CognitiveScience commited on
Commit
7cffecf
·
1 Parent(s): fe493ae

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +70 -9
app.py CHANGED
@@ -3,11 +3,15 @@ from bs4 import BeautifulSoup
3
  import requests
4
  from acogsphere import acf
5
  from bcogsphere import bcf
 
 
 
6
  import math
 
7
 
8
  import sqlite3
9
  import huggingface_hub
10
- import pandas as pd
11
  import shutil
12
  import os
13
  import datetime
@@ -15,7 +19,7 @@ from apscheduler.schedulers.background import BackgroundScheduler
15
 
16
  import random
17
  import time
18
- import requests
19
 
20
  from huggingface_hub import hf_hub_download
21
 
@@ -52,6 +56,8 @@ repo.git_pull()
52
  db = sqlite3.connect(DB_FILE)
53
  try:
54
  db.execute("SELECT * FROM reviews").fetchall()
 
 
55
  db.close()
56
  except sqlite3.OperationalError:
57
  db.execute(
@@ -63,17 +69,47 @@ except sqlite3.OperationalError:
63
  db.commit()
64
  db.close()
65
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
66
  def get_latest_reviews(db: sqlite3.Connection):
67
  reviews = db.execute("SELECT * FROM reviews ORDER BY id DESC limit 100").fetchall()
68
  total_reviews = db.execute("Select COUNT(id) from reviews").fetchone()[0]
69
  reviews = pd.DataFrame(reviews, columns=["id", "date_created", "name", "rate", "celsci"])
70
  return reviews, total_reviews
71
 
72
-
 
 
 
 
 
73
  def ccogsphere(name: str, rate: int, celsci: str):
74
  db = sqlite3.connect(DB_FILE)
75
  cursor = db.cursor()
76
- cursor.execute("INSERT INTO reviews(name, rate, celsci) VALUES(?,?,?)", [name, rate, celsci])
 
 
 
 
 
 
 
 
 
 
 
77
  db.commit()
78
  reviews, total_reviews = get_latest_reviews(db)
79
  db.close()
@@ -99,17 +135,42 @@ def run_actr():
99
  env.model2.choice=env.choice2
100
  env.run()
101
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
102
 
103
  def load_data():
104
  db = sqlite3.connect(DB_FILE)
105
  reviews, total_reviews = get_latest_reviews(db)
106
  db.close()
107
  return reviews, total_reviews
 
 
 
 
 
108
 
109
  css="footer {visibility: hidden}"
110
  # Applying style to highlight the maximum value in each row
111
  #styler = df.style.highlight_max(color = 'lightgreen', axis = 0)
112
- with gr.Blocks(css=css) as demo:
113
  with gr.Row():
114
  with gr.Column():
115
  data = gr.Dataframe() #styler)
@@ -120,7 +181,7 @@ with gr.Blocks(css=css) as demo:
120
  rate = gr.Textbox(label="b") #, placeholder="What is your name?") #gr.Radio(label="How satisfied are you with using gradio?", choices=[1, 2, 3, 4, 5])
121
  celsci = gr.Textbox(label="c") #, lines=10, placeholder="Do you have any feedback on gradio?")
122
  #run_actr()
123
- submit = gr.Button(value=".")
124
  submit.click(ccogsphere, [name, rate, celsci], [data, count])
125
  demo.load(load_data, None, [data, count])
126
  @name.change(inputs=name, outputs=celsci,_js="window.location.reload()")
@@ -163,9 +224,9 @@ def backup_db_csv():
163
  # demo.load(load_data,None, [reviews, total_reviews])
164
  # #return reviews, total_reviews
165
 
166
- scheduler2 = BackgroundScheduler()
167
- scheduler2.add_job(func=run_actr, trigger="interval", seconds=3600)
168
- scheduler2.start()
169
 
170
  scheduler2 = BackgroundScheduler()
171
  scheduler2.add_job(func=backup_db, trigger="interval", seconds=3633000)
 
3
  import requests
4
  from acogsphere import acf
5
  from bcogsphere import bcf
6
+ from ecogsphere import ecf
7
+
8
+ import pandas as pd
9
  import math
10
+ import json
11
 
12
  import sqlite3
13
  import huggingface_hub
14
+ #import pandas as pd
15
  import shutil
16
  import os
17
  import datetime
 
19
 
20
  import random
21
  import time
22
+ #import requests
23
 
24
  from huggingface_hub import hf_hub_download
25
 
 
56
  db = sqlite3.connect(DB_FILE)
57
  try:
58
  db.execute("SELECT * FROM reviews").fetchall()
59
+ #db.execute("SELECT * FROM reviews2").fetchall()
60
+
61
  db.close()
62
  except sqlite3.OperationalError:
63
  db.execute(
 
69
  db.commit()
70
  db.close()
71
 
72
+ db = sqlite3.connect(DB_FILE)
73
+ try:
74
+ db.execute("SELECT * FROM reviews2").fetchall()
75
+ #db.execute("SELECT * FROM reviews2").fetchall()
76
+
77
+ db.close()
78
+ except sqlite3.OperationalError:
79
+ db.execute(
80
+ '''
81
+ CREATE TABLE reviews2 (id TEXT,
82
+ title TEXT, link TEXT,channel TEXT, description TEXT, views INTEGER, uploaded TEXT, duration INTEGER, durationString TEXT)
83
+ ''')
84
+ db.commit()
85
+ db.close()
86
  def get_latest_reviews(db: sqlite3.Connection):
87
  reviews = db.execute("SELECT * FROM reviews ORDER BY id DESC limit 100").fetchall()
88
  total_reviews = db.execute("Select COUNT(id) from reviews").fetchone()[0]
89
  reviews = pd.DataFrame(reviews, columns=["id", "date_created", "name", "rate", "celsci"])
90
  return reviews, total_reviews
91
 
92
+ def get_latest_reviews2(db: sqlite3.Connection):
93
+ reviews2 = db.execute("SELECT * FROM reviews2 ORDER BY id DESC limit 100").fetchall()
94
+ total_reviews2 = db.execute("Select COUNT(id) from reviews2").fetchone()[0]
95
+ reviews2 = pd.DataFrame(reviews2, columns=["id","title", "link","channel", "description", "views", "uploaded", "duration", "durationString"])
96
+ return reviews2, total_reviews2
97
+
98
  def ccogsphere(name: str, rate: int, celsci: str):
99
  db = sqlite3.connect(DB_FILE)
100
  cursor = db.cursor()
101
+
102
+ try:
103
+ celsci2=celsci.split()
104
+ print("split",celsci2,celsci)
105
+ celsci2=celsci2[0] + "+" + celsci2[1]
106
+ celsci2=ecf(celsci2)
107
+ celsci2=json.dumps(celsci2["videos"])
108
+ except:
109
+ celsci2=" No Info Found"
110
+
111
+
112
+ cursor.execute("INSERT INTO reviews(name, rate, celsci) VALUES(?,?,?)", [name, rate, celsci+celsci2])
113
  db.commit()
114
  reviews, total_reviews = get_latest_reviews(db)
115
  db.close()
 
135
  env.model2.choice=env.choice2
136
  env.run()
137
 
138
+ def run_ecs(inp):
139
+ try:
140
+ result=ecf(inp)
141
+ df=pd.DataFrame.from_dict(result["videos"])
142
+ except sqlite3.OperationalError:
143
+ print ("db error")
144
+
145
+ df=df.drop(df.columns[4], axis=1)
146
+
147
+ db = sqlite3.connect(DB_FILE)
148
+ #cursor = db.cursor()
149
+ #cursor.execute("INSERT INTO reviews2(title, link, thumbnail,channel, description, views, uploaded, duration, durationString) VALUES(?,?,?,?,?,?,?,?,?)", [title, link, thumbnail,channel, description, views, uploaded, duration, durationString])
150
+ df.to_sql('reviews2', db, if_exists='replace', index=False)
151
+
152
+ #db.commit()
153
+ reviews2, total_reviews2 = get_latest_reviews(db)
154
+ db.close()
155
+ #print ("print000", total_reviews2,reviews2)
156
+ return reviews2, total_reviews2
157
+
158
 
159
  def load_data():
160
  db = sqlite3.connect(DB_FILE)
161
  reviews, total_reviews = get_latest_reviews(db)
162
  db.close()
163
  return reviews, total_reviews
164
+ def load_data2():
165
+ db = sqlite3.connect(DB_FILE)
166
+ reviews2, total_reviews2 = get_latest_reviews2(db)
167
+ db.close()
168
+ return reviews2, total_reviews2
169
 
170
  css="footer {visibility: hidden}"
171
  # Applying style to highlight the maximum value in each row
172
  #styler = df.style.highlight_max(color = 'lightgreen', axis = 0)
173
+ with gr.Blocks() as demo:
174
  with gr.Row():
175
  with gr.Column():
176
  data = gr.Dataframe() #styler)
 
181
  rate = gr.Textbox(label="b") #, placeholder="What is your name?") #gr.Radio(label="How satisfied are you with using gradio?", choices=[1, 2, 3, 4, 5])
182
  celsci = gr.Textbox(label="c") #, lines=10, placeholder="Do you have any feedback on gradio?")
183
  #run_actr()
184
+ submit = gr.Button(value=".")
185
  submit.click(ccogsphere, [name, rate, celsci], [data, count])
186
  demo.load(load_data, None, [data, count])
187
  @name.change(inputs=name, outputs=celsci,_js="window.location.reload()")
 
224
  # demo.load(load_data,None, [reviews, total_reviews])
225
  # #return reviews, total_reviews
226
 
227
+ scheduler1 = BackgroundScheduler()
228
+ scheduler1.add_job(func=run_actr, trigger="interval", seconds=36)
229
+ scheduler1.start()
230
 
231
  scheduler2 = BackgroundScheduler()
232
  scheduler2.add_job(func=backup_db, trigger="interval", seconds=3633000)