pip install azureml-sdk failing: Could not find a version that satisfies the requirement dotnetcore2>=2.1.9

[dumbledad]

• Package Name: azureml-sdk
• Operating System: Windows 10 Enterprise Insider Preview Dell XPS 15 laptop (build 19551.1001)
• Python Version: 3.7.0 (v3.7.0:1bf9cc5093, Jun 27 2018, 04:59:51) [MSC v.1914 64 bit (AMD64)]

Describe the bug
pip install azureml-sdk failing

To Reproduce
pip install azureml-sdk

Expected behavior
I expect pip to install the AzureML SDK

Actual behavior

ERROR: Could not find a version that satisfies the requirement dotnetcore2>=2.1.9 (from azureml-dataprep[fuse]<1.2.0a,>=1.1.37a->azureml-sdk) (from versions: none)
ERROR: No matching distribution found for dotnetcore2>=2.1.9 (from azureml-dataprep[fuse]<1.2.0a,>=1.1.37a->azureml-sdk)

Screenshots

Additional context
I have downloaded and installed the .Net Core SDK and runtime from https://dotnet.microsoft.com/download/

[allenjzhang]

Can you run in the same window dotnet --version?

[marcelaldecoa]

TL;DR

Just upgrade your PIP to 20.0.2.

Had same issue and the problem was related to the version of the PIP

Had same issue and the problem was related to the version of the PIP. Downgrade to a version such as 19.3.1 or better, upgrade to 20.0.2 that fixes the issue #7626.

Below we have a deep dive on the issue.

Why upgrading to PIP 20.0.1 is failing dotnetcore2

According to the PIP release notes, the version 20.0.1 is based on the version 20.0.0 that contains deprecations and removals, including the issue #6908.

A closer inspection to the pull request #7354 reveled a number of changes to the file pep425tags.py, which Generate and work with PEP 425 Compatibility Tags.

Let's run some code to understand that.

Using PIP 19.3.1

# Make sure to use PIP 19.3.1
pip --version

# Return the supported tags
python -c "import pip._internal.pep425tags; print(pip._internal.pep425tags.get_supported())"

will return

[('cp36', 'cp36m', 'manylinux2014_x86_64'), ('cp36', 'cp36m', 'manylinux2010_x86_64'), ('cp36', 'cp36m', 'manylinux1_x86_64'), ('cp36', 'cp36m', 'linux_x86_64'), ('cp36', 'abi3', 'manylinux2014_x86_64'), ('cp36', 'abi3', 'manylinux2010_x86_64'), ('cp36', 'abi3', 'manylinux1_x86_64'), ('cp36', 'abi3', 'linux_x86_64'), ('cp36', 'none', 'manylinux2014_x86_64'), ('cp36', 'none', 'manylinux2010_x86_64'), ('cp36', 'none', 'manylinux1_x86_64'), ('cp36', 'none', 'linux_x86_64'), ('cp35', 'abi3', 'manylinux2014_x86_64'), ('cp35', 'abi3', 'manylinux2010_x86_64'), ('cp35', 'abi3', 'manylinux1_x86_64'), ('cp35', 'abi3', 'linux_x86_64'), ('cp34', 'abi3', 'manylinux2014_x86_64'), ('cp34', 'abi3', 'manylinux2010_x86_64'), ('cp34', 'abi3', 'manylinux1_x86_64'), ('cp34', 'abi3', 'linux_x86_64'), ('cp33', 'abi3', 'manylinux2014_x86_64'), ('cp33', 'abi3', 'manylinux2010_x86_64'), ('cp33', 'abi3', 'manylinux1_x86_64'), ('cp33', 'abi3', 'linux_x86_64'), ('cp32', 'abi3', 'manylinux2014_x86_64'), ('cp32', 'abi3', 'manylinux2010_x86_64'), ('cp32', 'abi3', 'manylinux1_x86_64'), ('cp32', 'abi3', 'linux_x86_64'), ('py3', 'none', 'manylinux2014_x86_64'), ('py3', 'none', 'manylinux2010_x86_64'), ('py3', 'none', 'manylinux1_x86_64'), ('py3', 'none', 'linux_x86_64'), ('cp36', 'none', 'any'), ('cp3', 'none', 'any'), ('py36', 'none', 'any'), ('py3', 'none', 'any'), ('py35', 'none', 'any'), ('py34', 'none', 'any'), ('py33', 'none', 'any'), ('py32', 'none', 'any'), ('py31', 'none', 'any'), ('py30', 'none', 'any')]

From this list what matters to us is the tupple ('py3', 'none', 'linux_x86_64'). Why? Because if we download the wheel dotnetcore2-2.1.12-py3-none-manylinux1_x86_64.whl, rename the file to .zip, decompress it and open the file dotnetcore2-2.1.12.dist-info/WHEEL, we will see the following...

Wheel-Version: 1.0
Generator: bdist_wheel (0.32.3)
Root-Is-Purelib: true
Tag: py3-none-linux_x86_64

Notice the line Tag: py3-none-linux_x86_64, compatible with the supported tags as we saw in the tupple ('py3', 'none', 'linux_x86_64').

Using PIP 20.0.1

# Upgrade to PIP 20.0.1
python -m pip install pip==20.0.1

# Make sure it is upgraded to 20.0.1
pip --version

# Return the supported tags
python -c "import pip._internal.pep425tags; print(pip._internal.pep425tags.get_supported())"

will return

[<cp36-cp36m-manylinux2014_x86_64 @ 140664842340808>, <cp36-cp36m-manylinux2010_x86_64 @ 140664842340680>, <cp36-cp36m-manylinux1_x86_64 @ 140664842340744>, <cp36-cp36m-linux_x86_64 @ 140664842340872>, <cp36-abi3-manylinux2014_x86_64 @ 140664842341000>, <cp36-abi3-manylinux2010_x86_64 @ 140664842341064>, <cp36-abi3-manylinux1_x86_64 @ 140664842341128>, <cp36-abi3-linux_x86_64 @ 140664842341192>, <cp36-none-manylinux2014_x86_64 @ 140664842341320>, <cp36-none-manylinux2010_x86_64 @ 140664842341384>, <cp36-none-manylinux1_x86_64 @ 140664842341448>, <cp36-none-linux_x86_64 @ 140664842341512>, <cp35-abi3-manylinux2014_x86_64 @ 140664842341640>, <cp35-abi3-manylinux2010_x86_64 @ 140664842341704>, <cp35-abi3-manylinux1_x86_64 @ 140664842341768>, <cp35-abi3-linux_x86_64 @ 140664842341832>, <cp34-abi3-manylinux2014_x86_64 @ 140664842341960>, <cp34-abi3-manylinux2010_x86_64 @ 140664842342024>, <cp34-abi3-manylinux1_x86_64 @ 140664842342088>, <cp34-abi3-linux_x86_64 @ 140664842342152>, <cp33-abi3-manylinux2014_x86_64 @ 140664842342280>, <cp33-abi3-manylinux2010_x86_64 @ 140664842342344>, <cp33-abi3-manylinux1_x86_64 @ 140664842391624>, <cp33-abi3-linux_x86_64 @ 140664842391688>, <cp32-abi3-manylinux2014_x86_64 @ 140664842391816>, <cp32-abi3-manylinux2010_x86_64 @ 140664842391880>, <cp32-abi3-manylinux1_x86_64 @ 140664842391944>, <cp32-abi3-linux_x86_64 @ 140664842392008>, <py36-none-manylinux2014_x86_64 @ 140664842392264>, <py36-none-manylinux2010_x86_64 @ 140664842392136>, <py36-none-manylinux1_x86_64 @ 140664842392200>, <py36-none-linux_x86_64 @ 140664842392328>, <cp36-none-any @ 140664842392456>, <py36-none-any @ 140664842392520>, <py3-none-any @ 140664842392584>, <py35-none-any @ 140664842392648>, <py34-none-any @ 140664842392712>, <py33-none-any @ 140664842392776>, <py32-none-any @ 140664842392840>, <py31-none-any @ 140664842392904>, <py30-none-any @ 140664842392968>]

The closest that uses py3 is <py3-none-any @ 140664842392584>.

If we run pip install dotnetcore2-2.1.12-py3-none-manylinux1_x86_64.whl we get the error ERROR: dotnetcore2-2.1.12-py3-none-manylinux1_x86_64.whl is not a supported wheel on this platform..

What if we change the tag manually?

What if we change the tag in the file dotnetcore2-2.1.12.dist-info/WHEEL to py3-none-any, like this...

Wheel-Version: 1.0
Generator: bdist_wheel (0.32.3)
Root-Is-Purelib: true
Tag: py3-none-any

Notice the line Tag: py3-none-any, compatible with the supported tag <py3-none-any @ 140664842392584>

Once the change is applied, we simple zip the folders again and rename the file to something like dotnetcore2-2.1.12-py3-none-any.whl

Now if we run ....
pip install dotnetcore2-2.1.12-py3-none-any.whl

We will be able to install the dotnetcore2 wheel using PIP 20.0.1.

[maggiepint]

Hi- assuming that this question has been answered, so closing. Feel free to re-open an issue if this is still unresolved.

[JamesEarle]

I am still having this problem but for a different module @maggiepint @marcelaldecoa

pip install azureml-sdk

I am using pip version 20.2.2

Ends in the following error (other successful downloads excluded for brevity)

ERROR: Could not find a version that satisfies the requirement azureml-dataprep-native<21.0.0,>=20.0.2 (from azureml-dataprep<2.1.0a,>=2.0.1a->azureml-dataset-runtime[fuse]~=1.12.0->azureml-sdk) (from versions: none)
ERROR: No matching distribution found for azureml-dataprep-native<21.0.0,>=20.0.2 (from azureml-dataprep<2.1.0a,>=2.0.1a->azureml-dataset-runtime[fuse]~=1.12.0->azureml-sdk)

[cgideon]

I am running into the same error, running pip 20.2., python 3.8.6, and dotnet 3.1.109 on a Mac. This is the below error I get as well when running pip install azureml-sdk

ERROR: Could not find a version that satisfies the requirement azureml-sdk (from versions: none)
ERROR: No matching distribution found for azureml-sdk

[elsaVelazquez]

The following commands worked on my mac, and I attached the environment list here as specs.txt:

conda create --name azure_env python=3.7
conda activate azure_env
pip install azureml-sdk

specs.txt

[tanushreepaul04]

For me in Windows following commands worked.
Found azureml-sdk installation recommendation for docker this MS docs that also worked in Windows.
https://docs.microsoft.com/en-us/azure/machine-learning/resource-known-issues

conda create --name azure-ml-env
conda activate azure-ml-env
conda install -c r -y conda python=3.6.2 pip=20.1.1
pip install azureml-sdk