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goskyr

Quick Start
Installation
Semi-Automatic Configuration
Manual Configuration & Usage
Build ML Model for Improved Auto-Config
Related Projects
Build & Release
Contributing
Naming
Similar Projects

This project's goal is to make it easier to scrape list-like structured data from web pages. This could be a list of books from an online book store, a list of plays in a public theater, a list of newspaper articles, etc. Currently, the biggest use-case that I know of is croncert which is also the main motivation behind this project.

Next to manually configuring the scraper there is an option of (semi-)automatically generating a configuration file, see quick start and Semi-Automatic Configuration. Machine learning can be leveraged to predict field names more or less accurately, see section Build ML Model for Improved Auto-Config.

Quick Start

https://user-images.githubusercontent.com/26999089/210244250-09a11b64-0981-40d1-8f81-9fbb00e17164.mp4

To reproduce what happens above install goskyr and then run the following steps:

Start the configuration generation. The configuration file is written to the default location config.yml. Navigation in the interactive terminal window is done with the arrow keys, the return key and the tab key.

goskyr -g https://www.imdb.com/chart/top/ -f

Note, that different colors are used to show how 'close' certain fields are to each other in the html tree. This should help when there are multiple list-like structures on a web page and you need to figure out which fields belong together.

Next, start the scraping process. The configuration file is read from the default location config.yml.

goskyr

Optionally, modify the configuration file according to your needs. For more information check out the section on manually configuring the scraper. For a better understanding of the command line flags run

goskyr -help

Note that the feature to (semi-)automatically generate a configuration file is currently in an experimental stage and might not properly work in a lot of cases.

Installation

Download a prebuilt binary from the releases page, unpack and run!

Or if you have recent go compiler installed download goskyr by running

go install github.com/jakopako/goskyr@latest

Or clone the repository and then run with go run main.go ... or build it yourself.

Semi-Automatic Configuration

As shown under Quick Start goskyr can be used to automatically extract a configuration for a given url. A number of different options are available.

-g: Pass the url you want to extract data from to this flag.
-f: Only show fields that have varying values across the list of items.
-m: The minimum number of items on a page. This is needed to filter out noise. The default is 20.
-r: Render JS before starting to extract the configuration.
--model: This option is new since v0.4.0. You can pass a reference to a ML model that suggests names for the extracted fields. Note that the model currently consists of two files that have to be named exactly the same except for the ending. The string that you have to pass to the --model flag has to be the filename without the ending. Check out the section on building a ML model.
-w: Works in combination with --model. This flag is used to pass a the name of a directory that contains a bunch of text files with dictionary words. This is needed for feature extraction for the ML stuff. This repository contains an example of such a directory, word-lists, although the lists are pretty limited. Default is word-lists.

Note that when using machine learning & a properly trained model, the auto configuration is capable of determining what fields could be a date and what date components they contain. With that information another algorithm then tries to derive the format of the date that is needed for proper parsing. So in the best case you have to do nothing more than rename some of the fields to get the desired configuration.

Note that the machine learning feature is rather new and might not always work well, especially since it only takes into account a fields value and not its position in the DOM. A basic model is contained in the ml-models directory. It uses the labels text, url and date-component-*. You could for instance run goskyr -g https://www.schuur.ch/programm/ --model ml-models/knn-types-v0.4.4 which would suggest the following fields to you.

screenshot field extraction

Manual Configuration & Usage

Despite the option to automatically generate a configuration file for goskyr there are a lot more options that can be configured manually. Note that while writing and testing a new configuration it might make sense to use the -debug flag when running goskyr, to enable more detailed logging and have the scraped html's written to files.

A very simple configuration would look something like this:

scrapers:
  - name: LifeQuotes # The name is only for logging and scraper selection (with -s) and does not appear in the json output.
    url: "https://www.goodreads.com/quotes/tag/life"
    item: ".quote"
    fields:
      - name: "quote"
        location:
          selector: ".quoteText"
      - name: "author"
        location:
          selector: ".authorOrTitle"

Save this to a file, e.g. quotes-config.yml and run goskyr -c quotes-config.yml (or go run main.go -c quotes-config.yml) to retreive the scraped quotes as json string. The result should look something like this:

[
  {
    "author": "Marilyn Monroe",
    "quote": "“I'm selfish, impatient and a little insecure. I make mistakes, I am out of control and at times hard to handle. But if you can't handle me at my worst, then you sure as hell don't deserve me at my best.”"
  },
  {
    "author": "William W. Purkey",
    "quote": "“You've gotta dance like there's nobody watching,"
  },
  ...
]

A more complex configuration might look like this:

scrapers:
  - name: Kaufleuten
    url: "https://kaufleuten.ch/events/kultur/konzerte/"
    item: ".event"
    fields:
      - name: "location"
        value: "Kaufleuten"
      - name: "city"
        value: "Zurich"
      - name: "type"
        value: "concert"
      - name: "title"
        location:
          selector: "h3"
          regex_extract:
            exp: "[^•]*"
            index: 0
      - name: "comment"
        can_be_empty: true
        location:
          selector: ".subtitle strong"
      - name: "url"
        type: "url"
        location:
          selector: ".event-link"
      - name: "date"
        type: "date"
        on_subpage: "url"
        components:
          - covers:
              day: true
              month: true
              year: true
              time: true
            location:
              selector: ".event-meta time"
              attr: "datetime"
            layout: ["2006-01-02T15:04:05-07:00"]
        date_location: "Europe/Berlin"
    filters:
      - field: "title"
        exp: "Verschoben.*"
        match: false
      - field: "title"
        exp: "Abgesagt.*"
        match: false

The result should look something like this:

[
  {
    "city": "Zurich",
    "comment": "Der Schweizer Singer-Songwriter, mit Gitarre und bekannten sowie neuen Songs",
    "date": "2022-03-09T19:00:00+01:00",
    "location": "Kaufleuten",
    "title": "Bastian Baker",
    "type": "concert",
    "url": "https://kaufleuten.ch/event/bastian-baker/"
  },
  {
    "city": "Zurich",
    "comment": "Der kanadische Elektro-Star meldet sich mit neuem Album zurück",
    "date": "2022-03-13T19:00:00+01:00",
    "location": "Kaufleuten",
    "title": "Caribou",
    "type": "concert",
    "url": "https://kaufleuten.ch/event/caribou/"
  },
  ...
]

Basically, a config file contains a list of scrapers that each may have static and / or dynamic fields. Additionally, items can be filtered based on regular expressions and pagination is also supported. The resulting array of items is written to stdout or a file, as json string.

Static fields

Each scraper can define a number of static fields. Those fields are the same over all returned items. For the event scraping use case this might be the location name as shown in the example above. For a static field only a name and a value need to be defined:

fields:
  - name: "location"
    value: "Kaufleuten"

Dynamic fields

Dynamic fields are a little more complex as their values are extracted from the webpage and can have different types. In the most trivial case it suffices to define a field name and a selector so the scraper knows where to look for the corresponding value. The quotes scraper is a good example for that:

fields:
  - name: "quote"
    type: "text" # defaults to 'text' if ommited
    location:
      selector: ".quoteText"

A dynamic field can have one of the following three types: text, url or date. The following table shows which options are available for which type.

Option	Type `text`	Type `url`	Type `date`	Default value
can_be_empty	X	X		`false`
components			X	`[]`
date_language			X	`"de_DE"`
date_location			X	`"UTC"`
default	X	X		`""`
guess_year			X	`false`
hide	X	X	X	`false`
location	X	X		`[]`
name	X	X	X	`""`
on_subpage	X	X	X	`""`
separator	X			`""`
transform	X		X (date components)	`[]`
type	X	X	X	`"text"`

Options explained

can_be_empty

If set to false, an error message will be printed for each item where this field is missing (i.e. the html node does not exist or the corresponding string is empty) and the correspondig item will not be included in the resulting list of items. If set to true there won't be an error message and the corresponding value will be an empty string.

components

This key contains the configuration for the different date components that are needed to extract a valid date. A list of the following form needs to be defined.

components:
  - covers: # what part of the date is covered by the element located at 'location'?
      day: bool # optional
      month: bool # optional
      year: bool # optional
      time: bool # optional
    location: # the location has the same configuration as explained under option 'location' with the exception that it is not a list but just a single location configuration.
      selector: "<selector>"
      ...
    layout: ["<layout>"] # a list of layouts that apply to this date component. Needs to be configured the "golang-way" and always in English.
  - covers:
      ...

The following example should give you a better idea how such the definition of components might actually look like.

components:
  - covers:
      day: true
    location:
      selector: ".commingupEventsList_block2"
    layout: ["02. "]
  - covers:
      month: true
    location:
      selector: ".commingupEventsList_block3"
    layout: ["January"]
  - covers:
      time: true
    location:
      selector: ".commingupEventsList_block4"
    layout: ["15Uhr04"]

For more details about the layout check out this link or have a look at the numerous examples in the concerts-config.yml. Also note that mostly the layout list only contains one element. Only in rare cases where different events on the same site have different layouts it is necessary to define more than one layout.

date_language

The date_language needs to correspond to the language on the website. Note, that this doesn't matter for dates that only contain numbers. The values that are supported are the ones supported by the underlying library, goodsign/monday.

date_location

date_location sets the time zone of the respective date.

default

If no value is found on the website the field's value defaults to this default.

guess_year

If set to false and no date component is defined that covers the year, the year of the resulting date defaults to the current year. If set to true and no date component is defined that covers the year, goskyr will try to be 'smart' in guessing the year. This helps if a scraped list of dates covers more than one year and/or scraped dates are not within the current year but the next. Note that there are definitely some cases where this year guessing does not yet work.

hide

This option determines whether a field should be exlcuded from the resulting items. This can be handy when you want to filter based on a field that you don't want to include in the actual items. For more information on filters checkout the Filters section below.

location

There are two options on how to use the location key. Either you define a bunch of subkeys directly under location or you define a list of items each containing those subkeys. The latter is useful if you want the value of a field to be juxtaposition of multiple nodes in the html tree. The separator option will be used to join the strings. A very simple (imaginary) example could look something like this.

fields:
  - name: artist
    location:
      - selector: div.artist
      - selector: div.country
    separator: ", "

The result may look like this.

[...
{"artist": "Jacob Collier, UK"},
...]

Subkey: regex_extract

In some cases, it might be a bit more complex to extract the desired information. Take for instance the concert scraper configuration for "Kaufleuten", shown above, more specifically the config snippet for the title field.

fields:
  - name: "title"
    location:
      selector: "h3"
      regex_extract:
        exp: "[^•]*"
        index: 0

This field is implicitly of type text. The location tells the scraper where to look for the field value and how to extract it. In this case the selector on its own would not be enough to extract the desired value as we would get something like this: Bastian Baker • Konzert. That's why there is an extra option to define a regular expression to extract a substring. Note that in this example our extracted string would still contain a trailing space which is automatically removed by the scraper. Let's have a look at a few more examples to have a better understanding of the location configuration.

Subkey: child_index

Next, let's say we want to extract the time "20h00" from the following html snippet.

<div class="col-sm-8 col-xs-12">
  <h3>Freitag, 25. Feb 2022</h3>

  <h2>
    <a href="/events/924"
      ><strong>Jacob Lee (AUS) - Verschoben</strong>
      <!--(USA)-->
    </a>
  </h2>
  <q>Singer & Songwriter</q>

  <p><strong>+ Support</strong></p>
  <i
    ><strong>Doors</strong> : 19h00 /
    <strong>Show</strong>
    : 20h00
  </i>
</div>

This can be achieved with the following configuration:

location:
  selector: ".col-sm-8 i"
  child_index: 3
  regex_extract:
    exp: "[0-9]{2}h[0-9]{2}"

Here, the selector is not enough to extract the desired string and we can't go further down the tree by using different selectors. With the child_index we can point to the exact string we want. A child_index of 0 would point to the first <strong> node, a child_index of 1 would point to the string containing "19h00", a child_index of 2 would point to the second <strong> node and finally a child_index of 3 points to the correct string. If child_index is set to -1 the first child that results in a regex match will be used. This can be useful if the child_index varies across different items. In the current example however, the child_index is always the same but the string still contains more stuff than we need which is why we use a regular expression to extract the desired substring.

Subkey: entire_subtree

This subkey, if set to true causes goskyr to grab all text elements under the element defined in the location's selector. It is useful when the target location contains inline tags, eg. This is some text with a <strong>strong</strong> part.

Subkey: all_nodes

This subkey, if set to true joins together all strings having the given selector. The subkey separator will be used as separator string. If not defined the separator is an empty string. Example:

<div class="header">
  <h3 class="artist"><span class="name">Anja Schneider</span><span class="artist-info"></h3>
  <h3 class="artist"><span class="name">Steve Bug</span><span class="artist-info"></h3>
  <h3 class="artist"><span class="name">Dirty Flav</span><span class="artist-info">&nbsp;(WAD, D! Club - CH)</h3>
</div>

Config:

fields:
  - name: title
    location:
      selector: .artist .name
      all_nodes: true
      separator: ", "

Resulting json:

[...
{"title": "Anja Schneider, Steve Bug, Dirty Flav"},
...]

To get an even better feeling for the location configuration check out the numerous examples in the concerts-config.yml file.

Subkey: json_selector

If the string extracted from the webpage is a json string, then you can extract data from that json based on the give json_selector.

name

The name of the respective field.

on_subpage

If set to the name of another scraped field of type url, goskyr will fetch the corresponding page and extract the desired data from that page.

separator

This option is only relevant if the location option contains a list of locations of length > 1. If it does, the extracted strings (1 per location) will be joined using the defined separator.

transform

This option allows you to transform extracted text and date components. Currently, the only transform type is regex-replace. As the name suggests, this type allows you to replace a substring that matches the given regular expression with a user defined string. An example usage of this option would be as follows.

- name: title
  type: text
  location:
    - selector: div.event-info.single-day:nth-child(2) > div.event-title > h3 > a
  transform:
    - type: regex-replace
      regex: regex.*
      replace: New value

Note, that the transform can also be used for date components, eg.

- name: date
  type: date
  components:
    - covers:
        day: true
        month: true
      location:
        selector: div.col-12.col-md-3 > div.g-0.row > div.col-sm-12.p-0 > div.rhp-event-thumb > a.url > div.eventDateListTop > div.eventMonth.mb-0.singleEventDate.text-uppercase
      layout:
        - Mon, January 2
        - Mon, Jan 2
      transform:
        - type: regex-replace
          regex: Sept
          replace: Sep

type

This is the type of the field. As mentioned above its value can be text, url or date.

For a field of type text the value that is being extracted from the webpage based on the defined location will simply be assigned to the value of the corresponding field in the output.

If a field has type url, the resulting value in the output will allways be a full, valid url, meaning that it will contain protocol, hostname, path and query parameters. If the webpage does not provide this, goskyr will 'autocomplete' the url like a browser would. E.g. if a webpage, https://event-venue.com, contains <a href="/events/10-03-2023-krachstock-final-story" > and we would have a field of type url that extracts this url from the href attribute the resulting value would be https://event-venue.com/events/10-03-2023-krachstock-final-story. Also, the location.attr field is implicetly set to "href" if not defined by the user.

A date field is different from a text field in that the result is a complete, valid date. Internally, this is a time.Time object but in the json output it is represented by a string in RFC3339 format. In order to be able to handle a lot of different cases where date information might be spread across different locations, might be formatted in different ways using different languages a date field has a list of components and some other optional settings, see table above.

As can be seen, a component has to define which part of the date it covers (at least one part has to be covered). Next, the location of this component has to be defined. This is done the same way as we defined the location for a text field string. Finally, we need to define a list of possible layouts where each layout is defined the 'go-way' as this scraper is written in go. For more details check out this link or have a look at the numerous examples in the concerts-config.yml file. Note that a layout string is always in English although the date string on the scraped website might be in a different language. Also note that mostly the layout list only contains one element. Only in rare cases where different events on the same site have different layouts it is necessary to define more than one layout.

The date_language key needs to correspond to the language on the website. Currently, the default is de_DE. Note, that this doesn't matter for dates that only contain numbers. date_location sets the time zone of the respective date.

JS rendering

Since version 0.3.0 js rendering is supported. For this to work the google-chrome binary needs to be installed. In the configuration snippet of a scraper just add render_js: true and everything will be taken care of. With page_load_wait: <milliseconds> the default waiting time of 2000 ms can be adapted accordingly.

User interactions with the page (eg scrolling) might be implemented in the future. Clicking has been implemented, see below section Interaction.

Filters

Filters can be used to define what items should make it into the resulting list of items. A filter configuration can look as follows:

filters:
  - field: "status"
    exp: "cancelled"
    match: false
  - field: "status"
    exp: ".*(?i)(delayed).*"
    match: false
  - field: "date"
    exp: "> now" # format: <|> now|YYYY-MM-ddTHH:mm
    match: true

The field key determines to which field the expression will be applied. exp defines the expression and match determines whether the item should be included or excluded on match. Note, that as soon as there is one match for an expression that has match set to false the respective item will be excluded from the results without looking at the other filters.

The expression exp can be either a regular expression or a date comparison. Depending on the type of the respective field in the fields section of the configuration it has to be either one or the other. If the corresponding field is of type date the expression has to be a date comparison. For every other field type it has to be a regular expression.

Interaction

If a dynamic webpage does initially not load all the items it might be necessary to click some kind of 'load more' button. This can be configured as follows:

interaction:
  type: click # for now only click is supported.
  selector: .some > div.selector
  count: 1 # number of clicks. Default is 1
  delay: 2000 # milliseconds that the scraper waits after each click. Default is 1000

Note that these clicks are executed before the data is scraped. Also the interaction configuration will be ignored if render_js is not set to true because only in that case is the website actually run within a headless browser.

Pagination

If the list of items on a web page spans multiple pages pagination can be configured as follows:

paginator:
  location:
    selector: ".pagination .selector"

In case render_js is set to false by default the value of the href key is taken as url for the next page. However, you can change this and other parameters in the paginator configuration.

paginator:
  location:
    selector: ".pagination .selector"
    attr: <string>
  max_pages: <number>

If render_js is set to true the scraper will simulate a mouse click on the given selector to loop over the pages.

Output

Currently, the scraped data can either be written to stdout or to a file. If you don't explicitely configure the output in the configuration file the data is written to stdout. Otherwise you have to add the following snippet to your configuration file.

writer:
  type: file
  filepath: test-file.json

Build ML Model for Improved Auto-Config

In order for the auto configuration feature to find suitable names for the extracted fields, since v0.4.0 machine learning can be used. Goskyr allows you to extract a fixed set of features based on an existing goskyr configuration. Basically, goskyr scrapes all the websites you configured, extracts the raw text values based on the configured fields per site and then calculates the features for each extracted value, labeling the resulting vector with the field name you defined in the configuration. Currently, all features are based on the extracted text only, i.e. not on the location within the website. Checkout the Features struct in the ml/ml.go file if you want to know what exactly those features are. Extraction command:

goskyr -e features.csv -w word-lists -c some-goskyr-config.yml

Note that -w and -c are optional. The respective defaults are word-lists and config.yml. The resulting csv file can optionally be edited (eg if you want to remove or replace some labels) and consequently be used to build a ML model, like so:

goskyr -t features.csv

Currently, a KNN classifier is used. The output of the above command shows the result of the training. Additionally, two files are generated, goskyr.model and goskyr.class. Both together define the model that can be used for labeling fields during auto configuration, see Semi-Automatic Configuration.

Note that the classification will probably get better the more data you have to extract your features from. Also there might very well be cases where even a huge number of training data doesn't improve the classification results. This entire ML feature is rather experimental for now and time will tell how well it works and what needs to be improved or changed.

A real life example can be found in the jakopako/croncert-config repository.

Related Projects

The main motivation to start this project was a website idea that I wanted to implement. Currently, there are four repositories involved in this idea. The first one is of course this one, goskyr. The other three are:

croncert-web: a website that shows concerts in your area, deployed to concertcloud.live.
croncert-config: a repository that contains a big configuration file for goskyr, where all the concert venue websites that are part of concertcloud.live are configured. If you're interested, check out this repository to find out how to add new concert locations and to make yourself more familiar with how to use goskyr.
event-api: an API to store and fetch concert info, that serves as backend for concertcloud.live.

Build & Release

To build and release a new version of goskyr Goreleaser is used, also see Quick Start.

Make a "dry-run" release to see if it works using the release command:

make release-dry-run

Make sure you have a file called .release-env containing the github token.

GITHUB_TOKEN=YOUR_GH_TOKEN

Create a tag and push it to GitHub

git tag -a v0.1.5 -m "new features"
git push origin v0.1.5

Run GoReleaser at the root of this repository:

make release

Contributing

Feel free to contribute in any way you want! Help is always welcome.

Naming

Go Scraper > Go Scr > Go Skyr > goskyr

Similar Projects

There are similar projects that might do a better job in certain cases or are more generic tools. However, on the one hand this is a personal project to make myself familiar with webscraping and Go and on the other hand goskyr supports certain features that I haven't found in any other projects. For instance, the way dates can be extracted from websites, the notion of scraping information from subpages defined by previously at runtime extracted urls and how a website's structure can be automatically detected to decrease manual configuration effort.

Similar projects: