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Minimal DSL for API data extraction

Project description

Siphon

A minimal DSL for extracting data from JSON APIs.

Like a siphon draws liquid from a container, Siphon draws the data you need from nested JSON structures—just define the paths, and let it flow.

Install

pip install siphon-dsl

Or with uv:

uv add siphon-dsl

Quick Start

from siphon import process

data = {
    "data": {
        "id": "prod_123",
        "items": [
            {"id": 1, "status": "active", "name": "Widget"},
            {"id": 2, "status": "inactive", "name": "Gadget"},
            {"id": 3, "status": "active", "name": "Thing"},
        ],
    }
}

spec = {
    "extract": {
        "id": "$.data.id",
        "all_active": {
            "path": "$.data.items[*]",
            "where": {"status": "active"},
            "select": {"item_id": "id", "item_name": "name"},
            "collect": True,
        },
    }
}

result = process(spec, data)

Output:

{
  "id": "prod_123",
  "all_active": [
    {"item_id": 1, "item_name": "Widget"},
    {"item_id": 3, "item_name": "Thing"}
  ]
}

Features

Feature Syntax Description
Simple paths $.data.id Extract nested values
Array iteration $.items[*].name Traverse arrays
Filtering where: {status: "active"} Filter by field values
Ancestor filtering where: {parentId: 123} Filter by parent-level properties
Projection select: {new: "old"} Rename and reshape fields
Collect collect: true Return all matches (default: first only)
Reduce reduce: "min_time" Aggregate array values to a single result

Spec Format

Simple extraction

extract:
  id: "$.data.id"
  name: "$.data.name"

Extended extraction

extract:
  active_items:
    path: "$.data.items[*]"
    where: {status: "active"}
    select: {item_id: "id", item_name: "name"}
    collect: true

Reduce (aggregation)

extract:
  earliest_slot:
    path: "$.items[*].from_datetime"
    reduce: min_time          # earliest time-of-day across all items

  latest_slot:
    path: "$.items[*].to_datetime"
    reduce: max_time          # latest time-of-day across all items

  total_price:
    path: "$.items[*].price"
    reduce: sum

  unique_categories:
    path: "$.items[*].category"
    reduce: distinct

Available operators:

Operator Description
min_time / max_time Earliest/latest time-of-day (ignores date + timezone)
min_date / max_date Earliest/latest calendar date (ignores time)
min_datetime / max_datetime Earliest/latest full datetime (timezone-normalised)
min_int / max_int Minimum/maximum numeric value
sum Sum of numeric values
count Count of non-null values (returns 0 for empty)
first / last First or last value in traversal order
concat Join values as a string (default separator ", ")
distinct Deduplicated list, preserving first-seen order

For concat with a custom separator use the dict form:

"reduce": {"op": "concat", "sep": " | "}

Fetch from API

from siphon import fetch_and_process

spec = {
    "request": {"path": "/products"},
    "extract": {
        "id": "$.data.id",
        "names": {"path": "$.data.items[*].name", "collect": True},
    },
}

result = fetch_and_process(spec, "https://api.example.com")

Requires requests:

pip install siphon-dsl[http]

Typed Specs (Pydantic)

from siphon.typed import process_spec, ExtractSpec, FieldSpec

spec = ExtractSpec(
    extract={
        "id": "$.data.id",
        "active_items": FieldSpec(
            path="$.data.items[*]",
            where={"status": "active"},
            select={"item_id": "id", "name": "name"},
            collect=True,
        ),
    }
)

result = process_spec(spec, data)

Requires pydantic:

pip install siphon-dsl[typed]

Why Siphon?

  • Minimal — ~100 lines of code, no dependencies
  • Declarative — specs are data, not code
  • Composable — combine paths, filters, and projections

Spec History

See specs/ for version history and full documentation. Latest: v0.8 — adds reduce aggregation operators.

License

MIT

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