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 2.7 and 3.5+.
An HTTP interface to this package exists too. Try it out!
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-dev.pip pip install . nose2
Alternatively, you can also run the project via Docker:
docker build -t gutenberg -f Dockerfile-py3 . docker run -it -v /some/mount/path:/data gutenberg python
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.
If getting BSD-DB to run on your platform is difficult, take a look at gutenbergpy which only depends on SQLite or MongoDB.
On Linux, you can usually install BSD-DB using your distribution's package manager. For example, on Ubuntu, you can use apt-get:
sudo apt-get install libdb++-dev export BERKELEYDB_DIR=/usr pip install .
On Mac, you can install BSD-DB using homebrew:
brew install berkeley-db4 pip install .
On Windows, it's easiest to download a pre-compiled version of BSD-DB from pythonlibs which works great for Python 3.5+.
For example, if you have Python 3.5 on a 64-bit version of Windows, you
After you download the wheel, install it and you're good to go:
pip install bsddb3‑6.2.1‑cp35‑cp35m‑win_amd64.whl pip install .
Since its v6.x releases, BSD-DB switched to the AGPL3 license which is stricter than this project's Apache v2 license. This means that unless you're happy to comply to the terms of the AGPL3 license, you'll have to install an ealier version of BSD-DB (anything between 4.8.30 and 5.x should be fine). If you are happy to use this project under AGPL3 (or if you have a commercial license for BSD-DB), set the following environment variable before attempting to install BSD-DB:
Apache Jena Fuseki
As an alternative to the BSD-DB backend, this package can also use Apache Jena Fuseki
for the metadata store. The Apache Jena Fuseki backend is activated by
GUTENBERG_FUSEKI_URL environment variable to the HTTP
endpoint at which Fuseki is listening. If the Fuseki server has HTTP basic
authentication enabled, the username and password can be provided via the
For local development, the Fuseki server can be run via Docker:
docker run \ --detach \ --publish 3030:3030 \ --env ADMIN_PASSWORD=some-password \ --volume /some/mount/location:/fuseki \ stain/jena-fuseki:3.6.0 \ /jena-fuseki/fuseki-server --loc=/fuseki --update /ds export GUTENBERG_FUSEKI_URL=http://localhost:3030/ds export GUTENBERG_FUSEKI_USER=admin export GUTENBERG_FUSEKI_PASSWORD=some-password
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
A bunch of meta-data about ebooks can be 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, ...])
You can get a full list of the meta-data that can be queried by calling:
from gutenberg.query import list_supported_metadatas print(list_supported_metadatas()) # prints (u'author', u'formaturi', u'language', ...)
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_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)
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.