Enhanced command line SQL interpreter client for astronomical surveys.
easyaccess is an enhanced command line interpreter and Python package created to facilitate access to astronomical catalogs stored in SQL Databases. It provides a custom interface with custom commands and was specifically designed to access data from the Dark Energy Survey Oracle database, including autocompletion of tables, columns, users and commands, simple ways to upload and download tables using csv, fits and HDF5 formats, iterators, search and description of tables among others. It can easily be extended to another surveys or SQL databases. The package was completely written in Python and support customized addition of commands and functionalities.
For a short tutorial check here
Current version = 1.4.7
For DES public data release, you can start easyaccess with:
easyaccess -s desdr
To create an account click here.
- Oracle Client > 11g.2 (External library, no python) Check here for instructions on how to install these libraries
- cx_Oracle
- Note that cx_Oracle needs libaio on some Linux systems
- Note that cx_Oracle needs libbz2 on some Linux systems
- fitsio == 1.0.5
- pandas >= 0.14
- numpy
- termcolor
- PyTables (optional, for hdf5 output)
- future (for python 2/3 compatibility)
- requests
- gnureadline (optional, for better console behavior in OS X)
Installing easyaccess can be a little bit tricky given the external libraries required, in particular the Oracle libraries which are free to use. easyaccess is based heavily on the Oracle python client cx_Oracle, you can follow the installation instructions from here. For cx_Oracle to work, you will need the Oracle Instant Client packages which can be obtained from here.
Make sure you have these libraries installed before proceeding to the installation of easyaccess, you can try by opening a Python interpreter and type:
import cx_Oracle
If you have issues, please check the Troubleshooting page or our FAQ page.
You can clone this repository and install easyaccess with:
python setup.py install
easyaccess can also be installed using pip but it'd require the installation of the oracle instant client first as described above
pip install easyaccess==1.4.7
or directly from github:
pip install git+https://github.com/mgckind/easyaccess.git
For Collaborators, now easyaccess can be installed using conda out of the box! This is supported for versions 2.7 and 3.6
conda install easyaccess==1.4.7 -c mgckind -c anaconda
You can also create a new environment with:
conda create -n easy easyaccess==1.4.7 -c mgckind -c anaconda
and then:
source activate easy
For collaborators, We have a Docker image with easyaccess pre-installed which you can obtained from:
docker pull mgckind/easyaccess
We have a running list of FAQ which we will constantly update, please check here.
Please take a look st our Code of Conduct and or contribution guide.
If you use easyaccess in your work we would encourage to use this reference https://arxiv.org/abs/1810.02721 or copy/paste this BibTeX:
@ARTICLE{2018arXiv181002721C,
author = {{Carrasco Kind}, M. and {Drlica-Wagner}, A. and {Koziol}, A.~M.~G. and
{Petravick}, D.},
title = "{easyaccess: Enhanced SQL command line interpreter for astronomical surveys}",
journal = {arXiv e-prints},
keywords = {Astrophysics - Instrumentation and Methods for Astrophysics},
year = 2018,
month = Oct,
eid = {arXiv:1810.02721},
pages = {arXiv:1810.02721},
archivePrefix = {arXiv},
eprint = {1810.02721},
primaryClass = {astro-ph.IM},
adsurl = {https://ui.adsabs.harvard.edu/\#abs/2018arXiv181002721C},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
For a short tutorial and documentation see here, note that not all the features are available for the public use, i.e., DR1 users.
- Nice output format (using pandas)
- Very flexible configuration
- Smart tab autocompletion for commands, table names, column names, and file paths
- Write output results to CSV, TAB, FITS, or HDF5 files
- Load tables from CSV, FITS or HDF5 files directly into DB (memory friendly by using number of rows or memory limit)
- Intrinsic DB commands to describe tables, schema, quota, and more
- Easyaccess can be imported as module from Python with a complete Python API
- Run commands directly from command line
- Load SQL queries from a file and/or from the editor
- Show the execution plan of a query if needed
- Python functions can be run in a inline query
Assuming that easyaccess is in your path, you can enter the interactive interpreter by calling easyaccess without any command line arguments:
easyaccess
Once inside the interpreter run SQL queries by adding a ";" at the end::
DESDB ~> select ... from ... where ... ;
To save the results into a table add ">" after the end of the query (after ";") and namefile at the end of line
DESDB ~> select ... from ... where ... ; > test.fits
The file types supported so far are: .csv, .tab, .fits, and .h5. Any other extension is ignored.
To load a table it needs to be in a csv format with columns names in the first row the name of the table is taken from filename or with optional argument --tablename
DESDB ~> load_table <filename> --tablename <mytable> --chunksize <number of rows to read/upload> --memsize <memory in MB to read at a time>
The --chunsize and --memsize are optional arguments to facilitate uploading big files.
To load SQL queries just run:
DESDB ~> loadsql <filename.sql>
or
DESDB ~> @filename.sql
The query format is the same as the interpreter, SQL statement must end with ";" and to write output files the query must be followed by " > "
The configuration file is located at $HOME/.easyaccess/config.ini but everything can be configured from inside easyaccess type:
DESDB ~> help config
to see the meanings of all the options, and:
DESDB ~> config all show
to see the current values, to modify one value, e.g., the prefetch value
DESDB ~> config prefetch set 50000
and to see any particular option (e.g., timeout):
DESDB ~> config timeout show
Much of the functionality provided through the interpreter is also available directly from the command line. To see a list of command-line options, use the --help option
easyaccess --help
We have included a simplified UML diagram describing the architecture and dependencies of easyaccess which shows only the different methods for a given class and the name of the file hosting a given class. The main class, easy_or(), inherits all methods from all different subclasses, making this model flexible and extendable to other surveys or databases. These methods are then converted to command line commands and functions that can be called inside easyaccess. Given that there are some DES specific functions, we have moved DES methods into a separate class DesActions().
