Python Enhancement Proposals

PEP 3154 – Pickle protocol version 4

PEP
3154
Title
Pickle protocol version 4
Author
Antoine Pitrou <solipsis at pitrou.net>
Status
Final
Type
Standards Track
Created
11-Aug-2011
Python-Version
3.4
Post-History
12-Aug-2011
Resolution
Python-Dev

Contents

Abstract

Data serialized using the pickle module must be portable across Python versions. It should also support the latest language features as well as implementation-specific features. For this reason, the pickle module knows about several protocols (currently numbered from 0 to 3), each of which appeared in a different Python version. Using a low-numbered protocol version allows to exchange data with old Python versions, while using a high-numbered protocol allows access to newer features and sometimes more efficient resource use (both CPU time required for (de)serializing, and disk size / network bandwidth required for data transfer).

Rationale

The latest current protocol, coincidentally named protocol 3, appeared with Python 3.0 and supports the new incompatible features in the language (mainly, unicode strings by default and the new bytes object). The opportunity was not taken at the time to improve the protocol in other ways.

This PEP is an attempt to foster a number of incremental improvements in a new pickle protocol version. The PEP process is used in order to gather as many improvements as possible, because the introduction of a new pickle protocol should be a rare occurrence.

Proposed changes

Framing

Traditionally, when unpickling an object from a stream (by calling load() rather than loads()), many small read() calls can be issued on the file-like object, with a potentially huge performance impact.

Protocol 4, by contrast, features binary framing. The general structure of a pickle is thus the following:

+------+------+
| 0x80 | 0x04 |              protocol header (2 bytes)
+------+------+
|  OP  |                     FRAME opcode (1 byte)
+------+------+-----------+
| MM MM MM MM MM MM MM MM |  frame size (8 bytes, little-endian)
+------+------------------+
| .... |                     first frame contents (M bytes)
+------+
|  OP  |                     FRAME opcode (1 byte)
+------+------+-----------+
| NN NN NN NN NN NN NN NN |  frame size (8 bytes, little-endian)
+------+------------------+
| .... |                     second frame contents (N bytes)
+------+
  etc.

To keep the implementation simple, it is forbidden for a pickle opcode to straddle frame boundaries. The pickler takes care not to produce such pickles, and the unpickler refuses them. Also, there is no “last frame” marker. The last frame is simply the one which ends with a STOP opcode.

A well-written C implementation doesn’t need additional memory copies for the framing layer, preserving general (un)pickling efficiency.

Note

How the pickler decides to partition the pickle stream into frames is an implementation detail. For example, “closing” a frame as soon as it reaches ~64 KiB is a reasonable choice for both performance and pickle size overhead.

Binary encoding for all opcodes

The GLOBAL opcode, which is still used in protocol 3, uses the so-called “text” mode of the pickle protocol, which involves looking for newlines in the pickle stream. It also complicates the implementation of binary framing.

Protocol 4 forbids use of the GLOBAL opcode and replaces it with STACK_GLOBAL, a new opcode which takes its operand from the stack.

Serializing more “lookupable” objects

By default, pickle is only able to serialize module-global functions and classes. Supporting other kinds of objects, such as unbound methods [4], is a common request. Actually, third-party support for some of them, such as bound methods, is implemented in the multiprocessing module [5].

The __qualname__ attribute from PEP 3155 makes it possible to lookup many more objects by name. Making the STACK_GLOBAL opcode accept dot-separated names would allow the standard pickle implementation to support all those kinds of objects.

64-bit opcodes for large objects

Current protocol versions export object sizes for various built-in types (str, bytes) as 32-bit ints. This forbids serialization of large data [1]. New opcodes are required to support very large bytes and str objects.

Native opcodes for sets and frozensets

Many common built-in types (such as str, bytes, dict, list, tuple) have dedicated opcodes to improve resource consumption when serializing and deserializing them; however, sets and frozensets don’t. Adding such opcodes would be an obvious improvement. Also, dedicated set support could help remove the current impossibility of pickling self-referential sets [2].

Calling __new__ with keyword arguments

Currently, classes whose __new__ mandates the use of keyword-only arguments can not be pickled (or, rather, unpickled) [3]. Both a new special method (__getnewargs_ex__) and a new opcode (NEWOBJ_EX) are needed. The __getnewargs_ex__ method, if it exists, must return a two-tuple (args, kwargs) where the first item is the tuple of positional arguments and the second item is the dict of keyword arguments for the class’s __new__ method.

Better string encoding

Short str objects currently have their length coded as a 4-bytes integer, which is wasteful. A specific opcode with a 1-byte length would make many pickles smaller.

Smaller memoization

The PUT opcodes all require an explicit index to select in which entry of the memo dictionary the top-of-stack is memoized. However, in practice those numbers are allocated in sequential order. A new opcode, MEMOIZE, will instead store the top-of-stack in at the index equal to the current size of the memo dictionary. This allows for shorter pickles, since PUT opcodes are emitted for all non-atomic datatypes.

Summary of new opcodes

These reflect the state of the proposed implementation (thanks mostly to Alexandre Vassalotti’s work):

  • FRAME: introduce a new frame (followed by the 8-byte frame size and the frame contents).
  • SHORT_BINUNICODE: push a utf8-encoded str object with a one-byte size prefix (therefore less than 256 bytes long).
  • BINUNICODE8: push a utf8-encoded str object with an eight-byte size prefix (for strings longer than 2**32 bytes, which therefore cannot be serialized using BINUNICODE).
  • BINBYTES8: push a bytes object with an eight-byte size prefix (for bytes objects longer than 2**32 bytes, which therefore cannot be serialized using BINBYTES).
  • EMPTY_SET: push a new empty set object on the stack.
  • ADDITEMS: add the topmost stack items to the set (to be used with EMPTY_SET).
  • FROZENSET: create a frozenset object from the topmost stack items, and push it on the stack.
  • NEWOBJ_EX: take the three topmost stack items cls, args and kwargs, and push the result of calling cls.__new__(*args, **kwargs).
  • STACK_GLOBAL: take the two topmost stack items module_name and qualname, and push the result of looking up the dotted qualname in the module named module_name.
  • MEMOIZE: store the top-of-stack object in the memo dictionary with an index equal to the current size of the memo dictionary.

Alternative ideas

Prefetching

Serhiy Storchaka suggested to replace framing with a special PREFETCH opcode (with a 2- or 4-bytes argument) to declare known pickle chunks explicitly. Large data may be pickled outside such chunks. A naïve unpickler should be able to skip the PREFETCH opcode and still decode pickles properly, but good error handling would require checking that the PREFETCH length falls on an opcode boundary.

Acknowledgments

In alphabetic order:

  • Alexandre Vassalotti, for starting the second PEP 3154 implementation [6]
  • Serhiy Storchaka, for discussing the framing proposal [6]
  • Stefan Mihaila, for starting the first PEP 3154 implementation as a Google Summer of Code project mentored by Alexandre Vassalotti [7].

References

[1]
“pickle not 64-bit ready”: http://bugs.python.org/issue11564
[2]
“Cannot pickle self-referencing sets”: http://bugs.python.org/issue9269
[3]
“pickle/copyreg doesn’t support keyword only arguments in __new__”: http://bugs.python.org/issue4727
[4]
“pickle should support methods”: http://bugs.python.org/issue9276
[5]
Lib/multiprocessing/forking.py: http://hg.python.org/cpython/file/baea9f5f973c/Lib/multiprocessing/forking.py#l54
[6] (1, 2)
Implement PEP 3154, by Alexandre Vassalotti http://bugs.python.org/issue17810
[7]
Implement PEP 3154, by Stefan Mihaila http://bugs.python.org/issue15642

Source: https://github.com/python-discord/peps/blob/main/pep-3154.txt

Last modified: 2022-03-09 16:04:44 GMT