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
--indexless forget about ddf--index.csv and validate
--datapointless forget about datapoint validation
--hidden allow hidden folders validation
--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
--exclude-dirs Process all directories 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 --rules print information regarding supported rules
validate-ddf ../ddf-example --indexless forget about ddf--index.csv and validate
validate-ddf ../ddf-example --datapointless forget about datapoint validation
validate-ddf ../ddf-example --hidden allow hidden folders validation
validate-ddf ../ddf-example --include-rules "INCORRECT_JSON_FIELD" Validate only by INCORRECT_JSON_FIELD rule
validate-ddf ../ddf-example --exclude-tags "WARNING" 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', 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
npm run changelog
- generates content for CHANGELOG.md
file with changes that have happened since last releasenpm 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:
- CHANGELOG.md - because of added history.
- 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