drpt - npm Package Compare versions

Comparing version 0.7.0 to 0.8.0

PKG-INFO

 Metadata-Version: 2.1
 Name: drpt
-Version: 0.7.0
+Version: 0.8.0
 Summary: Tool for preparing a dataset for publishing by dropping, renaming, scaling, and obfuscating columns defined in a recipe.
@@ -5,0 +5,0 @@ Author-email: Constantinos Xanthopoulos <[e-mail]>

pyproject.toml

@@ -7,3 +7,3 @@ [build-system]
 name = "drpt"
-version = "0.7.0"
+version = "0.8.0"
 description = "Tool for preparing a dataset for publishing by dropping, renaming, scaling, and obfuscating columns defined in a recipe."
@@ -40,3 +40,3 @@ readme = "README.md"
 [tool.bumpver]
-current_version = "0.7.0"
+current_version = "0.8.0"
 version_pattern = "MAJOR.MINOR.PATCH[PYTAGNUM]"
@@ -43,0 +43,0 @@ commit_message = "Bump version {old_version} -> {new_version}"

src/drpt.egg-info/PKG-INFO

 Metadata-Version: 2.1
 Name: drpt
-Version: 0.7.0
+Version: 0.8.0
 Summary: Tool for preparing a dataset for publishing by dropping, renaming, scaling, and obfuscating columns defined in a recipe.
@@ -5,0 +5,0 @@ Author-email: Constantinos Xanthopoulos <[e-mail]>

src/drpt/__init__.py

@@ -1,1 +0,1 @@
-__version__ = "0.7.0"
+__version__ = "0.8.0"

src/drpt/drpt.py

@@ -69,2 +69,18 @@ #!/usr/bin/env python3.9
 
+class NpEncoder(json.JSONEncoder):
+    """
+    JSON Encoder for numpy types
+    Source: https://stackoverflow.com/a/57915246
+    """
+
+    def default(self, obj):
+        if isinstance(obj, np.integer):
+            return int(obj)
+        if isinstance(obj, np.floating):
+            return float(obj)
+        if isinstance(obj, np.ndarray):
+            return obj.tolist()
+        return super(NpEncoder, self).default(obj)
+
+
 class ProgressMessage:
@@ -249,5 +265,7 @@ def __init__(self, message, parent=None):
 
+                    # Prepare compute processes for a non-skipped column
                     if not skip_scaling:
                         col_min = self.data[col].min()
                         col_max = self.data[col].max()
+                        # Custom limits scaling
                         if self.limits is not None and col in self.limits:
@@ -261,4 +279,15 @@ min, max = self.limits[col]["min"], self.limits[col]["max"]
                                 )
+                                target = compute(
+                                    min_max_scale_limits(min, col_min, col_max)
+                                )[0]
                                 min, max = col_min, col_max
-                                self._report_log("SCALE_DEFAULT", col, f"[{min},{max}]")
+                                scale_properties = {
+                                    "range": [min, max],
+                                    "target": target,
+                                }
+                                self._report_log(
+                                    "SCALE_DEFAULT_TARGET",
+                                    col,
+                                    json.dumps(scale_properties, cls=NpEncoder),
+                                )
                             else:
@@ -305,2 +334,3 @@ if pd.isna(min):
                                     )
+                        # Default Min/Max scaling
                         else:
@@ -329,2 +359,3 @@ self._report_log(
 
+            # Execute scaling processes using Dask
             if not self.dry_run:
@@ -331,0 +362,0 @@ if len(min_max_scale_limit_futures) > 0:

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Improved metrics

Total package byte prevSize

47457

2.57%

Lines of code

487

6.1%