Import python venv for stability

2026-02-15 21:24:16 -08:00
parent 1343e93a59
commit 7d784705c9
4997 changed files with 1628270 additions and 0 deletions
@@ -0,0 +1,153 @@
+from __future__ import print_function
+
+import pandas as _pd
+from typing import Dict, Optional
+
+from .. import utils
+from ..config import YfConfig
+from ..data import YfData
+
+from .domain import Domain, _QUERY_URL_
+
+class Industry(Domain):
+    """
+    Represents an industry within a sector.
+    """
+
+    def __init__(self, key, session=None):
+        """
+        Args:
+            key (str): The key identifier for the industry.
+            session (optional): The session to use for requests.
+        """
+        YfData(session=session)
+        super(Industry, self).__init__(key, session)
+        self._query_url = f'{_QUERY_URL_}/industries/{self._key}'
+
+        self._sector_key = None
+        self._sector_name = None
+        self._top_performing_companies = None
+        self._top_growth_companies = None
+
+    def __repr__(self):
+        """
+        Returns a string representation of the Industry instance.
+        
+        Returns:
+            str: String representation of the Industry instance.
+        """
+        return f'yfinance.Industry object <{self._key}>'
+    
+    @property
+    def sector_key(self) -> str:
+        """
+        Returns the sector key of the industry.
+        
+        Returns:
+            str: The sector key.
+        """
+        self._ensure_fetched(self._sector_key)
+        return self._sector_key
+    
+    @property
+    def sector_name(self) -> str:
+        """
+        Returns the sector name of the industry.
+        
+        Returns:
+            str: The sector name.
+        """
+        self._ensure_fetched(self._sector_name)
+        return self._sector_name
+    
+    @property
+    def top_performing_companies(self) -> Optional[_pd.DataFrame]:
+        """
+        Returns the top performing companies in the industry.
+        
+        Returns:
+            Optional[pd.DataFrame]: DataFrame containing top performing companies.
+        """
+        self._ensure_fetched(self._top_performing_companies)
+        return self._top_performing_companies
+    
+    @property
+    def top_growth_companies(self) -> Optional[_pd.DataFrame]:
+        """
+        Returns the top growth companies in the industry.
+        
+        Returns:
+            Optional[pd.DataFrame]: DataFrame containing top growth companies.
+        """
+        self._ensure_fetched(self._top_growth_companies)
+        return self._top_growth_companies
+    
+    def _parse_top_performing_companies(self, top_performing_companies: Dict) -> Optional[_pd.DataFrame]:
+        """
+        Parses the top performing companies data.
+        
+        Args:
+            top_performing_companies (Dict): Dictionary containing top performing companies data.
+        
+        Returns:
+            Optional[pd.DataFrame]: DataFrame containing parsed top performing companies data.
+        """
+        compnaies_column = ['symbol','name','ytd return','last price','target price']
+        compnaies_values = [(c.get('symbol', None),
+                             c.get('name', None),
+                             c.get('ytdReturn',{}).get('raw', None),
+                             c.get('lastPrice',{}).get('raw', None),
+                             c.get('targetPrice',{}).get('raw', None),) for c in top_performing_companies]
+        
+        if not compnaies_values: 
+            return None
+
+        return _pd.DataFrame(compnaies_values, columns = compnaies_column).set_index('symbol')
+    
+    def _parse_top_growth_companies(self, top_growth_companies: Dict) -> Optional[_pd.DataFrame]:
+        """
+        Parses the top growth companies data.
+        
+        Args:
+            top_growth_companies (Dict): Dictionary containing top growth companies data.
+        
+        Returns:
+            Optional[pd.DataFrame]: DataFrame containing parsed top growth companies data.
+        """
+        compnaies_column = ['symbol','name','ytd return','growth estimate']
+        compnaies_values = [(c.get('symbol', None),
+                             c.get('name', None),
+                             c.get('ytdReturn',{}).get('raw', None),
+                             c.get('growthEstimate',{}).get('raw', None),) for c in top_growth_companies]
+        
+        if not compnaies_values: 
+            return None
+
+        return _pd.DataFrame(compnaies_values, columns = compnaies_column).set_index('symbol')
+
+    def _fetch_and_parse(self) -> None:
+        """
+        Fetches and parses the industry data.
+        """
+        result = None
+        
+        try:
+            result = self._fetch(self._query_url)
+            data = result['data']
+            self._parse_and_assign_common(data)
+
+            self._sector_key = data.get('sectorKey')
+            self._sector_name = data.get('sectorName')
+            self._top_performing_companies = self._parse_top_performing_companies(data.get('topPerformingCompanies'))
+            self._top_growth_companies = self._parse_top_growth_companies(data.get('topGrowthCompanies'))
+
+            return result
+        except Exception as e:
+            if not YfConfig.debug.hide_exceptions:
+                raise
+            logger = utils.get_yf_logger()
+            logger.error(f"Failed to get industry data for '{self._key}' reason: {e}")
+            logger.debug("Got response: ")
+            logger.debug("-------------")
+            logger.debug(f" {result}")
+            logger.debug("-------------")