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What is proio?

Proio is a language-neutral IO scheme for medium- and high-energy physics. It was born from an exploratory project at Argonne National Laboratory called eicio, and inspired by ProMC and EicMC. In order to be language-neutral, proio leverages Google's Protobuf compiler and associated libraries in various languages. The Protobuf compiler generates code in each language to be used that represents the data model described in proio.proto. In addition, thin libraries have been written in each language that are independent of the data model. Therefore, the data model can evolve in a language-independent way.

The name "proio" comes from the fact that it leverages Google's Protobuf, as well as from the prefix "proto" itself. A proto language is a common language that others evolve from. Similarly, proio can be the commonality between multiple experiments with slightly different data model needs. Each experiment can create necessary extensions to a core data model, and still maintain the ability to share data. Alternatively, experiments with particular needs can start the data model from scratch.

Data structure

Proio is a stream-oriented IO. Data are organized into events, and a proio stream is simply one serialized event followed by another. A proio file (*.proio or *.proio.gz) is no different than a proio stream, except that it is seekable (one can look back to the beginning of the file). As alluded to by the possible *.proio.gz extension, the proio stream can be used either compressed or uncompressed (for performance/space trade-offs), and a compressed stream is simply an uncompressed proio stream wrapped in a gzip stream. Proio is designed so that the following operations are valid:

cat run1.proio run2.proio > allruns.proio
gzip run1.proio run2.proio
cat run1.proio.gz run2.proio.gz > allruns.proio.gz

Additionally, both uncompressed and compressed proio streams and files can be arbitrarily large.

Within each event there is an event header - containing metadata for the event such as a timestamp as well as internal information about the structure of the data within the event. The event data are stored in what is referred to as the event payload, and within this payload is a set of collections. Each collection has a name and a type, and the type determines what kind of entries can be stored in the collection. The number of entries is arbitrary. The collections and entries are serialized by Protobuf, and all are described in the model directory. (Since the data structures are serialized by Protobuf, integer fields gain additional compressed by Google's "varints") As an example of a collection type, let's look at the MCParticle defined in model/lcio/lcio.proto:

message MCParticle {
	uint32 id = 1;
	repeated Reference parents = 2;
	repeated Reference children = 3;
	int32 PDG = 4;
	repeated double vertex = 5;
	float time = 6;
	repeated double p = 7;
	double mass = 8;
	float charge = 9;
	repeated double PEndPoint = 10;
	repeated float spin = 11;
	repeated int32 colorFlow = 12;

	int32 genStatus = 13;
	uint32 simStatus = 14;
}

message MCParticleCollection {
	uint32 id = 1;
	uint32 flags = 2;
	Params params = 3;
	repeated MCParticle entries = 4;
}

MCParticle represents generator-level particles in the LCIO data model, and these are stored in collections of type MCParticleCollection. A collection of this type may be placed into the event payload alongside other collections with the same or different type. The thin language-specific libraries each provide a type called Event which provides methods for adding, removing, and retrieving collections from the payload.

Referencing

Another key feature of proio is referencing. This is a concept taken from LCIO where persistent references to any collection or collection entry can be stored in another. This is implemented in the thin language-specific libraries with Reference() and Dereference() methods. These methods are associated with the event, which keeps track of the number of unique identifiers. The Reference() methods will take a collection or entry as an argument and return a Reference type object, which is a message described in model/proio.proto. Conversely, Dereference() will take a Reference type object and return the collection or entry that the Reference points to. One example of this can be found at the top of the go-proio API documentation: GoDoc

Getting started

Command-line tools

Tools are specific to each language implementation. However, most tools will continue to be written in go, and there are already a few useful ones. Let's try out a few. First, make sure you have the go compiler installed on your system, and make sure your GOPATH and PATH environment variables are set up appropriately to effectively use go get. A typical configuration is to set GOPATH=$HOME and PATH=$GOPATH/bin:$PATH. Then, let's grab and install the proio package:

go get github.com/decibelcooper/proio/go-proio/...

And then we can play around with manipulating the sample files...

Summarize and dump

proio-summary samples/smallSample.proio
proio-ls samples/smallSample.proio | less

Strip

proio-strip samples/smallSample.proio MCParticle BeamCalHits | proio-summary -
proio-strip -k samples/smallSample.proio MCParticle BeamCalHits | proio-summary -

Concat

cp samples/smallSample.proio.gz tmp.proio.gz
cat samples/smallSample.proio.gz tmp.proio.gz | proio-summary -g -

Cut

dd if=samples/smallSample.proio of=roughCut.proio bs=500K count=1
proio-strip -o cleanCut.proio.gz roughCut.proio
proio-summary cleanCut.proio.gz

Read examples

Go

package main

import (
    "fmt"
    "log"

    "github.com/decibelcooper/proio/go-proio"
    "github.com/decibelcooper/proio/go-proio/model/lcio"
)

func main() {
    reader, err := proio.Open("samples/smallSample.proio.gz")
    if err != nil {
        log.Fatal(err)
    }

    for event := range reader.ScanEvents() {
        mcColl := event.Get("MCParticle").(*lcio.MCParticleCollection)
        if mcColl == nil || len(mcColl.Entries) < 1 {
            continue
        }

        mcPart := mcColl.Entries[0]
        fmt.Println(mcPart)
    }
}

Python

import proio
  
with proio.Reader("samples/smallSample.proio.gz") as reader:
    for event in reader:
        mc_coll = event.get("MCParticle")
        if mc_coll == None or len(mc_coll.entries) < 1:
            continue

        mc_part = mc_coll.entries[0]
        print(mc_part)

C++

#include <iostream>

#include "proio/event.h"
#include "proio/model/lcio/lcio.pb.h"
#include "proio/reader.h"

using namespace proio::model;

int main(int argc, const char **argv) {
    auto reader = new proio::Reader("samples/smallSample.proio.gz");

    proio::Event *event;
    while ((event = reader->Get()) != NULL) {
        auto mcColl = (lcio::MCParticleCollection *)event->Get("MCParticle");
        if (mcColl == NULL || mcColl->entries_size() < 1) continue;

        lcio::MCParticle mcPart = mcColl->entries(0);
        std::cout << mcPart.DebugString() << std::endl;

        delete event;
    }

    delete reader;
    return EXIT_SUCCESS;
}

Java

import proio.Event;
import proio.Reader;
import proio.model.Lcio;

public class Read
{
    public static void main( String[] args )
    {
        try {
            Reader reader = new Reader("samples/smallSample.proio.gz");
            if (reader == null) return;

            for (Event event : reader) {
                Lcio.MCParticleCollection mcColl = (Lcio.MCParticleCollection) event.get("MCParticle");
                if (mcColl == null || mcColl.getEntriesCount() < 1) continue;

                Lcio.MCParticle mcPart = mcColl.getEntries(0);
                System.out.println(mcPart);
            }

            reader.close();
        } catch (Throwable e) {
            e.printStackTrace();
        }
    }
}

Write examples

Go

package main

import (
	"log"

	"github.com/decibelcooper/proio/go-proio"
	"github.com/decibelcooper/proio/go-proio/model/lcio"
)

func main() {
	writer, err := proio.Create("test.proio.gz")
	if err != nil {
		log.Fatal(err)
	}
	defer writer.Close()

	event := proio.NewEvent()
	mcColl := &lcio.MCParticleCollection{}
	event.Add(mcColl, "MCParticle")

	parent := &lcio.MCParticle{PDG: 443}
	mcColl.Entries = append(mcColl.Entries, parent)

	child1 := &lcio.MCParticle{PDG: 11}
	child2 := &lcio.MCParticle{PDG: -11}
	mcColl.Entries = append(mcColl.Entries, child1, child2)

	parent.Children = append(parent.Children, event.Reference(child1), event.Reference(child2))
	child1.Parents = append(child1.Children, event.Reference(parent))
	child2.Parents = append(child2.Children, event.Reference(parent))

	writer.Push(event)
}

Python

import proio
import proio.model.lcio as lcio

with proio.Writer("test.proio.gz") as writer:
    event = proio.Event()
    mc_coll = lcio.MCParticleCollection()
    event.add(mc_coll, "MCParticle")

    parent = mc_coll.entries.add()
    parent.PDG = 443

    child1 = mc_coll.entries.add()
    child1.PDG = 11
    child2 = mc_coll.entries.add()
    child2.PDG = -11

    parent.children.extend([event.reference(child1), event.reference(child2)])
    child1.parents.extend([event.reference(parent)])
    child2.parents.extend([event.reference(parent)])

    writer.push(event)

C++

#include <iostream>

#include "proio/event.h"
#include "proio/model/lcio/lcio.pb.h"
#include "proio/writer.h"

using namespace proio::model;

int main(int argc, const char **argv) {
    auto writer = new proio::Writer("test.proio.gz");

    auto event = new proio::Event();
    auto mcColl = new lcio::MCParticleCollection();
    event->Add(mcColl, "MCParticle");

    lcio::MCParticle *parent = mcColl->add_entries();
    parent->set_pdg(443);

    lcio::MCParticle *child1 = mcColl->add_entries();
    child1->set_pdg(11);
    lcio::MCParticle *child2 = mcColl->add_entries();
    child2->set_pdg(-11);

    event->Reference(child1, parent->add_children());
    event->Reference(child2, parent->add_children());
    event->Reference(parent, child1->add_parents());
    event->Reference(parent, child2->add_parents());

    writer->Push(event);

    delete event;

    delete writer;
    return EXIT_SUCCESS;
}

Adding to the data models

The data models are described in the model directory. For protobuf messages that define part of a data model, the following rules must be followed:

  1. For message type Msg, there must be a corresponding collection type named MsgCollection.
  2. Every message type and collection type must have a uint32 id field assigned any number.
  3. For collection type MsgCollection, there must be a repeated Msg entries field assigned any number. Any number of message and collection types may be defined. Other than the above rules, please see existing proto files as a guide for package naming conventions (at the top of the files). Please see the Protobuf Language Guide for details on the syntax.

Generating the code after modifying the model

Any time the data model protobuf files are modified, the language-specific code that describes the data model must be regenerated. For consistency, and because there are four different languages to generate, the code generation is done inside a container. In particular, we use a Singularity container. In order to generate the code, Singularity 2.3+ must be installed on your computer. Once it is installed, simply:

make

This will download over 1 GiB of container image layers from Docker Hub, and place the layers into a single image file called proio-gen.img that is twice as large (i.e. over 2 GiB). Please make sure you have the space before calling make. Once the image is created, a container will automatically be run to generate each piece of data model code for the different languages.

Backwards and forwards compatibility

It is important to understand a little bit about how Protobuf works to understand what changes can be made to the data model that maintain compatibility with other versions of the code. Please see the Protobuf documentation for details, but here are some important things to note:

  • New fields can be added without breaking forwards or backwards compatibility as long as new unique field numbers are used. This is because Protobuf will ignore unknown fields, and (staring with Protobuf 3) all fields are optional.
  • Fields can be removed from the data model for the same reason. It is important, however, to never reuse the field number or name of the removed field. In order to enforce this, the reserved tag should be use.
  • For the space-conscious, field numbers should be used wisely. The reason is that field numbers between 1 and 15 take one byte to identify, while larger field numbers must be identified with at least two bytes.