Skip to main content

access localhost with smartphone and get no response from the server

  1. website works via localhost on pc
  2. access with smartphone to localhost via ip too (I receive html, css and js for client)
  3. when I click the button, a "hi" is also added but function "search()" is not executed
  4. but when I enter the url http://localhost:3000/users I get the "hi1"

What do i have to do to make this work?

Client Side

const button = document.querySelector("button");

button.addEventListener("click", () => {
    document.getElementById("imageDiv").innerHTML = "Hi";//this work   
    search();//this not work
});

async function search(){
    await fetch("http://localhost:3000/users")
    .then(response => response.json())
    .then(response => {
        var image;   
        image = JSON.parse(JSON.stringify(Object.assign({},response)));
        document.getElementById("imageDiv").innerHTML = response;
    })};

Server Side

const express = require('express');
const bodyParser = require('body-parser');
const path = require("path"); // window or mac
const cors = require('cors');
const app = express();
const port = 3000;
//var word = "";
//const router = express.Router();


// configure CORS to avoid CORS errors
app.use(cors());

// configure body parser so we can read req.body
app.use(bodyParser.urlencoded({ extended: false }));
app.use(bodyParser.json());

app.use(express.static('./client'));

app.get('/', (req, res) => {
    res.sendFile("./index.html");
});


app.get("/users", (req, res) => {  
    datafiles = ["hi1"];
    res.json(datafiles);
    res.status(200);
});


app.listen(port, () => {
    console.log(`Server listening on http://localhost:${port}`);
});
Via Active questions tagged javascript - Stack Overflow https://ift.tt/1KpsiEP

Comments

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...

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

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...