HTTP Structured Fields in Python

This is a Python 3 library implementing parsing and serialisation of RFC8941.

This library also implements Display Strings and Dates, as specified in draft-ietf-httpbis-sfbis-05.

Python API

Parsing

Textual HTTP headers can be parsed by calling parse; the return value is a data structure that represents the field value.

>>> from http_sf import parse, ser
>>> parse(b"foo; a=1, bar; b=2", tltype="dictionary")
{'foo': (True, {'a': 1}), 'bar': (True, {'b': 2})}

parse() takes a bytes-like object as the first argument. If you want to parse a string, please .encode() it first.

Indicating Top-Level Type

Because the library needs to know which kind of field it is, you need to hint this when calling parse. There are two ways to do this:

1. Using a tltype parameter, whose value should be one of 'dictionary', 'list', or 'item'.
2. Using a name parameter to indicate a field name that has a registered type, per the retrofit draft.

Note that if you use name, a KeyError will be raised if the type associated with the name isn't known, unless you also pass a tltype as a fallback.

Types

In the returned data, Dictionaries are represented as Python dictionaries; Lists are represented as Python lists, and Items are the bare type.

Bare types are represented using the following Python types:

• Integers: int
• Decimals: float
• Strings: str
• Tokens: http_sf.Token (a UserString)
• Byte Sequences: bytes
• Booleans: bool
• Dates: datetime.datetime
• Display Strings: http_sf.DisplayString (a UserString)

Inner Lists are represented as lists as well.

Parameters

Structured Types that can have parameters (including Dictionary and List members as well as singular Items and Inner Lists) are represented as a tuple of (value, parameters) where parameters is a dictionary.

So, a single item that's a Token with one parameter whose value is an integer will be represented like this:

>>> parse(b"foo; a=1", tltype="item")
(Token("foo"), {'a': 1})

Note that even if there aren't parameters, a tuple will still be returned, as in some items on this List:

>>> parse(b"a, b; q=5, c", tltype="list")
[(Token("a"), {}), (Token("b"), {'q': 5}), (Token("c"), {})]

Serialisation

To serialise that data structure back to a textual Structured Field, use ser:

>>> field = parse(b"a, b; q=5, c", tltype="list")
>>> ser(field)
'a, b;q=5, c'

When using ser, if an Item or Inner List doesn't have parameters, they can be omitted; for example:

>>> structure = [5, 6, (7, {"with": "param"})]
>>> ser(structure)
'5, 6, 7;with="param"'

Note that ser produces a string, not a bytes-like object.

Command Line Use

You can validate and examine the data model of a field value by calling the library on the command line, using -d, -l and -i to denote dictionaries, lists or items respectively; e.g.,

> python3 -m http_sf -i "foo;bar=baz"
[
    {
        "__type": "token",
        "value": "foo"
    },
    {
        "bar": {
            "__type": "token",
            "value": "baz"
        }
    }
]

or:

> python3 -m http_sf -i "foo;&bar=baz"
FAIL: Key does not begin with lcalpha or * at: &bar=baz

Alternatively, you can pass the field name with the -n option, provided that it is a compatible retrofit field:

> python3 -m http_sf -n "Cache-Control" "max-age=40, must-revalidate"
{
    "max-age": [
        40,
        {}
    ],
    "must-revalidate": [
        true,
        {}
    ]
}

Note that if successful, the output is in the JSON format used by the test suite.