Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/piyoki/archiconda3

Light-weight Anaconda environment for ARM64 devices.
https://github.com/piyoki/archiconda3

anaconda archiconda conda jupyter virtualenv

Last synced: 2 months ago
JSON representation

Light-weight Anaconda environment for ARM64 devices.

Awesome Lists containing this project

README 

        
# Archiconda3



## Intro



`Archiconda3` is a distribution of `conda` for 64-bit ARM. Anaconda is a free and open-source distribution of the Python and R programming languages for scientific computing (data science, machine learning applications, large-scale data processing, predictive analytics, etc.), that aims to simplify package management and deployment. Like `Virtualenv`, Anaconda also uses the concept of creating environments so as to isolate different libraries and versions. The goal of this repository is to develop the groundwork needed to compile conda-forge on `aarch64`. Once that is laid out, we will be working toward backporting much of this work to conda-forge



## Setup



Since Archiconda3 is tailored for `ARM64` computer (Raspberry Pi, Jetson Devices), the setup process is different from the one with the normal Anaconda. To start off, please follow the setup instructions below:



#### Download the installation script and run it



```bash

$ wget https://github.com/Archiconda/build-tools/releases/download/0.2.3/Archiconda3-0.2.3-Linux-aarch64.sh

$ sudo sh Archiconda3-0.2.3-Linux-aarch64.sh

```



#### Export the path where Archiconda is installed, replace  to wherever it is installed



```bash

$ export PATH=/bin:$PATH

# ig:  export PATH=~/archiconda3/bin:$PATH

```



#### Check the version, if Conda is successfully installed, you will see the version info on the terminal.



```bash

$ conda -V

```



### To update to the latest version



```bash

$ conda update conda

$ conda -V

```



### To prevent Conda from activating the base environment by default



```bash

$ conda config --set auto_activate_base false

$ export "PATH=/bin:/usr/bin:$PATH" >> ~/.bashrc

$ source ~/.bashrc

$ which python3

```



## How To Use



### Create/Delete an environment



#### To create an environment



```bash

$ conda create --name envname (replace envname in your preference)

```



#### To create an environment with a specific version of Python



```bash

$ conda create -n envname python=3.6 (replace envname in your preference)

```



#### To delete an environment



```bash

$ conda remove -n envname --all (replace envname in your preference)

```



#### To remove an environment



```bash

$ conda remove -n envname --all (replace envname in your preference)

```



### Grant the current user permission



```bash

$ sudo chown -R username /archiconda

```



### Activate/Deactivate the environment



#### To activate the environment



```bash

$ conda activate envname (replace envname in your preference)

```



#### To deactivate the environment



```bash

$ conda deactivate

```



#### To prevent conda from activating the base environment by default



```bash

$ conda config --set auto_activate_base false

```



### Packages installation within an environment



#### To install a specific package such as SciPy into an existing environment--



```bash

$ conda install --name envname pkgname

```



#### If you do not specify the environment name, which in this example is done by --name myenv, the package installs into the current environment



```bash

$ conda install pkgname

```



#### Upgrade pip



```bash

$ python3 -m pip install --upgrade pip

```



#### Check pip version (Note please make sure you check the path of the pip, or the packages installed with pip/pip3 might not be installed in the conda environment)



```bash

$ which pip3

```



### Run jupyter notebook/lab inside the conda virtualenv



```bash

$ sudo chown -R username /archiconda

$ conda install -c conda-forge jupyterlab

$ conda install -c anaconda ipykernel

$ pip3 install --upgrade --force jupyter-console

```



#### Add an env to jupyter



```bash

$ ipykernel install --user --name=envname (replace envname in your preference)

```



#### Remove an env from jupyter



```bash

$ jupyter kernelspec uninstall envname (replace envname in your preference)

```



#### List the existing environments



```bash

$ jupyter kernelspec list

```



References:



- https://medium.com/@nrk25693/how-to-add-your-conda-environment-to-your-jupyter-notebook-in-just-4-steps-abeab8b8d084

- http://echrislynch.com/2019/02/01/adding-an-environment-to-jupyter-notebooks



## Run jupyter lab remotely from your client machine



For instance, you may open jupter notebook/lab from a windows/mac machine a client.



In the server machine, type the following commands:



```bash

$ jupyter lab --generate-config

$ sudo find / -name jupyter*notebook_config.py #it will display the path of the config file

$ vi /jupyter_notebook_config.py

# you may change the settings in your own preference.*

```



In your local client machine type the following commands:



```bash

$ rm ~/.ssh/known_hosts

$ ssh -L 8000:localhost:PORT username*@server_ip #check the port by opening jupter lab, the default is 8888 \

```



Note: you may change 8000 to whatever # in your preference



for example: `ssh -L 8000:localhost:9999 [email protected]`



type the adrress with the customized in the web browser localhost:8000



#### first-time login



1. Copy the token from the server terminal

2. Open a web browse from the client, type localhost:PORT (localhost:8000 as default), then it will promot up a windows to ask you to type in the token, just paste the token, and you should be good to go.



#### If you want to learn more about anaconda please visit the websites below:



- https://www.jianshu.com/p/11f980d912e3

- https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-pkgs.html

- https://blog.csdn.net/weixin_42401701/article/details/80820778