Skip to main content

Parse and serialise HTTP Structured Field Values

Project description

HTTP Structured Field Values in Python

Actions Status

This is a Python 3 library implementing parsing and serialisation of HTTP Structured Fields.

The library's initial purpose is to prove the algorithms in the specification; as a result, it is not at all optimised. It tracks the specification closely, but since it is not yet an RFC, may change at any time.

Currently, this implements draft 19 of the specification.

Python API

There are three top-level types for Structured Field Values; Dictionary, List and Item. After instantiation, each can be used to parse a string HTTP header field value by calling .parse():

>>> from http_sfv import List
>>> my_list = List()
>>> my_list.parse(b"foo; a=1, bar; b=2")

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

Members of Lists and Dictionaries are available by normal Pythonic list and dictionary methods, respectively:

>>> my_list
[<http_sfv.item.Item object at 0x106d25190>, <http_sfv.item.Item object at 0x106d25210>]
>>> my_list[0]
<http_sfv.item.Item object at 0x106d25190>

Items (whether top-level or inside a list or dictionary value) can have their values accessed with the .value property:

>>> my_list[0].value

Parameters on Items (and Inner Lists) can be accessed using the .params property, which is a dictionary:

>>> my_list[0].params['a']

Note that Tokens and Strings both evaluate as Python strings, but Tokens have a different class:

>>> type(my_list[0].value)
<class 'http_sfv.token.Token'>

That means that you need to create Tokens explicitly:

>>> from http_sfv import Token
>>> my_list.append(Token('bar'))
>>> my_list[-1]

If you compare two Items, they'll be considered to be equivalent if their values match, even when their parameters are different:

>>> Token('foo') in my_list  # note that my_list's 'foo' has a parameter
>>> my_list.count(Token("foo"))

Inner Lists can be added by passing a list:

>>> my_list.append(['another_thing', 'and_another'])
>>> print(my_list)
foo;a=1, bar;b=2, bar, ("another_thing" "and_another")
>>> my_list[-1][-1].params['a'] = True

Dictionaries, Lists, and Items can be instantiated with a value:

>>> from http_sfv import Dictionary
>>> my_dictionary = Dictionary({'a': '1', 'b': 2, 'c': Token('foo')})
>>> my_dictionary
{'a': <http_sfv.item.Item object at 0x106a94c40>, 'b': <http_sfv.item.Item object at 0x106a94d00>, 'c': <http_sfv.item.Item object at 0x106a94dc0>}

Once instantiated, parameters can then be accessed:

>>> my_dictionary['b'].params['1'] = 2.0

Finally, to serialise a field value, just evaluate it as a string:

>>> print(my_dictionary)
a=1, b=2;b1=2.0, c=foo

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_sfv -i "foo;bar=baz"
        "__type": "token",
        "value": "foo"
        "bar": {
            "__type": "token",
            "value": "baz"


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

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

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for http-sfv, version 0.9.1
Filename, size File type Python version Upload date Hashes
Filename, size http_sfv-0.9.1.tar.gz (14.1 kB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring DigiCert DigiCert EV certificate Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page