remove provenance machinery for now

src/tape/ensemble.py

@@ -69,7 +69,6 @@ def __init__(self, client=True, **kwargs):
         self._flux_col = None
         self._err_col = None
         self._band_col = None
-        self._provenance_col = None
 
         self.client = None
         self.cleanup_client = False
@@ -256,7 +255,6 @@ def insert_sources(
         timestamps,
         fluxes,
         flux_errs=None,
-        provenance_label="custom",
         force_repartition=False,
         **kwargs,
     ):
@@ -282,8 +280,6 @@ def insert_sources(
             A list of the fluxes of the observations.
         flux_errs: `list`, optional
             A list of the errors in the flux.
-        provenance_label: `str`, optional
-            A label that denotes the provenance of the new observations.
         force_repartition: `bool` optional
             Do an immediate repartition of the dataframes.
         """
@@ -302,16 +298,12 @@ def insert_sources(
                 f"Incorrect flux_errs length during insert" f"{num_inserting} != {len(flux_errs)}"
             )
 
-        # Construct provenance array
-        provenance = [provenance_label] * len(obj_ids)
-
         # Create a dictionary with the new information.
         rows = {
             self._id_col: obj_ids,
             self._band_col: bands,
             self._time_col: timestamps,
             self._flux_col: fluxes,
-            self._provenance_col: provenance,
         }
         if flux_errs is not None:
             rows[self._err_col] = flux_errs
@@ -1350,7 +1342,6 @@ def make_column_map(self):
             flux_col=self._flux_col,
             err_col=self._err_col,
             band_col=self._band_col,
-            provenance_col=self._provenance_col,
         )
         return result
 
@@ -1408,11 +1399,6 @@ def _load_column_mapper(self, column_mapper, **kwargs):
             self._flux_col = column_mapper.map["flux_col"]
             self._err_col = column_mapper.map["err_col"]
             self._band_col = column_mapper.map["band_col"]
-
-            # Assign optional columns if provided
-            if column_mapper.map["provenance_col"] is not None:
-                self._provenance_col = column_mapper.map["provenance_col"]
-
         else:
             raise ValueError(f"Missing required column mapping information: {needed}")
 
@@ -1423,7 +1409,6 @@ def from_parquet(
         source_file,
         object_file=None,
         column_mapper=None,
-        provenance_label="survey_1",
         sync_tables=True,
         additional_cols=True,
         npartitions=None,
@@ -1446,8 +1431,6 @@ def from_parquet(
         column_mapper: 'ColumnMapper' object
             If provided, the ColumnMapper is used to populate relevant column
             information mapped from the input dataset.
-        provenance_label: 'str', optional
-            Determines the label to use if a provenance column is generated
         sync_tables: 'bool', optional
             In the case where object files are loaded in, determines whether an
             initial sync is performed between the object and source tables. If
@@ -1484,20 +1467,13 @@ def from_parquet(
             columns = None  # None will prompt read_parquet to read in all cols
         else:
             columns = [self._time_col, self._flux_col, self._err_col, self._band_col]
-            if self._provenance_col is not None:
-                columns.append(self._provenance_col)
 
         # Read in the source parquet file(s)
         # Index is set False so that we can set it with a future set_index call
         # This has the advantage of letting Dask set partition boundaries based
         # on the divisions between the sources of different objects.
         source = SourceFrame.from_parquet(source_file, index=False, columns=columns, ensemble=self)
 
-        # Generate a provenance column if not provided
-        if self._provenance_col is None:
-            source["provenance"] = provenance_label
-            self._provenance_col = "provenance"
-
         object = None
         if object_file:
             # Read in the object file(s)
@@ -1550,7 +1526,6 @@ def from_dataset(self, dataset, **kwargs):
             source_file=dataset_info["source_file"],
             object_file=dataset_info["object_file"],
             column_mapper=col_map,
-            provenance_label=dataset,
             **kwargs,
         )
 

src/tape/ensemble_readers.py

@@ -132,7 +132,6 @@ def read_parquet(
     object_file=None,
     column_mapper=None,
     dask_client=True,
-    provenance_label="survey_1",
     sync_tables=True,
     additional_cols=True,
     npartitions=None,
@@ -158,8 +157,6 @@ def read_parquet(
         `client=True`, passing any additional kwargs to a
         dask.distributed.Client constructor call. If `client=False`, the
         Ensemble is created without a distributed client.
-    provenance_label: 'str', optional
-        Determines the label to use if a provenance column is generated
     sync_tables: 'bool', optional
         In the case where object files are loaded in, determines whether an
         initial sync is performed between the object and source tables. If
@@ -188,7 +185,6 @@ def read_parquet(
         source_file=source_file,
         object_file=object_file,
         column_mapper=column_mapper,
-        provenance_label=provenance_label,
         sync_tables=sync_tables,
         additional_cols=additional_cols,
         npartitions=npartitions,
@@ -322,7 +318,6 @@ def read_dataset(dataset, dask_client=True, **kwargs):
         source_file=dataset_info["source_file"],
         object_file=dataset_info["object_file"],
         column_mapper=col_map,
-        provenance_label=dataset,
         dask_client=dask_client,
         **kwargs,
     )

src/tape/utils/column_mapper/column_mapper.py

@@ -11,7 +11,6 @@ def __init__(
         flux_col=None,
         err_col=None,
         band_col=None,
-        provenance_col=None,
     ):
         """
 
@@ -27,9 +26,6 @@ def __init__(
             Identifies which column contains the flux/mag error information
         band_col: 'str', optional
             Identifies which column contains the band information
-        provenance_col: 'str', optional
-            Identifies which column contains the provenance information, if
-            None the provenance column is generated.
 
         Returns
         -------
@@ -44,7 +40,6 @@ def __init__(
             "flux_col": flux_col,
             "err_col": err_col,
             "band_col": band_col,
-            "provenance_col": provenance_col,
         }
 
         self.required = [
@@ -53,7 +48,6 @@ def __init__(
             Column("flux_col", True),
             Column("err_col", True),
             Column("band_col", True),
-            Column("provenance_col", False),
         ]
 
         self.known_maps = {"ZTF": ZTFColumnMapper}
@@ -76,8 +70,8 @@ def use_known_map(self, map_id):
 
         Returns
         -------
-        A ColumnMapper subclass object dependent on the map_id provided, for example
-        ZTFColumnMapper in the case of "ZTF"
+        A ColumnMapper subclass object dependent on the map_id provided,
+        ZTFColumnMapper in the case of "ZTF" for example
 
         """
         if map_id in self.known_maps:
@@ -122,7 +116,6 @@ def assign(
         flux_col=None,
         err_col=None,
         band_col=None,
-        provenance_col=None,
     ):
         """Updates a given set of columns
 
@@ -144,17 +137,13 @@ def assign(
         nobs_tot_col: 'str', optional
             Identifies which column contains the total number of observations,
             if available in the input object file
-        provenance_col: 'str', optional
-            Identifies which column contains the provenance information, if
-            None the provenance column is generated.
         """
         assign_map = {
             "id_col": id_col,
             "time_col": time_col,
             "flux_col": flux_col,
             "err_col": err_col,
             "band_col": band_col,
-            "provenance_col": provenance_col,
         }
 
         for item in assign_map.items():
@@ -175,7 +164,6 @@ def _set_known_map(self):
             "flux_col": "psFlux",
             "err_col": "psFluxErr",
             "band_col": "filterName",
-            "provenance_col": None,
         }
         return self
 

tests/tape_tests/test_ensemble.py

@@ -91,7 +91,6 @@ def test_parquet_construction(data_fixture, request):
         parquet_ensemble._flux_col,
         parquet_ensemble._err_col,
         parquet_ensemble._band_col,
-        parquet_ensemble._provenance_col,
     ]:
         # Check to make sure the critical quantity labels are bound to real columns
         assert parquet_ensemble.source[col] is not None
@@ -488,7 +487,6 @@ def test_insert(parquet_ensemble):
     flux_col = parquet_ensemble._flux_col
     err_col = parquet_ensemble._err_col
     band_col = parquet_ensemble._band_col
-    prov_col = parquet_ensemble._provenance_col
 
     # Test an insertion of 5 observations.
     new_inds = [2, 1, 100, 110, 111]
@@ -512,7 +510,6 @@ def test_insert(parquet_ensemble):
         assert new_source.loc[new_inds[i]][flux_col] == new_fluxes[i]
         assert new_source.loc[new_inds[i]][err_col] == new_errs[i]
         assert new_source.loc[new_inds[i]][band_col] == new_bands[i]
-        assert new_source.loc[new_inds[i]][prov_col] == "custom"
 
     # Check that all of the old data is still in there.
     obj_ids = old_source.index.unique()
@@ -553,7 +550,6 @@ def test_insert_paritioned(dask_client):
         flux_col="flux",
         err_col="err",
         band_col="band",
-        provenance_col="provenance",
     )
     ens.from_source_dict(rows, column_mapper=cmap, npartitions=4, sort=True)
 
@@ -725,14 +721,12 @@ def test_update_column_map(dask_client):
     assert cmap_1.map["flux_col"] == "flux"
     assert cmap_1.map["err_col"] == "err"
     assert cmap_1.map["band_col"] == "band"
-    assert cmap_1.map["provenance_col"] is None
 
     # Update the column map.
-    ens.update_column_mapping(flux_col="f2", provenance_col="p")
+    ens.update_column_mapping(flux_col="f2")
 
-    # Check that the flux and provenance columns have been updates.
+    # Check that the flux column has been updated.
     assert ens._flux_col == "f2"
-    assert ens._provenance_col == "p"
 
     # Check that we retrieve the updated column map.
     cmap_2 = ens.make_column_map()
@@ -741,7 +735,6 @@ def test_update_column_map(dask_client):
     assert cmap_2.map["flux_col"] == "f2"
     assert cmap_2.map["err_col"] == "err"
     assert cmap_2.map["band_col"] == "band"
-    assert cmap_2.map["provenance_col"] == "p"
 
 
 @pytest.mark.parametrize(

tests/tape_tests/test_utils.py

@@ -22,16 +22,12 @@ def test_column_mapper():
 
     assert col_map.is_ready()  # col_map should now be ready
 
-    # Assign the remaining columns
-    col_map.assign(provenance_col="provenance")
-
     expected_map = {
         "id_col": "id",
         "time_col": "time",
         "flux_col": "flux",
         "err_col": "err",
         "band_col": "band",
-        "provenance_col": "provenance",
     }
 
     assert col_map.map == expected_map  # The expected mapping
@@ -48,7 +44,6 @@ def test_column_mapper_init():
         flux_col="flux",
         err_col="err",
         band_col="band",
-        provenance_col="provenance",
     )
 
     assert col_map.is_ready()  # col_map should be ready
@@ -59,7 +54,6 @@ def test_column_mapper_init():
         "flux_col": "flux",
         "err_col": "err",
         "band_col": "band",
-        "provenance_col": "provenance",
     }
 
     assert col_map.map == expected_map  # The expected mapping