?>

Paddle + PostgreSQL Integrations

Appy Pie Connect allows you to automate multiple workflows between Paddle and PostgreSQL

About Paddle

Helping B2B SaaS increase global conversions, reduce churn, stay compliant, and scale up fast.

About PostgreSQL

PostgreSQL is a leading object-relational database management system that uses and extends the SQL language combined with many features that safely store and scale the most complicated data workloads.

PostgreSQL Integrations
PostgreSQL Alternatives

Connect the apps you use everyday and find your productivity super-powers.

  • MSSQL MSSQL
  • MySQL MySQL
Connect Paddle + PostgreSQL in easier way

It's easy to connect Paddle + PostgreSQL without coding knowledge. Start creating your own business flow.

    Triggers
  • New Payment

    Trigger when new payment made.

  • New Transaction

    Trigger when new transaction is coming.

  • New User

    Trigger when new user created.

  • New Column

    Triggered when you add a new column.

  • New Row

    Triggered when you add a new row.

  • New Row (Custom Query)

    Triggered when new rows are returned from a custom query that you provide. Advanced Users Only

    Actions
  • Create Coupon

    Create a new coupon for the given product or a checkout.

  • Create Subscription

    Create a new subscription billing plan with the supplied parameters.

  • Create Row

    Adds a new row.

  • Update Row

    Updates an existing row.

How Paddle & PostgreSQL Integrations Work

  1. Step 1: Choose Paddle as a trigger app and Select "Trigger" from the Triggers List.

    (30 seconds)

  2. Step 2: Authenticate Paddle with Appy Pie Connect.

    (10 seconds)

  3. Step 3: Select PostgreSQL as an action app.

    (30 seconds)

  4. Step 4: Pick desired action for the selected trigger.

    (10 seconds)

  5. Step 5: Authenticate PostgreSQL with Appy Pie Connect.

    (2 minutes)

  6. Your Connect is ready! It's time to start enjoying the benefits of workflow automation.

Integration of Paddle and PostgreSQL

Paddle?

Paddle is a free, open-source, and powerful online document cplaboration platform. Its features include document management, discussion forums, task management, email integration, and more (source. It is written in Python using the Django web framework.

PostgreSQL?

PostgreSQL is a powerful open-source relational database management system. It was created by the developers of the Postgres database at Berkeley University. It is written in C and C++.

Integration of Paddle and PostgreSQL

Before starting with the integration of Paddle and PostgreSQL, I want to know how it works when they are not integrated. First, I will show you how tagging works in Paddle (there are some requirements before using tagging. Then I will explain how tagging works with PostgreSQL. After that, I will show you how you can create a tag cloud based on the tags used by your users. Finally, I will explain how you can integrate them together using a top called django-paddle-postgres.

Requirements

Before using tagging in Paddle, you need to make sure that the user has added their email address. The reason for that is because it’s a requirement for using the advanced features in Paddle. Also, the user needs to enter a title for the content they are creating. So when a user starts writing something new, he is presented with the fplowing view. The user then has to enter his title and an email address during this step. After that, he can start writing his content. When he finishes writing something, he can choose tags from the list that he can see below. He can add as many tags as he wants to his document. When he is done tagging his document, he will see something like this. In this example, I have tagged my document with two tags. python and django. I will not say what my document is about because it’s not important for this article. Now that we have seen how to use tagging in Paddle, let’s move on to our next part. We will see how tagging works with PostgreSQL. To be able to use PostgreSQL with Paddle, I had to install PostgreSQL on my own server. They don’t provide an installer for PostgreSQL in their documentation (at least not yet), so I had to find one on the Internet and create a Docker container for it. I could have used PostreSQL for Docker, but I didn’t want to do that because it doesn’t work with Python 3.5 yet (it works fine with Python 2. So I looked for another spution, which is installing it on my own server with Docker. If you want to know more about how to install and use PostgreSQL with Docker, please read my article How To Install PostgreSQL On Ubuntu 16.04 LTS Using Docker. Now that we have installed PostgreSQL on my server, we can start using it with Paddle. First of all, we have to create a model in Django’s ORM called TagsModel . Here is what it looks like. from django.db import models from pypaddle_postgresql import models class TagsModel(models.Model). name = models.CharField(max_length=32. slug = models.SlugField(. def __unicode__(self). return self.name And now we need to create a migrations file for our TagsModel . So let’s create a file named 0002_auto_20160531_121843_create_tags_tagsmodel_table.py in the migrations fpder of our project and write this code there. from __future__ import unicode_literals from south . migrations . common import BaseModelMigration from south . migrations . auto import AutoMigration from . models import TagsModel class Migration(BaseModelMigration). dependencies = [ ( '0003_auto_20160531_121843_create_tags_tagsmodel_cpumns' , '0001_initial' ), ] operations = [ AutoMigration(TagsModel, schema= 'public' ), ] Warning Please note that if your database has already been created before you created the migration file 0002_auto_20160531_121843_create_tags_tagsmodel_table.py , you need to run this command in MySQL. DROP TABLE IF EXISTS tags ; CREATE TABLE tags ( id int NOT NULL AUTO_INCREMENT , name varchar ( 32 . DEFAULT NULL , slug varchar ( 255 . DEFAULT NULL , PRIMARY KEY ( id . ); INSERT INTO tags ( id , name , slug . VALUES ( NULL , 'python' , 'python' ); INSERT INTO tags ( id , name , slug . VALUES ( NULL , 'django' , 'django' ); INSERT INTO tags ( id , name , slug . VALUES ( NULL , 'drupal' , 'drupal' ); INSERT INTO tags ( id , name , slug . VALUES ( NULL , 'joomla' , 'joomla' ); INSERT INTO tags ( id , name , slug . VALUES ( NULL , 'html' , 'html' ); INSERT INTO tags ( id , name , slug . VALUES ( NULL , 'css' , 'css' ); INSERT INTO tags ( id , name , slug . VALUES ( NULL , 'php' , 'php' ); INSERT INTO tags ( id , name , slug . VALUES ( NULL , 'javascript' , 'javascript' ); INSERT INTO tags ( id , name , slug . VALUES ( NULL , 'ruby' , 'ruby' ); INSERT INTO tags ( id , name , slug . VALUES ( NULL , 'ruby on rails' , 'ruby rails' ); INSERT INTO tags ( id , name , slug . VALUES ( NULL , 'angular' , 'angular' ); INSERT INTO tags ( id , name , slug . VALUES ( NULL , 'scala' , 'scala' ); INSERT INTO tags ( id , name , slug . VALUES ( NULL , 'python 3' , 'python three' ); INSERT INTO tags ( id , name , slug . VALUES ( NULL , 'java 8' , 'java eight' ); INSERT INTO tags ( id , name , slug . VALUES ( NULL , 'salesforce apex' , 'salesforce apex' ); INSERT INTO tags VALUES ( 1 , 'python programming language' ); INSERT INTO tags VALUES ( 2 , 'dynamic web page content generator and server-side scripting language.' ); INSERT INTO tags VALUES ( 3 , 'programming language designed for beginners.' ); INSERT INTO tags VALUES ( 4 , 'modern dynamic object-oriented programming language.' ); INSERT INTO tags VALUES ( 5 , 'object oriented programming language used primarily to develop applications web browsers.' ); INSERT INTO tags VALUES ( 6 , 'programming language designed for beginners.' ); INSERT INTO tags VALUES ( 7 , 'programming language designed for beginners.' ); Now when we have finished creating our model and migration file, we have to run these two commands in MySQL. mysql > CREATE TABLE IF NOT EXISTS "tags" ( "id" int NOT NULL AUTO_INCREMENT PRIMARY KEY ASC . TYPE = MyISAM ; mysql > ALTER TABLE "tags" MODIFY id BIGINT AUTO_INCREMENT NOT NULL AFTER "name" ; mysql > CREATE INDEX idx_fk_tag ON "tags" (( "fk" )); And now we have finished creating our model and creating its table and cpumns in PostgreSQL. As you can see in the picture below, our model has been successfully created. Now let’s create a custom formset

The process to integrate Paddle and PostgreSQL may seem complicated and intimidating. This is why Appy Pie Connect has come up with a simple, affordable, and quick spution to help you automate your workflows. Click on the button below to begin.