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400 lines
13 KiB
Python
400 lines
13 KiB
Python
# imported from the tnetstring project: https://github.com/rfk/tnetstring
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#
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# Copyright (c) 2011 Ryan Kelly
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#
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# Permission is hereby granted, free of charge, to any person obtaining a copy
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# of this software and associated documentation files (the "Software"), to deal
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# in the Software without restriction, including without limitation the rights
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# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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# copies of the Software, and to permit persons to whom the Software is
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# furnished to do so, subject to the following conditions:
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#
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# The above copyright notice and this permission notice shall be included in
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# all copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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# THE SOFTWARE.
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"""
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tnetstring: data serialization using typed netstrings
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======================================================
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This is a data serialization library. It's a lot like JSON but it uses a
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new syntax called "typed netstrings" that Zed has proposed for use in the
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Mongrel2 webserver. It's designed to be simpler and easier to implement
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than JSON, with a happy consequence of also being faster in many cases.
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An ordinary netstring is a blob of data prefixed with its length and postfixed
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with a sanity-checking comma. The string "hello world" encodes like this::
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11:hello world,
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Typed netstrings add other datatypes by replacing the comma with a type tag.
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Here's the integer 12345 encoded as a tnetstring::
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5:12345#
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And here's the list [12345,True,0] which mixes integers and bools::
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19:5:12345#4:true!1:0#]
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Simple enough? This module gives you the following functions:
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:dump: dump an object as a tnetstring to a file
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:dumps: dump an object as a tnetstring to a string
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:load: load a tnetstring-encoded object from a file
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:loads: load a tnetstring-encoded object from a string
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:pop: pop a tnetstring-encoded object from the front of a string
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Note that since parsing a tnetstring requires reading all the data into memory
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at once, there's no efficiency gain from using the file-based versions of these
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functions. They're only here so you can use load() to read precisely one
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item from a file or socket without consuming any extra data.
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By default tnetstrings work only with byte strings, not unicode. If you want
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unicode strings then pass an optional encoding to the various functions,
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like so::
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>>> print(repr(tnetstring.loads("2:\\xce\\xb1,")))
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'\\xce\\xb1'
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>>>
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>>> print(repr(tnetstring.loads("2:\\xce\\xb1,","utf8")))
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u'\u03b1'
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"""
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from collections import deque
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import six
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__ver_major__ = 0
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__ver_minor__ = 2
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__ver_patch__ = 0
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__ver_sub__ = ""
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__version__ = "%d.%d.%d%s" % (
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__ver_major__, __ver_minor__, __ver_patch__, __ver_sub__)
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def dumps(value, encoding=None):
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"""dumps(object,encoding=None) -> string
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This function dumps a python object as a tnetstring.
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"""
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# This uses a deque to collect output fragments in reverse order,
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# then joins them together at the end. It's measurably faster
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# than creating all the intermediate strings.
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# If you're reading this to get a handle on the tnetstring format,
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# consider the _gdumps() function instead; it's a standard top-down
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# generator that's simpler to understand but much less efficient.
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q = deque()
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_rdumpq(q, 0, value, encoding)
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return "".join(q)
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def dump(value, file, encoding=None):
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"""dump(object,file,encoding=None)
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This function dumps a python object as a tnetstring and writes it to
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the given file.
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"""
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file.write(dumps(value, encoding))
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file.flush()
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def _rdumpq(q, size, value, encoding=None):
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"""Dump value as a tnetstring, to a deque instance, last chunks first.
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This function generates the tnetstring representation of the given value,
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pushing chunks of the output onto the given deque instance. It pushes
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the last chunk first, then recursively generates more chunks.
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When passed in the current size of the string in the queue, it will return
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the new size of the string in the queue.
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Operating last-chunk-first makes it easy to calculate the size written
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for recursive structures without having to build their representation as
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a string. This is measurably faster than generating the intermediate
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strings, especially on deeply nested structures.
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"""
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write = q.appendleft
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if value is None:
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write("0:~")
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return size + 3
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if value is True:
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write("4:true!")
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return size + 7
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if value is False:
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write("5:false!")
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return size + 8
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if isinstance(value, (int, long)):
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data = str(value)
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ldata = len(data)
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span = str(ldata)
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write("#")
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write(data)
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write(":")
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write(span)
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return size + 2 + len(span) + ldata
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if isinstance(value, (float,)):
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# Use repr() for float rather than str().
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# It round-trips more accurately.
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# Probably unnecessary in later python versions that
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# use David Gay's ftoa routines.
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data = repr(value)
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ldata = len(data)
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span = str(ldata)
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write("^")
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write(data)
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write(":")
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write(span)
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return size + 2 + len(span) + ldata
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if isinstance(value, str):
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lvalue = len(value)
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span = str(lvalue)
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write(",")
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write(value)
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write(":")
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write(span)
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return size + 2 + len(span) + lvalue
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if isinstance(value, (list, tuple,)):
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write("]")
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init_size = size = size + 1
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for item in reversed(value):
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size = _rdumpq(q, size, item, encoding)
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span = str(size - init_size)
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write(":")
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write(span)
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return size + 1 + len(span)
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if isinstance(value, dict):
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write("}")
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init_size = size = size + 1
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for (k, v) in six.iteritems(value):
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size = _rdumpq(q, size, v, encoding)
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size = _rdumpq(q, size, k, encoding)
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span = str(size - init_size)
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write(":")
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write(span)
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return size + 1 + len(span)
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if isinstance(value, unicode):
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if encoding is None:
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raise ValueError("must specify encoding to dump unicode strings")
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value = value.encode(encoding)
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lvalue = len(value)
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span = str(lvalue)
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write(",")
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write(value)
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write(":")
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write(span)
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return size + 2 + len(span) + lvalue
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raise ValueError("unserializable object")
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def _gdumps(value, encoding):
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"""Generate fragments of value dumped as a tnetstring.
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This is the naive dumping algorithm, implemented as a generator so that
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it's easy to pass to "".join() without building a new list.
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This is mainly here for comparison purposes; the _rdumpq version is
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measurably faster as it doesn't have to build intermediate strins.
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"""
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if value is None:
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yield "0:~"
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elif value is True:
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yield "4:true!"
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elif value is False:
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yield "5:false!"
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elif isinstance(value, (int, long)):
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data = str(value)
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yield str(len(data))
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yield ":"
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yield data
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yield "#"
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elif isinstance(value, (float,)):
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data = repr(value)
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yield str(len(data))
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yield ":"
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yield data
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yield "^"
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elif isinstance(value, (str,)):
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yield str(len(value))
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yield ":"
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yield value
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yield ","
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elif isinstance(value, (list, tuple,)):
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sub = []
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for item in value:
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sub.extend(_gdumps(item))
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sub = "".join(sub)
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yield str(len(sub))
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yield ":"
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yield sub
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yield "]"
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elif isinstance(value, (dict,)):
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sub = []
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for (k, v) in six.iteritems(value):
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sub.extend(_gdumps(k))
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sub.extend(_gdumps(v))
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sub = "".join(sub)
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yield str(len(sub))
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yield ":"
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yield sub
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yield "}"
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elif isinstance(value, (unicode,)):
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if encoding is None:
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raise ValueError("must specify encoding to dump unicode strings")
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value = value.encode(encoding)
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yield str(len(value))
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yield ":"
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yield value
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yield ","
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else:
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raise ValueError("unserializable object")
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def loads(string, encoding=None):
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"""loads(string,encoding=None) -> object
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This function parses a tnetstring into a python object.
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"""
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# No point duplicating effort here. In the C-extension version,
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# loads() is measurably faster then pop() since it can avoid
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# the overhead of building a second string.
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return pop(string, encoding)[0]
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def load(file, encoding=None):
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"""load(file,encoding=None) -> object
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This function reads a tnetstring from a file and parses it into a
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python object. The file must support the read() method, and this
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function promises not to read more data than necessary.
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"""
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# Read the length prefix one char at a time.
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# Note that the netstring spec explicitly forbids padding zeros.
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c = file.read(1)
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if not c.isdigit():
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raise ValueError("not a tnetstring: missing or invalid length prefix")
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datalen = ord(c) - ord("0")
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c = file.read(1)
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if datalen != 0:
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while c.isdigit():
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datalen = (10 * datalen) + (ord(c) - ord("0"))
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if datalen > 999999999:
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errmsg = "not a tnetstring: absurdly large length prefix"
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raise ValueError(errmsg)
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c = file.read(1)
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if c != ":":
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raise ValueError("not a tnetstring: missing or invalid length prefix")
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# Now we can read and parse the payload.
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# This repeats the dispatch logic of pop() so we can avoid
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# re-constructing the outermost tnetstring.
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data = file.read(datalen)
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if len(data) != datalen:
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raise ValueError("not a tnetstring: length prefix too big")
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type = file.read(1)
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if type == ",":
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if encoding is not None:
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return data.decode(encoding)
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return data
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if type == "#":
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try:
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return int(data)
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except ValueError:
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raise ValueError("not a tnetstring: invalid integer literal")
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if type == "^":
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try:
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return float(data)
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except ValueError:
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raise ValueError("not a tnetstring: invalid float literal")
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if type == "!":
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if data == "true":
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return True
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elif data == "false":
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return False
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else:
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raise ValueError("not a tnetstring: invalid boolean literal")
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if type == "~":
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if data:
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raise ValueError("not a tnetstring: invalid null literal")
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return None
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if type == "]":
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l = []
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while data:
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(item, data) = pop(data, encoding)
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l.append(item)
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return l
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if type == "}":
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d = {}
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while data:
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(key, data) = pop(data, encoding)
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(val, data) = pop(data, encoding)
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d[key] = val
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return d
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raise ValueError("unknown type tag")
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def pop(string, encoding=None):
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"""pop(string,encoding=None) -> (object, remain)
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This function parses a tnetstring into a python object.
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It returns a tuple giving the parsed object and a string
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containing any unparsed data from the end of the string.
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"""
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# Parse out data length, type and remaining string.
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try:
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(dlen, rest) = string.split(":", 1)
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dlen = int(dlen)
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except ValueError:
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raise ValueError("not a tnetstring: missing or invalid length prefix")
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try:
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(data, type, remain) = (rest[:dlen], rest[dlen], rest[dlen + 1:])
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except IndexError:
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# This fires if len(rest) < dlen, meaning we don't need
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# to further validate that data is the right length.
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raise ValueError("not a tnetstring: invalid length prefix")
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# Parse the data based on the type tag.
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if type == ",":
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if encoding is not None:
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return (data.decode(encoding), remain)
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return (data, remain)
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if type == "#":
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try:
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return (int(data), remain)
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except ValueError:
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raise ValueError("not a tnetstring: invalid integer literal")
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if type == "^":
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try:
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return (float(data), remain)
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except ValueError:
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raise ValueError("not a tnetstring: invalid float literal")
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if type == "!":
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if data == "true":
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return (True, remain)
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elif data == "false":
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return (False, remain)
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else:
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raise ValueError("not a tnetstring: invalid boolean literal")
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if type == "~":
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if data:
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raise ValueError("not a tnetstring: invalid null literal")
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return (None, remain)
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if type == "]":
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l = []
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while data:
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(item, data) = pop(data, encoding)
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l.append(item)
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return (l, remain)
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if type == "}":
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d = {}
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while data:
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(key, data) = pop(data, encoding)
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(val, data) = pop(data, encoding)
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d[key] = val
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return (d, remain)
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raise ValueError("unknown type tag")
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