Merge pull request #450 from jrycw/organize-imports

Refactor import statements in `_formats.py`

great_tables/_formats.py

@@ -1,6 +1,8 @@
 from __future__ import annotations
 
 import math
+import re
+from dataclasses import dataclass
 from datetime import date, datetime, time
 from decimal import Decimal
 from pathlib import Path
@@ -3426,6 +3428,12 @@ def fmt_image(
         The option to always use Base64 encoding for image paths that are determined to be local. By
         default, this is `True`.
 
+    Returns
+    -------
+    GT
+        The GT object is returned. This is the same object that the method is called on so that we
+        can facilitate method chaining.
+
     Examples
     --------
     Using a small portion of `metro` dataset, let's create a new table. We will only include a few
@@ -3476,9 +3484,6 @@ def fmt_image(
     return fmt(self, fns=formatter.to_html, columns=columns, rows=rows)
 
 
-from dataclasses import dataclass
-
-
 @dataclass
 class FmtImage:
     dispatch_on: DataFrameLike | Agnostic = Agnostic()
@@ -3492,8 +3497,6 @@ class FmtImage:
     SPAN_TEMPLATE: ClassVar = '<span style="white-space:nowrap;">{}</span>'
 
     def to_html(self, val: Any):
-        from pathlib import Path
-
         # TODO: are we assuming val is a string? (or coercing?)
 
         # otherwise...
@@ -3561,8 +3564,6 @@ def _get_image_uri(cls, filename: str) -> str:
 
     @staticmethod
     def _get_mime_type(filename: str) -> str:
-        from pathlib import Path
-
         # note that we strip off the leading "."
         suffix = Path(filename).suffix[1:]
 
@@ -3661,6 +3662,12 @@ def fmt_nanoplot(
         By using the [`nanoplot_options()`](`great_tables.nanoplot_options`) helper function here,
         you can alter the layout and styling of the nanoplots in the new column.
 
+    Returns
+    -------
+    GT
+        The GT object is returned. This is the same object that the method is called on so that we
+        can facilitate method chaining.
+
     Details
     -------
     Nanoplots try to show individual data with reasonably good visibility. Interactivity is included
@@ -3969,8 +3976,6 @@ def _generate_data_vals(
         list[Any]: A list of data values.
     """
 
-    import re
-
     if is_series(data_vals):
         data_vals = to_list(data_vals)
 
@@ -4063,8 +4068,6 @@ def _process_number_stream(data_vals: str) -> list[float]:
         list[float]: A list of numeric values.
     """
 
-    import re
-
     number_stream = re.sub(r"[;,]", " ", data_vals)
     number_stream = re.sub(r"\\[|\\]", " ", number_stream)
     number_stream = re.sub(r"^\\s+|\\s+$", "", number_stream)
@@ -4075,9 +4078,6 @@ def _process_number_stream(data_vals: str) -> list[float]:
     return number_stream
 
 
-import re
-
-
 def _process_time_stream(data_vals: str) -> list[float]:
     """
     Process a string of time values and convert to a list of floats.