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I have a python Codeartifact repository which has an upstream PyPI repo.
In PyPI a new version of a library (google-auth 2.3.1) was published on the 25th of October, but whenever I try to install it via Codeartifact the latest available version is 2.3.0.
Is there a way to tell Codeartifact that the upstream has newer versions? How long does it takes for Codeartifact to pick up updates in PyPI?
This is the only source I found from AWS which states that this can happen but not how to solve it: https://docs.aws.amazon.com/codeartifact/latest/ug/external-connection.html#external-connection-unavailable
Error message:
ERROR: No matching distribution found for google-authpip3 install google-auth==2.3.1
Looking in indexes: https://aws:****#packages-****.d.codeartifact.eu-central-1.amazonaws.com/pypi/common/simple/
ERROR: Could not find a version that satisfies the requirement google-auth==2.3.1 (from versions: 0.0.1, 0.1.0, 0.2.0, 0.3.0, 0.3.1, 0.3.2, 0.4.0, 0.5.0, 0.6.0, 0.7.0, 0.8.0, 0.9.0, 0.10.0, 1.0.0, 1.0.1, 1.0.2, 1.1.0, 1.1.1, 1.2.0, 1.2.1, 1.3.0, 1.4.0, 1.4.1, 1.4.2, 1.5.0, 1.5.1, 1.6.0, 1.6.1, 1.6.2, 1.6.3, 1.7.0, 1.7.1, 1.7.2, 1.8.0, 1.8.1, 1.8.2, 1.9.0, 1.10.0, 1.10.1, 1.10.2, 1.11.0, 1.11.1, 1.11.2, 1.11.3, 1.12.0, 1.13.0, 1.13.1, 1.14.0, 1.14.1, 1.14.2, 1.14.3, 1.15.0, 1.16.0, 1.16.1, 1.17.0, 1.17.1, 1.17.2, 1.18.0, 1.19.0, 1.19.1, 1.19.2, 1.20.0, 1.20.1, 1.21.0, 1.21.1, 1.21.2, 1.21.3, 1.22.0, 1.22.1, 1.23.0, 1.24.0, 1.25.0, 1.26.0, 1.26.1, 1.27.0, 1.27.1, 1.28.0, 1.28.1, 1.29.0, 1.30.0, 1.30.1, 1.30.2, 1.31.0, 1.32.0, 1.32.1, 1.33.0, 1.33.1, 1.34.0, 1.35.0, 2.0.0.dev0, 2.0.0b1, 2.0.0, 2.0.1, 2.0.2, 2.1.0, 2.2.0, 2.2.1, 2.3.0)
Solution which works for me right now:
create venv if not available python3 -m venv .venv
activate it source .venv/bin/activate
install the package given in the log-statement eg pip install google-authpip3 --no-cache
run poetry again poetry install
if more errors occur, continue with 3)
My assumption is, that the local pip/poetry cache is not up to date. So I force pip to fetch the latest versions
I want to set a dependency in my requirements.txt for tensorflow~=2.5.0. At the time of writing, tensorflow==2.5.0 hasn't been released yet. The latest version available is the release candidate tensorflow==2.5.0rc3. How can I succinctly tell pip to "install the most recent tensorflow 2.5.x version, including release candidates"?
What I've tried so far:
tensorflow~=2.5.0
ERROR: Could not find a version that satisfies the requirement tensorflow~=2.5.0 (from versions: 2.5.0rc0, 2.5.0rc1, 2.5.0rc2, 2.5.0rc3)
ERROR: No matching distribution found for tensorflow~=2.5.0
tensorflow>2.4.1
ERROR: Could not find a version that satisfies the requirement tensorflow>2.4.1 (from versions: 1.13.0rc1, 1.13.0rc2, 1.13.1, 1.13.2, 1.14.0rc0, 1.14.0rc1, 1.14.0, 1.15.0rc0, 1.15.0rc1, 1.15.0rc2, 1.15.0rc3, 1.15.0, 1.15.2, 1.15.3, 1.15.4, 1.15.5, 2.0.0a0, 2.0.0b0, 2.0.0b1, 2.0.0rc0, 2.0.0rc1, 2.0.0rc2, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 2.1.0rc0, 2.1.0rc1, 2.1.0rc2, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.2.0rc0, 2.2.0rc1, 2.2.0rc2, 2.2.0rc3, 2.2.0rc4, 2.2.0, 2.2.1, 2.2.2, 2.3.0rc0, 2.3.0rc1, 2.3.0rc2, 2.3.0, 2.3.1, 2.3.2, 2.4.0rc0, 2.4.0rc1, 2.4.0rc2, 2.4.0rc3, 2.4.0rc4, 2.4.0, 2.4.1, 2.5.0rc0, 2.5.0rc1, 2.5.0rc2, 2.5.0rc3)
ERROR: No matching distribution found for tensorflow>2.4.1
According to section "Pre-release Versions" in the pip documentation:
If a Requirement specifier includes a pre-release or development version (e.g. >=0.0.dev0) then pip will allow pre-release and development versions for that requirement. This does not include the != flag.
This can be tested on the command line. As Tensorflow 2.5.0 is currently not yet released, we get:
$ pip download tensorflow~=2.5.0
ERROR: Could not find a version that satisfies the requirement tensorflow~=2.5.0 (from versions: 2.5.0rc0, 2.5.0rc1, 2.5.0rc2, 2.5.0rc3)
ERROR: No matching distribution found for tensorflow~=2.5.0
But if we add a pre-release version specifier:
$ pip download tensorflow~=2.5.0rc0
Collecting tensorflow~=2.5.0rc0
Downloading tensorflow-2.5.0rc3-cp39-cp39-win_amd64.whl (422.6 MB)
…
This would install the regular release once it becomes available.
My project needs tensorflow==1.11.0
But when I tried to install it, I got:
pip install tensorflow-gpu==1.11.0
Looking in indexes: http://mirrors.aliyun.com/pypi/simple
ERROR: Could not find a version that satisfies the requirement tensorflow-gpu==1.11.0 (from versions: 1.13.1, 1.13.2, 1.14.0, 1.15.0rc0, 1.15.0rc1, 1.15.0rc2, 1.15.0rc3, 1.15.0, 1.15.2, 1.15.3, 2.0.0a0, 2.0.0b0, 2.0.0b1, 2.0.0rc0, 2.0.0rc1, 2.0.0rc2, 2.0.0, 2.0.1, 2.0.2, 2.1.0rc0, 2.1.0rc1, 2.1.0rc2, 2.1.0, 2.1.1, 2.2.0rc0, 2.2.0rc1, 2.2.0rc2, 2.2.0rc3, 2.2.0rc4, 2.2.0)
ERROR: No matching distribution found for tensorflow-gpu==1.11.0
Plus, I am using py3.7.
Some python versions are incompatible with some versions of Tensorflow. If you very specifically need Tensorflow 1.11.0 then you can probably install it in a Python 3.6 environment.
If you very specifically need Python 3.7, you can probably install Tensorflow 1.13.1 or later.
When I install turicreate package, it gives me the following error:
Collecting tensorflow>=2.0.0 (from turicreate)
Could not find a version that satisfies the requirement tensorflow>=2.0.0 (from turicreate) (from versions: 0.12.1, 1.0.0, 1.0.1, 1.1.0rc0, 1.1.0rc1, 1.1.0rc2, 1.1.0, 1.2.0rc0, 1.2.0rc1, 1.2.0rc2, 1.2.0, 1.2.1, 1.3.0rc0, 1.3.0rc1, 1.3.0rc2, 1.3.0, 1.4.0rc0, 1.4.0rc1, 1.4.0, 1.4.1, 1.5.0rc0, 1.5.0rc1, 1.5.0, 1.5.1, 1.6.0rc0, 1.6.0rc1, 1.6.0, 1.7.0rc0, 1.7.0rc1, 1.7.0, 1.7.1, 1.8.0rc0, 1.8.0rc1, 1.8.0, 1.9.0rc0, 1.9.0rc1, 1.9.0rc2, 1.9.0, 1.10.0rc0, 1.10.0rc1, 1.10.0, 1.10.1, 1.11.0rc0, 1.11.0rc1, 1.11.0rc2, 1.11.0, 1.12.0rc0, 1.12.0rc1, 1.12.0rc2, 1.12.0, 1.12.2, 1.12.3, 1.13.0rc0, 1.13.0rc1, 1.13.0rc2, 1.13.1, 1.13.2, 1.14.0rc0, 1.14.0rc1, 1.14.0, 2.0.0a0, 2.0.0b0, 2.0.0b1)
No matching distribution found for tensorflow>=2.0.0 (from turicreate)
which I encountered the same when installing tensorflow 2.0.0.
And I managed to install tensorflow2 with modification to the version(add a 'a0','b0','b1' after '2.0.0') using pip3 install tensorflow==2.0.0a0. However, I still cannot pass the installation of turicreate even with tensorflow2.0.0a0 installed and result in the same 'tensorflow error' shown above.
I am using python 3.6, numpy 1.16.5.
Can you please help me out?
Upgrade pip
# On Linux or macOS:
pip3 install -U pip
# On Windows:
python -m pip3 install -U pip
Install turicreate
pip3 install turicreate
This will solve your problem
I was having the same problem when I tried to install turicreate on the Jupyter Docker image that comes with some data science libraries loaded:
Image: jupyter/scipy-notebook
Packages: pandas, numexpr, matplotlib, scipy, seaborn, scikit-learn, scikit-image, sympy, cython, patsy, statsmodel, cloudpickle, dill, numba, bokeh, sqlalchemy, hdf5, vincent, beautifulsoup, protobuf, and xlrd packages
Error message:
Could not find a version that satisfies the requirement tensorflow>=2.0.0 (from turicreate) (from versions: 0.12.1, 1.0.0, 1.0.1, 1.1.0rc0, 1.1.0rc1, 1.1.0rc2, 1.1.0, 1.2.0rc0, 1.2.0rc1, 1.2.0rc2, 1.2.0, 1.2.1, 1.3.0rc0, 1.3.0rc1, 1.3.0rc2, 1.3.0, 1.4.0rc0, 1.4.0rc1, 1.4.0, 1.4.1, 1.5.0rc0, 1.5.0rc1, 1.5.0, 1.5.1, 1.6.0rc0, 1.6.0rc1, 1.6.0, 1.7.0rc0, 1.7.0rc1, 1.7.0, 1.7.1, 1.8.0rc0, 1.8.0rc1, 1.8.0, 1.9.0rc0, 1.9.0rc1, 1.9.0rc2, 1.9.0, 1.10.0rc0, 1.10.0rc1, 1.10.0, 1.10.1, 1.11.0rc0, 1.11.0rc1, 1.11.0rc2, 1.11.0, 1.12.0rc0, 1.12.0rc1, 1.12.0rc2, 1.12.0, 1.12.2, 1.12.3, 1.13.0rc0, 1.13.0rc1, 1.13.0rc2, 1.13.1, 1.13.2, 1.14.0rc0, 1.14.0rc1, 1.14.0, 2.0.0a0, 2.0.0b0, 2.0.0b1)
No matching distribution found for tensorflow>=2.0.0 (from turicreate)
However, when I took the basic (stripped) Jupyter image, it worked:
Image: jupyter/base-notebook
Packages: git, emacs, jed, nano, tzdata, and unzip
Installation instructions for turicreate:
from __future__ import print_function
import sys
!{sys.executable} -m pip install turicreate
Output:
Successfully installed absl-py-0.9.0 astor-0.8.1 cachetools-4.0.0 coremltools-3.1 gast-0.2.2 google-auth-1.10.0 google-auth-oauthlib-0.4.1 google-pasta-0.1.8 grpcio-1.26.0 h5py-2.10.0 keras-applications-1.0.8 keras-preprocessing-1.1.0 llvmlite-0.30.0 markdown-3.1.1 numba-0.46.0 numpy-1.16.4 opt-einsum-3.1.0 pandas-0.25.3 pillow-6.2.1 prettytable-0.7.2 protobuf-3.11.2 pyasn1-0.4.8 pyasn1-modules-0.2.7 pytz-2019.3 requests-oauthlib-1.3.0 resampy-0.2.1 rsa-4.0 scipy-1.4.1 tensorboard-2.0.2 tensorflow-2.0.0 tensorflow-estimator-2.0.1 termcolor-1.1.0 turicreate-6.0 werkzeug-0.16.0 wrapt-1.11.2
So, I guess the problem is that some of the libraries that you have installed in your environment conflict with turicreate. Perhaps you should try to use the above mentioned Docker image or try to create a virtual environment so you work in isolation (not tested this).
Info on the different Docker images:
https://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html#jupyter-scipy-notebook
Turicreate installation instructions where they comment on the virtual environment:
https://github.com/apple/turicreate#installation
Firstly, give try to a latest version of pip pip3 install -U pip, usually, it has less problems than previous.
Otherwise, if above fails, you can try running with pip3 install --no-deps turicreate to get past the cryptic error.
You'll need to install the dependencies manually. All 110 of them.
You can generate a list of them with something along these lines:
import os;
s = os.popen('pip3 freeze turicreate').read()
for q in [x.split('==')[0] for x in s.split('\n')]:
os.system('echo {} >> t.tmp'.format(q)
Then they can be installed with pip install -r t.tmp or for x in $(cat t.tmp); do pip3 install $x; done
I'm not sure how the funtionality related to the tensorflow or any other failed package is affected by this but I've managed to get simple sframes working with this method.
Then I've upgraded the pip and all the libs that weren't working installed without a problem.
Try upgrading pip. Tensorflow 2.0 needs newer versions of pip to be installed.
Personally this worked,
upgrade pip
installed tf2.0
installed turicreate.
I installed numpy, but when I install django_pandas it gives me an error:
Using cached pandas-0.22.0.tar.gz
Could not find a version that satisfies the re
sions: 1.10.4, 1.11.0, 1.11.1rc1, 1.11.1, 1.11.2
.12.0rc1, 1.12.0rc2, 1.12.0, 1.12.1rc1, 1.12.1,
13.1, 1.13.3, 1.14.0rc1, 1.14.0, 1.14.1, 1.14.2)
No matching distribution found for numpy==1.9.3
I had the same issue and downgrading pip worked for me, like this:
pip install pip==9.0.1
After that I could install django-pandas normally.