Creating a Conda Environment taking too long

Question

I have the latest version of Anaconda installed on my machine, 64bit. I have run the following command via VSCode:

conda env create -f 000_environment_setup/01_conda_environment.yml

Here is the yaml file contents:

# DS4B 101-P: PYTHON FOR DATA SCIENCE AUTOMATION ----
# Environment Setup ----

# Conda Environment Setup Instructions ----
#  - Using an environment.yml file with conda
#  - Key Terminal Commands:
#
#    conda env create -f 000_environment_setup/01_conda_environment.yml
#    conda env update --file 000_environment_setup/01_conda_environment.yml --prune
#    conda env export --name ds4b_101p > envname.yml
#    conda env remove --name ds4b_101p
#    conda env list

name: ds4b_101p
channels:
  - anaconda
  - conda-forge
  - defaults
dependencies:
  - python=3.7.1
  - pip
  - pip:
      # Core Data
      #- numpy==1.20.2
      - numpy
      - pandas==1.2.2

      # R Data
      - plydata==0.4.3
      - siuba==0.0.24
      - datatable

      # Visualization
      - matplotlib==3.3.4
      - plotnine==0.7.1
      - mizani==0.7.2
      - plotly==4.14.3
      - altair==4.1.0

      # EDA
      - pandas-profiling
      - ppscore==1.2.0
      - pyjanitor==0.20.14

      # Modeling & Machine Learning
      - statsmodels
      - nltk==3.6.6
      - h2o==3.32.0.3
      - pycaret==2.3.0
      - scikit-learn==0.23.2
      - xgboost==0.90
      - lightgbm==3.1.1
      - catboost==0.24.4
      - sklearn-pandas==2.0.4
      - scikit-misc==0.1.3

      # Time Series
      - sktime==0.5.3
      - pmdarima==1.8.1
      - tsfresh==0.17.0

      # Scalability & Automation
      - dask==2.30.0
      - dask-ml==1.8.0
      - dask-xgboost==0.1.11
      - zict==1.0.0
      - joblib==1.0.1

      # API
      - fastapi==0.65.2
      - uvicorn==0.13.4

      # Database
      - sqlalchemy==1.4.7

      # Excel
      - xlsxwriter==1.3.7
      - openpyxl

      # Jupyter
      - jupyterlab==3.0.17
      - jupyterlab-server==2.4.0
      - ipywidgets==7.6.3
      - ipympl==0.7.0
      - jupytext
      - papermill==2.3.3

      # Apps
      - streamlit==0.80.0

      # Terminal Formatting
      - rich

      # Extending Pandas
      - pandas_flavor

      # R users
      - radian
      - jedi==0.17.2

      # misc
      - bottleneck==1.3.2

In light of this seeming to never finish, is there something else I should be checking on?