Metadata-Version: 2.1
Name: gigantum
Version: 1.3.0
Summary: CLI for the Gigantum Client
Home-page: https://github.com/gigantum/gigantum-cli
Author: Gigantum, Inc.
Author-email: support@gigantum.com
License: MIT
Description: ## Gigantum CLI
        
        [![PyPI version](https://badge.fury.io/py/gigantum.svg)](https://badge.fury.io/py/gigantum)
        [![CircleCI](https://circleci.com/gh/gigantum/gigantum-cli/tree/master.svg?style=svg)](https://circleci.com/gh/gigantum/gigantum-cli/tree/master)
        [![FOSSA Status](https://app.fossa.io/api/projects/git%2Bgithub.com%2Fgigantum%2Fgigantum-cli.svg?type=shield)](https://app.fossa.io/projects/git%2Bgithub.com%2Fgigantum%2Fgigantum-cli?ref=badge_shield)
        
        Simple user-facing command line interface (CLI) for installing and running the
        Gigantum Client locally
        
        ## Introduction
        
        This Python package is provided as a method to install and run the Gigantum
        Client, locally on your computer. It provides a simple command line
        interface to install, update, start, stop, and configure the application.
        
        More detailed install instructions can be found at the Gigantum
        [docs site](https://docs.gigantum.com/docs)
        
        If you encounter any issues or have any questions or comments, please join our
         [Spectrum Chat Community](https://spectrum.chat/gigantum).
        
        ## Prerequisites
        
        1. **Python**
        
           This tool requires that you have Python and
           [pip](https://pip.pypa.io/en/stable/installing/) installed on your system.
           It works with Python 3.4 and newer.
        
        2. **Docker**
        
           Gigantum requires the free Docker Community Edition to be installed to run
           locally on your computer. You do not need to keep Docker running at all
           times, but it must be open before you start the Gigantum application and
           can be closed after you stop the Gigantum application.
        
           If you don't already have Docker, you can install it directly from the
           Docker [website](https://www.docker.com/community-edition#/download)
        
           - Windows:
             - Requires Microsoft Windows 10 Professional, Enterprise, or Education
               (64-bit)
             - On most systems, Virtualization must be enabled in the "BIOS" (aka
               UEFI), and Hyper-V must also be enabled. Docker will usually
               set this for you, but is a good first place to look if things
               aren't working.
             - Requires Docker CE Stable: [https://store.docker.com/editions/community/docker-ce-desktop-windows](https://store.docker.com/editions/community/docker-ce-desktop-windows)
        
           - Mac:
             - Docker for Mac works on OS X El Capitan 10.11 and newer macOS releases: [https://store.docker.com/editions/community/docker-ce-desktop-mac](https://store.docker.com/editions/community/docker-ce-desktop-mac)
        
           - Ubuntu:
             - Install using Docker's "helper" script, which
               will perform all install steps for you (you may inspect the
               get-docker.sh script before running it):
        
               ```bash
               $ cd ~
               $ curl -fsSL get.docker.com -o get-docker.sh
               $ sudo sh get-docker.sh
               ```
             - **OR** install manually, following the instructions here:
               [https://docs.docker.com/engine/installation/linux/docker-ce/ubuntu/](https://docs.docker.com/engine/installation/linux/docker-ce/ubuntu/)
               - Typical installations will use the `amd64` option in step 4 of
                 "Setup The Repository"
               - You can skip step 3 of install Docker CE
             - Regardless of the install method used above, it is required that you
               add your normal user account to the `docker` user group so that you
               can run Docker commands without elevated privileges. Run the following
               command and then logout and back into your system for changes to take
               effect.
        
               ```
               $ sudo usermod -aG docker <your username>
               ```
        
               - Note, Docker provides this warning when doing this, which in most
                 cases is not an issue:
        
                 > WARNING: Adding a user to the "docker" group will grant the ability
                 > to run containers which can be used to obtain root privileges on
                 > the docker host.  Refer to
                 > https://docs.docker.com/engine/security/security/#docker-daemon-attack-surface
                 > for more information.
        
        3. **(Optional) Adjust Docker Resources**
        
        On Windows or MacOS, you can configure the amount of CPU and RAM allocated to
        Docker by clicking on `Preferences > Advanced` from the Docker Menu. Docker
        will use up to the amount specified when operating.
        
            ![preferences](docs/img/resources.png)
        
        ## Install the CLI
        
        This package is available for install via `pip`. It runs on Python 3.4+ and
        supports Windows, OSX and Linux.
        
        1. (Optional) To isolate this package from your system Python, it is often best
           to create a virtual environment first.  This is not required, but
           recommended if you feel comfortable enough with Python. The Gigantum CLI
           installs a minimal set of Python dependencies, so in general it should be
           safe to just install if preferred.
        
           Using [virtualenvwrapper](https://virtualenvwrapper.readthedocs.io/en/latest/):
        
           ```
           $ mkvirtualenv gigantum
           ```
        
           If you are familiar with conda or prefer to manually manage a virtualenv (or
           venv), these methods will also work.
        
        2. Install Gigantum CLI
        
           ```
           $ python3 -m pip install -U gigantum
           ```
        
           **OR** if you are actively developing the CLI, you may wish to install it
           from a checkout of this repository like so:
        
           ```
           $ git checkout <URL for gigantum-cli>
           $ python3 -m pip install -e gigantum-cli
           ```
        
           Do NOT use `python setup.py develop`.
        
        ## Commands
        
        The Gigantum CLI provides a few simple commands to support installation,
        updating, and use. When the `pip` package is installed, the Gigantum CLI is
        installed as a globally available script called `gigantum`.
        
        Usage of the CLI then becomes:
        
        ```
        $ gigantum -h
        Usage: gigantum [OPTIONS] COMMAND [ARGS]...
        
          A Command Line Interface to manage the Gigantum Client.
        
        Options:
          -h, --help  Show this message and exit.
        
        Commands:
          config    Manage the Client configuration file.
          feedback  Open the default web browser to provide feedback.
          install   Install the Gigantum Client Docker Image.
          server    Manage server connections for this Client instance.
          start     Start Gigantum Client.
          stop      Stop Gigantum Client.
          update    Check if an update is available for Gigantum Client.
        ```
        
        ## Usage
        
        ### Gigantum Working Directory
        
        The Gigantum working directory is where all your work is stored on your local
        filesystem. You can interact directly with this directory if you'd like, but it
        is recommended to use the Gigantum UI as it ensures all activity is properly
        recorded.
        
        The default working directory location changes based on your operating system:
        
        - **Windows**: `C:\Users\<username>\gigantum`
        - **OSX**: `/Users/<username>/gigantum`
        - **Linux**: `/home/<username>/gigantum`
        
        This directory follows a standard directory structure that organizes content by
        user and namespace. A namespace is the "owner" of a Project or Dataset, and typically the
        creator. The working directory is organized as illustrated below:
        
        ```
        <Gigantum Working Directory>
            |_ servers
                |_ <server id>
                    |_ <logged in user's username>
                        |_ <namespace>
                               |_ labbooks
                                  |_ <project name>
                               |_ datasets
                                  |_ <dataset name>
        ```
        
        As an example, if the user `sarah` created 1 Project and downloaded 1 Project
        from the user `janet` the directory would look like this:
        
        ```
        <Gigantum Working Directory>
            |_ servers
                |_ gigantum-com
                    |_ sarah
                        |_ sarah
                               |_ labbooks
                                  |_ my-first-labbook
                        |_ janet
                               |_ labbooks
                                  |_ initial-analysis-1
        ```
        
        
        ### User Account
        
        To use the Gigantum application you must have a Gigantum user account. When you
        run the application for the first time you can register with the default server gigantum.com.
        
        By default, once you login your user identity is cached locally. This lets you run the
        application when disconnected from the internet and without needing to log in
        again. If you logout, you will not be able to use the application again until
        you have internet access and can re-authenticate.
        
        ### Typical Work Flow
        
        After everything is installed, a typical usage would follow a workflow like
        this:
        
        - Start the Docker app if it is not already running
        - Open a terminal
        - Activate your virtualenv (if setup)
        
          ```
          $ workon gigantum
          ```
        - Start the application
        
          ```
          $ gigantum start
          ```
        - A browser will open to [http://localhost:10000](http://localhost:10000)
        - Perform your desired work
        - When complete, stop the application
        
          ```
          $ gigantum stop
          ```
        - If desired, quit the Docker app
        
        
        ## Providing Feedback
        
        If you encounter any issues using the Gigantum CLI, submit them to this [GitHub
        repository issues page](https://github.com/gigantum/gigantum-cli/issues).
        
        If you encounter any issues or have any feedback while using the the Gigantum
        Application, use the `gigantum feedback` command to open the discussion board.
        
        ## Contributing
        
        Gigantum uses the [Developer Certificate of Origin](https://developercertificate.org/). 
        This is lightweight approach that doesn't require submission and review of a
        separate contributor agreement.  Code is signed directly by the developer using
        facilities built into git.
        
        Please see [`docs/contributing.md` in the gtm
        repository](https://github.com/gigantum/gtm/tree/integration/docs/contributing.md).
        
        ## Credits
        
        TODO
        
        
        ## License
        [![FOSSA Status](https://app.fossa.io/api/projects/git%2Bgithub.com%2Fgigantum%2Fgigantum-cli.svg?type=large)](https://app.fossa.io/projects/git%2Bgithub.com%2Fgigantum%2Fgigantum-cli?ref=badge_large)
        
Keywords: data-science,science,gigantum,open-science,machine-learning
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.4
Description-Content-Type: text/markdown
