feat: replace warnings with markdown printouts (#94)

Resolves #41
datamole-ai · Sep 4, 2023 · 7ef547b · 7ef547b
1 parent 0bab9ca
commit 7ef547b
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Showing 5 changed files with 1,721 additions and 1,672 deletions.
diff --git a/api-example.ipynb b/api-example.ipynb
diff --git a/edvart/report_sections/group_analysis.py b/edvart/report_sections/group_analysis.py
@@ -1,6 +1,5 @@
 """Group analysis module."""
 
-import warnings
 from typing import Any, Callable, Dict, List, Optional, Union
 
 import colorlover as cl
@@ -341,7 +340,12 @@ def group_barplot(
         """
         num_cat = df[column].nunique()
         if num_cat > group_count_threshold:
-            warnings.warn(f"Too many categories ({num_cat}), not plotting distribution")
+            display(
+                Markdown(
+                    f"Number of unique values ({num_cat}) greater than threshold."
+                    " Not plotting distribution"
+                )
+            )
             return
 
         pivot = df.pivot_table(index=groupby, columns=column, aggfunc="size", fill_value=0)
@@ -577,7 +581,6 @@ def required_imports(self) -> List[str]:
             "import plotly.graph_objects as go",
             "from edvart.data_types import infer_data_type, DataType",
             "from edvart import utils",
-            "import warnings",
             "from typing import List, Dict, Optional, Callable",
             "from plotly.subplots import make_subplots",
         ]

diff --git a/edvart/report_sections/timeseries_analysis/seasonal_decomposition.py b/edvart/report_sections/timeseries_analysis/seasonal_decomposition.py
@@ -1,6 +1,5 @@
 """Seasonal decomposition package."""
 
-import warnings
 from typing import Any, Dict, List, Optional, Tuple
 
 import matplotlib.pyplot as plt
@@ -91,9 +90,13 @@ def seasonal_decomposition(
         """
         df = df.interpolate(method="time")
         if pd.infer_freq(df.index) is None and period is None:
-            warnings.warn(
-                "Period could not be inferred, please set the period parameter to a suitable value."
-                "Decomposition will not be plotted."
+            display(
+                Markdown(
+                    "<div class='alert alert-block alert-warning'>"
+                    "Period could not be inferred, please set the `period` parameter"
+                    " to a suitable value. Not plotting seasonal decomposition."
+                    "</div>"
+                )
             )
             return
         if columns is None:

diff --git a/edvart/report_sections/timeseries_analysis/time_series_line_plot.py b/edvart/report_sections/timeseries_analysis/time_series_line_plot.py
@@ -157,7 +157,6 @@ def required_imports(self) -> List[str]:
             ]
         return [
             "from IPython.display import display, Markdown",
-            "import warnings",
             "import plotly",
             "import plotly.graph_objects as go",
             "plotly.offline.init_notebook_mode()",

diff --git a/edvart/report_sections/univariate_analysis.py b/edvart/report_sections/univariate_analysis.py
@@ -1,5 +1,4 @@
 """Univariate analysis package."""
-import warnings
 from typing import Any, Callable, Dict, List, Optional, Tuple
 
 import matplotlib.pyplot as plt
@@ -174,9 +173,11 @@ def bar_plot(
             Additional kwargs passed to pandas.Series.bar.
         """
         if series.nunique() > plotting_threshold:
-            warnings.warn(
-                f"Number of unique values is greater than {plotting_threshold},"
-                " not plotting bar plot."
+            display(
+                Markdown(
+                    f"Number of unique values is greater than {plotting_threshold},"
+                    " not plotting bar plot."
+                )
             )
         else:
             value_counts = series.value_counts()
@@ -308,7 +309,6 @@ def required_imports(self) -> List[str]:
             "import matplotlib.pyplot as plt",
             "%matplotlib inline",
             "import seaborn as sns",
-            "import warnings",
         ]
 
     def add_cells(self, cells: List[Dict[str, Any]]) -> None: