How to add a Publisher

Before contributing a publisher make sure you setup Fundus correctly alongside this steps. Then check the supported publishers table if there is already support for your desired publisher. In the following, we will walk you through an example implementation of the Los Angeles Times covering the best practices for adding a new publisher.

1. Creating a Parser Stub

Take a look at the file structure in fundus/publishers. Fundus uses the ALPHA-2 codes specified in ISO3166 to sort publishers into directories by country of origin. For example:

fundus/publishers/de/ for German publishers
fundus/publishers/us/ for US publishers
...

In case you don't see a directory labelled with the corresponding country code, feel free to create one. Within this directory add a file called __init__.py and create a class inheriting the PublisherEnum behaviour. As an example, if you were to add the US, it should look something like this:

from fundus.publishers.base_objects import PublisherEnum

class US(PublisherEnum):
    pass

Next, you should open the file fundus/publishers/__init__.py and make sure that the class PublisherCollection has an attribute corresponding to your newly added country:

from fundus.publishers.base_objects import PublisherCollectionMeta
from fundus.publishers.us import US

class PublisherCollection(metaclass=PublisherCollectionMeta):
    us = US

Now create an empty file in the corresponding country section using the publishers' name or some abbreviation as the file name. For the Los Angeles Times, the correct country section is fundus/publishers/us/, since they are a newspaper based in the United States, with a filename like la_times.py or los_angeles_times.py. We will continue here with la_times.py. In the newly created file, add an empty parser class inheriting from ParserProxy and a parser version V1 subclassing BaseParser.

from fundus.parser import ParserProxy, BaseParser


class LATimesParser(ParserProxy):
    class V1(BaseParser):
        pass

Internally, the ParserProxy maps crawl dates to specific versions (V1, V2, etc.) subclassing BaseParser. Since Fundus' parsers are handcrafted and usually tied to specific layouts, this proxying step helps address changes to the layout.

2. Creating a Publisher Specification

Next, add a new publisher specification for the publisher you want to cover. The publisher specification links information about the publisher, sources from where to get the HTML to parse, and the corresponding parser used by Fundus' Crawler.

You can add a new entry to the country-specific PublisherEnum in the __init__.py of the country section you want to contribute to, i.e. fundus/publishers/<country_code>/__init__.py. For now, we only specify the publisher's name, domain, and parser. We will cover sources in the next step.

For the Los Angeles Times (LA Times), we add the following entry to fundus/publishers/us/__init__.py.

class US(PublisherEnum):
    LATimes = PublisherSpec(
        name="Los Angeles Times",
        domain="https://www.latimes.com/",
        parser=LATimesParser,
    )

If the country section for your publisher did not exist before step 1, please add the PublisherEnum to the PublisherCollection in fundus/publishers/__init__.py'.

Adding Sources

For your newly added publisher to work you first need to specify where to find articles - in the form of HTML - to parse. Fundus adopts a unique approach by utilizing access points provided by the publishers, rather than resorting to generic web spiders. Publishers offer various methods to access their articles, with the most common being RSS feeds, APIs, or sitemaps. Presently, Fundus supports RSS feeds and sitemaps by adding them as corresponding URLSource using the source parameter of PublisherSpec.

Different `URLSource` types

Fundus provides the following types of URLSource, which you can import from fundus.scraping.html.

RSSFeed - specifying RSS feeds
Sitemap - specifying sitemaps
NewsMap - specifying a special kind of sitemap displaying only recent articles

Fundus distinguishes between these source types to facilitate crawling only recent articles (RSSFeed, NewsMap) or an entire website (Sitemap). This differentiation is mainly for efficiency reasons. Refer to this documentation on how to filter for different source types.

NOTE: When adding a new publisher, it is recommended to specify at least one Sitemap and one RSSFeed or NewsMap (preferred). If your publisher provides a NewsFeed, there is no need to specify an RSSFeed.

How to specify a `URLSource`

To instantiate an object inheriting from URLSource like RSSFeed or Sitemap, you first need to find a link to the corresponding feed or sitemap and then set it as the entry point using the url parameter of URLSource.

RSS feeds

Getting links for RSS feeds can vary from publisher to publisher. Most of the time, you can find them through a quick browser search. Building an RSSFeed looks like this:

from fundus import RSSFeed

RSSFeed("https://theintercept.com/feed/?rss")

Sitemaps

Sitemaps consist of a collection of <url> tags, indicating links to articles with properties attached, following a standardized schema. A typical sitemap looks like this:

<urlset ... >
   <url>
      <loc>https://www.latimes.com/recipe/peach-frozen-yogurt</loc>
      <lastmod>2020-01-29</lastmod>
   </url>
   ...

NOTE: There is a known issue with Firefox not displaying XML properly. You can find a plugin to resolve this issue here

Links to sitemaps are typically found within the robots.txt file provided by the publisher, often located at the end of it. To access this file, append robots.txt at the end of the publisher's domain. For example, to access the LA Times' robots.txt, use https://www.latimes.com/robots.txt in your preferred browser. This will give you the following two sitemap links:

Sitemap: https://www.latimes.com/sitemap.xml
Sitemap: https://www.latimes.com/news-sitemap.xml

The former refers to a regular sitemap, and the latter points to a NewsMap, which is a special kind of sitemap. To have a look at how to differentiate between those two, refer to this section.

Most Sitemaps, and sometimes NewsMaps as well, will be index maps. E.g. accessing https://www.latimes.com/news-sitemap.xml will give you something like this:

<sitemapindex ... >
   <sitemap>
      <loc>https://www.latimes.com/news-sitemap-content.xml</loc>
      <lastmod>2023-08-02T07:10-04:00</lastmod>
   </sitemap>
   ...
</sitemapindex>

The <sitemap>, and especially the <sitemapindex> tag, indicates that this is, in fact, an index map pointing to other sitemaps rather than articles. To address this, Sitemap and NewsMap will step through the given sitemap recursively by default. You can alter this behavior or reverse the order in which sitemaps are processed with the recursive respectively reverse parameters.

NOTE: If you wonder why you should reverse your sources from time to time, URLSource's should, if possible, yield URLs in descending order by publishing date.

Now building a new URLSource for a NewsMap covering the LA Times looks like this:

from fundus import NewsMap

NewsMap("https://www.latimes.com/news-sitemap.xml", reverse=True)

How to differentiate between `Sitemap` and `NewsMap`

Fundus differentiates between two types of sitemaps: Those that almost or actually span the entire site (Sitemap) and those that only reference recent articles (NewsMap), often called Google News Maps. You can check if a sitemap is a news map by:

Checking the file name: Often there is a string like news included. While this is a very simple method this can be unreliable.
Checking the namespace: Typically there is a namespace news defined within a news map using the xmlns:news attribute of the <urlset> tag. E.g. <urlset ... xmlns:news="http://www.google.com/schemas/sitemap-news/0.9" ... >
NOTE: This can only be found within the actual sitemap and not the index map.

Finishing the Publisher Specification

Sometimes sitemaps can include a lot of noise like maps pointing to a collection of tags or authors, etc. You can use the sitemap_filter parameter of Sitemap or NewsMap to prefilter these based on a regular expression. E.g.
```
Sitemap("https://apnews.com/sitemap.xml", sitemap_filter=regex_filter("apnews.com/hub/|apnews.com/video/"))
```
Will filter out all URLs encountered within the processing of the Sitemap object including either the string apnews.com/hub/ or apnews.com/video/.
If your publisher requires to use custom request headers to work properly you can alter it by using the request_header parameter of PublisherSpec. The default is: {"user_agent": "Fundus"}.
If you want to block URLs for the entire publisher use the url_filter parameter of PublisherSpec.
In some cases it can be necessary to append query parameters to the end of the URL, e.g. to load the article as one page. This can be achieved by adding the query_parameter attribute of PublisherSpec and assigning it a dictionary object containing the key - value pairs: e.g. {"page": "all"}. These key - value pairs will be appended to all crawled URLs.

Now, let's put it all together to specify the LA Times as a new publisher in Fundus:

class US(PublisherEnum):
    LATimes = PublisherSpec(
        name="Los Angeles Times",
        domain="https://www.latimes.com/",
        sources=[Sitemap("https://www.latimes.com/sitemap.xml"), 
                 NewsMap("https://www.latimes.com/news-sitemap.xml")],
        parser=LATimesParser,
    )

4. Validating the Current Implementation Progress

Now validate your implementation progress by crawling some example articles from your publisher. The following script fits the Los Angeles Times and is adaptable by changing the publisher variable accordingly.

from fundus import PublisherCollection, Crawler

# Change to:
# PublisherCollection.<country_section>.<publisher_specification>
publisher = PublisherCollection.us.LosAngelesTimes

crawler = Crawler(publisher)

for article in crawler.crawl(max_articles=2, only_complete=False):
    print(article)

If everything has been implemented correctly, the script should output text articles like the following.

Fundus-Article:
- Title: "--missing title--"
- Text:  "--missing plaintext--"
- URL:    https://www.latimes.com/sports/story/2023-06-26/100-years-los-angeles-coliseum-historical-events
- From:   Los Angeles Times
Fundus-Article:
- Title: "--missing title--"
- Text:  "--missing plaintext--"
- URL:    https://www.latimes.com/sports/sparks/story/2023-06-25/los-angeles-sparks-dallas-wings-wnba-game-analysis
- From:   Los Angeles Times

Since we didn't add any specific implementation to the parser yet, most entries are empty.

5. Implementing the Parser

Now bring your parser to life and define the attributes you want to extract.

One important caveat to consider is the type of content on a particular page. Some news outlets feature live tickers, displaying podcasts, or hub sites that link to other pages but are not articles themselves. At this stage, there's no need to concern yourself with handling non-article pages. our parser should concentrate on extracting desired attributes from most pages that can be classified as articles. Pages lacking the desired attributes will be filtered out by the library during a later phase of the processing pipeline.

You can add attributes by decorating the methods of your parser with the @attribute decorator. The expected return value for each attribute must precisely match the specifications outlined in the attribute guidelines.

For instance, if you want to extract article titles, first refer to the attribute guidelines and identify an attribute that aligns with your objective. There you can locate an attribute named title, which precisely corresponds to what you aim to extract, along with its expected return type. It is essential to adhere to the specified return types, as they are enforced through our unit tests. While you're welcome to experiment locally, contributions to the repository won't be accepted if your pull request deviates from the guidelines.

NOTE: Should you wish to add an attribute not covered in the guidelines, set the validate parameter of the attribute decorator to False, like this:

@attribute(validate=False)
def unsupported_attribute(self):
   ...

Attributes marked with validate=False will not be validated through unit tests.

Now, once we have identified the attribute we want to extract, we add it to the parser by defining a method using the associated name, in our case title, and marking it as an attribute using the @attribute decorator.

class LATimesParser(ParserProxy):
    class V1(BaseParser):

        @attribute
        def title(self) -> Optional[str]:
            return "This is a title"

To see the results of our newly added titles, we can use the following code:

for article in crawler.crawl(max_articles=2):
    print(article.title)

This should print the following output:

This is a title
This is a title

Fundus will automatically add your decorated attributes as instance attributes to the article object during parsing. Additionally, attributes defined in the attribute guidelines are explicitly defined as dataclasses.fields.

Extracting Attributes from Precomputed

One way to extract useful information from articles rather than placeholders is to utilize the ld and meta attributes of the Article. These attributes are automatically extracted when they are present in the currently parsed HTML. Often, valuable information about an article, such as the title, author, or topics, can be found in these two objects. To access them during parsing, you can use the precomputed attribute of BaseParser, which references a dataclass of type Precomputed. This object contains meta-information about the article you're currently parsing.

@dataclass
class Precomputed:
    html: str
    doc: lxml.html.HtmlElement
    meta: Dict[str, str]
    ld: LinkedData
    cache: Dict[str, Any]

Here is a brief description of the fields of Precomputed.

Precomputed Attribute	Description
html	The original fetched HTML.
doc	The root node of an `lxml.html.Etree` spanning the fetched html.
meta	The article's meta-information extracted from `<meta>` tags.
ld	The linked data extracted from the HTML's `ld+json`
cache	A cache specific to the currently parsed site, which can be used to share objects between attributes. Share objects with the `BaseParser.share` method.

For instance, to extract the title for an article in the Los Angeles Times, we can access the og:title through the attribute meta of Precomputed.

@attribute
def title(self) -> Optional[str]:
   # Use the `get` function to retrieve data from the `meta` precomputed attribute
   return self.precomputed.meta.get("og:title")

Extracting Attributes with XPath and CSS-Select

When parsing the ArticleBody, or the desired information cannot be extracted from the ld or meta attributes, you need to directly obtain information from the Document Object Model (DOM) of the HTML/XML. The DOM serves as an interface representing the underlying HTML or XML file as a tree structure, where each element (tag) of the file functions as a node in the tree. To select or search respectively for the information you need you can access these nodes using selectors like CSS-Select or XPath. Fundus relies on the Python package lxml and its selector implementation.

Working with `lxml`

Consider the following HTML example.

<html lang="de">
    <head>
        <meta charset="utf-8">
        <title>...</title>
    </head>
    <body>
        <h2>This is a heading.</h2>
        <p>This is a paragraph inside the body.</p>
        <p class="A">This is a paragraph with a class.</p>
        <div>
            <p>This is a paragraph within a div</p>    
        </div>
        <div class="B">
            <p>This is a paragraph within a div of class B</p>    
        </div>
        <p additional-attribute="not allowed">This is a paragraph with a weird attribute</p>  
    </body>
</html>

To work with lxml selectors, the initial step involves constructing an Etree, which represents the DOM of the HTML. This is achieved as follows:

root = lxml.html.document_fromstring(html)

This will return an object of type lxml.html.HtmlElement representing the root node of the DOM tree. Within the Fundus parser, the DOM tree is already generated for each article, and the root node can be accessed using the doc parameter of Precomputed. Next we will show you how to specify search conditions in the form of selectors and use them on the tree.

CSS-Select

CSS-Select is generally a simpler, but less comprehensive, selector compared to XPath. In most instances, it's advisable to use CSS-Select and resort to XPath only when necessary. To define your selector we recommend using this reference.

Here's an example of creating a selector to target all <p> tags within the tree and extracting their text content using text_content():

from lxml.cssselect import CSSSelector

selector = CSSSelector("p")
nodes = selector(root)
for node in nodes:
    print(node.text_content())

This should print the following lines:

This is a paragraph inside the body.
This is a paragraph with a class.
This is a paragraph within a div
This is a paragraph within a div of class B
This is a paragraph with a weird attribute

NOTE: The nodes are returned in depth-first pre-order.

Similarly, you can select based on the class attribute of a tag. For instance, selecting all <p> tags with class A looks like this.

selector = CSSSelector("p.A")

Which will print:

This is a paragraph with a class.

Often you need to select tags depending on their parents. To illustrate, let's select all <p> tags that have a <div> tag as their parent.

selector = CSSSelector("div > p")

Output:

This is a paragraph within a div
This is a paragraph within a div of class B

Combining these techniques, you can select all <p> tags that have a parent <div> with class B.

selector = CSSSelector("div.B > p")

Output:

This is a paragraph within a div of class B

Selectors can also target nodes with specific attribute values, even if those attributes are not standard in the HTML specification:

selector = CSSSelector("p[additional-attribute='not allowed']")

Output:

This is a paragraph with a weird attribute

NOTE: It's also possible to select solely by the existence of an attribute by omitting the equality. Sticking to the above example you can simply use CSSSelector("p[additional-attribute]") instead.

XPath

Given the complexity of XPath compared to CSS-Select, we refrain from providing an extensive tutorial here. Instead, we recommend referring to this documentation for a translation table and a concise overview of XPath functionalities beyond CSS-Select.

NOTE: Although it's possible to select nodes using the built-in methods of lxml.html.HtmlElement, it's recommended to use the dedicated selectors CSSSelect and XPath, as demonstrated in the above examples.

NOTE: The fundus/parser/utility.py module includes several utility functions that can assist you in implementing parser attributes. Make sure to examine other parsers and consult the attribute guidelines for specifics on attribute implementation. We strongly encourage utilizing these utility functions, especially when parsing the ArticleBody.

Checking the free_access attribute

In case your new publisher does not have a subscription model, you can go ahead and skip this step. If it does, please verify that there is a tag isAccessibleForFree within the HTMLs ld+json elements (refer to the section Extracting attributes from Precomputed for details) in the source code of premium articles that is set to either false or False, true/True respectively. It doesn't matter if the tag is missing in the freely accessible articles. If this is the case, you can continue with the next step. If not, please overwrite the existing function by adding the following snippet to your parser:

@attribute
def free_access(self) -> bool:
    # Your personalized logic goes here
    ...

Usually you can identify a premium article by an indicator within the URL or by using XPath or CSSSelector and selecting the element asking to purchase a subscription to view the article.

Finishing the Parser

Bringing all the above together, the Los Angeles Times now looks like this.

import datetime
from typing import List, Optional

from lxml.cssselect import CSSSelector

from fundus.parser import ArticleBody, BaseParser, ParserProxy, attribute
from fundus.parser.utility import (
    extract_article_body_with_selector,
    generic_author_parsing,
    generic_date_parsing,
)


class LATimesParser(ParserProxy):
    class V1(BaseParser):
        _paragraph_selector = CSSSelector("div[data-element*=story-body] > p")

        @attribute
        def body(self) -> ArticleBody:
            return extract_article_body_with_selector(
                self.precomputed.doc,
                paragraph_selector=self._paragraph_selector,
            )

        @attribute
        def publishing_date(self) -> Optional[datetime.datetime]:
            return generic_date_parsing(self.precomputed.ld.bf_search("datePublished"))

        @attribute
        def authors(self) -> List[str]:
            return generic_author_parsing(self.precomputed.ld.bf_search("author"))

        @attribute
        def title(self) -> Optional[str]:
            return self.precomputed.meta.get("og:title")

Now, execute the example script from step 4 to validate your implementation. If the attributes are implemented correctly, they appear in the printout accordingly.

Fundus-Article:
- Title: "One hundred years at the Coliseum: Much more than a sports venue"
- Text:  "Construction for the Los Angeles Coliseum was completed on May 1, 1923. Capacity
          at the time: 75,000. The stadium was designed by architects John [...]"
- URL:    https://www.latimes.com/sports/story/2023-06-26/100-years-los-angeles-coliseum-historical-events
- From:   Los Angeles Times (2023-06-26 12:00)
Fundus-Article:
- Title: "Sparks back at .500: Five things to know about the team after win Sunday"
- Text:  "Finally, the home crowd at Crypto.com Arena had something to cheer about.  After
          dropping the first three games of their longest homestand of the [...]"
- URL:    https://www.latimes.com/sports/sparks/story/2023-06-25/los-angeles-sparks-dallas-wings-wnba-game-analysis
- From:   Los Angeles Times (2023-06-25 21:30)

6. Generate unit tests and update tables

Add unit tests

To finish your newly added publisher you should add unit tests for the parser. We recommend you do this with the provided script.

To get started with this script, you may read the provided manual:

python -m scripts.generate_parser_test_files -h

Then in most cases it should be enough to simply run

python -m scripts.generate_parser_test_files -p <your_publisher_class>

with <your_publisher_class> being the class name of the PublisherEnum your working on.

In our case, we would run:

python -m scripts.generate_parser_test_files -p LATimes

to generate a unit test for our parser.

Update tables

To fully integrate your new publisher you have to add it to the supported publishers table. You do so by simply running

python -m scripts.generate_tables

Now to test your newly added publisher you should run pytest with the following command:

pytest

7. Opening a Pull Request

Make sure you tested your parser using pytest.
Run black src, isort src, and mypy src with no errors.
Push and open a new PR
Congratulation and thank you very much.

Provide feedback

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how_to_add_a_publisher.md

how_to_add_a_publisher.md

Table of Contents

How to add a Publisher

1. Creating a Parser Stub

2. Creating a Publisher Specification

Adding Sources

Different `URLSource` types

How to specify a `URLSource`

RSS feeds

Sitemaps

How to differentiate between `Sitemap` and `NewsMap`

Finishing the Publisher Specification

4. Validating the Current Implementation Progress

5. Implementing the Parser

Extracting Attributes from Precomputed

Extracting Attributes with XPath and CSS-Select

Working with `lxml`

CSS-Select

XPath

Checking the free_access attribute

Finishing the Parser

6. Generate unit tests and update tables

Add unit tests

Update tables

7. Opening a Pull Request

Files

how_to_add_a_publisher.md

Latest commit

History

how_to_add_a_publisher.md

File metadata and controls

Table of Contents

How to add a Publisher

1. Creating a Parser Stub

2. Creating a Publisher Specification

Adding Sources

Different URLSource types

How to specify a URLSource

RSS feeds

Sitemaps

How to differentiate between Sitemap and NewsMap

Finishing the Publisher Specification

4. Validating the Current Implementation Progress

5. Implementing the Parser

Extracting Attributes from Precomputed

Extracting Attributes with XPath and CSS-Select

Working with lxml

CSS-Select

XPath

Checking the free_access attribute

Finishing the Parser

6. Generate unit tests and update tables

Add unit tests

Update tables

7. Opening a Pull Request

Different `URLSource` types

How to specify a `URLSource`

How to differentiate between `Sitemap` and `NewsMap`

Working with `lxml`