conda

问题 I want to install fastai using setup.py in a project. The nicest way, if I have a conda environment, is to use the conda install command conda install -c pytorch -c fastai fastai . Unfortunately, if I just add fastai as a requirement, it gets installed using pip, which I have experienced issues with. Simply, is there a way to install fastai using conda a setup.py file (using the conda install command)? 回答1: As far as I know, conda package manager does not understand setup.py . As a result,

问题 I want to install fastai using setup.py in a project. The nicest way, if I have a conda environment, is to use the conda install command conda install -c pytorch -c fastai fastai . Unfortunately, if I just add fastai as a requirement, it gets installed using pip, which I have experienced issues with. Simply, is there a way to install fastai using conda a setup.py file (using the conda install command)? 回答1: As far as I know, conda package manager does not understand setup.py . As a result,

问题 I want to install fastai using setup.py in a project. The nicest way, if I have a conda environment, is to use the conda install command conda install -c pytorch -c fastai fastai . Unfortunately, if I just add fastai as a requirement, it gets installed using pip, which I have experienced issues with. Simply, is there a way to install fastai using conda a setup.py file (using the conda install command)? 回答1: As far as I know, conda package manager does not understand setup.py . As a result,

问题 Say I'm following the best practise workflow suggested for snakemake. Now I'd like to know how (i.e. which version) a given file, say plots/myplot.pdf , was generated. I found this surprisingly hard if not impossible only having the result folder at hand. In more detail, say I was generated the results using. snakemake --use-conda --conda-prefix ~/.conda/myenvs which will resolve and download the conda-environments specified in the rule below (copied from the documentation): rule NAME: input:

问题 I've recently started using the Anaconda environment and in the config list I came across an option called aggressive_update_packages . It is not very clear to me what happens when I add a new package to this. I couldn't find any satisfying description about this option (only a little bit here), so I only can assume what it does: I think it will keep autoupdated the certain package. However I'm certainly not sure how it works, that's what I'm asking. I'm actively developing a package

问题 I have installed anaconda in ubuntu and am facing a problem with anaconda. I was running the following command in a conda environment: 271 pip install --user -r requirements.txt 272 cd .. 273 conda install ipython jupyter 274 conda install jupyter 275 python 276 sudo apt-get install python-vtk python-wxgtk2.6 python-setuptools python-numpy python-configobj 277 sudo apt-get install python-vtk python-wxgtk2.8 python-setuptools python-numpy python-configobj 278 conda install -c anaconda mayavi=

问题 I have a new PC and I want to clone a Python environment from my older computer. I created the Python environment about two years ago using Anaconda 2 for Python 2.7. I am having trouble copying it exactly, because some of the packages are no longer available in the same versions and locations. I want to know if there is a way to copy the environment directly from one computer to another, rather than installing each package from a weblink (that in some cases no longer exists). I have tried

问题 I have a new PC and I want to clone a Python environment from my older computer. I created the Python environment about two years ago using Anaconda 2 for Python 2.7. I am having trouble copying it exactly, because some of the packages are no longer available in the same versions and locations. I want to know if there is a way to copy the environment directly from one computer to another, rather than installing each package from a weblink (that in some cases no longer exists). I have tried

问题 I've been using the balloon.py example script in the Matterport Mask R-CNN repo [https://github.com/matterport/Mask_RCNN/blob/master/samples/balloon/balloon.py] for learning how to implement tensorboard to monitor the training process. The training itself is going fine, but I've completely failed to implement tensorboard. So far I've added: # create Tensorboard logdir = os.path.join("logs", datetime.datetime.now().strftime("%Y%m%d-%H%M%S")) tensorboard_callback = tf.keras.callbacks

问题 I have the following Singularity container recipe: #!/bin/bash Bootstrap: docker From: nipype/nipype:latest %labels Version v1.0 %post # Install nano apt-get update apt-get install nano # Set up Python environment CONDA_ENV=/opt/conda/bin export PATH=$CONDA_ENV:$PATH chmod -R 777 $CONDA_ENV # Activate conda environment conda activate neuro conda install seaborn pip install pybids and I build the container with Singularity as follows: sudo singularity build swish.simg Singularity.swish The