Skip to main content

Next.js multi zones with i18n and shared components

I am using Next.js' multi zone feature with a blog and web app so I can develop and deploy both apps independently. It was easy to set up by following their with zones example and I have set up a blog app at port 4200 and a web app at port 3000, which is working fine. Unfortunately I am encountering some problems that aren't described anywhere in their documentation (as far as I can tell).

First of all, I am also using their internationalised routing which is working fine, however when going to my blog app it appends the locale to the end of the URL. Imagine I am on localhost:3000/en and navigate to the blog app, then it will show localhost:4200/blog/en instead of localhost:4200/en/blog. Is there any way around this (e.g. by using rewrites)?

Secondly, I am working in a monorepo and have shared components between both apps, such as the header and footer, which obviously includes navigation. When I am on the blog and want to navigate to e.g. the /about page, then it will obviously navigate to localhost:4200/blog/about instead of localhost:3000/about. One solution is to check the base path in the navigation component and then prepend localhost:3000 to the href if the base path equals blog, but that refreshes the entire app and does not result in smooth navigation, so it's not really viable imo. What else can I do about this?

Seemingly the multi zone feature is really only suitable for very small apps or I'm missing something. It seems others also have the same problem, if I am missing something, then the documentation could definitely be at the least.

Via Active questions tagged javascript - Stack Overflow https://ift.tt/2FdjaAW

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