What is the difference between yarn run and npm start?

Before discussing the differences between 'yarn run' and 'npm start', it's important to understand that 'yarn' and 'npm' are two distinct package managers used to help developers manage dependencies in projects. Although their core functionalities are similar, there are notable differences in how they execute commands and handle packages.

1. Differences in Commands

• npm start is a shorthand command for npm run start. This command executes the script named start under the scripts object in the package.json file. Developers can specify the exact command to run here, such as starting a server or launching a development environment.
• yarn run requires explicitly naming the script, such as yarn run start. Similar to npm start, yarn run start executes the start script under the scripts object in package.json.

2. Differences in Execution Process

• Performance: Yarn is generally considered faster when handling dependencies and parallel installations due to its modern caching mechanisms and parallel processing techniques. This means that in large projects, yarn run may execute faster than npm start.
• Lock Files: Yarn uses yarn.lock to lock dependency versions, while npm uses package-lock.json or npm-shrinkwrap.json. This ensures that in collaborative development, Yarn provides more precise assurance that all team members have identical dependency versions.

3. Practical Examples

Assume we have a Node.js project with the following script defined in its package.json file:

json
"scripts": {
  "start": "node app.js"
}

In this example, running either npm start or yarn run start will execute the node app.js command to start the application.

Conclusion

Overall, yarn run and npm start are functionally equivalent, both used to execute the start script defined in package.json. The primary distinctions lie in the performance characteristics and dependency management approaches of the underlying package managers. The choice depends on team preferences and project-specific requirements. For large-scale projects or performance-critical scenarios, Yarn is often preferred.