Python Nativo Connector

In this article you will learn how to integrate Nativo data to Python (live / bi-directional connection to Nativo). Nativo Connector can be used to integrated operations supported by Nativo REST API..

Using Nativo 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.

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

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

  1. Install ZappySys ODBC PowerPack.

  2. Open ODBC Data Sources (x64):
    Open ODBC Data Source

  3. Create a User Data Source (User DSN) based on ZappySys API Driver

    ZappySys API Driver
    Create new System DSN for ZappySys API 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. When the Configuration window appears give your data source a name if you haven't done that already, then select "Nativo" from the list of Popular Connectors. If "Nativo" is not present in the list, then click "Search Online" and download it. Then set the path to the location where you downloaded it. Finally, click Continue >> to proceed with configuring the DSN:

    NativoDSN
    Nativo
    ODBC DSN Template Selection

  5. Now it's time to configure the Connection Manager. Select Authentication Type, e.g. Token Authentication. Then select API Base URL (in most cases, the default one is the right one). More info is available in the Authentication section.

    Please refer to below API Reference (External Site) link for Http [Http]

    https://api-docs.nativo.com/docs/introduction

    Fill in all required parameters and set optional parameters if needed:

    NativoDSN
    Nativo
    Http [Http]
    https://api.nativo.com/v2
    Required Parameters
    Optional Parameters
    Api Key Fill in the parameter...
    Api Secret Fill in the parameter...
    RetryMode Fill in the parameter...
    RetryStatusCodeList Fill in the parameter...
    RetryCountMax Fill in the parameter...
    RetryMultiplyWaitTime Fill in the parameter...
    ODBC DSN HTTP Connection Configuration

  6. Once the data source has been configured, you can preview data. Select the Preview tab and use settings similar to the following to preview data:
    ODBC ZappySys Data Source Preview

  7. Click OK to finish creating the data source.

Read data in Python from the DSN

  1. Python code to get the data:

    NativoDSN')
    Python code to get the data from ZappySys DSN

  2. When you run the code it will make the API call and read the data:
    Python - Extracted data from ZappySys DSN

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

    
        import pyodbc
        conn = pyodbc.connect('DSN=NativoDSN')
    
        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 API 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.
      zappysys-data-source-copy-connectionstring
      zappysys-data-source-copy-connectionstring

    That's it connection string has been successfully copied.

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:

  1. Ensure you have Python installed on your system. If not, download it from the official Python website and follow the installation instructions.

  2. Open your terminal or command prompt.

  3. 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.


    Python - pip install pyodbc

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.

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:
    ZappySys Driver - Add Store Procedure

  2. Enter the desired Procedure name and click on OK:
    ZappySys Driver - Add Store Procedure Name

  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>';
    

    ZappySys Driver - Create Custom Store Procedure

  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';

    ZappySys Driver - Execute Custom Store Procedure

  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''')

    ZappySys Driver - Generate SQL Server Query

  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.
    ZappySys Driver - Generate SQL Server Query

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:
    ZappySys Driver - Add Table

  2. Enter the desired Table name and click on OK:
    ZappySys Driver - Add Table Name

  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'

    ZappySys Driver - Create Custom Table

  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"

    ZappySys Driver - Execute Custom Virtual Table Query

  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''')

    ZappySys Driver - Generate SQL Server Query

  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.
    ZappySys Driver - Generate SQL Server Query

Conclusion

In this article we discussed how to connect to Nativo in Python and integrate data without any coding. Click here to Download Nativo 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 Nativo Connector for Python Documentation 

Actions supported by Nativo Connector

Nativo Connector support following actions for REST API integration. If some actions are not listed below then you can easily edit Connector file and enhance out of the box functionality.
 Read Campaign Data
   [Read more...]
Parameter Description
advertiser_id Return campaigns only for this advertiser.
 Read Advertisers Data
   [Read more...]
 Read Metrics
   [Read more...]
 Read DirectCampaign Data
   [Read more...]
 Read Preferred Campaign Data
   [Read more...]
 Read Managed Campaign Data
   [Read more...]
 Read Demand Campaign Data
   [Read more...]
 Read Auction Campaign Data
   [Read more...]
 Read Inventory Campaign Data
   [Read more...]
 Read Performance Campaign Data (Depriciated)
   [Read more...]
 Generic Request
This is generic endpoint. Use this endpoint when some actions are not implemented by connector. Just enter partial URL (Required), Body, Method, Header etc. Most parameters are optional except URL.    [Read more...]
Parameter Description
Url API URL goes here. You can enter full URL or Partial URL relative to Base URL. If it is full URL then domain name must be part of ServiceURL or part of TrustedDomains
Body Request Body content goes here
IsMultiPart Check this option if you want to upload file(s) (i.e. POST RAW file data) or send data using Multi-Part encoding method (i.e. Content-Type: multipart/form-data). Multi-Part request allows you to mix key/value and upload files in same request. On the other hand raw upload allows only single file upload (without any key/value) ==== Raw Upload (Content-Type: application/octet-stream) ===== To upload single file in raw mode check this option and specify full file path starting with @ sign in the Body (e.g. @c:\data\myfile.zip ) ==== Form-Data / Multipart Upload (Content-Type: multipart/form-data) ===== To treat your Request data as multi part fields you must specify key/value pairs separated by new lines into RequestData field (i.e. Body). Each key value pair is entered on new-line and key/value are separated using equal sign (=). Preceding and trailing spaces are ignored also blank lines are ignored. If field value has some any special character(s) then use escape sequence (e.g. For NewLine: \r\n, For Tab: \t, For at (@): \@). When value of any field starts with at sign (@) its automatically treated as File you want to upload. By default file content type is determined based on extension however you can supply content type manually for any field using this way [ YourFileFieldName.Content-Type=some-content-type ]. By default File Upload Field always includes Content-Type in the request (non file fields do not have content-type by default unless you supply manually). For some reason if you dont want to use Content-Type header in your request then supply blank Content-Type to exclude this header altogather [e.g. SomeFieldName.Content-Type= ]. In below example we have supplied Content-Type for file2 and SomeField1, all other fields are using default content-type. See below Example of uploading multiple files along with additional fields. If some API requires you to pass Content-Type: multipart/form-data rather than multipart/form-data then manually set Request Header =&gt; Content-Type: multipart/mixed (it must starts with multipart/ else will be ignored). file1=@c:\data\Myfile1.txt file2=@c:\data\Myfile2.json file2.Content-Type=application/json SomeField1=aaaaaaa SomeField1.Content-Type=text/plain SomeField2=12345 SomeFieldWithNewLineAndTab=This is line1\r\nThis is line2\r\nThis is \ttab \ttab \ttab SomeFieldStartingWithAtSign=\@MyTwitterHandle
Filter Enter filter to extract array from response. Example: $.rows[*] --OR-- $.customers[*].orders[*]. Check your response document and find out hierarchy you like to extract
Headers Headers for Request. To enter multiple headers use double pipe or new line after each {header-name}:{value} pair

Nativo Connector Examples for Python Connection

This page offers a collection of SQL examples designed for seamless integration with the ZappySys API ODBC Driver under ODBC Data Source (36/64) or ZappySys Data Gateway, enhancing your ability to connect and interact with Prebuilt Connectors effectively.

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