Add: Decisive appraiser (שמאי מכריע) search via gov.il public API
Adds a new MCP tool `search_decisive_appraisals` that queries the Ministry of Justice public registry (~30K published decisions) by block (גוש), plot (חלקה), appraiser name, committee, decision/publicity date ranges, or free text — and returns metadata + direct PDF URLs. Implementation notes: - New `nadlan_mcp/govil/` package, parallel to `nadlan_mcp/govmap/`, for gov.il APIs that are not Govmap. Pydantic v2 models match the upstream PascalCase response via aliases. - Upstream sits behind an F5 WAF that rejects standard `requests`; uses `curl_cffi` with Chrome 120 impersonation to traverse it. - Static `x-client-id` header (issued to the gov.il SPA, public, visible in any DevTools session) is required by the gateway — without it every call returns a generic 500. - 14 unit tests cover model parsing, body shape, pagination, and the 500-is-fatal contract (configuration error, not retryable). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
+44
-30
@@ -69,8 +69,9 @@ class GovmapConfig:
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# Percentage-based backup filtering (catches extreme outliers in heterogeneous data)
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analysis_use_percentage_backup: bool = field(
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default_factory=lambda: os.getenv("ANALYSIS_USE_PERCENTAGE_BACKUP", "true").lower()
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== "true"
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default_factory=lambda: (
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os.getenv("ANALYSIS_USE_PERCENTAGE_BACKUP", "true").lower() == "true"
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)
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)
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analysis_percentage_threshold: float = field(
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default_factory=lambda: float(os.getenv("ANALYSIS_PERCENTAGE_THRESHOLD", "0.4"))
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@@ -91,8 +92,9 @@ class GovmapConfig:
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# Statistical Robustness (for investment analysis)
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analysis_use_robust_volatility: bool = field(
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default_factory=lambda: os.getenv("ANALYSIS_USE_ROBUST_VOLATILITY", "true").lower()
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== "true"
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default_factory=lambda: (
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os.getenv("ANALYSIS_USE_ROBUST_VOLATILITY", "true").lower() == "true"
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)
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)
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analysis_use_robust_trends: bool = field(
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default_factory=lambda: os.getenv("ANALYSIS_USE_ROBUST_TRENDS", "true").lower() == "true"
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@@ -100,8 +102,9 @@ class GovmapConfig:
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# Reporting
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analysis_include_unfiltered_stats: bool = field(
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default_factory=lambda: os.getenv("ANALYSIS_INCLUDE_UNFILTERED_STATS", "true").lower()
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== "true"
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default_factory=lambda: (
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os.getenv("ANALYSIS_INCLUDE_UNFILTERED_STATS", "true").lower() == "true"
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)
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)
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# Distance Filtering for Deal Relevance
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@@ -119,48 +122,59 @@ class GovmapConfig:
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# MCP Tool Availability (enable/disable specific tools)
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tool_autocomplete_address_enabled: bool = field(
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default_factory=lambda: os.getenv("TOOL_AUTOCOMPLETE_ADDRESS_ENABLED", "true").lower()
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== "true"
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default_factory=lambda: (
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os.getenv("TOOL_AUTOCOMPLETE_ADDRESS_ENABLED", "true").lower() == "true"
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)
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)
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tool_get_deals_by_radius_enabled: bool = field(
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default_factory=lambda: os.getenv("TOOL_GET_DEALS_BY_RADIUS_ENABLED", "false").lower()
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== "true"
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default_factory=lambda: (
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os.getenv("TOOL_GET_DEALS_BY_RADIUS_ENABLED", "false").lower() == "true"
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)
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)
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tool_get_street_deals_enabled: bool = field(
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default_factory=lambda: os.getenv("TOOL_GET_STREET_DEALS_ENABLED", "false").lower()
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== "true"
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default_factory=lambda: (
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os.getenv("TOOL_GET_STREET_DEALS_ENABLED", "false").lower() == "true"
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)
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)
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tool_get_neighborhood_deals_enabled: bool = field(
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default_factory=lambda: os.getenv("TOOL_GET_NEIGHBORHOOD_DEALS_ENABLED", "true").lower()
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== "true"
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default_factory=lambda: (
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os.getenv("TOOL_GET_NEIGHBORHOOD_DEALS_ENABLED", "true").lower() == "true"
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)
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)
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tool_find_recent_deals_for_address_enabled: bool = field(
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default_factory=lambda: os.getenv(
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"TOOL_FIND_RECENT_DEALS_FOR_ADDRESS_ENABLED", "true"
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).lower()
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== "true"
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default_factory=lambda: (
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os.getenv("TOOL_FIND_RECENT_DEALS_FOR_ADDRESS_ENABLED", "true").lower() == "true"
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)
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)
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tool_analyze_market_trends_enabled: bool = field(
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default_factory=lambda: os.getenv("TOOL_ANALYZE_MARKET_TRENDS_ENABLED", "true").lower()
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== "true"
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default_factory=lambda: (
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os.getenv("TOOL_ANALYZE_MARKET_TRENDS_ENABLED", "true").lower() == "true"
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)
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)
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tool_compare_addresses_enabled: bool = field(
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default_factory=lambda: os.getenv("TOOL_COMPARE_ADDRESSES_ENABLED", "true").lower()
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== "true"
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default_factory=lambda: (
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os.getenv("TOOL_COMPARE_ADDRESSES_ENABLED", "true").lower() == "true"
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)
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)
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tool_get_valuation_comparables_enabled: bool = field(
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default_factory=lambda: os.getenv("TOOL_GET_VALUATION_COMPARABLES_ENABLED", "true").lower()
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== "true"
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default_factory=lambda: (
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os.getenv("TOOL_GET_VALUATION_COMPARABLES_ENABLED", "true").lower() == "true"
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)
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)
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tool_get_deal_statistics_enabled: bool = field(
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default_factory=lambda: os.getenv("TOOL_GET_DEAL_STATISTICS_ENABLED", "true").lower()
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== "true"
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default_factory=lambda: (
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os.getenv("TOOL_GET_DEAL_STATISTICS_ENABLED", "true").lower() == "true"
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)
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)
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tool_get_market_activity_metrics_enabled: bool = field(
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default_factory=lambda: os.getenv(
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"TOOL_GET_MARKET_ACTIVITY_METRICS_ENABLED", "false"
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).lower()
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== "true"
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default_factory=lambda: (
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os.getenv("TOOL_GET_MARKET_ACTIVITY_METRICS_ENABLED", "false").lower() == "true"
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)
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)
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tool_search_decisive_appraisals_enabled: bool = field(
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default_factory=lambda: (
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os.getenv("TOOL_SEARCH_DECISIVE_APPRAISALS_ENABLED", "true").lower() == "true"
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)
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)
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def __post_init__(self):
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@@ -14,6 +14,7 @@ from mcp.server.fastmcp import FastMCP
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from starlette.responses import JSONResponse
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from nadlan_mcp.config import get_config
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from nadlan_mcp.govil import DecisiveAppraiserClient
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from nadlan_mcp.govmap import GovmapClient
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from nadlan_mcp.govmap.models import Deal
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from nadlan_mcp.govmap.outlier_detection import filter_deals_for_analysis
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@@ -28,6 +29,9 @@ mcp = FastMCP("nadlan-mcp")
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# Initialize the Govmap client
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client = GovmapClient()
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# Initialize the Decisive Appraiser (gov.il / Ministry of Justice) client
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decisive_appraiser_client = DecisiveAppraiserClient()
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def conditional_tool(config_flag: str):
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"""
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@@ -1310,6 +1314,112 @@ def get_market_activity_metrics(address: str, years_back: int = 2, radius_meters
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return f"Error analyzing market activity: {str(e)}"
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@conditional_tool("tool_search_decisive_appraisals_enabled")
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def search_decisive_appraisals(
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block: Optional[str] = None,
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plot: Optional[str] = None,
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decisive_appraiser: Optional[str] = None,
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committee: Optional[str] = None,
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decision_date_from: Optional[str] = None,
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decision_date_to: Optional[str] = None,
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publicity_date_from: Optional[str] = None,
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publicity_date_to: Optional[str] = None,
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search_text: Optional[str] = None,
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appraisal_header: Optional[str] = None,
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max_results: int = 30,
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) -> str:
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"""Search published "decisive appraiser" (שמאי מכריע) decisions from the Israeli
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Ministry of Justice public registry. The registry holds 30,000+ written
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decisions on land betterment levy, expropriation, real-estate disputes etc.
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All filters are optional. Use block + plot for property-level lookups
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(גוש + חלקה), or `decisive_appraiser` to find every decision by a given
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appraiser. Page size is fixed by the upstream at 10; this tool pages
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automatically up to `max_results`.
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Args:
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block: Land block number, גוש (e.g. "6212"). Exact match.
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plot: Land plot number, חלקה (e.g. "894"). Use with block.
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decisive_appraiser: Appraiser name in Hebrew (e.g. "דדון דוד").
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committee: Local planning committee (e.g. "תל אביב-יפו").
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decision_date_from / decision_date_to: Date range for the decision date.
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Format: dd-MM-yyyy (e.g. "01-01-2024"). Either bound is optional.
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publicity_date_from / publicity_date_to: Date range for publication.
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search_text: Free-text search inside the decision document.
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appraisal_header: Search within the decision title.
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max_results: Maximum number of decisions to return (default 30).
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Returns:
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JSON string with `total_results` (database-wide), `returned`, the
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applied `filters`, and a `decisions` array. Each decision contains
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the appraiser name, block/plot, committee, dates, the decision title
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and a `pdf_url` to download the original PDF.
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"""
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log_mcp_call(
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"search_decisive_appraisals",
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block=block,
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plot=plot,
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decisive_appraiser=decisive_appraiser,
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committee=committee,
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decision_date_from=decision_date_from,
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decision_date_to=decision_date_to,
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publicity_date_from=publicity_date_from,
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publicity_date_to=publicity_date_to,
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search_text=search_text,
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appraisal_header=appraisal_header,
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max_results=max_results,
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)
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try:
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response = decisive_appraiser_client.search_decisions_paged(
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max_results=max_results,
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block=block,
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plot=plot,
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decisive_appraiser=decisive_appraiser,
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committee=committee,
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decision_date_from=decision_date_from,
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decision_date_to=decision_date_to,
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publicity_date_from=publicity_date_from,
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publicity_date_to=publicity_date_to,
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search_text=search_text,
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appraisal_header=appraisal_header,
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)
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decisions = []
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for idx, decision in enumerate(response.results, start=1):
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data = decision.model_dump(mode="json", exclude_none=True)
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documents = data.pop("documents", []) or []
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primary_pdf = documents[0]["file_url"] if documents else None
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data["id"] = idx
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data["pdf_url"] = primary_pdf
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data["all_documents"] = documents
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decisions.append(data)
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return json.dumps(
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{
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"total_results": response.total_results,
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"returned": len(decisions),
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"filters": {
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"block": block,
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"plot": plot,
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"decisive_appraiser": decisive_appraiser,
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"committee": committee,
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"decision_date_from": decision_date_from,
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"decision_date_to": decision_date_to,
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"publicity_date_from": publicity_date_from,
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"publicity_date_to": publicity_date_to,
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"search_text": search_text,
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"appraisal_header": appraisal_header,
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},
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"decisions": decisions,
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},
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ensure_ascii=False,
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indent=None,
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)
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except Exception as e:
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logger.error(f"Error in search_decisive_appraisals: {e}", exc_info=True)
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return f"Error searching decisive appraisals: {str(e)}"
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# Health check endpoint for HTTP deployments
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@mcp.custom_route("/health", methods=["GET"])
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async def health_check(request):
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@@ -0,0 +1,21 @@
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"""
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Israeli government open API (gov.il) clients.
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This package provides clients for gov.il public APIs distinct from Govmap —
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notably the Ministry of Justice "Decisive Appraiser" search service that
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exposes published decisions of certified property appraisers.
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"""
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from .client import DecisiveAppraiserClient
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from .models import (
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AppraisalDecision,
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AppraisalDocument,
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DecisiveAppraiserSearchResponse,
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)
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__all__ = [
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"DecisiveAppraiserClient",
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"AppraisalDecision",
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"AppraisalDocument",
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"DecisiveAppraiserSearchResponse",
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]
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@@ -0,0 +1,263 @@
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"""
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Client for the Ministry of Justice "Decisive Appraiser" search API.
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The upstream endpoint sits behind an F5 WAF that fingerprints TLS clients
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and rejects standard `requests`. We use `curl_cffi` with Chrome
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impersonation to traverse it. A static `x-client-id` header issued to the
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gov.il SPA is required by the gateway; without it every request returns a
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generic 500 "General Error".
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"""
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from datetime import datetime
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import logging
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import time
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from typing import Any, Dict, List, Optional
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from curl_cffi import requests as cf_requests
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from nadlan_mcp.config import GovmapConfig, get_config
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from .models import (
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AppraisalDecision,
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DecisiveAppraiserSearchResponse,
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)
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logger = logging.getLogger(__name__)
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# Endpoint is public and stable; embedding it avoids forcing every operator
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# to set yet another env var. Override-able via config if the path moves.
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DEFAULT_API_URL = (
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"https://pub-justice.openapi.gov.il/pub/moj/portal/rest/searchpredefinedapi/v1"
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"/SearchPredefinedApi/DecisiveAppraiser/SearchDecisions"
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)
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DEFAULT_REFERER = "https://www.gov.il/he/departments/dynamiccollectors/decisive_appraisal_decisions"
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# Public client id assigned to the gov.il SPA and visible in any browser
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# DevTools session. Not a secret, but required by the gateway.
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DEFAULT_CLIENT_ID = "149a5bad-edde-49a6-9fb9-188bd17d4788"
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# Filters the upstream API understands. Anything else is silently dropped.
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_VALID_FILTER_KEYS = {
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"SearchText",
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"AppraisalHeader",
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"DecisiveAppraiser",
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"Block",
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"Plot",
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"Committee",
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"AppraisalType",
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"AppraiserType",
|
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"AppraisalVersion",
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"PublicityDate_from",
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"PublicityDate_to",
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"DecisionDate_from",
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"DecisionDate_to",
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}
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||||
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def _format_date(value: Optional[Any]) -> Optional[str]:
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"""Coerce a date / datetime / string into the dd-MM-yyyy format the API expects."""
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if value is None:
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return None
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if isinstance(value, datetime):
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return value.strftime("%d-%m-%Y")
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if hasattr(value, "strftime"):
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return value.strftime("%d-%m-%Y")
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s = str(value).strip()
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if not s:
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return None
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return s
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class DecisiveAppraiserClient:
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"""
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Search and download published decisive-appraiser decisions.
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||||
|
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Uses curl_cffi with Chrome 120 impersonation to satisfy the F5 WAF in
|
||||
front of pub-justice.openapi.gov.il. Honours the same retry / rate-limit
|
||||
knobs as `GovmapClient` so operators don't manage two configs.
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||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
config: Optional[GovmapConfig] = None,
|
||||
api_url: str = DEFAULT_API_URL,
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||||
client_id: str = DEFAULT_CLIENT_ID,
|
||||
impersonate: str = "chrome120",
|
||||
):
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||||
self.config = config or get_config()
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||||
self.api_url = api_url
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||||
self.client_id = client_id
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||||
self._impersonate = impersonate
|
||||
self._session = cf_requests.Session(impersonate=impersonate)
|
||||
self._session.headers.update(
|
||||
{
|
||||
"Accept": "application/json, text/plain, */*",
|
||||
"Accept-Language": "he-IL,he;q=0.9,en-US;q=0.8,en;q=0.7",
|
||||
"Content-Type": "application/json;charset=UTF-8",
|
||||
"Origin": "https://www.gov.il",
|
||||
"Referer": DEFAULT_REFERER,
|
||||
"Sec-Fetch-Dest": "empty",
|
||||
"Sec-Fetch-Mode": "cors",
|
||||
"Sec-Fetch-Site": "cross-site",
|
||||
"x-client-id": self.client_id,
|
||||
}
|
||||
)
|
||||
self._last_request_time = 0.0
|
||||
|
||||
def _rate_limit(self) -> None:
|
||||
min_interval = 1.0 / self.config.requests_per_second
|
||||
elapsed = time.time() - self._last_request_time
|
||||
if elapsed < min_interval:
|
||||
time.sleep(min_interval - elapsed)
|
||||
self._last_request_time = time.time()
|
||||
|
||||
def _post(self, body: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""POST `body` to the search endpoint with retries on transient failures."""
|
||||
last_exc: Optional[Exception] = None
|
||||
for attempt in range(self.config.max_retries + 1):
|
||||
self._rate_limit()
|
||||
try:
|
||||
response = self._session.post(
|
||||
self.api_url,
|
||||
json=body,
|
||||
timeout=(self.config.connect_timeout, self.config.read_timeout),
|
||||
)
|
||||
# 500 from this gateway typically means "you got past TLS but
|
||||
# the gateway rejected your shape/headers"; treat as fatal so
|
||||
# retries don't mask a misconfiguration.
|
||||
if response.status_code == 500:
|
||||
raise ValueError(
|
||||
f"DecisiveAppraiser API returned 500 — request shape or "
|
||||
f"x-client-id is likely wrong. Body keys sent: {list(body.keys())}"
|
||||
)
|
||||
if response.status_code >= 500:
|
||||
raise cf_requests.RequestsError(
|
||||
f"Upstream {response.status_code}: {response.text[:200]}"
|
||||
)
|
||||
if response.status_code != 200:
|
||||
raise ValueError(
|
||||
f"DecisiveAppraiser API returned {response.status_code}: "
|
||||
f"{response.text[:200]}"
|
||||
)
|
||||
return response.json()
|
||||
except (cf_requests.RequestsError, OSError) as e:
|
||||
last_exc = e
|
||||
if attempt < self.config.max_retries:
|
||||
wait = min(
|
||||
self.config.retry_max_wait,
|
||||
self.config.retry_min_wait * (2**attempt),
|
||||
)
|
||||
logger.warning(
|
||||
f"DecisiveAppraiser request failed (attempt {attempt + 1}/"
|
||||
f"{self.config.max_retries + 1}): {e}. Retrying in {wait}s"
|
||||
)
|
||||
time.sleep(wait)
|
||||
else:
|
||||
raise
|
||||
# Unreachable, but satisfies the type checker.
|
||||
raise last_exc if last_exc else RuntimeError("retry loop exited unexpectedly")
|
||||
|
||||
def search_decisions(
|
||||
self,
|
||||
block: Optional[str] = None,
|
||||
plot: Optional[str] = None,
|
||||
decisive_appraiser: Optional[str] = None,
|
||||
committee: Optional[str] = None,
|
||||
decision_date_from: Optional[Any] = None,
|
||||
decision_date_to: Optional[Any] = None,
|
||||
publicity_date_from: Optional[Any] = None,
|
||||
publicity_date_to: Optional[Any] = None,
|
||||
search_text: Optional[str] = None,
|
||||
appraisal_header: Optional[str] = None,
|
||||
skip: int = 0,
|
||||
) -> DecisiveAppraiserSearchResponse:
|
||||
"""
|
||||
Search published decisive-appraiser decisions.
|
||||
|
||||
All filters are optional — the API will return the latest 10 results
|
||||
when called with just `skip=0`. Page size is fixed at 10 server-side;
|
||||
use `skip` to paginate.
|
||||
|
||||
Args:
|
||||
block: Land block (גוש) — exact string match.
|
||||
plot: Land plot (חלקה) — exact string match within `block`.
|
||||
decisive_appraiser: Appraiser name (substring/exact, Hebrew).
|
||||
committee: Local committee name (e.g. "תל אביב-יפו").
|
||||
decision_date_from / decision_date_to: Filter by decision date.
|
||||
Accepts datetime, date, or "dd-MM-yyyy" string.
|
||||
publicity_date_from / publicity_date_to: Filter by publication date.
|
||||
search_text: Free-text search across the document body.
|
||||
appraisal_header: Search within the appraisal header text.
|
||||
skip: Pagination offset (multiples of 10).
|
||||
"""
|
||||
body: Dict[str, Any] = {"skip": int(skip)}
|
||||
if block:
|
||||
body["Block"] = str(block).strip()
|
||||
if plot:
|
||||
body["Plot"] = str(plot).strip()
|
||||
if decisive_appraiser:
|
||||
body["DecisiveAppraiser"] = decisive_appraiser.strip()
|
||||
if committee:
|
||||
body["Committee"] = committee.strip()
|
||||
if search_text:
|
||||
body["SearchText"] = search_text.strip()
|
||||
if appraisal_header:
|
||||
body["AppraisalHeader"] = appraisal_header.strip()
|
||||
df = _format_date(decision_date_from)
|
||||
if df:
|
||||
body["DecisionDate_from"] = df
|
||||
dt = _format_date(decision_date_to)
|
||||
if dt:
|
||||
body["DecisionDate_to"] = dt
|
||||
pf = _format_date(publicity_date_from)
|
||||
if pf:
|
||||
body["PublicityDate_from"] = pf
|
||||
pt = _format_date(publicity_date_to)
|
||||
if pt:
|
||||
body["PublicityDate_to"] = pt
|
||||
|
||||
raw = self._post(body)
|
||||
# Unwrap {"Results": [{"Data": {...}}, ...]} into [decision, ...]
|
||||
decisions: List[AppraisalDecision] = []
|
||||
for item in raw.get("Results", []) or []:
|
||||
data = item.get("Data") if isinstance(item, dict) else None
|
||||
if isinstance(data, dict):
|
||||
decisions.append(AppraisalDecision.model_validate(data))
|
||||
return DecisiveAppraiserSearchResponse(
|
||||
results=decisions,
|
||||
total_results=int(raw.get("TotalResults") or 0),
|
||||
status=raw.get("Status"),
|
||||
message=raw.get("message"),
|
||||
)
|
||||
|
||||
def search_decisions_paged(
|
||||
self,
|
||||
max_results: int = 50,
|
||||
**filters: Any,
|
||||
) -> DecisiveAppraiserSearchResponse:
|
||||
"""
|
||||
Page through `search_decisions` until `max_results` decisions are
|
||||
collected (or the upstream runs out).
|
||||
|
||||
`filters` are forwarded to `search_decisions`; do not pass `skip`.
|
||||
"""
|
||||
if "skip" in filters:
|
||||
raise ValueError("search_decisions_paged manages skip itself")
|
||||
|
||||
page_size = 10 # Server-side fixed.
|
||||
collected: List[AppraisalDecision] = []
|
||||
total = 0
|
||||
skip = 0
|
||||
while len(collected) < max_results:
|
||||
page = self.search_decisions(skip=skip, **filters)
|
||||
total = page.total_results
|
||||
if not page.results:
|
||||
break
|
||||
collected.extend(page.results)
|
||||
skip += page_size
|
||||
if skip >= total:
|
||||
break
|
||||
|
||||
return DecisiveAppraiserSearchResponse(
|
||||
results=collected[:max_results],
|
||||
total_results=total,
|
||||
)
|
||||
@@ -0,0 +1,63 @@
|
||||
"""
|
||||
Pydantic models for the Ministry of Justice "Decisive Appraiser" API.
|
||||
|
||||
The upstream API at pub-justice.openapi.gov.il returns decisions in a
|
||||
nested wrapper:
|
||||
|
||||
{"Results": [{"Data": {...decision fields...}}, ...],
|
||||
"TotalResults": 30398, "Status": ..., "message": ...}
|
||||
|
||||
These models flatten the wrapper for ergonomic use, while preserving the
|
||||
original Hebrew field labels via aliases.
|
||||
"""
|
||||
|
||||
from datetime import datetime
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
from pydantic import BaseModel, ConfigDict, Field
|
||||
|
||||
|
||||
class AppraisalDocument(BaseModel):
|
||||
"""A single PDF attached to an appraisal decision."""
|
||||
|
||||
model_config = ConfigDict(populate_by_name=True, extra="ignore")
|
||||
|
||||
file_url: str = Field(alias="FileName")
|
||||
display_name: Optional[str] = Field(default=None, alias="DisplayName")
|
||||
extension: Optional[str] = Field(default=None, alias="Extension")
|
||||
|
||||
|
||||
class AppraisalDecision(BaseModel):
|
||||
"""
|
||||
One published decision by a certified decisive appraiser (שמאי מכריע).
|
||||
|
||||
Field names are snake_case in Python; aliases match the upstream
|
||||
PascalCase JSON keys so the model can be constructed from a raw API
|
||||
payload via `AppraisalDecision.model_validate(data)`.
|
||||
"""
|
||||
|
||||
model_config = ConfigDict(populate_by_name=True, extra="ignore")
|
||||
|
||||
appraisal_header: Optional[str] = Field(default=None, alias="AppraisalHeader")
|
||||
appraisal_type: Optional[str] = Field(default=None, alias="AppraisalType")
|
||||
appraisal_version: Optional[str] = Field(default=None, alias="AppraisalVersion")
|
||||
decisive_appraiser: Optional[str] = Field(default=None, alias="DecisiveAppraiser")
|
||||
appraiser_type: Optional[str] = Field(default=None, alias="AppraiserType")
|
||||
block: Optional[str] = Field(default=None, alias="Block")
|
||||
plot: Optional[str] = Field(default=None, alias="Plot")
|
||||
committee: Optional[str] = Field(default=None, alias="Committee")
|
||||
decision_date: Optional[datetime] = Field(default=None, alias="DecisionDate")
|
||||
publicity_date: Optional[datetime] = Field(default=None, alias="PublicityDate")
|
||||
documents: List[AppraisalDocument] = Field(default_factory=list, alias="Document")
|
||||
doc_summary: Dict[str, Any] = Field(default_factory=dict, alias="DocSummary")
|
||||
|
||||
|
||||
class DecisiveAppraiserSearchResponse(BaseModel):
|
||||
"""Top-level wrapper of the SearchDecisions endpoint."""
|
||||
|
||||
model_config = ConfigDict(populate_by_name=True, extra="ignore")
|
||||
|
||||
total_results: int = Field(default=0, alias="TotalResults")
|
||||
results: List[AppraisalDecision] = Field(default_factory=list)
|
||||
status: Optional[Any] = Field(default=None, alias="Status")
|
||||
message: Optional[Any] = Field(default=None)
|
||||
@@ -27,6 +27,7 @@ dependencies = [
|
||||
"python-dotenv>=1.0.0",
|
||||
"pydantic>=2.0.0",
|
||||
"fastmcp>=2.13.0,<3.0.0",
|
||||
"curl_cffi>=0.5.0",
|
||||
]
|
||||
|
||||
[project.optional-dependencies]
|
||||
|
||||
@@ -0,0 +1,224 @@
|
||||
"""
|
||||
Unit tests for the DecisiveAppraiser (gov.il / Ministry of Justice) client.
|
||||
|
||||
These tests mock the curl_cffi session entirely so they're fast and offline.
|
||||
A separate integration test (marked `@pytest.mark.integration`) exercises
|
||||
the real upstream — run with `pytest -m integration` only when needed.
|
||||
"""
|
||||
|
||||
from unittest.mock import Mock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
from nadlan_mcp.govil import DecisiveAppraiserClient
|
||||
from nadlan_mcp.govil.client import _format_date
|
||||
from nadlan_mcp.govil.models import (
|
||||
AppraisalDecision,
|
||||
AppraisalDocument,
|
||||
DecisiveAppraiserSearchResponse,
|
||||
)
|
||||
|
||||
# A trimmed-but-realistic upstream payload, matching the live shape captured
|
||||
# during development.
|
||||
SAMPLE_RESPONSE = {
|
||||
"Results": [
|
||||
{
|
||||
"Data": {
|
||||
"AppraisalHeader": "הכרעת שמאי מכריע מיום 01-04-2026 בעניין היטל השבחה",
|
||||
"AppraisalType": "היטל השבחה",
|
||||
"AppraisalVersion": "שומה מקורית",
|
||||
"DecisiveAppraiser": "דדון דוד",
|
||||
"AppraiserType": "שמאי מכריע",
|
||||
"Block": "6212",
|
||||
"Plot": "894",
|
||||
"Committee": "תל אביב-יפו",
|
||||
"DecisionDate": "2026-04-01T00:00:00+03:00",
|
||||
"PublicityDate": "2026-04-11T00:00:00+03:00",
|
||||
"Document": [
|
||||
{
|
||||
"FileName": "https://free-justice.openapi.gov.il/.../abc=",
|
||||
"DisplayName": "הכרעת שמאי מכריע",
|
||||
"Extension": "pdf",
|
||||
}
|
||||
],
|
||||
"DocSummary": {},
|
||||
}
|
||||
}
|
||||
],
|
||||
"Status": None,
|
||||
"message": None,
|
||||
"TotalResults": 333,
|
||||
}
|
||||
|
||||
|
||||
class TestModels:
|
||||
def test_decision_parses_pascalcase_payload(self):
|
||||
decision = AppraisalDecision.model_validate(SAMPLE_RESPONSE["Results"][0]["Data"])
|
||||
assert decision.block == "6212"
|
||||
assert decision.plot == "894"
|
||||
assert decision.decisive_appraiser == "דדון דוד"
|
||||
assert decision.committee == "תל אביב-יפו"
|
||||
assert decision.decision_date is not None
|
||||
assert len(decision.documents) == 1
|
||||
assert isinstance(decision.documents[0], AppraisalDocument)
|
||||
assert decision.documents[0].file_url.endswith("abc=")
|
||||
assert decision.documents[0].extension == "pdf"
|
||||
|
||||
def test_decision_handles_missing_fields(self):
|
||||
decision = AppraisalDecision.model_validate({"Block": "1234"})
|
||||
assert decision.block == "1234"
|
||||
assert decision.plot is None
|
||||
assert decision.documents == []
|
||||
assert decision.doc_summary == {}
|
||||
|
||||
|
||||
class TestFormatDate:
|
||||
def test_none_passthrough(self):
|
||||
assert _format_date(None) is None
|
||||
|
||||
def test_empty_string(self):
|
||||
assert _format_date("") is None
|
||||
assert _format_date(" ") is None
|
||||
|
||||
def test_dd_mm_yyyy_string_passthrough(self):
|
||||
assert _format_date("01-04-2026") == "01-04-2026"
|
||||
|
||||
def test_datetime_formatting(self):
|
||||
from datetime import datetime as dt
|
||||
|
||||
assert _format_date(dt(2026, 4, 1)) == "01-04-2026"
|
||||
|
||||
def test_date_formatting(self):
|
||||
from datetime import date as date_type
|
||||
|
||||
assert _format_date(date_type(2026, 4, 1)) == "01-04-2026"
|
||||
|
||||
|
||||
class TestDecisiveAppraiserClient:
|
||||
@patch("nadlan_mcp.govil.client.cf_requests.Session")
|
||||
def test_search_by_block_builds_correct_body(self, mock_session_class):
|
||||
"""Block filter is sent as a flat top-level field, not under `filters`."""
|
||||
mock_response = Mock()
|
||||
mock_response.status_code = 200
|
||||
mock_response.json.return_value = SAMPLE_RESPONSE
|
||||
mock_session = Mock()
|
||||
mock_session.post.return_value = mock_response
|
||||
mock_session_class.return_value = mock_session
|
||||
|
||||
client = DecisiveAppraiserClient()
|
||||
result = client.search_decisions(block="6212")
|
||||
|
||||
# Body shape we discovered: flat keys, not nested filters.
|
||||
call_kwargs = mock_session.post.call_args.kwargs
|
||||
assert call_kwargs["json"] == {"skip": 0, "Block": "6212"}
|
||||
assert isinstance(result, DecisiveAppraiserSearchResponse)
|
||||
assert result.total_results == 333
|
||||
assert len(result.results) == 1
|
||||
assert result.results[0].block == "6212"
|
||||
|
||||
@patch("nadlan_mcp.govil.client.cf_requests.Session")
|
||||
def test_search_combines_all_filters(self, mock_session_class):
|
||||
mock_response = Mock()
|
||||
mock_response.status_code = 200
|
||||
mock_response.json.return_value = SAMPLE_RESPONSE
|
||||
mock_session = Mock()
|
||||
mock_session.post.return_value = mock_response
|
||||
mock_session_class.return_value = mock_session
|
||||
|
||||
client = DecisiveAppraiserClient()
|
||||
client.search_decisions(
|
||||
block="6212",
|
||||
plot="894",
|
||||
decisive_appraiser="דדון דוד",
|
||||
committee="תל אביב-יפו",
|
||||
decision_date_from="01-01-2025",
|
||||
decision_date_to="31-12-2026",
|
||||
search_text="היטל השבחה",
|
||||
skip=20,
|
||||
)
|
||||
body = mock_session.post.call_args.kwargs["json"]
|
||||
assert body["skip"] == 20
|
||||
assert body["Block"] == "6212"
|
||||
assert body["Plot"] == "894"
|
||||
assert body["DecisiveAppraiser"] == "דדון דוד"
|
||||
assert body["Committee"] == "תל אביב-יפו"
|
||||
assert body["DecisionDate_from"] == "01-01-2025"
|
||||
assert body["DecisionDate_to"] == "31-12-2026"
|
||||
assert body["SearchText"] == "היטל השבחה"
|
||||
|
||||
@patch("nadlan_mcp.govil.client.cf_requests.Session")
|
||||
def test_500_response_raises_immediately(self, mock_session_class):
|
||||
"""500 from this gateway is fatal (config issue), not retryable."""
|
||||
mock_response = Mock()
|
||||
mock_response.status_code = 500
|
||||
mock_response.text = '{"code":500,"message":"Internal Server Error"}'
|
||||
mock_session = Mock()
|
||||
mock_session.post.return_value = mock_response
|
||||
mock_session_class.return_value = mock_session
|
||||
|
||||
client = DecisiveAppraiserClient()
|
||||
with pytest.raises(ValueError, match="500"):
|
||||
client.search_decisions(block="6212")
|
||||
# Should not have retried — single call.
|
||||
assert mock_session.post.call_count == 1
|
||||
|
||||
@patch("nadlan_mcp.govil.client.cf_requests.Session")
|
||||
def test_empty_filters_only_sends_skip(self, mock_session_class):
|
||||
mock_response = Mock()
|
||||
mock_response.status_code = 200
|
||||
mock_response.json.return_value = {"Results": [], "TotalResults": 0}
|
||||
mock_session = Mock()
|
||||
mock_session.post.return_value = mock_response
|
||||
mock_session_class.return_value = mock_session
|
||||
|
||||
client = DecisiveAppraiserClient()
|
||||
client.search_decisions()
|
||||
assert mock_session.post.call_args.kwargs["json"] == {"skip": 0}
|
||||
|
||||
@patch("nadlan_mcp.govil.client.cf_requests.Session")
|
||||
def test_paged_collects_across_pages(self, mock_session_class):
|
||||
"""Pagination should keep calling skip+=10 until max_results is reached."""
|
||||
|
||||
def make_page(skip: int):
|
||||
# Three pages of 10, then empty.
|
||||
results = (
|
||||
[{"Data": {"Block": "6212", "Plot": str(skip + i)}} for i in range(10)]
|
||||
if skip < 30
|
||||
else []
|
||||
)
|
||||
return {"Results": results, "TotalResults": 30}
|
||||
|
||||
# Track call sequence
|
||||
call_log = []
|
||||
|
||||
def post_side_effect(url, **kwargs):
|
||||
call_log.append(kwargs["json"]["skip"])
|
||||
mock_resp = Mock()
|
||||
mock_resp.status_code = 200
|
||||
mock_resp.json.return_value = make_page(kwargs["json"]["skip"])
|
||||
return mock_resp
|
||||
|
||||
mock_session = Mock()
|
||||
mock_session.post.side_effect = post_side_effect
|
||||
mock_session_class.return_value = mock_session
|
||||
|
||||
client = DecisiveAppraiserClient()
|
||||
result = client.search_decisions_paged(max_results=25, block="6212")
|
||||
|
||||
assert call_log == [0, 10, 20] # 3 pages
|
||||
assert len(result.results) == 25 # truncated to max_results
|
||||
assert result.total_results == 30
|
||||
|
||||
def test_paged_rejects_explicit_skip(self):
|
||||
client = DecisiveAppraiserClient()
|
||||
with pytest.raises(ValueError, match="manages skip"):
|
||||
client.search_decisions_paged(max_results=10, skip=20, block="6212")
|
||||
|
||||
def test_init_sets_required_headers(self):
|
||||
client = DecisiveAppraiserClient()
|
||||
headers = client._session.headers
|
||||
# The static client_id is the gateway's auth gate — without it every
|
||||
# request returns 500.
|
||||
assert "x-client-id" in headers
|
||||
assert headers["x-client-id"] == "149a5bad-edde-49a6-9fb9-188bd17d4788"
|
||||
assert headers["Origin"] == "https://www.gov.il"
|
||||
Reference in New Issue
Block a user