README.md

Overview

Example solution that demonstrates the use of the EDK npm package to create various file type data sources.

Usage

Run npm install to install the package dependencies.

The solution can be built using the following command edk build.

Implementation

The project will involve creating some file based datasources, detecting their outputs, then visualising the outputs.

Adding datasources

Each data source was added with the following EDK commands:

• csv: edk add datasource csv --name Csv --uri file://files/test.csv --def_dir src/datasource
• json: edk add datasource json --name Json --uri file://files/test.json --def_dir src/datasource
• xlsx: edk add datasource xlsx --name Xlsx --uri file://files/test.xlsx --def_dir src/datasource
• csv two: edk add datasource csv --name "Csv Two" --uri file://files/test_two.csv --def_dir src/datasource
• xlsx two: edk add datasource xlsx --name "Xlsx Two" --uri file://files/test_two.xlsx --def_dir src/datasource

This will create an empty datasource for each file, for example for the json datasource:

import * as ELARA from "@elaraai/edk/lib"

export default ELARA.JsonSourceSchema({
    name: "Json",
    uri: 'file://files/test.json,
})

Note that the second version of each file (and datasource) are intentionally more complicated, containing duplicate rows (i.e. no unique key) and a much larger number of rows. Also, for test.csv dataset we know that rather than empty cells for variables, the file contains a "?" string.

Detecting datasources

The output expressions were detected for each data with the following commands.

• csv: edk-io detect csv --asset csv.source --defaults --empty ?
• json: edk-io detect json --asset json.source --defaults
• xlsx: edk-io detect xlsx --asset xlsx.source --defaults
• csv two: edk-io detect csv --asset csv_two.source --defaults --empty ?
• xlsx two: edk-io detect xlsx --asset xlsx_two.source --defaults

This will generate the types and expressions for the datasources, for example for json.source:

import * as ELARA from "@elaraai/edk/lib"

const json_struct_type = ELARA.StructType({
    string: 'string',
    date: 'datetime',
    'float': 'float',
    integer: 'integer',
    'boolean': 'boolean',
    struct: ELARA.StructType({
        string: 'string',
        date: 'datetime',
        'float': 'float',
        integer: 'integer',
        'boolean': 'boolean',
    }),
    array: 'set',
});

export default ELARA.JsonSourceSchema({
    name: "Json",
    uri: 'file://files/test.jsonl',
    primary_key: ELARA.Variable("string", 'string'),
    selections: {
        string: ELARA.Parse(ELARA.Variable("string", 'string')),
        date: ELARA.Parse(ELARA.Variable("date", 'datetime')),
        'float': ELARA.Parse(ELARA.Variable("float", 'float')),
        integer: ELARA.Parse(ELARA.Variable("integer", 'integer')),
        'boolean': ELARA.Parse(ELARA.Variable("boolean", 'boolean')),
        array: ELARA.Parse(ELARA.Variable("array", 'set')),
        struct: ELARA.Parse(ELARA.Variable("struct", json_struct_type)),
    },
})

Or alternatively for the second set of datasources, the detection will sample from the full set of rwos for efficiency, and also inject an index variable given the lack of a unique field. For example with the csv_two.source below.

// East type declarations 
import * as ELARA from "@elaraai/edk/lib"

export default ELARA.CsvSourceSchema({
    name: "Csv Two",
    uri: 'file://files/test_two.csv',
    primary_key: ELARA.Print(ELARA.Variable("index", 'integer')),
    index_variable: ELARA.Variable("index", 'integer'),
    selections: {
        string: ELARA.Parse(ELARA.IfElse(
            ELARA.Equal(ELARA.Variable("string", 'string'), ELARA.Const("?")),
            ELARA.Null('string'),
            ELARA.Variable("string", 'string')
        )),
        date: ELARA.Parse(ELARA.Variable("date", 'datetime')),
        number: ELARA.Parse(ELARA.Variable("number", 'float')),
        integer: ELARA.Parse(ELARA.Variable("integer", 'integer')),
        'boolean': ELARA.Parse(ELARA.Variable("boolean", 'boolean')),
        'Another String': ELARA.Parse(ELARA.IfElse(
            ELARA.Equal(ELARA.Variable("Another String", 'string'), ELARA.Const("?")),
            ELARA.Null('string'),
            ELARA.Variable("Another String", 'string')
        )),
    },
})

Add application

The application was added for the project with the following command: edk add plugin --name Application --def_dir src/plugin. The application contents was added to display the datasource outputs with the DataSourcePlugin for a default SuperUser:

import * as ELARA from "@elaraai/edk/lib"
import { ApplicationPlugin, Const, DataSourcePlugin, SuperUser } from "@elaraai/edk/lib"

import csv from "../../gen/csv.source"
import csv_two from "../../gen/csv_two.source"
import json from "../../gen/json.source"
import xlsx from "../../gen/xlsx.source"
import xlsx_two from "../../gen/xlsx_two.source"

export default ELARA.Schema(
    ApplicationPlugin({
        name: "File Datasources",
        schemas: {
            "Datasources": DataSourcePlugin({
                datasources: [csv, json, xlsx, csv_two, xlsx_two]
            })
        },
        users: [
            SuperUser({
                email: '[email protected]',
                name: 'Admin',
                password: Const('admin'),
            })
        ]
    })
)

Reference

General reference documentation for EDK usage is available in the following links:

• EDK CLI: detailed CLI usage reference and examples
• EDK API: programmatic api for the cli functionality