How to install .NET with dotnet-install script

Find more details in Microsoft scripted installation

  1. .NET SDK (Software Development Kit): The SDK includes everything you need to build and run .NET applications. This means it includes the runtime, but also includes other tools for developing, building, running, and testing .NET applications. This includes the .NET CLI (Command Line Interface), compilers, and libraries. You need the SDK to develop and build .NET applications.
  2. .NET Runtime: The runtime includes just the resources required to run existing .NET applications. It does not include the tools and libraries used for building applications. It's a smaller installation package compared to the SDK. When you deploy a .NET application to a server or a client machine, you usually only need to have the appropriate .NET Runtime installed on that machine, not the full SDK.


$ curl -sSL >
$ chmod +x
$ echo 'export DOTNET_ROOT=$HOME/.dotnet' >> ~/.zshrc
$ echo 'export PATH=$PATH:$DOTNET_ROOT:$DOTNET_ROOT/tools' >> ~/.zshrc

dotnet-install Script Reference

find reference for dotnet-install script reference in dotnet-install script reference

find options for dotnet-install script in dotnet-install script options

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Python Azure Function Debugging in Pyenv-virtualenv virtual environment

Creating virtual environment

$ mkdir python_demo
$ cd python_demo
$ pyenv local 3.9.16
$ pyenv virtualenv 3.9.16 python_demo-3.9.16

# OR pyenv-virtualenv will use local python runtime with the following command
$ pyenv virtualenv python_demo-3.9.16

setting pyenv local version to created virtual environment will allow to activate virtual environment automatically when we enter project folder, so exiting from project folder will deactivate virtual environment.

$ pyenv local python_demo-3.9.16

Activating virtual environment

$ pyenv activate python_demo-3.9.16
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Python listing virtual environments for conda, pipenv, pyenv-virtualenv


$ conda env list

# conda environments:
base                     /opt/homebrew/Caskroom/miniconda/base
python_azure_function_conda_virtual_env-3.9  *  /opt/homebrew/Caskroom/miniconda/base/envs/python_azure_function_conda_virtual_env-3.9
python_demo-3.9          /opt/homebrew/Caskroom/miniconda/base/envs/python_demo-3.9
test34-3.9               /opt/homebrew/Caskroom/miniconda/base/envs/test34-3.9
test35-3.9               /opt/homebrew/Caskroom/miniconda/base/envs/test35-3.9
test36-3.9               /opt/homebrew/Caskroom/miniconda/base/envs/test36-3.9


$ pyenv virtualenvs

  3.10.3/envs/test31-3.10.3 (created from /Users/kenanhancer/.pyenv/versions/3.10.3)
  3.10.5/envs/test31-3.10.5 (created from /Users/kenanhancer/.pyenv/versions/3.10.5)
  3.10.5/envs/test32-3.10.5 (created from /Users/kenanhancer/.pyenv/versions/3.10.5)
  3.11.4/envs/python_demo-3.11.4 (created from /Users/kenanhancer/.pyenv/versions/3.11.4)
  3.11.4/envs/test31-3.11.4 (created from /Users/kenanhancer/.pyenv/versions/3.11.4)
  3.11.4/envs/test32-3.11.4 (created from /Users/kenanhancer/.pyenv/versions/3.11.4)
  3.6.15/envs/test31-3.6.15 (created from /Users/kenanhancer/.pyenv/versions/3.6.15)
  3.9.1/envs/test29-3.9.1 (created from /Users/kenanhancer/.pyenv/versions/3.9.1)
  3.9.1/envs/test30-3.9.1 (created from /Users/kenanhancer/.pyenv/versions/3.9.1)
  3.9.1/envs/test31-3.9.1 (created from /Users/kenanhancer/.pyenv/versions/3.9.1)
  3.9.17/envs/python_demo-3.9.17 (created from /Users/kenanhancer/.pyenv/versions/3.9.17)
  3.9.17/envs/test29-3.9.17 (created from /Users/kenanhancer/.pyenv/versions/3.9.17)
  3.9.17/envs/test30-3.9.17 (created from /Users/kenanhancer/.pyenv/versions/3.9.17)
  3.9.17/envs/test31-3.9.17 (created from /Users/kenanhancer/.pyenv/versions/3.9.17)
  python_demo-3.11.4 (created from /Users/kenanhancer/.pyenv/versions/3.11.4)
  python_demo-3.9.17 (created from /Users/kenanhancer/.pyenv/versions/3.9.17)
  test29-3.9.1 (created from /Users/kenanhancer/.pyenv/versions/3.9.1)
  test29-3.9.17 (created from /Users/kenanhancer/.pyenv/versions/3.9.17)
  test30-3.9.1 (created from /Users/kenanhancer/.pyenv/versions/3.9.1)
  test30-3.9.17 (created from /Users/kenanhancer/.pyenv/versions/3.9.17)
  test31-3.10.3 (created from /Users/kenanhancer/.pyenv/versions/3.10.3)
  test31-3.10.5 (created from /Users/kenanhancer/.pyenv/versions/3.10.5)
  test31-3.11.4 (created from /Users/kenanhancer/.pyenv/versions/3.11.4)
  test31-3.6.15 (created from /Users/kenanhancer/.pyenv/versions/3.6.15)
  test31-3.9.1 (created from /Users/kenanhancer/.pyenv/versions/3.9.1)
  test31-3.9.17 (created from /Users/kenanhancer/.pyenv/versions/3.9.17)
  test32-3.10.5 (created from /Users/kenanhancer/.pyenv/versions/3.10.5)
  test32-3.11.4 (created from /Users/kenanhancer/.pyenv/versions/3.11.4)


$ ls -lat ~/.local/share/virtualenvs/

Python Azure Function Debugging in Conda virtual environment

Creating virtual environment

$ mkdir python_demo
$ cd python_demo

don't forget to update name of environment name, and i added pip, ptvsd packages to debug azure function.

$ cat > environment.yml <<EOL
name: python_demo-3.9
  - defaults
  - python=3.9
  - pip
  - pip:
    - ptvsd
$ conda env create -f environment.yml

Collecting package metadata (repodata.json): done
Solving environment: done

Downloading and Extracting Packages

Preparing transaction: done
Verifying transaction: done
Executing transaction: done
Installing pip dependencies: - Ran pip subprocess with arguments:
['/opt/homebrew/Caskroom/miniconda/base/envs/python_azure_function_conda_virtual_env-3.9/bin/python', '-m', 'pip', 'install', '-U', '-r', '/Users/kenanhancer/Documents/projects/python-projects-kenanhancer/python_azure_function_conda_virtual_env/condaenv.5uk0y5ie.requirements.txt', '--exists-action=b']
Pip subprocess output:
Collecting ptvsd (from -r /Users/kenanhancer/Documents/projects/python-projects-kenanhancer/python_azure_function_conda_virtual_env/condaenv.5uk0y5ie.requirements.txt (line 1))
  Using cached ptvsd-4.3.2-py2.py3-none-any.whl (4.9 MB)
Installing collected packages: ptvsd
Successfully installed ptvsd-4.3.2

# To activate this environment, use
#     $ conda activate python_azure_function_conda_virtual_env-3.9
# To deactivate an active environment, use
#     $ conda deactivate
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conda vs pipenv vs virtualenv commands

find more information in conda

TaskConda package and environment manager commandPip package manager commandVirtualenv environment manager command
Install a packageconda install $PACKAGE_NAMEpip install $PACKAGE_NAMEX
Update a packageconda update --name $ENVIRONMENT_NAME$PACKAGE_NAMEpip install --upgrade$PACKAGE_NAMEX
Update package managerconda update condaLinux/macOS: pip install -Upip Win: python -m pipinstall -U pipX
Uninstall a packageconda remove --name $ENVIRONMENT_NAME$PACKAGE_NAMEpip uninstall $PACKAGE_NAMEX
Create an environmentconda create --name $ENVIRONMENT_NAME pythonXcd $ENV_BASE_DIR; virtualenv$ENVIRONMENT_NAME
Activate an environmentconda activate $ENVIRONMENT_NAME*Xsource$ENV_BASE_DIR/$ENVIRONMENT_NAME/bin/activate
Deactivate an environmentconda deactivateXdeactivate
Search available packagesconda search $SEARCH_TERMpip search $SEARCH_TERMX
Install package from specific sourceconda install --channel $URL $PACKAGE_NAMEpip install --index-url $URL$PACKAGE_NAMEX
List installed packagesconda list --name $ENVIRONMENT_NAMEpip listX
Create requirements fileconda list --exportpip freezeX
List all environmentsconda info --envsXInstall virtualenv wrapper, then lsvirtualenv
Install other package managerconda install pippip install condaX
Install Pythonconda install python=x.xXX
Update Pythonconda update python*XX

How to create virtual environment with conda

Conda is an open-source package management system and virtual environment management system that runs on Windows, macOS, and Linux. It was created for Python programs but it can package and distribute software for any language such as R, Ruby, Lua, Scala, Java, JavaScript, C, C++, FORTRAN.

The two main purposes of Conda are:

  1. Package management: Conda makes it easy to manage and install packages, even for different versions of Python. In addition, it also supports binary package management, which makes it an efficient way to handle packages and dependencies in your projects.
  2. Virtual Environment management: Conda allows you to create separate environments containing files, packages, and their dependencies that will not interact with other environments. When switching between Python versions for different projects, Conda makes it simple to use the specific version you need.

While pip can install Python packages, Conda can install packages for any language. Conda packages are binaries, which eliminates the need to compile the code which makes installations faster and more straightforward.

Installing conda

$ brew update
$ brew install --cask miniconda

Checking conda version

$ conda --version

conda 23.3.1

Conda help

$ conda -h
usage: conda [-h] [-V] command ...

conda is a tool for managing and deploying applications, environments and packages.


positional arguments:
    clean             Remove unused packages and caches.
    compare           Compare packages between conda environments.
    config            Modify configuration values in .condarc. This is modeled after the git config command. Writes to the
                      user .condarc file (/Users/kenanhancer/.condarc) by default. Use the --show-sources flag to display
                      all identified configuration locations on your computer.
    create            Create a new conda environment from a list of specified packages.
    info              Display information about current conda install.
    init              Initialize conda for shell interaction.
    install           Installs a list of packages into a specified conda environment.
    list              List installed packages in a conda environment.
    package           Low-level conda package utility. (EXPERIMENTAL)
    remove (uninstall)
                      Remove a list of packages from a specified conda environment. Use `--all` flag to remove all packages
                      and the environment itself.
    rename            Renames an existing environment.
    run               Run an executable in a conda environment.
    search            Search for packages and display associated information.The input is a MatchSpec, a query language for
                      conda packages. See examples below.
    update (upgrade)  Updates conda packages to the latest compatible version.
    notices           Retrieves latest channel notifications.

  -h, --help          Show this help message and exit.
  -V, --version       Show the conda version number and exit.

conda commands available from other packages (legacy):
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How to create virtual environment with pipenv

Pipenv is a Python tool that aims to bring the best features of multiple other tools into one. It provides an easy way to manage virtual environments and manage package dependencies consistently. Its key goal is to simplify the workflow of managing a Python environment for your project.

Installing pipenv

$ python -m pip install pipenv

Checking pipenv version

$ pipenv --version

pipenv, version 2022.7.4

Checking pipenv version

$ pipenv -h
Usage: pipenv [OPTIONS] COMMAND [ARGS]...

  --where                         Output project home information.
  --venv                          Output virtualenv information.
  --py                            Output Python interpreter information.
  --envs                          Output Environment Variable options.
  --rm                            Remove the virtualenv.
  --bare                          Minimal output.
  --man                           Display manpage.
  --support                       Output diagnostic information for use in
                                  GitHub issues.
  --site-packages / --no-site-packages
                                  Enable site-packages for the virtualenv.
                                  [env var: PIPENV_SITE_PACKAGES]
  --python TEXT                   Specify which version of Python virtualenv
                                  should use.
  --three                         Use Python 3 when creating virtualenv.
  --clear                         Clears caches (pipenv, pip).  [env var:
  -q, --quiet                     Quiet mode.
  -v, --verbose                   Verbose mode.
  --pypi-mirror TEXT              Specify a PyPI mirror.
  --version                       Show the version and exit.
  -h, --help                      Show this message and exit.

Usage Examples:
   Create a new project using Python 3.7, specifically:
   $ pipenv --python 3.7

   Remove project virtualenv (inferred from current directory):
   $ pipenv --rm

   Install all dependencies for a project (including dev):
   $ pipenv install --dev

   Create a lockfile containing pre-releases:
   $ pipenv lock --pre

   Show a graph of your installed dependencies:
   $ pipenv graph

   Check your installed dependencies for security vulnerabilities:
   $ pipenv check

   Install a local into your virtual environment/Pipfile:
   $ pipenv install -e .

   Use a lower-level pip command:
   $ pipenv run pip freeze

  check         Checks for PyUp Safety security vulnerabilities and against
                PEP 508 markers provided in Pipfile.
  clean         Uninstalls all packages not specified in Pipfile.lock.
  graph         Displays currently-installed dependency graph information.
  install       Installs provided packages and adds them to Pipfile, or (if no
                packages are given), installs all packages from Pipfile.
  lock          Generates Pipfile.lock.
  open          View a given module in your editor.
  requirements  Generate a requirements.txt from Pipfile.lock.
  run           Spawns a command installed into the virtualenv.
  scripts       Lists scripts in current environment config.
  shell         Spawns a shell within the virtualenv.
  sync          Installs all packages specified in Pipfile.lock.
  uninstall     Uninstalls a provided package and removes it from Pipfile.
  update        Runs lock, then sync.
  verify        Verify the hash in Pipfile.lock is up-to-date.
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How to create virtual environment with pyenv-virtualenv plugin

pyenv-virtualenv is a pyenv plugin that provides features to manage virtualenvs and conda environments for Python on UNIX-like systems.

If you don't have pyenv in your system, follow below post;

Installing pyenv-virtualenv

$ brew update
$ brew install pyenv-virtualenv

Setting PATH

Run one of the following commands in terms of your shell's .rc file.

$ echo 'eval "$(pyenv virtualenv-init -)"' >> ~/.bashrc
$ echo 'eval "$(pyenv virtualenv-init -)"' >> ~/.zshrc

Creating virtual environment

$ mkdir python_demo
$ cd python_demo
$ pyenv install 3.11.4
$ pyenv virtualenv 3.11.4 python_demo-3.11.4
$ pyenv virtualenvs
$ pyenv prefix python_demo-3.11.4
$ ls -Llat $(pyenv prefix python_demo-3.11.4)

drwxr-xr-x  14 kenanhancer  staff  448 19 Jun 17:36 bin
-rw-r--r--   1 kenanhancer  staff  107 19 Jun 17:36 pyvenv.cfg
drwxr-xr-x   3 kenanhancer  staff   96 19 Jun 17:36 lib
drwxr-xr-x   2 kenanhancer  staff   64 19 Jun 17:36 include
$ tree -a -L 4 $(pyenv prefix python_demo-3.11.4)

├── bin
│   ├── Activate.ps1
│   ├── activate
│   ├── activate.csh
│   ├──
│   ├── pip
│   ├── pip3
│   ├── pip3.11
│   ├── pydoc
│   ├── python -> python3.11
│   ├── python3 -> python3.11
│   └── python3.11 -> /Users/kenanhancer/.pyenv/versions/3.11.4/bin/python3.11
├── include
│   └── python3.11
├── lib
│   └── python3.11
│       └── site-packages
│           ├── _distutils_hack
│           ├── distutils-precedence.pth
│           ├── pip
│           ├── pip-23.1.2.dist-info
│           ├── pkg_resources
│           ├── setuptools
│           └── setuptools-65.5.0.dist-info
└── pyvenv.cfg
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