Skip to main content

File organization made easy using tags

Project description

HyperTag

File organization made easy. HyperTag let's humans intuitively express how they think about their files using tags.

Objective Function: Minimize time between a thought and access to all relevant files.

Install

Available on PyPI

$ pip install hypertag

Community

Join the HyperTag matrix chat room to stay up to date on the latest developments.

Overview

HyperTag offers a slick CLI but more importantly it creates a directory called HyperTagFS which is a file system based representation of your files and tags using symbolic links and directories.

Directory Import: Import your existing directory hierarchies using $ hypertag import path/to/directory. HyperTag converts it automatically into a tag hierarchy using metatagging.

Semantic Text & Image Search (Experimental): Search for images (jpg, png) and text documents (yes, even PDF's) content with a simple text query. Text search is powered by the awesome Sentence Transformers library. Text to image search is powered by OpenAI's CLIP model. Currently only English queries are supported.

HyperTag Daemon (Experimental): Monitors HyperTagFS for user changes. Currently supports file and directory (tag) deletions + directory (name as query) creation with automatic query result population. Also spawns the DaemonService which speeds up semantic search significantly.

Fuzzy Matching Queries: HyperTag uses fuzzy matching to minimize friction in the unlikely case of a typo.

File Type Groups: HyperTag automatically creates folders containing common files (e.g. Images: jpg, png, etc., Documents: txt, pdf, etc., Source Code: py, js, etc.), which can be found in HyperTagFS.

HyperTag Graph: Quickly get an overview of your HyperTag Graph! HyperTag visualizes the metatag graph on every change and saves it at HyperTagFS/hypertag-graph.pdf.

HyperTag Graph Example

CLI Functions

Import existing directory recursively

Import files with tags inferred from the existing directory hierarchy

$ hypertag import path/to/directory

Tag file/s

Manually tag files

$ hypertag tag humans/*.txt with human "Homo Sapiens"

Untag file/s

Manually remove tag/s from file/s

$ hypertag untag humans/*.txt with human "Homo Sapiens"

Tag a tag

Metatag tag/s to create tag hierarchies

$ hypertag metatag human with animal

Merge tags

Merge all associations (files & tags) of tag A into tag B

$ hypertag merge human into "Homo Sapiens"

Query using Set Theory

Print file names of the resulting set matching the query. Queries are composed of tags and operands. Tags are fuzzy matched for convenience. Nesting is currently not supported, queries are evaluated from left to right

Print paths: $ hypertag query human --path
Print fuzzy matched tag: $ hypertag query man --verbose
Disable fuzzy matching: $ hypertag query human --fuzzy=0

Default operand is AND (intersection):
$ hypertag query human "Homo Sapiens" is equivalent to $ hypertag query human and "Homo Sapiens"

OR (union):
$ hypertag query human or "Homo Sapiens"

MINUS (difference):
$ hypertag query human minus "Homo Sapiens"

Index supported image and text files

Only indexed files can be searched.

$ hypertag index

To parse even unparseable PDF's, install tesseract: # pacman -S tesseract tesseract-data-eng

Index only image files: $ hypertag index --image
Index only text files: $ hypertag index --text

Semantic search for text files

Print text file names sorted by matching score. Performance benefits greatly from running the HyperTag daemon.

$ hypertag search "your important text query" --path --score --top_k=10

Semantic search for image files

Print image file names sorted by matching score. Performance benefits greatly from running the HyperTag daemon.

Text to image: $ hypertag search_image "your image content description" --path --score --top_k=10

Image to image: $ hypertag search_image "path/to/image.jpg" --path --score --top_k=10

Print all tags of file/s

$ hypertag tags filename1 filename2

Print all metatags of tag/s

$ hypertag metatags tag1 tag2

Print all tags

$ hypertag show

Print all files

Print names: $ hypertag show files

Print paths: $ hypertag show files --path

Visualize HyperTag Graph

Visualize the metatag graph hierarchy (saved at HyperTagFS root)

$ hypertag graph

Specify layout algorithm (default: fruchterman_reingold):

$ hypertag graph --layout=kamada_kawai

Generate HyperTagFS

Generate file system based representation of your files and tags using symbolic links and directories

$ hypertag mount

Start HyperTag daemon

Start daemon process with dual function:

  • Watch HyperTagFS directory for user changes
  • Spawn DaemonService to load and expose model used for semantic search

$ hypertag daemon

Set HyperTagFS directory path

Default is the user's home directory

$ hypertag set_hypertagfs_dir path/to/directory

Architecture

  • Python and it's vibrant open-source community power HyperTag
  • Many other awesome open-source projects make HyperTag possible (listed in pyproject.toml)
  • SQLite3 serves as the meta data storage engine (located at ~/.config/hypertag/hypertag.db)
  • Symbolic links are used to create the HyperTagFS directory structure
  • Semantic text search is powered by the awesome DistilBERT
  • Text to image search is powered by OpenAI's impressive CLIP model

Development

  • Clone repo: $ git clone https://github.com/SeanPedersen/HyperTag.git
  • $ cd HyperTag/
  • Install Poetry
  • Install dependencies: $ poetry install
  • Activate virtual environment: $ poetry shell
  • Run all tests: $ pytest -v
  • Run formatter: $ black hypertag/
  • Run linter: $ flake8
  • Run type checking: $ mypy **/*.py
  • Run security checking: $ bandit --exclude tests/ -r .
  • Run HyperTag: $ python -m hypertag

Inspiration

What is the point of HyperTag's existence?
HyperTag offers many unique features such as the import, semantic search for images and texts, graphing and fuzzy matching functions that make it very convenient to use. All while HyperTag's code base staying tiny at <1300 LOC in comparison to TMSU (>10,000 LOC) and SuperTag (>25,000 LOC), making it easy to hack on.

This project is partially inspired by these open-source projects:

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hypertag-0.5.3.tar.gz (22.7 kB view details)

Uploaded Source

Built Distribution

hypertag-0.5.3-py3-none-any.whl (22.6 kB view details)

Uploaded Python 3

File details

Details for the file hypertag-0.5.3.tar.gz.

File metadata

  • Download URL: hypertag-0.5.3.tar.gz
  • Upload date:
  • Size: 22.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.4 CPython/3.9.1 Linux/5.10.4-arch2-1

File hashes

Hashes for hypertag-0.5.3.tar.gz
Algorithm Hash digest
SHA256 a15547e43b027271df6db523ae4b66d145765128331b765785c43082a4ab224a
MD5 bf78238d767e75313407f1719f49221c
BLAKE2b-256 a00dfb5f5c4d752247336dc0db1e860339b56dfb2df98557fdb43f4fe608c257

See more details on using hashes here.

File details

Details for the file hypertag-0.5.3-py3-none-any.whl.

File metadata

  • Download URL: hypertag-0.5.3-py3-none-any.whl
  • Upload date:
  • Size: 22.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.4 CPython/3.9.1 Linux/5.10.4-arch2-1

File hashes

Hashes for hypertag-0.5.3-py3-none-any.whl
Algorithm Hash digest
SHA256 f10c3d95a22f2ac765076e7ce1a204b9b807778dcdf4cc695d8850ef694de2c0
MD5 f36fccac34e029863445743adcd2cca2
BLAKE2b-256 fe7606014527480eea9075e17a8dbb69ae1c4600ac19d0ea0a33e860fe758b6c

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page