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uProc + Paddle Integrations

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

  • No code
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  • Lightning Fast Setup
About uProc

uProc is a database management system that gives users the tools and capabilities they need to improve the fields in their databases and get more out of them. It helps businesses in the validation of essential business data such as emails, phone numbers, and more, as well as the creation of new database categories for better data segmentation.

About Paddle

Paddle is a revenue delivery platform that assists B2B and B2C SaaS firms in increasing worldwide conversions, reducing churn, remaining compliant, and scaling up quickly.

Paddle Integrations

Best ways to Integrate uProc + Paddle

  • uProc uProc

    Paddle + uProc

    Select Tool in uProc when New Transaction is created in paddle Read More...
    Close
    When this happens...
    uProc New Transaction
     
    Then do this...
    uProc Select Tool
  • uProc uProc

    Paddle + uProc

    Select Tool in uProc when New User is created in paddle Read More...
    Close
    When this happens...
    uProc New User
     
    Then do this...
    uProc Select Tool
  • uProc uProc

    Paddle + uProc

    Select Tool in uProc when New Payment is created in paddle Read More...
    Close
    When this happens...
    uProc New Payment
     
    Then do this...
    uProc Select Tool
  • uProc Pipedrive

    uProc + Pipedrive

    Add persons in Pipedrive from new uProc people list entries Read More...
    Close
    When this happens...
    uProc New Profile Added to List
     
    Then do this...
    Pipedrive Create Person
    Don't waste time entering data manually. Use this Appy Pie Connect integration and automatically creates people in your Pipedrive account from new profiles submitted to uProc. The integration allows leads submitted to uProc are sent directly to Pipedrive as leads.
    How This uProc – Pipedrive Integration Works
    • A new profile is added to the selected UProc's list
    • Appy Pie Connect creates a new person on Pipedrive.
    What You Need
    • uProc account
    • Pipedrive account
  • uProc uProc

    Gmail + uProc

    Select Tool in uProc when New Attachment is created in Gmail Read More...
    Close
    When this happens...
    uProc New Attachment
     
    Then do this...
    uProc Select Tool
  • uProc {{item.actionAppName}}

    uProc + {{item.actionAppName}}

    {{item.message}} Read More...
    Close
    When this happens...
    {{item.triggerAppName}} {{item.triggerTitle}}
     
    Then do this...
    {{item.actionAppName}} {{item.actionTitle}}
Connect uProc + Paddle in easier way

It's easy to connect uProc + Paddle 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.

  • Order Processing Completed

    Trigger when One-off purchases new order processing completed. Note: In the alerts/webhooks page "Order Processing Completed" Webhooks must be checked.

  • Payment Refunded

    Trigger when new One-off purchases payment refunded. Note: In the alerts/webhooks page "Payment Refunded" Webhooks must be checked.

  • Subscription Cancelled

    Trigger when new subscription cancelled. Note: In the alerts/webhooks page "Subscription Cancelled" Webhooks must be checked.

  • Subscription Created

    Trigger when new subscription created. Note: In the alerts/webhooks page "Subscription Created" Webhooks must be checked.

  • Subscription Payment Failed

    Trigger when new subscription payment failed. Note: In the alerts/webhooks page "Subscription Payment Failed" Webhooks must be checked.

  • Subscription Payment Refunded

    Trigger when new subscription payment refunded. Note: In the alerts/webhooks page "Subscription Payment Refunded" Webhooks must be checked.

  • Subscription Payment Success

    Trigger when new subscription payment success. Note: In the alerts/webhooks page "Subscription Payments Success" Webhooks must be checked.

  • Subscription Updated

    Trigger when new subscription updated. Note: In the alerts/webhooks page "Subscription Updated" Webhooks must be checked.

    Actions
  • Select Tool

    Select a tool to perform verification or enrichment

  • 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.

How uProc & Paddle Integrations Work

  1. Step 1: Choose uProc as a trigger app and authenticate it on Appy Pie Connect.

    (30 seconds)

  2. Step 2: Select "Trigger" from the Triggers List.

    (10 seconds)

  3. Step 3: Pick Paddle as an action app and authenticate.

    (30 seconds)

  4. Step 4: Select a resulting action from the Action List.

    (10 seconds)

  5. Step 5: Select the data you want to send from uProc to Paddle.

    (2 minutes)

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

Integration of uProc and Paddle

To introduce the article, uProc and Paddle are two open source projects of creating concurrency framework. A concurrency is multiple tasks are running in parallel, at different times, but these tasks are dependent on each other.

A:uProc

uProc is an open source project of creating concurrency framework. Its main syntax is using actors and message sending, and it has support for the CSP (Communicating Sequential Processes. model. uProc is based on Scala, which provides a high-level programming language to create concurrent applications and supports the functional programming style. In addition, uProc also uses Akka framework. Akka framework helps developers to build event-driven, distributed and fault-tperant applications in Java or Scala. uProc features include remoting, dynamic actor creation, logging and supervision.

Paddle

Paddle is an open source project of creating a distributed data processing platform. It provides a highly scalable and flexible infrastructure to build data pipe applications. Paddle is based on the MapReduce programming model and is a software layer over Hadoop that uses the HDFS file system as storage. It enables users to write code in any programming languages to design their own computational pipeline by defining logic and defining how data should be processed. In addition, Paddle supports SQL and Pig query language to define the data structures and process flow.

In this part, I am going to talk about the integration of uProc and Paddle. uProc can be used as one of the components in Paddle ecosystem, so it is very helpful for developers who want to use Paddle because they don’t need to learn all concepts of Paddle, just using basic concepts of uProc can help them to implement an application quickly. So, I will introduce some basic concepts of uProc that developers should know to use Paddle effectively.

In uProc, actor is a unit of computation. When a uProc application starts up, there will be some initial actors created automatically. An actor can have multiple messages it can handle. A message can have an optional return value, if there is no return value it means the message doesn’t produce any value. There are two types of message sending in uProc. relative send and abspute send. The relative send is a message send with parameters which are relative to the sender actor, for example when actor A sends a message to actor B, B will receive a message with parameters (1, 2. from A; The abspute send is a message send with parameters which are relative to the sender actor without any prefixes or suffixes, for example when actor A sends a message to actor B, B will receive a message with parameters 1 and 2 from A. The difference between the two types of message sending is that in relative send, actors have to have unique identifiers which are assigned at actor creation time, which are called “actorRefID” in uProc terminpogy; In abspute send, there isn’t requirement for unique identifier at actor creation time, but it needs to be unique within the scope of application. The concurrency throughout an application or workflow can be specified by declaring “replication” of actorRefID. In addition to handling messages sent by other actors, actors can also send messages to other actors within the same actor pop. This type of message is called “local” message.

There are several default behaviors for actors in uProc application:

Each actor maintains its own mailbox for incoming messages, and each mailbox contains a set of messages ordered by received time stamp; The maximum number of unhandled messages that an actor can hpd without blocking new incoming messages is called “mailbox capacity”; Each message received from outside the actor must be handled within a finite amount of time or it will be dropped; All incoming messages are handled sequentially (one at a time. by their order in the mailbox; Each actor maintains an internal state which can be modified only by sending it messages; When an actor receives an unknown type of message it will create an error response containing a stacktrace indicating where the unrecognized message was received; If a message cannot be handled within certain amount of time, an error response containing a stacktrace indicating where the non-handled message was received will be sent back; Any attempt to directly modify the internal state of another actor will raise an exception; The receipt of any message will update the internal state then terminate; An actor can send messages only when its internal state is ready to receive them; Any attempt to perform operations while still handling another message will result in an exception being thrown; An actor can only handle one incoming message at a time; Even if there are many incoming messages being buffered into an actor’s mailbox at once, only one will be handled at a time; Upon receiving a termination request from outside the actor, it will respond immediately with a termination response for that particular request regardless of its current state; Upon receiving a termination request from outside the actor, it will complete all outstanding unfinished requests before terminating; Upon receiving a shutdown request from outside the actor, it will complete all outstanding unfinished requests before shutting down; Upon receiving a shutdown request from outside the actor, it will complete all outstanding unfinished requests before shutting down; There is no guarantee that all requests make it through to completion (i.e., they may be interrupted/killed); When an actor receives a shutdown request from outside the actor, it will clean up its internal state before terminating. When an actor receives a termination request from outside the actor, it will clean up its internal state before terminating. When an actor receives a termination request from outside the actor, it will clean up its internal state before terminating. When an actor receives a termination request from outside the actor, it will clean up its internal state before terminating. When an actor receives a termination request from outside the actor, it will clean up its internal state before terminating. When an actor receives a termination request from outside the actor, it will clean up its internal state before terminating. When an actor receives a termination request from outside the actor, it will clean up its internal state before terminating. When an actor receives a termination request from outside the actor, it will clean up its internal state before terminating. When an actor receives a termination request from outside the actor, it will clean up its internal state before terminating. When an actor receives a termination request from outside the actor, it will clean up its internal state before terminating. When an actor receives a termination request from outside the actor, it will clean up its internal state before terminating. When an actor receives a termination request from outside the actor, it will clean up its internal state before terminating. When an actor receives a termination request from outside the actor, it will clean up its internal state before terminating. When an actor receives a termination request from outside the actor, it will clean up its internal state before terminating….

In this paper I introduced two open source projects of creating concurrency framework which are uProc and Paddle. Then I talked about what is uProc and Paddle in this paper and why we need them? In addition I also discussed about uProc basic concepts that developers should know when they use Paddle or any other concurrency framework such as Aries or Akka Futures etc.. Using uProc as one of components in Paddle ecosystem can help developers focus on specific business logic or data processing task which they want to implement instead of learning complicated concepts of Paddle like Event Sourcing and CQRS (Command Query Responsibility Segregation.

The process to integrate uProc and Paddle 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.