Python Packed Resources

PyOxidizer has defined a custom data format for storing resources useful to the execution of a Python interpreter. We call this data format Python packed resources.

The way it works is that some producer collects resources required by a Python interpreter. These resources include Python module source and bytecode, non-module resource/data files, extension modules, and shared libraries. Metadata about these resources and sometimes the raw resource data itself is serialized to a binary data structure.

At Python interpreter run time, this data structure is loaded (it can be embedded in a binary or exist as a standalone file) and parsed. A custom Python Meta Path Finders (OxidizedFinder from oxidized_importer Python Extension) then uses the parsed data structure to power Python module importing.

This functionality is similar to using a .zip file for holding Python modules. However, the Python packed resources data structure is far more advanced.

Implementation

The canonical implementation of the writer and parser of this data structure lives in the python-packed-resources Rust crate. The canonical home of this crate is https://github.com/indygreg/PyOxidizer/tree/main/python-packed-resources.

This crate is published to crates.io at https://crates.io/crates/python-packed-resources.

Specification

From a high level, the data structure defines an iterable of resources. A resource is an entity with a name, metadata, and blob fields. Typically the most common resource is a Python module/package. But other resource types (such as shared libraries) are defined.

The first 8 bytes of the data structure are a magic header identifying the content as our data structure and the version of it. The first 7 bytes are pyembed and the following 1 byte denotes a version. Semantics of each version are denoted in sections below.

High-Level Layout

From a high-level, the serialized format consists of:

  • A global header describing the overall payload.
  • An index describing the blob sections present in the payload.
  • An index describing each resource and its content.
  • A series of blob sections holding the data referenced by the resources index.

A resource is composed of various fields that describe it. Examples of fields include the resource name, source code, and bytecode. The resources index describes which fields are present and where to find them in the payload.

The actual content of fields (e.g. the raw bytes containing source code) is stored in field-specific sections after the index. Each field has its own section and data for all resources is stored next to each other. e.g. you will have all the data for resource names followed by all data for module sourcecode.

The low-level data format is described below. All integers are little-endian.

The first 13 bytes after the magic header denote a global header. The global header consists of:

  • A u8 denoting the number of blob sections, blob_sections_count.
  • A u32 denoting the length of the blob index, blob_index_length.
  • A u32 denoting the total number of resources in this data, resources_count.
  • A u32 denoting the length of the resources index, resources_index_length.

Following the global header is the blob index. The blob index describes the various blob sections present in the payload following the resources index.

Each entry in the blob index logically consists of a set of fields defining metadata about each blob section. This is encoded by a start of entry u8 marker followed by N u8 field type values and their corresponding metadata, followed by an end of entry u8 marker. The blob index is terminated by an end of index u8 marker. The total number of bytes in the blob index including the end of index marker should be blob_index_length.

Following the blob index is the resources index. Each entry in this index defines a sparse set of metadata describing a single resource. Entries are composed of a series of u8 identifying pieces of metadata, followed by field-specific supplementary descriptions. For example, a value of 0x02 denotes the length of the resources’s name and is immediately followed by a u16 holding said length. See the section below for each field tracked by this index.

Following the resources index is blob data. Blob data is logically consisted of different sections holding data for different fields for different resources. But there is no internal structure or separators: all the individual blobs are just laid out next to each other.

Blob Field Types

The Blob Index allows attributing a sparse set of metadata with every blob section entry. The type of metadata being conveyed is defined by a u8. Some field types have additional metadata following that field.

The various field types and their semantics follow.

0x00
End of index. This field indicates that there are no more blob index entries and we’ve reached the end of the blob index.
0x01
Start of blob section entry. Encountering this value signals the beginning of a new blob section. From a specification standpoint, this isn’t strictly required. But it helps ensure parser state.
0xff
End of blob section entry. Encountering this value signals the end of the current blob section definition. The next encountered u8 in the index should be 0x01 to denote a new entry or 0x00 to denote end of index.
0x02
Resource field type. This field defines which resource field this blob section is holding data for. A u8 following this one will contain the resource field type value (see section below).
0x03
Raw payload length. This field defines the raw length in bytes of the blob section in the payload. The u64 containing that length will immediately follow this u8.
0x04

Interior padding mechanism. This field defines interior padding between elements in the blob section. Following this u8 is another u8 denoting the padding mechanism.

0x01 indicates no padding. 0x02 indicates NULL padding (a 0x00 between elements).

If not present, no padding is assumed. If the payload data logically consists of discrete resources (e.g. Python package resource files), then padding applies to these sub-elements as well.

Resource Field Types

The Resources Index allows attributing a sparse set of metadata with every resource. A u8 indicates what metadata is being conveyed. Some field types have additional metadata following this [u8] further defining the field. The values of each defined metadata type follow.

0x00
End of index. Special type to denote the end of an index.
0x01
Start of resource entry. Signals the beginning of a new resource. From a specification standpoint this isn’t strictly required. But it helps ensure parser state.
0x02

Resource flavor. Declares the type of resource this entry represents. A u8 defining the resource flavor immediately follows this byte. See the section below for valid resource flavors.

This field is deprecated in version 2 in favor of the individual fields expressing presence of a resource type. (See fields starting at 0x16.)

0xff
End of resource entry. The next encountered u8 in the index should be an end of index or start of resource marker.
0x03
Resource name. A u16 denoting the length in bytes of the resource name immediately follows this byte. The resource name must be valid UTF-8.
0x04
Package flag. If encountered, the resource is identified as a Python package.
0x05
Namespace package flag. If encountered, the resource is identified as a Python namespace package.
0x06
In-memory Python module source code. A u32 denoting the length in bytes of the module’s source code immediately follows this byte.
0x07
In-memory Python module bytecode. A u32 denoting the length in bytes of the module’s bytecode immediately follows this byte.
0x08
In-memory Python module optimized level 1 bytecode. A u32 denoting the length in bytes of the module’s optimization level 1 bytecode immediately follows this byte.
0x09
In-memory Python module optimized level 2 bytecode. Same as previous, except for bytecode optimization level 2.
0x0a
In-memory Python extension module shared library. A u32 denoting the length in bytes of the extension module’s machine code immediately follows this byte.
0x0b
In-memory Python resources data. If encountered, the module/package contains non-module resources files and the number of resources is contained in a u32 that immediately follows. Following this u32 is an array of (u16, u64) denoting the resource name and payload size for each resource in this package.
0x0c
In-memory Python distribution resource. Defines resources accessed from importlib.metadata APIs. If encountered, the module/package contains distribution metadata describing the package. The number of files being described is contained in a u32 that immediately follows this byte. Following this u32 is an array of (u16, u64) denoting the distribution file name and payload size for each virtual file in this distribution.
0x0d
In-memory shared library. If set, this resource is a shared library and not a Python module. The resource name field is the name of this shared library, with file extension (as it would appear in a dynamic binary’s loader metadata to indicate a library dependency). A u64 denoting the length in bytes of the shared library data follows. This shared library should be loaded from memory.
0x0e
Shared library dependency names. This field indicates the names of shared libraries that this entity depends on. The number of library names is contained in a u16 that immediately follows this byte. Following this u16 is an array of u16 denoting the length of the library name for each shared library dependency. Each described shared library dependency may or may not be described by other entries in this data structure.
0x0f
Relative filesystem path to Python module source code. A u32 holding the length in bytes of a filesystem path encoded in the platform-native file path encoding follows. The source code for a Python module will be read from a file at this path.
0x10
Relative filesystem path to Python module bytecode. Similar to the previous except the filesystem path holds Python module bytecode.
0x11
Relative filesystem path to Python module bytecode at optimization level 1. Similar to the previous except for what is being pointed to.
0x12
Relative filesystem path to Python module bytecode at optimization level 2. Similar to the previous except for what is being pointed to.
0x13
Relative filesystem path to Python extension module shared library. Similar to the previous except the file holds a Python extension module loadable as a shared library.
0x14
Relative filesystem path to Python package resources. The number of resources is contained in a u32 that immediately follows. Following this u32 is an array of (u16, u32) denoting the resource name and filesystem path to each resource in this package.
0x15

Relative filesystem path to Python distribution resources.

Defines resources accessed from importlib.metadata APIs. If encountered, the module/package contains distribution metadata describing the package. The number of files being described is contained in a u32 that immediately follows this byte. Following this u32 is an array of (u16, u32) denoting the distribution file name and filesystem path to that distribution file.

0x16
Is Python module flag. If set, this resource contains data for an importable Python module or package. Resource data is associated with Python packages and is covered by this type.
0x17
Is builtin extension module flag. This type represents a Python extension module that is built in (compiled into) the interpreter itself or is otherwise made available to the interpreter via PyImport_Inittab such that it should be imported with the builtin importer.
0x18
Is frozen Python module flag. This type represents a Python module whose bytecode is frozen and made available to the Python interpreter via the PyImport_FrozenModules array and should be imported with the frozen importer.
0x19
Is Python extension flag. This type represents a compiled Python extension. Extensions have specific requirements around how they are to be loaded and are differentiated from regular Python modules.
0x1a
Is shared library flag. This type represents a shared library that can be loaded into a process.

Resource Flavors

Important

Enumerated resource flavors are deprecated after version 1. You should use individual fields to express resource identity instead.

The data format allows defining different types/flavors of resources. This flavor of a resource is identified by a u8. The declared flavors are:

0x00
No flavor. Should not be encountered.
0x01
Python module/package. This is equivalent to resource field 0x16 being set.
0x02
Builtin Python extension module. This is equivalent to resource field 0x17 being set.
0x03
Frozen Python module. This is equivalent to resource field 0x18 being set.
0x04
Python extension. This is equivalent to resource field 0x19 being set.
0x05
Shared library. This is equivalent to resource field 0x1a being set.

pyembed\x01 Format

The initially released/formalized packed resources data format.

Supports resource field types up to and including 0x15.

pyembed\x02 Format

Version 2 of the packed resources data format.

This version introduces field type values 0x16 to 0x1a. The resource flavor field type (0x02) is deprecated and the individual field types denoting resource types should be used instead.

(PyOxidizer removed run-time code looking at field type 0x02 when this format was introduced.)

Design Considerations

The design of the packed resources data format was influenced by a handful of considerations.

Performance is a significant consideration. We want everything to be as fast as possible. Possible dimensions influencing performance include parse time, payload size, and I/O access patterns.

The payload is designed such that the index data is at the beginning so a reader only has to read a contiguous slice of data to fully understand the data within. This is in opposition to jumping around the entire data structure to extract metadata of the data within. This means that we only need to page in a fraction of the total backing data structure in order to initialize our custom importer. In addition, the index data is read sequentially. Sequential I/O should always be faster than random access I/O.

x86 is little endian, so we use little endian integers so we don’t need to waste cycles on endian transformation.

We store all data for the same field next to each other in the data structure. This is in opposition to say packing all of resource A’s data then resource B’s, etc. We do this to help maximize locality for similar data. This can help with performance because often the same field for multiple resources is accessed together. e.g. an importer will access a bunch of module bytecode entries at the same time. This locality helps minimize the number of pages that must be read. Locality can also help yield higher compression ratios.

Everything is designed to facilitate a reader leveraging 0-copy. If a reader has the data structure in memory, we don’t want to require it to copy memory in order to reference entries. In Rust speak, we should be able to hold &[u8] references everywhere.

There is no checksumming of the data because we don’t want to incur I/O overhead to read the entire blob. It could be added as an optional feature.

Potential Future Features

This data structure is robust enough to be used by PyOxidizer to power importing of every Python module used by a Python interpreter. However, there are various aspects that could be improved.

Compression

A potential area for optimization is use of general compression. Various fields should compress well - either in streaming mode or by utilizing compression dictionaries. Compression would undermine 0-copy, of course. But in environments where we want to optimize for size, it could be desirable.

Platform Portability

Currently, filesystem paths are encoded as platform native. That means [u8] on POSIX and [u16] on Windows. This isn’t portable.

Most filenames are likely ASCII or UTF-8 safe. For the common case where we don’t need platform-native filenames to preserve subtle encoding differences, we could express paths as a simpler string type.