Loading src/lsst_inaf_agile/catalog_combined.py +38 −0 Original line number Diff line number Diff line Loading @@ -489,3 +489,41 @@ class CatalogCombined: area_deg2=self.get_area(), nmin=nmin, ) def write_database( self, name_table: str, filename_database: str, debug=False, blocksize=4096, *args, **kwargs ): """ Write the combined catalog into a sqlite3 database table. Parameters ---------- name_table: str name of the database table filename_database: str filename of the sqlite3 database """ import sqlite3 from astropy.table import Table if os.path.exists(filename_database): raise FileExistsError(f"Filename {filename_database} exists. Will not overwrite.") with sqlite3.connect(filename_database) as con: for fst in range(0, len(self.catalog_combined), blocksize): lst = fst + blocksize logger.info(f"ingesting {filename_database} {name_table} {fst} {lst} ...") df = Table(self.catalog_combined[fst:lst]).to_pandas() df = df.reset_index(drop=True) df.to_sql( f"{name_table}", con, index=False, if_exists="append", chunksize=1024, method="multi", ) return df Loading
src/lsst_inaf_agile/catalog_combined.py +38 −0 Original line number Diff line number Diff line Loading @@ -489,3 +489,41 @@ class CatalogCombined: area_deg2=self.get_area(), nmin=nmin, ) def write_database( self, name_table: str, filename_database: str, debug=False, blocksize=4096, *args, **kwargs ): """ Write the combined catalog into a sqlite3 database table. Parameters ---------- name_table: str name of the database table filename_database: str filename of the sqlite3 database """ import sqlite3 from astropy.table import Table if os.path.exists(filename_database): raise FileExistsError(f"Filename {filename_database} exists. Will not overwrite.") with sqlite3.connect(filename_database) as con: for fst in range(0, len(self.catalog_combined), blocksize): lst = fst + blocksize logger.info(f"ingesting {filename_database} {name_table} {fst} {lst} ...") df = Table(self.catalog_combined[fst:lst]).to_pandas() df = df.reset_index(drop=True) df.to_sql( f"{name_table}", con, index=False, if_exists="append", chunksize=1024, method="multi", ) return df