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"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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|