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Easily updatable local NCBI taxonomy dumps file copy

Project description

NtDownload

NtDownload is a tool for downloading and keeping up-to-date a local version of the NCBI Taxonomy database dump files

After download it creates a timestamp file, so that the next time the download is repeated only if a newer version is available.

Installation

The software is distributed as a Python 3 package and can be installed using pip install ntdownload.

Command line interface

ntdownload

To download the dump files, use the ntdownload script. Thereby the output directory is passed as CLI argument. If it does not exist, it is created. The file is downloaded using FTP, unless this does not work or the option --force-https is used, in which case HTTPS is used.

The dump files archive is unpacked after download and deleted, unless the option --no-unpack is used.

If the option --exitcode is used, then the exit code of the script is 100 if no newer version of the dump files was found, and thus nothing was downloaded. Otherwise the exit code is always 0 (or 1 on error).

ntnames

The script ntnames is provided, which, after download using ntdownload can be used for creating a list of taxonomy IDs and scientific names, which can be used as attribute source file for fastsubtrees.

API

Downloader

To download the dump files, use the Downloader class:

from ntdownload import Downloader
d = Downloader(output_directory_name)
has_downloaded = d.run()

The output directory is created if it does not exist. The dump files archive is unpacked and the archive deleted, except if the option unpack=False is used.

The download protocol is FTP unless it is not working or the option force_https=True is used, in which case HTTPS is used.

The return value of run() is True if a dump file was downloaded, False if no newer version was available.

Scientific names iterator

The function yield_scientific_names_from_dump(ntdumps_dir) yields tuples in the form (tax_id, scientific_name) reading them from the names.dmp file.

Test suite

The test suite is run using pytest.

Project details


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