Merge pull request #377 from xray/appveyor

shoyer · shoyer · commit 31d5d0feef02 · 2015-03-17T12:26:46.000-06:00
Add Appveyor for CI on Windows
diff --git a/appveyor.yml b/appveyor.yml
@@ -0,0 +1,35 @@
+# CI on Windows via appveyor
+# This file was based on Olivier Grisel's python-appveyor-demo
+
+environment:
+
+  matrix:
+    - PYTHON: "C:\\Python27-conda32"
+      PYTHON_VERSION: "2.7"
+      PYTHON_ARCH: "32"
+
+    - PYTHON: "C:\\Python34-conda64"
+      PYTHON_VERSION: "3.4"
+      PYTHON_ARCH: "64"
+
+install:
+  # Install miniconda Python
+  - "powershell ./ci/install_python.ps1"
+
+  # Prepend newly installed Python to the PATH of this build (this cannot be
+  # done from inside the powershell script as it would require to restart
+  # the parent CMD process).
+  - "SET PATH=%PYTHON%;%PYTHON%\\Scripts;%PATH%"
+
+  # Check that we have the expected version and architecture for Python
+  - "python --version"
+  - "python -c \"import struct; print(struct.calcsize('P') * 8)\""
+
+  # install xray and depenencies
+  - "conda install --yes --quiet pip nose numpy pandas scipy netCDF4"
+  - "python setup.py install"
+
+build: false
+
+test_script:
+  - "nosetests xray"
diff --git a/ci/install_python.ps1 b/ci/install_python.ps1
@@ -0,0 +1,93 @@
+# Sample script to install Python and pip under Windows
+# Authors: Olivier Grisel, Jonathan Helmus and Kyle Kastner
+# License: CC0 1.0 Universal: http://creativecommons.org/publicdomain/zero/1.0/
+
+$MINICONDA_URL = "http://repo.continuum.io/miniconda/"
+$BASE_URL = "https://www.python.org/ftp/python/"
+
+
+function DownloadMiniconda ($python_version, $platform_suffix) {
+    $webclient = New-Object System.Net.WebClient
+    if ($python_version -eq "3.4") {
+        $filename = "Miniconda3-3.7.3-Windows-" + $platform_suffix + ".exe"
+    } else {
+        $filename = "Miniconda-3.7.3-Windows-" + $platform_suffix + ".exe"
+    }
+    $url = $MINICONDA_URL + $filename
+
+    $basedir = $pwd.Path + "\"
+    $filepath = $basedir + $filename
+    if (Test-Path $filename) {
+        Write-Host "Reusing" $filepath
+        return $filepath
+    }
+
+    # Download and retry up to 3 times in case of network transient errors.
+    Write-Host "Downloading" $filename "from" $url
+    $retry_attempts = 2
+    for($i=0; $i -lt $retry_attempts; $i++){
+        try {
+            $webclient.DownloadFile($url, $filepath)
+            break
+        }
+        Catch [Exception]{
+            Start-Sleep 1
+        }
+   }
+   if (Test-Path $filepath) {
+       Write-Host "File saved at" $filepath
+   } else {
+       # Retry once to get the error message if any at the last try
+       $webclient.DownloadFile($url, $filepath)
+   }
+   return $filepath
+}
+
+
+function InstallMiniconda ($python_version, $architecture, $python_home) {
+    Write-Host "Installing Python" $python_version "for" $architecture "bit architecture to" $python_home
+    if (Test-Path $python_home) {
+        Write-Host $python_home "already exists, skipping."
+        return $false
+    }
+    if ($architecture -eq "32") {
+        $platform_suffix = "x86"
+    } else {
+        $platform_suffix = "x86_64"
+    }
+    $filepath = DownloadMiniconda $python_version $platform_suffix
+    Write-Host "Installing" $filepath "to" $python_home
+    $install_log = $python_home + ".log"
+    $args = "/S /D=$python_home"
+    Write-Host $filepath $args
+    Start-Process -FilePath $filepath -ArgumentList $args -Wait -Passthru
+    if (Test-Path $python_home) {
+        Write-Host "Python $python_version ($architecture) installation complete"
+    } else {
+        Write-Host "Failed to install Python in $python_home"
+        Get-Content -Path $install_log
+        Exit 1
+    }
+}
+
+
+function InstallMinicondaPip ($python_home) {
+    $pip_path = $python_home + "\Scripts\pip.exe"
+    $conda_path = $python_home + "\Scripts\conda.exe"
+    if (-not(Test-Path $pip_path)) {
+        Write-Host "Installing pip..."
+        $args = "install --yes pip"
+        Write-Host $conda_path $args
+        Start-Process -FilePath "$conda_path" -ArgumentList $args -Wait -Passthru
+    } else {
+        Write-Host "pip already installed."
+    }
+}
+
+
+function main () {
+    InstallMiniconda $env:PYTHON_VERSION $env:PYTHON_ARCH $env:PYTHON
+    InstallMinicondaPip $env:PYTHON
+}
+
+main
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
@@ -86,7 +86,7 @@ Bug fixes
   aggregation methods (:issue:`344`).
 - Dataset aggregations with ``keep_attrs=True`` now preserve attributes on
   data variables, not just the dataset itself.
-- Tests for xray now pass when run on Windows. DOUBLE CHECK THIS.
+- Tests for xray now pass when run on Windows (:issue:`360`).
 - Fixed a regression in v0.4 where saving to netCDF could fail with the error
   ``ValueError: could not automatically determine time units``.
 
diff --git a/xray/test/test_backends.py b/xray/test/test_backends.py
@@ -385,7 +385,7 @@ def test_dump_and_open_encodings(self):
 
             with open_dataset(tmp_file) as xray_dataset:
                 with create_tmp_file() as tmp_file2:
-                    xray_dataset.dump(tmp_file2)
+                    xray_dataset.to_netcdf(tmp_file2)
                     with nc4.Dataset(tmp_file2, 'r') as ds:
                         self.assertEqual(ds.variables['time'].getncattr('units'), units)
                         self.assertArrayEqual(ds.variables['time'], np.arange(10) + 4)
@@ -495,53 +495,6 @@ def test_default_to_char_arrays(self):
             self.assertDatasetIdentical(data, actual)
             self.assertEqual(actual['x'].dtype, np.dtype('S4'))
 
-    def test_open_encodings(self):
-        # Create a netCDF file with explicit time units
-        # and make sure it makes it into the encodings
-        # and survives a round trip
-        with create_tmp_file() as tmp_file:
-            with nc4.Dataset(tmp_file, 'w') as ds:
-                ds.createDimension('time', size=10)
-                ds.createVariable('time', np.int32, dimensions=('time',))
-                units = 'days since 1999-01-01'
-                ds.variables['time'].setncattr('units', units)
-                ds.variables['time'][:] = np.arange(10) + 4
-
-            expected = Dataset()
-
-            time = pd.date_range('1999-01-05', periods=10)
-            encoding = {'units': units, 'dtype': np.dtype('int32')}
-            expected['time'] = ('time', time, {}, encoding)
-
-            with open_dataset(tmp_file) as actual:
-                self.assertVariableEqual(actual['time'], expected['time'])
-                actual_encoding = dict((k, v) for k, v
-                                       in iteritems(actual['time'].encoding)
-                                       if k in expected['time'].encoding)
-                self.assertDictEqual(actual_encoding,
-                                     expected['time'].encoding)
-
-    def test_dump_and_open_encodings(self):
-        # Create a netCDF file with explicit time units
-        # and make sure it makes it into the encodings
-        # and survives a round trip
-        with create_tmp_file() as tmp_file:
-            with nc4.Dataset(tmp_file, 'w') as ds:
-                ds.createDimension('time', size=10)
-                ds.createVariable('time', np.int32, dimensions=('time',))
-                units = 'days since 1999-01-01'
-                ds.variables['time'].setncattr('units', units)
-                ds.variables['time'][:] = np.arange(10) + 4
-
-            xray_dataset = open_dataset(tmp_file)
-
-            with create_tmp_file() as tmp_file2:
-                xray_dataset.to_netcdf(tmp_file2)
-
-                with nc4.Dataset(tmp_file2, 'r') as ds:
-                    self.assertEqual(ds.variables['time'].getncattr('units'), units)
-                    self.assertArrayEqual(ds.variables['time'], np.arange(10) + 4)
-
     def test_coordinates_encoding(self):
         def equals_latlon(obj):
             return obj == 'lat lon' or obj == 'lon lat'
diff --git a/xray/test/test_variable.py b/xray/test/test_variable.py
@@ -755,7 +755,7 @@ def test_count(self):
 
         actual = Variable(['x'], [True, False, True]).count()
         self.assertVariableIdentical(expected, actual)
-        self.assertEqual(actual.dtype, 'int64')
+        self.assertEqual(actual.dtype, int)
 
         expected = Variable(['x'], [2, 3])
         actual = Variable(['x', 'y'], [[1, 0, np.nan], [1, 1, 1]]).count('y')
@@ -810,7 +810,7 @@ def test_converted_types(self):
             actual = _as_compatible_data(input_array)
             self.assertArrayEqual(np.asarray(input_array), actual)
             self.assertEqual(NumpyArrayAdapter, type(actual))
-            self.assertEqual(np.dtype(np.int64), actual.dtype)
+            self.assertEqual(np.asarray(input_array).dtype, actual.dtype)
 
     def test_masked_array(self):
         original = np.ma.MaskedArray(np.arange(5))
