Skip to main content

How to loop through a json file and change specific values based on specific criterias

I am trying to make a python script in which I can change a specific value based on a specific location inside a file for this example a json file specifically.

The json file is about 100k long there are multiple areas specified with "name": "Box #14", "name": "Box #16", "name": "Box #17" and the list keeps going. For each name it comes an image field just below the name e.g. "image": ".png", I want to edit that .png value to be based on a specific value depending on the name number. For example if "name": "Box #14 then "image": "13.png" and if "name": "Box #15 then "image": "14.png" and so on...

What I got so far is:

import re
import sys

i = 0
++i

PAT = re.compile('"image": ".png"')

KEYWORDS_PATH = 'images.json'
KEYWORDS = open(KEYWORDS_PATH).read().splitlines()

names = ['"name": ".*"']


def check_all(check, ws):
    return all(re.search(r'\b{}\b'.format(w), check) for w in ws)


with open('images.json') as inp, open('output.json', 'w') as out:

    for name in names:
        if names in KEYWORDS:
            print('Removed the keyword - %s' % names)
            sys.exit()
    for line in inp:
        out.write(PAT.sub('"image": "%s.png"' % i, line))

this is making everything 0.png

Update:

this is one examples inside the json file

{
  "name": "Box #14",
  "image": ".png",
  "attributes": [
    {
      "trait_type": "Size",
      "value": "0.8 inch"
    }   
  ]
    "files": [
      {
        "url": ".png",
        "type": "image/png"
      }
    ]
  }
}

All I want to do is replace the .png inside the image field with whatever the number on the name is but a digit below e.g. as shown above Box #14 name I want the image to be replaced from .png to 13.png



source https://stackoverflow.com/questions/70792602/how-to-loop-through-a-json-file-and-change-specific-values-based-on-specific-cri

Comments

Popular posts from this blog

Why is my reports service not connecting?

I am trying to pull some data from a Postgres database using Node.js and node-postures but I can't figure out why my service isn't connecting. my routes/index.js file: const express = require('express'); const router = express.Router(); const ordersCountController = require('../controllers/ordersCountController'); const ordersController = require('../controllers/ordersController'); const weeklyReportsController = require('../controllers/weeklyReportsController'); router.get('/orders_count', ordersCountController); router.get('/orders', ordersController); router.get('/weekly_reports', weeklyReportsController); module.exports = router; My controllers/weeklyReportsController.js file: const weeklyReportsService = require('../services/weeklyReportsService'); const weeklyReportsController = async (req, res) => { try { const data = await weeklyReportsService; res.json({data}) console...

How to show number of registered users in Laravel based on usertype?

i'm trying to display data from the database in the admin dashboard i used this: <?php use Illuminate\Support\Facades\DB; $users = DB::table('users')->count(); echo $users; ?> and i have successfully get the correct data from the database but what if i want to display a specific data for example in this user table there is "usertype" that specify if the user is normal user or admin i want to user the same code above but to display a specific usertype i tried this: <?php use Illuminate\Support\Facades\DB; $users = DB::table('users')->count()->WHERE usertype =admin; echo $users; ?> but it didn't work, what am i doing wrong? source https://stackoverflow.com/questions/68199726/how-to-show-number-of-registered-users-in-laravel-based-on-usertype

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...