MNT stop using colored in Windows since it does not work

rampwf/utils/pretty_print.py

@@ -2,11 +2,14 @@
 """
 Utility methods to print the results in a terminal using term colors
 """
-from __future__ import print_function
+import platform
 
 from pandas import option_context
+
 from ..externals.colored import stylize, fg, attr
 
+IS_WINDOWS = platform.system() == "Windows"
+
 # Dictionary of term colors used for printing to terminal
 fg_colors = {
     'official_train': 'light_green',
@@ -20,12 +23,16 @@
 }
 
 
-def print_title(str):
-    print(stylize(str, fg(fg_colors['title']) + attr('bold')))
+def print_title(title):
+    if not IS_WINDOWS:
+        title = stylize(title, fg(fg_colors['title']) + attr('bold'))
+    print(title)
 
 
-def print_warning(str):
-    print(stylize(str, fg(fg_colors['warning'])))
+def print_warning(warning):
+    if not IS_WINDOWS:
+        warning = stylize(warning, fg(fg_colors['warning']))
+    print(warning)
 
 
 def print_df_scores(df_scores, indent=''):
@@ -48,16 +55,18 @@ def print_df_scores(df_scores, indent=''):
             continue
         if color_key is None:
             # table header
-            line = stylize(line, fg(fg_colors['title']) + attr('bold'))
+            if not IS_WINDOWS:
+                line = stylize(line, fg(fg_colors['title']) + attr('bold'))
         if color_key is not None:
             tokens = line.split()
             tokens_bak = tokens[:]
             if 'official_' + color_key in fg_colors:
                 # line label and official score bold & bright
-                label_color = fg(fg_colors['official_' + color_key])
-                tokens[0] = stylize(tokens[0], label_color + attr('bold'))
-                tokens[1] = stylize(tokens[1], label_color + attr('bold'))
-            if color_key in fg_colors:
+                if not IS_WINDOWS:
+                    label_color = fg(fg_colors['official_' + color_key])
+                    tokens[0] = stylize(tokens[0], label_color + attr('bold'))
+                    tokens[1] = stylize(tokens[1], label_color + attr('bold'))
+            if not IS_WINDOWS and (color_key in fg_colors):
                 # other scores pale
                 tokens[2:] = [stylize(token, fg(fg_colors[color_key]))
                               for token in tokens[2:]]

rampwf/utils/scoring.py

@@ -4,6 +4,8 @@
 """
 import numpy as np
 import pandas as pd
+
+from .pretty_print import IS_WINDOWS
 from .pretty_print import print_warning
 
 
@@ -53,12 +55,20 @@ def mean_score_matrix(df_scores_list, score_types):
     precisions = [st.precision for st in score_types]
     precisions.append(1)  # for time
     # we use unicode no break space so split in print_df_scores works
-    strs = np.array([[
-        u'{val}\u00A0±\u00A0{std}'.format(
-            val=round(mean, prec),
-            std=round(std, prec + 1))
-        for mean, std, prec in zip(means, stds, precisions)]
-        for means, stds in zip(meanss, stdss)])
+    if not IS_WINDOWS:
+        strs = np.array([[
+            u'{val}\u00A0±\u00A0{std}'.format(
+                val=round(mean, prec),
+                std=round(std, prec + 1))
+            for mean, std, prec in zip(means, stds, precisions)]
+            for means, stds in zip(meanss, stdss)])
+    else:
+        strs = np.array([[
+            u'{val} +- {std}'.format(
+                val=round(mean, prec),
+                std=round(std, prec + 1))
+            for mean, std, prec in zip(means, stds, precisions)]
+            for means, stds in zip(meanss, stdss)])
     df_scores = pd.DataFrame(
         strs, columns=df_scores_list[0].columns, index=df_scores_list[0].index)
     return df_scores

testing-requirements.txt

@@ -10,5 +10,5 @@ xarray
 scikit-image
 joblib
 keras; python_version >= '3.5' or (python_version == '2.7' and sys_platform != 'win32')
-tensorflow == 2.0; python_version >= '3.5' or (python_version == '2.7' and sys_platform != 'win32')
+tensorflow == 2.0.1; python_version >= '3.5' or (python_version == '2.7' and sys_platform != 'win32')