A declarative text parsing library for Elixir that makes it easy to extract structured data from unstructured text using a simple, composable DSL.
- Declarative DSL: Define field extraction rules using a clean, readable syntax
- Pattern Matching: Use regex patterns to locate and capture data
- Custom Extractors: Define custom extraction logic using functions
- Data Transformation: Transform captured values with custom functions
- Component-based: Organize extraction logic into reusable components
- Type-safe: Works seamlessly with Elixir's pattern matching and type system
Add Parselet to your dependencies in mix.exs:
def deps do
[
{:parselet, "~> 0.1"}
]
endThen run mix deps.get.
Create a module using Parselet.Component and define fields to extract:
defmodule MyApp.Components.EmailParser do
use Parselet.Component
field :sender,
pattern: ~r/From:\s*(.+)/,
capture: :first,
transform: &String.trim/1
field :subject,
pattern: ~r/Subject:\s*(.+)/,
capture: :first
field :date,
pattern: ~r/Date:\s*(.+)/,
capture: :first
endUse Parselet.parse/2 to extract data:
email_text = """
From: alice@example.com
Subject: Meeting Tomorrow
Date: 2026-03-27
"""
result = Parselet.parse(email_text, components: [MyApp.Components.EmailParser])
# Result:
# %{
# sender: "alice@example.com",
# subject: "Meeting Tomorrow",
# date: "2026-03-27"
# }The main module for defining extraction components.
Define a field to extract from text.
Options:
:pattern- Regex pattern to match. Capture groups are extracted automatically.:capture- How to capture::first(default, returns first capture group) or:all(returns all capture groups as a list):transform- Optional function to transform the captured value. Default is identity function (& &1).:function- Custom extraction function. Takes the full text as input and returns the extracted value. Alternative to:pattern.:required- Boolean (defaultfalse). Mark field as required. Use withParselet.parse!/2for validation.
Examples:
# Simple pattern matching
field :email,
pattern: ~r/Email:\s*(\S+@\S+)/,
capture: :first
# Capture multiple groups
field :date_range,
pattern: ~r/(\d{4})-(\d{2})-(\d{2})/,
capture: :all
# Transform captured value
field :count,
pattern: ~r/Count:\s*(\d+)/,
capture: :first,
transform: &String.to_integer/1
# Custom extraction function
field :listing_name,
function: fn text ->
text
|> String.split("\n")
|> Enum.find(&String.contains?(&1, ["Apartment", "House"]))
end
# Mark as required
field :reservation_code,
pattern: ~r/Code:\s+([A-Z0-9]+)/,
capture: :first,
required: trueParse text using one or more components.
Parameters:
text- String to parsecomponentsorstructs- List of component modules to use for extraction
Returns: Map with extracted fields. Only fields that matched are included.
Examples:
result = Parselet.parse(text, components: [Component1, Component2])
# Fields from both components are merged into one map# Returns struct(s) when using `structs` option
result = Parselet.parse(text, structs: [MyApp.Components.EmailParser])
# => %MyApp.Components.EmailParser{sender: "alice@example.com", subject: "Meeting Tomorrow", date: "2026-03-27"}
# Multiple structs returned as a map when passing more than one module
result = Parselet.parse(text, structs: [Component1, Component2])
# => %{Component1 => %Component1{}, Component2 => %Component2{}}Parse text with validation of required fields.
Parameters:
text- String to parsecomponentsorstructs- List of component modules to use for extraction
Returns: Map with extracted fields (same as parse/2)
Raises: ArgumentError if any required fields are missing
Example:
result = Parselet.parse!(text, components: [Component1])
# Raises ArgumentError if any fields marked as required: true are not foundHere's a complete example parsing Airbnb reservation emails:
defmodule MyApp.Components.AirbnbReservation do
use Parselet.Component
# Simple extraction with trimming
field :reservation_code,
pattern: ~r/Reservation code[:\s]+([A-Z0-9\-]+)/i,
capture: :first
# Extract and trim whitespace
field :guest_name,
pattern: ~r/Reservation for\s+([^\n]+)/i,
capture: :first,
transform: &String.trim/1
# Multiple captures transformed into structured data
field :date_range,
pattern: ~r/([A-Za-z]{3} \d{1,2})\s*–\s*([A-Za-z]{3} \d{1,2})/,
capture: :all,
transform: &normalize_dates/1
# Numeric extraction
field :nights,
pattern: ~r/(\d+)\s+nights?/i,
capture: :first,
transform: &String.to_integer/1
# Currency extraction
field :payout_amount,
pattern: ~r/Payout[:\s]+\$?([\d,]+\.\d{2})/i,
capture: :first,
transform: fn amt ->
amt
|> String.replace(",", "")
|> String.to_float()
end
# Complex custom extraction
field :listing_name,
function: fn text ->
text
|> String.split("\n")
|> Enum.map(&String.trim/1)
|> Enum.reject(&(&1 == ""))
|> Enum.find(fn line ->
String.contains?(line, ["Apartment", "House"]) and
not String.match?(line, ~r/^\d+\s+guests?/i)
end)
end
defp normalize_dates([start_date, end_date]) do
%{
start: start_date,
end: end_date
}
end
end
# Usage
email = File.read!("reservation.txt")
result = Parselet.parse(email, components: [MyApp.Components.AirbnbReservation])
# Result might be:
# %{
# reservation_code: "ABC123XYZ",
# guest_name: "Alice Johnson",
# date_range: %{start: "Mar 28", end: "Apr 3"},
# nights: 6,
# payout_amount: 5452.22,
# listing_name: "Beachfront Apartment"
# }Parselet shines when you need to extract data from complex documents that contain multiple types of information. Here's an example of processing an invoice that contains both header information and line items:
defmodule MyApp.Components.InvoiceHeader do
use Parselet.Component
field :invoice_number,
pattern: ~r/Invoice\s*#?\s*([A-Z0-9\-]+)/i,
capture: :first,
required: true
field :invoice_date,
pattern: ~r/Date:\s*([^\n]+)/i,
capture: :first,
transform: &parse_date/1
field :customer_name,
pattern: ~r/Customer:\s*([^\n]+)/i,
capture: :first,
transform: &String.trim/1
field :total_amount,
pattern: ~r/Total:\s*\$?([\d,]+\.\d{2})/i,
capture: :first,
transform: fn amt ->
amt
|> String.replace(",", "")
|> String.to_float()
end,
required: true
defp parse_date(date_string) do
# Simple date parsing - in real code you'd use a proper date library
case Regex.run(~r/(\d{4})-(\d{2})-(\d{2})/, date_string) do
[_, year, month, day] ->
Date.from_iso8601!("#{year}-#{month}-#{day}")
_ ->
date_string # Return as string if parsing fails
end
end
end
defmodule MyApp.Components.InvoiceItems do
use Parselet.Component
field :line_items,
function: fn text ->
# Extract all line items from the invoice
text
|> String.split("\n")
|> Enum.map(&String.trim/1)
|> Enum.filter(&String.match?(&1, ~r/^\d+\.\s+.+\s+\$\d/))
|> Enum.map(&parse_line_item/1)
end
field :item_count,
function: fn text ->
# Count the number of line items
text
|> String.split("\n")
|> Enum.count(&String.match?(&1, ~r/^\d+\.\s+.+\s+\$\d/))
end
field :subtotal,
pattern: ~r/Subtotal:\s*\$?([\d,]+\.\d{2})/i,
capture: :first,
transform: fn amt ->
amt
|> String.replace(",", "")
|> String.to_float()
end
field :tax_amount,
pattern: ~r/Tax:\s*\$?([\d,]+\.\d{2})/i,
capture: :first,
transform: fn amt ->
amt
|> String.replace(",", "")
|> String.to_float()
end
defp parse_line_item(line) do
case Regex.run(~r/^(\d+)\.\s+(.+?)\s+\$([\d,]+\.\d{2})$/, line) do
[_, quantity, description, price] ->
%{
quantity: String.to_integer(quantity),
description: String.trim(description),
unit_price: price |> String.replace(",", "") |> String.to_float()
}
_ ->
nil
end
end
end
# Usage - parse with both components
invoice_text = """
INVOICE #INV-2026-001
Date: 2026-03-27
Customer: Acme Corporation
Line Items:
1. Office Chair $299.99
2. Desk Lamp $89.50
3. Keyboard $129.99
Subtotal: $519.48
Tax: $41.56
Total: $561.04
"""
result = Parselet.parse(invoice_text, components: [
MyApp.Components.InvoiceHeader,
MyApp.Components.InvoiceItems
])
# Result combines fields from both components:
# %{
# invoice_number: "INV-2026-001",
# invoice_date: ~D[2026-03-27],
# customer_name: "Acme Corporation",
# total_amount: 561.04,
# line_items: [
# %{quantity: 1, description: "Office Chair", unit_price: 299.99},
# %{quantity: 2, description: "Desk Lamp", unit_price: 89.50},
# %{quantity: 3, description: "Keyboard", unit_price: 129.99}
# ],
# item_count: 3,
# subtotal: 519.48,
# tax_amount: 41.56
# }This example demonstrates:
- Component Separation: Header info and line items are logically separated into different components
- Complex Extraction: Using custom functions for parsing structured line items
- Data Transformation: Converting strings to dates, numbers, and structured data
- Field Combination: All fields from both components are merged into a single result map
- Required Fields: Ensuring critical fields like invoice number and total are present
Bad:
field :amount, pattern: ~r/([\d.]+)/Good:
field :amount, pattern: ~r/Total:\s*\$([\d,]+\.\d{2})/iDon't extract strings when you need numbers:
Bad:
field :count, pattern: ~r/Count: (\d+)/
# Returns: "42" (string)Good:
field :count,
pattern: ~r/Count: (\d+)/,
transform: &String.to_integer/1
# Returns: 42 (integer)When regex patterns become too complex, use a custom function:
field :main_content,
function: fn text ->
text
|> String.split("\n")
|> Enum.find(&is_main_content?/1)
endFields that don't match simply won't appear in the result map:
result = Parselet.parse(text, components: [MyComponent])
# Access with safe defaults
name = Map.get(result, :name, "Unknown")Organize related fields into separate components:
result = Parselet.parse(text, components: [
MyApp.Components.Header,
MyApp.Components.Body,
MyApp.Components.Footer
])field :email,
pattern: ~r/[\w\.-]+@[\w\.-]+\.\w+/,
capture: :firstfield :phone,
pattern: ~r/(?:\+1[\s.-]?)?\(?(\d{3})\)?[\s.-]?(\d{3})[\s.-]?(\d{4})/,
capture: :all,
transform: fn [area, exchange, line] ->
"(#{area}) #{exchange}-#{line}"
endfield :date,
pattern: ~r/(\d{4})-(\d{2})-(\d{2})/,
capture: :all,
transform: fn [year, month, day] ->
Date.from_iso8601!("#{year}-#{month}-#{day}")
endfield :price,
pattern: ~r/\$?([\d,]+\.\d{2})/,
capture: :first,
transform: fn amount ->
amount
|> String.replace(",", "")
|> String.to_float()
endfield :url,
pattern: ~r/https?:\/\/[^\s]+/,
capture: :firstExample test for a component:
defmodule MyApp.Components.EmailParserTest do
use ExUnit.Case, async: true
alias MyApp.Components.EmailParser
test "parses email address" do
text = "From: alice@example.com"
result = Parselet.parse(text, components: [EmailParser])
assert result.sender == "alice@example.com"
end
test "returns empty map when no fields match" do
text = "Invalid content"
result = Parselet.parse(text, components: [EmailParser])
assert result == %{}
end
test "includes only matched fields" do
text = "From: bob@example.com\nSubject: Test"
result = Parselet.parse(text, components: [EmailParser])
assert Map.has_key?(result, :sender)
assert Map.has_key?(result, :subject)
assert !Map.has_key?(result, :date)
end
end-
Check the regex pattern
# Test your regex first Regex.run(~r/your_pattern/, text)
-
Verify case sensitivity
# Use /i flag for case-insensitive matching pattern: ~r/Pattern:/i
-
Check capture groups
:firstcaptures only the first group:allcaptures all groups
# This captures 2 groups pattern: ~r/(\d{4})-(\d{2})/ capture: :all # Returns ["2026", "03"]
Ensure your transform function handles the input type correctly:
# This will fail if input is a list
transform: &String.to_integer/1
# Use :all capture? Transform receives a list
field :date,
pattern: ~r/(\d{4})-(\d{2})-(\d{2})/,
capture: :all,
transform: fn [year, month, day] -> "#{year}-#{month}-#{day}" end- Patterns are compiled once at compile-time, so regex performance is optimal
- Multiple components are evaluated independently; you can parse with multiple components efficiently
- Transformation functions are called only for matched fields
This project is part of MyApp.