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Resolve NPM Error When Installing TODO-MVC Tutorial in ReactJS

The key to avoiding an installation error is running commands from the relevant directory instead of the root directory. This guide walks you through step-by-step installation.

Oct 26, 2020 • 4 Minute Read

Introduction

The TODO-MVC tutorial is an official example application that you can use, edit, or modify to learn the basics of Flux. However, the documentation isn't always developer-friendly, so you can run into errors when installing the TODO-MVC tutorial on your own. The key to avoiding any kind of installation error is running all the commands from the relevant directory instead of the root directory. This guide walks you through step-by-step installation of the TODO-MVC tutorial in ReactJS.

Installing TODO-MVC Tutorial in ReactJS

This guide follows the same commands and steps as dictated by TODO-MVC's official documentation, which you can find on their official GitHub repository at https://github.com/facebook/flux/tree/master/examples/flux-todomvc.

Downloading and Installing Flux

The first step is to download Flux. Flux is an architectural pattern developed by Facebook itself for handling state management in React apps. It solves the same problems that Redux or Context API do by giving you a simple model for handling the data you need to pass and share between components. Since the TODO-MVC tutorial is an example based on Flux, this example project lies inside the Flux repository and you need to download and install Flux first. In an empty directory, clone the entire Flux repository locally using the following command:

      git clone https://github.com/facebook/flux.git
    

This will download a local version of Flux to your system. Next, install all the dependencies by running the following command inside the root directory of Flux:

      npm install
    

Installing TODO-MVC Tutorial

The next step is essential for installing the TODO-MVC tutorial, and this is where you might run into an error. You need to navigate inside the flux-todomvc directory, which is present inside the examples folder nested two levels in the root directory. All Flux tutorials are located inside this examples directory. Using the following command, navigate into the flux-todomvc directory:

      cd examples/flux-todomvc
    

Now that you're in the correct directory, you can run all the npm commands correctly without running into any errors. Run the following command to install all dependencies required to run the TODO-MVC example:

      npm install
    

You can open this example project by running the following command:

      npm start
    

Alternatively, you can also see the example by opening the index.html file inside the flux-todomvc directory in the browser. It initially displays a starter message, and you can follow the official documentation for exploring the example further.

Conclusion

For most example projects contained within a library, you need to properly run their installation commands relative to a specific directory other than the root directory. This helps to avoid unnecessary errors in installing example projects and tutorials that may detour you from learning more about that library. Sometimes even popular libraries have unclear documentation, but community support helps out. You can post an issue on an official GitHub Repository to get a quick response from core developers, moderators of the library, or the open-source community.

TODO-MVC tutorial is a relevant example that helps you understand the basics of Flux by building something useful. You can explore more such example tutorials inside the examples directory and follow their documentation to learn about each.

Gaurav Singhal

Gaurav S.

Guarav is a Data Scientist with a strong background in computer science and mathematics. He has extensive research experience in data structures, statistical data analysis, and mathematical modeling. With a solid background in Web development he works with Python, JAVA, Django, HTML, Struts, Hibernate, Vaadin, Web Scrapping, Angular, and React. His data science skills include Python, Matplotlib, Tensorflows, Pandas, Numpy, Keras, CNN, ANN, NLP, Recommenders, Predictive analysis. He has built systems that have used both basic machine learning algorithms and complex deep neural network. He has worked in many data science projects, some of them are product recommendation, user sentiments, twitter bots, information retrieval, predictive analysis, data mining, image segmentation, SVMs, RandomForest etc.

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