mediawiki parser and utility library
Project description
mwlib - MediaWiki Parser and Utility Library
Overview
mwlib is a versatile library designed for parsing MediaWiki articles and converting them to various output formats. A notable application of mwlib is in Wikipedia's "Print/export" feature, where it is used to create PDF documents from Wikipedia articles.
Getting Started
Prerequisites
To build mwlib, ensure you have the following software installed:
- Python (version 3.11 or 3.12)
- Ploticus
- re2c
- Perl
- Pillow / PyImage
- ImageMagick
- uv (Python package installer, faster alternative to pip)
Setup a virtual environment for Python 3.11 or 3.12 and activate it.
Installing uv
If you don't have uv installed, you can install it following the instructions at uv's official documentation.
For example, on Unix-like systems:
curl -LsSf https://astral.sh/uv/install.sh | sh
Or using pip:
pip install uv
Installing mwlib
To install all dependencies and the project, run:
$ make install
This will use uv to install all required dependencies.
To build the C extensions and install mwlib in development mode:
$ make build
$ make develop
Documentation
Please visit http://mwlib.readthedocs.org/en/latest/index.html for detailed documentation.
Configuration
OAuth2 Configuration
mwlib supports OAuth2 client_credentials flow for Wikipedia API access. This allows authenticated access to MediaWiki APIs that require OAuth2 authentication, while maintaining compatibility with wikis that don't use OAuth2.
OAuth2 Configuration Options
The following configuration options are available for OAuth2:
oauth2.client_id: OAuth2 client IDoauth2.client_secret: OAuth2 client secretoauth2.token_url: URL for obtaining OAuth2 tokens (default: https://meta.wikimedia.org/w/rest.php/oauth2/access_token)oauth2.enabled: Whether to use OAuth2 (default: False)
HTTP/2 Configuration Options
mwlib also supports HTTP/2 for improved performance:
http2.enabled: Whether to use HTTP/2 (default: True)http2.auto_detect: Whether to auto-detect HTTP/2 support (default: True)
These configuration options can be set either through environment variables or in a configuration file (mwlib.ini or ~/.mwlibrc). The following table shows the mapping between configuration file options and their corresponding environment variables:
| Config File Option | Environment Variable | Description |
|---|---|---|
| oauth2.client_id | MWLIB_OAUTH2_CLIENT_ID | OAuth2 client ID |
| oauth2.client_secret | MWLIB_OAUTH2_CLIENT_SECRET | OAuth2 client secret |
| oauth2.token_url | MWLIB_OAUTH2_TOKEN_URL | Token endpoint URL |
| oauth2.enabled | MWLIB_OAUTH2_ENABLED | Enable OAuth2 (true/false) |
| http2.enabled | MWLIB_HTTP2_ENABLED | Enable HTTP/2 (true/false) |
| http2.auto_detect | MWLIB_HTTP2_AUTO_DETECT | Auto-detect HTTP/2 support |
Example configuration file (mwlib.ini):
[oauth2]
enabled=true
client_id=your-client-id
client_secret=your-client-secret
[http2]
auto_detect=true
Example Usage
You can also set the config parameters directly when instantiating MwApi:
from mwlib.network.sapi import MwApi
# Using OAuth2
api = MwApi(
apiurl="https://en.wikipedia.org/w/api.php",
use_oauth2=True
)
The recommended best practice, however, is to configure environment variables:
export MWLIB_OAUTH2_CLIENT_ID="your_client_id"
export MWLIB_OAUTH2_CLIENT_SECRET="your_client_secret"
export MWLIB_OAUTH2_ENABLED="True"
BigQuery Lookup for Image Description Pages
mwlib can use Google BigQuery to look up image description pages (namespace 6) instead of fetching them from the remote MediaWiki API. This significantly reduces the number of API requests and bypasses Wikipedia rate limits for configured domains.
The data originates from the Wikimedia Enterprise API snapshot endpoint, which provides Wikipedia page data as NDJSON files. These snapshots are loaded into a BigQuery table containing pre-extracted metadata: templates (used for license checking), image dimensions, content URLs, and license information.
How it works
- During ZIP creation (
mw-zip), image description page titles for configured domains (default:en.wikipedia.org) are batched and queried from BigQuery. - For pages found in BigQuery, templates are stored locally and an early license check is performed — images that fail the license filter are never downloaded.
- Pages not found in BigQuery fall back to the remote MediaWiki API.
- Non-configured domains (e.g., Commons) always use the remote API.
Prerequisites
The BigQuery client (and the wme-ingest CLI that loads snapshots into it)
is shipped behind the bigquery extra so default installs stay slim. Install
it via the extra rather than pinning google-cloud-bigquery directly:
# pip
pip install "mwlib[bigquery]"
# uv (project install)
uv pip install "mwlib[bigquery]"
# uv (developer checkout)
uv sync --extra bigquery
The bigquery extra is also pulled in by the dev dependency group, so
uv sync (default groups) installs it for development and test runs.
Set up GCP authentication by pointing to a service account JSON file:
export GOOGLE_APPLICATION_CREDENTIALS="/path/to/service-account.json"
BigQuery Configuration Options
| Config File Option | Environment Variable | Default | Description |
|---|---|---|---|
| bigquery.enabled | MWLIB_BIGQUERY_ENABLED | false | Master switch to enable BigQuery lookups |
| bigquery.project | MWLIB_BIGQUERY_PROJECT | (required) | GCP project ID |
| bigquery.dataset | MWLIB_BIGQUERY_DATASET | wme_snapshots | BigQuery dataset name |
| bigquery.table | MWLIB_BIGQUERY_TABLE | file_pages | BigQuery table name |
| bigquery.timeout | MWLIB_BIGQUERY_TIMEOUT | 30 | Query timeout in seconds |
| bigquery.domains | MWLIB_BIGQUERY_DOMAINS | en.wikipedia.org | Comma-separated domains to route through BigQuery |
Example environment variable configuration:
export MWLIB_BIGQUERY_ENABLED="true"
export MWLIB_BIGQUERY_PROJECT="my-gcp-project"
export MWLIB_BIGQUERY_DATASET="wikipedia"
export MWLIB_BIGQUERY_TABLE="file_pages"
export MWLIB_BIGQUERY_DOMAINS="en.wikipedia.org"
export GOOGLE_APPLICATION_CREDENTIALS="/path/to/service-account.json"
Or in a configuration file (mwlib.ini):
[bigquery]
enabled=true
project=my-gcp-project
dataset=wikipedia
table=file_pages
domains=en.wikipedia.org
When BigQuery is disabled or unavailable (missing credentials, network error, etc.), mwlib falls back to the remote API automatically with no change in behavior.
Loading Data into BigQuery
Use the wme-ingest command to download a Wikimedia Enterprise namespace 6 snapshot and load it into BigQuery:
# Full pipeline: download snapshot + load into BigQuery
wme-ingest --project my-gcp-project --dataset wikipedia
# Load from an already-downloaded tarball
wme-ingest -i /path/to/enwiki_ns6.tar.gz --project my-gcp-project --dataset wikipedia
# List available snapshots
wme-ingest --list
This requires Wikimedia Enterprise API credentials:
export WME_USERNAME="your-username"
export WME_PASSWORD="your-password"
Docker Compose Setup
For users interested in setting up mwlib using Docker Compose, detailed instructions are available at Docker Compose documentation.
License
Copyright (c) 2007-2012 PediaPress GmbH
All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
-
Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
-
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
-
Neither the name of PediaPress GmbH nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
.. _SpamBayes: http://spambayes.sourceforge.net/
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