mirror of
https://github.com/Bunsly/HomeHarvest.git
synced 2026-03-04 19:44:29 -08:00
Add pagination offset support for API queries
Implements offset parameter to enable pagination within the 10k API limit. Users can now fetch results in chunks (e.g., offset=200, limit=200 for results 200-399). Includes validation to ensure offset + limit doesn't exceed API maximum. Also fixes multi-page result sorting to preserve correct order across page boundaries. Fixes #139 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
@@ -278,7 +278,9 @@ Optional
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│
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│
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├── exclude_pending (True/False): If set, excludes 'pending' properties from the 'for_sale' results unless listing_type is 'pending'
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├── exclude_pending (True/False): If set, excludes 'pending' properties from the 'for_sale' results unless listing_type is 'pending'
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│
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│
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└── limit (integer): Limit the number of properties to fetch. Max & default is 10000.
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├── limit (integer): Limit the number of properties to fetch. Max & default is 10000.
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│
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└── offset (integer): Starting position for pagination within the 10k limit. Use with limit to fetch results in chunks.
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```
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```
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### Property Schema
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### Property Schema
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@@ -1,7 +1,7 @@
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import warnings
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import warnings
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import pandas as pd
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import pandas as pd
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from .core.scrapers import ScraperInput
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from .core.scrapers import ScraperInput
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from .utils import process_result, ordered_properties, validate_input, validate_dates, validate_limit, validate_datetime, validate_filters, validate_sort
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from .utils import process_result, ordered_properties, validate_input, validate_dates, validate_limit, validate_offset, validate_datetime, validate_filters, validate_sort
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from .core.scrapers.realtor import RealtorScraper
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from .core.scrapers.realtor import RealtorScraper
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from .core.scrapers.models import ListingType, SearchPropertyType, ReturnType, Property
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from .core.scrapers.models import ListingType, SearchPropertyType, ReturnType, Property
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from typing import Union, Optional, List
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from typing import Union, Optional, List
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@@ -21,6 +21,7 @@ def scrape_property(
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extra_property_data: bool = True,
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extra_property_data: bool = True,
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exclude_pending: bool = False,
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exclude_pending: bool = False,
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limit: int = 10000,
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limit: int = 10000,
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offset: int = 0,
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# New date/time filtering parameters
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# New date/time filtering parameters
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past_hours: int = None,
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past_hours: int = None,
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datetime_from: str = None,
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datetime_from: str = None,
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@@ -61,6 +62,7 @@ def scrape_property(
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:param extra_property_data: Increases requests by O(n). If set, this fetches additional property data (e.g. agent, broker, property evaluations etc.)
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:param extra_property_data: Increases requests by O(n). If set, this fetches additional property data (e.g. agent, broker, property evaluations etc.)
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:param exclude_pending: If true, this excludes pending or contingent properties from the results, unless listing type is pending.
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:param exclude_pending: If true, this excludes pending or contingent properties from the results, unless listing type is pending.
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:param limit: Limit the number of results returned. Maximum is 10,000.
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:param limit: Limit the number of results returned. Maximum is 10,000.
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:param offset: Starting position for pagination within the 10k limit (offset + limit cannot exceed 10,000). Use with limit to fetch results in chunks (e.g., offset=200, limit=200 fetches results 200-399). Should be a multiple of 200 (page size) for optimal performance. Default is 0. Note: Cannot be used to bypass the 10k API limit - use date ranges (date_from/date_to) to narrow searches and fetch more data.
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New parameters:
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New parameters:
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:param past_hours: Get properties in the last _ hours (requires client-side filtering)
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:param past_hours: Get properties in the last _ hours (requires client-side filtering)
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@@ -77,6 +79,7 @@ def scrape_property(
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validate_input(listing_type)
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validate_input(listing_type)
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validate_dates(date_from, date_to)
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validate_dates(date_from, date_to)
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validate_limit(limit)
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validate_limit(limit)
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validate_offset(offset, limit)
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validate_datetime(datetime_from)
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validate_datetime(datetime_from)
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validate_datetime(datetime_to)
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validate_datetime(datetime_to)
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validate_filters(
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validate_filters(
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@@ -100,6 +103,7 @@ def scrape_property(
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extra_property_data=extra_property_data,
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extra_property_data=extra_property_data,
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exclude_pending=exclude_pending,
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exclude_pending=exclude_pending,
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limit=limit,
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limit=limit,
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offset=offset,
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# New date/time filtering
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# New date/time filtering
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past_hours=past_hours,
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past_hours=past_hours,
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datetime_from=datetime_from,
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datetime_from=datetime_from,
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@@ -25,6 +25,7 @@ class ScraperInput(BaseModel):
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extra_property_data: bool | None = True
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extra_property_data: bool | None = True
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exclude_pending: bool | None = False
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exclude_pending: bool | None = False
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limit: int = 10000
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limit: int = 10000
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offset: int = 0
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return_type: ReturnType = ReturnType.pandas
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return_type: ReturnType = ReturnType.pandas
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# New date/time filtering parameters
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# New date/time filtering parameters
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@@ -106,6 +107,7 @@ class Scraper:
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self.extra_property_data = scraper_input.extra_property_data
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self.extra_property_data = scraper_input.extra_property_data
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self.exclude_pending = scraper_input.exclude_pending
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self.exclude_pending = scraper_input.exclude_pending
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self.limit = scraper_input.limit
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self.limit = scraper_input.limit
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self.offset = scraper_input.offset
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self.return_type = scraper_input.return_type
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self.return_type = scraper_input.return_type
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# New date/time filtering
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# New date/time filtering
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@@ -405,13 +405,23 @@ class RealtorScraper(Scraper):
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if self.return_type != ReturnType.raw:
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if self.return_type != ReturnType.raw:
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with ThreadPoolExecutor(max_workers=self.NUM_PROPERTY_WORKERS) as executor:
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with ThreadPoolExecutor(max_workers=self.NUM_PROPERTY_WORKERS) as executor:
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futures = [executor.submit(process_property, result, self.mls_only, self.extra_property_data,
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# Store futures with their indices to maintain sort order
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self.exclude_pending, self.listing_type, get_key, process_extra_property_details) for result in properties_list]
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futures_with_indices = [
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(i, executor.submit(process_property, result, self.mls_only, self.extra_property_data,
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self.exclude_pending, self.listing_type, get_key, process_extra_property_details))
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for i, result in enumerate(properties_list)
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]
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for future in as_completed(futures):
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# Collect results and sort by index to preserve API sort order
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results = []
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for idx, future in futures_with_indices:
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result = future.result()
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result = future.result()
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if result:
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if result:
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properties.append(result)
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results.append((idx, result))
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# Sort by index and extract properties in correct order
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results.sort(key=lambda x: x[0])
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properties = [result for idx, result in results]
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else:
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else:
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properties = properties_list
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properties = properties_list
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@@ -428,7 +438,7 @@ class RealtorScraper(Scraper):
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location_type = location_info["area_type"]
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location_type = location_info["area_type"]
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search_variables = {
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search_variables = {
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"offset": 0,
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"offset": self.offset,
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}
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}
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search_type = (
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search_type = (
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@@ -473,21 +483,30 @@ class RealtorScraper(Scraper):
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homes = result["properties"]
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homes = result["properties"]
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with ThreadPoolExecutor() as executor:
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with ThreadPoolExecutor() as executor:
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futures = [
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# Store futures with their offsets to maintain proper sort order
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executor.submit(
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# Start from offset + page_size and go up to offset + limit
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futures_with_offsets = [
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(i, executor.submit(
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self.general_search,
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self.general_search,
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variables=search_variables | {"offset": i},
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variables=search_variables | {"offset": i},
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search_type=search_type,
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search_type=search_type,
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)
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))
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for i in range(
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for i in range(
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self.DEFAULT_PAGE_SIZE,
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self.offset + self.DEFAULT_PAGE_SIZE,
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min(total, self.limit),
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min(total, self.offset + self.limit),
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self.DEFAULT_PAGE_SIZE,
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self.DEFAULT_PAGE_SIZE,
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)
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)
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]
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]
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for future in as_completed(futures):
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# Collect results and sort by offset to preserve API sort order across pages
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homes.extend(future.result()["properties"])
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results = []
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for offset, future in futures_with_offsets:
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results.append((offset, future.result()["properties"]))
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# Sort by offset and concatenate in correct order
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results.sort(key=lambda x: x[0])
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for offset, properties in results:
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homes.extend(properties)
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# Apply client-side hour-based filtering if needed
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# Apply client-side hour-based filtering if needed
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# (API only supports day-level filtering, so we post-filter for hour precision)
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# (API only supports day-level filtering, so we post-filter for hour precision)
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@@ -498,6 +517,11 @@ class RealtorScraper(Scraper):
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elif self.listing_type == ListingType.PENDING and (self.last_x_days or self.date_from):
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elif self.listing_type == ListingType.PENDING and (self.last_x_days or self.date_from):
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homes = self._apply_pending_date_filter(homes)
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homes = self._apply_pending_date_filter(homes)
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# Apply client-side sort to ensure results are properly ordered
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# This is necessary after filtering and to guarantee sort order across page boundaries
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if self.sort_by:
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homes = self._apply_sort(homes)
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return homes
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return homes
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def _apply_hour_based_date_filter(self, homes):
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def _apply_hour_based_date_filter(self, homes):
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@@ -722,6 +746,60 @@ class RealtorScraper(Scraper):
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return date_range['from_date'] <= date_obj <= date_range['to_date']
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return date_range['from_date'] <= date_obj <= date_range['to_date']
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return False
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return False
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def _apply_sort(self, homes):
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"""Apply client-side sorting to ensure results are properly ordered.
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This is necessary because:
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1. Multi-page results need to be re-sorted after concatenation
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2. Filtering operations may disrupt the original sort order
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Args:
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homes: List of properties (either dicts or Property objects)
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Returns:
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Sorted list of properties
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"""
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if not homes or not self.sort_by:
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return homes
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def get_sort_key(home):
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"""Extract the sort field value from a home (handles both dict and Property object)."""
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if isinstance(home, dict):
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value = home.get(self.sort_by)
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else:
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# Property object
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value = getattr(home, self.sort_by, None)
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# Handle None values - push them to the end
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if value is None:
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# Use a sentinel value that sorts to the end
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return (1, 0) if self.sort_direction == "desc" else (1, float('inf'))
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# For datetime fields, convert string to datetime for proper sorting
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if self.sort_by in ['list_date', 'sold_date', 'pending_date']:
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if isinstance(value, str):
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try:
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from datetime import datetime
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# Handle timezone indicators
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date_value = value
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if date_value.endswith('Z'):
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date_value = date_value[:-1] + '+00:00'
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parsed_date = datetime.fromisoformat(date_value)
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return (0, parsed_date)
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except (ValueError, AttributeError):
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# If parsing fails, treat as None
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return (1, 0) if self.sort_direction == "desc" else (1, float('inf'))
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return (0, value)
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# For numeric fields, ensure we can compare
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return (0, value)
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# Sort the homes
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reverse = (self.sort_direction == "desc")
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sorted_homes = sorted(homes, key=get_sort_key, reverse=reverse)
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return sorted_homes
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@retry(
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@retry(
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@@ -1,5 +1,6 @@
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from __future__ import annotations
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from __future__ import annotations
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import pandas as pd
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import pandas as pd
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import warnings
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from datetime import datetime
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from datetime import datetime
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from .core.scrapers.models import Property, ListingType, Advertisers
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from .core.scrapers.models import Property, ListingType, Advertisers
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from .exceptions import InvalidListingType, InvalidDate
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from .exceptions import InvalidListingType, InvalidDate
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@@ -182,6 +183,36 @@ def validate_limit(limit: int) -> None:
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raise ValueError("Property limit must be between 1 and 10,000.")
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raise ValueError("Property limit must be between 1 and 10,000.")
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def validate_offset(offset: int, limit: int = 10000) -> None:
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"""Validate offset parameter for pagination.
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Args:
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offset: Starting position for results pagination
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limit: Maximum number of results to fetch
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Raises:
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ValueError: If offset is invalid or if offset + limit exceeds API limit
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"""
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if offset is not None and offset < 0:
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raise ValueError("Offset must be non-negative (>= 0).")
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# Check if offset + limit exceeds API's hard limit of 10,000
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if offset is not None and limit is not None and (offset + limit) > 10000:
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raise ValueError(
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f"offset ({offset}) + limit ({limit}) = {offset + limit} exceeds API maximum of 10,000. "
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f"The API cannot return results beyond position 10,000. "
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f"To fetch more results, narrow your search."
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)
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# Warn if offset is not a multiple of 200 (API page size)
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if offset is not None and offset > 0 and offset % 200 != 0:
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warnings.warn(
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f"Offset should be a multiple of 200 (page size) for optimal performance. "
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f"Using offset {offset} may result in less efficient pagination.",
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UserWarning
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)
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|
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def validate_datetime(datetime_str: str | None) -> None:
|
def validate_datetime(datetime_str: str | None) -> None:
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"""Validate ISO 8601 datetime format."""
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"""Validate ISO 8601 datetime format."""
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if not datetime_str:
|
if not datetime_str:
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@@ -1,6 +1,6 @@
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[tool.poetry]
|
[tool.poetry]
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name = "homeharvest"
|
name = "homeharvest"
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version = "0.7.1"
|
version = "0.7.2"
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description = "Real estate scraping library"
|
description = "Real estate scraping library"
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authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
|
authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
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homepage = "https://github.com/ZacharyHampton/HomeHarvest"
|
homepage = "https://github.com/ZacharyHampton/HomeHarvest"
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@@ -870,66 +870,111 @@ def test_combined_filters():
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|
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|
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def test_sorting_by_price():
|
def test_sorting_by_price():
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"""Test sorting by list_price - note API sorting may not be perfect"""
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"""Test sorting by list_price with actual sort order validation"""
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|
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# Sort ascending (cheapest first)
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# Sort ascending (cheapest first) with multi-page limit to test concatenation
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result_asc = scrape_property(
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result_asc = scrape_property(
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location="Orlando, FL",
|
location="Orlando, FL",
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listing_type="for_sale",
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listing_type="for_sale",
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sort_by="list_price",
|
sort_by="list_price",
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sort_direction="asc",
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sort_direction="asc",
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limit=20
|
limit=250 # Multi-page to test concatenation logic
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)
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)
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|
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assert result_asc is not None and len(result_asc) > 0
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assert result_asc is not None and len(result_asc) > 0
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|
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# Verify ascending sort order (allow for None/NA values at the end)
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prices_asc = result_asc["list_price"].dropna().tolist()
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assert len(prices_asc) > 0, "No properties with prices found"
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assert prices_asc == sorted(prices_asc), f"Prices not in ascending order: {prices_asc[:10]}"
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|
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# Sort descending (most expensive first)
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# Sort descending (most expensive first)
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result_desc = scrape_property(
|
result_desc = scrape_property(
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location="San Antonio, TX",
|
location="San Antonio, TX",
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listing_type="for_sale",
|
listing_type="for_sale",
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sort_by="list_price",
|
sort_by="list_price",
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sort_direction="desc",
|
sort_direction="desc",
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limit=20
|
limit=250 # Multi-page to test concatenation logic
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)
|
)
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|
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assert result_desc is not None and len(result_desc) > 0
|
assert result_desc is not None and len(result_desc) > 0
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|
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# Note: Realtor API sorting may not be perfectly reliable for all search types
|
# Verify descending sort order (allow for None/NA values at the end)
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# The test ensures the sort parameters don't cause errors, actual sort order may vary
|
prices_desc = result_desc["list_price"].dropna().tolist()
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|
assert len(prices_desc) > 0, "No properties with prices found"
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|
assert prices_desc == sorted(prices_desc, reverse=True), f"Prices not in descending order: {prices_desc[:10]}"
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|
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|
|
||||||
def test_sorting_by_date():
|
def test_sorting_by_date():
|
||||||
"""Test sorting by list_date - note API sorting may not be perfect"""
|
"""Test sorting by list_date with actual sort order validation"""
|
||||||
|
|
||||||
result = scrape_property(
|
# Test descending (newest first) with multi-page limit
|
||||||
|
result_desc = scrape_property(
|
||||||
location="Columbus, OH",
|
location="Columbus, OH",
|
||||||
listing_type="for_sale",
|
listing_type="for_sale",
|
||||||
sort_by="list_date",
|
sort_by="list_date",
|
||||||
sort_direction="desc", # Newest first
|
sort_direction="desc", # Newest first
|
||||||
limit=20
|
limit=250 # Multi-page to test concatenation logic
|
||||||
)
|
)
|
||||||
|
|
||||||
assert result is not None and len(result) > 0
|
assert result_desc is not None and len(result_desc) > 0
|
||||||
|
|
||||||
# Test ensures sort parameter doesn't cause errors
|
# Verify descending sort order (allow for None/NA values at the end)
|
||||||
# Note: Realtor API sorting may not be perfectly reliable for all search types
|
dates_desc = result_desc["list_date"].dropna().tolist()
|
||||||
|
assert len(dates_desc) > 0, "No properties with dates found"
|
||||||
|
assert dates_desc == sorted(dates_desc, reverse=True), f"Dates not in descending order (newest first): {dates_desc[:10]}"
|
||||||
|
|
||||||
|
# Test ascending (oldest first)
|
||||||
|
result_asc = scrape_property(
|
||||||
|
location="Columbus, OH",
|
||||||
|
listing_type="for_sale",
|
||||||
|
sort_by="list_date",
|
||||||
|
sort_direction="asc", # Oldest first
|
||||||
|
limit=250
|
||||||
|
)
|
||||||
|
|
||||||
|
assert result_asc is not None and len(result_asc) > 0
|
||||||
|
|
||||||
|
# Verify ascending sort order
|
||||||
|
dates_asc = result_asc["list_date"].dropna().tolist()
|
||||||
|
assert len(dates_asc) > 0, "No properties with dates found"
|
||||||
|
assert dates_asc == sorted(dates_asc), f"Dates not in ascending order (oldest first): {dates_asc[:10]}"
|
||||||
|
|
||||||
|
|
||||||
def test_sorting_by_sqft():
|
def test_sorting_by_sqft():
|
||||||
"""Test sorting by square footage - note API sorting may not be perfect"""
|
"""Test sorting by square footage with actual sort order validation"""
|
||||||
|
|
||||||
result = scrape_property(
|
# Test descending (largest first) with multi-page limit
|
||||||
|
result_desc = scrape_property(
|
||||||
location="Indianapolis, IN",
|
location="Indianapolis, IN",
|
||||||
listing_type="for_sale",
|
listing_type="for_sale",
|
||||||
sort_by="sqft",
|
sort_by="sqft",
|
||||||
sort_direction="desc", # Largest first
|
sort_direction="desc", # Largest first
|
||||||
limit=20
|
limit=250 # Multi-page to test concatenation logic
|
||||||
)
|
)
|
||||||
|
|
||||||
assert result is not None and len(result) > 0
|
assert result_desc is not None and len(result_desc) > 0
|
||||||
|
|
||||||
# Test ensures sort parameter doesn't cause errors
|
# Verify descending sort order (allow for None/NA values at the end)
|
||||||
# Note: Realtor API sorting may not be perfectly reliable for all search types
|
sqfts_desc = result_desc["sqft"].dropna().tolist()
|
||||||
|
assert len(sqfts_desc) > 0, "No properties with sqft found"
|
||||||
|
assert sqfts_desc == sorted(sqfts_desc, reverse=True), f"Square footages not in descending order: {sqfts_desc[:10]}"
|
||||||
|
|
||||||
|
# Test ascending (smallest first)
|
||||||
|
result_asc = scrape_property(
|
||||||
|
location="Indianapolis, IN",
|
||||||
|
listing_type="for_sale",
|
||||||
|
sort_by="sqft",
|
||||||
|
sort_direction="asc", # Smallest first
|
||||||
|
limit=250
|
||||||
|
)
|
||||||
|
|
||||||
|
assert result_asc is not None and len(result_asc) > 0
|
||||||
|
|
||||||
|
# Verify ascending sort order
|
||||||
|
sqfts_asc = result_asc["sqft"].dropna().tolist()
|
||||||
|
assert len(sqfts_asc) > 0, "No properties with sqft found"
|
||||||
|
assert sqfts_asc == sorted(sqfts_asc), f"Square footages not in ascending order: {sqfts_asc[:10]}"
|
||||||
|
|
||||||
|
|
||||||
def test_filter_validation_errors():
|
def test_filter_validation_errors():
|
||||||
|
|||||||
Reference in New Issue
Block a user