iex-api-python 0.0.3

Fetch data from the IEX API

[](https://travis-ci.org/danielecook/iex-api-python) [](https://coveralls.io/github/danielecook/iex-api-python)  [](http://www.danielecook.com/iex-api-python/)

# IEX-API-Python



This module is currently being actively developed. Feedback is welcomed.

### Summary

The `iex-api-python` module is a wrapper for the [IEX API](https://iextrading.com/developer/docs/#getting-started), and is designed to closely map to the organization of the original API while adding functionality. A few examples of the additional functionality are:

* Many queries are retadurned as [Pandas Dataframes](https://pandas.pydata.org/).
* Built-in support for websockets connections.
* Option to format timestamps as datetime objects or ISO format.

### Installation

_Note that you must be using Python >=3.6_

``` shell
pip install iex-api-python
```

### Getting Started

From the [API documenation](https://iextrading.com/developer/docs/#getting-started):

> The IEX API is a set of services designed for developers and engineers. It can be used to build high-quality apps and services. We’re always working to improve the IEX API. Please check back for enhancements and improvements.

* [Read the terms](https://iextrading.com/api-terms/).
* [Read the manual](https://iextrading.com/developer/docs/#market-data) and start building.
* [Attribute properly](https://iextrading.com/developer/docs/#attribution).

**The API terms apply to the use of this module, as does the requirement to properly attribute the use of IEX data.**

### Organization

The `IEX-API-Python` module is designed to map closely to the API from IEX. For many of the API calls, the resulting dataset is better represented in a tabular format. For these calls, data are returned as a [pandas.DataFrame](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html).

### Examples

To illustrate a few things you can do with `iex-api-python`, take a look at the examples below.

__Fetch all stock symbols__

``` python
from iex import reference
ref = reference()
ref.symbols() # Returns a Pandas Dataframe of all stock symbols, names, and more.
```
```
symbol date iexId isEnabled \
0 A 2018-05-16 2 True
1 AA 2018-05-16 12042 True
2 AABA 2018-05-16 7653 True
3 AAC 2018-05-16 9169 True
```

__Get a stock price__

``` python
from iex import stock
stock("F").price()
```
```
11.4
```

__Get a stocks price for the last year__
``` python
from iex import stock
stock("F").chart_table(range="1y")
```
```
change changeOverTime changePercent close date high \
0 0.000000 0.000000 0.000 10.2760 2017-05-16 10.3982
1 -0.169075 -0.016446 -1.645 10.1070 2017-05-17 10.2854
2 0.028180 -0.013712 0.279 10.1351 2017-05-18 10.1633
3 0.075144 -0.006394 0.741 10.2103 2017-05-19 10.2760
4 0.216042 0.014626 2.116 10.4263 2017-05-22 10.4545
5 -0.046966 0.010062 -0.450 10.3794 2017-05-23 10.4874
6 -0.084539 0.001830 -0.814 10.2948 2017-05-24 10.3888
...
```