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pipenv - Pipfile.lock is not being generated due to the 'Could not find a version that matches keras-nightly~=2.5.0.dev' error

As the title clearly describes the issue I've been experiencing, no Pipfile.lock is being generated as I get the following error when I execute the recommended command pipenv lock --clear:

ERROR: ERROR: Could not find a version that matches keras-nightly~=2.5.0.dev
Skipped pre-versions: 2.5.0.dev2021020510, 2.5.0.dev2021020600, 2.5.0.dev2021020700, 2.5.0.dev2021020800, 2.5.0.dev2021020900, 2.5.0.dev2021021000, 2.5.0.dev2021021100, 2.5.0.dev2021021200, 2.5.0.dev2021021300, 2.5.0.dev2021021400, 2.5.0.dev2021021500, 2.5.0.dev2021021600, 2.5.0.dev2021021700, 2.5.0.dev2021021800, 2.5.0.dev2021021900, 2.5.0.dev2021022000, 2.5.0.dev2021022100, 2.5.0.dev2021022200, 2.5.0.dev2021022300, 2.5.0.dev2021022317, 2.5.0.dev2021022400, 2.5.0.dev2021022411, 2.5.0.dev2021022500, 2.5.0.dev2021022600, 2.5.0.dev2021022700, 2.5.0.dev2021022800, 2.5.0.dev2021030100, 2.5.0.dev2021030200, 2.5.0.dev2021030300, 2.5.0.dev2021030400, 2.5.0.dev2021030500, 2.5.0.dev2021030600, 2.5.0.dev2021030700, 2.5.0.dev2021030800, 2.5.0.dev2021030900, 2.5.0.dev2021031000, 2.5.0.dev2021031100, 2.5.0.dev2021031200, 2.5.0.dev2021031300, 2.5.0.dev2021031400, 2.5.0.dev2021031500, 2.5.0.dev2021031600, 2.5.0.dev2021031700, 2.5.0.dev2021031800, 2.5.0.dev2021032213, 2.5.0.dev2021032300, 2.5.0.dev2021032413, 2.5.0.dev2021032500, 2.5.0.dev2021032600, 2.5.0.dev2021032610, 2.5.0.dev2021032700, 2.5.0.dev2021032800, 2.5.0.dev2021032900, 2.6.0.dev2021033000, 2.6.0.dev2021033100, 2.6.0.dev2021040100, 2.6.0.dev2021040200, 2.6.0.dev2021040300, 2.6.0.dev2021040400, 2.6.0.dev2021040500, 2.6.0.dev2021040600, 2.6.0.dev2021040714, 2.6.0.dev2021040800, 2.6.0.dev2021040900, 2.6.0.dev2021041000, 2.6.0.dev2021041100, 2.6.0.dev2021041200, 2.6.0.dev2021041300, 2.6.0.dev2021041400, 2.6.0.dev2021041500, 2.6.0.dev2021041600, 2.6.0.dev2021041700, 2.6.0.dev2021041800, 2.6.0.dev2021041900, 2.6.0.dev2021042000, 2.6.0.dev2021042100, 2.6.0.dev2021042200, 2.6.0.dev2021042300, 2.6.0.dev2021042500, 2.6.0.dev2021042600, 2.6.0.dev2021042700, 2.6.0.dev2021042800, 2.6.0.dev2021042900, 2.6.0.dev2021043000, 2.6.0.dev2021050100, 2.6.0.dev2021050200, 2.6.0.dev2021050300, 2.6.0.dev2021050400, 2.6.0.dev2021050500, 2.6.0.dev2021050600, 2.6.0.dev2021051200, 2.6.0.dev2021051300, 2.6.0.dev2021051400, 2.6.0.dev2021051500, 2.6.0.dev2021051600, 2.6.0.dev2021051700, 2.6.0.dev2021051800, 2.6.0.dev2021051900, 2.6.0.dev2021052000, 2.6.0.dev2021052100, 2.6.0.dev2021052200, 2.6.0.dev2021052300, 2.6.0.dev2021052400, 2.6.0.dev2021052500, 2.6.0.dev2021052600, 2.6.0.dev2021052700
There are incompatible versions in the resolved dependencies.

So, how can I overcome this situation? I'm basically developing a deep neural network using Keras. I simply installed the following dependencies without explicitly declaring versions:

tensorflow = "*"
nltk = "*"
pandas = "*"
tweepy = "*"
textblob = "*"
seaborn = "*"
matplotlib = "*"
wordcloud = "*"
stop-words = "*"
vadersentiment = "*"
scikit-learn = "*"
keras = "*"
like image 699
talha06 Avatar asked Jun 02 '21 13:06

talha06


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Could not find a version that matches Pipenv?

You likely have a mismatch in your sub-dependencies. First try clearing your dependency cache with $ pipenv lock --clear, then try the original command again. Alternatively, you can use $ pipenv install --skip-lock to bypass this mechanism, then run $ pipenv graph to inspect the situation.

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$ pipenv lock is used to create a Pipfile. lock , which declares all dependencies (and sub-dependencies) of your project, their latest available versions, and the current hashes for the downloaded files.

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lock. The Pipfile. lock is intended to specify, based on the packages present in Pipfile, which specific version of those should be used, avoiding the risks of automatically upgrading packages that depend upon each other and breaking your project dependency tree.


1 Answers

By looking at the pypi site for keras-nightly library, I could see that there are no versions named 2.5.0.dev. Check which package is generating the error and try downgrading that package.

like image 94
Kishore Avatar answered Oct 24 '22 00:10

Kishore