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fix: strip duplicated resolution frame validation #208

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nikbpetrov wants to merge 2 commits into from
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fix: strip duplicated resolution frame validation #208

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4dcd18d
fix: strip duplicated resolution frame validation
nikbpetrov Jun 8, 2026
11e3324
fix: polymarket's duplicated validation
nikbpetrov Jun 10, 2026
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4 changes: 2 additions & 2 deletions src/sources/infer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -386,14 +386,14 @@ def _build_resolution_file(

@staticmethod
def _finalize_resolution_df(df: pd.DataFrame) -> DataFrame[ResolutionFrame]:

@houtanb houtanb Jun 10, 2026

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Should this return pd.DataFrame now that validation has moved to UpdateResult.__post_init__? Currently DataFrame[ResolutionFrame] implies this helper returns a validated schema.

@houtanb houtanb Jun 10, 2026

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Same question for:

    def _build_resolution_file(
        self,
        question: dict,
        resolved: bool,
        existing_df: DataFrame[ResolutionFrame] | None = None,
    ) -> DataFrame[ResolutionFrame]:

@nikbpetrov nikbpetrov Jun 10, 2026

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I want to keep the annotation for readability reasons. I appreciate the implicitness of the annotation but it's not decorated with @pa.check_types so validation does not apply.

"""Apply date filtering and return as validated ResolutionFrame.
"""Apply date filtering and select resolution columns.

Args:
df (pd.DataFrame): Raw resolution data with id, date, value columns.
"""
df["date"] = pd.to_datetime(df["date"])
df = df[df["date"].dt.date >= constants.BENCHMARK_START_DATE_DATETIME_DATE]
return ResolutionFrame.validate(df[["id", "date", "value"]])
return df[["id", "date", "value"]].astype(dtype=constants.RESOLUTION_FILE_COLUMN_DTYPE)

# ------------------------------------------------------------------
# Private: question transformation
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5 changes: 2 additions & 3 deletions src/sources/manifold.py
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Expand Up @@ -407,11 +407,10 @@ def _build_resolution_file(

@staticmethod
def _finalize_resolution_df(df: pd.DataFrame) -> DataFrame[ResolutionFrame]:
"""Filter to benchmark period and validate as ResolutionFrame."""
"""Filter to benchmark period and select resolution columns."""
df["date"] = pd.to_datetime(df["date"])
df = df[df["date"].dt.date >= constants.BENCHMARK_START_DATE_DATETIME_DATE]
df = df[["id", "date", "value"]].astype(dtype=constants.RESOLUTION_FILE_COLUMN_DTYPE)
return ResolutionFrame.validate(df)
return df[["id", "date", "value"]].astype(dtype=constants.RESOLUTION_FILE_COLUMN_DTYPE)

@staticmethod
def _get_resolved_market_value(market: dict) -> float:
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5 changes: 2 additions & 3 deletions src/sources/metaculus.py
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Expand Up @@ -446,7 +446,7 @@ def set_date(end_datetime):

@staticmethod
def _finalize_resolution_df(df: pd.DataFrame) -> DataFrame[ResolutionFrame]:
"""Cast types and return as a validated ResolutionFrame.
"""Cast types and select resolution columns.

Unlike infer/manifold, Metaculus does not filter to the benchmark start date:
the aggregation history is already bounded by the question's open window, and
Expand All @@ -455,5 +455,4 @@ def _finalize_resolution_df(df: pd.DataFrame) -> DataFrame[ResolutionFrame]:
Args:
df (pd.DataFrame): Raw resolution data with id, date, value columns.
"""
df = df[["id", "date", "value"]].astype(dtype=constants.RESOLUTION_FILE_COLUMN_DTYPE)
return ResolutionFrame.validate(df)
return df[["id", "date", "value"]].astype(dtype=constants.RESOLUTION_FILE_COLUMN_DTYPE)
2 changes: 1 addition & 1 deletion src/sources/polymarket.py
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Expand Up @@ -547,4 +547,4 @@ def _build_resolution_file(self, question: dict) -> DataFrame[ResolutionFrame]:
df = pd.DataFrame(question["historical_prices"])
df["id"] = question["id"]
df = df[["id", "date", "value"]].astype(dtype=constants.RESOLUTION_FILE_COLUMN_DTYPE)
return ResolutionFrame.validate(df)
return df
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