flask send data

react_app.py

 from dataclasses import dataclass
-from flask import Flask, request, current_app, send_file, send_from_directory
+from flask import Flask, request, current_app, send_file, send_from_directory, redirect, url_for, session
 from flask_cors import CORS, cross_origin
 
 import os
@@ -24,87 +24,86 @@ CORS(app)
 @app.route('/home', methods=["GET", "POST"])
 # @cross_origin()
 def get_form_data():
-    print('@@@ in Flask Home')
-    # form_data = request.get_json() 
-    # form_data = request.files['ds_upload'] 
-    # print('@@@ form_data', form_data) 
- 
-    form_data = request.form
-    print('@@@ this is form data', form_data)
-
-    # required input
-    ds = form_data['select_dataset'] # pick dataset (MNIST, KMNIST, FashionMNIST, CIFAR10, CIFAR100)
-    IsLeNet = form_data["select_network"]   # using LeNet or EasyNet or SimpleNet ->> default 
-    auto_aug_learner = form_data["select_learner"] # augmentation methods to be excluded
-
-    print('@@@ required user input:', 'ds', ds, 'IsLeNet:', IsLeNet, 'auto_aug_leanrer:',auto_aug_learner)
-    # advanced input
-    if form_data['batch_size'] != 'undefined': 
-        batch_size = form_data['batch_size']       # size of batch the inner NN is trained with
-    else: 
-        batch_size = 1 # this is for demonstration purposes
-    if form_data['learning_rate'] != 'undefined': 
-        learning_rate =  form_data['learning_rate']  # fix learning rate
-    else: 
-        learning_rate = 10-1
-    if form_data['toy_size'] != 'undefined': 
-        toy_size = form_data['toy_size']      # total propeortion of training and test set we use
-    else: 
-        toy_size = 1 # this is for demonstration purposes
-    if form_data['iterations'] != 'undefined': 
-        iterations = form_data['iterations']      # total iterations, should be more than the number of policies
-    else: 
-        iterations = 10
-    exclude_method = form_data['select_action']
-    print('@@@ advanced search: batch_size:', batch_size, 'learning_rate:', learning_rate, 'toy_size:', toy_size, 'iterations:', iterations, 'exclude_method', exclude_method)
     
-
-    # default values 
-    max_epochs = 10      # max number of epochs that is run if early stopping is not hit
-    early_stop_num = 10   # max number of worse validation scores before early stopping is triggered
-    num_policies = 5      # fix number of policies
-    num_sub_policies = 5  # fix number of sub-policies in a policy
-    
-    
-    # if user upload datasets and networks, save them in the database
-    if ds == 'Other':
-        ds_folder = request.files['ds_upload'] 
-        print('!!!ds_folder', ds_folder)
-        ds_name_zip = ds_folder.filename
-        ds_name = ds_name_zip.split('.')[0]
-        ds_folder.save('./datasets/'+ ds_name_zip)
-        with zipfile.ZipFile('./datasets/'+ ds_name_zip, 'r') as zip_ref:
-            zip_ref.extractall('./datasets/upload_dataset/')
-        if not current_app.debug:
-            os.remove(f'./datasets/{ds_name_zip}')
-    else: 
-        ds_name_zip = None
-        ds_name = None
-
-    # test if uploaded dataset meets the criteria 
-    for (dirpath, dirnames, filenames) in os.walk(f'./datasets/upload_dataset/{ds_name}/'):
-        for dirname in dirnames:
-            if dirname[0:6] != 'class_':
-                return None # neet to change render to a 'failed dataset webpage'
-
-    # save the user uploaded network
-    if IsLeNet == 'Other':
-        childnetwork = request.files['network_upload']
-        childnetwork.save('./child_networks/'+childnetwork.filename)
-        network_name = childnetwork.filename
-    else: 
-        network_name = None
-
-    
-    print("@@@ user input has all stored in the app")
-
-    data = {'ds': ds, 'ds_name': ds_name_zip, 'IsLeNet': IsLeNet, 'network_name': network_name,
-            'auto_aug_learner':auto_aug_learner, 'batch_size': batch_size, 'learning_rate': learning_rate, 
-            'toy_size':toy_size, 'iterations':iterations, 'exclude_method': exclude_method, }
-
-    current_app.config['data'] = data
-    
-    print('@@@ all data sent', current_app.config['data'])
+    if request.method == 'POST':
+        print('@@@ in Flask Home')
+        
+        form_data = request.form
+        print('@@@ this is form data', form_data)
+
+        # required input
+        ds = form_data['select_dataset'] # pick dataset (MNIST, KMNIST, FashionMNIST, CIFAR10, CIFAR100)
+        IsLeNet = form_data["select_network"]   # using LeNet or EasyNet or SimpleNet ->> default 
+        auto_aug_learner = form_data["select_learner"] # augmentation methods to be excluded
+
+        print('@@@ required user input:', 'ds', ds, 'IsLeNet:', IsLeNet, 'auto_aug_leanrer:',auto_aug_learner)
+        # advanced input
+        if form_data['batch_size'] != 'undefined': 
+            batch_size = form_data['batch_size']       # size of batch the inner NN is trained with
+        else: 
+            batch_size = 1 # this is for demonstration purposes
+        if form_data['learning_rate'] != 'undefined': 
+            learning_rate =  form_data['learning_rate']  # fix learning rate
+        else: 
+            learning_rate = 10-1
+        if form_data['toy_size'] != 'undefined': 
+            toy_size = form_data['toy_size']      # total propeortion of training and test set we use
+        else: 
+            toy_size = 1 # this is for demonstration purposes
+        if form_data['iterations'] != 'undefined': 
+            iterations = form_data['iterations']      # total iterations, should be more than the number of policies
+        else: 
+            iterations = 10
+        exclude_method = form_data['select_action']
+        print('@@@ advanced search: batch_size:', batch_size, 'learning_rate:', learning_rate, 'toy_size:', toy_size, 'iterations:', iterations, 'exclude_method', exclude_method)
+        
+
+        # default values 
+        max_epochs = 10      # max number of epochs that is run if early stopping is not hit
+        early_stop_num = 10   # max number of worse validation scores before early stopping is triggered
+        num_policies = 5      # fix number of policies
+        num_sub_policies = 5  # fix number of sub-policies in a policy
+        
+        
+        # if user upload datasets and networks, save them in the database
+        if ds == 'Other':
+            ds_folder = request.files['ds_upload'] 
+            print('!!!ds_folder', ds_folder)
+            ds_name_zip = ds_folder.filename
+            ds_name = ds_name_zip.split('.')[0]
+            ds_folder.save('./datasets/'+ ds_name_zip)
+            with zipfile.ZipFile('./datasets/'+ ds_name_zip, 'r') as zip_ref:
+                zip_ref.extractall('./datasets/upload_dataset/')
+            if not current_app.debug:
+                os.remove(f'./datasets/{ds_name_zip}')
+        else: 
+            ds_name_zip = None
+            ds_name = None
+
+        # test if uploaded dataset meets the criteria 
+        for (dirpath, dirnames, filenames) in os.walk(f'./datasets/upload_dataset/{ds_name}/'):
+            for dirname in dirnames:
+                if dirname[0:6] != 'class_':
+                    return None # neet to change render to a 'failed dataset webpage'
+
+        # save the user uploaded network
+        if IsLeNet == 'Other':
+            childnetwork = request.files['network_upload']
+            childnetwork.save('./child_networks/'+childnetwork.filename)
+            network_name = childnetwork.filename
+        else: 
+            network_name = None
+
+        
+        print("@@@ user input has all stored in the app")
+
+        data = {'ds': ds, 'ds_name': ds_name_zip, 'IsLeNet': IsLeNet, 'network_name': network_name,
+                'auto_aug_learner':auto_aug_learner, 'batch_size': batch_size, 'learning_rate': learning_rate, 
+                'toy_size':toy_size, 'iterations':iterations, 'exclude_method': exclude_method, }
+
+        current_app.config['data'] = data
+        
+        print('@@@ all data sent', current_app.config['data'])
 
     # try this if you want it might work, it might not
     # wapp_util.parse_users_learner_spec(
@@ -114,8 +113,11 @@ def get_form_data():
     #                         max_epochs,
     #                         **data,
     #                         )
-
-    return {'data': 'all stored'}
+    else: 
+        print('it is GET method')
+    data = current_app.config['data']
+    return data
+    # return redirect(url_for('confirm', data=data))
 
 
 
@@ -123,9 +125,12 @@ def get_form_data():
 # ========================================================================
 @app.route('/confirm', methods=['POST', 'GET'])
 @cross_origin()
-def confirm():
+def confirm():  
     print('inside confirm page')
     data = current_app.config['data']
+    print("current_app.config['data']", current_app.config['data'])
+    # print("session.get('data')", session.get('data'))
+    # data = request.args.get('data')
     return data
 
 
@@ -145,11 +150,11 @@ def training():
 
     # fake training
     print('pretend it is training')
-    time.sleep(3)
+    time.sleep(1)
     print('epoch: 1')
-    time.sleep(3)
+    time.sleep(1)
     print('epoch: 2')
-    time.sleep(3) 
+    time.sleep(1) 
     print('epoch: 3')
     print('it has finished training')
 

react_frontend/build/asset-manifest.json

 {
   "files": {
     "main.css": "/static/css/main.073c9b0a.css",
-    "main.js": "/static/js/main.a39dcf9a.js",
+    "main.js": "/static/js/main.1009a38b.js",
     "static/js/787.5006ed28.chunk.js": "/static/js/787.5006ed28.chunk.js",
     "index.html": "/index.html",
     "main.073c9b0a.css.map": "/static/css/main.073c9b0a.css.map",
-    "main.a39dcf9a.js.map": "/static/js/main.a39dcf9a.js.map",
+    "main.1009a38b.js.map": "/static/js/main.1009a38b.js.map",
     "787.5006ed28.chunk.js.map": "/static/js/787.5006ed28.chunk.js.map"
   },
   "entrypoints": [
     "static/css/main.073c9b0a.css",
-    "static/js/main.a39dcf9a.js"
+    "static/js/main.1009a38b.js"
   ]
 }
\ No newline at end of file

react_frontend/build/index.html

-<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="/favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1"/><meta name="theme-color" content="#000000"/><meta name="description" content="Web site created using create-react-app"/><link rel="apple-touch-icon" href="/logo192.png"/><link rel="manifest" href="/manifest.json"/><title>MetaRL for AutoAugmentation</title><script defer="defer" src="/static/js/main.a39dcf9a.js"></script><link href="/static/css/main.073c9b0a.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
+<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="/favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1"/><meta name="theme-color" content="#000000"/><meta name="description" content="Web site created using create-react-app"/><link rel="apple-touch-icon" href="/logo192.png"/><link rel="manifest" href="/manifest.json"/><title>MetaRL for AutoAugmentation</title><script defer="defer" src="/static/js/main.1009a38b.js"></script><link href="/static/css/main.073c9b0a.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
\ No newline at end of file

react_frontend/src/pages/Confirm.js

@@ -9,8 +9,9 @@ export default function Confirm() {
     const [dataset, setDataset] = useState()
     const [network, setNetwork] = useState()
 
+    // console.log('already in confirm react')
   useEffect(() => {
-    const res = fetch('/confirm').then(
+    const res = fetch('/home').then(
       response => response.json()
       ).then(data => {setMyData(data);
         if (data.ds == 'Other'){setDataset(data.ds_name)} else {setDataset(data.ds)};

react_frontend/src/pages/Home.js

@@ -60,7 +60,11 @@ export default function Home() {
         method: 'POST',
         body: formData
         }).then((response) => response.json());
-        
+        // {console.log('before calling response'); 
+        //                         response.json();
+        //                         console.log('after calling response')});
+
+        console.log('before navigate to confirm')
         navigate('/confirm', {replace:true});
         // 
         ///////// testing