lisa.trace: Save dataframe custom attrs to parquet

Use a workaround until this ENH is implemented:
pandas-dev/pandas#20521

lisa/trace.py

@@ -47,6 +47,7 @@
 import pandas as pd
 from pandas.api.types import is_numeric_dtype
 import pyarrow.lib
+import pyarrow.parquet
 
 import devlib
 
@@ -2826,11 +2827,51 @@ def _update_swap_cost(self, data, swap_cost, mem_usage, swap_size):
     def _is_written_to_swap(self, pd_desc):
         return pd_desc.normal_form in self._swap_content
 
+    @staticmethod
+    def _data_to_parquet(data, path, **kwargs):
+        """
+        Equivalent to `df.to_parquet(...)` but workaround until pandas can save
+        attrs to parquet on its own: ENH request on pandas:
+        https://github.com/pandas-dev/pandas/issues/20521
+
+        Workaround:
+        https://github.com/pandas-dev/pandas/pull/20534#issuecomment-453236538
+        """
+        if isinstance(data, pd.DataFrame):
+            # Data must be convertible to bytes so we dump them as JSON
+            attrs = json.dumps(data.attrs)
+            table = pyarrow.Table.from_pandas(data)
+            updated_metadata = dict(
+                table.schema.metadata or {},
+                lisa=attrs,
+            )
+            table = table.replace_schema_metadata(updated_metadata)
+            pyarrow.parquet.write_table(table, path, **kwargs)
+        else:
+            data.to_parquet(path, **kwargs)
+
+    @staticmethod
+    def _data_from_parquet(path):
+        """
+        Equivalent to `pd.read_parquet(...)` but also load the metadata back
+        into dataframes's attrs
+        """
+        data = pd.read_parquet(path)
+
+        # Load back LISA metadata into "df.attrs", as they were written in
+        # _data_to_parquet()
+        if isinstance(data, pd.DataFrame):
+            schema = pyarrow.parquet.read_schema(path)
+            attrs = schema.metadata.get(b'lisa', '{}')
+            data.attrs = json.loads(attrs)
+
+        return data
+
     @classmethod
     def _write_data(cls, data, path):
         if cls.DATAFRAME_SWAP_FORMAT == 'parquet':
             # Snappy compression seems very fast
-            data.to_parquet(path, compression='snappy', index=True)
+            cls._data_to_parquet(data, path, compression='snappy')
         else:
             raise ValueError(f'Dataframe swap format "{cls.DATAFRAME_SWAP_FORMAT}" not handled')
 
@@ -2974,7 +3015,7 @@ def fetch(self, pd_desc, insert=True):
                 # Try to load the dataframe from that path
                 try:
                     if self.DATAFRAME_SWAP_FORMAT == 'parquet':
-                        data = pd.read_parquet(path)
+                        data = self._data_from_parquet(path)
                     else:
                         raise ValueError(f'Dataframe swap format "{self.DATAFRAME_SWAP_FORMAT}" not handled')
                 except (OSError, pyarrow.lib.ArrowIOError):