ENASearch - Release: 0.2.0

• Move and fix data serialization
• Add doc
  • Context
  • Usage example
  • Interaction with ENA
  • Functional doc

Scientific Software - Peer-reviewed - Python
Published by bebatut over 8 years ago

ENASearch - Release: 0.1.1

Fix: - Error handling with a user-friendly output - All returnable fields as default - Comma-separated support for fields - Ugly output of the CLI

Add - Code coverage checking - Code health checking - Tests for CLI

Scientific Software - Peer-reviewed - Python
Published by bebatut over 8 years ago

ENASearch - Release: 0.0.6

Fix:

• Support -h as well as --help
• Add --version
• Remove (strange) boolean checking

Scientific Software - Peer-reviewed - Python
Published by bebatut over 8 years ago

ENASearch - Release: 0.0.5

Scientific Software - Peer-reviewed - Python
Published by bebatut over 8 years ago

ENASearch - First version of ENASearch

ENASearch is a Python library for interacting with ENA's API.

Usage

ENASearch is easy to use

``` $ enasearch --help Usage: enasearch [OPTIONS] COMMAND [ARGS]...

Options:

--help Show this message and exit.

Commands: getanalysisfields Get analysis fields getdisplayoptions Get display options

  get_download_options      Get download options
  get_filter_fields         Get filter fields

  get_filter_types          Get filter types

  get_results               Get list of results
  get_returnable_fields     Get returnable fields
  get_run_fields            Get run fields
  get_sortable_fields       Get sortable fields
  get_taxonomy_results      Get list of taxonomy results
  retrieve_analysis_report  Retrieve analysis report
  retrieve_data             Retrieve ENA data
  retrieve_run_report       Retrieve run report
  retrieve_taxons           Retrieve ENA taxon data
  search_data               Search data

$ enasearch searchdata --help Usage: enasearch searchdata [OPTIONS]

  Search data given a query

Options: --query TEXT Query string, made up of filtering conditions, joined by logical ANDs , ORs and NOTs and bound by double quotes; the filter fields for a query are accessible with getfilterfields and the type of filters with get_ filtertypes --result TEXT Id of a result (accessible with getresults) --display TEXT Display option to specify the display format (accessible with get_ displayoptions) --download TEXT (Optional) Download option to specify that records are to be saved in a file (used with file option, list accessible with getdownload_ options) --file PATH (Optional) File to save the content of the search (used with download option) --fields TEXT (Optional, Multiple) Fields to return (accessible with getreturnable _fields, used only for report as display value) --sortfields TEXT (Optional, Multiple) Fields to sort the results (accessible with get sortable_fields, used only for report as display value) --offset INTEGER RANGE (Optional) First record to get (used only for display different of fasta and fastq --length INTEGER RANGE (Optional) Number of records to retrieve (used only for display different of fasta and fastq --help Show this message and exit. ```

It can also be used as a Python library:

```

import enasearch enasearch.retrievedata( ids="A00145", display="fasta", download=None, file=None, offset=0, length=100000, subseqrange="3-63", expanded=None, header=None) [SeqRecord(seq=Seq('GAAGGAAGGTCTTCAGAGAACCTAGAGAGCAGGTTCACAGAGTCACCCACCTCA...GCC', SingleLetterAlphabet()), id='ENA|A00145|A00145.1', name='ENA|A00145|A00145.1', description='ENA|A00145|A00145.1 B.taurus BoIFN-alpha A mRNA : Location:3..63', dbxrefs=[])] ```

The information extracted from ENA can be in several formats: HTML, Text, XML, FASTA, FASTQ, ... XML outputs are transformed in a Python dictionary using xmltodict and the FASTA and FASTQ into SeqRecord objects using BioPython <http://biopython.org/wiki/Biopython>_.

Installation

To install ENASearch, simply:

$ pip install enasearch

Tests

ENASearch comes with tests:

$ make test

Generate the data descriptions

To run, ENASearch needs some data from ENA to describe how to query ENA. Currently, such information is manually extracted into CSV files in the data directory. Python objects are generated from these CSV files with

$ python src/serialize_ena_data_descriptors.py

Scientific Software - Peer-reviewed - Python
Published by bebatut almost 9 years ago