From 70237b5a5d82e8425eb5870a975bde497a6def08 Mon Sep 17 00:00:00 2001
From: Pinapelz <donaldshan1@outlook.com>
Date: Tue, 20 Jun 2023 02:14:34 -0700
Subject: Refactored entire codebase - Replaced most code with HTML templates -
 Fixed some janky SQL queries - Replaced config.py with ini and json

---
 html_builders/elements.py | 91 +++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 91 insertions(+)
 create mode 100644 html_builders/elements.py

(limited to 'html_builders/elements.py')

diff --git a/html_builders/elements.py b/html_builders/elements.py
new file mode 100644
index 0000000..41c8525
--- /dev/null
+++ b/html_builders/elements.py
@@ -0,0 +1,91 @@
+import math
+import pandas as pd
+import warnings
+from datetime import datetime, timedelta
+
+def build_title_banner(text: str, menu_items):
+    banner_html = f"""
+    <div class="banner-container">
+        <div class="banner-text">{text}</div>
+    </div>
+    <div class="menu-bar">
+    """
+    for item in menu_items:
+        banner_html += f"""
+            <a href="{item[1]}">{item[0]}</a>
+
+        """
+    banner_html += "</div>"
+    return banner_html
+
+def build_projection_card(server, table_name, curr_subscribers, channel_name,
+                        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
+    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) AND name = \"{channel_name}\" ORDER BY timestamp DESC"
+    df = pd.read_sql_query(query, server.get_connection())
+    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)
+
+
+
-- 
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