{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e0114ca0-14f6-40f5-bbb2-a9a11cbf871b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "    ╔═══════════════════════════════════════════════════════════════════════╗\n",
      "    ║                    MULTI-SOURCE NEWS FETCHER                          ║\n",
      "    ║                    For Trading & Economic News                        ║\n",
      "    ╚═══════════════════════════════════════════════════════════════════════╝\n",
      "\n",
      "    REQUIRED PACKAGES:\n",
      "    pip install requests beautifulsoup4 pandas\n",
      "\n",
      "    API KEYS (Optional but recommended):\n",
      "    1. Trading Economics: https://tradingeconomics.com/api/\n",
      "    2. NewsAPI.org: https://newsapi.org/\n",
      "\n",
      "    \n",
      "\n",
      ">>> Fetching from free sources (Forex Factory & Investing.com)...\n",
      "\n",
      "\n",
      "====================================================================================================\n",
      "FETCHING NEWS FROM ALL SOURCES\n",
      "====================================================================================================\n",
      "\n",
      "[1/4] Fetching from Forex Factory...\n",
      "\n",
      "====================================================================================================\n",
      "FOREX FACTORY ECONOMIC CALENDAR\n",
      "====================================================================================================\n",
      "Error fetching Forex Factory data: 403 Client Error: Forbidden for url: https://www.forexfactory.com/calendar\n",
      "\n",
      "[2/4] Fetching from Investing.com...\n",
      "\n",
      "====================================================================================================\n",
      "INVESTING.COM ECONOMIC CALENDAR\n",
      "====================================================================================================\n",
      "\n",
      "Fetched 39 events from Investing.com\n",
      " Time Currency Importance                                         Event    Actual Forecast Previous\n",
      "01:00      RUB     Medium                S&P Global Services PMI  (Dec)      52.3              52.2\n",
      "03:00      CHF     Medium                 KOF Leading Indicators  (Dec)     103.4    101.5    101.7\n",
      "03:00      EUR        Low                         Core CPI (YoY)  (Dec)      2.6%              2.6%\n",
      "03:00      EUR        Low                      Spanish CPI (MoM)  (Dec)      0.3%              0.2%\n",
      "03:00      EUR     Medium                      Spanish CPI (YoY)  (Dec)      2.9%     2.8%     3.0%\n",
      "03:00      EUR        Low                     Spanish HICP (MoM)  (Dec)      0.3%              0.0%\n",
      "03:00      EUR     Medium                     Spanish HICP (YoY)  (Dec)      3.0%     3.0%     3.2%\n",
      "03:00      EUR        Low             Spanish Retail Sales (YoY)  (Nov)      6.0%              3.9%\n",
      "04:00      EUR        Low                Spanish Current account  (Oct)     7.18B             1.87B\n",
      "06:17      ZAR        Low                   Budget Balance (MoM)  (Nov)   -14.99B           -35.83B\n",
      "06:30      BRL        Low                  Net Debt-to-GDP ratio  (Nov)     65.2%             65.0%\n",
      "06:30      BRL        Low                         Budget Balance  (Nov) -101.600B -86.400B -81.522B\n",
      "06:30      BRL        Low                         Budget Surplus  (Nov)  -14.400B           32.392B\n",
      "06:30      BRL     Medium          Gross Debt-to-GDP ratio (MoM)  (Nov)     79.0%    79.0%    78.6%\n",
      "07:00      INR        Low                      Foreign Debt (USD)  (Q3)    746.0B            747.2B\n",
      "07:00      INR        Low                               M3 Money Supply      9.3%             10.2%\n",
      "07:00      BRL     Medium                      Unemployment Rate  (Nov)      5.2%     5.4%     5.4%\n",
      "08:55      USD        Low                                 Redbook (YoY)      7.6%              7.2%\n",
      "09:00      USD        Low                House Price Index (MoM)  (Oct)      0.4%     0.1%    -0.1%\n",
      "09:00      USD        Low                House Price Index (YoY)  (Oct)      1.7%              1.8%\n",
      "09:00      USD        Low                      House Price Index  (Oct)     436.7             435.2\n",
      "09:00      USD        Low   S&P/CS HPI Composite - 20 s.a. (MoM)  (Oct)      0.3%              0.2%\n",
      "09:00      USD     Medium S&P/CS HPI Composite - 20 n.s.a. (YoY)  (Oct)      1.3%     1.1%     1.4%\n",
      "09:00      USD     Medium S&P/CS HPI Composite - 20 n.s.a. (MoM)  (Oct)     -0.3%             -0.5%\n",
      "09:45      USD       High                            Chicago PMI  (Dec)      43.5     39.8     36.3\n",
      "10:30      USD        Low           Dallas Fed Services Revenues  (Dec)       0.1              -2.5\n",
      "10:30      USD        Low          Texas Services Sector Outlook  (Dec)      -3.3              -2.3\n",
      "12:00      BRL        Low                 CAGED Net Payroll Jobs  (Nov)    85.86K   75.00K   85.15K\n",
      "13:00      USD     Medium               U.S. Baker Hughes Oil Rig Count       412               409\n",
      "13:00      USD     Medium             U.S. Baker Hughes Total Rig Count       546               545\n",
      "14:00      USD       High                          FOMC Meeting Minutes                            \n",
      "16:30      USD     Medium                    API Weekly Crude Oil Stock    1.700M            2.400M\n",
      "18:00      KRW        Low                              CPI (YoY)  (Dec)      2.3%     2.3%     2.4%\n",
      "18:00      KRW        Low                              CPI (MoM)  (Dec)      0.3%     0.2%    -0.2%\n",
      "20:30      CNY     Medium                  Chinese Composite PMI  (Dec)      50.7              49.7\n",
      "20:30      CNY       High                      Manufacturing PMI  (Dec)      50.1     49.2     49.2\n",
      "20:30      CNY     Medium                  Non-Manufacturing PMI  (Dec)      50.2     49.6     49.5\n",
      "20:45      CNY     Medium         Caixin Manufacturing PMI (MoM)  (Dec)      50.1     49.8     49.9\n",
      "23:30      SGD        Low                           Bank Lending  (Nov)                      866.1B\n",
      "\n",
      "[3/4] Fetching from Trading Economics...\n",
      "\n",
      "====================================================================================================\n",
      "TRADING ECONOMICS API\n",
      "====================================================================================================\n",
      "\n",
      "API Key required!\n",
      "Get your free API key at: https://tradingeconomics.com/api/\n",
      "Then call: fetch_trading_economics_news(api_key='YOUR_KEY')\n",
      "\n",
      "[4/4] Fetching from NewsAPI.org...\n",
      "\n",
      "====================================================================================================\n",
      "NEWSAPI.ORG - FINANCIAL NEWS\n",
      "====================================================================================================\n",
      "\n",
      "API Key required!\n",
      "Get your free API key at: https://newsapi.org/\n",
      "Then call: fetch_newsapi_org(api_key='YOUR_KEY')\n",
      "\n",
      "====================================================================================================\n",
      "SUMMARY\n",
      "====================================================================================================\n",
      "✗ forexfactory: Failed or requires API key\n",
      "✓ investing: 39 items fetched\n",
      "✗ trading_economics: Failed or requires API key\n",
      "✗ newsapi: Failed or requires API key\n"
     ]
    }
   ],
   "source": [
    "import requests\n",
    "from bs4 import BeautifulSoup\n",
    "import pandas as pd\n",
    "from datetime import datetime, timedelta\n",
    "import json\n",
    "\n",
    "# ============================================================================\n",
    "# 1. FOREX FACTORY CALENDAR API (Web Scraping - No official API)\n",
    "# ============================================================================\n",
    "\n",
    "def fetch_forexfactory_news():\n",
    "    \"\"\"\n",
    "    Fetch economic calendar from Forex Factory\n",
    "    Note: Forex Factory doesn't have an official API, so we scrape the website\n",
    "    \"\"\"\n",
    "    print(\"\\n\" + \"=\"*100)\n",
    "    print(\"FOREX FACTORY ECONOMIC CALENDAR\")\n",
    "    print(\"=\"*100)\n",
    "    \n",
    "    try:\n",
    "        url = \"https://www.forexfactory.com/calendar\"\n",
    "        headers = {\n",
    "            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'\n",
    "        }\n",
    "        \n",
    "        response = requests.get(url, headers=headers, timeout=10)\n",
    "        response.raise_for_status()\n",
    "        \n",
    "        soup = BeautifulSoup(response.content, 'html.parser')\n",
    "        \n",
    "        # Find calendar table\n",
    "        calendar_rows = soup.find_all('tr', class_='calendar__row')\n",
    "        \n",
    "        events = []\n",
    "        current_date = None\n",
    "        \n",
    "        for row in calendar_rows:\n",
    "            # Get date if available\n",
    "            date_cell = row.find('td', class_='calendar__cell calendar__date')\n",
    "            if date_cell and date_cell.text.strip():\n",
    "                current_date = date_cell.text.strip()\n",
    "            \n",
    "            # Get time\n",
    "            time_cell = row.find('td', class_='calendar__cell calendar__time')\n",
    "            time_str = time_cell.text.strip() if time_cell else ''\n",
    "            \n",
    "            # Get currency\n",
    "            currency_cell = row.find('td', class_='calendar__cell calendar__currency')\n",
    "            currency = currency_cell.text.strip() if currency_cell else ''\n",
    "            \n",
    "            # Get impact (importance)\n",
    "            impact_cell = row.find('td', class_='calendar__cell calendar__impact')\n",
    "            impact_span = impact_cell.find('span') if impact_cell else None\n",
    "            impact = ''\n",
    "            if impact_span:\n",
    "                if 'icon--ff-impact-red' in impact_span.get('class', []):\n",
    "                    impact = 'High'\n",
    "                elif 'icon--ff-impact-ora' in impact_span.get('class', []):\n",
    "                    impact = 'Medium'\n",
    "                elif 'icon--ff-impact-yel' in impact_span.get('class', []):\n",
    "                    impact = 'Low'\n",
    "            \n",
    "            # Get event name\n",
    "            event_cell = row.find('td', class_='calendar__cell calendar__event')\n",
    "            event_name = event_cell.text.strip() if event_cell else ''\n",
    "            \n",
    "            # Get actual, forecast, previous values\n",
    "            actual_cell = row.find('td', class_='calendar__cell calendar__actual')\n",
    "            actual = actual_cell.text.strip() if actual_cell else ''\n",
    "            \n",
    "            forecast_cell = row.find('td', class_='calendar__cell calendar__forecast')\n",
    "            forecast = forecast_cell.text.strip() if forecast_cell else ''\n",
    "            \n",
    "            previous_cell = row.find('td', class_='calendar__cell calendar__previous')\n",
    "            previous = previous_cell.text.strip() if previous_cell else ''\n",
    "            \n",
    "            if event_name:\n",
    "                events.append({\n",
    "                    'Date': current_date,\n",
    "                    'Time': time_str,\n",
    "                    'Currency': currency,\n",
    "                    'Impact': impact,\n",
    "                    'Event': event_name,\n",
    "                    'Actual': actual,\n",
    "                    'Forecast': forecast,\n",
    "                    'Previous': previous\n",
    "                })\n",
    "        \n",
    "        if events:\n",
    "            df = pd.DataFrame(events)\n",
    "            print(f\"\\nFetched {len(events)} events from Forex Factory\")\n",
    "            print(df.to_string(index=False))\n",
    "            return df\n",
    "        else:\n",
    "            print(\"No events found\")\n",
    "            return None\n",
    "            \n",
    "    except Exception as e:\n",
    "        print(f\"Error fetching Forex Factory data: {e}\")\n",
    "        return None\n",
    "\n",
    "# ============================================================================\n",
    "# 2. INVESTING.COM ECONOMIC CALENDAR (Web Scraping)\n",
    "# ============================================================================\n",
    "\n",
    "def fetch_investing_com_news():\n",
    "    \"\"\"\n",
    "    Fetch economic calendar from Investing.com\n",
    "    Note: Requires web scraping as API access is restricted\n",
    "    \"\"\"\n",
    "    print(\"\\n\" + \"=\"*100)\n",
    "    print(\"INVESTING.COM ECONOMIC CALENDAR\")\n",
    "    print(\"=\"*100)\n",
    "    \n",
    "    try:\n",
    "        url = \"https://www.investing.com/economic-calendar/\"\n",
    "        headers = {\n",
    "            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'\n",
    "        }\n",
    "        \n",
    "        response = requests.get(url, headers=headers, timeout=10)\n",
    "        response.raise_for_status()\n",
    "        \n",
    "        soup = BeautifulSoup(response.content, 'html.parser')\n",
    "        \n",
    "        # Find economic calendar events\n",
    "        events = []\n",
    "        \n",
    "        # Look for calendar table/rows (structure may vary)\n",
    "        table = soup.find('table', {'id': 'economicCalendarData'})\n",
    "        \n",
    "        if table:\n",
    "            rows = table.find_all('tr', class_='js-event-item')\n",
    "            \n",
    "            for row in rows:\n",
    "                time_cell = row.find('td', class_='time')\n",
    "                currency_cell = row.find('td', class_='flagCur')\n",
    "                event_cell = row.find('td', class_='event')\n",
    "                actual_cell = row.find('td', {'id': lambda x: x and 'eventActual' in x})\n",
    "                forecast_cell = row.find('td', {'id': lambda x: x and 'eventForecast' in x})\n",
    "                previous_cell = row.find('td', {'id': lambda x: x and 'eventPrevious' in x})\n",
    "                \n",
    "                # Get importance (bull icons)\n",
    "                importance_cell = row.find('td', class_='sentiment')\n",
    "                importance = 'Low'\n",
    "                if importance_cell:\n",
    "                    bulls = len(importance_cell.find_all('i', class_='grayFullBullishIcon'))\n",
    "                    if bulls == 3:\n",
    "                        importance = 'High'\n",
    "                    elif bulls == 2:\n",
    "                        importance = 'Medium'\n",
    "                \n",
    "                events.append({\n",
    "                    'Time': time_cell.text.strip() if time_cell else '',\n",
    "                    'Currency': currency_cell.text.strip() if currency_cell else '',\n",
    "                    'Importance': importance,\n",
    "                    'Event': event_cell.text.strip() if event_cell else '',\n",
    "                    'Actual': actual_cell.text.strip() if actual_cell else '',\n",
    "                    'Forecast': forecast_cell.text.strip() if forecast_cell else '',\n",
    "                    'Previous': previous_cell.text.strip() if previous_cell else ''\n",
    "                })\n",
    "        \n",
    "        if events:\n",
    "            df = pd.DataFrame(events)\n",
    "            print(f\"\\nFetched {len(events)} events from Investing.com\")\n",
    "            print(df.to_string(index=False))\n",
    "            return df\n",
    "        else:\n",
    "            print(\"No events found or structure changed\")\n",
    "            return None\n",
    "            \n",
    "    except Exception as e:\n",
    "        print(f\"Error fetching Investing.com data: {e}\")\n",
    "        return None\n",
    "\n",
    "# ============================================================================\n",
    "# 3. TRADING ECONOMICS API (Requires API Key)\n",
    "# ============================================================================\n",
    "\n",
    "def fetch_trading_economics_news(api_key=None):\n",
    "    \"\"\"\n",
    "    Fetch economic calendar from Trading Economics API\n",
    "    Get free API key at: https://tradingeconomics.com/api/\n",
    "    \"\"\"\n",
    "    print(\"\\n\" + \"=\"*100)\n",
    "    print(\"TRADING ECONOMICS API\")\n",
    "    print(\"=\"*100)\n",
    "    \n",
    "    if not api_key:\n",
    "        print(\"\\nAPI Key required!\")\n",
    "        print(\"Get your free API key at: https://tradingeconomics.com/api/\")\n",
    "        print(\"Then call: fetch_trading_economics_news(api_key='YOUR_KEY')\")\n",
    "        return None\n",
    "    \n",
    "    try:\n",
    "        # Get today's calendar\n",
    "        today = datetime.now().strftime('%Y-%m-%d')\n",
    "        url = f\"https://api.tradingeconomics.com/calendar/country/all/{today}\"\n",
    "        \n",
    "        params = {\n",
    "            'c': api_key,\n",
    "            'f': 'json'\n",
    "        }\n",
    "        \n",
    "        response = requests.get(url, params=params, timeout=10)\n",
    "        response.raise_for_status()\n",
    "        \n",
    "        data = response.json()\n",
    "        \n",
    "        if data:\n",
    "            events = []\n",
    "            for item in data:\n",
    "                events.append({\n",
    "                    'Date': item.get('Date'),\n",
    "                    'Country': item.get('Country'),\n",
    "                    'Category': item.get('Category'),\n",
    "                    'Event': item.get('Event'),\n",
    "                    'Importance': item.get('Importance', 'N/A'),\n",
    "                    'Actual': item.get('Actual'),\n",
    "                    'Forecast': item.get('Forecast'),\n",
    "                    'Previous': item.get('Previous'),\n",
    "                    'Currency': item.get('Currency')\n",
    "                })\n",
    "            \n",
    "            df = pd.DataFrame(events)\n",
    "            print(f\"\\nFetched {len(events)} events from Trading Economics\")\n",
    "            print(df.to_string(index=False))\n",
    "            return df\n",
    "        else:\n",
    "            print(\"No events found\")\n",
    "            return None\n",
    "            \n",
    "    except Exception as e:\n",
    "        print(f\"Error fetching Trading Economics data: {e}\")\n",
    "        return None\n",
    "\n",
    "# ============================================================================\n",
    "# 4. NEWSAPI.ORG (General News - Requires API Key)\n",
    "# ============================================================================\n",
    "\n",
    "def fetch_newsapi_org(api_key=None, query='forex OR economy OR trading', days_back=1):\n",
    "    \"\"\"\n",
    "    Fetch general news from NewsAPI.org\n",
    "    Get free API key at: https://newsapi.org/\n",
    "    \"\"\"\n",
    "    print(\"\\n\" + \"=\"*100)\n",
    "    print(\"NEWSAPI.ORG - FINANCIAL NEWS\")\n",
    "    print(\"=\"*100)\n",
    "    \n",
    "    if not api_key:\n",
    "        print(\"\\nAPI Key required!\")\n",
    "        print(\"Get your free API key at: https://newsapi.org/\")\n",
    "        print(\"Then call: fetch_newsapi_org(api_key='YOUR_KEY')\")\n",
    "        return None\n",
    "    \n",
    "    try:\n",
    "        # Calculate date range\n",
    "        from_date = (datetime.now() - timedelta(days=days_back)).strftime('%Y-%m-%d')\n",
    "        \n",
    "        url = \"https://newsapi.org/v2/everything\"\n",
    "        \n",
    "        params = {\n",
    "            'apiKey': api_key,\n",
    "            'q': query,\n",
    "            'from': from_date,\n",
    "            'sortBy': 'publishedAt',\n",
    "            'language': 'en',\n",
    "            'pageSize': 100\n",
    "        }\n",
    "        \n",
    "        response = requests.get(url, params=params, timeout=10)\n",
    "        response.raise_for_status()\n",
    "        \n",
    "        data = response.json()\n",
    "        \n",
    "        if data.get('status') == 'ok' and data.get('articles'):\n",
    "            articles = data['articles']\n",
    "            \n",
    "            news_list = []\n",
    "            for article in articles:\n",
    "                news_list.append({\n",
    "                    'Published': article.get('publishedAt'),\n",
    "                    'Source': article.get('source', {}).get('name'),\n",
    "                    'Title': article.get('title'),\n",
    "                    'Description': article.get('description'),\n",
    "                    'URL': article.get('url')\n",
    "                })\n",
    "            \n",
    "            df = pd.DataFrame(news_list)\n",
    "            print(f\"\\nFetched {len(news_list)} news articles\")\n",
    "            print(df[['Published', 'Source', 'Title']].to_string(index=False))\n",
    "            return df\n",
    "        else:\n",
    "            print(f\"No articles found or error: {data.get('message', 'Unknown error')}\")\n",
    "            return None\n",
    "            \n",
    "    except Exception as e:\n",
    "        print(f\"Error fetching NewsAPI data: {e}\")\n",
    "        return None\n",
    "\n",
    "# ============================================================================\n",
    "# MAIN FUNCTION - FETCH FROM ALL SOURCES\n",
    "# ============================================================================\n",
    "\n",
    "def fetch_all_news(trading_economics_key=None, newsapi_key=None):\n",
    "    \"\"\"\n",
    "    Fetch news from all available sources\n",
    "    \"\"\"\n",
    "    print(\"\\n\" + \"=\"*100)\n",
    "    print(\"FETCHING NEWS FROM ALL SOURCES\")\n",
    "    print(\"=\"*100)\n",
    "    \n",
    "    results = {}\n",
    "    \n",
    "    # 1. Forex Factory (free, no API key needed)\n",
    "    print(\"\\n[1/4] Fetching from Forex Factory...\")\n",
    "    results['forexfactory'] = fetch_forexfactory_news()\n",
    "    \n",
    "    # 2. Investing.com (free, no API key needed)\n",
    "    print(\"\\n[2/4] Fetching from Investing.com...\")\n",
    "    results['investing'] = fetch_investing_com_news()\n",
    "    \n",
    "    # 3. Trading Economics (requires API key)\n",
    "    print(\"\\n[3/4] Fetching from Trading Economics...\")\n",
    "    results['trading_economics'] = fetch_trading_economics_news(trading_economics_key)\n",
    "    \n",
    "    # 4. NewsAPI.org (requires API key)\n",
    "    print(\"\\n[4/4] Fetching from NewsAPI.org...\")\n",
    "    results['newsapi'] = fetch_newsapi_org(newsapi_key)\n",
    "    \n",
    "    print(\"\\n\" + \"=\"*100)\n",
    "    print(\"SUMMARY\")\n",
    "    print(\"=\"*100)\n",
    "    for source, data in results.items():\n",
    "        if data is not None:\n",
    "            print(f\"✓ {source}: {len(data)} items fetched\")\n",
    "        else:\n",
    "            print(f\"✗ {source}: Failed or requires API key\")\n",
    "    \n",
    "    return results\n",
    "\n",
    "# ============================================================================\n",
    "# USAGE EXAMPLES\n",
    "# ============================================================================\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    print(\"\"\"\n",
    "    ╔═══════════════════════════════════════════════════════════════════════╗\n",
    "    ║                    MULTI-SOURCE NEWS FETCHER                          ║\n",
    "    ║                    For Trading & Economic News                        ║\n",
    "    ╚═══════════════════════════════════════════════════════════════════════╝\n",
    "    \n",
    "    REQUIRED PACKAGES:\n",
    "    pip install requests beautifulsoup4 pandas\n",
    "    \n",
    "    API KEYS (Optional but recommended):\n",
    "    1. Trading Economics: https://tradingeconomics.com/api/\n",
    "    2. NewsAPI.org: https://newsapi.org/\n",
    "    \n",
    "    \"\"\")\n",
    "    \n",
    "    # Option 1: Fetch from all sources (free sources only)\n",
    "    print(\"\\n>>> Fetching from free sources (Forex Factory & Investing.com)...\\n\")\n",
    "    results = fetch_all_news()\n",
    "    \n",
    "    # Option 2: Fetch with API keys (uncomment and add your keys)\n",
    "    # results = fetch_all_news(\n",
    "    #     trading_economics_key='YOUR_TRADING_ECONOMICS_KEY',\n",
    "    #     newsapi_key='YOUR_NEWSAPI_KEY'\n",
    "    # )\n",
    "    \n",
    "    # Option 3: Fetch from individual sources\n",
    "    # df_ff = fetch_forexfactory_news()\n",
    "    # df_inv = fetch_investing_com_news()\n",
    "    # df_te = fetch_trading_economics_news('YOUR_KEY')\n",
    "    # df_news = fetch_newsapi_org('YOUR_KEY')"
   ]
  },
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