{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Extracted 241 titles and stored them in titles.txt\n" ] } ], "source": [ "import json\n", "\n", "# Define the input and output file names\n", "input_file = 'Chrome\\History.json'\n", "output_file = 'titles.txt'\n", "\n", "# Read the JSON data from the input file\n", "with open(input_file, 'r') as file:\n", " data = json.load(file)\n", "\n", "# Extract titles from the JSON data\n", "titles = [entry['title'] for entry in data.get('Browser History', [])]\n", "\n", "# Write the extracted titles to the output file\n", "with open(output_file, 'w') as file:\n", " for title in titles:\n", " if len(title.strip()) != 0:\n", " file.write(f\"{title}\\n\")\n", "\n", "print(f\"Extracted {len(titles)} titles and stored them in {output_file}\")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2024-03-13 11:57:15\n" ] } ], "source": [ "from datetime import datetime\n", "\n", "\n", "def convert_time_usec_to_readable(time_usec):\n", " # Convert microseconds to seconds\n", " time_seconds = time_usec / 1000000\n", "\n", " # Convert Unix timestamp to a datetime object\n", " dt_object = datetime.fromtimestamp(time_seconds)\n", "\n", " # Format the datetime object to a readable string\n", " readable_time = dt_object.strftime(\"%Y-%m-%d %H:%M:%S\")\n", "\n", " return readable_time\n", "\n", "\n", "# Example time_usec value\n", "time_usec = 1710345435804090\n", "print(convert_time_usec_to_readable(time_usec)) # Output: '2024-05-22 14:37:15'" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Extracted 241 titles and stored them along with timestamp in titles_with_timestamp.txt\n" ] } ], "source": [ "import json\n", "from datetime import datetime\n", "\n", "# Define the input and output file names\n", "input_file = \"Chrome\\History.json\"\n", "output_file = \"titles_with_timestamp.txt\"\n", "\n", "# Read the JSON data from the input file\n", "with open(input_file, \"r\") as file:\n", " data = json.load(file)\n", "\n", "# Extract titles from the JSON data\n", "entries = [\n", " (entry[\"title\"], entry[\"time_usec\"]) for entry in data.get(\"Browser History\", [])\n", "]\n", "\n", "\n", "# Write the extracted titles with timestamp to the output file\n", "with open(output_file, \"w\") as file:\n", " for title, time_usec in entries:\n", " if len(title.strip()) != 0:\n", " readable_timestamp = convert_time_usec_to_readable(time_usec)\n", " file.write(f\"{readable_timestamp}: {title}\\n\")\n", "\n", "print(\n", " f\"Extracted {len(titles)} titles and stored them along with timestamp in {output_file}\"\n", ")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "torch2", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.18" } }, "nbformat": 4, "nbformat_minor": 2 }