ddf-validation

ddf-validation

npm version

Install

npm i ddf-validation -g

Test

npm test or npm run n-test without eslint

Console utility usage

validate-ddf <root> [options]

Commands:
  root  DDF Root directory

Options:
  -i               Generate index file
  -j               Fix wrong JSONs
  --rules          print information regarding supported rules
  --include-tags   Process only issues by selected tags
  --exclude-tags   Process all tags except selected
  --include-rules  Process only issues by selected rules
  --exclude-rules  Process all rules except selected

Examples:
  validate-ddf ../ddf-example                                        validate DDF datasets for the root
  validate-ddf ../ddf-example -i                                     generate ddf--index file
  validate-ddf ../ddf-example -j                                     fix JSONs for this DDF dataset
  validate-ddf ../ddf-example --rules                                print information regarding supported rules
  validate-ddf ../ddf-example --include-rules "INCORRECT_JSON_FIELD" Validate only by  INCORRECT_JSON_FIELD rule
  validate-ddf ../ddf-example --exclude-tags "WARNING_TAG"           Get all kinds of issues except warnings

API usage

First of all you should install this package: npm i ddf-validation

ddf-validation can be used via an API in three different ways:

• JSON based validator (JSONValidator)
• Stream based validator (StreamValidator)
• Validator that checks whether dataset has errors and if there are some - returns true, otherwise - false

Some examples of API using:

JSONValidator

Simple example

const api = require('ddf-validation');
const JSONValidator = api.JSONValidator;
const jsonValidator = new JSONValidator('path to ddf dataset');

jsonValidator.on('finish', (err, jsonIssuesContent) => {
  console.log(err, jsonIssuesContent);
});

api.validate(jsonValidator);

This validator's type returns all issues as JSON object. And for this reason it's not suitable for huge DDF datasets.

StreamValidator

const api = require('ddf-validation');
const StreamValidator = api.StreamValidator;
const streamValidator = new StreamValidator('path to ddf dataset');

streamValidator.on('issue', () => {
  // catch new issue here
});

streamValidator.on('finish', err => {
  // validation is finished
});

api.validate(streamValidator);

StreamValidator returns each issue separately one by one. It is good choice for huge DDF datasets. StreamValidator is the default validator.

SimpleValidator

According to the state of the dataset (valid or not) this validator returns only true or false with appropriate meaning. This is the fastest validator among given here.

const api = require('ddf-validation');
const SimpleValidator = api.SimpleValidator;
const simpleValidator = new SimpleValidator('./test/fixtures/good-folder-indexed');

simpleValidator.on('finish', (err, isDataSetCorrect) => {
  // isDataSetCorrect === true if DDF dataset is correct
  // isDataSetCorrect === true if DDF dataset is incorrect
});

api.validate(simpleValidator);

Custom rules

Also all validators supports validation parameters that corresponds with command line:

• includeTags Process only issues by selected tags
• excludeTags Process all tags except selected
• includeRules Process only issues by selected rules
• excludeRules Process all rules except selected

Here is an example:

const api = require('ddf-validation');
const expectedRule = 'INCORRECT_FILE';
const StreamValidator = api.StreamValidator;
const streamValidator = new StreamValidator(path, {includeRules: expectedRule});

streamValidator.on('issue', issue => {
  // only one type of issue (INCORRECT_FILE) should be catched
});

streamValidator.on('finish', err => {
  console.log('finished');
});

api.validate(streamValidator);

index file creation

validate-ddf <folder with DDF data set> -i

Attention: existing ddf--index.csv file will be overwritten!

Developer guide

you can see it here

Release

1. npm run changelog - generates content for CHANGELOG.md file with changes that have happened since last release
2. npm version - this one is a bit more complicated. Let's start with what it needs in order to run.

• CONVENTIONAL_GITHUB_RELEASER_TOKEN environment variable should be set up for this command:

  Example: CONVENTIONAL_GITHUB_RELEASER_TOKEN=aaaaaaaaaabbbbbbbbbbccccccccccffffffffff npm version minor

• this command understands following parameters:

  • major (having initially version 0.0.0 by applying this option it will be changed to 1.0.0).

    Example:

      CONVENTIONAL_GITHUB_RELEASER_TOKEN=aaaaaaaaaabbbbbbbbbbccccccccccffffffffff npm version major
    

  • minor (having initially version 0.0.0 by applying this option it will be changed to 0.1.0)

    Example:

      CONVENTIONAL_GITHUB_RELEASER_TOKEN=aaaaaaaaaabbbbbbbbbbccccccccccffffffffff npm version minor
    

  • patch (having initially version 0.0.0 by applying this option it will be changed to 0.0.1)

    Example:

      CONVENTIONAL_GITHUB_RELEASER_TOKEN=aaaaaaaaaabbbbbbbbbbccccccccccffffffffff npm version patch
    

  During the release process two files will be changed and pushed to github:

  1. CHANGELOG.md - because of added history.
  2. package.json - because of bumped version.

  Note: aaaaaaaaaabbbbbbbbbbccccccccccffffffffff - is the fake token. In order to generate proper one you need to do following: github tutorial

  Important note: you should merge development branch into master and performing npm verison on master branch according to our gitflow

  Even more important note: while generating token (using tutorial given above) you need to choose which permissions should be granted to it. For our release purposes you need to choose all permissions under the section repo