Add support for pl.DataFrame in Logger.report_table

clearml/backend_interface/metrics/reporter.py

@@ -654,7 +654,7 @@ class Reporter(InterfaceBase, AbstractContextManager, SetupUploadMixin, AsyncMan
         :param series: Series (AKA variant)
         :type series: str
         :param table: The table data
-        :type table: pandas.DataFrame
+        :type table: pandas.DataFrame or polars.DataFrame
         :param iteration: Iteration number
         :type iteration: int
         :param layout_config: optional dictionary for layout configuration, passed directly to plotly

clearml/logger.py

@@ -10,6 +10,11 @@ from pathlib2 import Path
 
 from .debugging.log import LoggerRoot
 
+try:
+    import polars as pl
+except ImportError:
+    pl = None
+
 try:
     import pandas as pd
 except ImportError:
@@ -326,7 +331,7 @@ class Logger(object):
         title,  # type: str
         series,  # type: str
         iteration=None,  # type: Optional[int]
-        table_plot=None,  # type: Optional[pd.DataFrame, Sequence[Sequence]]
+        table_plot=None,  # type: Optional[pd.DataFrame, pl.DataFrame, Sequence[Sequence]]
         csv=None,  # type: Optional[str]
         url=None,  # type: Optional[str]
         extra_layout=None,  # type: Optional[dict]
@@ -392,15 +397,15 @@ class Logger(object):
         mutually_exclusive(UsageError, _check_none=True, table_plot=table_plot, csv=csv, url=url)
         table = table_plot
         if url or csv:
-            if not pd:
+            if not pd and not pl:
                 raise UsageError(
-                    "pandas is required in order to support reporting tables using CSV or a URL, "
-                    "please install the pandas python package"
+                    "pandas or polars is required in order to support reporting tables using CSV "
+                    "or a URL, please install the pandas or polars python package"
                 )
             if url:
-                table = pd.read_csv(url, index_col=[0])
+                table = pd.read_csv(url, index_col=[0]) if pd else pl.read_csv(url)
             elif csv:
-                table = pd.read_csv(csv, index_col=[0])
+                table = pd.read_csv(csv, index_col=[0]) if pd else pl.read_csv(csv)
 
         def replace(dst, *srcs):
             for src in srcs:
@@ -409,7 +414,8 @@ class Logger(object):
         if isinstance(table, (list, tuple)):
             reporter_table = table
         else:
-            reporter_table = table.fillna(str(np.nan))
+            nan = str(np.nan)
+            reporter_table = table.fillna(nan) if pd else table.fill_nan(nan)
             replace("NaN", np.nan, math.nan if six.PY3 else float("nan"))
             replace("Inf", np.inf, math.inf if six.PY3 else float("inf"))
             minus_inf = [-np.inf, -math.inf if six.PY3 else -float("inf")]

clearml/utilities/plotly_reporter.py

@@ -4,6 +4,10 @@ import numpy as np
 from ..errors import UsageError
 from ..utilities.dicts import merge_dicts
 
+try:
+    import polars as pl
+except ImportError:
+    pl = None
 try:
     import pandas as pd
 except ImportError:
@@ -486,7 +490,7 @@ def create_plotly_table(table_plot, title, series, layout_config=None, data_conf
     """
     Create a basic Plotly table json style to be sent
 
-    :param table_plot: the output table in pandas.DataFrame structure or list of rows (list) in a table
+    :param table_plot: the output table in pandas.DataFrame structure or polars.Dataframe structure or list of rows (list) in a table
     :param title: Title (AKA metric)
     :type title: str
     :param series: Series (AKA variant)
@@ -503,11 +507,19 @@ def create_plotly_table(table_plot, title, series, layout_config=None, data_conf
     elif is_list and table_plot[0] and isinstance(table_plot[0], (list, tuple)):
         headers_values = table_plot[0]
         cells_values = [list(i) for i in zip(*table_plot[1:])]
+    elif pl and isinstance(table_plot, pl.DataFrame):
+        headers_values = list([col] for col in table_plot.columns)
+        # Convert datetimes to ISO strings
+        datetime_columns = table_plot.select(pl.selectors.datetime()).columns
+        exprs = [pl.col(col).dt.to_string("iso:strict") for col in datetime_columns]
+        # Get cell values and preserve value types
+        cells_values_transpose = table_plot.with_columns(*exprs).rows()
+        cells_values = list(map(list, zip(*cells_values_transpose)))
     else:
         if not pd:
             raise UsageError(
-                "pandas is required in order to support reporting tables using CSV or a URL, "
-                "please install the pandas python package"
+                "pandas or polars is required in order to support reporting tables using CSV or a URL, "
+                "please install the pandas or polars python package"
             )
         index_added = not isinstance(table_plot.index, pd.RangeIndex)
         headers_values = list([col] for col in table_plot.columns)