Comet Hunter
Comet Hunter is an automated astronomical image ingestion and processing system designed to assist in the discovery of sungrazing comets from SOHO LASCO imagery.
About The Project
NASA's Sungrazer Project enables the discovery and reporting of comets visible from the SOHO and STEREO satellites. To date, over five thousand comets have been discovered using the SOHO satellite. On board SOHO is the LASCO coronagraph, which consists of two telescopes — C2 and C3. Images from these telescopes are primarily used for reporting new comets.
Why This Exists?
For comet discovery, users rely on fragmented tools for downloading, processing, and reviewing imagery. There is no unified platform that automates the complete workflow from raw image availability to chronological playback of processed frames. Comet Hunter aims to bridge this gap.
Present Challenges
- RAW images must be processed before becoming usable
- Sungrazer comets are often indistinguishable in single frames
- Chronological playback significantly improves detectability
- Most comets are reported within minutes of data availability.
- Time is critical.
The problem is not merely detection - it is rapid detection.
This requires a robust automation of the complete workflow: from RAW image ingestion to chronological playback of processed frames.
Current Capabilities
- Downlink slot synchronization
- Metadata ingestion from LASCO sources
- Parallel RAW image downloading
- Image processing pipelines for C2/C3
- Time-indexed frame retrieval
- REST API backend
- Scheduler-driven ingestion workflows
- Interactive frontend visualization
User Interface
Getting Started
End User Installation
Install Comet Hunter directly from PyPI:
pip install comet-hunter
End User Commands
Start the application
comet-hunter start
Check application status
comet-hunter status
Stop the application
comet-hunter stop
Note
When started, the application will be available at:
http://localhost:8080
Application data, logs, and database files are stored in:
Windows:
C:\Users\<username>\.comet_hunter
Linux/macOS:
~/.comet_hunter
Development Setup
Clone Repository
git clone https://github.com/AnandKri/comet-hunter.git
cd comet-hunter
Create Virtual Environment
Linux/macOS
python -m venv .venv
source .venv/bin/activate
Windows
python -m venv .venv
.venv\Scripts\activate
Install Dependencies
pip install -r requirements.txt
Run Backend
uvicorn backend.main:app --reload
Run Frontend
python frontend/app.py
Documentation
View full documentation hereMetadata
Release files for comet-hunter 0.2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| comet_hunter-0.2.1.tar.gz | 58.1 kB | Without provenance | Details for comet_hunter-0.2.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| comet_hunter-0.2.1-py3-none-any.whl | Python 3 | none | any | Details for comet_hunter-0.2.1-py3-none-any.whl |
Total release size: 141.9 kB
Release files / comet_hunter-0.2.1.tar.gz
| Download URL | comet_hunter-0.2.1.tar.gz |
|---|---|
| Size | 58.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.4
|
Release files / comet_hunter-0.2.1-py3-none-any.whl
| Download URL | comet_hunter-0.2.1-py3-none-any.whl |
|---|---|
| Size | 83.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.4
|
Security for comet-hunter 0.2.1
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