Comments (5)
Hi Catherine, did you try to download the wheel from https://github.com/logicalclocks/maggy/releases/tag/1.0.0rc0 and install it?
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I think it is also important to mention somewhere in the documentation the prerequisites e.g that the library requires Python>=3.7 . This is because in some cases updating a package is not as easy as downloading python and installing it, it a whole process of sending emails to ops teams and waiting for the request to be added in a sprint and things like that, and this can save up some time to get started with the actual work :-).
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Hey @crakama,
which version of pip are you using? Are you using any proxy for pip?
I tried reproducing your installation error but it works as expected with pip 21.1.1.
The requirement of Python>=3.7 is among the PyPi classifiers.
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I upgraded my ipython kernel in jupiterlab from 3.6 to 3.8 and I could install maggy 0.5.3 but seamlessly graded the version
using pip install --user --pre --upgrade --no-deps --force-reinstall maggy
I am getting other errors not related to maggy but once the errors are fixed I will test maggy's source code again and see if the problem is solved
Otherwise if a python kernel of below 3.7 is used, the package 0.5.3 gets installed and then you will be required to manually install other other dependency packages such as ERROR: Could not find a version that satisfies the requirement scikit-optimize==0.7.4 (from maggy) (from versions: 0.1, 0.2, 0.3, 0.4rc1, 0.4, 0.5, 0.5.1, 0.5.2, 0.7rc4, 0.7, 0.7.1, 0.7.2) ERROR: No matching distribution found for scikit-optimize==0.7.4
Even after manual installations of all dependencies, the error that maggy requires python 3.7 and above will still show up.
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Yes like I said, Python 3.7 is a requirement.
And like I said please make sure to use an up to date version of pip.
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Related Issues (20)
- Run on Python kernel
- Consecutive experiments on Databricks failing HOT 2
- AttributeError: module 'maggy.experiment' has no attribute 'lagom' HOT 1
- Maggy requirements too strict
- lagom() got an unexpected keyword argument 'searchspace'
- Is maggy applicable to my use case? HOT 12
- Replace Black Box term with Opaque or similar neutral terms HOT 1
- Can Maggy be used with a Spark Cluster that uses YARN
- Infer Number of Available Executors on Different Environments
- Infer IP address of Driver/Worker
- Create Environment classes with common interface HOT 1
- Distribution Driver to integrate in along with Optimization and Ablation Drivers
- DistributionExecutor Function PyTorch
- DistributionExecutor function TensorFlow
- Oblivious Training Function API
- Upgrade Ablation to use new HSFS APIs for feature store access
- [Ablation] Develop a dataset generator function for databricks HOT 1
- Add gridsearch optimizer
- Distributed training using tensorflow HOT 1
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