Upload app.py

app.py

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+import streamlit as st
+import twint
+import pandas as pd
+
+
+# add banner image
+st.header("Data Scraper App")
+st.image('images/twitter.jpg')
+st.subheader('''
+A simple app to scrap data from Twitter.
+''')
+
+# form to collect searcy query and other conditions
+my_form = st.form(key='Twitter_form')
+search_query = my_form.text_input('Input your search query')
+data_limit = my_form.slider('How many tweets do you want to get?', 
+                    10, 
+                    3000, 
+                    value= 100,
+                    step=10)
+
+output_csv = my_form.radio('Save data to a CSV file?', 
+                        ['Yes', 'No'])
+file_name = my_form.text_input('Name the CSV file:')
+submit = my_form.form_submit_button(label='Search')
+
+# function to show output in pandas dataframe with specific folumns 
+def twint_to_pd(columns):
+  return twint.output.panda.Tweets_df[columns]
+
+# configure twint to serach the query
+if submit:
+    config = twint.Config()
+    config.Search = search_query
+    config.Limit = data_limit
+    config.Pandas = True
+    if output_csv == "Yes":
+        config.Store_csv = True
+        config.Output = 'data/{}.csv'.format(file_name)
+    twint.run.Search(config)
+
+    st.subheader("Results: Sample Data")
+    if output_csv == "Yes":
+        # show data in pandas dataframe
+        data = pd.read_csv('data/{}.csv'.format(file_name),usecols=['date','username','tweet'])
+        st.table(data)
+    else:
+        data = twint_to_pd(["date","username","tweet"])
+        st.table(data)
+        
+    
+    #download the dataframe
+    @st.cache
+    def convert_df(df):
+        # IMPORTANT: Cache the conversion to prevent computation on every rerun
+        return df.to_csv().encode('utf-8')
+
+    csv = convert_df(data)
+
+    st.download_button(
+        label="Download scrapped data as CSV",
+        data=csv,
+        file_name='{}.csv'.format(file_name),
+        mime='text/csv',
+ )