chore: script

scripts/list_finalizing_markets.ipynb

@@ -1,5 +1,54 @@
 {
  "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#!/usr/bin/env python3\n",
+    "# -*- coding: utf-8 -*-\n",
+    "# ------------------------------------------------------------------------------\n",
+    "#\n",
+    "#   Copyright 2024 Valory AG\n",
+    "#\n",
+    "#   Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "#   you may not use this file except in compliance with the License.\n",
+    "#   You may obtain a copy of the License at\n",
+    "#\n",
+    "#       http://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "#   Unless required by applicable law or agreed to in writing, software\n",
+    "#   distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "#   See the License for the specific language governing permissions and\n",
+    "#   limitations under the License.\n",
+    "#\n",
+    "# ------------------------------------------------------------------------------\n",
+    "\n",
+    "\"\"\"Script for analyzing market creator markets.\"\"\"\n",
+    "\n",
+    "from collections import defaultdict\n",
+    "from datetime import datetime, timedelta\n",
+    "from enum import Enum\n",
+    "from mech_request_utils import get_mech_requests, IPFS_ADDRESS\n",
+    "from scipy import stats\n",
+    "from string import Template\n",
+    "from typing import Any, Dict, Optional\n",
+    "from IPython.display import display, HTML\n",
+    "\n",
+    "import seaborn as sns\n",
+    "import dateutil.parser\n",
+    "import json\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import pytz\n",
+    "import requests\n",
+    "\n",
+    "MARKET_CREATOR_ADDRESS = \"0x89c5cc945dd550BcFfb72Fe42BfF002429F46Fec\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -54,8 +103,10 @@
     "# Filter out outliers\n",
     "mean = deliver_delay_blocks_stats[2]\n",
     "std = np.sqrt(deliver_delay_blocks_stats[3])\n",
-    "alpha = 1\n",
+    "alpha = 5\n",
     "deliver_delay_blocks = [td for td in deliver_delay_blocks if np.abs(td - mean) <= alpha * std]\n",
+    "#deliver_delay_blocks = [td for td in deliver_delay_blocks]\n",
+    "\n",
     "\n",
     "# Create histogram\n",
     "plt.hist(deliver_delay_blocks, bins=100, color='blue', edgecolor='black')\n",
@@ -165,8 +216,8 @@
     "display_latest_requests(mech_requests)\n",
     "plot_latest_mech_requests_count(mech_requests)\n",
     "\n",
-    "from_date = \"2024-01-01T00:00:00Z\"\n",
-    "to_date = \"2024-12-31T23:59:59Z\"\n",
+    "from_date = \"2024-04-01T00:00:00Z\"\n",
+    "to_date = \"2024-04-25T23:59:59Z\"\n",
     "\n",
     "from_timestamp = int(dateutil.parser.isoparse(from_date).replace(tzinfo=pytz.utc).timestamp())\n",
     "to_timestamp = int(dateutil.parser.isoparse(to_date).replace(tzinfo=pytz.utc).timestamp())\n",
@@ -193,7 +244,7 @@
     "from_date = \"2024-02-19T00:00:00Z\"\n",
     "from_timestamp = int(dateutil.parser.isoparse(from_date).replace(tzinfo=pytz.utc).timestamp())\n",
     "\n",
-    "plot_delivers_evolution_over_time(mech_requests, from_timestamp, weeks=9)  # Plot evolution for 4 weeks\n"
+    "plot_delivers_evolution_over_time(mech_requests, from_timestamp, weeks=12)  # Plot evolution for 4 weeks\n"
    ]
   },
   {
@@ -511,10 +562,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "\n",
-    "from IPython.display import display, HTML\n",
-    "import seaborn as sns\n",
-    "\n",
     "\n",
     "def plot_opened_markets(data: Dict[str, Any]) -> None:\n",
     "\n",
@@ -552,12 +599,15 @@
     "def plot_market_state_count(df: pd.DataFrame) -> None:\n",
     "    state_counts = df[\"State\"].value_counts()\n",
     "\n",
-    "    print(state_counts)\n",
     "    # Plot pie chart\n",
     "    plt.figure(figsize=(8, 8))\n",
     "    plt.pie(state_counts, labels=state_counts.index, autopct='%1.1f%%', startangle=140)\n",
     "    plt.title('Market State Counts')\n",
     "    plt.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
+    "\n",
+    "    # Display legend next to the pie chart\n",
+    "    plt.legend(loc='center left', bbox_to_anchor=(1, 0.5), title=\"States\", fancybox=True)\n",
+    "\n",
     "    plt.show()\n",
     "\n",
     "\n",