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  1. API reference
  2. Welcome
    1. Component overview
    2. Get Flexmonster
    3. Quick start
    4. System requirements
    5. Troubleshooting
    6. Managing license keys
    7. Migrating from WebDataRocks to Flexmonster
  3. Integration with frameworks
    1. Available tutorials
    2. Integration with Angular
    3. Integration with React
    4. Integration with Vue
    5. Other integrations
      1. Integration with Python
        1. Integration with Django
        2. Integration with Jupyter Notebook
      2. Integration with React Native
      3. Integration with AngularJS (v1.x)
      4. Integration with TypeScript
      5. Integration with R Shiny
      6. Integration with jQuery
      7. Integration with Ionic
      8. Integration with Electron.js
      9. Integration with Webpack
      10. Integration with RequireJS
  4. Connecting to Data Source
    1. Supported data sources
    2. JSON
      1. Connecting to JSON
      2. Connecting to JSON using Flexmonster Data Server
      3. Data types in JSON
    3. CSV
      1. Connecting to CSV
      2. Connecting to CSV using Flexmonster Data Server
      3. Data types in CSV
    4. Database
      1. Connecting to SQL databases
      2. Connecting to a MySQL database
      3. Connecting to a Microsoft SQL Server database
      4. Connecting to a PostgreSQL database
      5. Connecting to an Oracle database
      6. Connecting to other databases
    5. Flexmonster Data Server
      1. Getting started with Flexmonster Data Server
      2. Installation guide
      3. Configurations reference
      4. Data sources guide
      5. Security and authorization guide
      6. The Data Server as a DLL
        1. Getting started with the Data Server as a DLL
        2. Referring the Data Server as a DLL
        3. Implementing the API controller
        4. Implementing the server filter
        5. Implementing the custom parser
        6. DLL configurations reference
        7. The controller's methods for request handling
    6. MongoDB
      1. Introduction to Flexmonster MongoDB Connector
      2. Getting started with the MongoDB Connector
      3. Embedding the MongoDB Connector into the server
    7. Microsoft Analysis Services
      1. Connecting to Microsoft Analysis Services
      2. Getting started with Flexmonster Accelerator
      3. Referring the Accelerator as a DLL
      4. Configuring the authentication process
      5. Configuring a secure HTTPS connection
      6. Troubleshooting
    8. Custom data source API
      1. Introduction to the custom data source API
      2. A quick overview of a sample Node.js server
      3. A quick overview of a sample .NET Core server
      4. Implement your own server
        1. Implementing the custom data source API server
        2. Implementing filters
        3. Supporting more aggregation functions
        4. Returning data for the drill-through view
    9. Elasticsearch
      1. Connecting to Elasticsearch
      2. Configuring the mapping
    10. Pentaho Mondrian
      1. Connecting to Pentaho Mondrian
      2. Getting started with the Accelerator
      3. Configuring Mondrian roles
      4. Configuring username/password protection
      5. Configuring a secure HTTPS connection
      6. Troubleshooting
  5. Security
    1. Security in Flexmonster
    2. Security aspects of connecting to an OLAP cube
      1. Ways of connecting to an OLAP cube
      2. The data transfer process
      3. Data security
      4. Data access management
  6. Configuring report
    1. What is a report
    2. Data source
    3. Slice
    4. Options
    5. Mapping
    6. Number formatting
    7. Conditional formatting
    8. Set the report for the component
    9. Get the report from the component
    10. Date and time formatting
    11. Configuring global options
    12. Export and print
    13. Calculated values
    14. Custom sorting
  7. Charts
    1. Available tutorials
    2. Flexmonster Pivot Charts
    3. Integration with Highcharts
    4. Integration with amCharts
    5. Integration with Google Charts
    6. Integration with FusionCharts
    7. Integration with any charting library
  8. Customizing
    1. Customizing the Toolbar
    2. Customizing appearance
    3. Customizing the context menu
    4. Customizing the grid
    5. Customizing the pivot charts
    6. Localizing the component
  9. Updating to the latest version
    1. Updating to the latest version
    2. Release notes
    3. Migration guide from 2.7 to 2.8
    4. Migration guide from 2.6 to 2.7
    5. Migration guide from 2.5 to 2.6
    6. Migration guide from 2.4 to 2.5
    7. Migration guide from 2.3 to 2.4
    8. Migration guide from 2.2 to 2.3
    9. Documentation for older versions
  10. Flexmonster CLI Reference
    1. Overview
    2. Troubleshooting the CLI
    3. flexmonster create
    4. flexmonster add
    5. flexmonster update
    6. flexmonster version
    7. flexmonster help
Table of contents

Implementing the custom parser

One of the DLL’s main advantages is the possibility to visualize data from a custom data source. To use the custom data source with the DLL, implement a special parser.

This guide describes how to create and use a parser for the custom data source:

Example of a custom parser

To make the implementation of the custom parser easier, we designed a sample ASP.NET Core application using Flexmonster.DataServer.Core.dll. This application contains an example of a custom parser, which can be viewed in the CustomParser.cs file.

To create a new ASP.NET Core application with the Data Server or embed the DLL in the existing project, refer to the guide on Flexmonster.DataServer.Core.dll.

Initializing the custom parser

The CustomParser class implements the IParser interface.

First, the custom parser’s properties are specified:

public string Type { get; private set; }

public IndexOptions IndexOptions { get; set; }

public Dictionary<int, ColumnInfo> ColumnInfoByIndex { get; set; }

To learn more about these properties, see the IParser interface section.

Then, the parser’s type is set in the constructor (in this case, the type is "custom"):

public CustomParser()
Type = "custom";

Specifying the data

This parser uses built-in data defined in the data variable. The data has three fields; their names and types are added to the ColumnInfoByIndex collection in the FillDataInfo() method:

private void FillDataInfo()
ColumnInfoByIndex = new Dictionary<int, ColumnInfo>();
ColumnInfoByIndex.Add(0, new ColumnInfo("Country", data[0, 0].GetType()));
ColumnInfoByIndex.Add(1, new ColumnInfo("Price", data[0, 1].GetType()));
ColumnInfoByIndex.Add(2, new ColumnInfo("Date", data[0, 2].GetType()));

Parsing the data

The Parse() method is responsible for parsing data. In this case, Parse() calls the FillDataInfo() method first, then processes and returns the data:

public IEnumerable<object[,]> Parse()
for (int i = 0; i < data.GetLength(0); i++)
var partData = new object[1, 3];
for (int j = 0; j < data.GetLength(1); j++)
partData[0, j] = data[i, j];
//return data by line
yield return partData;

See the IParser interface section to learn more about the Parse() method.

Using the created parser

To be available to the DLL, the custom parser is added to the dependency injection container in the ConfigureServices() method of Startup.cs:

services.AddTransient<IParser, CustomParser>(); 

The AddTransient() method is used to provide a new parser instance each time it is requested from the service container.

The IParser interface

All the parsers should implement the IParser interface. IParser has the following definition:

public interface IParser
    string Type { get; }
    IndexOptions IndexOptions { get; set; }
    IEnumerable<object[,]> Parse();
    Dictionary<int, ColumnInfo> ColumnInfoByIndex { get; }

Below is a detailed description of each parser’s parameter:

  • Type – String. The parser’s name. It will be used in the appsettings.json file when creating the index, for example:
          "Type": "custom",
          "Indexes": {
            "custom-index": null
  • Parse – Function. Responsible for parsing the data. The main idea of the function is partial data loading, which allows working with large datasets. The Parse() method has the following signature:
    IEnumerable<object[,]> Parse(); 
    object can have either any primitive type or the DateTime type, so all dates in the dataset to parse should have the DateTime type.
  • IndexOptions – IndexOptions. Stores options defined when creating an index. Index options can be set either via the appsettings.json file or inside the dependency injection container in the ConfigureServices() method of the Startup.cs file:
    services.Configure<DatasourceOptions>(options =>
        // other configs
        options.Indexes.Add("custom-index", new CustomIndexOptions("custom"));
        // other configs
    For the custom parser, we recommend setting options in the ConfigureServices() method. This allows adding index-specific options that cannot be defined in the parser. To specify custom index options, create a class based on the IndexOptions class, for example:
    public class CustomIndexOptions: IndexOptions
    public string MyProp{ get; set; }
    public JsonIndexOptions(object myProp) : base("custom")
           MyProp= myProp;
    Then, use the class when setting options and in the parser:
    // in the custom parser
    var customIndexOptions = (CustomIndexOptions)IndexOptions;
    customIndexOptions.MyProp; // to access the custom option
  • ColumnInfoByIndex – Dictionary<int, ColumnInfo>. Allows setting the name and type for the column (note that each column must have the name and type). ColumnInfoByIndex is a collection of [key, value] pairs, where key is the column’s number (starting from 0) and value is an instance of the following class:
       public string Name { get; set; }
       public Type Type { get; set; }
    Note: the ColumnInfoByIndex collection should contain information about columns before the Parse() method returns the data.

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