Ylem documentation
  • 🗒️General information
    • Introduction to Ylem
    • Quick start guide
    • Release notes
  • 🔬Open-source edition
    • Installation
    • Usage of Apache Kafka
    • Task processing architecture
    • Configuring integrations with .env variables
  • 💡Integrations
    • Connecting an integration
    • Library of integrations
      • Amazon Redshift
      • Apache Kafka
      • APIs
      • Atlassian Jira
      • AWS Lambda
      • AWS RDS
      • AWS S3
      • ClickHouse
      • ElasticSearch
      • E-mail
      • Google Big Query
      • Google Cloud SQL
      • Google Pub/Sub
      • Google Sheets
      • Immuta
      • Incident.io
      • Jenkins
      • Hubspot
      • Microsoft Azure SQL
      • MySQL
      • OpenAI ChatGPT
      • Opsgenie
      • PostgreSQL
      • PlanetScale
      • RabbitMQ
      • Salesforce
      • Slack
      • Snowflake
      • Tableau
      • Twilio. SMS
      • WhatsApp (through Twilio)
    • Initial demo data source
  • 🚡Pipelines
    • Pipeline management
    • Tasks
      • Aggregator
      • API Call
      • Code
      • Condition
      • External trigger
      • Filter
      • For each
      • GPT
      • Merge
      • Notification
      • Query
      • Pipeline runner
      • Processor
      • Transformer
    • Running and scheduling pipelines
    • Library of templates
    • Environment variables
    • Mathematical functions and operations
    • Formatting of messages
  • 📈Statistics and profiling
    • Statistics of runs
    • Slow tasks
  • 📊Metrics
    • Metric management
    • Using previous values of a metric
  • 💼Use cases, patterns, templates, examples
    • Use cases
    • Messaging patterns
      • Datatype Channel
      • Message Dispatcher
      • Messaging Bridge
      • Message Bus
      • Message Filter
      • Message Router
      • Point-to-Point Channel
      • Publish-Subscribe Channel
      • Pull-Push
    • Functional use cases
      • Streaming from Apache Kafka and messaging queues
      • Streaming from APIs
      • Streaming from databases
      • Data orchestration, transformation and processing
      • Usage of Python and Pandas
      • KPI Monitoring
      • OKRs and custom metrics
      • Data Issues & Incidents
      • Reporting
      • Other functional use cases
    • Industry-specific use cases
      • Finance and Payments
      • E-commerce & Logistics
      • Customer Success
      • Security, Risk, and Anti-Fraud
      • Anti-Money Laundering (AML)
  • 🔌API
    • OAuth clients
    • API Reference
  • 👁️‍🗨️Other resources
    • FAQ
    • Our blog on Medium
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  1. Pipelines
  2. Tasks

API Call

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Last updated 1 year ago

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The "API Call" can be used at the beginning of the pipeline to read data from a certain API Endpoint and also at the end to send data to a certain external or internal API. API Endpoints are configured in the .

The task supports all the attributes of a normal API Call when it is done from the command line using curl or a software like Postman, such as body payload, headers, and query strings.

Here is an example of how to use it for sending some input data in the Body of the POST request:

You can also attach files, dynamically created from the input dataset to it. For example, if in front of the "API call" you place a "" that converts input to CSV, the result can be sent further as a .csv file.

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