Metadata-Version: 1.2
Name: inscriptis
Version: 2.2.0
Summary: inscriptis - HTML to text converter.
Home-page: https://github.com/weblyzard/inscriptis
Author: Albert Weichselbraun, Fabian Odoni
Author-email: albert.weichselbraun@fhgr.ch, fabian.odoni@fhgr.ch
License: Apache 2.0
Description: ==================================================================================
        inscriptis -- HTML to text conversion library, command line client and Web service
        ==================================================================================
        
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        A python based HTML to text conversion library, command line client and Web
        service with support for **nested tables**, a **subset of CSS** and optional
        support for providing an **annotated output**. 
        
        Inscriptis is particularly well suited for applications that require high-performance, high-quality (i.e., layout-aware) text representations of HTML content, and will aid knowledge extraction and data science tasks conducted upon Web data.
        
        Please take a look at the
        `Rendering <https://github.com/weblyzard/inscriptis/blob/master/RENDERING.md>`_
        document for a demonstration of inscriptis' conversion quality.
        
        A Java port of inscriptis 1.x is available
        `here <https://github.com/x28/inscriptis-java>`_.
        
        This document provides a short introduction to Inscriptis. 
        
        - The full documentation is built automatically and published on `Read the Docs <https://inscriptis.readthedocs.org/en/latest/>`_. 
        - If you are interested in a more general overview on the topic of *text extraction from HTML*, this `blog post on different HTML to text conversion approaches, and criteria for selecting them <https://www.semanticlab.net/linux/big%20data/knowledge%20extraction/Extracting-text-from-HTML-with-Python/>`_ might be interesting to you.
        
        .. contents:: Table of contents
        
        Statement of need - why inscriptis?
        ===================================
        
        1. Inscriptis provides a **layout-aware** conversion of HTML that more closely resembles the rendering obtained from standard Web browsers and, therefore, better preserves the spatial arrangement of text elements. 
        
           Conversion quality becomes a factor once you need to move beyond simple HTML snippets. Non-specialized approaches and less sophisticated libraries do not correctly interpret HTML semantics and, therefore, fail to properly convert constructs such as itemizations, enumerations, and tables.
        
           Beautiful Soup's `get_text()` function, for example, converts the following HTML enumeration to the string ``firstsecond``.
        
           .. code-block:: HTML
           
              <ul>
                <li>first</li>
                <li>second</li>
              <ul>
        
        
           Inscriptis, in contrast, not only returns the correct output
           
           .. code-block::
           
              * first
              * second
        
           but also supports much more complex constructs such as nested tables and also interprets a subset of HTML (e.g., `align`, `valign`) and CSS (e.g., `display`, `white-space`, `margin-top`, `vertical-align`, etc.) attributes that determine the text alignment. Any time the spatial alignment of text is relevant (e.g., for many knowledge extraction tasks, the computation of word embeddings and language models, and sentiment analysis) an accurate HTML to text conversion is essential.
        
        2. Inscriptis supports `annotation rules <#annotation-rules>`_, i.e., user-provided mappings that allow for annotating the extracted text based on structural and semantic information encoded in HTML tags and attributes used for controlling structure and layout in the original HTML document. These rules might be used to
        
           - provide downstream knowledge extraction components with additional information that may be leveraged to improve their respective performance.
           - assist manual document annotation processes (e.g., for qualitative analysis or gold standard creation). ``Inscriptis`` supports multiple export formats such as XML, annotated HTML and the JSONL format that is used by the open source annotation tool `doccano <https://github.com/doccano/doccano>`_.
           - enabling the use of ``Inscriptis``  for tasks such as content extraction (i.e., extract task-specific relevant content from a Web page) which rely on information on the HTML document's structure.
        
        
        Installation
        ============
        
        At the command line::
        
            $ pip install inscriptis
        
        Or, if you don't have pip installed::
        
            $ easy_install inscriptis
        
        If you want to install from the latest sources, you can do::
        
            $ git clone https://github.com/weblyzard/inscriptis.git
            $ cd inscriptis
            $ python setup.py install
        
        
        Python library
        ==============
        
        Embedding inscriptis into your code is easy, as outlined below:
        
        .. code-block:: python
           
           import urllib.request
           from inscriptis import get_text
           
           url = "https://www.fhgr.ch"
           html = urllib.request.urlopen(url).read().decode('utf-8')
           
           text = get_text(html)
           print(text)
        
        
        Standalone command line client
        ==============================
        The command line client converts HTML files or text retrieved from Web pages to
        the corresponding text representation.
        
        
        Command line parameters
        -----------------------
        
        The inscript.py command line client supports the following parameters::
        
            usage: inscript.py [-h] [-o OUTPUT] [-e ENCODING] [-i] [-d] [-l] [-a] [-r ANNOTATION_RULES] [-p POSTPROCESSOR] [--indentation INDENTATION]
                               [--table-cell-separator TABLE_CELL_SEPARATOR] [-v]
                               [input]
        
            Convert the given HTML document to text.
        
            positional arguments:
              input                 Html input either from a file or a URL (default:stdin).
        
            optional arguments:
              -h, --help            show this help message and exit
              -o OUTPUT, --output OUTPUT
                                    Output file (default:stdout).
              -e ENCODING, --encoding ENCODING
                                    Input encoding to use (default:utf-8 for files; detected server encoding for Web URLs).
              -i, --display-image-captions
                                    Display image captions (default:false).
              -d, --deduplicate-image-captions
                                    Deduplicate image captions (default:false).
              -l, --display-link-targets
                                    Display link targets (default:false).
              -a, --display-anchor-urls
                                    Display anchor URLs (default:false).
              -r ANNOTATION_RULES, --annotation-rules ANNOTATION_RULES
                                    Path to an optional JSON file containing rules for annotating the retrieved text.
              -p POSTPROCESSOR, --postprocessor POSTPROCESSOR
                                    Optional component for postprocessing the result (html, surface, xml).
              --indentation INDENTATION
                                    How to handle indentation (extended or strict; default: extended).
              --table-cell-separator TABLE_CELL_SEPARATOR
                                    Separator to use between table cells (default: three spaces).
              -v, --version         display version information
        
           
        
        HTML to text conversion
        -----------------------
        convert the given page to text and output the result to the screen::
        
          $ inscript.py https://www.fhgr.ch
           
        convert the file to text and save the output to output.txt::
        
          $ inscript.py fhgr.html -o fhgr.txt
           
        convert HTML provided via stdin and save the output to output.txt::
        
          $ echo '<body><p>Make it so!</p></body>' | inscript.py -o output.txt 
        
        
        HTML to annotated text conversion
        ---------------------------------
        convert and annotate HTML from a Web page using the provided annotation rules. 
        
        Download the example `annotation-profile.json <https://github.com/weblyzard/inscriptis/blob/master/examples/annotation-profile.json>`_ and save it to your working directory::
        
          $ inscript.py https://www.fhgr.ch -r annotation-profile.json
        
        The annotation rules are specified in `annotation-profile.json`:
        
        .. code-block:: json
        
           {
            "h1": ["heading", "h1"],
            "h2": ["heading", "h2"],
            "b": ["emphasis"],
            "div#class=toc": ["table-of-contents"],
            "#class=FactBox": ["fact-box"],
            "#cite": ["citation"]
           }
        
        The dictionary maps an HTML tag and/or attribute to the annotations
        inscriptis should provide for them. In the example above, for instance, the tag
        `h1` yields the annotations `heading` and `h1`, a `div` tag with a
        `class` that contains the value `toc` results in the annotation
        `table-of-contents`, and all tags with a `cite` attribute are annotated with
        `citation`.
        
        Given these annotation rules the HTML file
        
        .. code-block:: HTML
        
           <h1>Chur</h1>
           <b>Chur</b> is the capital and largest town of the Swiss canton of the
           Grisons and lies in the Grisonian Rhine Valley.
        
        yields the following JSONL output
        
        .. code-block:: json
        
           {"text": "Chur\n\nChur is the capital and largest town of the Swiss canton
                     of the Grisons and lies in the Grisonian Rhine Valley.",
            "label": [[0, 4, "heading"], [0, 4, "h1"], [6, 10, "emphasis"]]}
        
        The provided list of labels contains all annotated text elements with their
        start index, end index and the assigned label.
        
        
        Annotation postprocessors
        -------------------------
        Annotation postprocessors enable the post processing of annotations to formats
        that are suitable for your particular application. Post processors can be
        specified with the `-p` or `--postprocessor` command line argument::
        
          $ inscript.py https://www.fhgr.ch \
                  -r ./examples/annotation-profile.json \
                  -p surface
        
        
        Output:
        
        .. code-block:: json
        
           {"text": "  Chur\n\n  Chur is the capital and largest town of the Swiss
                     canton of the Grisons and lies in the Grisonian Rhine Valley.",
            "label": [[0, 6, "heading"], [8, 14, "emphasis"]],
            "tag": "<heading>Chur</heading>\n\n<emphasis>Chur</emphasis> is the
                   capital and largest town of the Swiss canton of the Grisons and
                   lies in the Grisonian Rhine Valley."}
        
        
        
        Currently, inscriptis supports the following postprocessors:
        
        - surface: returns a list of mapping between the annotation's surface form and its label::
        
            [
               ['heading', 'Chur'], 
               ['emphasis': 'Chur']
            ]
        
        - xml: returns an additional annotated text version::
        
            <?xml version="1.0" encoding="UTF-8" ?>
            <heading>Chur</heading>
        
            <emphasis>Chur</emphasis> is the capital and largest town of the Swiss
            canton of the Grisons and lies in the Grisonian Rhine Valley.
        
        - html: creates an HTML file which contains the converted text and highlights all annotations as outlined below:
        
        .. figure:: https://github.com/weblyzard/inscriptis/raw/master/docs/paper/images/annotations.png
           :align: left
           :alt: Annotations extracted from the Wikipedia entry for Chur with the `--postprocess html` postprocessor.
        
           Snippet of the rendered HTML file created with the following command line options and annotation rules:
        
           .. code-block:: bash
        
              inscript.py --annotation-rules ./wikipedia.json \
                          --postprocessor html \
                          https://en.wikipedia.org/wiki/Chur.html
        
           Annotation rules encoded in the `wikipedia.json` file:
        
           .. code-block:: json
        
              {
                "h1": ["heading"],
                "h2": ["heading"],
                "h3": ["subheading"],
                "h4": ["subheading"],
                "h5": ["subheading"],
                "i": ["emphasis"],
                "b": ["bold"],
                "table": ["table"],
                "th": ["tableheading"],
                "a": ["link"]
              } 
        
        
        Web Service
        ===========
        
        The Flask Web Service translates HTML pages to the corresponding plain text.
        
        Additional Requirements
        -----------------------
        
        * python3-flask
        
        Startup
        -------
        Start the inscriptis Web service with the following command::
        
          $ export FLASK_APP="inscriptis.service.web"
          $ python3 -m flask run
        
        Usage
        -----
        
        The Web services receives the HTML file in the request body and returns the
        corresponding text. The file's encoding needs to be specified
        in the `Content-Type` header (`UTF-8` in the example below)::
        
          $ curl -X POST  -H "Content-Type: text/html; encoding=UTF8"  \
                  --data-binary @test.html  http://localhost:5000/get_text
        
        The service also supports a version call::
        
          $ curl http://localhost:5000/version
        
        
        Example annotation profiles
        ===========================
        
        The following section provides a number of example annotation profiles illustrating the use of Inscriptis' annotation support.
        The examples present the used annotation rules and an image that highlights a snippet with the annotated text on the converted web page, which has been 
        created using the HTML postprocessor as outlined in Section `annotation postprocessors <#annotation-postprocessors>`_.
        
        Wikipedia tables and table metadata
        -----------------------------------
        
        
        The following annotation rules extract tables from Wikipedia pages, and annotate table headings that are typically used to indicate column or row headings.
        
        .. code-block:: json
        
           {
              "table": ["table"],
              "th": ["tableheading"],
              "caption": ["caption"]
           }
        
        The figure below outlines an example table from Wikipedia that has been annotated using these rules.
        
        .. figure:: https://github.com/weblyzard/inscriptis/raw/master/docs/images/wikipedia-chur-table-annotation.png
           :alt: Table and table metadata annotations extracted from the Wikipedia entry for Chur.
        
        
        References to entities, missing entities and citations from Wikipedia
        ---------------------------------------------------------------------
        
        This profile extracts references to Wikipedia entities, missing entities and citations. Please note that the profile isn't perfect, since it also annotates `[ edit ]` links.
        
        .. code-block:: json
        
           {
              "a#title": ["entity"],
              "a#class=new": ["missing"],
              "class=reference": ["citation"]
           }
        
        The figure shows entities and citations that have been identified on a Wikipedia page using these rules.
        
        .. figure:: https://github.com/weblyzard/inscriptis/raw/master/docs/images/wikipedia-chur-entry-annotation.png
           :alt: Metadata on entries, missing entries and citations extracted from the Wikipedia entry for Chur.
        
        
        
        
        
        Posts and post metadata from the XDA developer forum
        ----------------------------------------------------
        
        The annotation rules below, extract posts with metadata on the post's time, user and the user's job title from the XDA developer forum.
        
        .. code-block:: json
        
           {
               "article#class=message-body": ["article"],
               "li#class=u-concealed": ["time"],
               "#itemprop=name": ["user-name"],
               "#itemprop=jobTitle": ["user-title"]
           }
        
        The figure illustrates the annotated metadata on posts from the XDA developer forum.
        
        .. figure:: https://github.com/weblyzard/inscriptis/raw/master/docs/images/xda-posts-annotation.png
           :alt: Posts and post metadata extracted from the XDA developer forum.
        
        
        
        Code and metadata from Stackoverflow pages
        ------------------------------------------
        The rules below extracts code and metadata on users and comments from Stackoverflow pages.
        
        .. code-block:: json
        
           {
              "code": ["code"],
              "#itemprop=dateCreated": ["creation-date"],
              "#class=user-details": ["user"],
              "#class=reputation-score": ["reputation"],
              "#class=comment-date": ["comment-date"],
              "#class=comment-copy": ["comment-comment"]
           }
        
        Applying these rules to a Stackoverflow page on text extraction from HTML yields the following snippet:
        
        .. figure:: https://github.com/weblyzard/inscriptis/raw/master/docs/images/stackoverflow-code-annotation.png
           :alt: Code and metadata from Stackoverflow pages.
        
        
        Advanced topics
        ===============
        
        Annotated text
        --------------
        Inscriptis can provide annotations alongside the extracted text which allows
        downstream components to draw upon semantics that have only been available in
        the original HTML file.
        
        The extracted text and annotations can be exported in different formats,
        including the popular JSONL format which is used by
        `doccano <https://github.com/doccano/doccano>`_.
        
        Example output:
        
        .. code-block:: json
        
           {"text": "Chur\n\nChur is the capital and largest town of the Swiss canton
                     of the Grisons and lies in the Grisonian Rhine Valley.",
            "label": [[0, 4, "heading"], [0, 4, "h1"], [6, 10, "emphasis"]]}
        
        The output above is produced, if inscriptis is run with the following
        annotation rules:
        
        .. code-block:: json
        
           {
            "h1": ["heading", "h1"],
            "b": ["emphasis"],
           }
        
        The code below demonstrates how inscriptis' annotation capabilities can
        be used within a program:
        
        .. code-block:: python
        
          import urllib.request
          from inscriptis import get_annotated_text, ParserConfig
        
          url = "https://www.fhgr.ch"
          html = urllib.request.urlopen(url).read().decode('utf-8')
        
          rules = {'h1': ['heading', 'h1'],
                   'h2': ['heading', 'h2'],
                   'b': ['emphasis'],
                   'table': ['table']
                  }
        
          output = get_annotated_text(html, ParserConfig(annotation_rules=rules)
          print("Text:", output['text'])
          print("Annotations:", output['label'])
        
        Fine tuning
        -----------
        
        The following options are available for fine tuning inscriptis' HTML rendering:
        
        1. **More rigorous indentation:** call `inscriptis.get_text()` with the
           parameter `indentation='extended'` to also use indentation for tags such as
           `<div>` and `<span>` that do not provide indentation in their standard
           definition. This strategy is the default in `inscript.py` and many other
           tools such as Lynx. If you do not want extended indentation you can use the
           parameter `indentation='standard'` instead.
        
        2. **Overwriting the default CSS definition:** inscriptis uses CSS definitions
           that are maintained in `inscriptis.css.CSS` for rendering HTML tags. You can
           override these definitions (and therefore change the rendering) as outlined
           below:
        
        .. code-block:: python
        
              from lxml.html import fromstring
              from inscriptis.css_profiles import CSS_PROFILES, HtmlElement
              from inscriptis.html_properties import Display
              from inscriptis.model.config import ParserConfig
              
              # create a custom CSS based on the default style sheet and change the
              # rendering of `div` and `span` elements
              css = CSS_PROFILES['strict'].copy()
              css['div'] = HtmlElement(display=Display.block, padding=2)
              css['span'] = HtmlElement(prefix=' ', suffix=' ')
              
              html_tree = fromstring(html)
              # create a parser using a custom css
              config = ParserConfig(css=css)
              parser = Inscriptis(html_tree, config)  usage: inscript.py [-h] [-o OUTPUT] [-e ENCODING] [-i] [-d] [-l] [-a] [-r ANNOTATION_RULES] [-p POSTPROCESSOR]
                             [--indentation INDENTATION] [-v]
                             [input]
        
          Convert the given HTML document to text.
        
          positional arguments:
            input                 Html input either from a file or a URL (default:stdin).
        
          optional arguments:
            -h, --help            show this help message and exit
            -o OUTPUT, --output OUTPUT
                                  Output file (default:stdout).
            -e ENCODING, --encoding ENCODING
                                  Input encoding to use (default:utf-8 for files; detected server encoding for Web URLs).
            -i, --display-image-captions
                                  Display image captions (default:false).
            -d, --deduplicate-image-captions
                                  Deduplicate image captions (default:false).
            -l, --display-link-targets
                                  Display link targets (default:false).
            -a, --display-anchor-urls
                                  Display anchor URLs (default:false).
            -r ANNOTATION_RULES, --annotation-rules ANNOTATION_RULES
                                  Path to an optional JSON file containing rules for annotating the retrieved text.
            -p POSTPROCESSOR, --postprocessor POSTPROCESSOR
                                  Optional component for postprocessing the result (html, surface, xml).
            --indentation INDENTATION
                                  How to handle indentation (extended or strict; default: extended).
            -v, --version         display version information
              text = parser.get_text()
        
        
        Citation
        ========
        
        There is a `Journal of Open Source Software <https://joss.theoj.org>`_ `paper <https://joss.theoj.org/papers/10.21105/joss.03557>`_ you can cite for Inscriptis:
        
        .. code-block:: bibtex
        
              @article{Weichselbraun2021,
                doi = {10.21105/joss.03557},
                url = {https://doi.org/10.21105/joss.03557},
                year = {2021},
                publisher = {The Open Journal},
                volume = {6},
                number = {66},
                pages = {3557},
                author = {Albert Weichselbraun},
                title = {Inscriptis - A Python-based HTML to text conversion library optimized for knowledge extraction from the Web},
                journal = {Journal of Open Source Software}
              }
        
        
        Changelog
        =========
        
        A full list of changes can be found in the
        `release notes <https://github.com/weblyzard/inscriptis/releases>`_.
        
        
Keywords: HTML,converter,text
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Topic :: Text Processing
Classifier: Topic :: Text Processing :: Markup :: HTML
Classifier: Topic :: Utilities
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
Requires-Python: >=3.6
