Merge pull request #24 from B612-Asteroid-Institute/nt/remove_pandera

After running bump-pydantic

cutouts/filter.py

@@ -1,17 +1,15 @@
 import logging
 
 import numpy as np
-import pandera as pa
-from pandera.typing import DataFrame
+import pandas as pd
 
-from .io.types import CutoutRequest, CutoutResult, CutoutsResultSchema
+from .io.types import CutoutRequest, CutoutResult
 
 logger = logging.getLogger(__file__)
 
 
-@pa.check_types
 def select_cutout(
-    results_df: DataFrame[CutoutsResultSchema], cutout_request: CutoutRequest
+    results_df: pd.DataFrame, cutout_request: CutoutRequest
 ) -> CutoutResult:
     """
     Select the cutout closest to the requested exposure start time +- delta_time.
@@ -91,9 +89,8 @@ def select_cutout(
     return result
 
 
-@pa.check_types
 def select_comparison_cutout(
-    results_df: DataFrame[CutoutsResultSchema],
+    results_df: pd.DataFrame,
     cutout_result: CutoutResult,
     cutout_request: CutoutRequest,
     min_time_separation: float = 1 / 24,

cutouts/io/nsc.py

@@ -1,11 +1,10 @@
 import logging
 
-import pandera as pa
-from pandera.typing import DataFrame
+import pandas as pd
 from pyvo.dal.sia import SIAResults
 
 from .sia import SIAHandler
-from .types import CutoutRequest, CutoutsResultSchema
+from .types import CutoutRequest
 from .util import exposure_id_from_url
 
 logger = logging.getLogger(__name__)
@@ -16,10 +15,9 @@ def _get_generic_image_url_from_cutout_url(cutout_url: str):
     return cutout_url.split("&POS=")[0]
 
 
-@pa.check_types
 def find_cutouts_nsc_dr2(
     cutout_request: CutoutRequest,
-) -> DataFrame[CutoutsResultSchema]:
+) -> pd.DataFrame:
     """
     Search the NOIRLab Archive for cutouts and images at a given RA, Dec.
 

cutouts/io/skymapper.py

@@ -1,12 +1,10 @@
 import logging
 
 import pandas as pd
-import pandera as pa
-from pandera.typing import DataFrame
 from pyvo.dal.sia import SIAResults
 
 from .sia import SIAHandler
-from .types import CutoutRequest, CutoutsResultSchema
+from .types import CutoutRequest
 
 logger = logging.getLogger(__name__)
 
@@ -22,10 +20,9 @@ def _get_generic_image_url_from_cutout_url(cutout_url: str):
     return url_string
 
 
-@pa.check_types
 def find_cutouts_skymapper_dr2(
     cutout_request: CutoutRequest,
-) -> DataFrame[CutoutsResultSchema]:
+) -> pd.DataFrame:
     """
     Search the Skymapper SIA service for cutouts and images at a given RA, Dec.
 

cutouts/io/tests/test_nsc_dr2.py

@@ -1,15 +1,11 @@
 import os
 from contextlib import contextmanager
 from unittest.mock import patch
-import pathlib
-import pickle
-import pandas as pd
 
 from astropy.io.votable import parse
 from pyvo.dal.sia import SIAResults
 
 from ..nsc import NSC_DR2_SIA, find_cutouts_nsc_dr2
-from ...main import get_cutouts
 from ..types import CutoutRequest
 
 # 2014 HE199 (2014-04-28T08:07:52.435)
@@ -44,7 +40,6 @@ def mock_sia_nsc_dr2_query(table_file: str):
 
 
 def test_sia_nsc_dr2_query():
-
     with mock_sia_nsc_dr2_query(
         "nsc_dr2_227.5251615214173_-27.026013823449265_56775.33880132809.xml"
     ) as mock:
@@ -71,23 +66,3 @@ def test_sia_nsc_dr2_query():
             assert col in results.columns
 
         assert "VR" in results["filter"].values
-
-
-def test_sia_nsc_dr2_query_():
-
-    with mock_sia_nsc_dr2_query(
-        "nsc_dr2_227.5251615214173_-27.026013823449265_56775.33880132809.xml"
-    ) as mock:
-        results, comparison_results = get_cutouts(
-            pd.DataFrame(cutout_request1),
-            out_dir=pathlib.Path(os.path.dirname(os.path.abspath(__file__)))
-        )
-        print(results)
-        print(comparison_results)
-
-        with open('cutout_results.pickle', 'wb') as f:
-            pickle.dump(results, f)
-        with open('cutout_comparison_results.pickle', 'wb') as f:
-            pickle.dump(comparison_results, f)
-
-        assert False

cutouts/io/types.py

@@ -1,63 +1,21 @@
 from typing import Optional
 
-import pandera as pa
-from pandera.typing import Series
 from pydantic import BaseModel
 
 
-class CutoutRequestSchema(pa.SchemaModel):
-    """
-    Dataframe validation for multiple cutout requests
-    """
-
-    request_id: Optional[Series[str]] = pa.Field(nullable=True)
-    observatory_code: Series[str] = pa.Field(coerce=True)
-    exposure_start_mjd: Series[float] = pa.Field(nullable=False, coerce=True)
-    ra_deg: Series[float] = pa.Field(ge=0, le=360, coerce=True)
-    dec_deg: Series[float] = pa.Field(ge=-90, le=90, coerce=True)
-    filter: Optional[
-        Series[str]
-    ] = pa.Field()  # TODO: validate against real list of filters?
-    exposure_id: Optional[Series[str]] = pa.Field(nullable=True)
-    exposure_duration: Optional[Series[float]] = pa.Field(
-        ge=0, le=2000, coerce=True, nullable=True
-    )
-    height_arcsec: Series[float] = pa.Field(ge=0, le=200, coerce=True, nullable=True)
-    width_arcsec: Series[float] = pa.Field(ge=0, le=200, coerce=True, nullable=True)
-    delta_time: Series[float] = pa.Field(ge=0, le=100, coerce=True, nullable=True)
-
-
-class CutoutsResultSchema(pa.SchemaModel):
-    # TODO: ra, dec here are the ra, dec returned by the query and
-    # these should be equal to the queried ra and dec.
-    # However, this may not always be true and we may want to consider
-    # adding additional fields to allow backends to return things such as the
-    # the center of the image/cutout.
-    ra_deg: Series[float] = pa.Field(ge=0, le=360, coerce=True)
-    dec_deg: Series[float] = pa.Field(ge=-90, le=90, coerce=True)
-    filter: Series[str] = pa.Field()
-    exposure_id: Series[str] = pa.Field()
-    exposure_start_mjd: Series[float] = pa.Field(nullable=False, coerce=True)
-    exposure_duration: Series[float] = pa.Field(ge=0, le=2000, coerce=True)
-    cutout_url: Series[str] = pa.Field(coerce=True)
-    image_url: Series[str] = pa.Field(coerce=True)
-    height_arcsec: Series[float] = pa.Field(ge=0, le=200, coerce=True)
-    width_arcsec: Series[float] = pa.Field(ge=0, le=200, coerce=True)
-
-
 class CutoutRequest(BaseModel):
     """
     A single cutout request
     """
 
-    request_id: Optional[str]
+    request_id: Optional[str] = None
     observatory_code: str
     exposure_start_mjd: float
     ra_deg: float
     dec_deg: float
-    filter: Optional[str]
-    exposure_id: Optional[str]
-    exposure_duration: Optional[float]
+    filter: Optional[str] = None
+    exposure_id: Optional[str] = None
+    exposure_duration: Optional[float] = None
     height_arcsec: float
     width_arcsec: float
     delta_time: float
@@ -69,13 +27,13 @@ class CutoutResult(BaseModel):
     """
 
     cutout_url: str
-    dec_deg: Optional[float]
+    dec_deg: Optional[float] = None
     exposure_duration: float
-    exposure_id: Optional[str]
+    exposure_id: Optional[str] = None
     exposure_start_mjd: float
-    filter: Optional[str]
+    filter: Optional[str] = None
     height_arcsec: float
     image_url: str
-    ra_deg: Optional[float]
-    request_id: Optional[str]
+    ra_deg: Optional[float] = None
+    request_id: Optional[str] = None
     width_arcsec: float

cutouts/io/ztf.py

@@ -5,11 +5,9 @@
 import backoff
 import numpy as np
 import pandas as pd
-import pandera as pa
 import requests
-from pandera.typing import DataFrame
 
-from .types import CutoutRequest, CutoutsResultSchema
+from .types import CutoutRequest
 
 logger = logging.getLogger(__file__)
 
@@ -83,8 +81,7 @@ def perform_request(search_url):
     return response.text
 
 
-@pa.check_types()
-def find_cutouts_ztf(cutout_request: CutoutRequest) -> DataFrame[CutoutsResultSchema]:
+def find_cutouts_ztf(cutout_request: CutoutRequest) -> pd.DataFrame:
     """
     Search the ZTF service for cutouts and images at a given RA, Dec.