File size: 1,077 Bytes
36bbacc c9d6da6 ac3ed37 ca66fd2 de5b00f aa8465d 9650f42 00f9a85 e2ba2da d2082a1 e2ba2da d2082a1 9165b8b 4d1ba77 d2082a1 add49a5 4d1ba77 e98811a f648e82 e98811a f648e82 e98811a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 |
import urllib.request
import streamlit as st
import os
from datasets import load_from_disk
import requests
with urllib.request.urlopen('https://huggingface.co/datasets/Seetha/Visualization') as response:
data = response.read()
with open('./level2.json','r+') as fi:
data = fi.read()
st.write('before change', data)
fi.seek(0)
fi.write('Hello world!')
fi.truncate()
st.write(os.path.abspath("./level2.json"))
with open('./level2.json','w') as dat:
dat.write('hello hello')
#st.write(data_after)
# bin_file = open('./level2.json', 'rb')
# # Execute the request
# response = requests.post('https://huggingface.co/datasets/Seetha/Visualization', files={'file': bin_file})
# # Close the file
# bin_file.close()
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("Seetha/Visualization")
# Make changes to the dataset
# ...
# Save the changed dataset to a file
dataset.save_to_disk('./level.json')
# In your Streamlit app, load the dataset from the file
dataset = load_dataset('json', data_files='./level.json')
|