diff --git a/README.md b/README.md index 795a939..417088b 100644 --- a/README.md +++ b/README.md @@ -1,19 +1,25 @@ # 💹 justETF Scraping -Scrape the [justETF](https://www.justetf.com). +Scrape the [justETF](https://www.justetf.com) - Fork optimize for [LibreFolio](https://github.com/Alfystar/LibreFolio) code. ## 🛠️ Installation To use justETF scraping package in your project, install the actual version from GitHub: ```shell -pip install git+https://github.com/druzsan/justetf-scraping.git +pip install git+https://github.com/Alfystar/justetf-scraping.git +``` + +If you are using pipenv: + +```shell +pipenv install git+https://github.com/Alfystar/justetf-scraping.git ``` If you are going to play [notebooks](./notebooks) through, use the following installation: ```shell -pip install justetf-scraping[all]@git+https://github.com/druzsan/justetf-scraping.git +pip install justetf-scraping[all]@git+https://github.com/Alfystar/justetf-scraping.git ``` ## 🚀 Usage @@ -371,6 +377,17 @@ df = justetf_scraping.load_overview(strategy="epg-longOnly", index="MSCI World") ### 📈 Scrape ETF Chart Data from justETF ([e.g.](https://www.justetf.com/en/etf-profile.html?isin=IE00B0M62Q58#chart)) +#### Get raw chart data with `query_chart` + +Get the raw JSON response from justETF API: + +```python +data = justetf_scraping.query_chart("IE00B0M62Q58") +# Returns dict with: latestQuote, latestQuoteDate, price, performance, series, etc. +``` + +#### Load and process chart data with `load_chart` + Load the whole history of a chosen ETF by its ISIN: ```python @@ -378,6 +395,12 @@ df = justetf_scraping.load_chart("IE00B0M62Q58") df ``` +You can also include the current day's value in the response (useful for up-to-date data): + +```python +df = justetf_scraping.load_chart("IE00B0M62Q58", addCurrentValue=True) +``` + @@ -549,9 +572,9 @@ df = justetf_scraping.compare_charts( { "IE00B0M62Q58": justetf_scraping.load_chart("IE00B0M62Q58"), "IE00B0M63177": justetf_scraping.load_chart("IE00B0M63177"), - }, + }, input_value="quote_with_dividends" -) + ) df ``` @@ -628,6 +651,81 @@ df

7057 rows × 2 columns

+### 🔍 Scrape ETF Profile Data (NEW!) + +Get comprehensive ETF profile data including description, holdings allocation by country and sector, and real-time quotes from gettex. + +#### Get complete ETF overview with `get_etf_overview` + +```python +overview = justetf_scraping.get_etf_overview("IE00B3RBWM25") + +# Access basic info +print(f"Name: {overview['name']}") +print(f"TER: {overview['ter']}%") +print(f"Fund Size: EUR {overview['fund_size_eur']}m") +print(f"Description: {overview['description']}") + +# Access country allocation (full list, not truncated) +for country in overview['countries']: + print(f" {country['name']}: {country['percentage']}%") + +# Access sector allocation (full list) +for sector in overview['sectors']: + print(f" {sector['name']}: {sector['percentage']}%") + +# Access top 10 holdings with their ISINs +for holding in overview['top_holdings']: + print(f" {holding['name']} ({holding['isin']}): {holding['percentage']}%") + +# Access real-time gettex quote +quote = overview['gettex'] +print(f"Bid: {quote['bid']} {quote['currency']}") +print(f"Ask: {quote['ask']} {quote['currency']}") +print(f"Day Change: {quote['day_change_percent']}%") +``` + +The `get_etf_overview` function returns a dictionary with: + +| Field | Type | Description | +|-----------------------|-------|----------------------------------| +| `isin` | str | ISIN code | +| `name` | str | ETF name | +| `description` | str | Short description | +| `index` | str | Tracked index | +| `ter` | float | Total Expense Ratio (e.g., 0.19) | +| `fund_size_eur` | float | Fund size in EUR millions | +| `replication` | str | Replication method | +| `fund_currency` | str | Fund currency | +| `distribution_policy` | str | Distributing/Accumulating | +| `inception_date` | str | Launch date | +| `fund_domicile` | str | Country of domicile | +| `countries` | list | Full country allocation | +| `sectors` | list | Full sector allocation | +| `top_holdings` | list | Top 10 holdings with ISINs | +| `gettex` | dict | Real-time quote data | + +#### Get real-time gettex quote only with `get_gettex_quote` + +```python +quote = justetf_scraping.get_gettex_quote("IE00B3RBWM25") + +print(f"Bid: {quote['bid']} EUR") +print(f"Ask: {quote['ask']} EUR") +print(f"Spread: {quote['spread_percent']}%") +print(f"Day Change: {quote['day_change_percent']}%") +print(f"Timestamp: {quote['timestamp']}") # datetime object +``` + +#### Get raw gettex data with `get_gettex_quote_raw` + +```python +raw_data = justetf_scraping.get_gettex_quote_raw("IE00B3RBWM25") +# Returns the raw JSON response from the WebSocket +``` + +For a complete example, see [test_scrape.py](notebooks/test_scrape.py) + For further exploration examples, see [Jupyter Notebooks](notebooks/) ## ⚒️ Development Setup diff --git a/justetf_scraping/__init__.py b/justetf_scraping/__init__.py index cd09722..54f9045 100644 --- a/justetf_scraping/__init__.py +++ b/justetf_scraping/__init__.py @@ -1,8 +1,21 @@ """ Scrape the [justETF](https://www.justetf.com). """ -from .charts import load_chart, compare_charts +from .charts import load_chart, compare_charts, query_chart from .overview import load_overview +from .etf_profile import ( + get_etf_overview, + get_gettex_quote, + get_gettex_quote_raw, +) -__all__ = ["load_chart", "compare_charts", "load_overview"] +__all__ = [ + "query_chart", + "load_chart", + "compare_charts", + "load_overview", + "get_etf_overview", + "get_gettex_quote", + "get_gettex_quote_raw", +] diff --git a/justetf_scraping/charts.py b/justetf_scraping/charts.py index 8036f22..4dbc06e 100644 --- a/justetf_scraping/charts.py +++ b/justetf_scraping/charts.py @@ -18,7 +18,7 @@ "reduceData": "false", "includeDividends": "false", "features": "DIVIDENDS", -} + } def parse_series(raw_series: Dict, value_name: str = "value") -> pd.DataFrame: @@ -37,7 +37,56 @@ def relative(series: pd.Series) -> pd.Series: return 100 * (series / series.iloc[0] - 1) -def load_chart(isin: str, currency: Currency = "EUR") -> pd.DataFrame: +def query_chart(isin: str, currency: Currency = "EUR") -> dict: + """ + :param isin: + :param currency: + :return: dictionary with this structure: +{ + "latestQuote": { + "raw": 9.94, "localized": "9.94" + }, + "latestQuoteDate": "2025-12-16", + "price": { + "raw": 9.96, "localized": "9.96" + }, + "performance": { + "raw": 3.86, "localized": "3.86" + }, + "prevDaySeries": [], + "series": [ + { + "date": "2025-11-15", + "value": { + "raw": 9.59, "localized": "9.59" + } + }, + { + "date": "2025-12-15", + "value": { + "raw": 9.96, "localized": "9.96" + } + } + ], + "latestDate": "2025-12-15", + "endOfDay": "2025-12-16T21:00:00Z", + "features": { + "DIVIDENDS": [] + } +} + """ + url = BASE_URL.format(isin=isin) + response = requests.get( + url, + params={**BASE_PARAMS, "currency": currency}, + headers={"User-Agent": USER_AGENT}, + ) + assert_response_status_ok(response, "chart") + data = response.json() + return data + + +def load_chart(isin: str, currency: Currency = "EUR", addCurrentValue: bool = False) -> pd.DataFrame: """ Get and enrich an ETF chart for the whole time period. @@ -70,14 +119,7 @@ def load_chart(isin: str, currency: Currency = "EUR") -> pd.DataFrame: payed out until the given date if they were reinvested immediately. """ - url = BASE_URL.format(isin=isin) - response = requests.get( - url, - params={**BASE_PARAMS, "currency": currency}, - headers={"User-Agent": USER_AGENT}, - ) - assert_response_status_ok(response, "chart") - data = response.json() + data = query_chart(isin, currency) df = parse_series(data["series"], "quote") df["relative"] = relative(df["quote"]) @@ -90,26 +132,40 @@ def load_chart(isin: str, currency: Currency = "EUR") -> pd.DataFrame: df["relative_with_dividends"] = relative(df["quote_with_dividends"]) df["reinvested_dividends"] = 0 for index, row in dividends_df.iterrows(): - df["reinvested_dividends"] += ( - df["quote"] * row["dividends"] / df.at[index, "quote"] - ).mask(df.index < index, 0) + df["reinvested_dividends"] += (df["quote"] * row["dividends"] / df.at[index, "quote"]).mask(df.index < index, 0) df["quote_with_reinvested_dividends"] = df["quote"] + df["reinvested_dividends"] - df["relative_with_reinvested_dividends"] = relative( - df["quote_with_reinvested_dividends"] - ) + df["relative_with_reinvested_dividends"] = relative(df["quote_with_reinvested_dividends"]) + if addCurrentValue: + latestQuoteDate = data["latestQuoteDate"] + latestQuote = data["latestQuote"]["raw"] + if latestQuoteDate not in df.index: + first_quote = df["quote"].iloc[0] + first_quote_with_dividends = df["quote_with_dividends"].iloc[0] + first_quote_with_reinvested = df["quote_with_reinvested_dividends"].iloc[0] + new_row = pd.DataFrame({ + "quote": [latestQuote], + "relative": [100 * (latestQuote / first_quote - 1)], + "dividends": [0], + "cumulative_dividends": [0], + "quote_with_dividends": [latestQuote], + "relative_with_dividends": [100 * (latestQuote / first_quote_with_dividends - 1)], + "reinvested_dividends": [0], + "quote_with_reinvested_dividends": [latestQuote], + "relative_with_reinvested_dividends": [100 * (latestQuote / first_quote_with_reinvested - 1)] + }, index=[pd.to_datetime(latestQuoteDate)]) + df = pd.concat([df, new_row]) df.index.name = "date" return df +# TODO: add Metadata extraction like countries or Sectors def compare_charts( - charts: Dict[str, pd.DataFrame], - dates: Literal["shortest", "longest"] = "shortest", - input_value: Literal[ - "quote", "quote_with_dividends", "quote_with_reinvested_dividends" - ] = "quote_with_dividends", - output_value: Literal["absolute", "relative", "percentage"] = "percentage", -) -> pd.DataFrame: + charts: Dict[str, pd.DataFrame], + dates: Literal["shortest", "longest"] = "shortest", + input_value: Literal["quote", "quote_with_dividends", "quote_with_reinvested_dividends"] = "quote_with_dividends", + output_value: Literal["absolute", "relative", "percentage"] = "percentage", + ) -> pd.DataFrame: longest_chart = max(charts.values(), key=len) charts_df = pd.DataFrame(index=longest_chart.index) for isin, chart in charts.items(): @@ -123,7 +179,7 @@ def compare_charts( raise ValueError( f"`dates` argument must be one of 'shortest' or 'longest', but " f"value '{dates}' received." - ) + ) if output_value == "absolute": return charts_df @@ -134,4 +190,4 @@ def compare_charts( raise ValueError( f"`output_value` argument must be one of 'absolute', 'relative' or " f"'percentage', but value '{output_value}' received." - ) + ) diff --git a/justetf_scraping/etf_profile.py b/justetf_scraping/etf_profile.py new file mode 100644 index 0000000..79f2321 --- /dev/null +++ b/justetf_scraping/etf_profile.py @@ -0,0 +1,457 @@ +""" +Scrape ETF profile data from justETF (https://www.justetf.com/en/etf-profile.html). + +This module provides functions to: +1. Get real-time gettex quote data via WebSocket +2. Get ETF overview including description, basic data, countries, and sectors +""" + +import json +import re +from datetime import datetime +from typing import Any, Dict, List, Optional, TypedDict +from xml.etree import ElementTree + +import requests +from bs4 import BeautifulSoup +from websocket import create_connection + +from .helpers import USER_AGENT + + +# Type definitions +class AllocationItem(TypedDict): + name: str + percentage: float + + +class HoldingItem(TypedDict): + name: str + percentage: float + isin: Optional[str] + + +class GettexQuote(TypedDict): + isin: str + timestamp: datetime + trend: str + ask: float + bid: float + mid: float + last: float + currency: str + day_change_decimal: float + day_change_percent: float + day_change_amount: float + spread_amount: float + spread_decimal: float + spread_percent: float + stock_exchange: str + quote_type: str + + +class EtfOverview(TypedDict): + isin: str + name: Optional[str] + description: Optional[str] + index: Optional[str] + investment_focus: Optional[str] + fund_size_eur: Optional[float] + ter: Optional[float] + replication: Optional[str] + legal_structure: Optional[str] + strategy_risk: Optional[str] + sustainability: Optional[bool] + fund_currency: Optional[str] + currency_hedged: Optional[bool] + volatility_1y: Optional[float] + inception_date: Optional[str] + distribution_policy: Optional[str] + distribution_frequency: Optional[str] + fund_domicile: Optional[str] + fund_provider: Optional[str] + top_holdings: List[HoldingItem] + countries: List[AllocationItem] + sectors: List[AllocationItem] + holdings_date: Optional[str] + gettex: Optional[GettexQuote] + + +# Constants +BASE_URL = "https://www.justetf.com/en/etf-profile.html" +WEBSOCKET_URL = "wss://api.mobile.stock-data-subscriptions.justetf.com" +DEFAULT_HEADERS = { + "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36" +} + + +def _parse_percentage(value: str) -> Optional[float]: + """Parse percentage string to float (e.g., '59.03%' -> 59.03).""" + if not value: + return None + match = re.search(r'([\d.]+)\s*%', value) + if match: + return float(match.group(1)) + return None + + +def _parse_fund_size(value: str) -> Optional[float]: + """Parse fund size string to float in millions (e.g., 'EUR 18,588 m' -> 18588.0).""" + if not value: + return None + match = re.search(r'([\d,]+)\s*m', value, re.I) + if match: + return float(match.group(1).replace(',', '')) + return None + + +def _parse_ter(value: str) -> Optional[float]: + """Parse TER string to float (e.g., '0.19% p.a.' -> 0.19).""" + return _parse_percentage(value) + + +def _parse_date(value: str) -> Optional[str]: + """Extract date from string (e.g., '22 May 2012' or 'As of 29/10/2025').""" + if not value: + return None + # Try to extract date pattern + value = value.replace('As of ', '').strip() + return value + + +def get_gettex_quote(isin: str, currency: str = "EUR", language: str = "en") -> Optional[GettexQuote]: + """ + Get real-time quote data from gettex via WebSocket. + + Args: + isin: The ISIN of the ETF + currency: Currency for the quote (default: EUR) + language: Language code (default: en) + + Returns: + GettexQuote dictionary with parsed numeric values, or None if failed + """ + url = f"{WEBSOCKET_URL}?subscription=trend¶meters=isins:{isin}/currency:{currency}/language:{language}" + ws_headers = { + "User-Agent": USER_AGENT, + "Origin": "https://www.justetf.com" + } + + try: + ws = create_connection(url, header=ws_headers, timeout=10) + result = ws.recv() + ws.close() + + if not result: + return None + + data = json.loads(result) + + # Parse and return cleaned data + return GettexQuote( + isin=data.get("isin", isin), + timestamp=datetime.fromisoformat(data["timestamp"].replace("Z", "+00:00")) if data.get("timestamp") else None, + trend=data.get("trend", ""), + ask=data.get("ask", {}).get("raw"), + bid=data.get("bid", {}).get("raw"), + mid=data.get("mid", {}).get("raw"), + last=data.get("last", {}).get("raw"), + currency=data.get("currency", currency), + day_change_decimal=data.get("dtdDec", {}).get("raw"), + day_change_percent=data.get("dtdPrc", {}).get("raw"), + day_change_amount=data.get("dtdAmt", {}).get("raw"), + spread_amount=data.get("spreadAmt", {}).get("raw"), + spread_decimal=data.get("spreadDec", {}).get("raw"), + spread_percent=data.get("spreadPrc", {}).get("raw"), + stock_exchange=data.get("stockExchange", "gettex"), + quote_type=data.get("quoteType", ""), + ) + except Exception as e: + print(f"WebSocket error for {isin}: {e}") + return None + + +def get_gettex_quote_raw(isin: str, currency: str = "EUR", language: str = "en") -> Optional[Dict[str, Any]]: + """ + Get raw real-time quote data from gettex via WebSocket. + + Args: + isin: The ISIN of the ETF + currency: Currency for the quote (default: EUR) + language: Language code (default: en) + + Returns: + Raw dictionary from WebSocket response, or None if failed + """ + url = f"{WEBSOCKET_URL}?subscription=trend¶meters=isins:{isin}/currency:{currency}/language:{language}" + ws_headers = { + "User-Agent": USER_AGENT, + "Origin": "https://www.justetf.com" + } + + try: + ws = create_connection(url, header=ws_headers, timeout=10) + result = ws.recv() + ws.close() + + if result: + return json.loads(result) + return None + except Exception as e: + print(f"WebSocket error for {isin}: {e}") + return None + + +def _fetch_ajax_data(session: requests.Session, isin: str, endpoint: str, element_id: str) -> Optional[str]: + """ + Fetch expanded data via AJAX request (for countries/sectors load more). + + Args: + session: requests Session with cookies from main page + isin: The ISIN of the ETF + endpoint: The AJAX endpoint path (e.g., 'holdingsSection-countries-loadMoreCountries') + element_id: The element ID for Wicket (e.g., 'id6') + + Returns: + HTML content from AJAX response, or None if failed + """ + ajax_url = f"{BASE_URL}?0-1.0-{endpoint}&isin={isin}&_wicket=1" + ajax_headers = { + **DEFAULT_HEADERS, + 'X-Requested-With': 'XMLHttpRequest', + 'Wicket-Ajax': 'true', + 'Wicket-Ajax-BaseURL': f'en/etf-profile.html?isin={isin}', + 'Accept': 'application/xml, text/xml, */*; q=0.01', + 'Referer': f'{BASE_URL}?isin={isin}', + } + + try: + resp = session.get(ajax_url, headers=ajax_headers) + if resp.status_code == 200 and resp.text: + return resp.text + except Exception as e: + print(f"AJAX request error: {e}") + + return None + + +def _parse_allocation_from_ajax(xml_response: str, table_id: str, name_testid: str, pct_testid: str) -> List[AllocationItem]: + """ + Parse allocation data (countries/sectors) from AJAX XML response. + + Args: + xml_response: XML response from AJAX call + table_id: ID of the table element (e.g., 'id47') + name_testid: data-testid for name element + pct_testid: data-testid for percentage element + + Returns: + List of AllocationItem dictionaries + """ + allocations = [] + + try: + # Parse XML and extract CDATA content for the table + root = ElementTree.fromstring(xml_response) + for component in root.findall('.//component'): + if component.get('id') == table_id: + html_content = component.text + if html_content: + soup = BeautifulSoup(html_content, 'html.parser') + rows = soup.find_all('tr', attrs={'data-testid': True}) + for row in rows: + name_elem = row.find('td', attrs={'data-testid': name_testid}) + pct_elem = row.find('span', attrs={'data-testid': pct_testid}) + if name_elem and pct_elem: + name = name_elem.get_text(strip=True) + pct = _parse_percentage(pct_elem.get_text(strip=True)) + if name and pct is not None: + allocations.append(AllocationItem(name=name, percentage=pct)) + break + except Exception as e: + print(f"Error parsing allocation data: {e}") + + return allocations + + +def _parse_allocation_from_soup(soup: BeautifulSoup, row_testid: str, name_testid: str, pct_testid: str) -> List[AllocationItem]: + """ + Parse allocation data from main page soup (fallback if AJAX fails). + """ + allocations = [] + rows = soup.find_all('tr', attrs={'data-testid': row_testid}) + for row in rows: + name_elem = row.find('td', attrs={'data-testid': name_testid}) + pct_elem = row.find('span', attrs={'data-testid': pct_testid}) + if name_elem and pct_elem: + name = name_elem.get_text(strip=True) + pct = _parse_percentage(pct_elem.get_text(strip=True)) + if name and pct is not None: + allocations.append(AllocationItem(name=name, percentage=pct)) + return allocations + + +def get_etf_overview(isin: str, include_gettex: bool = True, expand_allocations: bool = True) -> EtfOverview: + """ + Get comprehensive ETF overview data from justETF. + + Args: + isin: The ISIN of the ETF + include_gettex: Whether to fetch real-time gettex quote (default: True) + expand_allocations: Whether to fetch full countries/sectors lists via AJAX (default: True) + + Returns: + EtfOverview dictionary with all available data + """ + session = requests.Session() + + # Fetch main page + url = f"{BASE_URL}?isin={isin}" + response = session.get(url, headers=DEFAULT_HEADERS) + + if response.status_code != 200: + raise RuntimeError(f"Failed to fetch ETF page for {isin}: status {response.status_code}") + + soup = BeautifulSoup(response.text, 'html.parser') + + # Parse description + desc_elem = soup.find('div', attrs={'data-testid': 'etf-quote-section_description-label'}) + description = desc_elem.get_text(strip=True) if desc_elem else None + + # Parse name from title + title_elem = soup.find('title') + name = None + if title_elem: + title_text = title_elem.get_text(strip=True) + # Format: "ETF Name | WKN | ISIN" + if '|' in title_text: + name = title_text.split('|')[0].strip() + + # Parse basic data from table 2 + basic_data = {} + tables = soup.find_all('table') + if len(tables) >= 2: + table = tables[1] + rows = table.find_all('tr') + for row in rows: + cells = row.find_all(['th', 'td']) + if len(cells) >= 2: + key = cells[0].get_text(strip=True) + value = cells[1].get_text(strip=True) + basic_data[key] = value + + # Parse top 10 holdings + top_holdings = [] + holdings_rows = soup.find_all('tr', attrs={'data-testid': 'etf-holdings_top-holdings_row'}) + for row in holdings_rows: + name_elem = row.find('a', attrs={'data-testid': 'tl_etf-holdings_top-holdings_link_name'}) + pct_elem = row.find('span', attrs={'data-testid': 'tl_etf-holdings_top-holdings_value_percentage'}) + if name_elem and pct_elem: + holding_name = name_elem.get_text(strip=True) + pct = _parse_percentage(pct_elem.get_text(strip=True)) + # Try to extract ISIN from link + href = name_elem.get('href', '') + holding_isin = None + if '/stock-profiles/' in href: + holding_isin = href.split('/stock-profiles/')[-1] + if holding_name and pct is not None: + top_holdings.append(HoldingItem(name=holding_name, percentage=pct, isin=holding_isin)) + + # Parse countries + if expand_allocations: + # Try AJAX for full list + countries_xml = _fetch_ajax_data(session, isin, 'holdingsSection-countries-loadMoreCountries', 'id6') + if countries_xml: + countries = _parse_allocation_from_ajax( + countries_xml, 'id47', + 'tl_etf-holdings_countries_value_name', + 'tl_etf-holdings_countries_value_percentage' + ) + else: + countries = _parse_allocation_from_soup( + soup, 'etf-holdings_countries_row', + 'tl_etf-holdings_countries_value_name', + 'tl_etf-holdings_countries_value_percentage' + ) + else: + countries = _parse_allocation_from_soup( + soup, 'etf-holdings_countries_row', + 'tl_etf-holdings_countries_value_name', + 'tl_etf-holdings_countries_value_percentage' + ) + + # Parse sectors + if expand_allocations: + # Try AJAX for full list + sectors_xml = _fetch_ajax_data(session, isin, 'holdingsSection-sectors-loadMoreSectors', 'id7') + if sectors_xml: + sectors = _parse_allocation_from_ajax( + sectors_xml, 'id48', + 'tl_etf-holdings_sectors_value_name', + 'tl_etf-holdings_sectors_value_percentage' + ) + else: + sectors = _parse_allocation_from_soup( + soup, 'etf-holdings_sectors_row', + 'tl_etf-holdings_sectors_value_name', + 'tl_etf-holdings_sectors_value_percentage' + ) + else: + sectors = _parse_allocation_from_soup( + soup, 'etf-holdings_sectors_row', + 'tl_etf-holdings_sectors_value_name', + 'tl_etf-holdings_sectors_value_percentage' + ) + + # Parse holdings date + ref_date_elem = soup.find('div', attrs={'data-testid': 'tl_etf-holdings_reference-date'}) + holdings_date = _parse_date(ref_date_elem.get_text(strip=True)) if ref_date_elem else None + + # Get gettex quote + gettex = None + if include_gettex: + gettex = get_gettex_quote(isin) + + # Build result + return EtfOverview( + isin=isin, + name=name, + description=description, + index=basic_data.get('Index'), + investment_focus=basic_data.get('Investment focus'), + fund_size_eur=_parse_fund_size(basic_data.get('Fund size')), + ter=_parse_ter(basic_data.get('Total expense ratio')), + replication=basic_data.get('Replication'), + legal_structure=basic_data.get('Legal structure'), + strategy_risk=basic_data.get('Strategy risk'), + sustainability=basic_data.get('Sustainability', '').lower() == 'yes', + fund_currency=basic_data.get('Fund currency'), + currency_hedged=basic_data.get('Currency risk', '').lower() != 'currency unhedged', + volatility_1y=_parse_percentage(basic_data.get('Volatility 1 year (in EUR)')), + inception_date=basic_data.get('Inception/ Listing Date'), + distribution_policy=basic_data.get('Distribution policy'), + distribution_frequency=basic_data.get('Distribution frequency'), + fund_domicile=basic_data.get('Fund domicile'), + fund_provider=basic_data.get('Fund Provider'), + top_holdings=top_holdings, + countries=countries, + sectors=sectors, + holdings_date=holdings_date, + gettex=gettex, + ) + + +if __name__ == "__main__": + # Test with VGWL + import pprint + + isin = "IE00B3RBWM25" + print(f"Fetching ETF overview for {isin}...") + + overview = get_etf_overview(isin) + + print("\n" + "="*60) + print("ETF OVERVIEW") + print("="*60) + pprint.pprint(dict(overview), width=100) + diff --git a/justetf_scraping/overview.py b/justetf_scraping/overview.py index 121ad6d..ea62598 100644 --- a/justetf_scraping/overview.py +++ b/justetf_scraping/overview.py @@ -403,7 +403,7 @@ def load_overview( ) # Convert columns. for column in df.columns.intersection(BOOL_COLUMNS): - df[column] = df[column].replace({"Yes": True, "No": False}).astype("bool") + df[column] = df[column].map({"Yes": True, "No": False}).astype("bool") for column in df.columns.intersection(INT64_COLUMNS): if column in df: df[column] = df[column].astype("Int64") diff --git a/notebooks/test_scrape.py b/notebooks/test_scrape.py new file mode 100644 index 0000000..113a1d7 --- /dev/null +++ b/notebooks/test_scrape.py @@ -0,0 +1,38 @@ +#!/usr/bin/env python3 +"""Test script for the etf_profile module.""" + +from justetf_scraping import get_etf_overview, get_gettex_quote + +# Test get_etf_overview +isin = 'IE00B3RBWM25' +print(f"Fetching ETF overview for {isin}...") +overview = get_etf_overview(isin) + +print('\n' + '='*60) +print('=== ETF OVERVIEW ===') +print('='*60) +print(f'Name: {overview["name"]}') +print(f'ISIN: {overview["isin"]}') +print(f'TER: {overview["ter"]}%') +print(f'Fund Size: EUR {overview["fund_size_eur"]}m') +print(f'Description: {overview["description"][:100]}...') + +print(f'\n=== COUNTRIES ({len(overview["countries"])}) ===') +for c in overview['countries']: + print(f' {c["name"]}: {c["percentage"]}%') + +print(f'\n=== SECTORS ({len(overview["sectors"])}) ===') +for s in overview['sectors']: + print(f' {s["name"]}: {s["percentage"]}%') + +print(f'\n=== TOP HOLDINGS ({len(overview["top_holdings"])}) ===') +for h in overview['top_holdings'][:5]: + print(f' {h["name"]} ({h["isin"]}): {h["percentage"]}%') + +print(f'\n=== GETTEX QUOTE ===') +g = overview['gettex'] +if g: + print(f' Bid: {g["bid"]} {g["currency"]}') + print(f' Ask: {g["ask"]} {g["currency"]}') + print(f' Day Change: {g["day_change_percent"]}%') + print(f' Timestamp: {g["timestamp"]}') diff --git a/poetry.lock b/poetry.lock index 188406a..6c961f3 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,26 +1,25 @@ -# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand. 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= ["python-socks", "wsaccel"] +test = ["pytest", "websockets"] [extras] all = ["notebook", "seaborn"] exploration = ["notebook", "seaborn"] [metadata] -lock-version = "2.0" -python-versions = "^3.8" -content-hash = "adb21adcaa3adf5ee993db09ca1faacf399083daa719b538b43b1b30d9694ad9" +lock-version = "2.1" +python-versions = "^3.10" +content-hash = "04ed28c182b8621ae146d2e111a24702a99a6df4b5e13de182d50715324549bc" diff --git a/pyproject.toml b/pyproject.toml index df4d64c..d84e7dc 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,9 +8,11 @@ readme = "README.md" packages = [{include = "justetf_scraping"}] [tool.poetry.dependencies] -python = "^3.8" +python = "^3.10" requests = "*" pandas = ">=2.0.0" +beautifulsoup4 = "^4.12.0" +websocket-client = "^1.6.0" notebook = { version = ">=7.0.0", optional = true } seaborn = { version = "*", optional = true } pycountry = "^23.12.11"