"""Module containing functions that work with sample data""" from typing import Any, Tuple, Dict, Callable import MySQLdb from gn3.csvcmp import extract_strain_name from gn3.csvcmp import parse_csv_column _MAP = { "PublishData": ("StrainId", "Id", "value"), "PublishSE": ("StrainId", "DataId", "error"), "NStrain": ("StrainId", "DataId", "count"), } def __extract_actions( original_data: str, updated_data: str, csv_header: str ) -> Dict: """Return a dictionary containing elements that need to be deleted, inserted, or updated. """ result: Dict[str, Any] = { "delete": {"data": [], "csv_header": []}, "insert": {"data": [], "csv_header": []}, "update": {"data": [], "csv_header": []}, } strain_name = "" for _o, _u, _h in zip( original_data.strip().split(","), updated_data.strip().split(","), csv_header.strip().split(","), ): if _h == "Strain Name": strain_name = _o if _o == _u: # No change continue if _o and _u == "x": # Deletion result["delete"]["data"].append(_o) result["delete"]["csv_header"].append(_h) elif _o == "x" and _u: # Insert result["insert"]["data"].append(_u) result["insert"]["csv_header"].append(_h) elif _o and _u: # Update result["update"]["data"].append(_u) result["update"]["csv_header"].append(_h) for key, val in result.items(): if not val["data"]: result[key] = None else: result[key]["data"] = f"{strain_name}," + ",".join( result[key]["data"] ) result[key]["csv_header"] = "Strain Name," + ",".join( result[key]["csv_header"] ) return result def get_trait_sample_data( conn: Any, trait_name: int, phenotype_id: int ) -> Dict: """Fetch a trait's sample data and return it as a dict""" with conn.cursor() as cursor: cursor.execute(""" SELECT st.Name, ifnull(pd.value, 'x'), ifnull(ps.error, 'x'), ifnull(ns.count, 'x') FROM PublishFreeze pf JOIN PublishXRef px ON px.InbredSetId = pf.InbredSetId JOIN PublishData pd ON pd.Id = px.DataId JOIN Strain st ON pd.StrainId = st.Id LEFT JOIN PublishSE ps ON ps.DataId = pd.Id AND ps.StrainId = pd.StrainId LEFT JOIN NStrain ns ON ns.DataId = pd.Id AND ns.StrainId = pd.StrainId WHERE px.Id = %s AND px.PhenotypeId = %s ORDER BY st.Name""", (trait_name, phenotype_id)) sample_data = {} for data in cursor.fetchall(): sample, value, error, n_cases = data sample_data[sample] = { 'value': value, 'error': error, 'n_cases:': n_cases } return sample_data def get_trait_csv_sample_data( conn: Any, trait_name: int, phenotype_id: int, sample_list: list ) -> str: """Fetch a trait and return it as a csv string""" with conn.cursor() as cursor: cursor.execute(""" SELECT DISTINCT st.Name, concat(st.Name, ',', ifnull(pd.value, 'x'), ',', ifnull(ps.error, 'x'), ',', ifnull(ns.count, 'x')) AS 'Data' FROM PublishFreeze pf JOIN PublishXRef px ON px.InbredSetId = pf.InbredSetId JOIN PublishData pd ON pd.Id = px.DataId JOIN Strain st ON pd.StrainId = st.Id LEFT JOIN PublishSE ps ON ps.DataId = pd.Id AND ps.StrainId = pd.StrainId LEFT JOIN NStrain ns ON ns.DataId = pd.Id AND ns.StrainId = pd.StrainId WHERE px.Id = %s AND px.PhenotypeId = %s ORDER BY st.Name""", (trait_name, phenotype_id)) if not (data := cursor.fetchall()): return "No Sample Data Found" # Get list of samples with data in the DB existing_samples = [el[0] for el in data] trait_csv = ["Strain Name,Value,SE,Count"] for sample in sample_list: if sample in existing_samples: trait_csv.append(data[existing_samples.index(sample)][1]) else: trait_csv.append(sample + ",x,x,x") return "\n".join(trait_csv) def get_sample_data_ids( conn: Any, publishxref_id: int, phenotype_id: int, strain_name: str ) -> Tuple: """Get the strain_id, publishdata_id and inbredset_id for a given strain""" strain_id, publishdata_id, inbredset_id = None, None, None with conn.cursor() as cursor: cursor.execute( "SELECT st.id, pd.Id, pf.InbredSetId " "FROM PublishData pd " "JOIN Strain st ON pd.StrainId = st.Id " "JOIN PublishXRef px ON px.DataId = pd.Id " "JOIN PublishFreeze pf ON pf.InbredSetId " "= px.InbredSetId WHERE px.Id = %s " "AND px.PhenotypeId = %s AND st.Name = %s", (publishxref_id, phenotype_id, strain_name), ) if _result := cursor.fetchone(): strain_id, publishdata_id, inbredset_id = _result if not all([strain_id, publishdata_id, inbredset_id]): # Applies for data to be inserted: cursor.execute( "SELECT DataId, InbredSetId FROM PublishXRef " "WHERE Id = %s AND PhenotypeId = %s", (publishxref_id, phenotype_id), ) publishdata_id, inbredset_id = cursor.fetchone() cursor.execute( "SELECT Id FROM Strain WHERE Name = %s", (strain_name,) ) strain_id = cursor.fetchone()[0] return (strain_id, publishdata_id, inbredset_id) # pylint: disable=[R0913, R0914] def update_sample_data( conn: Any, trait_name: str, original_data: str, updated_data: str, csv_header: str, phenotype_id: int, ) -> int: """Given the right parameters, update sample-data from the relevant table.""" def __update_data(conn, table, value): if value and value != "x": with conn.cursor() as cursor: sub_query = " = %s AND ".join(_MAP.get(table)[:2]) + " = %s" _val = _MAP.get(table)[-1] cursor.execute( (f"UPDATE {table} SET {_val} = %s " f"WHERE {sub_query}"), (value, strain_id, data_id), ) conn.commit() return cursor.rowcount return 0 def __update_case_attribute( conn, value, strain_id, case_attr, inbredset_id ): if value != "x": (id_, name) = parse_csv_column(case_attr) with conn.cursor() as cursor: if id_: cursor.execute( "UPDATE CaseAttributeXRefNew " "SET Value = %s " "WHERE StrainId = %s AND CaseAttributeId = %s " "AND InbredSetId = %s", (value, strain_id, id_, inbredset_id), ) else: cursor.execute( "UPDATE CaseAttributeXRefNew " "SET Value = %s " "WHERE StrainId = %s AND CaseAttributeId = " "(SELECT CaseAttributeId FROM " "CaseAttribute WHERE Name = %s) " "AND InbredSetId = %s", (value, strain_id, name, inbredset_id), ) conn.commit() return cursor.rowcount return 0 strain_id, data_id, inbredset_id = get_sample_data_ids( conn=conn, publishxref_id=int(trait_name), phenotype_id=phenotype_id, strain_name=extract_strain_name(csv_header, original_data), ) none_case_attrs: Dict[str, Callable] = { "Strain Name": lambda x: 0, "Value": lambda x: __update_data(conn, "PublishData", x), "SE": lambda x: __update_data(conn, "PublishSE", x), "Count": lambda x: __update_data(conn, "NStrain", x), } count = 0 try: __actions = __extract_actions( original_data=original_data, updated_data=updated_data, csv_header=csv_header, ) if __actions.get("update"): _csv_header = __actions["update"]["csv_header"] _data = __actions["update"]["data"] # pylint: disable=[E1101] for header, value in zip(_csv_header.split(","), _data.split(",")): header = header.strip() value = value.strip() if header in none_case_attrs: count += none_case_attrs[header](value) else: count += __update_case_attribute( conn=conn, value=value, strain_id=strain_id, case_attr=header, inbredset_id=inbredset_id, ) if __actions.get("delete"): _rowcount = delete_sample_data( conn=conn, trait_name=trait_name, data=__actions["delete"]["data"], csv_header=__actions["delete"]["csv_header"], phenotype_id=phenotype_id, ) if _rowcount: count += 1 if __actions.get("insert"): _rowcount = insert_sample_data( conn=conn, trait_name=trait_name, data=__actions["insert"]["data"], csv_header=__actions["insert"]["csv_header"], phenotype_id=phenotype_id, ) if _rowcount: count += 1 except Exception as _e: raise MySQLdb.Error(_e) from _e return count def delete_sample_data( conn: Any, trait_name: str, data: str, csv_header: str, phenotype_id: int ) -> int: """Given the right parameters, delete sample-data from the relevant tables.""" def __delete_data(conn, table): sub_query = " = %s AND ".join(_MAP.get(table)[:2]) + " = %s" with conn.cursor() as cursor: cursor.execute( (f"DELETE FROM {table} " f"WHERE {sub_query}"), (strain_id, data_id), ) conn.commit() return cursor.rowcount def __delete_case_attribute(conn, strain_id, case_attr, inbredset_id): with conn.cursor() as cursor: (id_, name) = parse_csv_column(case_attr) if id_: cursor.execute( "DELETE FROM CaseAttributeXRefNew " "WHERE StrainId = %s AND CaseAttributeId = %s " "AND InbredSetId = %s", (strain_id, id_, inbredset_id), ) else: cursor.execute( "DELETE FROM CaseAttributeXRefNew " "WHERE StrainId = %s AND CaseAttributeId = " "(SELECT CaseAttributeId FROM " "CaseAttribute WHERE Name = %s) " "AND InbredSetId = %s", (strain_id, name, inbredset_id), ) conn.commit() return cursor.rowcount strain_id, data_id, inbredset_id = get_sample_data_ids( conn=conn, publishxref_id=int(trait_name), phenotype_id=phenotype_id, strain_name=extract_strain_name(csv_header, data), ) none_case_attrs: Dict[str, Any] = { "Strain Name": lambda: 0, "Value": lambda: __delete_data(conn, "PublishData"), "SE": lambda: __delete_data(conn, "PublishSE"), "Count": lambda: __delete_data(conn, "NStrain"), } count = 0 try: for header in csv_header.split(","): header = header.strip() if header in none_case_attrs: count += none_case_attrs[header]() else: count += __delete_case_attribute( conn=conn, strain_id=strain_id, case_attr=header, inbredset_id=inbredset_id, ) except Exception as _e: raise MySQLdb.Error(_e) from _e return count # pylint: disable=[R0913, R0914] def insert_sample_data( conn: Any, trait_name: str, data: str, csv_header: str, phenotype_id: int ) -> int: """Given the right parameters, insert sample-data to the relevant table.""" def __insert_data(conn, table, value): if value and value != "x": with conn.cursor() as cursor: columns = ", ".join(_MAP.get(table)) cursor.execute( ( f"INSERT INTO {table} " f"({columns}) " f"VALUES (%s, %s, %s)" ), (strain_id, data_id, value), ) conn.commit() return cursor.rowcount return 0 def __insert_case_attribute(conn, case_attr, value): if value != "x": with conn.cursor() as cursor: (id_, name) = parse_csv_column(case_attr) if not id_: cursor.execute( "SELECT Id FROM CaseAttribute WHERE Name = %s", (name,), ) if case_attr_id := cursor.fetchone(): id_ = case_attr_id[0] cursor.execute( "SELECT StrainId FROM " "CaseAttributeXRefNew WHERE StrainId = %s " "AND CaseAttributeId = %s " "AND InbredSetId = %s", (strain_id, id_, inbredset_id), ) if (not cursor.fetchone()) and id_: cursor.execute( "INSERT INTO CaseAttributeXRefNew " "(StrainId, CaseAttributeId, Value, InbredSetId) " "VALUES (%s, %s, %s, %s)", (strain_id, id_, value, inbredset_id), ) row_count = cursor.rowcount conn.commit() return row_count conn.commit() return 0 strain_id, data_id, inbredset_id = get_sample_data_ids( conn=conn, publishxref_id=int(trait_name), phenotype_id=phenotype_id, strain_name=extract_strain_name(csv_header, data), ) none_case_attrs: Dict[str, Any] = { "Strain Name": lambda _: 0, "Value": lambda x: __insert_data(conn, "PublishData", x), "SE": lambda x: __insert_data(conn, "PublishSE", x), "Count": lambda x: __insert_data(conn, "NStrain", x), } try: count = 0 # Check if the data already exists: with conn.cursor() as cursor: cursor.execute( "SELECT Id FROM PublishData where Id = %s " "AND StrainId = %s", (data_id, strain_id)) data_exists = cursor.fetchone() if data_exists: # Data already exists return count for header, value in zip(csv_header.split(","), data.split(",")): header = header.strip() value = value.strip() if header in none_case_attrs: count += none_case_attrs[header](value) else: count += __insert_case_attribute( conn=conn, case_attr=header, value=value ) return count except Exception as _e: raise MySQLdb.Error(_e) from _e