Fix/update libs

.github/workflows/plotly_ci.yaml

@@ -39,6 +39,9 @@ jobs:
       - name: Run formatter
         run: make lint
 
+      - name: Run stubs install
+        run: make stubs
+
       - name: Run checks
         run: make checks
 

Makefile

@@ -21,6 +21,10 @@ checks:
 	@poetry run pytest tests/
 	@poetry run poetry check
 
+stubs:
+	@poetry run mypy --install-types --non-interactive plotly_calplot
+	@poetry run python3 -m pip install types-pytz
+
 pypi_deploy:
 	@poetry config pypi-token.pypi $(PLOTLY_PRD_TOKEN)
 	@poetry build

examples/plotly_fig_show.py

@@ -8,7 +8,7 @@
 dummy_end_date = "2022-10-03"
 dummy_df = pd.DataFrame(
     {
-        "ds": pd.date_range(dummy_start_date, dummy_end_date),
+        "ds": pd.date_range(dummy_start_date, dummy_end_date, tz="Singapore"),
         "value": np.random.randint(
             -10,
             30,
@@ -17,6 +17,7 @@
         ),
     }
 )
+
 fig1 = calplot(
     dummy_df,
     x="ds",
@@ -30,7 +31,5 @@
     dummy_df,
     x="ds",
     y="value",
-    dark_theme=True,
-    showscale=True,
 )
 fig2.show()

plotly_calplot/calplot.py

@@ -1,5 +1,5 @@
 from datetime import date
-from typing import Any, Dict, Optional
+from typing import Any, Dict, Optional, Union
 
 import numpy as np
 from pandas import DataFrame, Grouper, Series
@@ -11,7 +11,7 @@
     showscale_of_heatmaps,
 )
 from plotly_calplot.single_year_calplot import year_calplot
-from plotly_calplot.utils import fill_empty_with_zeros
+from plotly_calplot.utils import fill_empty_with_zeros, validate_date_column
 
 
 def _get_subplot_layout(**kwargs: Any) -> go.Layout:
@@ -65,7 +65,7 @@ def calplot(
     colorscale: str = "greens",
     title: str = "",
     month_lines: bool = True,
-    total_height: int = None,
+    total_height: Union[int, None] = None,
     space_between_plots: float = 0.08,
     showscale: bool = False,
     text: Optional[str] = None,
@@ -74,6 +74,7 @@ def calplot(
     cmap_max: Optional[float] = None,
     start_month: int = 1,
     end_month: int = 12,
+    date_fmt: str = "%Y-%m-%d",
 ) -> go.Figure:
     """
     Yearly Calendar Heatmap
@@ -149,7 +150,15 @@ def calplot(
 
     end_month : int = 12
         ending month range to plot, defaults to 12 (December)
+
+    date_fmt : str = "%Y-%m-%d"
+        date format for the date column in data, defaults to "%Y-%m-%d"
+        If the date column is already in datetime format, this parameter
+        will be ignored.
     """
+    print(data[x])
+    data[x] = validate_date_column(data[x], date_fmt)
+    print(data[x])
     unique_years = data[x].dt.year.unique()
     unique_years_amount = len(unique_years)
     if years_title:
@@ -236,8 +245,9 @@ def month_calplot(
     colorscale: str = "greens",
     title: str = "",
     year_height: int = 30,
-    total_height: int = None,
+    total_height: Union[int, None] = None,
     showscale: bool = False,
+    date_fmt: str = "%Y-%m-%d",
 ) -> go.Figure:
     """
     Yearly Calendar Heatmap by months (12 cols per row)
@@ -279,6 +289,11 @@ def month_calplot(
 
     showscale : bool = False
         wether to show the scale of the data
+
+    date_fmt : str = "%Y-%m-%d"
+        date format for the date column in data, defaults to "%Y-%m-%d"
+        If the date column is already in datetime format, this parameter
+        will be ignored.
     """
     if data is None:
         if not isinstance(x, Series):
@@ -292,6 +307,8 @@ def month_calplot(
         x = x.name
         y = y.name
 
+    data[x] = validate_date_column(data[x], date_fmt)
+
     gData = data.set_index(x)[y].groupby(Grouper(freq="M")).sum()
     unique_years = gData.index.year.unique()
     unique_years_amount = len(unique_years)

plotly_calplot/date_extractors.py

@@ -18,7 +18,7 @@ def get_month_names(
 
 
 def get_date_coordinates(
-    data: pd.DataFrame, x: str, start_month: int, end_month: int
+    data: pd.DataFrame, x: str
 ) -> Tuple[Any, List[float], List[int]]:
     month_days = []
     for m in data[x].dt.month.unique():

plotly_calplot/single_year_calplot.py

@@ -1,4 +1,4 @@
-from typing import List, Optional
+from typing import List, Optional, Union
 
 from pandas.core.frame import DataFrame
 from plotly import graph_objects as go
@@ -27,7 +27,7 @@ def year_calplot(
     colorscale: str = "greens",
     title: str = "",
     month_lines: bool = True,
-    total_height: int = None,
+    total_height: Union[int, None] = None,
     text: Optional[List[str]] = None,
     text_name: Optional[str] = None,
     years_as_columns: bool = False,
@@ -40,7 +40,7 @@ def year_calplot(
 
     month_names = get_month_names(data, x, start_month, end_month)
     month_positions, weekdays_in_year, weeknumber_of_dates = get_date_coordinates(
-        data, x, start_month, end_month
+        data, x
     )
 
     # the calendar is actually a heatmap :)

plotly_calplot/utils.py

@@ -11,6 +11,19 @@ def fill_empty_with_zeros(
     start_month: int,
     end_month: int,
 ) -> pd.DataFrame:
+    """
+    Fills empty dates with zeros in the selected year data.
+
+    Args:
+        selected_year_data (DataFrame): The data for the selected year.
+        x (str): The column name for the date values.
+        year (int): The year for which the data is being filled.
+        start_month (int): The starting month of the year.
+        end_month (int): The ending month of the year.
+
+    Returns:
+        pd.DataFrame: The final DataFrame with empty dates filled with zeros.
+    """
     if end_month != 12:
         last_date = datetime(year, end_month + 1, 1) + timedelta(days=-1)
     else:
@@ -20,3 +33,35 @@ def fill_empty_with_zeros(
     df = pd.DataFrame({x: pd.date_range(year_min_date, year_max_date)})
     final_df = df.merge(selected_year_data, how="left")
     return final_df
+
+
+def validate_date_column(date_column: pd.Series, date_fmt: str) -> pd.Series:
+    """
+    Validate the date column from a DataFrame.
+
+    Parameters:
+        data (DataFrame): The input DataFrame.
+        x (str): The name of the column containing the date values.
+
+    Returns:
+        pd.Series: The date column extracted from the DataFrame.
+
+    Raises:
+        ValueError: If the column is not in datetime format.
+    """
+    if date_column.dtype == "datetime64[ns]":
+        return date_column
+    elif date_column.dtype == "object":
+        try:
+            return pd.to_datetime(date_column, format=date_fmt)
+        except ValueError:
+            raise ValueError(
+                f"Date column is not in the {date_fmt} format. Use change date_fmt parameter to match your dates."  # noqa
+            )
+    try:
+        if date_column.dt.tz is not None:
+            return date_column.dt.tz_localize(None)
+    except Exception as e:
+        raise Exception(
+            f"Exception {e}\nDate column is not in datetime format or not in the right string format. Please convert it to datetime format first or use the date_fmt parameter."  # noqa
+        )