Conda Create Environment Takes Forever
Question:
Is it only me or is it like this with Conda? I’m having a environment file that looks like this:
name: python-cvcourse
channels:
- menpo
- conda-forge
- defaults
dependencies:
- jupyter=1.0.0
- jupyterlab=0.34.9
- keras=2.2.2=0
- matplotlib=2.2.3
- numpy=1.15.1
- opencv=4.1.0
- pandas=0.23.4
- python=3.6.6
- scikit-learn=0.19.1
- scipy=1.1.0
- tensorboard=1.10.0
- tensorflow=1.10.0
- pillow=8.3.2
prefix: /anaconda3/envs/cvcourse
I’m using the following command to update the environment:
conda env update -f requirements.yaml
It has been at this prompt below for more than few minutes and I’m starting to think if there is something that could be done about it:
(python-cvcourse) joesan@joesan-InfinityBook-S-14-v5:~/Projects/Private/sandbox-projects/udemvy-opencv-python$ conda env update -f cvcourse_linux.yml
Collecting package metadata (repodata.json): done
Solving environment: -
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
Answers:
I just tried running your yaml file myself and I was able to successfully create a conda environment with it. Instead of running conda env update
try creating the environment from scratch with the yaml? The following is the command I ran:
conda env create -f environment.yml
.
Where environment.yml
is the environment file you provided. Keep it mind it did take a couple of minutes to create the environment. Hope this is of some help.
I noticed that in your environment file you are asking for very specific versions of each of the packages. This probably increases the risk of conflicts between the requested packages because a specific version of package A may depend on a specific version of package B. If, in addition to this, you are request a lot of packages the combination of possible inconsistencies rapidly increases.
I would therefore suggest you relax some of the requirements and try abstaining from requesting a specific version of a (few) package(s) where you think this is acceptable. (I would get rid of all version specifications for a start to let conda sort out what environment would actually be feasible. You can later add version specifications where you feel this is necessary.)
Is it only me or is it like this with Conda? I’m having a environment file that looks like this:
name: python-cvcourse
channels:
- menpo
- conda-forge
- defaults
dependencies:
- jupyter=1.0.0
- jupyterlab=0.34.9
- keras=2.2.2=0
- matplotlib=2.2.3
- numpy=1.15.1
- opencv=4.1.0
- pandas=0.23.4
- python=3.6.6
- scikit-learn=0.19.1
- scipy=1.1.0
- tensorboard=1.10.0
- tensorflow=1.10.0
- pillow=8.3.2
prefix: /anaconda3/envs/cvcourse
I’m using the following command to update the environment:
conda env update -f requirements.yaml
It has been at this prompt below for more than few minutes and I’m starting to think if there is something that could be done about it:
(python-cvcourse) joesan@joesan-InfinityBook-S-14-v5:~/Projects/Private/sandbox-projects/udemvy-opencv-python$ conda env update -f cvcourse_linux.yml
Collecting package metadata (repodata.json): done
Solving environment: -
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
I just tried running your yaml file myself and I was able to successfully create a conda environment with it. Instead of running conda env update
try creating the environment from scratch with the yaml? The following is the command I ran:
conda env create -f environment.yml
.
Where environment.yml
is the environment file you provided. Keep it mind it did take a couple of minutes to create the environment. Hope this is of some help.
I noticed that in your environment file you are asking for very specific versions of each of the packages. This probably increases the risk of conflicts between the requested packages because a specific version of package A may depend on a specific version of package B. If, in addition to this, you are request a lot of packages the combination of possible inconsistencies rapidly increases.
I would therefore suggest you relax some of the requirements and try abstaining from requesting a specific version of a (few) package(s) where you think this is acceptable. (I would get rid of all version specifications for a start to let conda sort out what environment would actually be feasible. You can later add version specifications where you feel this is necessary.)