Changelogs » Enasearch

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Enasearch

0.2.0

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

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

0.0.6

Fix:
  
  - Support `-h` as well as `--help`
  - Add `--version`
  - Remove (strange) boolean checking

0.0.5


        

0.0.1

ENASearch is a Python library for interacting with [ENA](http://www.ebi.ac.uk/ena/browse/programmatic-access)'s API.
  
  
  Usage
  
  ENASearch is easy to use
  
  
  $ enasearch --help
  Usage: enasearch [OPTIONS] COMMAND [ARGS]...
  
  Options:
  
  --help  Show this message and exit.
  
  Commands:
  get_analysis_fields       Get analysis fields
  get_display_options       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 search_data --help
  Usage: enasearch search_data [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 get_filter_fields and the type
  of filters with get_    filter_types
  --result TEXT           Id of a result (accessible with get_results)
  --display TEXT          Display option to specify the display format
  (accessible with get_    display_options)
  --download TEXT         (Optional) Download option to specify that records
  are to be saved     in a file (used with file
  option, list accessible with get_download_
  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 get_returnable    _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.retrieve_data(
  ids="A00145",
  display="fasta",
  download=None,
  file=None,
  offset=0,
  length=100000,
  subseq_range="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