Conda Store Env Build Resource Usage

[Adam-D-Lewis]

This env took 18 minutes to build and used a max of 7.2 GiB RAM and 2 CPUs

name: env2
channels:

• conda-forge
  dependencies:
• python=3.10
• cdsdashboards-singleuser=0.6.3
• cufflinks-py=0.17.3
• dash=2.8.1
• geopandas=0.12.2
• geopy=2.3.0
• geoviews=1.9.6
• gunicorn=20.1.0
• holoviews=1.15.4
• ipykernel=6.21.2
• ipywidgets=8.0.4
• jupyter=1.0.0
• jupyterlab=3.6.1
• jupyter_bokeh=3.0.5
• matplotlib=3.7.0
• nebari-dask==2023.1.1
• nodejs=18.12.1
• numpy
• openpyxl=3.1.1
• pandas=1.5.3
• panel=0.14.3
• param=1.12.3
• plotly=5.13.0
• python-graphviz=0.20.1
• rich=13.3.1
• streamlit=1.9.0
• sympy=1.11.1
• voila=0.4.0
• pip=23.0
• pip:
  • streamlit-image-comparison==0.0.3
  • noaa-coops==0.2.1
  • dash_core_components==2.0.0
  • dash_html_components==2.0.0
    variables: {}

[Adam-D-Lewis]

This env took 57 minutes to build and used a max of 12.5 GiB RAM and 2 CPUs

channels:

• conda-forge
• bokeh
  dependencies:
• python=3.10
• panel
• ipykernel
• ipywidgets
• ipywidgets_bokeh
• holoviews
• openjdk=17.0.9
• pyspark
• findspark
• jhsingle-native-proxy>=0.8.2
• bokeh-root-cmd>=0.1.2
• nbconvert
• nrtk
• xaitk-saliency
• maite
• daml
• pytorch
• loguru
• pytest
• pyright
• torchmetrics
• torchvision
• multiprocess
• smqtk-detection
  variables: {}

[Adam-D-Lewis]

This env took 8 minutes to build and used a max of 3-4 GiB RAM and 2 CPUs

name: env
channels:

• conda-forge
  dependencies:
• python=3.10.8
• ipykernel=6.21.0
• ipywidgets==7.7.1
• nebari-dask ==2023.1.1
• python-graphviz=0.20.1
• pyarrow=10.0.1
• s3fs=2023.1.0
• gcsfs=2023.1.0
• numpy=1.23.5
• numba=0.56.4
• pandas=1.5.3
  variables: {}