Conda environments help in handling multiple projects and their requirement dependencies seperatly. It is like creating seperate folders for seperate tasks/projects.

install conda: official docs

create env:

# version of python as per ones preference
conda create --name/-n <env-name> python=3.8
# create conda env useing YAML files
conda env update -f <file-path>

actiavte and deactivate env:

conda activate <env-name>
conda deactivate

remove env:

# method-1
conda env remove --name/-n <env-name>
# method-2
rm -rf <path-of-env-dir>
# method-3
conda remove --name <env-name> --all

install modules:

# first activate and then pip
conda activate <env-name> | pip install <module-name>
# directly install using conda
conda install -n <env-name> <module-name>

misc:
```
# to see env list
conda info --envs
```
a demo YAML file: ```yaml
YAML file for Conda Environment

Name of the Conda environment

name: my_environment

Conda channels where packages will be searched

channels:

defaults
conda-forge # Additional channels can be added as needed

Main dependencies installed using Conda

dependencies:

python=3.8
numpy>=1.18

# Additional Conda packages can be listed here

# Example: Uncomment the following line to include matplotlib # - matplotlib

# Example: Uncomment the following line to include pandas # - pandas

# Specify versions, constraints, or additional packages as needed

Dependencies installed using pip (Python packages not available in Conda)

Useful for packages that are not available in Conda repositories

or for more recent versions of certain packages

Note: ‘pip’ itself is automatically included

pip:

requests>=2.22
Flask>=1.1

# Additional pip packages can be listed here

# Example: Uncomment the following line to include pytest # - pytest

# Specify versions or additional packages as needed

```

YAML file for Conda Environment