Upload app.py

app.py

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+import streamlit as st
+import datasets
+from datasets import load_dataset
+import pandas as pd
+from streamlit.components.v1 import html
+from streamlit import markdown
+import re
+import os
+import time
+
+import json
+
+
+st.title('StackOverflow Question Demo.')
+
+library = st.radio('Select a library', ('numpy', 'tensorflow', 'pytorch', 'scipy', 'scikit-learn', 'pandas'))
+
+#question_path = './{}.txt'.format(library)
+question_path = 'numpy.txt'
+# loading stackoverflow questions.
+# using huggingface load_dataset function.
+# not done yet
+#@st.cache
+#def load_data(path):
+#    return load_dataset('text', data_files = path, cache_dir = './data')
+
+
+dataset = []
+#dataset = load_data(question_path)
+with open(question_path) as f:
+    lines = f.readlines()
+    question = ''
+    temp = {}
+    tag = ''
+    for line in lines:
+        if line == 'Origin:\n' or line == 'Function:\n' or re.match(r'A\d:\n', line):
+            if not tag:
+                tag = line[:-2]
+            else:
+                temp[tag] = question
+                question = ''
+                tag = line[:-2]
+        else:
+            if tag:
+                question += line
+
+dataset.append(temp)
+
+# Select index
+number = st.number_input("Insert a index: range from", 
+    min_value = 0, max_value = len(dataset) - 1)
+st.write('The current index is ', number)
+data_index = int(number)
+
+# Selece modification
+options = tuple(dataset[data_index].keys())
+modification = st.radio('Which modification would you choose?',
+            options = options
+)
+
+
+st.write(dataset[data_index][modification])
+
+