Skip to main content

Easy access to the DES DB. Enhanced command line SQL interpreter client for DES

Project description

# easyaccess <a href="https://github.com/mgckind/easyaccess/releases/tag/1.4.6"> <img src="https://img.shields.io/badge/release-v1.4.6-blue.svg" alt="latest release" /></a> <a href="https://github.com/mgckind/easyaccess/blob/master/LICENSE.txt"><img src="https://img.shields.io/badge/license-NCSA%20License-blue.svg" alt="License" /> </a> <a href="https://pypi.python.org/pypi/easyaccess/1.4.6"><img src="https://img.shields.io/badge/pypi-v1.4.6-orange.svg" alt="pypi version"/></a> ![](https://img.shields.io/conda/v/mgckind/easyaccess.svg) ![](https://img.shields.io/conda/pn/mgckind/easyaccess.svg) ![](https://img.shields.io/badge/python-2.7%7C3.6-blue.svg)

Enhanced command line SQL interpreter client for astronomical surveys.
![help_screen](data/help.gif)

## Description
`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](http://matias-ck.com/easyaccess)

**Current version = 1.4.6**

#### DES DR1 users
For DES public data release, you can start `easyaccess` with:

easyaccess -s desdr

To create an account click [here](https://des.ncsa.illinois.edu/easyweb/signup/).

## Requirements

- [Oracle Client](https://www.oracle.com/technetwork/database/database-technologies/instant-client/overview/index.html) > 11g.2 (External library, no python)
Check [here](https://www.oracle.com/technetwork/database/database-technologies/instant-client/overview/index.html) for instructions on how to install these libraries
- [cx_Oracle](https://cx-oracle.readthedocs.io/en/latest/index.html)
- Note that cx_Oracle needs libaio on some Linux systems
- Note that cx_Oracle needs libbz2 on some Linux systems
- [fitsio](https://github.com/esheldon/fitsio) >= 0.9.6
- [pandas](http://pandas.pydata.org/) >= 0.14
- [numpy](https://docs.scipy.org/doc/numpy-1.15.1/reference/index.html)
- [termcolor](https://pypi.python.org/pypi/termcolor)
- [PyTables](http://pytables.github.io/) (optional, for hdf5 output)
- [future](http://python-future.org/) (for python 2/3 compatibility)
- [requests](http://docs.python-requests.org/en/master/)
- [gnureadline](https://github.com/ludwigschwardt/python-gnureadline) (optional, for better console behavior in OS X)

## Installation

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](https://cx-oracle.readthedocs.io/en/latest/installation.html#quick-start-cx-oracle-installation). For `cx_Oracle` to work, you will need the Oracle Instant Client packages which can be obtained from [here](https://www.oracle.com/technetwork/database/database-technologies/instant-client/overview/index.html).

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](https://cx-oracle.readthedocs.io/en/latest/installation.html#troubleshooting) or our [FAQ page](FAQ.md).

#### Source Installation

You can clone this repository and install `easyaccess` with:

python setup.py install

#### Pip installation
`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==1.4.6

or directly from github:

pip install git+https://github.com/mgckind/easyaccess.git

#### Conda installation
For Collaborators, now easyaccess can be installed using [conda](http://conda.pydata.org/docs/install/quick.html) out of the box!

conda install easyaccess==1.4.6 -c mgckind -c anaconda

#### Docker
For collaborators, We have a Docker image with easyaccess pre-installed which you can obtained from:

docker pull mgckind/easyaccess

## FAQ
We have a running list of [FAQ](FAQ.md) which we will constantly update, please check [here](FAQ.md).

#### Contributing
Please take a look st our [Code of Conduct](CODE_OF_CONDUCT.md) and or [contribution guide](CONTRIBUTING.md).


## Citation
If you use `easyaccess` in your work we would encourage to use this reference [https://arxiv.org/abs/1810.02721](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}
}
```


## Usage

For a short tutorial and documentation see [here](http://matias-ck.com/easyaccess), note that not all the features are available for the public use, i.e., DR1 users.

#### Some *great* features
- 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


#### Interactive interpreter

Assuming that ```easyaccess``` is in your path, you can enter the interactive interpreter by calling ```easyaccess``` without any command line arguments:

easyaccess

#### Running SQL commands
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.

#### Load tables
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.

#### Load SQL queries
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 " > <output file>"

#### Configuration

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

#### Command line usage

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

## Architecture

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()`.

![`easyaccess` architecture diagram](paper/classes_simple.png)

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

easyaccess-1.4.6.tar.gz (1.4 MB view details)

Uploaded Source

Built Distribution

easyaccess-1.4.6-py2.py3-none-any.whl (55.6 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file easyaccess-1.4.6.tar.gz.

File metadata

  • Download URL: easyaccess-1.4.6.tar.gz
  • Upload date:
  • Size: 1.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: Python-urllib/3.6

File hashes

Hashes for easyaccess-1.4.6.tar.gz
Algorithm Hash digest
SHA256 3d2f436e0eceb17c5b8fb46a9750234f2546da22dc841a2530ded58fcaf3efd6
MD5 1ec8b1036a41629ab6a82f7d15ed86e4
BLAKE2b-256 4c658822a83ac6b1827a493122d25ea4dcea1b14b3c2e62a7e2e182c765a4d89

See more details on using hashes here.

File details

Details for the file easyaccess-1.4.6-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for easyaccess-1.4.6-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 0c829558c075b661bcc6678279f274c06c2d08e4e1bd24674ee20dc602a68f8a
MD5 69994c7c9fd574cb211a545cd841797f
BLAKE2b-256 4d1cc15ad26f6ba790e0e80067dbe77d27e507eb11bbe6f98160bc392daa4c1e

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