Python SDK for interacting neuroscience data via the Boss API.
Project description
# intern
[![PyPI version](https://badge.fury.io/py/intern.svg)](https://badge.fury.io/py/intern)
[![CircleCI](https://circleci.com/gh/jhuapl-boss/intern.svg?style=svg)](https://circleci.com/gh/jhuapl-boss/intern)
**intern** (Integrated Toolkit for Extensible and Reproducible Neuroscience) is
a Python 2/3 module that enables big-data neuroscience. Currently, it provides
an interface to the Boss API, and in the future may provide interfaces to other
neuroscience databases.
intern is inspired by the [NeuroData](http://neurodata.io) ndio package:
[https://github.com/neurodata/ndio](https://github.com/neurodata/ndio)
## Installation
- It's always a good idea to use virtualenv to isolate your work from your system Python installation
- Using [virtualenv](https://virtualenv.pypa.io/en/stable/):
```
virtualenv intern
. intern/bin/activate
```
- Using [virtualenvwrapper](https://virtualenvwrapper.readthedocs.io/en/latest/):
```
mkvirtualenv intern
```
- (Preferred) Install via pypi
```
pip install intern
```
- Install via git
Clone the repository from https://github.com/jhuapl-boss/intern and run
`pip install -r requirements.txt` from the repository's location on your
system.
Add `<repository location>` to your `PYTHONPATH`.
For example, on a *nix system, if intern was cloned to ~/intern:
`export PYTHONPATH=$PYTHONPATH:~/intern`
## Getting Started
To quickly get started with intern, check out the wiki: [https://github.com/jhuapl-boss/intern/wiki](https://github.com/jhuapl-boss/intern/wiki)
## Documentation
Full detailed documentation can be found here: [https://jhuapl-boss.github.io/intern/](https://jhuapl-boss.github.io/intern/)
## Contributing
Please submit bug reports, or get in touch using GitHub Issues.
[![PyPI version](https://badge.fury.io/py/intern.svg)](https://badge.fury.io/py/intern)
[![CircleCI](https://circleci.com/gh/jhuapl-boss/intern.svg?style=svg)](https://circleci.com/gh/jhuapl-boss/intern)
**intern** (Integrated Toolkit for Extensible and Reproducible Neuroscience) is
a Python 2/3 module that enables big-data neuroscience. Currently, it provides
an interface to the Boss API, and in the future may provide interfaces to other
neuroscience databases.
intern is inspired by the [NeuroData](http://neurodata.io) ndio package:
[https://github.com/neurodata/ndio](https://github.com/neurodata/ndio)
## Installation
- It's always a good idea to use virtualenv to isolate your work from your system Python installation
- Using [virtualenv](https://virtualenv.pypa.io/en/stable/):
```
virtualenv intern
. intern/bin/activate
```
- Using [virtualenvwrapper](https://virtualenvwrapper.readthedocs.io/en/latest/):
```
mkvirtualenv intern
```
- (Preferred) Install via pypi
```
pip install intern
```
- Install via git
Clone the repository from https://github.com/jhuapl-boss/intern and run
`pip install -r requirements.txt` from the repository's location on your
system.
Add `<repository location>` to your `PYTHONPATH`.
For example, on a *nix system, if intern was cloned to ~/intern:
`export PYTHONPATH=$PYTHONPATH:~/intern`
## Getting Started
To quickly get started with intern, check out the wiki: [https://github.com/jhuapl-boss/intern/wiki](https://github.com/jhuapl-boss/intern/wiki)
## Documentation
Full detailed documentation can be found here: [https://jhuapl-boss.github.io/intern/](https://jhuapl-boss.github.io/intern/)
## Contributing
Please submit bug reports, or get in touch using GitHub Issues.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
intern-0.9.3.tar.gz
(52.1 kB
view hashes)
Built Distribution
intern-0.9.3-py2.py3-none-any.whl
(103.7 kB
view hashes)
Close
Hashes for intern-0.9.3-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d161f459458fd2110a50b4f7d7a756231abc5d67fa129afd6e3e1c6760aafd76 |
|
MD5 | 70347d812217fd56a4e74a69bffc2008 |
|
BLAKE2b-256 | 7c2a2d9fb9f3568462d06df68372f063de2e275ee41e32a53fc6330dff7445ed |