Skip to content

viveikjha/ztfquery

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

ztfquery

PyPI

DOI

cite ztfquery

ztfquery: a python tool to access ztf (and SEDM) data

ztfquery contains a list of tools:


Credits

Citation

Mickael Rigault. (2018, August 14). ztfquery, a python tool to access ZTF data (Version doi). Zenodo. http://doi.org/10.5281/zenodo.1345222

Acknowledgments

If you have used ztfquery for a research you are publishing, please include the following in your acknowledgments: "The ztfquery code was funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement n°759194 - USNAC, PI: Rigault)."

Corresponding Author:

M. Rigault: [email protected], CNRS/IN2P3


Installation

Install the code

using pip: pip install ztfquery (favored)

or for the latest version:

go wherever you want to save the folder and then

git clone https://github.com/MickaelRigault/ztfquery.git
cd ztfquery
python setup.py install

Set your environment

You should also create the global variable $ZTFDATA (usually in your ~/.bash_profile or ~/.cshrc). Data you will download from IRSA will be saved in the directory indicated by $ZTFDATA following the IRSA data structure.

Login and Password storage

Your credentials will requested the first time you need to access a service (IRSA, Marshal, etc.). They will then be stored, crypted, under ~/.ztfquery. Use ztfquery.io.set_account(servicename) to reset it.

You can also directly provide account settings when running load_metadata and download_data using the auth=[your_username, your_password] parameter. Similarly, directly provide the username and password to the ztf ops page when loading NightSummary using the ztfops_auth parameter.


Quick Examples

About

Access ZTF data from Python

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Jupyter Notebook 92.5%
  • Python 7.4%
  • TeX 0.1%