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Gutenberg

https://travis-ci.org/c-w/Gutenberg.svg?branch=master

Overview

This package contains a variety of scripts to make working with the Project Gutenberg body of public domain texts easier.

The functionality provided by this package includes:

  • Downloading texts from Project Gutenberg.
  • Cleaning the texts: removing all the crud, leaving just the text behind.
  • Making meta-data about the texts easily accessible.

The package has been tested with Python 2.6, 2.7 and 3.4

Installation

This project is on PyPI, so I'd recommend that you just install everything from there using your favourite Python package manager.

pip install gutenberg

If you want to install from source or modify the package, you'll need to clone this repository:

git clone https://github.com/c-w/Gutenberg.git

Now, you should probably install the dependencies for the package and verify your checkout by running the tests.

cd Gutenberg

virtualenv --no-site-packages virtualenv
source virtualenv/bin/activate
pip install -r requirements.pip

pip install nose
nosetests

Python 3

This package depends on BSD-DB. The bsddb module was removed from the Python standard library since version 2.7. This means that if you wish to use gutenberg on Python 3, you will need to manually install BSD-DB.

sudo apt-get install libdb5.1-dev
export BERKELEYDB_DIR=/usr
pip install -r requirements-py3.pip

If you are unable to install BSD-DB manually (e.g. on Windows), the library provides a SQLite-based fallback to the default BSD-DB implementation. However, be warned that this backend is much slower.

Usage

Downloading a text

from gutenberg.acquire import load_etext
from gutenberg.cleanup import strip_headers

text = strip_headers(load_etext(2701)).strip()
print(text)  # prints 'MOBY DICK; OR THE WHALE\n\nBy Herman Melville ...'
python -m gutenberg.acquire.text 2701 moby-raw.txt
python -m gutenberg.cleanup.strip_headers moby-raw.txt moby-clean.txt

Looking up meta-data

Title and author meta-data can queried:

from gutenberg.query import get_etexts
from gutenberg.query import get_metadata

print(get_metadata('title', 2701))  # prints frozenset([u'Moby Dick; Or, The Whale'])
print(get_metadata('author', 2701)) # prints frozenset([u'Melville, Hermann'])

print(get_etexts('title', 'Moby Dick; Or, The Whale'))  # prints frozenset([2701, ...])
print(get_etexts('author', 'Melville, Hermann'))        # prints frozenset([2701, ...])

Before you use one of the gutenberg.query functions you must populate the local metadata cache. This one-off process will take quite a while to complete (18 hours on my machine) but once it is done, any subsequent calls to get_etexts or get_metadata will be very fast. If you fail to populate the cache, the calls will raise an exception.

To populate the cache:

from gutenberg.acquire import get_metadata_cache
cache = get_metadata_cache()
cache.populate()

If you need more fine-grained control over the cache (e.g. where it's stored or which backend is used), you can use the set_metadata_cache function to switch out the backend of the cache before you populate it. For example, to use the Sqlite cache backend instead of the default Sleepycat backend and store the cache at a custom location, you'd do the following:

from gutenberg.acquire import set_metadata_cache
from gutenberg.acquire.metadata import SqliteMetadataCache

cache = SqliteMetadataCache('/my/custom/location/cache.sqlite')
cache.populate()
set_metadata_cache(cache)

Limitations

This project deliberately does not include any natural language processing functionality. Consuming and processing the text is the responsibility of the client; this library merely focuses on offering a simple and easy to use interface to the works in the Project Gutenberg corpus. Any linguistic processing can easily be done client-side e.g. using the TextBlob library.