimized to work with very large files. Let's follow the steps below to see how we can accomplish that! XML File Connector for Python is based on ZappySys XML 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. |
Connect to XML File in other apps
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Create ODBC Data Source (DSN) based on ZappySys XML Driver
Step-by-step instructions
To get data from XML File using Python we first need to create a DSN (Data Source) which will access data from XML File. We will later be able to read data using Python. Perform these steps:
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Install ZappySys ODBC PowerPack.
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Open ODBC Data Sources (x64):
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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.
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Create and use User DSN
if the client application is run under a User Account.
This is an ideal option
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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.xml (will read only single reponse.xml file) C:\SSIS\Test\j*.xml (all files starting with file name j) C:\SSIS\Test\*.xml (all files with .xml Extension and located under folder subfolder)
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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[*] -
Once you configured a data source, you can preview data. Hit Preview tab, and use similar settings to preview data:
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Click OK to finish creating the data source.
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That's it; we are done. In a few clicks we configured the call to XML File using ZappySys XML File Connector.
Video instructions
Read data in Python
Using ODBC DSN
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Python code to get the data:
XmlFileDSN') -
When you run the code it will make the API call and read the data:
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Here is Python program's code in text format:
import pyodbc conn = pyodbc.connect('DSN=XmlFileDSN') 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:
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Open ODBC data source configuration and click Copy settings:
ZappySys XML Driver - XML FileXML File Connector can be used to extract and output XML data stored in local XML files or direct XML String (variables or DB columns). XML Connector also supports Path expression to extract data from any level. This Connector is optimized to work with very large files.XmlFileDSN
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The window opens, telling us the connection string was successfully copied to the clipboard:
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Then in your Python code use Connection String when initializing OdbcConnection object, for example:
conn = pyodbc.connect('DRIVER={ZappySys XML 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.
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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.
Advanced topics
Create Custom Stored 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 Stored Procedure in ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here
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Go to Custom Objects Tab and Click on Add button and Select Add Procedure:
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Enter the desired Procedure name and click on OK:
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Select the created Stored Procedure and write the your desired stored procedure and Save it and it will create the custom stored 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>';
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That's it now go to Preview Tab and Execute your Stored 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';
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Let's generate the SQL Server Query Code to make the API call using stored 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([LINKED_SERVER_TO_XML_FILE_IN_DATA_GATEWAY], 'EXEC usp_get_orders @fromdate=''1996-07-30''')
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Now go to SQL served and execute that query and it will make the API call using stored 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.
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Go to Custom Objects Tab and Click on Add button and Select Add Table:
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Enter the desired Table name and click on OK:
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And it will open the New Query Window Click on Cancel to close that window and go to Custom Objects Tab.
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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'
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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"
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Let's generate the SQL Server Query Code to make the API call using stored 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([LINKED_SERVER_TO_XML_FILE_IN_DATA_GATEWAY], 'EXEC [usp_get_orders] ''1996-01-01''')
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Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
Conclusion
In this article we showed you how to connect to XML File in Python and integrate data without any coding, saving you time and effort. We encourage you to download XML File 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 XML File Connector for Python Documentation
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