Skip to main content

How to access directory or file outside of root directory in React Native

I am working on project that involves creating a mobile app and website, so I decide to create same or shared screen (pages) for both my app and website.

So I decided to go with this file structure.

Monorepo App(React-Native) Web(Next.js) Screen (all screens will be here)

now, I'm stuck at one problem: I can't access file outside of my root directory, that is my App directory how can I access files outside of root directory?

I also change my metro.config.js file and babel.config.js file now they look like this:

metro.config.js

const {getDefaultConfig, mergeConfig} = require('@react-native/metro-config');
const path = require("path");

/**
Metro configuration
 * https://facebook.github.io/metro/docs/configuration
 *
 * @type {import('metro-config').MetroConfig}
 */
const extraNodeModules = {
    shared: path.resolve(__dirname + "/../screen"),
  };
  const watchFolders = [path.resolve(__dirname + "/../screen")];

const nodeModulesPaths = [path.resolve(path.join(__dirname, "./node_modules"))];
const config = {
    resolver:{
    extraNodeModules,
    nodeModulesPaths,
    },
    watchFolders
};

module.exports = mergeConfig(getDefaultConfig(__dirname), config);

babel.config.js

module.exports = {
  presets: ['module:metro-react-native-babel-preset'],
  plugins: [
    "react-native-reanimated/plugin",
    [
      "module-resolver",
      {
        root: ["."],
        alias: {
          "@screen": "../screen",
        },
      },
    ],
  ],
}

and I am getting this error:

Warning: Invalid hook call. Hooks can only be called inside of the body of a function component.

I try changing the metro.config.js file to access files outside of my file, but I always get different types of errors.

I am expecting that I can access my shared file in my React Native App folder.

Via Active questions tagged javascript - Stack Overflow https://ift.tt/KtZYgRC

Labels

Labels:

Comments

Post a Comment

Popular posts from this blog

ValueError: X has 10 features, but LinearRegression is expecting 1 features as input

So, I am trying to predict the model but its throwing error like it has 10 features but it expacts only 1. So I am confused can anyone help me with it? more importantly its not working for me when my friend runs it. It works perfectly fine dose anyone know the reason about it? cv = KFold(n_splits = 10) all_loss = [] for i in range(9): # 1st for loop over polynomial orders poly_order = i X_train = make_polynomial(x, poly_order) loss_at_order = [] # initiate a set to collect loss for CV for train_index, test_index in cv.split(X_train): print('TRAIN:', train_index, 'TEST:', test_index) X_train_cv, X_test_cv = X_train[train_index], X_test[test_index] t_train_cv, t_test_cv = t[train_index], t[test_index] reg.fit(X_train_cv, t_train_cv) loss_at_order.append(np.mean((t_test_cv - reg.predict(X_test_cv))**2)) # collect loss at fold all_loss.append(np.mean(loss_at_order)) # collect loss at order plt.plot(np.log(al...
Post a Comment
Read more

Sorting large arrays of big numeric stings

I was solving bigSorting() problem from hackerrank: Consider an array of numeric strings where each string is a positive number with anywhere from to digits. Sort the array's elements in non-decreasing, or ascending order of their integer values and return the sorted array. I know it works as follows: def bigSorting(unsorted): return sorted(unsorted, key=int) But I didnt guess this approach earlier. Initially I tried below: def bigSorting(unsorted): int_unsorted = [int(i) for i in unsorted] int_sorted = sorted(int_unsorted) return [str(i) for i in int_sorted] However, for some of the test cases, it was showing time limit exceeded. Why is it so? PS: I dont know exactly what those test cases were as hacker rank does not reveal all test cases. source https://stackoverflow.com/questions/73007397/sorting-large-arrays-of-big-numeric-stings
Post a Comment
Read more

How to load Javascript with imported modules?

I am trying to import modules from tensorflowjs, and below is my code. test.html <!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <title>Document</title </head> <body> <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@2.0.0/dist/tf.min.js"></script> <script type="module" src="./test.js"></script> </body> </html> test.js import * as tf from "./node_modules/@tensorflow/tfjs"; import {loadGraphModel} from "./node_modules/@tensorflow/tfjs-converter"; const MODEL_URL = './model.json'; const model = await loadGraphModel(MODEL_URL); const cat = document.getElementById('cat'); model.execute(tf.browser.fromPixels(cat)); Besides, I run the server using python -m http.server in my command prompt(Windows 10), and this is the error prompt in the console log of my browser: Failed to loa...
Post a Comment
Read more