Merge pull request #2 from pinapelz/develop-rewrite

Refactored entire codebase

1 files changed, 0 insertions, 128 deletions

diff --git a/sql/graph_builder.py b/sql/graph_builder.py
deleted file mode 100644
index df108b3..0000000
--- a/sql/graph_builder.py
+++ /dev/null
@@ -1,128 +0,0 @@
-import plotly.graph_objs as go
-import pandas as pd
-import mysql.connector
-from mysql.connector import errorcode
-import warnings
-import math
-from datetime import datetime, timedelta
-import numpy as np
-
-
-def plot_subscriber_count_over_time(host, username, password, database_name, table_name,
-                                    gtitle = "Subscriber Count Over Time for Nijisanji Members",
-                                    overrideQuery = None, markers = "lines", exclude_channels = []):
-    warnings.filterwarnings('ignore')  # Ignore pandas warning regarding pyodbc
-    try:
-        cnx = mysql.connector.connect(user = username, password = password,
-                                      host = host, database = database_name)
-    except mysql.connector.Error as err:
-        if err.errno == errorcode.ER_ACCESS_DENIED_ERROR:
-            print("Something is wrong with your user name or password")
-        elif err.errno == errorcode.ER_BAD_DB_ERROR:
-            print("Database does not exist")
-        else:
-            print(err)
-    query = f"SELECT name, subscriber_count, timestamp, channel_id FROM {table_name} ORDER by timestamp DESC" if overrideQuery is None else overrideQuery
-    df = pd.read_sql_query(query, cnx)
-    groups = df.groupby("name")
-    fig = go.Figure()
-    config = dict({'responsive': True, 'displaylogo': False})
-    for channel, group in groups:
-        if len(exclude_channels) != 0 and group['channel_id'].iloc[0] in exclude_channels:
-            continue
-        fig.add_trace(go.Scattergl(
-            x = group["timestamp"], y = group["subscriber_count"], name = channel, mode = markers,
-            showlegend = True))
-
-    fig.update_layout(
-        title = {'text': gtitle, 'x': 0.5, 'xanchor': 'center',
-                 'yanchor': 'top', 'font': {'family': 'Arial', 'size': 30}},
-        xaxis_title = "Timestamp",
-        yaxis_title = "Subscribers",
-        legend = dict(font = dict(size = 16), title = dict(text = "Channels")),
-        height = 950
-    )
-    return fig.to_html(config = config)
-
-
-def generate_projection(host, username, password, database_name, table_name, curr_subscribers,
-                        timezone = "Pacific Standard Time"):
-    def get_next_milestone(subscriber_count):
-        num_digits = len(str(subscriber_count))
-        if num_digits <= 4:
-            milestone_interval = 10000
-        else:
-            milestone_interval = 10 ** (num_digits - 1)
-        next_milestone = math.ceil(
-            subscriber_count / milestone_interval) * milestone_interval
-
-        return next_milestone
-
-    warnings.filterwarnings('ignore')  # Ignore pandas warning regarding pyodbc
-    try:
-        cnx = mysql.connector.connect(user = username, password = password,
-                                      host = host, database = database_name)
-    except mysql.connector.Error as err:
-        if err.errno == errorcode.ER_ACCESS_DENIED_ERROR:
-            print("Something is wrong with your user name or password")
-        elif err.errno == errorcode.ER_BAD_DB_ERROR:
-            print("Database does not exist")
-        else:
-            print(err)
-
-    def create_milestone_card(time_until_milestone, next_milestone, not_enough_data = False,
-                              declining = False):
-        now = datetime.now()
-        milestone_date = (
-                now + timedelta(seconds = time_until_milestone)).strftime('%Y-%m-%d')
-        relative_time = now + timedelta(seconds = time_until_milestone) - now
-        next_milestone_str = "{:,}".format(next_milestone)
-        if relative_time.days > 1:
-            relative_time_str = f"In {relative_time.days} days"
-        elif relative_time.days == 1:
-            relative_time_str = f"In {relative_time.days} day"
-        elif relative_time.days < 0:
-            relative_time_str = f"{-relative_time.days} days ago"
-        elif not_enough_data:
-            relative_time_str = "Not enough data"
-        elif declining:
-            relative_time_str = "Declining"
-        else:
-            relative_time_str = "Today"
-        card = f"""
-        <div style="background-color: #ffffff; padding: 20px; border-radius: 10px; box-shadow: 0 0 10px rgba(0, 0, 0, 0.2); font-family: 'Poppins', sans-serif;">
-            <div style="font-size: 24px; font-weight: bold; margin-bottom: 10px;">Next Milestone</div>
-            <div style="font-size: 18px; margin-bottom: 10px;">{next_milestone_str}</div>
-            <div style="display: flex; flex-direction: row; justify-content: space-between; margin-bottom: 10px;">
-                <div style="font-size: 16px;">Estimated Date:</div>
-                <div style="font-size: 16px; font-weight: bold;">{milestone_date}</div>
-            </div>
-            <div style="display: flex; flex-direction: row; justify-content: space-between; color: #888;">
-                <div style="font-size: 16px;">{relative_time_str}</div>
-                <div style="font-size: 16px;">{timezone}</div>
-            </div>
-        </div>
-        <br>
-        """
-
-        return card
-
-    query = f"SELECT name, subscriber_count, timestamp FROM {table_name} WHERE timestamp >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY) ORDER BY timestamp DESC"
-    df = pd.read_sql_query(query, cnx)
-    df = df.sort_values(by = 'timestamp')
-    # get the rate of change from first data point to last data point
-    first_data = df.iloc[0]
-    last_data = df.iloc[-1]
-    delta_sub_count = last_data['subscriber_count'] - first_data['subscriber_count']
-    delta_time = (last_data['timestamp'] - first_data['timestamp']).total_seconds()
-
-    # Calculate the average rate of change of subscriber_count over time
-    avg_rate_of_change = delta_sub_count / delta_time
-    next_milestone = get_next_milestone(curr_subscribers)
-    if avg_rate_of_change == 0 or math.isnan(avg_rate_of_change) or math.isinf(avg_rate_of_change):
-        return create_milestone_card(0, next_milestone, not_enough_data = True)
-    if avg_rate_of_change < 0:
-        return create_milestone_card(0, next_milestone, declining = True)
-    time_to_next_milestone = (
-                                     next_milestone - curr_subscribers) / avg_rate_of_change
-    return create_milestone_card(time_to_next_milestone, next_milestone)