def query(self, query: peewee.ModelSelect) -> dict:
"""Custom query, returns a generator that will return
a dictionary (corresponding to a row).
Parameters:
query (peewee.ModelSelect) : Custom query.
"""
for res in query.dicts():
yield res
def query_to_pandas(self, query: peewee.ModelSelect, array_cols: list = None) -> pd.DataFrame:
"""Convert a model query to a pandas dataframe."""
df = pd.DataFrame(query.dicts())
if not array_cols:
array_cols = self._array_types # Try to use the new data to infer what the format should be
# Convert array columns to numpy arrays. Leave as string if not specified
if array_cols:
for key in array_cols:
df[key] = df.apply(lambda x: np.array(ast.literal_eval(x[key]), dtype=x[f'{key}_dtype']), axis=1)
df.drop(f'{key}_dtype', axis=1, inplace=True)
return df
def _query_to_dataframe(cls, query: peewee.ModelSelect) -> pd.DataFrame:
dict_query = {indice: row for indice, row in enumerate(query.dicts())}
return pd.DataFrame.from_dict(dict_query, orient='index')