datavizhub 0.1.4

A tool to ingest data from various sources and formats, create imagery or video based on that data, and send the results to various locations for dissemination.

DataVizHub

Overview

This project automates the the ability to injest data from a variety of sources and formats, create imagery or video based on that data, and send the results to a variety of locations for dissemination. It's designed to efficiently handle tasks like syncing files from an FTP server, processing these files into a video, and updating metadata in a cloud storage system.

Features

• FTP Syncing: Automatically syncs image files from a specified FTP server.
• Video Processing: Processes a sequence of images into a cohesive video file.
• Vimeo Integration: Uploads the processed video to a specified Vimeo account.
• AWS S3 Management: Handles the uploading of metadata files to an AWS S3 bucket.
• Command-Line Interface: Easy to use CLI for configuring and running the system.

Prerequisites

Before you begin, ensure you have met the following requirements:

• Python 3.x installed.
• Optional: A Vimeo account with API credentials for video uploading.
• Optional: An AWS account with S3 access for metadata management.
• Optional: FFmpeg installed for video processing.
• Optional: Access to an FTP server for image file syncing.

Development Installation

To install the necessary Python packages, from the project root run:

pipx install poetry

poetry install

Package Installation

To install the datavizhub package change directory to the download directory and type:

pip install datavizhub-<version>.tar.gz

Configuration

The system requires several configurations to be passed as command-line arguments. These include paths to directories, FTP server details, Vimeo and AWS credentials, etc.

Usage

To run the script, use the following command:

Replace [arguments] with the necessary command-line arguments.

rtvideo [arguments]

Command Line Arguments

This script supports various command line arguments for customizing its operation. Below is a detailed explanation of each argument:

• -i, --input_dir (required):

  • Description: The directory where the input image files are located.
  • Usage: -i <path_to_directory> or --input_dir <path_to_directory>

• -o, --output_file (required):

  • Description: The path for the output video file.
  • Usage: -o <output_file_path> or --output_file <output_file_path>

• -vimeo-uri, --existing_video_uri (required):

  • Description: The URI on Vimeo where the updated video will be placed.
  • Usage: -vimeo-uri <vimeo_uri> or --existing_video_uri <vimeo_uri>

• -id, --dataset_id (required):

  • Description: The catalog dataset ID to update with the new video.
  • Usage: -id <dataset_id> or --dataset_id <dataset_id>

• -period, --dataset_period (required):

  • Description: The duration for which to generate the movie (in ISO 8601 format).
  • Usage: -period <duration> or --dataset_period <duration>

• -vimeo-client, --vimeo_client_id (required, credential if argument not provided):

  • Description: The Vimeo client ID associated with the app.
  • Usage: -vimeo-client <client_id> or --vimeo_client_id <client_id>

• -vimeo-secret, --vimeo_client_secret (required, credential if argument not provided):

  • Description: The Vimeo client secret associated with the app.
  • Usage: -vimeo-secret <client_secret> or --vimeo_client_secret <client_secret>

• -vimeo-token, --vimeo_access_token (required, credential if argument not provided):

  • Description: The Vimeo access token associated with the app.
  • Usage: -vimeo-token <access_token> or --vimeo_access_token <access_token>

• -aws-key, --aws_access_key (required, credential if argument not provided):

  • Description: The AWS access key required for S3 transfers.
  • Usage: -aws-key <access_key> or --aws_access_key <access_key>

• -aws-secret, --aws_secret_key (required, credential if argument not provided):

  • Description: The AWS secret key required for S3 transfers.
  • Usage: -aws-secret <secret_key> or --aws_secret_key <secret_key>

• -host, --ftp_host (optional):

  • Description: The FTP host to connect to. Default is "public.sos.noaa.gov".
  • Usage: -host <ftp.example.com> or --ftp_host <ftp.example.com>

• -b'=, --basemap (optional):

  • Description: The internal path to an optional basemap image that will appear behind data in a video.
  • Usage: --basemap "earth_vegetation.jpg

• -v, --verbose,

  • Description: Enable verbose logging.
  • Usage: --verbose

Example (no environmental variables)

rtvideo -i "./images" -o "./output/video.mp4" -vimeo-uri "/videos/12345" -id "DATASET_ID" -period "1Y" -vimeo-client "VIMEO_CLIENT_ID" -vimeo-secret "VIMEO_CLIENT_SECRET" -vimeo-token "VIMEO_ACCESS_TOKEN" -aws-key "AWS_ACCESS_KEY" -aws-secret "AWS_SECRET_KEY" -host "ftp.example.com" -r "/ftp/images" -u "ftpuser" -p "ftppassword"

Example ( environmental variables)

rtvideo -i "./images" -o "./output/video.mp4" -vimeo-uri "/videos/12345" -id "DATASET_ID" -period "1Y" -host "ftp.example.com" -r "/ftp/images" -u "ftpuser" -p "ftppassword"

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Your Name - [e-mail]

Project Link: https://github.com/NOAA-GSL/datavizhub

PyPi Package: https://pypi.org/project/datavizhub/