ffmetadata-py 2.0.0

Python wrapper for The Fragile Families Metadata API

ffmetadata-py

Python wrapper for Fragile Families Metadata API

This Python package provides convenient wrappers to interface with the Fragile Families Metadata API. By downloading and importing the ff module, users can query the metadata variables. No other software installation is necessary.

Requirements

The ff module has been tested on Python 3.6, and should work on most Python 3.x installations.

Installation

The ffmetadata-py package is available on The Python Package Index (PyPI). The easiest way to install and use the module is to do a pip install

pip install ffmetadata-py

This step will also install any dependencies if needed (currently, the requests and simplejson libraries).

Alternatively, you can clone this Github repository and place the ff folder and it's contents at a location accessible by your Python 3.x installation (most commonly the site-packages folder for your Python installation). In this scenario, make sure that you have recent versions of the requests and simplejson libraries installed.

Getting Started

To get started, import the ff module using import ff. Follow the examples below on how to use the library.

Examples

Getting attributes of a variable

Get all attributes of a variable

Given the variable name, this function call returns a dictionary of all attribute name/value pairs.

>>> ff.select('ce3datey')
{'data_source': 'constructed', 'data_type': 'Continuous', ...

Get a single attribute of a variable

To get a single attribute value, call the select function with the second argument as the attribute you're interested in. Most attributes return str values, but a handful have int return values.

>>> ff.select('ce3datey', 'data_source')
'constructed'

Get multiple attributes of a variable

To get multiple attribute values, call the select function with the second argument as a list of string attribute names. A dictionary with name/value pairs is returned.

>>> ff.select('ce3datey', ['name', 'data_source'])
{'data_source': 'constructed', 'name': 'ce3datey'}

Searching for variables

Querying variables is done using the search function. In the simplest case, this function expects a dictionary with keys name, op and val. In all cases, a list of variable names is returned. Some examples follow.

Find variable(s) where name='ce3datey'

>>> ff.search({'name': 'name', 'op': 'eq', 'val': 'ce3datey'})
['ce3datey']

Find variable(s) where data_source='constructed' AND name ends with 'e'

Multiple search criteria can be specified by passing in a list of dictionaries. These are combined with an AND clause.

>>> ff.search([{'name': 'data_source', 'op': 'eq', 'val': 'constructed'}, {'name': 'name', 'op': 'like', 'val': '%e'}])
['cf1age', 'cf1ethrace', ...

Find variable(s) where data_source='constructed' OR name starts with 'c' OR name ends with 'd'

To specify an OR clause for multiple search combination, replace the search criteria with a dictionary keyed by OR, with values as a list of dictionaries.

>>> ff.search({'or': [{'name': 'data_source', 'op': 'eq', 'val': 'constructed'}, {'name': 'name', 'op': 'like', 'val': 'c%'}, {'name': 'name', 'op': 'like', 'val': '%d'}]})
['cf1intmon', 'cf1intyr', ...

Find variable(s) where data_source='constructed' OR (name ends with 'f' AND data_source='questionnaire')

More complicated search queries can b constructed, by combining several AND/OR clauses. In such cases, at any point where you want to specify a sub-query, pass in a dictionary keyed by either an AND or OR, with the values being valid search criteria themselves - either dictionaries of name/op/val keys, or sub-queries (defined recursively).

>>> ff.search({'or': [{'name': 'data_source', 'op': 'eq', 'val': 'constructed'}, {'and': [{'name': 'name', 'op': 'like', 'val': '%f'}, {'name': 'data_source', 'op': 'eq', 'val': 'questionnaire'}]}]})
['cf1intmon', 'cf1intyr', ...

For more complicated search queries, you may find the interactive Advanced Search page on the project website useful.