Metadata-Version: 1.2
Name: courlan
Version: 0.7.0
Summary: Clean, filter and sample URLs to optimize data collection – includes spam, content type and language filters.
Home-page: https://github.com/adbar/courlan
Author: Adrien Barbaresi
Author-email: barbaresi@bbaw.de
License: GPLv3+
Project-URL: Blog, https://adrien.barbaresi.eu/blog/
Project-URL: Tracker, https://github.com/adbar/courlan/issues
Description: coURLan: Clean, filter, normalize, and sample URLs
        ==================================================
        
        
        .. image:: https://img.shields.io/pypi/v/courlan.svg
            :target: https://pypi.python.org/pypi/courlan
            :alt: Python package
        
        .. image:: https://img.shields.io/pypi/pyversions/courlan.svg
            :target: https://pypi.python.org/pypi/courlan
            :alt: Python versions
        
        .. image:: https://img.shields.io/codecov/c/github/adbar/courlan.svg
            :target: https://codecov.io/gh/adbar/courlan
            :alt: Code Coverage
        
        
        
        Why coURLan?
        ------------
        
            “It is important for the crawler to visit "important" pages first, so that the fraction of the Web that is visited (and kept up to date) is more meaningful.” (Cho et al. 1998)
        
            “Given that the bandwidth for conducting crawls is neither infinite nor free, it is becoming essential to crawl the Web in not only a scalable, but efficient way, if some reasonable measure of quality or freshness is to be maintained.” (Edwards et al. 2001)
        
        
        This library provides an additional “brain” for web crawling, scraping and management of Internet archives:
        
        - Avoid loosing bandwidth capacity and processing time for webpages which are probably not worth the effort.
        - Stay away from pages with little text content or explicitly target synoptic pages to gather links.
        
        Using content and language-focused filters, Courlan helps navigating the Web and enhancing text quality. Additional functions include straightforward domain name extraction and URL sampling.
        
        
        Features
        --------
        
        Separate `the wheat from the chaff <https://en.wiktionary.org/wiki/separate_the_wheat_from_the_chaff>`_ and optimize crawls by focusing on non-spam HTML pages containing primarily text.
        
        - Heuristics for triage of links
           - Targeting spam and unsuitable content-types
           - Language-aware filtering
           - Crawl management
        - URL handling
           - Validation
           - Canonicalization/Normalization
           - Sampling
        - Usable with Python or on the command-line
        
        
        **Let the coURLan fish out juicy bits for you!**
        
        .. image:: courlan_harns-march.jpg
            :alt: Courlan 
            :align: center
            :width: 65%
            :target: https://commons.wikimedia.org/wiki/File:Limpkin,_harns_marsh_(33723700146).jpg
        
        Here is a `courlan <https://en.wiktionary.org/wiki/courlan>`_ (source: `Limpkin at Harn's Marsh by Russ <https://commons.wikimedia.org/wiki/File:Limpkin,_harns_marsh_(33723700146).jpg>`_, CC BY 2.0).
        
        
        
        Installation
        ------------
        
        This package is compatible with with all common versions of Python, it is tested on Linux, macOS and Windows systems.
        
        Courlan is available on the package repository `PyPI <https://pypi.org/>`_ and can notably be installed with the Python package manager ``pip``:
        
        .. code-block:: bash
        
            $ pip install courlan # pip3 install on systems where both Python 2 and 3 are installed
            $ pip install --upgrade courlan # to make sure you have the latest version
            $ pip install git+https://github.com/adbar/courlan.git # latest available code (see build status above)
        
        
        Python
        ------
        
        Most filters revolve around the ``strict`` and ``language`` arguments.
        
        
        check_url()
        ~~~~~~~~~~~
        
        All useful operations chained in ``check_url(url)``:
        
        .. code-block:: python
        
            >>> from courlan import check_url
            # returns url and domain name
            >>> check_url('https://github.com/adbar/courlan')
            ('https://github.com/adbar/courlan', 'github.com')
            # noisy query parameters can be removed
            my_url = 'https://httpbin.org/redirect-to?url=http%3A%2F%2Fexample.org'
            >>> check_url(my_url, strict=True)
            ('https://httpbin.org/redirect-to', 'httpbin.org')
            # Check for redirects (HEAD request)
            >>> url, domain_name = check_url(my_url, with_redirects=True)
        
        
        Language-aware heuristics, notably internationalization in URLs, are available in ``lang_filter(url, language)``:
        
        .. code-block:: python
        
            # optional argument targeting webpages in English or German
            >>> url = 'https://www.un.org/en/about-us'
            # success: returns clean URL and domain name
            >>> check_url(url, language='en')
            ('https://www.un.org/en/about-us', 'un.org')
            # failure: doesn't return anything
            >>> check_url(url, language='de')
            >>>
            # optional argument: strict
            >>> url = 'https://en.wikipedia.org/'
            >>> check_url(url, language='de', strict=False)
            ('https://en.wikipedia.org', 'wikipedia.org')
            >>> check_url(url, language='de', strict=True)
            >>>
        
        
        Define stricter restrictions on the expected content type with ``strict=True``. Also blocks certain platforms and pages types crawlers should stay away from if they don't target them explicitly and other black holes where machines get lost.
        
        .. code-block:: python
        
            # strict filtering: blocked as it is a major platform
            >>> check_url('https://www.twitch.com/', strict=True)
            >>>
        
        
        
        Sampling by domain name
        ~~~~~~~~~~~~~~~~~~~~~~~
        
        
        .. code-block:: python
        
            >>> from courlan import sample_urls
            >>> my_urls = ['https://example.org/' + str(x) for x in range(100)]
            >>> my_sample = sample_urls(my_urls, 10)
            # optional: exclude_min=None, exclude_max=None, strict=False, verbose=False
        
        
        Web crawling and URL handling
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        
        Determine if a link leads to another host:
        
        .. code-block:: python
        
            >>> from courlan import is_external
            >>> is_external('https://github.com/', 'https://www.microsoft.com/')
            True
            # default
            >>> is_external('https://google.com/', 'https://www.google.co.uk/', ignore_suffix=True)
            False
            # taking suffixes into account
            >>> is_external('https://google.com/', 'https://www.google.co.uk/', ignore_suffix=False)
            True
        
        
        Other useful functions dedicated to URL handling:
        
        - ``get_base_url(url)``: strip the URL of some of its parts
        - ``get_host_and_path(url)``: decompose URLs in two parts: protocol + host/domain and path
        - ``get_hostinfo(url)``: extract domain and host info (protocol + host/domain)
        - ``fix_relative_urls(baseurl, url)``: prepend necessary information to relative links
        
        
        .. code-block:: python
        
            >>> from courlan import *
            >>> url = 'https://www.un.org/en/about-us'
            >>> get_base_url(url)
            'https://www.un.org'
            >>> get_host_and_path(url)
            ('https://www.un.org', '/en/about-us')
            >>> get_hostinfo(url)
            ('un.org', 'https://www.un.org')
            >>> fix_relative_urls('https://www.un.org', 'en/about-us')
            'https://www.un.org/en/about-us'
        
        
        Other filters dedicated to crawl frontier management:
        
        - ``is_not_crawlable(url)``: check for deep web or pages generally not usable in a crawling context
        - ``is_navigation_page(url)``: check for navigation and overview pages
        
        
        .. code-block:: python
        
            >>> from courlan import is_navigation_page, is_not_crawlable
            >>> is_navigation_page('https://www.randomblog.net/category/myposts')
            True
            >>> is_not_crawlable('https://www.randomblog.net/login')
            True
        
        
        Python helpers
        ~~~~~~~~~~~~~~
        
        Helper function, scrub and normalize:
        
        .. code-block:: python
        
            >>> from courlan import clean_url
            >>> clean_url('HTTPS://WWW.DWDS.DE:80/')
            'https://www.dwds.de'
        
        
        Basic scrubbing only:
        
        .. code-block:: python
        
            >>> from courlan import scrub_url
        
        
        Basic canonicalization/normalization only, i.e. modifying and standardizing URLs in a consistent manner:
        
        .. code-block:: python
        
            >>> from urllib.parse import urlparse
            >>> from courlan import normalize_url
            >>> my_url = normalize_url(urlparse(my_url))
            # passing URL strings directly also works
            >>> my_url = normalize_url(my_url)
            # remove unnecessary components and re-order query elements
            >>> normalize_url('http://test.net/foo.html?utm_source=twitter&post=abc&page=2#fragment', strict=True)
            'http://test.net/foo.html?page=2&post=abc'
        
        
        Basic URL validation only:
        
        .. code-block:: python
        
            >>> from courlan import validate_url
            >>> validate_url('http://1234')
            (False, None)
            >>> validate_url('http://www.example.org/')
            (True, ParseResult(scheme='http', netloc='www.example.org', path='/', params='', query='', fragment=''))
        
        
        UrlStore class
        ~~~~~~~~~~~~~~
        
        The `UrlStore` class allow for storing and retrieving domain-classified URLs, where a domain is in the form "https://example.org") and a URL in the form "https://example.org/path/testpage". It features the following methods:
        
        - URL management
           - ``add_urls(urls=[], appendleft=None, visited=False)``: Add a list of URLs to the (possibly) existing one. Optional: append certain URLs to the left, specify if the URLs have already been visited.
           - ``dump_urls()``: Print all URLs in store (URL + TAB + visited or not).
           - ``is_known(url)``: Check if the given URL has already been stored.
           - ``has_been_visited(url)``: Check if the given URL has already been visited.
           - ``filter_unknown_urls(urls)``: Take a list of URLs and return the currently unknown ones.
           - ``filter_unvisited_urls(urls)``: Take a list of URLs and return the currently unvisited ones.
           - ``find_known_urls(domain)``: Get all already known URLs for the given domain (ex. "https://example.org").
           - ``find_unvisited_urls(domain)``: Get all unvisited URLs for the given domain.
        - Crawling and downloads
           - ``get_url(domain)``: Retrieve a single URL and consider it to be visited (with corresponding timestamp).
           - ``get_download_urls(timelimit=10)``: Get a list of immediately downloadable URLs according to the given time limit per domain.
           - ``establish_download_schedule(max_urls=100, time_limit=10)``: Get up to the specified number of URLs along with a suitable backoff schedule (in seconds).
        
        
        
        Command-line
        ------------
        
        The main fonctions are also available through a command-line utility.
        
        .. code-block:: bash
        
            $ courlan --inputfile url-list.txt --outputfile cleaned-urls.txt
            $ courlan --help
            usage: courlan [-h] -i INPUTFILE -o OUTPUTFILE [-d DISCARDEDFILE] [-v]
                           [--strict] [-l LANGUAGE] [-r] [--sample]
                           [--samplesize SAMPLESIZE] [--exclude-max EXCLUDE_MAX]
                           [--exclude-min EXCLUDE_MIN]
        
        
        optional arguments:
          -h, --help            show this help message and exit
        
        I/O:
          Manage input and output
        
          -i INPUTFILE, --inputfile INPUTFILE
                                name of input file (required)
          -o OUTPUTFILE, --outputfile OUTPUTFILE
                                name of output file (required)
          -d DISCARDEDFILE, --discardedfile DISCARDEDFILE
                                name of file to store discarded URLs (optional)
          -v, --verbose         increase output verbosity
        
        Filtering:
          Configure URL filters
        
          --strict              perform more restrictive tests
          -l LANGUAGE, --language LANGUAGE
                                use language filter (ISO 639-1 code)
          -r, --redirects       check redirects
        
        Sampling:
          Use sampling by host, configure sample size
        
          --sample              use sampling
          --samplesize SAMPLESIZE
                                size of sample per domain
          --exclude-max EXCLUDE_MAX
                                exclude domains with more than n URLs
          --exclude-min EXCLUDE_MIN
                                exclude domains with less than n URLs
        
        
        License
        -------
        
        *coURLan* is distributed under the `GNU General Public License v3.0 <https://github.com/adbar/courlan/blob/master/LICENSE>`_. If you wish to redistribute this library but feel bounded by the license conditions please try interacting `at arms length <https://www.gnu.org/licenses/gpl-faq.html#GPLInProprietarySystem>`_, `multi-licensing <https://en.wikipedia.org/wiki/Multi-licensing>`_ with `compatible licenses <https://en.wikipedia.org/wiki/GNU_General_Public_License#Compatibility_and_multi-licensing>`_, or `contacting me <https://github.com/adbar/courlan#author>`_.
        
        See also `GPL and free software licensing: What's in it for business? <https://www.techrepublic.com/blog/cio-insights/gpl-and-free-software-licensing-whats-in-it-for-business/>`_
        
        
        
        Settings
        --------
        
        ``courlan`` is optimized for English and German but its generic approach is also usable in other contexts.
        
        Details of strict URL filtering can be reviewed and changed in the file ``settings.py``. To override the default settings, `clone the repository <https://docs.github.com/en/github/creating-cloning-and-archiving-repositories/cloning-a-repository-from-github>`_ and `re-install the package locally <https://packaging.python.org/tutorials/installing-packages/#installing-from-a-local-src-tree>`_.
        
        
        
        Contributing
        ------------
        
        `Contributions <https://github.com/adbar/courlan/blob/master/CONTRIBUTING.md>`_ are welcome!
        
        Feel free to file issues on the `dedicated page <https://github.com/adbar/courlan/issues>`_.
        
        
        Author
        ------
        
        This effort is part of methods to derive information from web documents in order to build `text databases for research <https://www.dwds.de/d/k-web>`_ (chiefly linguistic analysis and natural language processing). Extracting and pre-processing web texts to the exacting standards of scientific research presents a substantial challenge for those who conduct such research. Web corpus construction involves numerous design decisions, and this software package can help facilitate text data collection and enhance corpus quality.
        
        - Barbaresi, A. "`Trafilatura: A Web Scraping Library and Command-Line Tool for Text Discovery and Extraction <https://aclanthology.org/2021.acl-demo.15/>`_." *Proceedings of ACL/IJCNLP 2021: System Demonstrations*, 2021, pp. 122-131.
        - Barbaresi, A. "`Generic Web Content Extraction with Open-Source Software <https://konvens.org/proceedings/2019/papers/kaleidoskop/camera_ready_barbaresi.pdf>`_." *Proceedings of the 15th Conference on Natural Language Processing (KONVENS 2019)*, 2019, pp. 267-268.
        
        Contact: see `homepage <https://adrien.barbaresi.eu/>`_ or `GitHub <https://github.com/adbar>`_.
        
        Software ecosystem: see `this graphic <https://github.com/adbar/trafilatura/blob/master/docs/software-ecosystem.png>`_.
        
        
        
        Similar work
        ------------
        
        These Python libraries perform similar normalization tasks but do not entail language or content filters. They also do not focus on crawl optimization:
        
        - `furl <https://github.com/gruns/furl>`_
        - `ural <https://github.com/medialab/ural>`_
        - `yarl <https://github.com/aio-libs/yarl>`_
        
        
        References
        ----------
        
        - Cho, J., Garcia-Molina, H., & Page, L. (1998). Efficient crawling through URL ordering. *Computer networks and ISDN systems*, 30(1-7), 161–172.
        - Edwards, J., McCurley, K. S., and Tomlin, J. A. (2001). "An adaptive model for optimizing performance of an incremental web crawler". In *Proceedings of the 10th international conference on World Wide Web - WWW '01*, pp. 106–113.
        
Keywords: cleaner,crawler,preprocessing,url-parsing,url-manipulation,urls,validation,webcrawling
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Internet :: WWW/HTTP
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Text Processing :: Filters
Classifier: Topic :: Text Processing :: Linguistic
Requires-Python: >=3.6
