This library helps to model MySQL as document DB. We have simplified MySQL to have only
two columns. More columns will be added only while creating an index for JSON fields using
createIndexForJsonField
method.
- column1: documentId, a random alphanumeric of type
VARCHAR(32).
- column2: Document column to store documents in MySQL. Documents are stored as
JSON
documents.
documentId
is created when we put a document into the database by calling put
method
import {createTable, init, close} from "@aicore/libmysql";
import {getMySqlConfigs} from "@aicore/libcommonutils";
const configs = getMySqlConfigs();
init(configs);
const tableName = 'customers';
try {
await createTable(tableName);
} catch (e) {
console.error(JSON.stringify(e));
}
close();
documentID | document |
---|
import {put, init, close} from "@aicore/libmysql";
import {getMySqlConfigs} from "@aicore/libcommonutils";
const configs = getMySqlConfigs();
init(configs);
const tableName = 'customers';
const document = {
'lastName': 'Alice',
'Age': 100,
'active': true,
'location': {
'city': 'Banglore',
'state': 'Karnataka',
'layout': {
'block': '1stblock'
}
}
};
try {
const docId = await put(tableName, document);
} catch (e) {
console.error(JSON.stringify(e));
}
close();
documentID | document |
---|---|
d20ab50a3e4deefe508f1b26a32e2632 | {'lastName': 'Alice','Age': 100, 'active': true, 'location': {'city': 'Banglore','state': 'Karnataka','layout': {'block': '1stblock'} }} |
import {deleteKey, init, close} from "@aicore/libmysql";
import {getMySqlConfigs} from "@aicore/libcommonutils";
const configs = getMySqlConfigs();
init(configs);
const tableName = 'customers';
const docId = '1234';
try {
await deleteKey(tableName, docId);
} catch (e) {
console.error(JSON.stringify(e));
}
close();
import {get, init, close} from "@aicore/libmysql";
import {getMySqlConfigs} from "@aicore/libcommonutils";
const configs = getMySqlConfigs();
const tableName = 'customers';
const docId = '1234';
try {
const document = await get(tableName, docId);
console.log(JSON.stringify(document));
} catch (e) {
console.error(JSON.stringify(e));
}
close();
import {getFromNonIndex, init, close} from "@aicore/libmysql";
import {getMySqlConfigs} from "@aicore/libcommonutils";
const configs = getMySqlConfigs();
const tableName = 'customers';
const queryObject = {
'lastName': 'Alice',
'Age': 100
};
try {
const documents = await getFromNonIndex(tableName, queryObject);
console.log(JSON.stringify(documents));
} catch (e) {
console.error(JSON.stringify(e));
}
close();
Note that only a maximum of 1000 entries will be returned. Use page options to get paginated results.
To get paginated results past 1000 results, Eg. getFromNonIndex(tableName, queryObject, {pageOffset: 56,pageLimit: 1000});
- pageOffset [number]: specify which row to start retrieving documents from. Eg: to get 10 documents from the 100'th document, you should specify pageOffset = 100 and pageLimit = 10
- pageLimit [number]: specify number of documents to retrieve. Eg: to get 10 documents from the 100'th document, you should specify pageOffset = 100 and pageLimit = 10
import {deleteTable, init, close} from "@aicore/libmysql";
import {getMySqlConfigs} from "@aicore/libcommonutils";
const configs = getMySqlConfigs();
const tableName = 'customers';
try {
await deleteTable(tableName);
} catch (e) {
console.error(JSON.stringify(e));
}
close();
import {createIndexForJsonField, DATA_TYPES, init, close} from "@aicore/libmysql";
import {getMySqlConfigs} from "@aicore/libcommonutils";
const configs = getMySqlConfigs();
const tableName = 'customers';
try {
// To make index unique constraint for new column and index set isUnique to true;
const isUnique = false;
await createIndexForJsonField(tableName, 'lastName', DATA_TYPES.VARCHAR(50), isUnique);
await createIndexForJsonField(tableName, 'Age', DATA_TYPES.INT, isUnique);
} catch (e) {
console.error(JSON.stringify(e));
}
close();
documentID | document | ef21925fada6dfb684b5d8ec72114bb1 | 9d8d2d5ab12b515182a505f54db7f538 |
---|---|---|---|
9d8d2d5ab12b515182a505f54db7f538 | {"Age": 100, "active": true, "lastName": "Alice", "location": {"city": "Banglore", "state": "Karnataka", "layout": {"block": "1stblock"}}} |
Alice | 100 |
import {getFromIndex, init, close} from "@aicore/libmysql";
import {getMySqlConfigs} from "@aicore/libcommonutils";
const configs = getMySqlConfigs();
const tableName = 'customers';
const queryObject = {
'lastName': 'Alice',
'Age': 100
};
try {
const documents = await getFromIndex(tableName, queryObject);
console.log(JSON.stringify(documents));
} catch (e) {
console.error(JSON.stringify(e));
}
close();
Note that only a maximum of 1000 entries will be returned. Use page options to get paginated results.
To get paginated results past 1000 results, Eg. getFromIndex(tableName, queryObject, {pageOffset: 56,pageLimit: 1000});
- pageOffset [number]: specify which row to start retrieving documents from. Eg: to get 10 documents from the 100'th document, you should specify pageOffset = 100 and pageLimit = 10
- pageLimit [number]: specify number of documents to retrieve. Eg: to get 10 documents from the 100'th document, you should specify pageOffset = 100 and pageLimit = 10
import {update, init, close} from "@aicore/libmysql";
import {getMySqlConfigs} from "@aicore/libcommonutils";
const configs = getMySqlConfigs();
init(configs);
const tableName = 'customers';
const docId = 1234;
const document = {
'FirstName': 'Alice',
'lastName': 'Bob',
'Age': 20,
'active': true
};
try {
const docId = await update(tableName, docId, document);
// or if you want to do conditional updates, ie update the document
// only if the condition specified is satisfied.
const docId1 = await update(tableName, docId, document, "$.Age=20");
} catch (e) {
console.error(JSON.stringify(e));
}
close();
Since this is a pure JS template project, build command just runs test with coverage.
> npm install // do this only once.
> npm run build
To lint the files in the project, run the following command:
> npm run lint
To Automatically fix lint errors:
> npm run lint:fix
To run all tests:
> npm run test
Additionally, to run unit/integration tests only, use the commands:
> npm run test:unit
> npm run test:integ
To run all tests with coverage:
> npm run cover
After running coverage, detailed reports can be found in the coverage folder listed in the output of coverage command. Open the file in browser to view detailed reports.
To run unit/integration tests only with coverage
> npm run cover:unit
> npm run cover:integ
Unit and integration test coverage settings can be updated by configs .nycrc.unit.json
and .nycrc.integration.json
.
See https://github.com/istanbuljs/nyc for config options.
Please run npm run release
on the main
branch and push the changes to main. The release command will bump the npm
version.
!NB: NPM publish will faill if there is another release with the same version.
To publish a package to npm, push contents to npm
branch in
this repository.
If you are looking to publish to package owned by core.ai, you will need access to the GitHub Organization
secret NPM_TOKEN
.
For repos managed by aicore org in GitHub, Please contact your Admin to get access to core.ai's NPM tokens.
Alternatively, if you want to publish the package to your own npm account, please follow these docs:
- Create an automation access token by following this link .
- Add NPM_TOKEN to your repository secret by following this link
To edit the publishing workflow, please see file: .github/workflows/npm-publish.yml
We use Rennovate for dependency updates: https://blog.logrocket.com/renovate-dependency-updates-on-steroids/
- By default, dep updates happen on sunday every week.
- The status of dependency updates can be viewed here if you have this repo permissions in github: https://app.renovatebot.com/dashboard#github/aicore/template-nodejs
- To edit rennovate options, edit the rennovate.json file in root, see https://docs.renovatebot.com/configuration-options/ Refer
Several automated workflows that check code integrity are integrated into this template. These include:
- GitHub actions that runs build/test/coverage flows when a contributor raises a pull request
- Sonar cloud integration using
.sonarcloud.properties
SonarLint is currently available as a free plugin for jetbrains, eclipse, vscode and visual studio IDEs. Use sonarLint plugin for webstorm or any of the available IDEs from this link before raising a pull request: https://www.sonarlint.org/ .
SonarLint static code analysis checker is not yet available as a Brackets extension.
# install docker
sudo docker pull mysql
sudo docker images
sudo docker run -d --name mysql-server -p 3306:3306 -e "MYSQL_ROOT_PASSWORD=1234" mysql
# install mysql client
sudo apt-get install mysql-client
# connect to mysql running in docker
# type password as 1234
mysql -h 127.0.0.1 -u root -p
# create a database
CREATE DATABASE testdb;
# now Goto file `setupIntegTest.js` and uncomment the config part. Tests can now be run
# list running dockers
sudo docker container ls
# stop docker
sudo docker container stop <container id obtained from previous step>
# get list of all avalible containers
sudo docker container ls -a
# Remove container first
sudo docker container rm <container id from previous step>
# Remover docker image
sudo docker image rm mysql
# get mysql container id
sudo docker container ls -a
# start Mysql
sudo docker start <contianer Id>
# Connect to MySql
mysql -h 127.0.0.1 -u root -p
See https://mochajs.org/#getting-started on how to write tests Use chai for BDD style assertions (expect, should etc..). See move here: https://www.chaijs.com/guide/styles/#expect
if you want to mock/spy on fn() for unit tests, use sinon. refer docs: https://sinonjs.org/
we use c8 for coverage https://github.com/bcoe/c8. Its reporting is based on nyc, so detailed docs can be found here: https://github.com/istanbuljs/nyc ; We didn't use nyc as it do not yet have ES module support see: digitalbazaar/bedrock-test#16 . c8 is drop replacement for nyc coverage reporting tool