Initial commitv3.3.4

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diff --git a/tests/incite/schemas/test_admin_responses.py b/tests/incite/schemas/test_admin_responses.py
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+++ b/tests/incite/schemas/test_admin_responses.py
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+from datetime import datetime, timezone, timedelta
+from random import sample
+from typing import List
+
+import numpy as np
+import pandas as pd
+import pytest
+
+from generalresearch.incite.schemas import empty_dataframe_from_schema
+from generalresearch.incite.schemas.admin_responses import (
+    AdminPOPSchema,
+    SIX_HOUR_SECONDS,
+)
+from generalresearch.locales import Localelator
+
+
+class TestAdminPOPSchema:
+    schema_df = empty_dataframe_from_schema(AdminPOPSchema)
+    countries = list(Localelator().get_all_countries())[:5]
+    dates = [datetime(year=2024, month=1, day=i, tzinfo=None) for i in range(1, 10)]
+
+    @classmethod
+    def assign_valid_vals(cls, df: pd.DataFrame) -> pd.DataFrame:
+        for c in df.columns:
+            check_attrs: dict = AdminPOPSchema.columns[c].checks[0].statistics
+            df[c] = np.random.randint(
+                check_attrs["min_value"], check_attrs["max_value"], df.shape[0]
+            )
+
+        return df
+
+    def test_empty(self):
+        with pytest.raises(Exception):
+            AdminPOPSchema.validate(pd.DataFrame())
+
+    def test_new_empty_df(self):
+        df = empty_dataframe_from_schema(AdminPOPSchema)
+
+        assert isinstance(df, pd.DataFrame)
+        assert isinstance(df.index, pd.MultiIndex)
+        assert df.columns.size == len(AdminPOPSchema.columns)
+
+    def test_valid(self):
+        # (1) Works with raw naive datetime
+        dates = [
+            datetime(year=2024, month=1, day=i, tzinfo=None).isoformat()
+            for i in range(1, 10)
+        ]
+        df = pd.DataFrame(
+            index=pd.MultiIndex.from_product(
+                iterables=[dates, self.countries], names=["index0", "index1"]
+            ),
+            columns=self.schema_df.columns,
+        )
+        df = self.assign_valid_vals(df)
+
+        df = AdminPOPSchema.validate(df)
+        assert isinstance(df, pd.DataFrame)
+
+        # (2) Works with isoformat naive datetime
+        dates = [datetime(year=2024, month=1, day=i, tzinfo=None) for i in range(1, 10)]
+        df = pd.DataFrame(
+            index=pd.MultiIndex.from_product(
+                iterables=[dates, self.countries], names=["index0", "index1"]
+            ),
+            columns=self.schema_df.columns,
+        )
+        df = self.assign_valid_vals(df)
+
+        df = AdminPOPSchema.validate(df)
+        assert isinstance(df, pd.DataFrame)
+
+    def test_index_tz_parser(self):
+        tz_dates = [
+            datetime(year=2024, month=1, day=i, tzinfo=timezone.utc)
+            for i in range(1, 10)
+        ]
+
+        df = pd.DataFrame(
+            index=pd.MultiIndex.from_product(
+                iterables=[tz_dates, self.countries], names=["index0", "index1"]
+            ),
+            columns=self.schema_df.columns,
+        )
+        df = self.assign_valid_vals(df)
+
+        # Initially, they're all set with a timezone
+        timestmaps: List[pd.Timestamp] = [i for i in df.index.get_level_values(0)]
+        assert all([ts.tz == timezone.utc for ts in timestmaps])
+
+        # After validation, the timezone is removed
+        df = AdminPOPSchema.validate(df)
+        timestmaps: List[pd.Timestamp] = [i for i in df.index.get_level_values(0)]
+        assert all([ts.tz is None for ts in timestmaps])
+
+    def test_index_tz_no_future_beyond_one_year(self):
+        now = datetime.now(tz=timezone.utc)
+        tz_dates = [now + timedelta(days=i * 365) for i in range(1, 10)]
+
+        df = pd.DataFrame(
+            index=pd.MultiIndex.from_product(
+                iterables=[tz_dates, self.countries], names=["index0", "index1"]
+            ),
+            columns=self.schema_df.columns,
+        )
+        df = self.assign_valid_vals(df)
+
+        with pytest.raises(Exception) as cm:
+            AdminPOPSchema.validate(df)
+
+        assert (
+            "Index 'index0' failed element-wise validator "
+            "number 0: less_than(" in str(cm.value)
+        )
+
+    def test_index_only_str(self):
+        # --- float64 to str! ---
+        df = pd.DataFrame(
+            index=pd.MultiIndex.from_product(
+                iterables=[self.dates, np.random.rand(1, 10)[0]],
+                names=["index0", "index1"],
+            ),
+            columns=self.schema_df.columns,
+        )
+        df = self.assign_valid_vals(df)
+
+        vals = [i for i in df.index.get_level_values(1)]
+        assert all([isinstance(v, float) for v in vals])
+
+        df = AdminPOPSchema.validate(df, lazy=True)
+
+        vals = [i for i in df.index.get_level_values(1)]
+        assert all([isinstance(v, str) for v in vals])
+
+        # --- int to str ---
+
+        df = pd.DataFrame(
+            index=pd.MultiIndex.from_product(
+                iterables=[self.dates, sample(range(100), 20)],
+                names=["index0", "index1"],
+            ),
+            columns=self.schema_df.columns,
+        )
+        df = self.assign_valid_vals(df)
+
+        vals = [i for i in df.index.get_level_values(1)]
+        assert all([isinstance(v, int) for v in vals])
+
+        df = AdminPOPSchema.validate(df, lazy=True)
+
+        vals = [i for i in df.index.get_level_values(1)]
+        assert all([isinstance(v, str) for v in vals])
+
+        # a = 1
+        assert isinstance(df, pd.DataFrame)
+
+    def test_invalid_parsing(self):
+        # (1) Timezones AND as strings will still parse correctly
+        tz_str_dates = [
+            datetime(
+                year=2024, month=1, day=1, minute=i, tzinfo=timezone.utc
+            ).isoformat()
+            for i in range(1, 10)
+        ]
+        df = pd.DataFrame(
+            index=pd.MultiIndex.from_product(
+                iterables=[tz_str_dates, self.countries],
+                names=["index0", "index1"],
+            ),
+            columns=self.schema_df.columns,
+        )
+        df = self.assign_valid_vals(df)
+        df = AdminPOPSchema.validate(df, lazy=True)
+
+        assert isinstance(df, pd.DataFrame)
+        timestmaps: List[pd.Timestamp] = [i for i in df.index.get_level_values(0)]
+        assert all([ts.tz is None for ts in timestmaps])
+
+        # (2) Timezones are removed
+        dates = [
+            datetime(year=2024, month=1, day=1, minute=i, tzinfo=timezone.utc)
+            for i in range(1, 10)
+        ]
+        df = pd.DataFrame(
+            index=pd.MultiIndex.from_product(
+                iterables=[dates, self.countries], names=["index0", "index1"]
+            ),
+            columns=self.schema_df.columns,
+        )
+        df = self.assign_valid_vals(df)
+
+        # Has tz before validation, and none after
+        timestmaps: List[pd.Timestamp] = [i for i in df.index.get_level_values(0)]
+        assert all([ts.tz is timezone.utc for ts in timestmaps])
+
+        df = AdminPOPSchema.validate(df, lazy=True)
+
+        timestmaps: List[pd.Timestamp] = [i for i in df.index.get_level_values(0)]
+        assert all([ts.tz is None for ts in timestmaps])
+
+    def test_clipping(self):
+        df = pd.DataFrame(
+            index=pd.MultiIndex.from_product(
+                iterables=[self.dates, self.countries],
+                names=["index0", "index1"],
+            ),
+            columns=self.schema_df.columns,
+        )
+        df = self.assign_valid_vals(df)
+        df = AdminPOPSchema.validate(df)
+        assert df.elapsed_avg.max() < SIX_HOUR_SECONDS
+
+        # Now that we know it's valid, break the elapsed avg
+        df["elapsed_avg"] = np.random.randint(
+            SIX_HOUR_SECONDS, SIX_HOUR_SECONDS + 10_000, df.shape[0]
+        )
+        assert df.elapsed_avg.max() > SIX_HOUR_SECONDS
+
+        # Confirm it doesn't fail if the values are greater, and that
+        #   all the values are clipped to the max
+        df = AdminPOPSchema.validate(df)
+        assert df.elapsed_avg.eq(SIX_HOUR_SECONDS).all()
+
+    def test_rounding(self):
+        df = pd.DataFrame(
+            index=pd.MultiIndex.from_product(
+                iterables=[self.dates, self.countries],
+                names=["index0", "index1"],
+            ),
+            columns=self.schema_df.columns,
+        )
+        df = self.assign_valid_vals(df)
+
+        df["payout_avg"] = 2.123456789900002
+
+        assert df.payout_avg.sum() == 95.5555555455001
+
+        df = AdminPOPSchema.validate(df)
+        assert df.payout_avg.sum() == 95.40000000000003