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"""
Flask app for serving the static files
"""
from flask import Flask, send_file, jsonify
from flask_cors import CORS
from sql.sql_handler import SQLHandler
import fileutil as fs
import datetime
import pandas
from sklearn.linear_model import LinearRegression
import numpy as np
app = Flask(__name__)
CONFIG = fs.load_config("config.ini")
CORS(app)
# Optional setting to use any of the custom options below
START_DATE = "2023-04-01" # 2023 April 1st
# Do not include datapoints before the START_DATE for any /api/subscribers/ endpoint
# For when you only want to serve actual data you collected at those specific endpoints
ALL_EXCLUDE_MANUAL_DATA = False
# Do not include datapoints before the START_DATE for any /api/subscribers/<channel_id> endpoint
# For when you only want to serve actual data you collected at those specific endpoints
INDIVIDUAL_EXCLUDE_MANUAL_DATA = True
@app.route("/")
def index():
return send_file("index.html")
@app.route("/api/subscribers")
def api_subscribers():
server = SQLHandler(CONFIG["SQL"]["host"], CONFIG["SQL"]["user"], CONFIG["SQL"]["password"], CONFIG["SQL"]["database"])
data = server.execute_query("SELECT * FROM subscriber_data INNER JOIN 24h_historical ON subscriber_data.channel_id = 24h_historical.channel_id ORDER BY subscriber_count DESC")
channel_data_list = [{"channel_name":row[3], "profile_pic": row[2], "subscribers": row[4], "sub_org": row[5], "video_count": row[6], "day_diff": int(row[4] - int(row[10]))} for row in data]
subscriber_data = {"timestamp": datetime.datetime.now(),"channel_data":channel_data_list}
return jsonify(subscriber_data)
@app.route("/api/subscribers/<channel_name>")
def api_subscribers_channel(channel_name):
server = SQLHandler(CONFIG["SQL"]["host"], CONFIG["SQL"]["user"], CONFIG["SQL"]["password"], CONFIG["SQL"]["database"])
data = server.execute_query("SELECT * FROM subscriber_data_historical WHERE name = %s AND timestamp > %s", (channel_name, START_DATE))
sorted_data = sorted(data, key=lambda row: row[5].strftime("%Y-%m-%d"))
labels = []
data_points = []
seen_dates = set()
for row in sorted_data:
date_string = row[5].strftime("%Y-%m-%d")
if date_string in seen_dates:
continue
labels.append(date_string)
data_points.append(row[4])
seen_dates.add(date_string)
return jsonify({"labels": labels, "datasets": data_points})
@app.route("/api/subscribers/<channel_name>/7d")
def api_subscribers_channel_7d(channel_name):
server = SQLHandler(CONFIG["SQL"]["host"], CONFIG["SQL"]["user"], CONFIG["SQL"]["password"], CONFIG["SQL"]["database"])
data = server.execute_query("SELECT * FROM subscriber_data_historical WHERE name = %s", (channel_name,))
sorted_data = sorted(data, key=lambda row: row[5].strftime("%Y-%m-%d"))
labels = []
data_points = []
seen_dates = set()
for row in sorted_data:
date_string = row[5].strftime("%Y-%m-%d")
if date_string in seen_dates:
continue
labels.append(date_string)
data_points.append(row[4])
seen_dates.add(date_string)
return jsonify({"labels": labels[-7:], "datasets": data_points[-7:]})
@app.route("/api/channel/<channel_name>")
def get_channel_information(channel_name):
def find_next_milestone(subscriber_count):
if subscriber_count < 100000:
return ((subscriber_count // 10000) + 1) * 10000
elif subscriber_count < 1000000:
return ((subscriber_count // 100000) + 1) * 100000
else:
return ((subscriber_count // 1000000) + 1) * 1000000
server = SQLHandler(CONFIG["SQL"]["host"], CONFIG["SQL"]["user"], CONFIG["SQL"]["password"], CONFIG["SQL"]["database"])
data = server.execute_query("SELECT * FROM subscriber_data WHERE name = %s", (channel_name,))
channel_data = {"channel_id":data[0][1],"channel_name":data[0][3], "profile_pic": data[0][2], "subscribers": data[0][4], "sub_org": data[0][5], "video_count": data[0][6]}
historical_data = server.execute_query("SELECT * FROM subscriber_data_historical WHERE name = %s", (channel_name,))
current_subscriber_count = data[0][4]
subscriber_points = []
date_strings = []
seen_dates = set()
for row in historical_data:
date_string = row[5].strftime("%Y-%m-%d")
if date_string in seen_dates:
continue
subscriber_points.append(row[4])
date_strings.append(date_string)
seen_dates.add(date_string)
data = {"subscribers": subscriber_points, "dates": date_strings}
df = pandas.DataFrame(data=data)
df['dates'] = pandas.to_datetime(df['dates'])
df.set_index('dates', inplace=True)
try:
model = LinearRegression()
X = np.array(range(len(df))).reshape(-1, 1)
y = df['subscribers']
model.fit(X, y)
next_milestone = find_next_milestone(current_subscriber_count)
days_until_next_milestone = (next_milestone - model.intercept_) / model.coef_
days_until_next_milestone_scalar = int(days_until_next_milestone[0])
next_milestone_date = (df.index[0] + pandas.Timedelta(days=days_until_next_milestone_scalar)).date()
time_until_next_milestone = (next_milestone_date - datetime.datetime.now().date()).days
channel_data["next_milestone_date"] = str(next_milestone_date)
channel_data["days_until_next_milestone"] = str(time_until_next_milestone)
channel_data["next_milestone"] = str(next_milestone)
except OverflowError:
channel_data["next_milestone_date"] = "N/A"
channel_data["days_until_next_milestone"] = "N/A"
channel_data["next_milestone"] = "N/A"
return jsonify(channel_data)
@app.route("/api/announcement")
def api_announcement():
"""
Can be used to show a particular message/error on the NEXT interface
"""
announcement_data = {"message": "None", "show_message": False} # stub TODO
@app.errorhandler(404)
def not_found(error):
return jsonify(error=str(error)), 404
if __name__ == "__main__":
app.run(debug=True, port=5001)
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