From: W. Trevor King <wking@drexel.edu>
Date: Fri, 29 Jul 2011 10:54:07 +0000 (-0400)
Subject: Numeric types are now stored in native format (vs. old strings).
X-Git-Tag: v0.2~33
X-Git-Url: http://git.tremily.us/?a=commitdiff_plain;h=0f39adfab67eca66ac79fa1dcb88c362f3611200;p=h5config.git

Numeric types are now stored in native format (vs. old strings).

ChoiceSettings have string-type storage values anyway, so we'll leave
them as strings in the data files.
---

diff --git a/h5config/storage/hdf5.py b/h5config/storage/hdf5.py
index b488c37..93913d6 100644
--- a/h5config/storage/hdf5.py
+++ b/h5config/storage/hdf5.py
@@ -18,6 +18,8 @@
 """HDF5 backend implementation
 """
 
+import types as _types
+
 import h5py as _h5py
 
 from .. import LOG as _LOG
@@ -75,8 +77,6 @@ def h5_create_group(cwg, path, force=False):
 class HDF5_Storage (_FileStorage):
     """Back a `Config` class with an HDF5 file.
 
-    TODO: Special handling for Choice (enums), FloatList (arrays), etc.?
-
     The `.save` and `.load` methods have an optional `group` argument
     that allows you to save and load settings from an externally
     opened HDF5 file.  This can make it easier to stash several
@@ -98,15 +98,15 @@ class HDF5_Storage (_FileStorage):
     >>> pprint_HDF5(filename)  # doctest: +REPORT_UDIFF
     /
       /base
-        <HDF5 dataset "age": shape (), type "|S3">
+        <HDF5 dataset "age": shape (), type "<f8">
           1.3
-        <HDF5 dataset "alive": shape (), type "|S3">
-          yes
-        <HDF5 dataset "bids": shape (), type "|S11">
-          5.4, 3.2, 1
+        <HDF5 dataset "alive": shape (), type "|b1">
+          True
+        <HDF5 dataset "bids": shape (3,), type "<f8">
+          [ 5.4  3.2  1. ]
         <HDF5 dataset "children": shape (), type "|S1">
     <BLANKLINE>
-        <HDF5 dataset "daisies": shape (), type "|S2">
+        <HDF5 dataset "daisies": shape (), type "<i4">
           13
         <HDF5 dataset "name": shape (), type "|S1">
     <BLANKLINE>
@@ -155,6 +155,16 @@ class HDF5_Storage (_FileStorage):
             for s in config.settings:
                 if s.name not in group.keys():
                     continue
+                elif isinstance(s, (_config.BooleanSetting,
+                                    _config.NumericSetting,
+                                    _config.FloatListSetting)):
+                    v = group[s.name][...]
+                    if isinstance(v, _types.StringTypes):
+                        # convert back from None, etc.
+                        v = s.convert_from_text(v)
+                    elif isinstance(s, _config.FloatListSetting):
+                        v = list(v)  # convert from numpy array
+                    config[s.name] = v
                 elif isinstance(s, _config.ConfigListSetting):
                     try:
                         cwg = h5_create_group(group, s.name)
@@ -195,7 +205,14 @@ class HDF5_Storage (_FileStorage):
                 f = _h5py.File(self._filename, 'a')
                 group = f[self.group]
             for s in config.settings:
-                if isinstance(s, _config.ConfigListSetting):
+                value = None
+                if isinstance(s, (_config.BooleanSetting,
+                                    _config.NumericSetting,
+                                    _config.FloatListSetting)):
+                    value = config[s.name]
+                    if value in [None, []]:
+                        value = s.convert_to_text(value)
+                elif isinstance(s, _config.ConfigListSetting):
                     configs = config[s.name]
                     if configs:
                         cwg = h5_create_group(group, s.name, force=True)
@@ -209,7 +226,8 @@ class HDF5_Storage (_FileStorage):
                         cwg = h5_create_group(group, s.name, force=True)
                         self._save(config=cfg, group=cwg)
                         continue
-                value = s.convert_to_text(config[s.name])
+                if value is None:  # not set yet, or invalid
+                    value = s.convert_to_text(config[s.name])
                 try:
                     del group[s.name]
                 except KeyError:
diff --git a/h5config/storage/yaml.py b/h5config/storage/yaml.py
index ec06aba..3550230 100644
--- a/h5config/storage/yaml.py
+++ b/h5config/storage/yaml.py
@@ -21,6 +21,7 @@
 from __future__ import absolute_import
 
 import os.path as _os_path
+import types as _types
 
 import yaml as _yaml  # global PyYAML module
 
@@ -45,8 +46,6 @@ _YAMLDumper.add_representer(bool, _YAMLDumper.represent_bool)
 class YAML_Storage (_FileStorage):
     """Back a `Config` class with a YAML file.
 
-    TODO: Special handling for Choice (enums), etc.?
-
     >>> import os
     >>> from ..test import TestConfig
     >>> import os.path
@@ -109,6 +108,9 @@ class YAML_Storage (_FileStorage):
             if isinstance(setting, (_config.BooleanSetting,
                                     _config.NumericSetting,
                                     _config.FloatListSetting)):
+                if isinstance(v, _types.StringTypes):
+                    # older versions of h5config
+                    value = s.convert_from_text(value)
                 v = value
             elif isinstance(setting, _config.ConfigListSetting) and value:
                 values = []
diff --git a/h5config/test.py b/h5config/test.py
index 5734a27..a0e2182 100644
--- a/h5config/test.py
+++ b/h5config/test.py
@@ -43,15 +43,15 @@ Saving fills in all the config values.
 >>> pprint_HDF5(filename)  # doctest: +REPORT_UDIFF
 /
   /base
-    <HDF5 dataset "age": shape (), type "|S3">
+    <HDF5 dataset "age": shape (), type "<f8">
       1.3
-    <HDF5 dataset "alive": shape (), type "|S2">
-      no
-    <HDF5 dataset "bids": shape (), type "|S11">
-      5.4, 3.2, 1
+    <HDF5 dataset "alive": shape (), type "|b1">
+      False
+    <HDF5 dataset "bids": shape (3,), type "<f8">
+      [ 5.4  3.2  1. ]
     <HDF5 dataset "children": shape (), type "|S1">
 <BLANKLINE>
-    <HDF5 dataset "daisies": shape (), type "|S2">
+    <HDF5 dataset "daisies": shape (), type "<i4">
       13
     <HDF5 dataset "name": shape (), type "|S1">
 <BLANKLINE>