Coming from Alteryx

If you're an Alteryx user, you're already familiar with visual workflows and the power of drag-and-drop data transformation. Sigilweaver follows similar principles with some key differences.

Terminology Mapping

Alteryx	Sigilweaver	Notes
Workflow (yxmd)	Workflow (swwf)	Both are saved files
Tool	Tool	Dragged from palette onto canvas
Connection	Wire	Links between tools
Browse Tool	Data Preview	Click any tool to inspect output
Input Data Tool	Input tool	Load CSV, Parquet, Excel
Output Data Tool	Output tool	Save to various formats
Select Tool	Select tool	Choose, rename, reorder, cast columns
Filter Tool	Filter tool	Split data on condition
Summarize Tool	Summarize tool	Group and aggregate
Join Tool	Join tool	Combine datasets
Union Tool	Union tool	Stack datasets vertically
Formula Tool	Formula tool	Create calculated columns
Sort Tool	Sort tool	Order rows by columns

Common Tasks

Loading Data

Alteryx:
Drag Input Data tool → Browse for file → Auto-preview

Sigilweaver:
Drag Input tool → Pick your file → Preview after execution

Filtering Rows

Alteryx:
Drag Filter tool → Build expression with GUI → True/False outputs

Sigilweaver:
Drag Filter tool → Write Polars expression like pl.col("amount") > 100 → T/F outputs

Key difference: Sigilweaver uses code-based expressions instead of Alteryx's expression builder GUI. More concise, but requires learning the Polars syntax.

Creating Calculated Columns

Alteryx:
Drag Formula tool → Name new column → Build expression

Sigilweaver:
Drag Formula tool → Write expression like pl.col("price") * 1.1 → Name the output column

Both tools create new columns or replace existing ones.

Selecting Columns

Alteryx:
Drag Select tool → Check/uncheck columns → Rename if needed

Sigilweaver:
Drag Select tool → Configure columns to keep/remove → Rename, reorder, or cast types

Aggregating Data

Alteryx:
Drag Summarize tool → Group By columns → Add aggregations (Sum, Count, etc.)

Sigilweaver:
Drag Summarize tool → Set columns to "Group By" → Choose aggregation type for each metric column

Joining Tables

Alteryx:
Drag Join tool → Connect L and R inputs → Configure join keys → J/L/R outputs

Sigilweaver:
Drag Join tool → Wire left (L) and right (R) inputs → Configure keys → Three outputs: J (matched), L (unmatched left), R (unmatched right)

Same concept! Sigilweaver's join outputs work exactly like Alteryx's J/L/R anchors.

Key Differences

1. Expression Syntax

Alteryx uses its own expression language with functions like [Field1] + [Field2] and IF-THEN-ELSE.

Sigilweaver uses Polars expressions:

# Column reference
pl.col("field_name")

# Calculation
pl.col("price") * pl.col("quantity")

# Conditional (like IF-THEN-ELSE)
pl.when(pl.col("status") == "active")
  .then(pl.col("price"))
  .otherwise(0)

The Expressions Guide covers everything you need.

2. Lazy Evaluation

Alteryx executes tools as you run the workflow. Sigilweaver uses lazy evaluation:

• Workflow is optimized before execution
• Operations are only executed when needed (preview or save)
• Enables processing datasets larger than memory

3. No Visual GUI Builders

Alteryx has visual configuration for many operations (Select Records, Expression Builder, etc.). Sigilweaver relies more on text-based configuration:

• Faster for experienced users
• More concise and reproducible
• Requires learning expression syntax upfront

4. Cross-Platform Desktop App

Alteryx is Windows-only. Sigilweaver runs natively on Linux, macOS, and Windows.

Your First Workflow

Let's build a common Alteryx pattern: load transaction data, filter for completed orders, calculate revenue, and summarize by product.

Steps:

1. Load transactions:

   • Drag Input tool to canvas
   • Pick your CSV file
   • Click to preview data

2. Filter for completed orders:

   • Drag Filter tool, wire from Input
   • Expression: pl.col("order_status") == "completed"
   • Use the T output for next step

3. Calculate revenue:

   • Drag Formula tool, wire from Filter's T output
   • Expression: pl.col("price") * pl.col("quantity")
   • Output column name: revenue

4. Summarize by product:

   • Drag Summarize tool, wire from Formula
   • Set product_name to Group By
   • Set revenue to Sum
   • Set order_id to Count (for order count)

5. Save results:

   • Drag Output tool, wire from Summarize
   • Configure output path (CSV, Parquet, or Excel)
   • Execute workflow

Performance Note

Alteryx is fast. Sigilweaver is also fast—it's built on Polars, a Rust-based dataframe library designed for performance. For most workloads, performance is comparable. The lazy evaluation model can actually be faster for complex workflows since Sigilweaver optimizes the entire pipeline before executing.

Next Steps

• Interface Guide - Canvas navigation, shortcuts, and tips
• Expressions Basics - Learn Polars expression syntax
• Tools Reference - Detailed docs for every tool

If you're comfortable with Alteryx workflows, you'll adapt to Sigilweaver quickly. The main learning curve is the expression language, but it becomes second nature with practice.