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A pattern matching and template library.

Project description

Matcho

A pattern matching and template library.

Macho was originally written by a need to convert hierarchical JSON data into flattish data frames. It may yet transcend this purpose.

Installation

pip install matcho

Quick Start

from matcho import build_matcher, build_template, bind, insert

# match a list of any length and bind "x" to its items
matcher = build_matcher([bind("x"), ...])

# match some data
bindings = matcher([1, 2, 3])

# a template that reconstructs the original list
template = build_template([insert("x"), ...])

assert template(bindings) == [1, 2, 3]

Motivating example

What if you want to convert data from a deeply nested structure like JSON to a flat tabular format?

For example, say we want to extract the columns "date", "time", "station" and "event_type" from the following structure:

data = {
    "date": "2022-02-20",
    "uid": "DEADBEEF",
    "reports": [
        {
            "station": 7,
            "events": [
                {"time": 1300, "type": "ON"},
                {"time": 1700, "type": "OFF"}
            ]
        },
        {
            "station": 5,
            "events": [
                {"time": 1100, "type": "ON"},
                {"time": 1800, "type": "OFF"}
            ]
        }
    ]
}

That's how a Matcho would do it:

from matcho import build_matcher, build_template, bind, insert

pattern = {
        "date": bind("date"),
        "reports": [
            {
                "station": bind("station"),
                "events": [{"time": bind("time"), "type": bind("event_type")}, ...],
            },
            ...,  # note that the ... really are Python syntax
        ],
    }

template_spec = [
        [insert("date"), insert("time"), insert("station"), insert("event_type")],
        ...,
        ...,  # note that the number of ... matches the pattern
    ]

matcher = build_matcher(pattern)
bindings = matcher(data)

template = build_template(template_spec)
table = template(bindings)

assert table == [
    ["2022-02-20", 1300, 7, "ON"],
    ["2022-02-20", 1700, 7, "OFF"],
    ["2022-02-20", 1100, 5, "ON"],
    ["2022-02-20", 1800, 5, "OFF"],
]

Inspiration

Matcho was inspired by Scheme's syntax-rules pattern language. The Lisp dialect Scheme allows programmers to define macros using pattern matching and template substitution. Since code in Scheme consists of list this enables cool syntax transformations. In Python we are limited to transforming data, but that's cool enough.

Why not just use Python 3.10's match syntax instead?

The new match syntax is great and it's even used by the implementation of Macho. However, it has one shortcoming: names can only capture one value. While it's possible to match an arbitary number of list items with [*items], it's not possible to do something like [*{"nested": item}], where we would like to capture the values of in a sequence of dictionaries. In Matcho, this is possible with a pattern of the form [{"nested": item}, ...].

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