Skip to main content

uproot extension for reading custom classes

Project description

uproot-custom

This is a prototype repository of an extension that allows uproot to read custom classes from ROOT files.

uproot can already read some custom classes directly. However, in some cases, custom classes are too complex for uproot to read, such as when their Streamer methods are overridden or some specific data members are not supported by uproot.

This extension privides a Reader interface and allows you to read such custom classes by providing your own Reader. The Reader interface defines how to read the data members of a class from the binary stream.

Design overview

In ROOT, data are stored in a tree structure. For example, when a custom class is defined as:

class TMySubClass : public TObject {
    int m_index;
    float m_x;
};

class TMyClass : public TObject {
    double m_energy;
    std::vector<MySubClass> m_daughters;
};

The data tree is:

graph TD
    A([TMyClass]) --> B(double m_energy)
    A --> C(std::vector&lt;TMySubClass&gt; m_daughters)
    C --> D([TMySubClass])
    D --> E(int m_index)
    D --> F(float m_x)

To handle the tree-like data structure, Reader is introduced. It consists of Python and C++ parts. The Python part is responsible for generating the information tree, constructing C++ readers, and reconstructing data to awkward array. The C++ part is responsible for reading the data members of the class from the binary stream.

Generate information tree

uproot can read these structure information from the ROOT file, but not in tree format. So the first step is to generate an information tree from the ROOT file. The information tree is a nested structure that contains the data members of the class, including types, names and children if any.

Construct C++ readers

According to the information tree, we can instantiate C++ readers and combine them into a tree structure. The top reader drives its sub-readers to read data recursively. After the reading process, readers obtain the results from their sub-readers recursively, then the top reader returns the final result.

Reconstruct data to awkward array

Since embedding arrays together into awkward array in C++ is not straightforward, we left this task to Python. After the C++ reader returns the result, we can reconstruct the data into awkward array according to the information tree.

Predefined readers

uproot-custom provides some predefined readers for common ROOT classes:

Reader Description
BasicTypeReader Reads basic types like int, float, double, etc.
TObjectReader Skip TObject header when reading classes that inherit from TObject.
TStringReader Reads TString
STLSeqReader Reads std::vector, std::array, etc.
STLMapReader Reads std::map, std::unordered_map, etc.
STLStringReader Reads std::string
TArrayReader Reads TArray types like TArrayI, TArrayF, TArrayD, etc.
ObjectReader Reads custom classes that inherit from TObject.
CArrayReader Reads C-style arrays like int[]
EmptyReader A reader that does nothing. Some branches may not have any data, and the information of the corresponding class will not be stored in the ROOT file. In this case, EmptyReader is used to skip the branch.

Implement your own Reader

Full example

A complete example of how to impolement your own readers is available in the example directory of this repository.

Pre-requisites

Make sure you have GCC>13.1/Clang>=16.0.0/MSVC>=19.31, cmake installed on your system.

  1. Create a Python project and install uproot-custom:

    mkdir my_reader
    cd my_reader
    python3 -m venv .venv
    source .venv/bin/activate
    pip install uproot-custom
    
  2. Create a pyproject.toml file in the root directory of your project:

    [build-system]
    requires = ["scikit-build-core>=0.11", "pybind11>=2.10.0", "uproot-custom"]
    build-backend = "scikit_build_core.build"
    
    [project]
    name = "my-reader"
    requires-python = ">=3.9"
    dependencies = ["uproot-custom"]
    version = "0.1.0"
    
    [tool.scikit-build]
    wheel.packages = ["my_reader"]
    build-dir = "build/{wheel_tag}"
    cmake.source-dir = "cpp"
    cmake.build-type = "Debug" # Comment for release builds
    
    [tool.black]
    exclude = "/(build|dist|env|.git|.tox|.eggs|.venv)/"
    line-length = 95
    target-version = ['py39', 'py310', 'py311', 'py312', 'py313']
    

    you can change the name, version, and other fields as you like.

Reader interface

For a custom Reader, a C++ part and a Python part are both required.

For C++ part, the constructor must inherit from IElementReader, and these methods must be implemented:

  • void read(BinaryBuffer& buffer): Read data from the binary buffer.
  • py::object data() const: Return the data as a Python object. You can return anything defined in pybind11, such as py::tuple, py::list, py::array_t, etc.

For Python part, the class must inherit from uproot_custom.BaseReader and implement the following class methods:

  • gen_tree_config: Generate a configuration dictionary for the reader based on the information tree. It should return a dictionary if you want your reader to be used, otherwise return None.
  • get_cpp_reader: Identify the tree configuration and return the C++ reader instance if it matches, otherwise return None.
  • reconstruct_array: Reconstruct the raw data to an awkward array according to the tree configuration.

Implement the C++ reader

  1. Create a cpp directory in the root directory of your project, and create a my_reader.cc file in it.

  2. In my_reader.cc, include the necessary headers and implement your reader class. For example:

    #include "uproot-custom/uproot-custom.hh"
    using namespace uproot;
    
    class MyReader : public IElementReader {
        public:
            // Must at least receive a name
            MyReader( std::string name )
                : IElementReader(name), m_data( std::make_shared<std::vector<int>>() ) {}
    
            // Implement these methods
            void read( BinaryBuffer& buffer ) {
                // Read data from the buffer
                // Implement your reading logic here
            }
    
            py::object data() const {
                // Return the data as a Python object
                return make_array( m_data );
            }
    
        private:
            const std::string m_name;
            std::shared_ptr<std::vector<int>> m_data; // Example data member
    };
    

    then declare the C++ module in the same file:

    PYBIND11_MODULE( my_reader_cpp, m ) {
        register_reader<MyReader>(m, "MyReader");
    }
    

    if the constructor requires more parameters, register it with the constructor signature (except the name):

    // Constructor signature:
    MyReader( std::string name, bool param1, std::vector<IElementReader> sub_readers )
    
    // Register the reader with the constructor signature:
    PYBIND11_MODULE( my_reader_cpp, m ) {
        register_reader<MyReader, bool, std::vector<IElementReader>>(m, "MyReader");
    }
    

[!IMPORTANT] Use std::shared_ptr for data members in your reader class, as uproot-custom will manage the memory of the data members. This is important to avoid memory leaks and ensure proper cleanup.

  1. Create a CMakeLists.txt file in cpp directory:

    cmake_minimum_required(VERSION 3.20)
    
    if(CMAKE_VERSION VERSION_GREATER_EQUAL 3.27)
        cmake_policy(SET CMP0148 NEW)
    endif()
    
    set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
    set(CMAKE_CXX_STANDARD 20)
    
    project(${SKBUILD_PROJECT_NAME}
        VERSION ${SKBUILD_PROJECT_VERSION}
        LANGUAGES CXX
    )
        
    set(PYBIND11_NEWPYTHON ON)
    find_package(pybind11 REQUIRED)
    find_package(uproot-custom REQUIRED)
    
    pybind11_add_module(my_reader_cpp
        my_reader.cc
        # Add other source files here if needed
    )
    
    target_link_libraries(my_reader_cpp PRIVATE uproot-custom)
    
    if(DEFINED SKBUILD_PROJECT_NAME)
        install(
            TARGETS my_reader_cpp
            LIBRARY DESTINATION ${SKBUILD_PROJECT_NAME}
        )
    endif()
    

Implement the Python reader

  1. Create a my_reader directory in the root directory of your project, and create a __init__.py file in it.

  2. In __init__.py, import the C++ module and implement your Python reader class:

    from . import my_reader_cpp as _cpp
    from uproot_custom import BaseReader
    
    
    class MyReader(BaseReader):
        @classmethod
        def gen_tree_config(
            cls,
            top_type_name: str,
            cls_streamer_info: dict,
            all_streamer_info: dict,
            item_path: str = "",
        ) -> dict | None:
            """
            Identify the node in the information tree,
            return the configuration dictionary if the node is matched,
            otherwise return None.
            """
    
        @classmethod
        def get_cpp_reader(cls, tree_config) -> _cpp.MyReader | None:
            """
            Identify the tree_config,
            if it is matched, return the C++ reader instance,
            otherwise return None.
            """
    
        @classmethod
        def reconstruct_array(cls, raw_data, tree_config):
            """
            Reconstruct the raw data to an `awkward` array according to the tree_config.
            """
    

    ![NOTE] The @classmethod is not necesarry, but when a regular member method is used, you should pass the instance of the class to registered_readers.

Register the reader

Register branch path

The default interpretation uproot_custom.AsCustom needs to know which branch to read with custom readers. You can export the branch path with:

import uproot
from uproot_custom import regularize_object_path

f = uproot.open("my_file.root")
branch = f["path/to/my_branch"]

print(regularize_object_path(branch.object_path))

This will print the regularized object path like /my_tree:my_branch. Then you can add it to the AsCustom.target_branches set:

from uproot_custom import AsCustom

AsCustom.target_branches.add("your-branch-path")

Register the reader

To let uproot_custom.AsCustom know your reader, you need to register it:

from uproot_custom import registered_readers
from my_reader import MyReader

registered_readers.add(MyReader)

Then you can use uproot to read the custom class as usual.

[!TIP] It is recommended to do the registration in your project __init__.py, so that you can use your custom reader as long as you import your project.

Download files

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

Source Distribution

uproot_custom-1.0.0a5.tar.gz (901.3 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

uproot_custom-1.0.0a5-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (173.6 kB view details)

Uploaded CPython 3.13manylinux: glibc 2.17+ x86-64

uproot_custom-1.0.0a5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (173.5 kB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ x86-64

uproot_custom-1.0.0a5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (172.8 kB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64

uproot_custom-1.0.0a5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (171.7 kB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

uproot_custom-1.0.0a5-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (171.8 kB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

File details

Details for the file uproot_custom-1.0.0a5.tar.gz.

File metadata

  • Download URL: uproot_custom-1.0.0a5.tar.gz
  • Upload date:
  • Size: 901.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for uproot_custom-1.0.0a5.tar.gz
Algorithm Hash digest
SHA256 7ee416c864be54bb36fc59f99de15777e071ed7fd58a3c4700558faaa9da904f
MD5 5cc8d1ef2a04fef22553d16e0ab456d8
BLAKE2b-256 d0d8f6a6bc918e2a78f4b0e8fdb8e4b0d4f13b5eacb24f6d19e99328f03da4e1

See more details on using hashes here.

Provenance

The following attestation bundles were made for uproot_custom-1.0.0a5.tar.gz:

Publisher: python-publish.yml on mrzimu/uproot-custom

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file uproot_custom-1.0.0a5-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for uproot_custom-1.0.0a5-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c90576d32d0064f16986a2afa26fbf6b467b00181595030444657592d4acf9b0
MD5 88940786efbfdb30c52f64a4c474a47d
BLAKE2b-256 36ac851230f85a2a569cedf2a586827544eeb1608215698dd59ce87f0fe10b55

See more details on using hashes here.

Provenance

The following attestation bundles were made for uproot_custom-1.0.0a5-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl:

Publisher: python-publish.yml on mrzimu/uproot-custom

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file uproot_custom-1.0.0a5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for uproot_custom-1.0.0a5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2eb8de197d3469ed088317a0c7662acca39ff771fcb72d9fd98d60ddd572ae80
MD5 6690c5b2363729ff7e1d1fb04c44e35a
BLAKE2b-256 c526cdd718d05fbca381aa4455587419aac123a8e9f7bf1d7f4bbceeea1cdbf4

See more details on using hashes here.

Provenance

The following attestation bundles were made for uproot_custom-1.0.0a5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl:

Publisher: python-publish.yml on mrzimu/uproot-custom

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file uproot_custom-1.0.0a5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for uproot_custom-1.0.0a5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 9f5d261b97c746aaac69e2037e52bcfbcdf88d136ba278ab06e8e65da6ae9cc8
MD5 ece144368dffc159796aa78e01ee4e38
BLAKE2b-256 e738bbce02c45530c01c07aa348c57b3bbc7c58d80b969e096528ec6094a95c5

See more details on using hashes here.

Provenance

The following attestation bundles were made for uproot_custom-1.0.0a5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl:

Publisher: python-publish.yml on mrzimu/uproot-custom

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file uproot_custom-1.0.0a5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for uproot_custom-1.0.0a5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6d9d1ee1f50424fa8f96f543ef555f00f542a8b6b7435f5a17888d3895ede776
MD5 fdb90822afcea08367ed8be69ad4f6c7
BLAKE2b-256 4be46dfe8bfcf4c0d070c870ed07a62fa8b155f4875d30f120992e058aeef0c3

See more details on using hashes here.

Provenance

The following attestation bundles were made for uproot_custom-1.0.0a5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl:

Publisher: python-publish.yml on mrzimu/uproot-custom

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file uproot_custom-1.0.0a5-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for uproot_custom-1.0.0a5-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b9a7a3821da0cc11121f13943a9cfc467d5b496afbb70af93322a08494532c20
MD5 ae41beeb1b665a45a3ea276a80450e81
BLAKE2b-256 e791d66caef7519056f1a8f80590683661ee86dccff751a0a01c336530f759b8

See more details on using hashes here.

Provenance

The following attestation bundles were made for uproot_custom-1.0.0a5-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl:

Publisher: python-publish.yml on mrzimu/uproot-custom

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page