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.gitattributes

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my_container_sandbox/workspace/anaconda3/lib/python3.8/__pycache__/_pydecimal.cpython-38.pyc

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my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/Deprecated-1.2.13.dist-info/INSTALLER

@@ -0,0 +1 @@
+pip

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/Deprecated-1.2.13.dist-info/LICENSE.rst

@@ -0,0 +1,21 @@
+The MIT License (MIT)
+
+Copyright (c) 2017 Laurent LAPORTE
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/Deprecated-1.2.13.dist-info/METADATA

@@ -0,0 +1,187 @@
+Metadata-Version: 2.1
+Name: Deprecated
+Version: 1.2.13
+Summary: Python @deprecated decorator to deprecate old python classes, functions or methods.
+Home-page: https://github.com/tantale/deprecated
+Author: Laurent LAPORTE
+Author-email: tantale.solutions@gmail.com
+License: MIT
+Project-URL: Documentation, https://deprecated.readthedocs.io/en/latest/
+Project-URL: Source, https://github.com/tantale/deprecated
+Project-URL: Bug Tracker, https://github.com/tantale/deprecated/issues
+Keywords: deprecate,deprecated,deprecation,warning,warn,decorator
+Platform: any
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Environment :: Web Environment
+Classifier: Intended Audience :: Developers
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 2
+Classifier: Programming Language :: Python :: 2.7
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.4
+Classifier: Programming Language :: Python :: 3.5
+Classifier: Programming Language :: Python :: 3.6
+Classifier: Programming Language :: Python :: 3.7
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Topic :: Software Development :: Libraries :: Python Modules
+Requires-Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*
+Description-Content-Type: text/x-rst
+License-File: LICENSE.rst
+Requires-Dist: wrapt (<2,>=1.10)
+Provides-Extra: dev
+Requires-Dist: tox ; extra == 'dev'
+Requires-Dist: bump2version (<1) ; extra == 'dev'
+Requires-Dist: sphinx (<2) ; extra == 'dev'
+Requires-Dist: importlib-metadata (<3) ; (python_version < "3") and extra == 'dev'
+Requires-Dist: importlib-resources (<4) ; (python_version < "3") and extra == 'dev'
+Requires-Dist: configparser (<5) ; (python_version < "3") and extra == 'dev'
+Requires-Dist: sphinxcontrib-websupport (<2) ; (python_version < "3") and extra == 'dev'
+Requires-Dist: zipp (<2) ; (python_version < "3") and extra == 'dev'
+Requires-Dist: PyTest (<5) ; (python_version < "3.6") and extra == 'dev'
+Requires-Dist: PyTest-Cov (<2.6) ; (python_version < "3.6") and extra == 'dev'
+Requires-Dist: PyTest ; (python_version >= "3.6") and extra == 'dev'
+Requires-Dist: PyTest-Cov ; (python_version >= "3.6") and extra == 'dev'
+
+
+Deprecated Library
+------------------
+
+Deprecated is Easy to Use
+`````````````````````````
+
+If you need to mark a function or a method as deprecated,
+you can use the ``@deprecated`` decorator:
+
+Save in a hello.py:
+
+.. code:: python
+
+    from deprecated import deprecated
+
+
+    @deprecated(version='1.2.1', reason="You should use another function")
+    def some_old_function(x, y):
+        return x + y
+
+
+    class SomeClass(object):
+        @deprecated(version='1.3.0', reason="This method is deprecated")
+        def some_old_method(self, x, y):
+            return x + y
+
+
+    some_old_function(12, 34)
+    obj = SomeClass()
+    obj.some_old_method(5, 8)
+
+
+And Easy to Setup
+`````````````````
+
+And run it:
+
+.. code:: bash
+
+    $ pip install Deprecated
+    $ python hello.py
+    hello.py:15: DeprecationWarning: Call to deprecated function (or staticmethod) some_old_function.
+    (You should use another function) -- Deprecated since version 1.2.0.
+      some_old_function(12, 34)
+    hello.py:17: DeprecationWarning: Call to deprecated method some_old_method.
+    (This method is deprecated) -- Deprecated since version 1.3.0.
+      obj.some_old_method(5, 8)
+
+
+You can document your code
+``````````````````````````
+
+Have you ever wonder how to document that some functions, classes, methods, etc. are deprecated?
+This is now possible with the integrated Sphinx directives:
+
+For instance, in hello_sphinx.py:
+
+.. code:: python
+
+    from deprecated.sphinx import deprecated
+    from deprecated.sphinx import versionadded
+    from deprecated.sphinx import versionchanged
+
+
+    @versionadded(version='1.0', reason="This function is new")
+    def function_one():
+        '''This is the function one'''
+
+
+    @versionchanged(version='1.0', reason="This function is modified")
+    def function_two():
+        '''This is the function two'''
+
+
+    @deprecated(version='1.0', reason="This function will be removed soon")
+    def function_three():
+        '''This is the function three'''
+
+
+    function_one()
+    function_two()
+    function_three()  # warns
+
+    help(function_one)
+    help(function_two)
+    help(function_three)
+
+
+The result it immediate
+```````````````````````
+
+Run it:
+
+.. code:: bash
+
+    $ python hello_sphinx.py
+
+    hello_sphinx.py:23: DeprecationWarning: Call to deprecated function (or staticmethod) function_three.
+    (This function will be removed soon) -- Deprecated since version 1.0.
+      function_three()  # warns
+
+    Help on function function_one in module __main__:
+
+    function_one()
+        This is the function one
+
+        .. versionadded:: 1.0
+           This function is new
+
+    Help on function function_two in module __main__:
+
+    function_two()
+        This is the function two
+
+        .. versionchanged:: 1.0
+           This function is modified
+
+    Help on function function_three in module __main__:
+
+    function_three()
+        This is the function three
+
+        .. deprecated:: 1.0
+           This function will be removed soon
+
+
+Links
+`````
+
+* `Python package index (PyPi) <https://pypi.python.org/pypi/deprecated>`_
+* `GitHub website <https://github.com/tantale/deprecated>`_
+* `Read The Docs <https://readthedocs.org/projects/deprecated>`_
+* `EBook on Lulu.com <http://www.lulu.com/commerce/index.php?fBuyContent=21305117>`_
+* `StackOverFlow Q&A <https://stackoverflow.com/a/40301488/1513933>`_
+* `Development version
+  <https://github.com/tantale/deprecated/zipball/master#egg=Deprecated-dev>`_
+
+
+

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my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/Deprecated-1.2.13.dist-info/WHEEL

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+Wheel-Version: 1.0
+Generator: bdist_wheel (0.33.6)
+Root-Is-Purelib: true
+Tag: py2-none-any
+Tag: py3-none-any
+

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/Deprecated-1.2.13.dist-info/top_level.txt

@@ -0,0 +1 @@
+deprecated

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/SimpleITK/__init__.py

@@ -0,0 +1,21 @@
+# ========================================================================
+#
+#  Copyright NumFOCUS
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#         http://www.apache.org/licenses/LICENSE-2.0.txt
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+# ========================================================================
+from SimpleITK.SimpleITK import *
+from SimpleITK.extra import *
+
+from SimpleITK._version import __version__

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/SimpleITK/_version.py

@@ -0,0 +1,54 @@
+# ========================================================================
+#
+#  Copyright NumFOCUS
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#         http://www.apache.org/licenses/LICENSE-2.0.txt
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+# ========================================================================
+
+
+def _get_pep386version():
+    """Uses configured CMake version variable to construct a pep 386 compliant version string."""
+
+    sitk_major = "2"
+    sitk_minor = "1"
+    sitk_patch = "1"
+    sitk_tweak = "2"
+    sitk_rc = ""
+    sitk_post = ""
+    sitk_dev = ""
+    sitk_hash = "5627c"
+
+    version = sitk_major + "." + sitk_minor
+
+    if sitk_patch:
+        version += "." + sitk_patch
+        if sitk_tweak:
+            version += "." + sitk_tweak
+
+    if sitk_rc:
+        version += sitk_rc
+
+    if sitk_post:
+        version += ".post" + sitk_post
+    elif sitk_dev:
+        version += ".dev" + sitk_dev
+
+    # Local Version Identifier
+    if sitk_hash and "ON" not in ['1', 'ON']:
+        version += "+g" + sitk_hash
+
+    return version
+
+
+__version__ = _get_pep386version()

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/SimpleITK/extra.py

@@ -0,0 +1,444 @@
+# ========================================================================
+#
+#  Copyright NumFOCUS
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#         http://www.apache.org/licenses/LICENSE-2.0.txt
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+# ========================================================================
+
+from SimpleITK.SimpleITK import *
+from SimpleITK.SimpleITK import _GetMemoryViewFromImage
+from SimpleITK.SimpleITK import _SetImageFromArray
+
+from typing import List, Union
+
+
+def Resample(image1, *args, **kwargs):
+    """
+     Resample ( Image image1,
+                Transform transform = itk::simple::Transform(),
+                InterpolatorEnum interpolator = itk::simple::sitkLinear,
+                double defaultPixelValue = 0.0,
+                PixelIDValueEnum outputPixelType = itk::simple::sitkUnknown,
+                bool useNearestNeighborExtrapolator = false);
+
+     Resample ( Image image1,
+                Image referenceImage,
+                Transform transform = itk::simple::Transform(),
+                InterpolatorEnum interpolator = itk::simple::sitkLinear,
+                double defaultPixelValue = 0.0,
+                PixelIDValueEnum outputPixelType = sitkUnknown,
+                bool useNearestNeighborExtrapolator = false);
+
+     Resample ( const Image& image1,
+                VectorUInt32 size,
+                Transform transform = itk::simple::Transform(),
+                InterpolatorEnum interpolator = itk::simple::sitkLinear,
+                VectorDouble outputOrigin = std::vector<double>(3, 0.0),
+                VectorDouble outputSpacing = std::vector<double>(3, 1.0),
+                VectorDouble outputDirection = std::vector<double>(),
+                double defaultPixelValue = 0.0,
+                PixelIDValueEnum outputPixelType = sitkUnknown,
+                bool useNearestNeighborExtrapolator = false);
+
+     itk::simple::ResampleImageFilter procedural interface.
+
+     This is a custom overloaded python method, which fully supports the 3 signatures with positional and keyword
+      arguments. The second positional parameters without a default value are used to determine which overloaded
+      procedure signature to invoke.
+
+    """
+
+    def _r_image(referenceImage,
+                 transform=Transform(),
+                 interpolator=sitkLinear,
+                 defaultPixelValue=0.0,
+                 outputPixelType=sitkUnknown,
+                 useNearestNeighborExtrapolator=False):
+        resampler = ResampleImageFilter()
+        resampler.SetReferenceImage(referenceImage)
+        resampler.SetTransform(transform)
+        resampler.SetInterpolator(interpolator)
+        resampler.SetDefaultPixelValue(defaultPixelValue)
+        resampler.SetOutputPixelType(outputPixelType)
+        resampler.SetUseNearestNeighborExtrapolator(useNearestNeighborExtrapolator)
+        return resampler.Execute(image1)
+
+    def _r(size,
+           transform=Transform(),
+           interpolator=sitkLinear,
+           outputOrigin=(0.0, 0.0, 0.0),
+           outputSpacing=(1.0, 1.0, 1.0),
+           outputDirection=(),
+           defaultPixelValue=0.0,
+           outputPixelType=sitkUnknown,
+           useNearestNeighborExtrapolator=False):
+        resampler = ResampleImageFilter()
+        resampler.SetSize(size)
+        resampler.SetTransform(transform)
+        resampler.SetInterpolator(interpolator)
+        resampler.SetOutputOrigin(outputOrigin)
+        resampler.SetOutputSpacing(outputSpacing)
+        resampler.SetOutputDirection(outputDirection)
+        resampler.SetDefaultPixelValue(defaultPixelValue)
+        resampler.SetOutputPixelType(outputPixelType)
+        resampler.SetUseNearestNeighborExtrapolator(useNearestNeighborExtrapolator)
+        return resampler.Execute(image1)
+
+    if args:
+        if isinstance(args[0], Image):
+            return _r_image(*args, **kwargs)
+        if not isinstance(args[0], Transform):
+            try:
+                iter(args[0])
+                return _r(*args, **kwargs)
+            except TypeError as e:
+                pass
+
+    if "referenceImage" in kwargs:
+        return _r_image(*args, **kwargs)
+    if "size" in kwargs:
+        return _r(*args, **kwargs)
+
+    return _r_image(image1, *args, **kwargs)
+
+
+HAVE_NUMPY = True
+try:
+    import numpy
+except ImportError:
+    HAVE_NUMPY = False
+
+
+def _get_numpy_dtype(sitkImage):
+    """Given a SimpleITK image, returns the numpy.dtype which describes the data"""
+
+    if not HAVE_NUMPY:
+        raise ImportError('Numpy not available.')
+
+    # this is a mapping from sitk's pixel id to numpy's dtype
+    _sitk_np = {sitkUInt8: numpy.uint8,
+                sitkUInt16: numpy.uint16,
+                sitkUInt32: numpy.uint32,
+                sitkUInt64: numpy.uint64,
+                sitkInt8: numpy.int8,
+                sitkInt16: numpy.int16,
+                sitkInt32: numpy.int32,
+                sitkInt64: numpy.int64,
+                sitkFloat32: numpy.float32,
+                sitkFloat64: numpy.float64,
+                sitkComplexFloat32: numpy.complex64,
+                sitkComplexFloat64: numpy.complex128,
+                sitkVectorUInt8: numpy.uint8,
+                sitkVectorInt8: numpy.int8,
+                sitkVectorUInt16: numpy.uint16,
+                sitkVectorInt16: numpy.int16,
+                sitkVectorUInt32: numpy.uint32,
+                sitkVectorInt32: numpy.int32,
+                sitkVectorUInt64: numpy.uint64,
+                sitkVectorInt64: numpy.int64,
+                sitkVectorFloat32: numpy.float32,
+                sitkVectorFloat64: numpy.float64,
+                sitkLabelUInt8: numpy.uint8,
+                sitkLabelUInt16: numpy.uint16,
+                sitkLabelUInt32: numpy.uint32,
+                sitkLabelUInt64: numpy.uint64
+                }
+
+    return _sitk_np[sitkImage.GetPixelIDValue()]
+
+
+def _get_sitk_pixelid(numpy_array_type):
+    """Returns a SimpleITK PixelID given a numpy array."""
+
+    if not HAVE_NUMPY:
+        raise ImportError('Numpy not available.')
+
+    # This is a Mapping from numpy array types to sitks pixel types.
+    _np_sitk = {numpy.character: sitkUInt8,
+                numpy.uint8: sitkUInt8,
+                numpy.uint16: sitkUInt16,
+                numpy.uint32: sitkUInt32,
+                numpy.uint64: sitkUInt64,
+                numpy.int8: sitkInt8,
+                numpy.int16: sitkInt16,
+                numpy.int32: sitkInt32,
+                numpy.int64: sitkInt64,
+                numpy.float32: sitkFloat32,
+                numpy.float64: sitkFloat64,
+                numpy.complex64: sitkComplexFloat32,
+                numpy.complex128: sitkComplexFloat64
+                }
+
+    try:
+        return _np_sitk[numpy_array_type.dtype]
+    except KeyError:
+        for key in _np_sitk:
+            if numpy.issubdtype(numpy_array_type.dtype, key):
+                return _np_sitk[key]
+        raise TypeError('dtype: {0} is not supported.'.format(numpy_array_type.dtype))
+
+
+def _get_sitk_vector_pixelid(numpy_array_type):
+    """Returns a SimpleITK vector PixelID given a numpy array."""
+
+    if not HAVE_NUMPY:
+        raise ImportError('Numpy not available.')
+
+    # This is a Mapping from numpy array types to sitks pixel types.
+    _np_sitk = {numpy.character: sitkVectorUInt8,
+                numpy.uint8: sitkVectorUInt8,
+                numpy.uint16: sitkVectorUInt16,
+                numpy.uint32: sitkVectorUInt32,
+                numpy.uint64: sitkVectorUInt64,
+                numpy.int8: sitkVectorInt8,
+                numpy.int16: sitkVectorInt16,
+                numpy.int32: sitkVectorInt32,
+                numpy.int64: sitkVectorInt64,
+                numpy.float32: sitkVectorFloat32,
+                numpy.float64: sitkVectorFloat64,
+
+                }
+
+    try:
+        return _np_sitk[numpy_array_type.dtype]
+    except KeyError:
+        for key in _np_sitk:
+            if numpy.issubdtype(numpy_array_type.dtype, key):
+                return _np_sitk[key]
+        raise TypeError('dtype: {0} is not supported as an array.'.format(numpy_array_type.dtype))
+
+
+# SimplyITK <-> Numpy Array conversion support.
+
+def GetArrayViewFromImage(image):
+    """Get a NumPy ndarray view of a SimpleITK Image.
+
+    Returns a Numpy ndarray object as a "view" of the SimpleITK's Image buffer. This reduces pixel buffer copies, but
+     requires that the SimpleITK image object is kept around while the buffer is being used.
+    """
+
+    if not HAVE_NUMPY:
+        raise ImportError('NumPy not available.')
+
+    pixel_id = image.GetPixelIDValue()
+    assert pixel_id != sitkUnknown, "An SimpleITK image of Unknown pixel type should not exists!"
+
+    dtype = _get_numpy_dtype(image)
+
+    shape = image.GetSize()
+    if image.GetNumberOfComponentsPerPixel() > 1:
+        shape = (image.GetNumberOfComponentsPerPixel(), ) + shape
+
+    image.MakeUnique()
+
+    image_memory_view = _GetMemoryViewFromImage(image)
+    array_view = numpy.asarray(image_memory_view).view(dtype = dtype)
+    array_view.shape = shape[::-1]
+
+    return array_view
+
+
+def GetArrayFromImage(image):
+    """Get a NumPy ndarray from a SimpleITK Image.
+
+    This is a deep copy of the image buffer and is completely safe and without potential side effects.
+    """
+
+    # TODO: If the image is already not unique then a second copy may be made before the numpy copy is done.
+    array_view = GetArrayViewFromImage(image)
+
+    # perform deep copy of the image buffer
+    return numpy.array(array_view, copy=True)
+
+
+def GetImageFromArray(arr, isVector=None):
+    """ Get a SimpleITK Image from a numpy array.
+
+     If isVector is True, then the Image will have a Vector pixel type, and the last dimension of the array will be
+     considered the component index. By default when isVector is None, 4D arrays
+     are automatically considered 3D vector images, but 3D arrays are 3D images.
+    """
+
+    if not HAVE_NUMPY:
+        raise ImportError('Numpy not available.')
+
+    z = numpy.asarray(arr)
+
+    if isVector is None:
+      if z.ndim == 4 and z.dtype != numpy.complex64 and z.dtype != numpy.complex128:
+          isVector = True
+
+    if isVector:
+        id = _get_sitk_vector_pixelid(z)
+        if z.ndim > 2:
+            number_of_components = z.shape[-1]
+            shape = z.shape[-2::-1]
+        else:
+            number_of_components = 1
+            shape = z.shape[::-1]
+    else:
+        number_of_components = 1
+        id = _get_sitk_pixelid(z)
+        shape = z.shape[::-1]
+
+    # SimpleITK throws an exception if the image dimension is not supported
+    img = Image(shape, id, number_of_components)
+
+    _SetImageFromArray(z.tobytes(), img)
+
+    return img
+
+
+def ReadImage(fileName: Union[str, List[str]],
+              outputPixelType: "PixelIDValueEnum" = sitkUnknown,
+              imageIO: str = "") \
+        -> Image:
+    r"""ReadImage is a procedural interface to the ImageFileReader class which is convenient for most image reading
+     tasks.
+
+    This method can read a single image or a list of images into a volume.
+
+    Parameters
+    ----------
+    fileName
+     A single or a list of file names. the filename of an Image e.g. "cthead.mha"
+    outputPixelType
+     The pixel type of the returned Image. By default the value is sitkUnknown, which enable the output pixel type to
+     be same as the file. If the pixel type is specified then the itk::ConvertPixelBuffer will be used to convert the
+     pixels.
+    imageIO
+     The name of the ITK ImageIO to use to read the file. An option to override the automatically detected ImageIO used
+     to read the image. The available ImageIOs are listed by the GetRegisteredImageIOs method. If the ImageIO can not
+     be constructed an exception will be generated. If the ImageIO can not read the file an exception will be
+     generated.
+
+    Returns
+    -------
+     The provided image file name(s) read into an Image.
+
+    Also See
+    --------
+     itk::simple::ImageFileReader for reading a single file.
+     itk::simple::ImageSeriesReader for reading a series and meta-data dictionaries.
+
+    """
+
+    if isinstance(fileName, str):
+        reader = ImageFileReader()
+        reader.SetFileName(fileName)
+    else:
+        reader = ImageSeriesReader()
+        reader.SetFileNames(fileName)
+
+    reader.SetImageIO(imageIO)
+    reader.SetOutputPixelType(outputPixelType)
+    return reader.Execute()
+
+
+def WriteImage(image: "Image",
+               fileName: Union[str, List[str]],
+               useCompression: bool = False,
+               compressionLevel=-1,
+               *,
+               imageIO: str = "",
+               compressor: str = "") -> "None":
+    r"""
+    WriteImage is a procedural interface to the ImageFileWriter and ImageSeriesWriter classes which is convenient for
+    many image writing tasks.
+
+    For an input image of N dimensions, a series of N-1 dimensional (slices) images can be written by providing a list
+    if file names equal to the number of slices in the input image.
+
+    Parameters
+    ----------
+    image
+     the input image to be written
+    fileName
+     a single or a list of file names to be written
+    useCompression
+     request to compress the written file
+    compressionLevel
+     a hint for the amount of compression to be applied during writing
+    imageIO
+     the name of the ImageIO to perform the writing
+    compressor
+     a hint for the compression algorithm to use
+
+    Also See
+    --------
+     itk::simple::ImageFileWriter for writing a single file.
+     itk::simple::ImageSeriesWriter for writing a series of files
+    """
+    if isinstance(fileName, str):
+        writer = ImageFileWriter()
+        writer.SetFileName(fileName)
+    else:
+        writer = ImageSeriesWriter()
+        writer.SetFileNames(fileName)
+
+    writer.SetUseCompression(useCompression)
+    writer.SetCompressionLevel(compressionLevel)
+    writer.SetImageIO(imageIO)
+    writer.SetCompressor(compressor)
+    return writer.Execute(image)
+
+
+def SmoothingRecursiveGaussian(image1, sigma=[1]*3, normalizeAcrossScale=False):
+    """Computes the smoothing of an image by convolution with
+    the Gaussian kernels implemented as IIR filters.
+
+    This function directly calls the execute method of SmoothingRecursiveGaussianImageFilter
+    in order to support a procedural API.
+
+    Also See
+    --------
+      itk::simple::SmoothingRecursiveGaussianImageFilter for the object oriented interface
+    """
+
+    f = SmoothingRecursiveGaussianImageFilter()
+    f.SetSigma(sigma)
+    f.SetNormalizeAcrossScale(normalizeAcrossScale)
+    return f.Execute(image1)
+
+
+def DiscreteGaussian(image1, variance=[1] * 3, maximumKernelWidth=32, maximumError=0.01, useImageSpacing=True):
+    """Blurs an image by separable convolution with discrete
+     gaussian kernels. This filter performs Gaussian blurring by
+     separable convolution of an image and a discrete Gaussian
+     operator (kernel).
+
+     This function directly calls the execute method of DiscreteGaussianImageFilter
+     in order to support a procedural API.
+
+    Also See
+    --------
+      \sa itk::simple::DiscreteGaussianImageFilter for the object oriented interface
+    """
+    f = DiscreteGaussianImageFilter()
+    f.SetVariance(variance)
+    f.SetMaximumKernelWidth(maximumKernelWidth)
+    f.SetMaximumError(maximumError)
+    f.SetUseImageSpacing(useImageSpacing)
+    return f.Execute(image1)
+
+
+
+__all__ = ["Resample",
+           "GetArrayViewFromImage",
+           "GetArrayFromImage",
+           "GetImageFromArray",
+           "ReadImage",
+           "WriteImage",
+           "SmoothingRecursiveGaussian",
+           "DiscreteGaussian"]

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/async_timeout/__init__.py

@@ -0,0 +1,247 @@
+import asyncio
+import enum
+import sys
+import warnings
+from types import TracebackType
+from typing import Any, Optional, Type
+
+
+if sys.version_info >= (3, 8):
+    from typing import final
+else:
+    from typing_extensions import final
+
+
+__version__ = "4.0.2"
+
+
+__all__ = ("timeout", "timeout_at", "Timeout")
+
+
+def timeout(delay: Optional[float]) -> "Timeout":
+    """timeout context manager.
+
+    Useful in cases when you want to apply timeout logic around block
+    of code or in cases when asyncio.wait_for is not suitable. For example:
+
+    >>> async with timeout(0.001):
+    ...     async with aiohttp.get('https://github.com') as r:
+    ...         await r.text()
+
+
+    delay - value in seconds or None to disable timeout logic
+    """
+    loop = _get_running_loop()
+    if delay is not None:
+        deadline = loop.time() + delay  # type: Optional[float]
+    else:
+        deadline = None
+    return Timeout(deadline, loop)
+
+
+def timeout_at(deadline: Optional[float]) -> "Timeout":
+    """Schedule the timeout at absolute time.
+
+    deadline argument points on the time in the same clock system
+    as loop.time().
+
+    Please note: it is not POSIX time but a time with
+    undefined starting base, e.g. the time of the system power on.
+
+    >>> async with timeout_at(loop.time() + 10):
+    ...     async with aiohttp.get('https://github.com') as r:
+    ...         await r.text()
+
+
+    """
+    loop = _get_running_loop()
+    return Timeout(deadline, loop)
+
+
+class _State(enum.Enum):
+    INIT = "INIT"
+    ENTER = "ENTER"
+    TIMEOUT = "TIMEOUT"
+    EXIT = "EXIT"
+
+
+@final
+class Timeout:
+    # Internal class, please don't instantiate it directly
+    # Use timeout() and timeout_at() public factories instead.
+    #
+    # Implementation note: `async with timeout()` is preferred
+    # over `with timeout()`.
+    # While technically the Timeout class implementation
+    # doesn't need to be async at all,
+    # the `async with` statement explicitly points that
+    # the context manager should be used from async function context.
+    #
+    # This design allows to avoid many silly misusages.
+    #
+    # TimeoutError is raised immadiatelly when scheduled
+    # if the deadline is passed.
+    # The purpose is to time out as sson as possible
+    # without waiting for the next await expression.
+
+    __slots__ = ("_deadline", "_loop", "_state", "_timeout_handler")
+
+    def __init__(
+        self, deadline: Optional[float], loop: asyncio.AbstractEventLoop
+    ) -> None:
+        self._loop = loop
+        self._state = _State.INIT
+
+        self._timeout_handler = None  # type: Optional[asyncio.Handle]
+        if deadline is None:
+            self._deadline = None  # type: Optional[float]
+        else:
+            self.update(deadline)
+
+    def __enter__(self) -> "Timeout":
+        warnings.warn(
+            "with timeout() is deprecated, use async with timeout() instead",
+            DeprecationWarning,
+            stacklevel=2,
+        )
+        self._do_enter()
+        return self
+
+    def __exit__(
+        self,
+        exc_type: Optional[Type[BaseException]],
+        exc_val: Optional[BaseException],
+        exc_tb: Optional[TracebackType],
+    ) -> Optional[bool]:
+        self._do_exit(exc_type)
+        return None
+
+    async def __aenter__(self) -> "Timeout":
+        self._do_enter()
+        return self
+
+    async def __aexit__(
+        self,
+        exc_type: Optional[Type[BaseException]],
+        exc_val: Optional[BaseException],
+        exc_tb: Optional[TracebackType],
+    ) -> Optional[bool]:
+        self._do_exit(exc_type)
+        return None
+
+    @property
+    def expired(self) -> bool:
+        """Is timeout expired during execution?"""
+        return self._state == _State.TIMEOUT
+
+    @property
+    def deadline(self) -> Optional[float]:
+        return self._deadline
+
+    def reject(self) -> None:
+        """Reject scheduled timeout if any."""
+        # cancel is maybe better name but
+        # task.cancel() raises CancelledError in asyncio world.
+        if self._state not in (_State.INIT, _State.ENTER):
+            raise RuntimeError(f"invalid state {self._state.value}")
+        self._reject()
+
+    def _reject(self) -> None:
+        if self._timeout_handler is not None:
+            self._timeout_handler.cancel()
+            self._timeout_handler = None
+
+    def shift(self, delay: float) -> None:
+        """Advance timeout on delay seconds.
+
+        The delay can be negative.
+
+        Raise RuntimeError if shift is called when deadline is not scheduled
+        """
+        deadline = self._deadline
+        if deadline is None:
+            raise RuntimeError("cannot shift timeout if deadline is not scheduled")
+        self.update(deadline + delay)
+
+    def update(self, deadline: float) -> None:
+        """Set deadline to absolute value.
+
+        deadline argument points on the time in the same clock system
+        as loop.time().
+
+        If new deadline is in the past the timeout is raised immediatelly.
+
+        Please note: it is not POSIX time but a time with
+        undefined starting base, e.g. the time of the system power on.
+        """
+        if self._state == _State.EXIT:
+            raise RuntimeError("cannot reschedule after exit from context manager")
+        if self._state == _State.TIMEOUT:
+            raise RuntimeError("cannot reschedule expired timeout")
+        if self._timeout_handler is not None:
+            self._timeout_handler.cancel()
+        self._deadline = deadline
+        if self._state != _State.INIT:
+            self._reschedule()
+
+    def _reschedule(self) -> None:
+        assert self._state == _State.ENTER
+        deadline = self._deadline
+        if deadline is None:
+            return
+
+        now = self._loop.time()
+        if self._timeout_handler is not None:
+            self._timeout_handler.cancel()
+
+        task = _current_task(self._loop)
+        if deadline <= now:
+            self._timeout_handler = self._loop.call_soon(self._on_timeout, task)
+        else:
+            self._timeout_handler = self._loop.call_at(deadline, self._on_timeout, task)
+
+    def _do_enter(self) -> None:
+        if self._state != _State.INIT:
+            raise RuntimeError(f"invalid state {self._state.value}")
+        self._state = _State.ENTER
+        self._reschedule()
+
+    def _do_exit(self, exc_type: Optional[Type[BaseException]]) -> None:
+        if exc_type is asyncio.CancelledError and self._state == _State.TIMEOUT:
+            self._timeout_handler = None
+            raise asyncio.TimeoutError
+        # timeout has not expired
+        self._state = _State.EXIT
+        self._reject()
+        return None
+
+    def _on_timeout(self, task: "asyncio.Task[None]") -> None:
+        task.cancel()
+        self._state = _State.TIMEOUT
+        # drop the reference early
+        self._timeout_handler = None
+
+
+if sys.version_info >= (3, 7):
+
+    def _current_task(loop: asyncio.AbstractEventLoop) -> "Optional[asyncio.Task[Any]]":
+        return asyncio.current_task(loop=loop)
+
+else:
+
+    def _current_task(loop: asyncio.AbstractEventLoop) -> "Optional[asyncio.Task[Any]]":
+        return asyncio.Task.current_task(loop=loop)
+
+
+if sys.version_info >= (3, 7):
+
+    def _get_running_loop() -> asyncio.AbstractEventLoop:
+        return asyncio.get_running_loop()
+
+else:
+
+    def _get_running_loop() -> asyncio.AbstractEventLoop:
+        loop = asyncio.get_event_loop()
+        if not loop.is_running():
+            raise RuntimeError("no running event loop")
+        return loop

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/async_timeout/py.typed

@@ -0,0 +1 @@
+Placeholder

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/chardet-3.0.4.dist-info/INSTALLER

@@ -0,0 +1 @@
+conda

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/chardet-3.0.4.dist-info/LICENSE

@@ -0,0 +1,504 @@
+		  GNU LESSER GENERAL PUBLIC LICENSE
+		       Version 2.1, February 1999
+
+ Copyright (C) 1991, 1999 Free Software Foundation, Inc.
+     51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA
+ Everyone is permitted to copy and distribute verbatim copies
+ of this license document, but changing it is not allowed.
+
+[This is the first released version of the Lesser GPL.  It also counts
+ as the successor of the GNU Library Public License, version 2, hence
+ the version number 2.1.]
+
+			    Preamble
+
+  The licenses for most software are designed to take away your
+freedom to share and change it.  By contrast, the GNU General Public
+Licenses are intended to guarantee your freedom to share and change
+free software--to make sure the software is free for all its users.
+
+  This license, the Lesser General Public License, applies to some
+specially designated software packages--typically libraries--of the
+Free Software Foundation and other authors who decide to use it.  You
+can use it too, but we suggest you first think carefully about whether
+this license or the ordinary General Public License is the better
+strategy to use in any particular case, based on the explanations below.
+
+  When we speak of free software, we are referring to freedom of use,
+not price.  Our General Public Licenses are designed to make sure that
+you have the freedom to distribute copies of free software (and charge
+for this service if you wish); that you receive source code or can get
+it if you want it; that you can change the software and use pieces of
+it in new free programs; and that you are informed that you can do
+these things.
+
+  To protect your rights, we need to make restrictions that forbid
+distributors to deny you these rights or to ask you to surrender these
+rights.  These restrictions translate to certain responsibilities for
+you if you distribute copies of the library or if you modify it.
+
+  For example, if you distribute copies of the library, whether gratis
+or for a fee, you must give the recipients all the rights that we gave
+you.  You must make sure that they, too, receive or can get the source
+code.  If you link other code with the library, you must provide
+complete object files to the recipients, so that they can relink them
+with the library after making changes to the library and recompiling
+it.  And you must show them these terms so they know their rights.
+
+  We protect your rights with a two-step method: (1) we copyright the
+library, and (2) we offer you this license, which gives you legal
+permission to copy, distribute and/or modify the library.
+
+  To protect each distributor, we want to make it very clear that
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+modified by someone else and passed on, the recipients should know
+that what they have is not the original version, so that the original
+author's reputation will not be affected by problems that might be
+introduced by others.
+
+  Finally, software patents pose a constant threat to the existence of
+any free program.  We wish to make sure that a company cannot
+effectively restrict the users of a free program by obtaining a
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+any patent license obtained for a version of the library must be
+consistent with the full freedom of use specified in this license.
+
+  Most GNU software, including some libraries, is covered by the
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+General Public License, applies to certain designated libraries, and
+is quite different from the ordinary General Public License.  We use
+this license for certain libraries in order to permit linking those
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+
+  When a program is linked with a library, whether statically or using
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+
+  We call this license the "Lesser" General Public License because it
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+  For example, on rare occasions, there may be a special need to
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+  Although the Lesser General Public License is Less protective of the
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+   TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION
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+

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/chardet-3.0.4.dist-info/METADATA

@@ -0,0 +1,98 @@
+Metadata-Version: 2.1
+Name: chardet
+Version: 3.0.4
+Summary: Universal encoding detector for Python 2 and 3
+Home-page: https://github.com/chardet/chardet
+Author: Mark Pilgrim
+Author-email: mark@diveintomark.org
+Maintainer: Daniel Blanchard
+Maintainer-email: dan.blanchard@gmail.com
+License: LGPL
+Keywords: encoding,i18n,xml
+Platform: UNKNOWN
+Classifier: Development Status :: 4 - Beta
+Classifier: Intended Audience :: Developers
+Classifier: License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 2
+Classifier: Programming Language :: Python :: 2.6
+Classifier: Programming Language :: Python :: 2.7
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.3
+Classifier: Programming Language :: Python :: 3.4
+Classifier: Programming Language :: Python :: 3.5
+Classifier: Programming Language :: Python :: 3.6
+Classifier: Topic :: Software Development :: Libraries :: Python Modules
+Classifier: Topic :: Text Processing :: Linguistic
+
+Chardet: The Universal Character Encoding Detector
+--------------------------------------------------
+
+.. image:: https://img.shields.io/travis/chardet/chardet/stable.svg
+   :alt: Build status
+   :target: https://travis-ci.org/chardet/chardet
+
+.. image:: https://img.shields.io/coveralls/chardet/chardet/stable.svg
+   :target: https://coveralls.io/r/chardet/chardet
+
+.. image:: https://img.shields.io/pypi/v/chardet.svg
+   :target: https://warehouse.python.org/project/chardet/
+   :alt: Latest version on PyPI
+
+.. image:: https://img.shields.io/pypi/l/chardet.svg
+   :alt: License
+
+
+Detects
+ - ASCII, UTF-8, UTF-16 (2 variants), UTF-32 (4 variants)
+ - Big5, GB2312, EUC-TW, HZ-GB-2312, ISO-2022-CN (Traditional and Simplified Chinese)
+ - EUC-JP, SHIFT_JIS, CP932, ISO-2022-JP (Japanese)
+ - EUC-KR, ISO-2022-KR (Korean)
+ - KOI8-R, MacCyrillic, IBM855, IBM866, ISO-8859-5, windows-1251 (Cyrillic)
+ - ISO-8859-5, windows-1251 (Bulgarian)
+ - ISO-8859-1, windows-1252 (Western European languages)
+ - ISO-8859-7, windows-1253 (Greek)
+ - ISO-8859-8, windows-1255 (Visual and Logical Hebrew)
+ - TIS-620 (Thai)
+
+.. note::
+   Our ISO-8859-2 and windows-1250 (Hungarian) probers have been temporarily
+   disabled until we can retrain the models.
+
+Requires Python 2.6, 2.7, or 3.3+.
+
+Installation
+------------
+
+Install from `PyPI <https://pypi.python.org/pypi/chardet>`_::
+
+    pip install chardet
+
+Documentation
+-------------
+
+For users, docs are now available at https://chardet.readthedocs.io/.
+
+Command-line Tool
+-----------------
+
+chardet comes with a command-line script which reports on the encodings of one
+or more files::
+
+    % chardetect somefile someotherfile
+    somefile: windows-1252 with confidence 0.5
+    someotherfile: ascii with confidence 1.0
+
+About
+-----
+
+This is a continuation of Mark Pilgrim's excellent chardet. Previously, two
+versions needed to be maintained: one that supported python 2.x and one that
+supported python 3.x.  We've recently merged with `Ian Cordasco <https://github.com/sigmavirus24>`_'s
+`charade <https://github.com/sigmavirus24/charade>`_ fork, so now we have one
+coherent version that works for Python 2.6+.
+
+:maintainer: Dan Blanchard
+
+

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+chardet/latin1prober.py,sha256=S2IoORhFk39FEFOlSFWtgVybRiP6h7BlLldHVclNkU8,5370
+chardet/mbcharsetprober.py,sha256=AR95eFH9vuqSfvLQZN-L5ijea25NOBCoXqw8s5O9xLQ,3413
+chardet/mbcsgroupprober.py,sha256=h6TRnnYq2OxG1WdD5JOyxcdVpn7dG0q-vB8nWr5mbh4,2012
+chardet/mbcssm.py,sha256=SY32wVIF3HzcjY3BaEspy9metbNSKxIIB0RKPn7tjpI,25481
+chardet/sbcharsetprober.py,sha256=LDSpCldDCFlYwUkGkwD2oFxLlPWIWXT09akH_2PiY74,5657
+chardet/sbcsgroupprober.py,sha256=1IprcCB_k1qfmnxGC6MBbxELlKqD3scW6S8YIwdeyXA,3546
+chardet/sjisprober.py,sha256=IIt-lZj0WJqK4rmUZzKZP4GJlE8KUEtFYVuY96ek5MQ,3774
+chardet/universaldetector.py,sha256=qL0174lSZE442eB21nnktT9_VcAye07laFWUeUrjttY,12485
+chardet/utf8prober.py,sha256=IdD8v3zWOsB8OLiyPi-y_fqwipRFxV9Nc1eKBLSuIEw,2766
+chardet/version.py,sha256=sp3B08mrDXB-pf3K9fqJ_zeDHOCLC8RrngQyDFap_7g,242

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/chardet-3.0.4.dist-info/WHEEL

@@ -0,0 +1,6 @@
+Wheel-Version: 1.0
+Generator: bdist_wheel (0.35.1)
+Root-Is-Purelib: true
+Tag: py2-none-any
+Tag: py3-none-any
+

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/chardet-3.0.4.dist-info/entry_points.txt

@@ -0,0 +1,3 @@
+[console_scripts]
+chardetect = chardet.cli.chardetect:main
+

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/chardet-3.0.4.dist-info/top_level.txt

@@ -0,0 +1 @@
+chardet

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/conda_package_streaming/__init__.py

@@ -0,0 +1 @@
+__version__ = "0.9.0"

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/conda_package_streaming/extract.py

@@ -0,0 +1,85 @@
+"""
+Extract package to directory, with checks against tar members extracting outside
+the target directory.
+"""
+
+from __future__ import annotations
+
+import os
+import tarfile
+from errno import ELOOP
+from pathlib import Path
+from typing import Generator
+
+from . import exceptions, package_streaming
+
+__all__ = ["extract_stream", "extract"]
+
+
+def extract_stream(
+    stream: Generator[tuple[tarfile.TarFile, tarfile.TarInfo], None, None],
+    dest_dir: Path | str,
+):
+    """
+    Pipe ``stream_conda_component`` output here to extract every member into
+    dest_dir.
+
+    For ``.conda`` will need to be called twice (for info and pkg components);
+    for ``.tar.bz2`` every member is extracted.
+    """
+    dest_dir = os.path.realpath(dest_dir)
+
+    def is_within_dest_dir(name):
+        abs_target = os.path.realpath(os.path.join(dest_dir, name))
+        prefix = os.path.commonpath((dest_dir, abs_target))
+        return prefix == dest_dir
+
+    for tar_file, _ in stream:
+        # careful not to seek backwards
+        def checked_members():
+            # from conda_package_handling
+            for member in tar_file:
+                if not is_within_dest_dir(member.name):
+                    raise exceptions.SafetyError(f"contains unsafe path: {member.name}")
+                yield member
+
+        try:
+            tar_file.extractall(path=dest_dir, members=checked_members())
+        except OSError as e:
+            if e.errno == ELOOP:
+                raise exceptions.CaseInsensitiveFileSystemError() from e
+            raise
+
+        # next iteraton of for loop raises GeneratorExit in stream
+        stream.close()
+
+
+def extract(filename, dest_dir=None, fileobj=None):
+    """
+    Extract all components of conda package to dest_dir.
+
+    fileobj: must be seekable if provided, if a ``.conda`` package.
+    """
+    assert dest_dir, "dest_dir is required"
+    if str(filename).endswith(".conda"):
+        components = [
+            package_streaming.CondaComponent.pkg,
+            package_streaming.CondaComponent.info,
+        ]
+    else:  # .tar.bz2 doesn't filter by component
+        components = [package_streaming.CondaComponent.pkg]
+
+    closefd = False
+    if not fileobj:
+        fileobj = open(filename, "rb")
+        closefd = True
+
+    try:
+        for component in components:
+            stream = package_streaming.stream_conda_component(
+                filename, fileobj, component=component
+            )
+            extract_stream(stream, dest_dir)
+    finally:
+        if closefd:
+            fileobj.close()

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/conda_package_streaming/lazy_wheel.py

@@ -0,0 +1,265 @@
+"""Lazy ZIP over HTTP"""
+
+from __future__ import annotations
+
+import logging
+import zipfile
+from bisect import bisect_left, bisect_right
+from contextlib import contextmanager
+from tempfile import NamedTemporaryFile
+from typing import Any, Iterator
+from zipfile import BadZipfile, ZipFile
+
+from requests import Session
+from requests.models import CONTENT_CHUNK_SIZE, Response
+
+# from pip 22.0.3 with fixes & remove imports from pip
+
+
+log = logging.getLogger(__name__)
+
+# If-Match (etag) to detect file changed during fetch would also be nice
+HEADERS = {"Accept-Encoding": "identity"}
+
+
+class HTTPRangeRequestUnsupported(Exception):
+    pass
+
+
+class LazyZipOverHTTP:
+    """File-like object mapped to a ZIP file over HTTP.
+
+    This uses HTTP range requests to lazily fetch the file's content,
+    which is supposed to be fed to ZipFile.  If such requests are not
+    supported by the server, raise HTTPRangeRequestUnsupported
+    during initialization.
+    """
+
+    def __init__(
+        self, url: str, session: Session, chunk_size: int = CONTENT_CHUNK_SIZE
+    ) -> None:
+        # if CONTENT_CHUNK_SIZE is bigger than the file:
+        # In [8]: response.headers["Content-Range"]
+        # Out[8]: 'bytes 0-3133374/3133375'
+
+        self._request_count = 0
+
+        self._session, self._url, self._chunk_size = session, url, chunk_size
+
+        # initial range request for the end of the file
+        tail = self._stream_response(start="", end=CONTENT_CHUNK_SIZE)
+        # e.g. {'accept-ranges': 'bytes', 'content-length': '10240',
+        # 'content-range': 'bytes 12824-23063/23064', 'last-modified': 'Sat, 16
+        # Apr 2022 13:03:02 GMT', 'date': 'Thu, 21 Apr 2022 11:34:04 GMT'}
+
+        if tail.status_code != 206:
+            raise HTTPRangeRequestUnsupported("range request is not supported")
+
+        # lowercase content-range to support s3
+        self._length = int(tail.headers["content-range"].partition("/")[-1])
+        self._file = NamedTemporaryFile()
+        self.truncate(self._length)
+
+        # length is also in Content-Length and Content-Range header
+        with self._stay():
+            content_length = int(tail.headers["content-length"])
+            if hasattr(tail, "content"):
+                assert content_length == len(tail.content)
+            self.seek(self._length - content_length)
+            for chunk in tail.iter_content(self._chunk_size):
+                self._file.write(chunk)
+        self._left: list[int] = [self._length - content_length]
+        self._right: list[int] = [self._length - 1]
+
+    @property
+    def mode(self) -> str:
+        """Opening mode, which is always rb."""
+        return "rb"
+
+    @property
+    def name(self) -> str:
+        """Path to the underlying file."""
+        return self._file.name
+
+    def seekable(self) -> bool:
+        """Return whether random access is supported, which is True."""
+        return True
+
+    def close(self) -> None:
+        """Close the file."""
+        self._file.close()
+
+    @property
+    def closed(self) -> bool:
+        """Whether the file is closed."""
+        return self._file.closed
+
+    def read(self, size: int = -1) -> bytes:
+        """Read up to size bytes from the object and return them.
+
+        As a convenience, if size is unspecified or -1,
+        all bytes until EOF are returned.  Fewer than
+        size bytes may be returned if EOF is reached.
+        """
+        # BUG does not download correctly if size is unspecified
+        download_size = size
+        start, length = self.tell(), self._length
+        stop = length if size < 0 else min(start + download_size, length)
+        start = max(0, stop - download_size)
+        self._download(start, stop - 1)
+        return self._file.read(size)
+
+    def readable(self) -> bool:
+        """Return whether the file is readable, which is True."""
+        return True
+
+    def seek(self, offset: int, whence: int = 0) -> int:
+        """Change stream position and return the new absolute position.
+
+        Seek to offset relative position indicated by whence:
+        * 0: Start of stream (the default).  pos should be >= 0;
+        * 1: Current position - pos may be negative;
+        * 2: End of stream - pos usually negative.
+        """
+        return self._file.seek(offset, whence)
+
+    def tell(self) -> int:
+        """Return the current position."""
+        return self._file.tell()
+
+    def truncate(self, size: int | None = None) -> int:
+        """Resize the stream to the given size in bytes.
+
+        If size is unspecified resize to the current position.
+        The current stream position isn't changed.
+
+        Return the new file size.
+        """
+        return self._file.truncate(size)
+
+    def writable(self) -> bool:
+        """Return False."""
+        return False
+
+    def __enter__(self) -> LazyZipOverHTTP:
+        self._file.__enter__()
+        return self
+
+    def __exit__(self, *exc: Any) -> bool | None:
+        return self._file.__exit__(*exc)
+
+    @contextmanager
+    def _stay(self) -> Iterator[None]:
+        """Return a context manager keeping the position.
+
+        At the end of the block, seek back to original position.
+        """
+        pos = self.tell()
+        try:
+            yield
+        finally:
+            self.seek(pos)
+
+    def _check_zip(self) -> None:
+        """Check and download until the file is a valid ZIP."""
+        end = self._length - 1
+        for start in reversed(range(0, end, self._chunk_size)):
+            self._download(start, end)
+            with self._stay():
+                try:
+                    # For read-only ZIP files, ZipFile only needs
+                    # methods read, seek, seekable and tell.
+                    ZipFile(self)  # type: ignore
+                except BadZipfile:
+                    pass
+                else:
+                    break
+
+    def _stream_response(
+        self, start: int | str, end: int, base_headers: dict[str, str] = HEADERS
+    ) -> Response:
+        """Return HTTP response to a range request from start to end.
+
+        :param start: if "", request ``end` bytes from end of file."""
+        headers = base_headers.copy()
+        headers["Range"] = f"bytes={start}-{end}"
+        log.debug("%s", headers["Range"])
+        # TODO: Get range requests to be correctly cached
+        headers["Cache-Control"] = "no-cache"
+        self._request_count += 1
+        response = self._session.get(self._url, headers=headers, stream=True)
+        response.raise_for_status()
+        return response
+
+    def _merge(
+        self, start: int, end: int, left: int, right: int
+    ) -> Iterator[tuple[int, int]]:
+        """Return an iterator of intervals to be fetched.
+
+        Args:
+            start (int): Start of needed interval
+            end (int): End of needed interval
+            left (int): Index of first overlapping downloaded data
+            right (int): Index after last overlapping downloaded data
+        """
+        lslice, rslice = self._left[left:right], self._right[left:right]
+        i = start = min([start] + lslice[:1])
+        end = max([end] + rslice[-1:])
+        for j, k in zip(lslice, rslice):
+            if j > i:
+                yield i, j - 1
+            i = k + 1
+        if i <= end:
+            yield i, end
+        self._left[left:right], self._right[left:right] = [start], [end]
+
+    def _download(self, start: int, end: int) -> None:
+        """Download bytes from start to end inclusively."""
+        with self._stay():
+            left = bisect_left(self._right, start)
+            right = bisect_right(self._left, end)
+            for start, end in self._merge(start, end, left, right):
+                response = self._stream_response(start, end)
+                self.seek(start)
+                for chunk in response.iter_content(self._chunk_size):
+                    self._file.write(chunk)
+
+
+class LazyConda(LazyZipOverHTTP):
+    def prefetch(self, conda_file_id):
+        """
+        Conda fork specific. Prefetch the `.info` range from the remote archive.
+        Reduces number of Range requests to 2 or 3 (1 or 2 for the directory, 1
+        for the file).
+
+        conda_file_id: name of .conda without path or `.conda` extension
+        """
+        target_file = f"info-{conda_file_id}.tar.zst"
+        with self._stay():  # not strictly necessary
+            # try to read entire conda info in one request
+            zf = zipfile.ZipFile(self)
+            infolist = zf.infolist()
+            for i, info in enumerate(infolist):
+                if info.filename == target_file:
+                    # could be incorrect if zipfile was concatenated to another
+                    # file (not likely for .conda)
+                    start = info.header_offset
+                    try:
+                        end = infolist[i + 1].header_offset
+                        # or info.header_offset
+                        # + len(info.filename)
+                        # + len(info.extra)
+                        # + info.compress_size
+                        # (unless Zip64)
+                    except IndexError:
+                        end = zf.start_dir
+                    self.seek(start)
+                    self.read(end - start)
+                    log.debug(
+                        "prefetch %s-%s",
+                        info.header_offset,
+                        end,
+                    )
+                    break
+            else:
+                log.debug("no zip prefetch")

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/conda_package_streaming/s3.py

@@ -0,0 +1,83 @@
+"""
+Adapt s3 to package_streaming
+"""
+
+from __future__ import annotations
+
+import typing
+from contextlib import closing
+from typing import Any
+
+from . import package_streaming
+
+if typing.TYPE_CHECKING:  # pragma: no cover
+    from mypy_boto3_s3 import Client
+    from mypy_boto3_s3.type_defs import GetObjectOutputTypeDef
+else:
+    Client = GetObjectOutputTypeDef = None
+
+from .url import conda_reader_for_url
+
+__all__ = ["stream_conda_info", "conda_reader_for_s3"]
+
+
+class ResponseFacade:
+    def __init__(self, response: GetObjectOutputTypeDef):
+        self.response = response
+        self.raw: Any = response["Body"]
+
+    def raise_for_status(self):
+        # s3 get_object raises automatically?
+        pass
+
+    @property
+    def status_code(self):
+        return self.response["ResponseMetadata"]["HTTPStatusCode"]
+
+    @property
+    def headers(self):
+        # a case-sensitive dict; keys may be lowercased always?
+        return self.response["ResponseMetadata"]["HTTPHeaders"]
+
+    def iter_content(self, n: int):
+        return iter(lambda: self.raw.read(n), b"")
+
+
+class SessionFacade:
+    """
+    Make s3 client look just enough like a requests.session for LazyZipOverHTTP
+    """
+
+    def __init__(self, client: Client, bucket: str, key: str):
+        self.client = client
+        self.bucket = bucket
+        self.key = key
+
+    def get(self, url, *, headers: dict | None = None, stream=True):
+        if headers and "Range" in headers:
+            response = self.client.get_object(
+                Bucket=self.bucket, Key=self.key, Range=headers["Range"]
+            )
+        else:
+            response = self.client.get_object(Bucket=self.bucket, Key=self.key)
+        return ResponseFacade(response)
+
+
+def stream_conda_info(client, bucket, key):
+    """
+    Yield (tar, member) for conda package.
+
+    Just "info/" for .conda, all members for tar.
+    """
+    filename, conda = conda_reader_for_s3(client, bucket, key)
+
+    with closing(conda):
+        yield from package_streaming.stream_conda_info(filename, conda)
+
+
+def conda_reader_for_s3(client: Client, bucket: str, key: str):
+    """
+    Return (name, file_like) suitable for package_streaming APIs
+    """
+    session: Any = SessionFacade(client, bucket, key)
+    return conda_reader_for_url(key, session)

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/conda_package_streaming/transmute.py

@@ -0,0 +1,161 @@
+"""
+Convert .tar.bz2 to .conda
+
+Uses `tempfile.SpooledTemporaryFile` to buffer `pkg-*` `.tar` and `info-*`
+`.tar`, then compress directly into an open `ZipFile` at the end.
+`SpooledTemporaryFile` buffers the first 10MB of the package and its metadata in
+memory, but writes out to disk for larger packages.
+
+Conda packages created this way have `info-*` as the last element in the
+`ZipFile`, instead of the first for `.conda` packages created with pre-2.0
+`conda-package-handling`.
+"""
+
+from __future__ import annotations
+
+import json
+import os
+import shutil
+import tarfile
+import tempfile
+import zipfile
+from pathlib import Path
+from typing import Callable
+
+import zstandard
+
+# streams everything in .tar.bz2 mode
+from .package_streaming import CondaComponent, stream_conda_component
+
+# increase to reduce speed and increase compression (levels above 19 use much
+# more memory)
+ZSTD_COMPRESS_LEVEL = 19
+# increase to reduce compression and increase speed
+ZSTD_COMPRESS_THREADS = 1
+
+CONDA_PACKAGE_FORMAT_VERSION = 2
+
+
+def transmute(
+    package,
+    path,
+    *,
+    compressor: Callable[
+        [], zstandard.ZstdCompressor
+    ] = lambda: zstandard.ZstdCompressor(
+        level=ZSTD_COMPRESS_LEVEL, threads=ZSTD_COMPRESS_THREADS
+    ),
+    is_info: Callable[[str], bool] = lambda filename: filename.startswith("info/"),
+) -> Path:
+    """
+    Convert .tar.bz2 conda :package to .conda-format under path.
+
+    :param package: path to .tar.bz2 conda package
+    :param path: destination path for transmuted .conda package
+    :param compressor: A function that creates instances of
+        ``zstandard.ZstdCompressor()`` to override defaults.
+    :param is_info: A function that returns True if a file belongs in the
+        ``info`` component of a `.conda` package.  ``conda-package-handling``
+        (not this package ``conda-package-streaming``) uses a set of regular
+        expressions to keep expected items in the info- component, while other
+        items starting with ``info/`` wind up in the pkg- component.
+
+    :return: Path to transmuted package.
+    """
+    assert package.endswith(".tar.bz2"), "can only convert .tar.bz2 to .conda"
+    assert os.path.isdir(path)
+    file_id = os.path.basename(package)[: -len(".tar.bz2")]
+    output_path = Path(path, f"{file_id}.conda")
+
+    with tempfile.SpooledTemporaryFile() as info_file, tempfile.SpooledTemporaryFile() as pkg_file:
+        with tarfile.TarFile(fileobj=info_file, mode="w") as info_tar, tarfile.TarFile(
+            fileobj=pkg_file, mode="w"
+        ) as pkg_tar:
+            # If we wanted to compress these at a low setting to save temporary
+            # space, we could insert a file object that counts bytes written in
+            # front of a zstd (level between 1..3) compressor.
+            stream = iter(stream_conda_component(package))
+            for tar, member in stream:
+                tar_get = info_tar if is_info(member.name) else pkg_tar
+                if member.isfile():
+                    tar_get.addfile(member, tar.extractfile(member))
+                else:
+                    tar_get.addfile(member)
+
+            info_tar.close()
+            pkg_tar.close()
+
+            info_size = info_file.tell()
+            pkg_size = pkg_file.tell()
+
+            info_file.seek(0)
+            pkg_file.seek(0)
+
+        with zipfile.ZipFile(
+            output_path,
+            "x",  # x to not append to existing
+            compresslevel=zipfile.ZIP_STORED,
+        ) as conda_file:
+            # Use a maximum of one Zstd compressor, stream_writer at a time to save memory.
+            data_compress = compressor()
+
+            pkg_metadata = {"conda_pkg_format_version": CONDA_PACKAGE_FORMAT_VERSION}
+            conda_file.writestr("metadata.json", json.dumps(pkg_metadata))
+
+            with conda_file.open(
+                f"pkg-{file_id}.tar.zst", "w"
+            ) as pkg_file_zip, data_compress.stream_writer(
+                pkg_file_zip, size=pkg_size, closefd=False
+            ) as pkg_stream:
+                shutil.copyfileobj(pkg_file._file, pkg_stream)
+
+            with conda_file.open(
+                f"info-{file_id}.tar.zst", "w"
+            ) as info_file_zip, data_compress.stream_writer(
+                info_file_zip, size=info_size, closefd=False
+            ) as info_stream:
+                shutil.copyfileobj(info_file._file, info_stream)
+
+    return output_path
+
+
+def transmute_tar_bz2(
+    package: str,
+    path,
+) -> Path:
+    """
+    Convert .conda :package to .tar.bz2 format under path.
+
+    Can recompress .tar.bz2 packages.
+
+    :param package: path to `.conda` or `.tar.bz2` package.
+    :param path: destination path for transmuted package.
+
+    :return: Path to transmuted package.
+    """
+    assert package.endswith((".tar.bz2", ".conda")), "Unknown extension"
+    assert os.path.isdir(path)
+
+    incoming_format = ".conda" if package.endswith(".conda") else ".tar.bz2"
+
+    file_id = os.path.basename(package)[: -len(incoming_format)]
+
+    if incoming_format == ".conda":
+        # .tar.bz2 MUST place info/ first.
+        components = [CondaComponent.info, CondaComponent.pkg]
+    else:
+        # .tar.bz2 doesn't filter by component
+        components = [CondaComponent.pkg]
+
+    output_path = Path(path, f"{file_id}.tar.bz2")
+
+    with open(package, "rb") as fileobj, tarfile.open(output_path, "x:bz2") as pkg_tar:
+        for component in components:
+            stream = iter(stream_conda_component(package, fileobj, component=component))
+            for tar, member in stream:
+                if member.isfile():
+                    pkg_tar.addfile(member, tar.extractfile(member))
+                else:
+                    pkg_tar.addfile(member)
+
+    return output_path

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/einops_exts/einops_exts.py

@@ -0,0 +1,63 @@
+import re
+from torch import nn
+from functools import wraps, partial
+
+from einops import rearrange, reduce, repeat
+
+# checking shape
+# @nils-werner
+# https://github.com/arogozhnikov/einops/issues/168#issuecomment-1042933838
+
+def check_shape(tensor, pattern, **kwargs):
+    return rearrange(tensor, f"{pattern} -> {pattern}", **kwargs)
+
+# do same einops operations on a list of tensors
+
+def _many(fn):
+    @wraps(fn)
+    def inner(tensors, pattern, **kwargs):
+        return (fn(tensor, pattern, **kwargs) for tensor in tensors)
+    return inner
+
+# do einops with unflattening of anonymously named dimensions
+# (...flattened) ->  ...flattened
+
+def _with_anon_dims(fn):
+    @wraps(fn)
+    def inner(tensor, pattern, **kwargs):
+        regex = r'(\.\.\.[a-zA-Z]+)'
+        matches = re.findall(regex, pattern)
+        get_anon_dim_name = lambda t: t.lstrip('...')
+        dim_prefixes = tuple(map(get_anon_dim_name, set(matches)))
+
+        update_kwargs_dict = dict()
+
+        for prefix in dim_prefixes:
+            assert prefix in kwargs, f'dimension list "{prefix}" was not passed in'
+            dim_list = kwargs[prefix]
+            assert isinstance(dim_list, (list, tuple)), f'dimension list "{prefix}" needs to be a tuple of list of dimensions'
+            dim_names = list(map(lambda ind: f'{prefix}{ind}', range(len(dim_list))))
+            update_kwargs_dict[prefix] = dict(zip(dim_names, dim_list))
+
+        def sub_with_anonymous_dims(t):
+            dim_name_prefix = get_anon_dim_name(t.groups()[0])
+            return ' '.join(update_kwargs_dict[dim_name_prefix].keys())
+
+        pattern_new = re.sub(regex, sub_with_anonymous_dims, pattern)
+
+        for prefix, update_dict in update_kwargs_dict.items():
+            del kwargs[prefix]
+            kwargs.update(update_dict)
+
+        return fn(tensor, pattern_new, **kwargs)
+    return inner
+
+# generate all helper functions
+
+rearrange_many = _many(rearrange)
+repeat_many = _many(repeat)
+reduce_many = _many(reduce)
+
+rearrange_with_anon_dims = _with_anon_dims(rearrange)
+repeat_with_anon_dims = _with_anon_dims(repeat)
+reduce_with_anon_dims = _with_anon_dims(reduce)

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/einops_exts/torch.py

@@ -0,0 +1,19 @@
+from torch import nn
+from einops import rearrange
+
+# for rearranging to and from a pattern
+
+class EinopsToAndFrom(nn.Module):
+    def __init__(self, from_einops, to_einops, fn):
+        super().__init__()
+        self.from_einops = from_einops
+        self.to_einops = to_einops
+        self.fn = fn
+
+    def forward(self, x, **kwargs):
+        shape = x.shape
+        reconstitute_kwargs = dict(tuple(zip(self.from_einops.split(' '), shape)))
+        x = rearrange(x, f'{self.from_einops} -> {self.to_einops}')
+        x = self.fn(x, **kwargs)
+        x = rearrange(x, f'{self.to_einops} -> {self.from_einops}', **reconstitute_kwargs)
+        return x

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/elasticdeform/__init__.py

@@ -0,0 +1 @@
+from .deform_grid import deform_grid, deform_grid_gradient, deform_random_grid

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/elasticdeform/deform_grid.py

@@ -0,0 +1,455 @@
+import numpy
+import scipy.ndimage
+
+from . import _deform_grid
+
+def deform_random_grid(X, sigma=25, points=3, order=3, mode='constant', cval=0.0,
+                       crop=None, prefilter=True, axis=None,
+                       affine=None, rotate=None, zoom=None):
+    """
+    Elastic deformation with a random deformation grid
+
+    This generates a random, square deformation grid with displacements
+    sampled from from a normal distribution with standard deviation `sigma`.
+    The deformation is then applied to the image or list of images,
+
+    See ``deform_grid`` for a full description of the parameters.
+
+    Parameters
+    ----------
+    X : numpy array or list of arrays
+        image, or list of images of the same size
+    sigma : float
+        standard deviation of the normal distribution
+    points : array
+        number of points of the deformation grid
+    rotate : float or None
+        angle in degrees to rotate the output
+
+        This only works for 2D images and rotates the image around
+        the center of the output.
+    zoom : float or None
+        scale factor to zoom the output
+
+        This only works for 2D images and scales the image around
+        the center of the output.
+
+    See Also
+    --------
+    deform_grid : for a full description of the parameters.
+    """
+    # prepare inputs and axis selection
+    Xs = _normalize_inputs(X)
+    axis, deform_shape = _normalize_axis_list(axis, Xs)
+
+    if not isinstance(points, (list, tuple)):
+        points = [points] * len(deform_shape)
+
+    displacement = numpy.random.randn(len(deform_shape), *points) * sigma
+    return deform_grid(X, displacement, order, mode, cval, crop, prefilter, axis, affine, rotate, zoom)
+
+
+def deform_grid(X, displacement, order=3, mode='constant', cval=0.0, crop=None, prefilter=True, axis=None,
+                affine=None, rotate=None, zoom=None):
+    """
+    Elastic deformation with a deformation grid
+
+    The procedure generates a coarse displacement grid with a random displacement
+    for each grid point. This grid is then interpolated to compute a displacement for
+    each pixel in the input image. The input image is then deformed using the
+    displacement vectors and a spline interpolation.
+
+    Parameters
+    ----------
+    X : numpy array or list of arrays
+        image, or list of images of the same size
+
+        If X is a list of images, the values for order, mode and cval can be lists
+        to specify a different value for every image in X.
+    displacement : numpy array
+        displacement vectors for each control point
+
+        displacement is a NumPy array with displacement vectors for each
+        control points. For example, to deform a 2D image with 3 x 5 control
+        points, provide a displacement matrix of shape 2 x 3 x 5.
+    order : {0, 1, 2, 3, 4}
+        interpolation order
+    mode : ({nearest, wrap, reflect, mirror, constant})
+        border mode
+    cval : float
+        constant value to be used if mode == 'constant'
+    crop : None or list
+        None, or a list of slice() objects to crop the output
+
+        crop can be a list of slice() objects to crop the output with.
+        Only very simple slicing is supported: the slice start and stop values must
+        be positive and should not be larger than the output. Note that this parameter
+        is dependent of the axis parameter: if an axis list is given, crop must only
+        contain slice() objects for the dimensions in axis.
+    prefilter : bool
+        if True the input X will be pre-filtered with a spline filter
+    axis : None, int, a list of ints, or a list of lists of ints
+        the axes to deform over
+
+        axis indicates the axes on which the deformation should be applied.
+        The default (None) is to apply a deformation to all dimensions of the input.
+        Giving a single axis (int) or a tuple of axes will apply the deformation only
+        to those axes. The shape of the displacement must match this number of axes.
+        If multiple inputs are given, axis should be None or a list of tuples with
+        the axes for each input.
+    affine : None, numpy array of shape (ndim, ndim + 1)
+        affine transformation to apply to the output
+
+        The affine transformation is applied to the output during interpolation.
+    rotate : float or None
+        angle in degrees to rotate the output
+
+        This only works for 2D images and rotates the image around
+        the center of the output.
+    zoom : float or None
+        scale factor to zoom the output
+
+        This only works for 2D images and scales the image around
+        the center of the output.
+
+    Returns
+    -------
+    numpy array or list of arrays
+        The deformed image, or a list of deformed images if a list of inputs is given.
+
+    Notes
+    -----
+    See the SciPy documentation for scipy.ndimage.interpolation.map_coordinates
+    for more details on some of the parameters.
+
+    The elastic deformation approach is found in
+
+    * Ronneberger, Fischer, and Brox, "U-Net: Convolutional Networks for Biomedical
+      Image Segmentation"  https://arxiv.org/abs/1505.04597
+    * Cicek et al., "3D U-Net: Learning Dense Volumetric
+      Segmentation from Sparse Annotation"  https://arxiv.org/abs/1606.06650
+
+    Based on a Python implementation by Florian Calvet.
+    """
+    # prepare inputs and axis selection
+    Xs = _normalize_inputs(X)
+    axis, deform_shape = _normalize_axis_list(axis, Xs)
+
+    # prepare output cropping
+    output_shapes, output_offset = _compute_output_shapes(Xs, axis, deform_shape, crop)
+
+    # prepare other parameters
+    displacement = _normalize_displacement(displacement, Xs, axis)
+    order = _normalize_order(order, Xs)
+    mode = _normalize_mode(mode, Xs)
+    cval = _normalize_cval(cval, Xs)
+    affine = _normalize_affine(affine, axis)
+
+    # compute inverse affine given output affine
+    inverse_affine = _compute_inverse_affine(affine)
+
+    # add rotation and zoom to the inverse affine matrix
+    inverse_affine = _apply_rotation_and_zoom(rotate, zoom, inverse_affine, [output_shapes[0][d] for d in axis[0]])
+
+    # prefilter inputs
+    Xs_f = []
+    for i, x in enumerate(Xs):
+        if prefilter and order[i] > 1:
+            x_f = numpy.zeros_like(x)
+            for d in axis[i]:
+                scipy.ndimage.spline_filter1d(x, axis=d, order=order[i], output=x_f)
+                x = x_f
+            Xs_f.append(x_f)
+        else:
+            Xs_f.append(x)
+    # prefilter displacement
+    displacement_f = numpy.zeros_like(displacement)
+    for d in range(1, displacement.ndim):
+        scipy.ndimage.spline_filter1d(displacement, axis=d, order=3, output=displacement_f)
+        displacement = displacement_f
+
+    # prepare output arrays
+    outputs = [numpy.zeros(os, dtype=x.dtype) for os, x in zip(output_shapes, Xs)]
+
+    _deform_grid.deform_grid(Xs_f, displacement_f, output_offset, outputs, axis, order, mode, cval, inverse_affine)
+
+    if isinstance(X, list):
+        return outputs
+    else:
+        return outputs[0]
+
+
+def deform_grid_gradient(dY, displacement, order=3, mode='constant', cval=0.0, crop=None,
+                         prefilter=True, axis=None, X_shape=None,
+                         affine=None, rotate=None, zoom=None):
+    """
+    Gradient for deform_grid.
+
+    This method performs the backward operation that returns the gradient of deform_grid
+    with respect to the input. This is similar to performing an inverse deformation on
+    the gradient, but not exactly the same: this function gives an exact gradient that
+    also takes the interpolation into account.
+
+    The X_shape parameter specifices the shape of the original inputs, and is only
+    necessary if the crop parameter is used. Otherwise, the input shape is the same as
+    the shape of the gradient dY.
+
+    See the documentation for ``deform_grid``.
+
+    Parameters
+    ----------
+    dY : numpy array
+        the input gradient, or list of gradients of the same size
+    displacement : numpy array
+        displacement vectors for each control point
+    order : {0, 1, 2, 3, 4}
+        interpolation order
+    mode : ({nearest, wrap, reflect, mirror, constant})
+        border mode
+    cval : float
+        constant value to be used if mode == 'constant'
+    crop : None or list
+        None, or a list of slice() objects to crop the output
+    prefilter : bool
+        if True the input X will be pre-filtered with a spline filter
+    axis : None, int, a list of ints, or a list of lists of ints
+        the axes to deform over
+    X_shape: tuple with the shape of the input, or a list of tuples
+    affine : None, numpy array of shape (ndim, ndim + 1)
+        affine transformation to apply to the output
+    rotate : float or None
+        angle in degrees to rotate the output
+    zoom : float or None
+        scale factor to zoom the output
+
+    Returns
+    -------
+    numpy array
+        Returns the gradient with respect to X.
+
+    """
+    # prepare inputs
+    dYs = _normalize_inputs(dY)
+
+    # find input shape
+    if isinstance(X_shape, tuple):
+        X_shape = [X_shape]
+    elif X_shape is None:
+        if crop is not None:
+            raise ValueError("X_shape is required if the crop parameter is given.")
+        X_shape = [dy.shape for dy in dYs]
+
+    # initialize gradient outputs
+    dXs = [numpy.zeros(s, dy.dtype) for s, dy in zip(X_shape, dYs)]
+
+    # prepare axis selection
+    axis, deform_shape = _normalize_axis_list(axis, dXs)
+
+    # prepare cropping
+    output_shapes, output_offset = _compute_output_shapes(dXs, axis, deform_shape, crop)
+    if [tuple(s) for s in output_shapes] != [dy.shape for dy in dYs]:
+        raise ValueError("X_shape does not match output shape and cropping. "
+                         "Expected output shape is %s, but %s given."
+                         % (str(output_shapes), str([dy.shape for dy in dYs])))
+
+    # prepare other parameters
+    displacement = _normalize_displacement(displacement, dYs, axis)
+    order = _normalize_order(order, dYs)
+    mode = _normalize_mode(mode, dYs)
+    cval = _normalize_cval(cval, dYs)
+    affine = _normalize_affine(affine, axis)
+
+    # compute inverse affine given output affine
+    inverse_affine = _compute_inverse_affine(affine)
+
+    # add rotation and zoom to the affine matrix
+    inverse_affine = _apply_rotation_and_zoom(rotate, zoom, inverse_affine, [output_shapes[0][d] for d in axis[0]])
+
+    # prefilter displacement
+    displacement_f = numpy.zeros_like(displacement)
+    for d in range(1, displacement.ndim):
+        scipy.ndimage.spline_filter1d(displacement, axis=d, order=3, output=displacement_f)
+        displacement = displacement_f
+
+    _deform_grid.deform_grid_grad(dXs, displacement_f, output_offset, dYs, axis, order, mode, cval, inverse_affine)
+
+    # compute gradient of prefilter operation
+    dXs_f = []
+    for i, x in enumerate(dXs):
+        if prefilter and order[i] > 1:
+            x_f = numpy.zeros_like(x)
+            for d in axis[i]:
+                _deform_grid.spline_filter1d_grad(x, x_f, d, order[i])
+                x = x_f
+            dXs_f.append(x_f)
+        else:
+            dXs_f.append(x)
+
+    if isinstance(dY, list):
+        return dXs_f
+    else:
+        return dXs_f[0]
+
+
+
+def _normalize_inputs(X):
+    if isinstance(X, numpy.ndarray):
+        Xs = [X]
+    elif isinstance(X, list):
+        Xs = X
+    else:
+        raise Exception('X should be a numpy.ndarray or a list of numpy.ndarrays.')
+
+    # check X inputs
+    assert len(Xs) > 0, 'You must provide at least one image.'
+    assert all(isinstance(x, numpy.ndarray) for x in Xs), 'All elements of X should be numpy.ndarrays.'
+    return Xs
+
+def _normalize_axis_list(axis, Xs):
+    if axis is None:
+        axis = [tuple(range(x.ndim)) for x in Xs]
+    elif isinstance(axis, int):
+        axis = (axis,)
+    if isinstance(axis, tuple):
+        axis = [axis] * len(Xs)
+    assert len(axis) == len(Xs), 'Number of axis tuples should match number of inputs.'
+    input_shapes = []
+    for x, ax in zip(Xs, axis):
+        assert isinstance(ax, tuple), 'axis should be given as a tuple'
+        assert all(isinstance(a, int) for a in ax), 'axis must contain ints'
+        assert len(ax) == len(axis[0]), 'All axis tuples should have the same length.'
+        assert ax == tuple(set(ax)), 'axis must be sorted and unique'
+        assert all(0 <= a < x.ndim for a in ax), 'invalid axis for input'
+        input_shapes.append(tuple(x.shape[d] for d in ax))
+    assert len(set(input_shapes)) == 1, 'All inputs should have the same shape.'
+    deform_shape = input_shapes[0]
+    return axis, deform_shape
+
+def _compute_output_shapes(Xs, axis, deform_shape, crop):
+    if crop is not None:
+        assert isinstance(crop, (tuple, list)), "crop must be a tuple or a list."
+        assert len(crop) == len(deform_shape)
+        output_shapes = [list(x.shape) for x in Xs]
+        output_offset = [0 for d in range(len(axis[0]))]
+        for d in range(len(axis[0])):
+            if isinstance(crop[d], slice):
+                assert crop[d].step is None
+                start = (crop[d].start or 0)
+                stop = (crop[d].stop or deform_shape[d])
+                assert start >= 0
+                assert start < stop and stop <= deform_shape[d]
+                for i in range(len(Xs)):
+                    output_shapes[i][axis[i][d]] = stop - start
+                if start > 0:
+                    output_offset[d] = start
+            else:
+                raise Exception('Crop must be a slice.')
+        if any(o > 0 for o in output_offset):
+            output_offset = numpy.array(output_offset).astype('int64')
+        else:
+            output_offset = None
+    else:
+        output_shapes = [x.shape for x in Xs]
+        output_offset = None
+    return output_shapes, output_offset
+
+def _normalize_displacement(displacement, Xs, axis):
+    assert isinstance(displacement, numpy.ndarray), 'Displacement matrix should be a numpy.ndarray.'
+    assert displacement.ndim == len(axis[0]) + 1, 'Number of dimensions of displacement does not match input.'
+    assert displacement.shape[0] == len(axis[0]), 'First dimension of displacement should match number of input dimensions.'
+    return displacement
+
+def _normalize_order(order, Xs):
+    if not isinstance(order, (tuple, list)):
+        order = [order] * len(Xs)
+    assert len(Xs) == len(order), 'Number of order parameters should be equal to number of inputs.'
+    assert all(0 <= o and o <= 5 for o in order), 'order should be 0, 1, 2, 3, 4 or 5.'
+    return numpy.array(order).astype('int64')
+
+def _normalize_mode(mode, Xs):
+    if not isinstance(mode, (tuple, list)):
+        mode = [mode] * len(Xs)
+    mode = [_extend_mode_to_code(o) for o in mode]
+    assert len(Xs) == len(mode), 'Number of mode parameters should be equal to number of inputs.'
+    return numpy.array(mode).astype('int64')
+
+def _normalize_cval(cval, Xs):
+    if not isinstance(cval, (tuple, list)):
+        cval = [cval] * len(Xs)
+    assert len(Xs) == len(cval), 'Number of cval parameters should be equal to number of inputs.'
+    return numpy.array(cval).astype('float64')
+
+def _normalize_affine(affine, axis):
+    if affine is None:
+        return affine
+    n_axes = len(axis[0])
+    if affine.shape == (n_axes + 1, n_axes + 1):
+        assert numpy.allclose(affine[n_axes, :], [0, 0, 1]), 'Invalid affine matrix.'
+        affine = affine[:n_axes, :]
+    assert affine.shape == (n_axes, n_axes + 1), 'Affine matrix should have shape (ndim, ndim+1).'
+    return numpy.array(affine).astype('float64')
+
+def _compute_inverse_affine(affine):
+    if affine is None:
+        return None
+    else:
+        inverse_affine = numpy.zeros(affine.shape, dtype='float64')
+        inverse_affine[:, :-1] = numpy.linalg.inv(affine[:, :-1])
+        inverse_affine[:, -1] = -numpy.dot(inverse_affine[:, :-1], affine[:, -1])
+        return inverse_affine
+
+def _compute_rotation_zoom_affine(angle=None, zoom=None, center=None):
+    affine = None
+    if center is not None:
+        a = numpy.array([[1, 0, -center[0]],
+                         [0, 1, -center[1]],
+                         [0, 0, 1]])
+        affine = a if affine is None else numpy.dot(a, affine)
+    if angle:
+        theta = numpy.radians(angle)
+        a = numpy.array([[numpy.cos(theta), -numpy.sin(theta), 0],
+                         [numpy.sin(theta),  numpy.cos(theta), 0],
+                         [0, 0, 1]])
+        affine = a if affine is None else numpy.dot(a, affine)
+    if zoom:
+        a = numpy.array([[zoom, 0, 0],
+                         [0, zoom, 0],
+                         [0, 0, 1]])
+        affine = a if affine is None else numpy.dot(a, affine)
+    if center is not None:
+        a = numpy.array([[1, 0, center[0]],
+                         [0, 1, center[1]],
+                         [0, 0, 1]])
+        affine = a if affine is None else numpy.dot(a, affine)
+    return affine
+
+def _apply_rotation_and_zoom(rotate, zoom, inverse_affine, output_shape):
+    if rotate is None and zoom is None:
+        return inverse_affine
+    assert len(output_shape) == 2, 'Zoom and rotate is only implemented for 2D images.'
+    rotate = -float(rotate or 0)
+    zoom = 1 / float(zoom or 1)
+    new_inverse_affine = _compute_rotation_zoom_affine(angle=rotate, zoom=zoom, center=numpy.array(output_shape) / 2 - 0.5)
+    if inverse_affine is not None:
+        base_inverse_affine = numpy.eye(3, dtype='float64')
+        base_inverse_affine[:-1, :] = inverse_affine
+        return numpy.dot(new_inverse_affine, base_inverse_affine)[:2, :]
+    else:
+        return new_inverse_affine[:2, :]
+
+def _extend_mode_to_code(mode):
+    """Convert an extension mode to the corresponding integer code.
+    """
+    if mode == 'nearest':
+        return 0
+    elif mode == 'wrap':
+        return 1
+    elif mode == 'reflect':
+        return 2
+    elif mode == 'mirror':
+        return 3
+    elif mode == 'constant':
+        return 4
+    else:
+        raise RuntimeError('boundary mode not supported')
+

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/elasticdeform/tf.py

@@ -0,0 +1,72 @@
+import numpy
+import tensorflow
+import elasticdeform
+
+def deform_grid(X, displacement, *args, **kwargs):
+    """
+    Elastic deformation with a deformation grid, wrapped in a TensorFlow Op.
+
+    This function wraps the ``elasticdeform.deform_grid`` function in a TensorFlow Op
+    with a custom gradient.
+
+    Parameters
+    ----------
+    X : Tensor or list of Tensors
+        input image or list of input images
+    displacement : Tensor or numpy array
+        displacement vectors for each control point
+
+    Returns
+    -------
+    Tensor
+       the deformed image, or a list of deformed images
+
+    See Also
+    --------
+    elasticdeform.deform_grid : for the other parameters
+    """
+    use_tf_v1 = hasattr(tensorflow, 'py_func')
+    @tensorflow.custom_gradient
+    def f(displacement, *xs):
+        def fwd(displacement, *xs):
+            if not use_tf_v1:
+                xs = [x.numpy() for x in list(xs)]
+                displacement = displacement.numpy()
+            return elasticdeform.deform_grid(list(xs), displacement, *args, **kwargs)
+
+        def bwd(*dys):
+            def grad(*dys_disp_xs):
+                dys = list(dys_disp_xs[:len(xs)])
+                displacement = dys_disp_xs[len(xs)]
+                X_shape = [x.shape for x in dys_disp_xs[len(xs) + 1:]]
+                if not use_tf_v1:
+                    dys = [dy.numpy() for dy in dys]
+                    displacement = displacement.numpy()
+                dXs = elasticdeform.deform_grid_gradient(dys, displacement,
+                                                         *args, X_shape=X_shape, **kwargs)
+                return [numpy.nan * displacement] + dXs
+            grad_inputs = dys + (displacement,) + xs
+            grad_output_dtypes = [displacement.dtype] + [x.dtype for x in xs]
+            if use_tf_v1:
+                # TensorFlow 1
+                return tensorflow.py_func(grad, grad_inputs, grad_output_dtypes,
+                                          stateful=False, name='DeformGridGrad')
+            else:
+                # TensorFlow 2
+                return tensorflow.py_function(grad, grad_inputs, grad_output_dtypes,
+                                              name='DeformGridGrad')
+
+        inputs = (displacement,) + xs
+        output_dtypes = [x.dtype for x in xs]
+        if use_tf_v1:
+            # TensorFlow 1
+            y = tensorflow.py_func(fwd, inputs, output_dtypes, stateful=False, name='DeformGrid')
+        else:
+            # TensorFlow 2
+            y = tensorflow.py_function(fwd, inputs, output_dtypes, name='DeformGrid')
+        return y, bwd
+
+    if isinstance(X, (list, tuple)):
+        return f(displacement, *X)
+    else:
+        return f(displacement, X)[0]

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/elasticdeform/torch.py

@@ -0,0 +1,66 @@
+import numpy
+import torch
+import elasticdeform
+
+class ElasticDeform(torch.autograd.Function):
+    @staticmethod
+    def forward(ctx, displacement, deform_args, deform_kwargs, *xs):
+        ctx.save_for_backward(displacement)
+        ctx.deform_args = deform_args
+        ctx.deform_kwargs = deform_kwargs
+        ctx.x_shapes = [x.shape for x in xs]
+
+        xs_numpy = [x.detach().cpu().numpy() for x in xs]
+        displacement = displacement.detach().cpu().numpy()
+        ys = elasticdeform.deform_grid(xs_numpy, displacement, *deform_args, **deform_kwargs)
+        return tuple(torch.tensor(y, device=x.device) for x, y in zip(xs, ys))
+
+    @staticmethod
+    def backward(ctx, *dys):
+        displacement, = ctx.saved_tensors
+        deform_args = ctx.deform_args
+        deform_kwargs = ctx.deform_kwargs
+        x_shapes = ctx.x_shapes
+
+        dys_numpy = [dy.detach().cpu().numpy() for dy in dys]
+        displacement = displacement.detach().cpu().numpy()
+        dxs = elasticdeform.deform_grid_gradient(dys_numpy, displacement,
+                                                 *deform_args, X_shape=x_shapes, **deform_kwargs)
+        return (None, None, None) + tuple(torch.tensor(dx, device=dy.device) for dx, dy in zip(dxs, dys))
+
+
+
+def deform_grid(X, displacement, *args, **kwargs):
+    """
+    Elastic deformation with a deformation grid, wrapped for PyTorch.
+
+    This function wraps the ``elasticdeform.deform_grid`` function in a PyTorch function
+    with a custom gradient.
+
+    Parameters
+    ----------
+    X : torch.Tensor or list of torch.Tensors
+        input image or list of input images
+    displacement : torch.Tensor
+        displacement vectors for each control point
+
+    Returns
+    -------
+    torch.Tensor
+       the deformed image, or a list of deformed images
+
+    See Also
+    --------
+    elasticdeform.deform_grid : for the other parameters
+    """
+    if not isinstance(X, (list, tuple)):
+        X_list = [X]
+    else:
+        X_list = X
+    displacement = torch.as_tensor(displacement)
+    y = ElasticDeform.apply(displacement, args, kwargs, *X_list)
+
+    if isinstance(X, (list, tuple)):
+        return y
+    else:
+        return y[0]

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/frozenlist-1.3.0.dist-info/INSTALLER

@@ -0,0 +1 @@
+pip

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/frozenlist-1.3.0.dist-info/LICENSE

@@ -0,0 +1,201 @@
+Apache License
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my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/frozenlist-1.3.0.dist-info/METADATA

@@ -0,0 +1,152 @@
+Metadata-Version: 2.1
+Name: frozenlist
+Version: 1.3.0
+Summary: A list-like structure which implements collections.abc.MutableSequence
+Home-page: https://github.com/aio-libs/frozenlist
+Maintainer: aiohttp team <team@aiohttp.org>
+Maintainer-email: team@aiohttp.org
+License: Apache 2
+Project-URL: Chat: Gitter, https://gitter.im/aio-libs/Lobby
+Project-URL: CI: Github Actions, https://github.com/aio-libs/frozenlist/actions
+Project-URL: Coverage: codecov, https://codecov.io/github/aio-libs/frozenlist
+Project-URL: Docs: RTD, https://frozenlist.readthedocs.io
+Project-URL: GitHub: issues, https://github.com/aio-libs/frozenlist/issues
+Project-URL: GitHub: repo, https://github.com/aio-libs/frozenlist
+Platform: UNKNOWN
+Classifier: License :: OSI Approved :: Apache Software License
+Classifier: Intended Audience :: Developers
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.7
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Operating System :: POSIX
+Classifier: Operating System :: MacOS :: MacOS X
+Classifier: Operating System :: Microsoft :: Windows
+Requires-Python: >=3.7
+Description-Content-Type: text/x-rst
+License-File: LICENSE
+
+==========
+frozenlist
+==========
+
+.. image:: https://github.com/aio-libs/frozenlist/workflows/CI/badge.svg
+   :target: https://github.com/aio-libs/frozenlist/actions
+   :alt: GitHub status for master branch
+
+.. image:: https://codecov.io/gh/aio-libs/frozenlist/branch/master/graph/badge.svg
+   :target: https://codecov.io/gh/aio-libs/frozenlist
+   :alt: codecov.io status for master branch
+
+.. image:: https://badge.fury.io/py/frozenlist.svg
+   :target: https://pypi.org/project/frozenlist
+   :alt: Latest PyPI package version
+
+.. image:: https://readthedocs.org/projects/frozenlist/badge/?version=latest
+   :target: https://frozenlist.readthedocs.io/
+   :alt: Latest Read The Docs
+
+.. image:: https://img.shields.io/discourse/topics?server=https%3A%2F%2Faio-libs.discourse.group%2F
+   :target: https://aio-libs.discourse.group/
+   :alt: Discourse group for io-libs
+
+.. image:: https://badges.gitter.im/Join%20Chat.svg
+   :target: https://gitter.im/aio-libs/Lobby
+   :alt: Chat on Gitter
+
+Introduction
+============
+
+``frozenlist.FrozenList`` is a list-like structure which implements
+``collections.abc.MutableSequence``. The list is *mutable* until ``FrozenList.freeze``
+is called, after which list modifications raise ``RuntimeError``:
+
+
+>>> from frozenlist import FrozenList
+>>> fl = FrozenList([17, 42])
+>>> fl.append('spam')
+>>> fl.append('Vikings')
+>>> fl
+<FrozenList(frozen=False, [17, 42, 'spam', 'Vikings'])>
+>>> fl.freeze()
+>>> fl
+<FrozenList(frozen=True, [17, 42, 'spam', 'Vikings'])>
+>>> fl.frozen
+True
+>>> fl.append("Monty")
+Traceback (most recent call last):
+  File "<stdin>", line 1, in <module>
+  File "frozenlist/_frozenlist.pyx", line 97, in frozenlist._frozenlist.FrozenList.append
+    self._check_frozen()
+  File "frozenlist/_frozenlist.pyx", line 19, in frozenlist._frozenlist.FrozenList._check_frozen
+    raise RuntimeError("Cannot modify frozen list.")
+RuntimeError: Cannot modify frozen list.
+
+
+FrozenList is also hashable, but only when frozen. Otherwise it also throws a RuntimeError:
+
+
+>>> fl = FrozenList([17, 42, 'spam'])
+>>> hash(fl)
+Traceback (most recent call last):
+  File "<stdin>", line 1, in <module>
+  File "frozenlist/_frozenlist.pyx", line 111, in frozenlist._frozenlist.FrozenList.__hash__
+    raise RuntimeError("Cannot hash unfrozen list.")
+RuntimeError: Cannot hash unfrozen list.
+>>> fl.freeze()
+>>> hash(fl)
+3713081631934410656
+>>> dictionary = {fl: 'Vikings'} # frozen fl can be a dict key
+>>> dictionary
+{<FrozenList(frozen=True, [1, 2])>: 'Vikings'}
+
+
+Installation
+------------
+
+::
+
+   $ pip install frozenlist
+
+The library requires Python 3.6 or newer.
+
+
+Documentation
+=============
+
+https://frozenlist.readthedocs.io/
+
+Communication channels
+======================
+
+*aio-libs discourse group*: https://aio-libs.discourse.group
+
+Feel free to post your questions and ideas here.
+
+*gitter chat* https://gitter.im/aio-libs/Lobby
+
+Requirements
+============
+
+- Python >= 3.6
+
+License
+=======
+
+``frozenlist`` is offered under the Apache 2 license.
+
+Source code
+===========
+
+The project is hosted on GitHub_
+
+Please file an issue in the `bug tracker
+<https://github.com/aio-libs/frozenlist/issues>`_ if you have found a bug
+or have some suggestions to improve the library.
+
+.. _GitHub: https://github.com/aio-libs/frozenlist
+
+

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/frozenlist-1.3.0.dist-info/RECORD

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my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/frozenlist-1.3.0.dist-info/WHEEL

@@ -0,0 +1,8 @@
+Wheel-Version: 1.0
+Generator: bdist_wheel (0.37.1)
+Root-Is-Purelib: false
+Tag: cp38-cp38-manylinux_2_5_x86_64
+Tag: cp38-cp38-manylinux1_x86_64
+Tag: cp38-cp38-manylinux_2_17_x86_64
+Tag: cp38-cp38-manylinux2014_x86_64
+

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/frozenlist-1.3.0.dist-info/top_level.txt

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my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/grpcio-1.47.0.dist-info/INSTALLER

@@ -0,0 +1 @@
+pip

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/grpcio-1.47.0.dist-info/LICENSE

@@ -0,0 +1,242 @@
+
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
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+
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+
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my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/grpcio-1.47.0.dist-info/METADATA

@@ -0,0 +1,144 @@
+Metadata-Version: 2.1
+Name: grpcio
+Version: 1.47.0
+Summary: HTTP/2-based RPC framework
+Home-page: https://grpc.io
+Author: The gRPC Authors
+Author-email: grpc-io@googlegroups.com
+License: Apache License 2.0
+Platform: UNKNOWN
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.5
+Classifier: Programming Language :: Python :: 3.6
+Classifier: Programming Language :: Python :: 3.7
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: License :: OSI Approved :: Apache Software License
+Requires-Python: >=3.6
+License-File: LICENSE
+Requires-Dist: six (>=1.5.2)
+Requires-Dist: futures (>=2.2.0) ; python_version < "3.2"
+Requires-Dist: enum34 (>=1.0.4) ; python_version < "3.4"
+Provides-Extra: protobuf
+Requires-Dist: grpcio-tools (>=1.47.0) ; extra == 'protobuf'
+
+gRPC Python
+===========
+
+|compat_check_pypi|
+
+Package for gRPC Python.
+
+.. |compat_check_pypi| image:: https://python-compatibility-tools.appspot.com/one_badge_image?package=grpcio
+   :target: https://python-compatibility-tools.appspot.com/one_badge_target?package=grpcio
+
+Supported Python Versions
+-------------------------
+Python >= 3.6
+
+Installation
+------------
+
+gRPC Python is available for Linux, macOS, and Windows.
+
+Installing From PyPI
+~~~~~~~~~~~~~~~~~~~~
+
+If you are installing locally...
+
+::
+
+  $ pip install grpcio
+
+Else system wide (on Ubuntu)...
+
+::
+
+  $ sudo pip install grpcio
+
+If you're on Windows make sure that you installed the :code:`pip.exe` component
+when you installed Python (if not go back and install it!) then invoke:
+
+::
+
+  $ pip.exe install grpcio
+
+Windows users may need to invoke :code:`pip.exe` from a command line ran as
+administrator.
+
+n.b. On Windows and on Mac OS X one *must* have a recent release of :code:`pip`
+to retrieve the proper wheel from PyPI. Be sure to upgrade to the latest
+version!
+
+Installing From Source
+~~~~~~~~~~~~~~~~~~~~~~
+
+Building from source requires that you have the Python headers (usually a
+package named :code:`python-dev`).
+
+::
+
+  $ export REPO_ROOT=grpc  # REPO_ROOT can be any directory of your choice
+  $ git clone -b RELEASE_TAG_HERE https://github.com/grpc/grpc $REPO_ROOT
+  $ cd $REPO_ROOT
+  $ git submodule update --init
+
+  # For the next two commands do `sudo pip install` if you get permission-denied errors
+  $ pip install -rrequirements.txt
+  $ GRPC_PYTHON_BUILD_WITH_CYTHON=1 pip install .
+
+You cannot currently install Python from source on Windows. Things might work
+out for you in MSYS2 (follow the Linux instructions), but it isn't officially
+supported at the moment.
+
+Troubleshooting
+~~~~~~~~~~~~~~~
+
+Help, I ...
+
+* **... see a** :code:`pkg_resources.VersionConflict` **when I try to install
+  grpc**
+
+  This is likely because :code:`pip` doesn't own the offending dependency,
+  which in turn is likely because your operating system's package manager owns
+  it. You'll need to force the installation of the dependency:
+
+  :code:`pip install --ignore-installed $OFFENDING_DEPENDENCY`
+
+  For example, if you get an error like the following:
+
+  ::
+
+    Traceback (most recent call last):
+    File "<string>", line 17, in <module>
+     ...
+    File "/usr/lib/python2.7/dist-packages/pkg_resources.py", line 509, in find
+      raise VersionConflict(dist, req)
+    pkg_resources.VersionConflict: (six 1.8.0 (/usr/lib/python2.7/dist-packages), Requirement.parse('six>=1.10'))
+
+  You can fix it by doing:
+
+  ::
+
+    sudo pip install --ignore-installed six
+
+* **... see the following error on some platforms**
+
+  ::
+
+    /tmp/pip-build-U8pSsr/cython/Cython/Plex/Scanners.c:4:20: fatal error: Python.h: No such file or directory
+    #include "Python.h"
+                    ^
+    compilation terminated.
+
+  You can fix it by installing `python-dev` package. i.e
+
+  ::
+
+    sudo apt-get install python-dev
+
+
+

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+grpcio-1.47.0.dist-info/WHEEL,sha256=-ijGDuALlPxm3HbhKntps0QzHsi-DPlXqgerYTTJkFE,148
+grpcio-1.47.0.dist-info/top_level.txt,sha256=eEd2Jq_aVQFp38bWW8Pfwjz_5iibqeOFT-2zXlPAq_8,5

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/grpcio-1.47.0.dist-info/WHEEL

@@ -0,0 +1,6 @@
+Wheel-Version: 1.0
+Generator: bdist_wheel (0.37.1)
+Root-Is-Purelib: false
+Tag: cp38-cp38-manylinux_2_17_x86_64
+Tag: cp38-cp38-manylinux2014_x86_64
+

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/grpcio-1.47.0.dist-info/top_level.txt

@@ -0,0 +1 @@
+grpc

my_container_sandbox/workspace/anaconda3/lib/python3.8/site-packages/networkx-2.8.5.dist-info/INSTALLER

@@ -0,0 +1 @@
+pip