Metadata-Version: 2.4
Name: transon
Version: 0.2.3
Summary: Homogeneous JSON template engine
Project-URL: Homepage, https://github.com/transon-org/transon
Project-URL: Documentation, https://transon-org.github.io/
Project-URL: Repository, https://github.com/transon-org/transon
Project-URL: Bug Tracker, https://github.com/transon-org/transon/issues
Author-email: Eugene Chernyshov <chernyshov.eugene@gmail.com>
License-Expression: MIT
License-File: LICENSE
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.9
Description-Content-Type: text/markdown

# transon

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> Homogeneous JSON template engine — the template is itself plain JSON.

## What is transon?

`transon` turns one JSON document into another. You describe the **shape** of the
output as a template — itself plain JSON — and put small placeholder rules (objects
marked with `"$"`) where data should flow in. No glue code to write, no separate
template language to learn.

![JSON Template plus JSON Input, through transon, produce JSON Output](https://raw.githubusercontent.com/transon-org/transon/main/docs/assets/transon-flow.svg)

A template, some input, and what comes out — pull one field from every record:

**Template:**

```json
{"$": "map", "item": {"$": "attr", "name": "email"}}
```

**Input:**

```json
[
  {"name": "Ada", "email": "ada@example.com"},
  {"name": "Alan", "email": "alan@example.com"},
  {"name": "Grace", "email": "grace@example.com"}
]
```

**Output:**

```json
["ada@example.com", "alan@example.com", "grace@example.com"]
```

Try it live in the [documentation & playground](https://transon-org.github.io/).

## Why transon?

- **Templates are data.** Store them in a database, generate them from code, review
  them as diffs, validate them before running — they are plain JSON values, not
  strings in a DSL.
- **A few rules, endlessly combined.** Iteration, lookups, conditionals, formatting —
  even arithmetic — are the same small building blocks, nested inside each other.
- **Extend it in Python.** Register your own rules, operators, and functions when the
  built-ins aren't enough.

Inspired by [XSLT](https://en.wikipedia.org/wiki/XSLT) (declarative, tree-to-tree
transformation) and [JsonLogic](https://jsonlogic.com/) (logic expressed as data).

## Installation

```shell
pip install transon
```

Your first transform:

```python
from transon import Transformer

template = {"items": {"$": "map", "item": {"$": "item"}}}
Transformer(template).transform(["a", "b"])  # => {"items": ["a", "b"]}
```

## Highlights

Things you'll appreciate once you start writing real templates:

- **Missing data just disappears.** An absent field produces "no value" rather than an
  error; containers skip it instead of emitting `null` holes; and any lookup can
  declare a `default`.
- **Catch template mistakes before running anything.** Opt-in static validation checks
  a template's structure with no input data at all.
- **Errors that point at the template.** A malformed template and data that doesn't
  fit are distinct errors, and both name the exact template path that failed
  (`at template → …`).
- **Emit anything — even data that looks like a rule.** Literal `$` keys are
  expressible, and the marker itself is configurable if `$` collides with your data.
- **The docs travel with the package.** An installed `transon` serves its own
  [Language Reference](transon/resources/LANGUAGE.md), editor metadata, and generated
  docs — offline, version-matched.

## Comparison

JSON transformation is a crowded space. `transon`'s bet is that **templates are
themselves pure JSON** — storable, generatable, diff-able, and extensible with your own
rules — traded against the terseness of a string DSL. Pick the tool that fits the job:

| Tool | Template / language | Extensible | Deps & runtime | Best when |
|---|---|---|---|---|
| **transon** | pure JSON tree | custom rules, operators, functions | none (Python stdlib) | templates must be stored / generated / validated as JSON, with domain-specific rules, in Python |
| [JSONata](https://jsonata.org/) | string expression DSL | limited | JS library | concise queries & expressions over JSON in JavaScript |
| [jq](https://jqlang.github.io/jq/) | string filter language | limited | native binary | CLI piping and ad-hoc filtering in the shell |
| [JSLT](https://github.com/schibsted/jslt) | string DSL (jq-like) | user functions | JVM | compact JSON→JSON on the JVM |
| [Jolt](https://github.com/bazaarvoice/jolt) | JSON spec | limited | JVM | declarative structural reshaping on the JVM |
| [JsonLogic](https://jsonlogic.com/) | JSON logic tree | limited | small libs (many languages) | portable business/boolean rules shared across services |
| [JSON-e](https://json-e.js.org/) | JSON template | limited | JS / Python | parameterising JSON config with interpolation |
| [Jsonnet](https://jsonnet.org/) | full templating language | yes | native binary | generating large config (e.g. Kubernetes) from a real language |
| [json-templates](https://github.com/datavis-tech/json-templates) | JSON with `{{placeholders}}` | no | tiny JS library | simple value substitution into a JSON skeleton |

**Where `transon` is _not_ the best pick** (worth being honest about):

- **Expression-heavy** transforms read far more concisely in a string DSL like JSONata
  or jq — `transon` spells `(a + b) * c` as a nested rule tree.
- **Maturity & ecosystem**: jq and JSONata are battle-tested with large communities;
  `transon` is young and Python-only.

### The trade-off, concretely

The same transform — *multiply each order's `qty` by its `price`* — over input
`{"orders": [{"qty": 2, "price": 3}, {"qty": 5, "price": 7}]}`:

JSONata — a terse string expression:

```text
orders.(qty * price)
```

`transon` — pure JSON, composable rules:

```json
{
  "$": "chain",
  "funcs": [
    {"$": "attr", "name": "orders"},
    {
      "$": "map",
      "item": {
        "$": "expr",
        "op": "mul",
        "values": [
          {"$": "attr", "name": "qty"},
          {"$": "attr", "name": "price"}
        ]
      }
    }
  ]
}
```

Both yield `[6, 35]`. JSONata wins on brevity; `transon` wins when the template itself
must be **data** — stored in a database, generated by another program, reviewed as a
diff, checked with `Transformer.validate()`, or extended with your own rules.

## Development Principles

`transon` was built with a set of key development principles in mind, including:

 - **Flexibility and Extensibility**: `transon` is designed to be highly flexible and extensible, allowing you to add new rules and types of placeholders to suit your unique needs.
 - **Valid JSON Structure**: `transon` templates are defined as valid JSON structures, making them easy to work with and compatible with a wide range of tools and applications.
 - **Composable Rules**: `transon` rules are highly composable, allowing you to define complex behavior patterns using a combination of nested rules. 
For example, arithmetic expressions can be defined with nested rules, where each rule represents a specific operation. 
This approach eliminates the need for a domain-specific language (DSL) for arithmetic expressions.
 - **Marker-Based Templates**: The most important aspect of a `transon` template is the use of the `$` marker. 
This marker is a special key within the JSON structure that distinguishes it from other types of JSON data. 
By default, the `$` key is used as the marker, but you can change it to any other value you prefer.
 
By using a marker-based approach, `transon` ensures that templates are easy to work with and can be easily distinguished from other types of JSON data. 
This makes it simple to generate dynamic templates, manipulate JSON data, and produce new JSON structures that meet your specific requirements. 
Additionally, the composable rules approach allows for advanced behavior patterns that can be defined using a combination of nested rules, making `transon` highly flexible and extensible.

## Development

Requires Python 3.9+ and [uv](https://docs.astral.sh/uv/).

```shell
uv sync --dev
uv run pytest .
```
