academictorrents 2.2.0

Academic Torrents Python APIs

Copyright (c) 2018 academictorrents

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Description: # Academic Torrents Python API

[](https://travis-ci.org/AcademicTorrents/at-python)
[](https://codecov.io/gh/AcademicTorrents/at-python)

This repository is an implementation of the BitTorrent protocol written in Python and downloadable as a `pip` module. You can download datasets from AcademicTorrents.com in two lines of code:
```
import academictorrents as at
path_of_giant_dataset = at.get("323a0048d87ca79b68f12a6350a57776b6a3b7fb") # Download massive dataset
```

# For people who want to download datasets
we're compatible with Python versions: 2.7, 3.4, 3.5, 3.6

To install:
`pip install academictorrents`

This package works with the academictorrents tracker. You can add a hash from [academictorrents.com](academictorrents.com) for your torrent, and download datasets into your project.

Here's a little example (it's implemented in `examples/basic_test.py` in case you want to play with our source code):
```
# Import the library
import academictorrents as at

# Download the data (or verify existing data)
filename = at.get("323a0048d87ca79b68f12a6350a57776b6a3b7fb")

# Then work with the data
import pickle, gzip
import sys, os, time

mnist = gzip.open(filename, 'rb')
train_set, valid_set, test_set = pickle.load(mnist, encoding='latin1')
mnist.close()
```


# For Contributors to the AcademicTorrents Python client
## Introduction
We use Github issues and pull requests to manage development of this repository. The folllowing is a guide for setting up the codebase to contribute PRs or try to debug issues.

## Installation
Getting setup to work on this client is pretty easy. First, install the source code, then install the dependencies with `pip`:

```
git clone https://github.com/AcademicTorrents/at-python.git
cd at-python
pip install -r requirements.txt
```
Done!

## Testing
We've got a test suite that you can run with `pytest -s tests/`. These tests also run on travis after every push to github. Some of our tests are empty -- usually in parts of the codebase that have been changing quickly -- but we should continue increasing our coverage. If you want to just run one little download, use `python examples/basic_test.py` (example code above).

## Architecture
The `academictorrents` module only has one "public" function, `.get`. This function checks for the torrent data on the filesystem. If it's not present, then it initiates a `Client` to download the data for us.

`Client` is our main thread, it manages the lifecycle of our other threads including `Tracker`, `PeerManager`, `PieceManager`, and many `WebSeedManager` threads. The `Client` thread uses the `PieceManager` class (not thread) to keep track of all the pieces of data. The main thread makes socket requests to `Peer`s, and enqueues jobs to request data from `HttpPeer`s. Socket responses are handled by `PeerManager`, whereas a fleet of `WebSeedManagers` threads handles the `HttpPeer`s.

Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2.6Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.0
Classifier: Programming Language :: Python :: 3.1
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6