implement client-side pending_date filtering for PENDING properties

- Fix PENDING properties to filter by pending_date instead of list_date
- Add client-side filtering for PENDING as server-side pending_date filter is broken
- Include contingent properties without pending_date for comprehensive results
- Enhance documentation to clarify past_days behavior per listing type
- Add property_history field to GraphQL queries for future enhancements
- Add comprehensive test for pending date filtering functionality
- Optimize filtering logic with helper methods for better maintainability

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
Zachary Hampton
2025-09-08 16:36:48 -07:00
parent 44e6a43cc4
commit 75c245cde7
5 changed files with 207 additions and 3 deletions

View File

@@ -137,6 +137,10 @@ class RealtorScraper(Scraper):
date_param = f'sold_date: {{ min: "{self.date_from}", max: "{self.date_to}" }}'
elif self.last_x_days:
date_param = f'sold_date: {{ min: "$today-{self.last_x_days}D" }}'
elif self.listing_type == ListingType.PENDING:
# Skip server-side date filtering for PENDING as both pending_date and contract_date
# filters are broken in the API. Client-side filtering will be applied later.
pass
else:
if self.date_from and self.date_to:
date_param = f'list_date: {{ min: "{self.date_from}", max: "{self.date_to}" }}'
@@ -378,8 +382,126 @@ class RealtorScraper(Scraper):
for future in as_completed(futures):
homes.extend(future.result()["properties"])
# Apply client-side date filtering for PENDING properties
# (server-side filters are broken in the API)
if self.listing_type == ListingType.PENDING and (self.last_x_days or self.date_from):
homes = self._apply_pending_date_filter(homes)
return homes
def _apply_pending_date_filter(self, homes):
"""Apply client-side date filtering for PENDING properties based on pending_date field.
For contingent properties without pending_date, tries fallback date fields."""
if not homes:
return homes
from datetime import datetime, timedelta
# Determine date range for filtering
date_range = self._get_date_range()
if not date_range:
return homes
filtered_homes = []
for home in homes:
# Extract the best available date for this property
property_date = self._extract_property_date_for_filtering(home)
# Handle properties without dates (include contingent properties)
if property_date is None:
if self._is_contingent(home):
filtered_homes.append(home) # Include contingent without date filter
continue
# Check if property date falls within the specified range
if self._is_date_in_range(property_date, date_range):
filtered_homes.append(home)
return filtered_homes
def _get_pending_date(self, home):
"""Extract pending_date from a home property (handles both dict and Property object)."""
if isinstance(home, dict):
return home.get('pending_date')
else:
# Assume it's a Property object
return getattr(home, 'pending_date', None)
def _is_contingent(self, home):
"""Check if a property is contingent."""
if isinstance(home, dict):
flags = home.get('flags', {})
return flags.get('is_contingent', False)
else:
# Property object - check flags attribute
if hasattr(home, 'flags') and home.flags:
return getattr(home.flags, 'is_contingent', False)
return False
def _get_date_range(self):
"""Get the date range for filtering based on instance parameters."""
from datetime import datetime, timedelta
if self.last_x_days:
cutoff_date = datetime.now() - timedelta(days=self.last_x_days)
return {'type': 'since', 'date': cutoff_date}
elif self.date_from and self.date_to:
try:
from_date = datetime.fromisoformat(self.date_from)
to_date = datetime.fromisoformat(self.date_to)
return {'type': 'range', 'from_date': from_date, 'to_date': to_date}
except ValueError:
return None
return None
def _extract_property_date_for_filtering(self, home):
"""Extract pending_date from a property for filtering.
Returns parsed datetime object or None.
"""
date_value = self._get_pending_date(home)
if date_value:
return self._parse_date_value(date_value)
return None
def _parse_date_value(self, date_value):
"""Parse a date value (string or datetime) into a timezone-naive datetime object."""
from datetime import datetime
if isinstance(date_value, datetime):
return date_value.replace(tzinfo=None)
if not isinstance(date_value, str):
return None
try:
# Handle timezone indicators
if date_value.endswith('Z'):
date_value = date_value[:-1] + '+00:00'
elif '.' in date_value and date_value.endswith('Z'):
date_value = date_value.replace('Z', '+00:00')
# Try ISO format first
try:
parsed_date = datetime.fromisoformat(date_value)
return parsed_date.replace(tzinfo=None)
except ValueError:
# Try simple datetime format: '2025-08-29 00:00:00'
return datetime.strptime(date_value, '%Y-%m-%d %H:%M:%S')
except (ValueError, AttributeError):
return None
def _is_date_in_range(self, date_obj, date_range):
"""Check if a datetime object falls within the specified date range."""
if date_range['type'] == 'since':
return date_obj >= date_range['date']
elif date_range['type'] == 'range':
return date_range['from_date'] <= date_obj <= date_range['to_date']
return False
@retry(

View File

@@ -202,6 +202,11 @@ fragment HomeData on Home {
}
}
taxHistory: tax_history { __typename tax year assessment { __typename building land total } }
property_history {
date
event_name
price
}
monthly_fees {
description
display_amount