quicklook is a Python pipeline that searches for transit signals in TESS light curves. Given a target name, it downloads the light curve, estimates the stellar rotation period, searches for transiting companions using the Transit Least Squares (TLS) algorithm, and produces a publication-ready 9-panel diagnostic figure.
Although quicklook is optimized to find transiting exoplanets, it can also detect eclipsing binaries, variable stars, and other periodic signals.
- Multi-pipeline support -- SPOC, TESS-SPOC, QLP, CDIPS, PATHOS, TGLC, TASOC
- Automated detrending -- biweight, cosine, median, GP, and other wotan methods
- Stellar rotation -- Generalized Lomb-Scargle (GLS) periodogram
- Transit detection -- Transit Least Squares (TLS) periodogram
- Neighbor check -- Gaia source overlay on archival sky images
- Batch processing --
--each-sectormode, GNU parallel support, and candidate ranking tools - Web GUI -- Flask-based interface with live progress, job queue, and gallery
- HDF5 output -- full TLS results saved for downstream filtering
Create a conda environment and install from PyPI:
conda create -n quicklook python=3.12
conda activate quicklook
pip install -U quicklook-package# Web GUI
pip install -U "quicklook-package[gui]"
# Jupyter notebooks
pip install -U "quicklook-package[notebooks]"
# Development (testing, linting, formatting)
pip install -U "quicklook-package[dev]"
# Basic run on the latest TESS sector
ql --name WASP-21 -save -verbose
# Specific sector and pipeline
ql --name TOI-125.01 --sector 2 --pipeline qlp
# Custom detrending
ql --name TOI-125.01 --flatten_method cosine --window_length 0.3
# Restrict TLS period search range
ql --name TOI-125.01 --period_limits 1 5
# Run on every available sector
ql --name TOI-125.01 --each-sector -save
# Run all sectors with 4 parallel workers
ql --name TOI-125.01 --each-sector -j 4 -savefrom quicklook import TessQuickLook
ql = TessQuickLook(
target_name="WASP-21",
sector=56,
pipeline="SPOC",
flux_type="pdcsap",
verbose=True,
)
fig = ql.plot_tql()
# Access results
print(f"Rotation period: {ql.Prot_ls:.2f} days")
print(f"TLS period: {ql.tls_results.period:.4f} days")
print(f"TLS SDE: {ql.tls_results.SDE:.1f}")ql-guiOpen http://127.0.0.1:5000 in your browser. Enter a target, adjust parameters, and click Run QuickLook. Progress is streamed live via WebSocket. Supports single targets, batch submission, and each-sector mode.
ql --name WASP-21 -save -verbose
The 9-panel figure shows:
| Panel | Content |
|---|---|
| 1 | Raw light curve + trend line |
| 2 | GLS periodogram (stellar rotation period) |
| 3 | Phase-folded light curve at rotation period |
| 4 | Flattened light curve + detected transits |
| 5 | TLS periodogram (orbital period) |
| 6 | TESS aperture + Gaia sources on archival image |
| 7 | Phase-folded transit (odd/even comparison) |
| 8 | Secondary eclipse check at phase 0.5 |
| 9 | Summary of stellar and companion parameters |
| Command | Description |
|---|---|
ql |
Run the full QuickLook pipeline on a target |
read_tls |
Extract TLS results from a directory of .h5 files into a CSV |
rank_tls |
Filter and rank candidates by SDE from the CSV output |
ql-gui |
Launch the web GUI (requires [gui] extra) |
Process a list of TIC IDs:
# Generate batch script
cat tic_ids.txt | while read tic; do
echo "ql --name TIC$tic -save --outdir results | tee TIC$tic.log"
done > run_batch.sh
# Run in parallel with GNU parallel
cat run_batch.sh | parallel -j 4
# Extract and rank results
read_tls results/
rank_tls results/ --output_dir ranked
# Combine ranked plots into a PDF
pip install img2pdf
img2pdf ranked/*.png --output ranked.pdfFull documentation is available at quicklook.readthedocs.io.
See LICENSE for details.