diff --git a/pyerrors/input/pandas.py b/pyerrors/input/pandas.py index 388ca680..62cf5ed9 100644 --- a/pyerrors/input/pandas.py +++ b/pyerrors/input/pandas.py @@ -22,7 +22,7 @@ def to_sql(df, table_name, db, if_exists="replace", gz=True): gz : bool If True the json strings are gzipped. """ - se_df = pe.input.pandas.serialize_df(df, gz=gz) + se_df = _serialize_df(df, gz=gz) con = sqlite3.connect(db) se_df.to_sql(table_name, con, if_exists=if_exists) con.close() @@ -44,7 +44,7 @@ def read_sql_query(sql, db, auto_gamma=False): con = sqlite3.connect(db) extract_df = pd.read_sql_query(sql, con) con.close() - return pe.input.pandas.deserialize_df(extract_df, auto_gamma=auto_gamma) + return _deserialize_df(extract_df, auto_gamma=auto_gamma) def dump_df(df, fname, gz=True): @@ -62,7 +62,7 @@ def dump_df(df, fname, gz=True): gz : bool If True, the output is a gzipped csv file. If False, the output is a csv file. """ - out = serialize_df(df, gz=False) + out = _serialize_df(df, gz=False) if not fname.endswith('.csv'): fname += '.csv' @@ -101,10 +101,10 @@ def load_df(fname, auto_gamma=False, gz=True): warnings.warn("Trying to read from %s without unzipping!" % fname, UserWarning) re_import = pd.read_csv(fname) - return deserialize_df(re_import, auto_gamma=auto_gamma) + return _deserialize_df(re_import, auto_gamma=auto_gamma) -def serialize_df(df, gz=False): +def _serialize_df(df, gz=False): """Serializes all Obs or Corr valued columns into json strings according to the pyerrors json specification. Parameters @@ -123,7 +123,7 @@ def serialize_df(df, gz=False): return out -def deserialize_df(df, auto_gamma=False): +def _deserialize_df(df, auto_gamma=False): """Deserializes all pyerrors json strings into Obs or Corr objects according to the pyerrors json specification. Parameters diff --git a/tests/pandas_test.py b/tests/pandas_test.py index dec98456..059010c9 100644 --- a/tests/pandas_test.py +++ b/tests/pandas_test.py @@ -48,6 +48,6 @@ def test_gz_serialization(): my_obs = pe.pseudo_Obs(0.1, 0.01, "pandas DataFrame ensemble only for test purposes.") my_df = pd.DataFrame([{"Label": 1, "Obs": my_obs}]) for gz in [False, True]: - ser = pe.input.pandas.serialize_df(my_df, gz=gz) - deser = pe.input.pandas.deserialize_df(ser) + ser = pe.input.pandas._serialize_df(my_df, gz=gz) + deser = pe.input.pandas._deserialize_df(ser) np.all(my_df == deser)