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is the introduction to SNiPER framework and its application in JUNO experiment\n"},"motivation.html":{"url":"motivation.html","title":"Motivation","keywords":"","body":"The offline software system is developed for the offline data processing, including Monte Carlo (MC) data production as well as experimental data processing and physics analysis. Usually the offline software system consists of framework, generator, detector simulation, electronics simulation, calibration, reconstruction and physics analysis tools. The framework takes very important roles for the performance, functionality, flexibility, extensibility as well as portability of the whole offline software system in many current high energy physics (HEP) experiments.\nThe framework provides most of the common functionalities according to the offline data processing in HEP experiments, such as: data management, data processing controlling, data storage, common services and tools, friendly user interface. The framework builds the unified software environments and platform to develop application software such as Event generators, Detector simulation, Electronics Simulation, Calibration, Reconstruction and Physics analysis tools. It defines the standard interfaces between different applications, therefore many people can synchronously develop their applications. All applications developed by following the standard interfaces can be smoothly plugged into the framework and run very well.\nFor collider physics experiments, there is a very popular and powerful framework, Gaudi, developed by the LHCb experiment. Originally Gaudi was designed for processing independent events (or collider experiments) such as ATLAS, BESIII although it currently also is used by other non-collider experiments such as, FERMi, MINERvA, Daya Bay and LBNE with some extensions on their data management system.\nSNiPER (abbreviation of Software for Non-collider Physics ExpeRiment) is designed and developed for non-collider physics Experiments from scratch with Object-Oriented technology and bi-language, C++ and Python. It evolved from the LAF (light weighted Analysis Framework) of Daya Bay experiment and also learned some technologies from Gaudi. SNiPER does have many innovations on the management of dependent events by introducing event buffer mechanism, multi-task processing controlling, less dependences on the third-party software and tools. SNiPER also reserved the interfaces to implementation of multi-threading computing. More details can be found at the following chapters.\n"},"Architecture/0.Architecture.html":{"url":"Architecture/0.Architecture.html","title":"Architecture","keywords":"","body":"Architecture\nIn this chapter, we will give some general introductions to the SNiPER architecture. We hope you will have a brief impression to the main conpoments and principles of the framework.\n"},"Architecture/1.Concepts.html":{"url":"Architecture/1.Concepts.html","title":"General Concepts","keywords":"","body":"General Concepts\nIn SNiPER, users can implement their own modules, which can be loaded and executed dynamically at run time. We call these modules as Dynamically Loadable Elements (DLE). According to the roles they played in SNiPER, DLE modules are further distinguished as algorithms, services and tasks.\n\nIt’s helpful if you are familiar with Gaudi. There are some similarity. The concepts of algorithm and service in SNiPER are equivalent to that in Gaudi, and task is somewhat like the application manager. However, we will assume our readers as fresh users of any software frameworks. \n\nLet's consider a general data processing procedure. There are a seqence of events in the data, and we process the events one by one with a loop (the so-called events loop).\nCreated with Raphaël 2.1.4StartMore Event ?Read an EventProcess an EventSave ResultEndyesno\nThere can be a fixed procedure to each event: read in the event data, perform some calculation, and then write out the result. During the calculation, we may occasionally access the detector geometry, database, or anything else. In this application, each subroutine can be implemented as a module, so that they can be assembled and reused easily for different purpose. These subroutines, in SNiPER, are mainly the algorithms and services.\nThe following show the difference between algorithm and service, and the role of task.\n\nalgorithm: the calculation subroutine that applied to each event, for example, a reconstruction algorithm. Generally it is invoked by the framework during the event loop.\nservice: the subroutine to provide a specific functionality, for example, users can access the detector geometry via the specified geometry service. It can be invoked by users' code or the framework whenever we want.\ntask: the manager of algorithms and services, and the controller of the event loop. The entrance of a SNiPER application is always a task.\n\nIn SNiPER, there are some more assistant functionalities that can be invoked globally, including PropertyMgr, SniperLog and IncidentMgr.\n\nproperty: a configurable variable. Users can customize its value during the job configuration, without code modification and re-compiling.\nSniperLog: logs with output levels. Users can selectively print more or less messages, for debugging or production purpose.\nincident: a trigger to the registered subroutines (incident handlers). This is also a concept that taken from Gaudi.\n\nThe following picture shows these components togother.\n\n"},"Architecture/2.Interfaces.html":{"url":"Architecture/2.Interfaces.html","title":"Interfaces","keywords":"","body":"User Interfaces\nIn a framework, there are always some conventions to implement a module. Only the legal modules can be recognized by the framework, and be used like plugins.\nIn SNiPER, the most frequently used concepts are algorithm and service. They are expressed as C++ classes.\n\na concrete algorithm class must be inherited from the AlgBase class;\na concrete service class must be inherithed from the SvcBase class;\n\nMoreover, we have to at least implement the following 3 methods in a concrete algorithm, which are defined as abstract interface in the base classes.\n\ninitialize(): be invoked once by the framework before the event loop. We can add any preparation works here.\nexecute(): be invoked once to each event by the framework during the event loop. We can perform the data calculations here.\nfinalize(): be invoked once by the framework after the event loop.\n\nIt is similar to a concrete service class, except that the SvcBase class doesn't have an abstract execute() method.\nThe following picture shows the core C++ class diagram in SniperKernel.\n\nSuppose we have implemented an algorithm, then how to use it in our job? This is configured by the Python interface of SNiPER.\nLet's take an example, there is a HelloAlg algorithm class in the SNiPER (package Examples/HelloWorld). Then a minimal Python configuration may look like the following code.\n#!/usr/bin/env python\n\nimport Sniper\ntask = Sniper.Task(\"task\")  # create a Task instance\ntask.setEvtMax(3)  # set the number of the event loop\n\nimport HelloWorld  # load the HelloWorld module into SNiPER\ntask.property(\"algs\").append(\"HelloAlg\")  # create a HelloAlg instance\n\n#start the processing procedure\n#the HelloAlg::execute() will be invoked 3 times during the event loop\ntask.run()\n\nWe can save the code in a python script file and execute it directly.\n$ python run.py\nWe only show the form to configure and execute a SNiPER application here. The details will be described in later setions.\n"},"Architecture/3.ExeSeq.html":{"url":"Architecture/3.ExeSeq.html","title":"Execution Sequence","keywords":"","body":"Execution Sequence\nThe execution of SNiPER mainly consists of 3 steps, initialize, events loop and finalize. Each step consists some sub-steps as following,\n\ninitialize\nall services are initialized in the order of their creation;\nthen all algorithms are initialized in the order of their creation;\n\n\nevents loop: loop all events. To each event, the following procedures are applied,\nbroadcast an incident named BeginEvt (begin event);\ninvoke the execute() method of all algorithms, in the order of their creation;\nbroadcast an incident named EndEvt (end event);\n\n\nfinalize\nall algorithms are finalized in the inverted order of their creation;\nthen all services are finalized in the inverted order of their creation;\n\n\n\nThe following shows the execution sequence diagram.\nCreated with Raphaël 2.1.4TaskTaskSvcSupervisorSvcSupervisorAlgSupervisorAlgSupervisorIncidentMgrIncidentMgrconfiginitializeinitializeservices listinitializeinitializealgorithms liststart events loopBeginEvtexecute allalgorithmsoptional invokesresultEndEvtloop to BeginEvtend events loopfinalizefinalizealgorithms listfinalizefinalizeservices listterminate\n"},"Algorithms/0.Algorithms.html":{"url":"Algorithms/0.Algorithms.html","title":"Algorithms","keywords":"","body":"Algorithms\nThe algorithm is the basic block of a data processing procedure. In this chapter, we will show how to implement and use an algorithm via a very simple example. The content covers the C++ algorithm code and Python configuration. Please see the appendix to find how to setup the environment and compile a package by CMT.\n"},"Algorithms/1.CppCode.html":{"url":"Algorithms/1.CppCode.html","title":"C++ Implementation","keywords":"","body":"The C++ Code\nSuppose we have created a package named FirstAlg, and we want to define an algorithm with the same name. The necessary work includes,\n\ndefine a C++ class named FirstAlg, which is inherited from the AlgBase class;\ndefine a constructor, which takes a string parameter;\nimplement the 3 abstract methods in base class, initialize(), execute() and finalize(); The bool return value indicates the execution status. If there is any error, the return value should be false, and the application will be stopped.\n\nClass defination\nIn the example, we will also involve the properties, which are defined as the data members of the algorithm class.\nThe contents of the header file (FirstAlg.h),\n// file FirstAlg.h\n#ifndef FIRST_ALG_H\n#define FIRST_ALG_H\n\n#include \"SniperKernel/AlgBase.h\"  //the AlgBase defination\n\nclass FirstAlg : public AlgBase\n{\n    public:\n        FirstAlg(const std::string& name);  //constructor\n\n        bool initialize();\n        bool execute();\n        bool finalize();\n\n    private:\n        unsigned int  m_count;  //the count of event loop\n        int           m_value;  //an int property\n        std::string   m_msg;    //a string property\n};\n#endif\n\nAlgorithm declaration\nAn algorithm must be declared in SNiPER, so that it can be registered into the framework when the module is loaded. This is done by a macro DECLARE_ALGORITHM, which takes the algorithm class name as its parameter. It's recommended to put the declaration at the beginning of the source file.\nDECLARE_ALGORITHM(FirstAlg);\n\nProperties\nProperties are the C++ variables that configurable in Python at run time. In an algorithm, a property can be declared by the declProp() method. This method takes 2 parameters, the first is the name of the property, and the second is its correlated variable.\nThe following variable types can be declared as properties,\n\nscalar: C++ build in types and std::string;\nstd::vector with scalar element type\nstd::map with scalar key type and scalar value type\n\nThe properties have to be declared in the constructor. We can set a default value while the declaration. For example,\ndeclProp(\"TheValue\", m_value = 1);\nLogs\nWe can print any message via SniperLog just like the std::cout.\nLogDebug The corresponding message on the screen is,\ntask:FirstAlg.execute         DEBUG: in the FirstAlg::execute()\nAt the beginning, it shows this is a log printed in the execute() method of FirstAlg. Then, it is an indicator of the log level. And finally it is the log content.\nThere are 6 log levels in SNiPER. From lowest to highest they are,\n\n0: LogTest, the indicator is \"TEST\";\n2: LogDebug, the indicator is \"DEBUG\";\n3: LogInfo, the indicator is \"INFO\";\n4: LogWarn, the indicator is \"WARN\", means this is a warning message;\n5: LogError, the indicator is \"ERROR\";\n6: LogFatal, the indicator is \"FATAL\";\n\nWe can set the log level globally via Task, or set a different log level to each DLE component. Then the logs with lower levels will not shown on the screen.\nThe implementation\nWe put the contents together. Here is the implementation of the source file (FirstAlg.cc),\n// file FirstAlg.cc\n#include \"FirstAlg.h\"\n#include \"SniperKernel/AlgFactory.h\"  //the macro DECLARE_ALGORITHM\n\nDECLARE_ALGORITHM(FirstAlg);\n\nFirstAlg::FirstAlg(const std::string& name)\n    : AlgBase(name),\n      m_count(0)\n{\n    declProp(\"TheValue\", m_value = 1);\n    declProp(\"Message\",  m_msg);\n}\n\nbool FirstAlg::initialize()\n{\n    LogDebug \n"},"Algorithms/2.Python.html":{"url":"Algorithms/2.Python.html","title":"Python Configuration and Execution","keywords":"","body":"Python Configuration and Execution\nLoad and Register an Algorithm\nAfter the compilation, a dynamic library is generated. Suppose it is named as \"libFirstAlg.so\". We can load the library in python like this,\nimport Sniper\nSniper.loadDll(\"libFirstAlg.so\")\n\nThen the algorithm FirstAlg is automatically registered and can be used in SNiPER.\nHowever, if we want to use the package in Python style, we can wrap the previous code in a Python module. In the FirstAlg package, we can make the Python module by adding the code in the following file (please keep the directory structure),\npython/FirstAlg/__init__.py\nThen we can load and register FirstAlg with a single line in the main Python configuration script,\nimport FirstAlg\n\nA SNiPER application is always start from a Task instance. When an algorithm is registered, we can create its instance via the Task,\ntask.createAlg(\"FirstAlg\")\nConfigure a Job\nThe following Python code shows a complete executable SNiPER application,\n#!/usr/bin/env python\n\nimport Sniper\ntask = Sniper.Task(\"task\")  # create a Task instance\ntask.setEvtMax(3)  # events loop number (3 times)\ntask.setLogLevel(2)  # the SniperLog print level\n\nimport FirstAlg\nalg = task.createAlg(\"FirstAlg\")  # create a FirstAlg instance\nalg.property(\"TheValue\").set(2)\nalg.property(\"Message\").set(\" the value is \")\n\ntask.run()\n\nIn the example, we will execute the FirstAlg 3 time during events loop. The 2 properties are set via their names. The values of the correlated C++ variables will be directly modified. The result of this configuration is,\n$ python run.py\n*****************************************\n***     Welcome to SNiPER Python      ***\n*****************************************\nRunning @ lxslc603.ihep.ac.cn on Mon Dec 10 10:18:39 2017\n\ntask:FirstAlg.initialize      DEBUG: in the FirstAlg::initialize()\ntask.initialize                INFO: initialized\ntask:FirstAlg.execute         DEBUG: in the FirstAlg::execute()\ntask:FirstAlg.execute          INFO: Loop 1 the value is 2\ntask:FirstAlg.execute         DEBUG: in the FirstAlg::execute()\ntask:FirstAlg.execute          INFO: Loop 2 the value is 4\ntask:FirstAlg.execute         DEBUG: in the FirstAlg::execute()\ntask:FirstAlg.execute          INFO: Loop 3 the value is 12\ntask:FirstAlg.finalize        DEBUG: in the FirstAlg::finalize()\ntask.finalize                  INFO: finalized\n\n***  SNiPER Terminated Successfully!  ***\nDLE Instance Name\nIn the previous section, we defined a constructor with a string parameter in FirstAlg. That means we can assign a name to the algorithm instance. In fact, each DLE (algorithm, service and task) instance has a name, and the name can be customizd. The default name of algorithm/service is its class name. We can assign a different one when we create the instance,\ntask.createAlg(\"FirstAlg/NewName\")\nThe sub-string after \"/\" is the instance name we assigned.\nIn this way, we can create more than one instances of an algorithm without conflicts. For example,\n#!/usr/bin/env python\n\nimport Sniper\ntask = Sniper.Task(\"App\")\ntask.setEvtMax(3)\ntask.setLogLevel(3)\n\nimport FirstAlg\nalg1 = task.createAlg(\"FirstAlg/Alg1\")\nalg1.property(\"TheValue\").set(2)\nalg1.property(\"Message\").set(\" the value is \")\n\nalg2 = task.createAlg(\"FirstAlg/Alg2\")\nalg2.property(\"TheValue\").set(20)\nalg2.property(\"Message\").set(\" the value is \")\n\ntask.run()\n\nIn this example, we create 2 instances of FirstAlg with different names Alg1 and Alg2. Please notice that,\n\nwe assign a new name (\"App\") to the Task instance, too;\nwe changed the log level to 3, so the DEBUG messages will not be printed;\nthe 2 algorithm instances, Alg1 and Alg2, have different property values;\n\nThen the result of this configuration is,\n$ python run.py\n*****************************************\n***     Welcome to SNiPER Python      ***\n*****************************************\nRunning @ lxslc603.ihep.ac.cn on Mon Dec 10 10:56:17 2017\n\nApp.initialize                 INFO: initialized\nApp:Alg1.execute               INFO: Loop 1 the value is 2\nApp:Alg2.execute               INFO: Loop 1 the value is 20\nApp:Alg1.execute               INFO: Loop 2 the value is 4\nApp:Alg2.execute               INFO: Loop 2 the value is 40\nApp:Alg1.execute               INFO: Loop 3 the value is 12\nApp:Alg2.execute               INFO: Loop 3 the value is 120\nApp.finalize                   INFO: finalized\n\n***  SNiPER Terminated Successfully!  ***\nPlease compare the logs and find the difference to the previous example. It is helpful to understand the DLE names and the SniperLog.\n"},"Services/0.Services.html":{"url":"Services/0.Services.html","title":"Services","keywords":"","body":"Services\nA service is a subroutine that can be invoked by users on demand. In this chapter, we will show how to implement and use a service module. For the similarity between service and algorithm, we will concentrate on the differences, but not all the details.\n"},"Services/1.CppCode.html":{"url":"Services/1.CppCode.html","title":"C++ Implementation","keywords":"","body":"The C++ code\nWe will implement a service named FirstSvc.\nFor a service can be invoked by others, the header file should be visible globally. We can export the FirstSvc.h header file directly for simplicity. However, we can add a pure virtual class to declare the user APIs. So that we can implement different services with the same APIs. These services can be replaced with each other. This is an useful feature in a framework.\nThe defination of the pure virtual class is,\n// file FirstSvc/IfMySvc.h\n#ifndef IF_MY_SVC_H\n#define IF_MY_SVC_H\n\nclass IfMySvc\n{\n    public:\n        virtual void doSomeThing() = 0;\n};\n#endif\n\nWe put this header file in a seperated directory, and copy it into a directory that can be found by the compiler. (This is guaranteed by a pattern of CMT at present.)\nWe use a multiple inheritance in the defination of FirstSvc. The code is,\n// file FirstSvc.h\n#ifndef FIRST_SVC_H\n#define FIRST_SVC_H\n\n#include \"FirstSvc/IfMySvc.h\"\n#include \"SniperKernel/SvcBase.h\"\n\nclass FirstSvc : public SvcBase, public IfMySvc\n{\n    public:\n        FirstSvc(const std::string& name);\n\n        bool initialize();\n        bool finalize();\n\n        void doSomeThing();\n};\n#endif\n\nThere is no execute() method. Instead, we should implement the method doSomeThing() as the user API.\nThe source file is,\n// file FirstSvc.cc\n#include \"FirstSvc/FirstSvc.h\"\n#include \"SniperKernel/SvcFactory.h\"\n\nDECLARE_SERVICE(FirstSvc);\n\nFirstSvc::FirstSvc(const std::string& name)\n    : SvcBase(name)\n{\n}\n\nbool FirstSvc::initialize()\n{\n    LogDebug \nLike the algorithm, a service must be declared by a macro DECLARE_SERVICE. We can declare properties in the servcie constructor, too. But we will not repeat this here.\nIn this example, we only print a message in the doSomeThing() API.\n"},"Services/2.Invoke.html":{"url":"Services/2.Invoke.html","title":"Invoke a Service","keywords":"","body":"Invoke a Service\nIn this section we create a new algorithm, SecondAlg, in which the FirstSvc is invoked.\nThe header file is,\n// file SecondAlg.h\n#ifndef SECOND_ALG_H\n#define SECOND_ALG_H\n\n#include \"SniperKernel/AlgBase.h\"\n\nclass IfMySvc;\n\nclass SecondAlg : public AlgBase\n{\n    public:\n        SecondAlg(const std::string& name);\n\n        bool initialize();\n        bool execute();\n        bool finalize();\n\n    private:\n        unsigned int  m_count;\n        IfMySvc*      m_svc;\n};\n#endif\n\nAnd the source file is,\n// file SecondAlg.cc\n#include \"SecondAlg.h\"\n#include \"FirstSvc/IfMySvc.h\"\n#include \"SniperKernel/AlgFactory.h\"\n\nDECLARE_ALGORITHM(SecondAlg);\n\nSecondAlg::SecondAlg(const std::string& name)\n    : AlgBase(name),\n      m_count(0)\n{\n}\n\nbool SecondAlg::initialize()\n{\n    LogDebug  _svc(this->getScope(), \"MyService\");\n    if ( _svc.valid() ) {\n        LogInfo doSomeThing();\n    }\n\n    return true;\n}\n\nbool SecondAlg::finalize()\n{\n    LogDebug \nIn order to avoid the retrieval of FirstSvc in each time of the events loop, we retrieve it in initialize(), which is executed only once at the beginning of the application. A class template, SniperPtr, is used for the retrival. Then the raw pointer is assigned to the data member m_svc.\n\nthe template parameter can be the concrete type of the service (FirstSvc), or the pure virtual base class (IfMySvc). We use the later one for flexibility in this example.\nthe 1st constructor parameter indicates where to find the service. In most situations it is this->getScope(). It might be different when we have multiple Task instances, which will be described as an advanced topic in later sections.\nthe 2nd constructor parameter indicates the name of the service instance;\n\nDuring the event loop, the service is not always invoked. In this example, it's invoked only when the loop count is odd.\n"},"Services/3.Python.html":{"url":"Services/3.Python.html","title":"Python Configuration and Execution","keywords":"","body":"Python Configuration and Execution\nThe Python configuration script is,\n#!/usr/bin/env python\n\nimport Sniper\ntask = Sniper.Task(\"task\")\ntask.setEvtMax(3)\ntask.setLogLevel(3)\n\nimport FirstSvc\ntask.createSvc(\"FirstSvc/MyService\")\n\nimport SecondAlg\ntask.createAlg(\"SecondAlg\")\n\ntask.run()\n\nAnd the execution result is,\n$ python run.py\n*****************************************\n***     Welcome to SNiPER Python      ***\n*****************************************\nRunning @ lxslc603.ihep.ac.cn on Mon Dec 10 12:58:26 2017\n\ntask:SecondAlg.initialize      INFO: the IfMySvc instance is retrieved\ntask.initialize                INFO: initialized\ntask:SecondAlg.execute         INFO: loop 1\ntask:MyService.doSomeThing     INFO: Do some thing in a service\ntask:SecondAlg.execute         INFO: loop 2\ntask:SecondAlg.execute         INFO: loop 3\ntask:MyService.doSomeThing     INFO: Do some thing in a service\ntask.finalize                  INFO: finalized\n\n***  SNiPER Terminated Successfully!  ***\nPlease notice that we retrieve the service instance via the name \"MyService\" in C++, which is not a fixed service type. Then in Python, we assigne the name of the FirstSvc instance as \"MyService\". \nIt's simple to implement a new service with the same API, \nclass SecondSvc : public SvcBase, public IfMySvc\n{\n    // the definations ...\n}\n\nAnd it's simple to replace FirstSvc by SecondSvc in the Python configuration,\n#import FirstSvc\n#task.createSvc(\"FirstSvc/MyService\")\nimport SecondSvc\ntask.createSvc(\"SecondSvc/MyService\")\n\nIn this way, we can flexibly assemble many DLE modules and add/remove/replace each one of them, just by configuration.\n"},"Task/0.Task.html":{"url":"Task/0.Task.html","title":"Tasks","keywords":"","body":"Task\nTasks act as lightweight application managers, containing algorithms, DataBuffer, services and other subtasks. Tasks are dynamically configurable and orchestrate the sequential execution of the contained algorithms. Different tasks are executed with an incident mechanism, enabling event mixing and splitting to be implemented.\n"},"Task/1.StateMachine.html":{"url":"Task/1.StateMachine.html","title":"State Machine","keywords":"","body":"State Machine\n\n"},"DataManagement.html":{"url":"DataManagement.html","title":"Data Management","keywords":"","body":"Data Management\nData management system is designed to manage the event data during offline data processing. It includes the event data model (EDM) which defines the event data entity to be processed, the memory manager that holds the EDM objects in memory and the data input/output (I/O) system that implements the writing and reading of data files.\nSNiPER provides the basic idea and architecture of data management system, on which developers could develop the experiment-specific system based on their requirements. This chapter introduces the basic SNiPER data management architecture as well as the data management system of JUNO (Jiangmen Underground Neutrino Observation) offline software as an example.\n"},"DataManagement/basic-concept.html":{"url":"DataManagement/basic-concept.html","title":"General Concept","keywords":"","body":"General Concept\nIn previous chapters, we have introduced the primary components of SNiPER, including Task, Algorithm and Service, and how the event processing procedure (event loop) is achieved based on them.\n"},"DataManagement/relevant-tools.html":{"url":"DataManagement/relevant-tools.html","title":"Relevant Utilities","keywords":"","body":""},"DataManagement/data-buffer.html":{"url":"DataManagement/data-buffer.html","title":"Data Buffer","keywords":"","body":"Data Buffer\nDataBuffer is a dynamically allocated region of memory that holds multiple events in order to facilitate correlation analysis. The size is configured with a time window. In each execution, an event acts as the anchor of the time window and its adjacent events in the time window are cached in the DataBuffer simultaneously. During the event loops, the anchor event moves forward one by one, and events in the time window are accordingly updated.\n"},"DataManagement/rootwriter.html":{"url":"DataManagement/rootwriter.html","title":"RootWriter","keywords":"","body":""},"DataManagement/example-juno-data-management.html":{"url":"DataManagement/example-juno-data-management.html","title":"Example: JUNO Data Management","keywords":"","body":""},"Tools.html":{"url":"Tools.html","title":"Tools","keywords":"","body":"Tools\n"}}}