Add application file

app.py

@@ -0,0 +1,111 @@
+#R11142005 紀柔安
+import streamlit as st
+from views.components.spinner import dowload_ckip_package, download_cwn_drivers
+import pandas as pd
+import requests 
+import bs4
+from snownlp import SnowNLP
+
+
+def run_app(ckip_nlp_models, cwn_upgrade) -> None:
+    # need to download first because CWN packages will first check whether
+    # there is .cwn_graph folder in the root directory.
+    download_cwn_drivers(cwn_upgrade)
+    dowload_ckip_package(ckip_nlp_models)
+
+    from views.components.sidebar import visualize_side_bar
+    from views.containers import display_cwn, display_ckip, display_data_form
+
+    st.title("NLP app for PTT")
+    st.write("這是一個針對PTT語料的 情緒分析｜中文NLP管線處理🔎")
+    st.image("/Users/joannechi/nlpWeb/myApp/nlpweb/nlp_assignment_1/img/Mo-PTT-Logo.png", width=200)
+
+    #menu = ["Text","Sentences"]
+    #choice = st.sidebar.selectbox("Menu",menu) 
+
+
+    #spectra = st.file_uploader("upload your file", type={"csv", "txt"})
+    #if spectra is not None:
+    #    spectra_df = pd.read_csv(spectra) #讀取csv
+    #    st.write(spectra_df)
+
+    #~~web crawler~~
+    st.subheader("PTT Crawler 🐛")
+    st.text('目前看板有：HatePolitics｜Gossiping｜Military｜Stock')
+    selected = st.selectbox('請選擇看板：', 
+      ['HatePolitics', 'Gossiping','Military','Stock']) 
+    if selected=='HatePolitics':
+        URL = "https://www.ptt.cc/bbs/HatePolitics/index.html"
+    elif selected=='Gossiping':
+        URL = "https://www.ptt.cc/bbs/Gossiping/index.html"
+    elif selected=='Military':
+        URL = "https://www.ptt.cc/bbs/Military/index.html"
+    else:
+        URL = "https://www.ptt.cc/bbs/Stock/index.html"
+
+    my_headers = {'cookie': 'over18=1;'}
+    response = requests.get(URL, headers = my_headers)
+    soup = bs4.BeautifulSoup(response.text,"html.parser")
+    list_results=[]
+    for t in soup.find_all('div','title'):
+        find_a=t.find('a')
+        find_href="https://www.ptt.cc"+find_a.get("href")
+        title=t.text
+        results={
+            "title":title,
+            "url":find_href
+        }
+        list_results.append(results)        
+    my_df=pd.DataFrame(list_results)
+    print(my_df)
+    st.write(my_df)
+    #~~web crawler~~
+
+    #~~sentiment analysis~~
+    st.subheader("情緒分析")
+    with st.form(key="nlpForm"):
+        raw_text=st.text_area("請輸入句子✏️")
+        submit_button=st.form_submit_button(label="確定")
+        
+    if submit_button:
+        
+        st.info("sentiment")
+        sentiment=SnowNLP(SnowNLP(raw_text).han) #轉簡體
+        sentiment_han=sentiment.sentiments
+        st.write(sentiment_han)
+
+            #emoji
+        if sentiment_han>0:
+            st.markdown("Sentiment:: Positive :smiley: ")
+        elif sentiment_han<0:
+            st.markdown("Sentiment:: Negative :angry: ")
+        else:
+            st.markdown("Sentiment:: Neutral :neutral: ")
+
+
+
+        #with col2:
+            #st.info("category")
+            #category=SnowNLP(SnowNLP(raw_text).han) #轉簡體
+            #category_han=list(category.tags)
+            #st.write(category_han)
+
+    #~~sentiment analysis~~
+
+    st.subheader("中文 NLP 管線處理")
+
+    input_data = display_data_form()
+    model, pipeline, active_visualizers = visualize_side_bar(ckip_nlp_models) 
+                                        #return model_options, pipeline_options, active_visualizers
+
+    display_factories = {"CKIP": display_ckip, "CWN": display_cwn}
+
+    if "input_data" in st.session_state:
+        display_factories[pipeline](
+            model, active_visualizers, st.session_state["input_data"]
+        )
+
+
+if __name__ == "__main__":
+    ckip_nlp_models = ["bert-base", "albert-tiny", "bert-tiny", "albert-base"]
+    run_app(ckip_nlp_models, cwn_upgrade=False)