intrinio 0.1.15

Intrinio API client

intrinio
========

`|Build Status| <https://travis-ci.org/nhedlund/intrinio>`_

Unofficial Intrinio API client for Python. It gives easy access to
financial data.

Setup
-----

Install this package by using the pip tool:

::

pip install intrinio

Before retrieving data using the package the API username and password
has to be configured, either by setting the username and password
attributes of the intrinio package:

::

import intrinio
intrinio.username = 'USERNAME_FROM_INTRINIO'
intrinio.password = 'PASSWORD_FROM_INTRINIO'

Or by setting the system environment variables:

- INTRINIO\_USERNAME
- INTRINIO\_PASSWORD

Quick start
-----------

Get prices starting at 2016-01-01 for Apple:

::

import intrinio
intrinio.prices('AAPL', start_date='2016-01-01')

Get company information about Google:

``python import intrinio intrinio.companies('GOOG')`` Get company
information about Google using the low level **get** function:

::

import intrinio
intrinio.get('companies', identifier='GOOG')

Get cik, lei, name and ticker of companies with "Bank" in their company
name:

::

import intrinio
intrinio.companies(query='Bank')

Usage
-----

There are a high- and low level functions used to access the Intrinio
API.

The high level functions are mostly simple wrappers of the **get**
function that retrieves all data with optional parameters to filter the
data. They might also do some data conversion like for example the
prices endpoint where the date column is used as the index for the
Pandas DataFrame.

Low level functions
~~~~~~~~~~~~~~~~~~~

For more information about available endpoints and their parameters, see
Intrinio API documentation at: http://docs.intrinio.com/

- get(endpoint, \*\*parameters):

Get complete dataset from an endpoint using optional query
parameters.

Args:

::

endpoint: Intrinio endpoint, for example: companies
parameters: Optional query parameters

Returns: Dataset as a Pandas DataFrame

- get\_page(endpoint, page\_number=1, page\_size=None, \*\*parameters):

Get a dataset page from an endpoint using optional query parameters.

Args:

::

endpoint: Intrinio endpoint, for example: companies
page_number: Optional page number where 1 is first page (default 1)
page_size: Optional page size (default max page size for the endpoint)
parameters: Optional query parameters

Returns: Dataset page as a Pandas DataFrame with an additional
total\_pages attribute

High level functions
~~~~~~~~~~~~~~~~~~~~

- companies(identifier=None, query=None):

Get companies with optional filtering using parameters.

Args:

::

identifier: Identifier for the legal entity or a security associated
with the company: TICKER SYMBOL | FIGI | OTHER IDENTIFIER
query: Search of company name or ticker symbol

Returns: Dataset as a Pandas DataFrame

- securities(identifier=None, query=None, exch\_symbol=None):

Get securities with optional filtering using parameters.

Args:

::

identifier: Identifier for the legal entity or a security associated
with the company: TICKER SYMBOL | FIGI | OTHER IDENTIFIER
query: Search of security name or ticker symbol
exch_symbol: Exchange symbol

Returns: Dataset as a Pandas DataFrame

- indices(identifier=None, query=None, type=None):

Get indices with optional filtering using parameters.

Args:

::

identifier: Intrinio symbol associated with the index
query: Search of index name or symbol
type: Type of indices: stock_market | economic | sic

Returns: Dataset as a Pandas DataFrame

- prices(identifier, start\_date=None, end\_date=None,
frequency='daily', sort\_order='desc'):

Get historical stock market prices or indices.

Args:

::

identifier: Stock market symbol or index
start_date: Start date of prices (default no filter)
end_date: Last date (default today)
frequency: Frequency of prices: daily (default) | weekly | monthly |
quarterly | yearly
sort_order: Order of prices: asc | desc (default)

Returns: Dataset as a Pandas DataFrame

- news(identifier):

Get news for a company.

Args:

::

identifier: stock market ticker symbol associated with the company's
common stock. If the company is foreign, use the stock exchange
code, followed by a colon, then the ticker.

Returns: Dataset as a Pandas DataFrame

Tests
-----

Run the tests using pytest in the root directory of the project:

::

py.test

Or run the runtests script to also generate a coverage report (saved to
tmp/).

::

bin/runtests

Version history
---------------

- 0.1: Initial version

License
-------

- MIT License

.. |Build
Status| image:: https://travis-ci.org/nhedlund/intrinio.svg?branch=master