🤹Tasks

Tasks are the building blocks of Ignite Scenarios, designed to perform specific actions or operations within the wallet access management process. Each task represents a discrete function or step in the workflow, which can be combined with other tasks to create complex, event-driven scenarios.

Tasks are executed sequentially within an Ignite Scenario, with the output of one task serving as the input for the next task in the chain. This enables you to create multi-step processes with conditional logic and data manipulation capabilities, allowing for unparalleled flexibility and customization.

Some examples of tasks include:

• Retrieving external data or information

• Performing calculations or transformations on data

• Generating signatures or keys

• Updating the state of the system or wallet

• Triggering other scenarios or tasks based on specific conditions

By composing your Ignite Scenarios with a combination of tasks, you can create custom workflows that cater to your specific wallet access management requirements. This modular approach ensures that your processes remain agile and adaptable, allowing you to quickly respond to changes in your environment or business needs.

Pipelines

DOT syntax is a simple and powerful way to define the structure and relationships between tasks in Ignite Scenarios. It allows you to create a visual representation of your workflow by defining nodes (tasks) and edges (connections between tasks). This representation takes the form of a Directed Acyclic Graph (DAG), a graph with directed edges and no cycles.

A DAG is particularly useful for modeling complex workflows because it ensures that tasks can only move in one direction, from a starting point to an end point, without loops or circular dependencies. This linear progression helps to maintain the integrity of the data flow and makes it easier to manage and understand the relationships between tasks.

In a DAG, tasks are represented as nodes, and the directed edges between nodes signify the data flow between tasks. The output of one task is passed as input to the next task in the sequence, creating a clear path of data through the workflow. This data flow is critical for tasks that rely on the output of previous tasks or for tasks that need to manipulate data from multiple sources.

Here's a simple example of DOT syntax to represent a DAG:

{
  TaskA -> TaskB;
  TaskB -> TaskC;
  TaskC -> TaskD;
}

In this example, the workflow consists of four tasks (TaskA, TaskB, TaskC, and TaskD) connected by directed edges. The workflow starts with TaskA, which passes its output to TaskB. TaskB then processes the data and passes its output to TaskC, and so on until the workflow reaches its end at TaskD.

By leveraging DOT syntax and the DAG structure, you can create clear, concise, and efficient workflows for your Ignite Scenarios, ensuring the proper flow of data and the execution of tasks in the correct order.

Example

data_source_1  [type="http" method=GET url="https://chain.link/eth_usd"]
data_source_2  [type="http" method=GET url="https://coingecko.com/eth_usd"]
medianize_data [type="median"]
submit_to_ea   [type="bridge" name="my_bridge"]

data_source_1 -> medianize_data
data_source_2 -> medianize_data
medianize_data -> submit_to_ea