mirror of
https://github.com/bytedream/bambulab-store-tracker.git
synced 2025-12-15 10:30:43 +01:00
1108 lines
36 KiB
Plaintext
1108 lines
36 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"id": "initial_id",
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"metadata": {
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"collapsed": true,
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"ExecuteTime": {
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"end_time": "2024-10-02T15:04:24.676647Z",
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"start_time": "2024-10-02T15:04:24.261802Z"
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}
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},
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"source": [
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"from datetime import datetime\n",
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"import sqlite3\n",
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"\n",
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"import plotly.graph_objects as go\n",
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"import pandas as pd"
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],
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"outputs": [],
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"execution_count": 1
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},
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{
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"metadata": {},
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"cell_type": "code",
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"source": [
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"sqlite_file = input(\"Sqlite file: \")\n",
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"conn = sqlite3.connect(sqlite_file)"
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],
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"id": "2a888e85f7940c39",
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"outputs": [],
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"execution_count": null
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},
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{
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"metadata": {},
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"cell_type": "code",
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"source": [
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"query = '''\n",
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"SELECT timestamp, filament_variant_id, available, region\n",
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" FROM availability\n",
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" LEFT JOIN measurements ON availability.measurement_id = measurements.id\n",
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" LEFT JOIN filament_variants ON availability.filament_variant_id = filament_variants.id\n",
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" LEFT JOIN filaments ON filament_variants.filament_id = filaments.id\n",
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"'''\n",
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"df = pd.read_sql(query, conn)\n",
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"\n",
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"all_timestamps = list(df['timestamp'].dropna().unique())\n",
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"all_regions = list(df['region'].dropna().unique())\n",
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"\n",
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"available = {region: [] for region in all_regions}\n",
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"not_available = {region: [] for region in all_regions}\n",
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"\n",
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"for timestamp in all_timestamps:\n",
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" values = df.query(f'timestamp <= {timestamp}').drop(columns=['timestamp']).drop_duplicates(keep='last', subset=['filament_variant_id', 'region'])\n",
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" \n",
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" for region in all_regions:\n",
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" available[region].append(len(values.query(f'(available == 1) and (region == \"{region}\")')))\n",
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" not_available[region].append(len(values.query(f'(available == 0) and (region == \"{region}\")')))\n",
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"\n",
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"fig = go.Figure()\n",
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"for region in all_regions:\n",
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" timestamp_datetime = [datetime.fromtimestamp(timestamp) for timestamp in all_timestamps]\n",
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" ratios = []\n",
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" ratio_texts = []\n",
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" for i in range(len(available[region])):\n",
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" ratios.append(round((available[region][i] / (available[region][i] + not_available[region][i])) * 100, 2))\n",
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" ratio_texts.append(f'({available[region][i]} / {available[region][i] + not_available[region][i]})')\n",
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" \n",
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" fig.add_trace(go.Scatter(x=timestamp_datetime, y=ratios, text=ratio_texts, mode='lines', name=region.upper()))\n",
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"fig.update_layout(title='Availability', xaxis_title='Time', yaxis_title='Availability in %', yaxis_range=[0, 100], yaxis_ticksuffix = '%', hovermode='x unified')\n",
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"fig.show()"
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],
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"id": "28dd4fe644bc6a1d",
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"outputs": [],
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"execution_count": null
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-10-02T17:15:27.885991Z",
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"start_time": "2024-10-02T17:15:27.304499Z"
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}
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},
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"cell_type": "code",
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"source": [
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"query = '''\n",
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"SELECT timestamp, price, filament_variant_id, region\n",
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" FROM prices\n",
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" LEFT JOIN measurements ON prices.measurement_id = measurements.id\n",
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" LEFT JOIN filament_variants ON prices.filament_variant_id = filament_variants.id\n",
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" LEFT JOIN filaments ON filament_variants.filament_id = filaments.id\n",
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"'''\n",
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"df = pd.read_sql(query, conn)\n",
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"\n",
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"# average price changes\n",
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"fig = go.Figure()\n",
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"for region in list(df['region'].dropna().unique()):\n",
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" changed = 0\n",
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" unchanged = 0\n",
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" price_changes = []\n",
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" \n",
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" for _, rows in df.query(f'(price > 0) and (region == \"{region}\")').groupby('filament_variant_id'):\n",
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" if len(rows) == 1:\n",
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" unchanged += 1\n",
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" continue\n",
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" else:\n",
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" changed += 1\n",
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" \n",
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" first_price = rows.iloc[0].iloc[1]\n",
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" last_price = rows.iloc[-1].iloc[1]\n",
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" \n",
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" price_changes.append((last_price - first_price) / first_price * 100)\n",
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" \n",
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" price_changes_percent = sum(price_changes) / len(price_changes)\n",
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" fig.add_trace(go.Bar(name=region, text=f'{price_changes_percent:.2f}%', x=[region], y=[price_changes_percent]))\n",
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"fig.update_layout(title='Average price changes', xaxis_title='Region', yaxis_title='Average price change in %', yaxis_range=[-100, 100])\n",
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"fig.show()"
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],
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"id": "820c18682316ff52",
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"outputs": [
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{
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"data": {
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