Create your first pipeline

After discovering Bethemesh tools and experimenting with the Workspace, you’ll quickly notice that many workflows are repeated over time. You clean a CSV file, rename columns, sort the data, export the result… and a few days later you find yourself performing exactly the same sequence again.

Pipelines were designed to eliminate this repetitive work.

Instead of rebuilding the same workflow every time, you can save it once and reuse it whenever you need it.

What is a pipeline?

A pipeline is a reusable description of your workflow.

It usually does not contain your files. Instead, it stores everything needed to reproduce the same processing:

• the modules used;
• their execution order;
• their settings;
• the connections between each step.

You can think of a pipeline as a cooking recipe. The recipe explains how to prepare the meal, but it does not contain the ingredients themselves.

This approach lets you preserve your workflows without unnecessarily storing the data used to create them.

Before creating your first pipeline

Before saving a pipeline, it’s a good idea to build and validate a complete workflow inside the Workspace.

Start with a real task.

For example:

• removing duplicate rows from a CSV file;
• renaming several columns;
• sorting records;
• exporting a clean dataset.

Once everything works as expected, you can save the workflow for future use.

Trying to automate an unfinished process usually creates more work than it saves.

Build your workflow

The Workspace allows you to add modules one step at a time.

Each module performs one specific operation.

For example:

Import CSV
      ↓
Remove duplicates
      ↓
Rename columns
      ↓
Sort data
      ↓
Export result

After each step, you can immediately verify the output before moving on.

This makes complex processing much easier to understand, debug, and improve.

Test before saving

Take a few minutes to test your workflow before turning it into a pipeline.

Run it with different datasets.

Check that every module behaves as expected and that the final output matches your objective.

A well-tested pipeline can then be reused many times without requiring additional adjustments.

Save your pipeline

Once you’re satisfied with your workflow, save it.

Choose a descriptive name.

Examples include:

• Partner CSV Cleanup
• Website Image Optimization
• Monthly PDF Reports
• Event QR Code Generator

A meaningful name makes your pipeline much easier to find several weeks or months later.

Reuse your pipeline

This is where pipelines become truly valuable.

The next time you need the same processing, simply reopen the saved pipeline.

You’ll instantly recover:

• every module;
• every configuration;
• the complete execution order.

Instead of rebuilding your workflow from scratch, you simply provide new input data and run it again.

Common mistakes

New users often make the same mistakes.

Saving too early

Build and validate your workflow before creating a reusable pipeline.

Trying to automate everything

Not every task deserves its own pipeline.

If you only perform an operation once, a standalone tool is often the simplest solution.

Choosing vague names

Avoid names such as:

• Test
• Pipeline 1
• New Pipeline

Instead, use names that clearly describe the workflow’s purpose.

Best practices

To keep your pipeline library organized:

• create one pipeline for one objective;
• always test your workflow before saving it;
• use descriptive names;
• delete obsolete pipelines;
• improve existing pipelines instead of creating unnecessary duplicates.

A well-organized library quickly becomes one of the most valuable parts of your Workspace.

What’s next?

Once you’ve created your first pipeline, you’ll be ready to explore more advanced capabilities.

You’ll be able to:

• reuse the same workflow with different files;
• improve it as your needs evolve;
• synchronize it across multiple devices when synchronization is enabled;
• build a personal library of reusable workflows.

Over time, your pipelines become much more than saved workflows. They become reliable building blocks that help you automate repetitive tasks, preserve your best practices, and get the most out of Bethemesh.