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Client for Ambry libraries

Project Description

A client application for Ambry libraries. The client presents a simple interface that returns acessors objects, providing a thin attrubute interface on the dictionaries you normally get by directly converting the JSON objects the library returns.

Installation

$ pip install ambry-client

Command Line Client

The ambry-client package also installs a command line program ambrydl. Run ambrydl -h for the help message. If you want download all of the public files from a library:

$ ambrydl http://example.com

If the files in the library are not public, you will need to set a username and secret. ( Note that the secret is used for the API, and is different from the password, which is used in the web UI )

$ ambrydl -u eric -s ABwq9ZAch3Jiy4CPce8r http://example.com

If you want to download a subset of the files, you can specify a subset of datasets or files using their vid or vnames. These are viewable in the web interface, or using the ambrydl -l command. These values look like:

  • File vid: p03r003003
  • File name: oshpd.ca.gov-pqi-pqi-county-0.0.3
  • Dataset vid: d03r003
  • Dataset vname: oshpd.ca.gov-pqi-0.0.3

Using one or more of these names, you can download specific files, or all of the files in a dataset:

$ ambrydl http://example.com d03r003 cdph.ca.gov-hci-abuse_neglect-california

By default, the files will be written with the cache key, which is the standard path name for ambry files. You can also use the -v option to write the file names using the vid, or -n to write the files using the vname.

Authentication

To authenticate with the command line client, use the -u option to specify a username, and the -s option to specify a secret. These values can be set on the server site using the ambry ui user add command.

API

The Client object has these methods:

  • list() Return a list of Dataset objects, one for each dataset in the library. The Dataset objects have a limited number of fields, fewer than those returned by dataset()
  • dataset(ref) Return a dataset, with all of the fields. Most significantly is the partitions property, which holds records for all of the files in the dataset.
  • partition(ref) Return a partition, with all of its fields.

If you use list() to get datasets, they will have a subset of the available fields, to make the reuqest faster. To get the complete list use the Dataset.detailed property to re-request all of the fields.

Locating Properties

There are a lot of properties for each object, dynamically generated from the response from the Library server. To get a sense of what properties are available, you can either iterate over the Dataset or Partition object as a dictionary, using keys(), values() or items(), or view the JSON output on the Library website, available from the blue ‘{json}’ buttons in the footer.

Writing Files

The Partition object have several methods for acessing row information and writing CSV files:

  • rows returns an iterator, over the rows in the file. The first row is the header
  • csvlines returns an iterator, iterating over CSV formatted lines.
  • write_csv(path) writes the data in the partition to a CSV file.

Example

Here is a simple example of iterating over all of the partitions in a library, printing out the dataset and partition titles, and writing CSV files:

from ambry_client import Client
import os

base_url = 'http://localhost:8080'

client = Client(base_url, username, secret)

for ds in client.list():

    print ds.vid, ds.title

    for p in ds.partitions:
        print '  ', p.vid, p.description

        fn = '{}.csv'.format(p.vid)

        if not os.path.exists(fn):
            p.write_csv(fn)
Release History

Release History

This version
History Node

0.0.2

History Node

0.0.1

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