Update wiki, wikibooks, wikisource (#87)

- Updated wiki, wikibooks, wikisource. (455c42b5f0afebf3803e6f7ffb455eff571e4ba7)
- Renamed wiki to wikipedia (154f222309459bef9a9e8d4675e7ef56dd638f56)
- Fixed rounding error in average tokens (a0053a7604c8fcae20ba45fd82ce71004e2e60db)
- Renamed wiki to wikipedia (12c0ca93c6898f3d4f4c8cbc88881ba73af57f6f)
- Improved token count (2a9b93c9c8a6caa932675681fd1a59f7220989b7)
- Fixed logging issues. (914ab8dfe209489ab09c14517ff18d3782566fff)
- Updated changelog to reflect new changes (0bd2b88ea6c556f47e07432cd6291eda5a9dc9b8)
- Adding explanation for the use of `wtf_wikipedia` as parser. (077726d1e73b4912d4b623020277019b06dddbdf)

.gitignore

@@ -20,3 +20,6 @@ tmp.py
 
 ## to allow temporary data drops without pushing it to the hub
 data/*/tmp/*
+
+## node_modules
+**/node_modules/

CHANGELOG.md

@@ -5,6 +5,18 @@ All notable changes to this project will be documented in this file.
 
 The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
+## [v1.2.10] - 2025-08-18
+
+### Changed
+
+- Updated the wiki, wikibooks, wikisource datasets. 
+- Changed `wiki` to `wikipedia`
+- Fixed rounding error in average token count
+- Improved the speed of token counting
+
+### Added 
+
+- Added `create.py` for wiki, wikibooks, wikisource.
 
 ## [v1.2.9] - 2025-08-05
 

README.md

@@ -152,10 +152,10 @@ configs:
   data_files:
   - split: train
     path: data/synne/*.parquet
-- config_name: wiki
+- config_name: wikipedia
   data_files:
   - split: train
-    path: data/wiki/*.parquet
+    path: data/wikipedia/*.parquet
 - config_name: nordjyllandnews
   data_files:
   - split: train
@@ -194,7 +194,7 @@ https://github.com/huggingface/datasets/blob/main/templates/README_guide.md
 <!-- START README TABLE -->
 |              |                                                                                                                                                             |
 | ------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| **Version**  | 1.2.8 ([Changelog](/CHANGELOG.md))                                                                                                                          |
+| **Version** | 1.2.10 ([Changelog](/CHANGELOG.md)) |
 | **Language** | dan, dansk, Danish                                                                                                                                          |
 | **License**  | Openly Licensed, See the respective dataset                                                                                                                 |
 | **Models**   | For model trained used this data see [danish-foundation-models](https://huggingface.co/danish-foundation-models)                                            |
@@ -233,8 +233,8 @@ https://github.com/huggingface/datasets/blob/main/templates/README_guide.md
 ## Dataset Description
 
 <!-- START-DESC-STATS -->
-- **Number of samples**: 5.55M
-- **Number of tokens (Llama 3)**: 5.83B
+- **Number of samples**: 5.60M
+- **Number of tokens (Llama 3)**: 5.88B
 - **Average document length in tokens (min, max)**: 1.05K (2, 9.81M)
 <!-- END-DESC-STATS -->
 
@@ -299,16 +299,16 @@ This dynaword consist of data from various domains (e.g., legal, books, social m
 |:-------------|:---------------------------------------------------------------------------------------------------------|:------------|
 | Legal        | [cellar], [eur-lex-sum-da], [fm-udgivelser], [retsinformationdk], [skat], [retspraksis], [domsdatabasen] | 2.32B       |
 | News         | [enevaeldens_nyheder], [ncc_newspaper], [tv2r], [nordjyllandnews]                                        | 1.09B       |
-| Books        | [grundtvig], [ncc_books], [memo], [adl], [wikibooks], [jvj], [gutenberg], [relig]                        | 732.52M     |
+| Books        | [grundtvig], [ncc_books], [memo], [adl], [wikibooks], [jvj], [gutenberg], [relig]                        | 733.92M     |
 | Conversation | [danske-taler], [opensubtitles], [ep], [ft], [spont], [naat]                                             | 497.09M     |
 | Social Media | [hest]                                                                                                   | 389.32M     |
 | Other        | [ncc_parliament], [dannet], [depbank], [synne]                                                           | 340.59M     |
 | Web          | [ai-aktindsigt], [ncc_maalfrid], [miljoeportalen]                                                        | 295.87M     |
-| Encyclopedic | [wikisource], [wiki]                                                                                     | 127.35M     |
+| Encyclopedic | [wikisource], [wikipedia]                                                                                | 179.61M     |
 | Medical      | [health_hovedstaden]                                                                                     | 27.07M      |
 | Readaloud    | [nota]                                                                                                   | 7.30M       |
 | Dialect      | [botxt]                                                                                                  | 847.97K     |
-| **Total**    |                                                                                                          | 5.83B       |
+| **Total**    |                                                                                                          | 5.88B       |
 
 [ai-aktindsigt]: data/ai-aktindsigt/ai-aktindsigt.md
 [cellar]: data/cellar/cellar.md
@@ -342,7 +342,7 @@ This dynaword consist of data from various domains (e.g., legal, books, social m
 [depbank]: data/depbank/depbank.md
 [naat]: data/naat/naat.md
 [synne]: data/synne/synne.md
-[wiki]: data/wiki/wiki.md
+[wikipedia]: data/wikipedia/wikipedia.md
 [nordjyllandnews]: data/nordjyllandnews/nordjyllandnews.md
 [relig]: data/relig/relig.md
 [nota]: data/nota/nota.md
@@ -369,13 +369,13 @@ The following gives an overview of the licensing in the Dynaword. To get the exa
 These license is applied to the constituent data, i.e., the text. The collection of datasets (metadata, quality control, etc.) is licensed under [CC-0](https://creativecommons.org/publicdomain/zero/1.0/legalcode.en).
 
 <!-- START-LICENSE TABLE -->
-| License                         | Sources                                                                                                                                                                                                                                                                        | N. Tokens   |
-|:--------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------|
-| CC-BY-SA 4.0                    | [cellar], [enevaeldens_nyheder], [eur-lex-sum-da], [fm-udgivelser], [memo], [tv2r], [jvj], [depbank]                                                                                                                                                                           | 2.41B       |
-| CC-0                            | [grundtvig], [danske-taler], [ncc_books], [ncc_newspaper], [miljoeportalen], [opensubtitles], [ep], [ft], [wikisource], [spont], [adl], [hest], [skat], [retspraksis], [wikibooks], [botxt], [naat], [synne], [wiki], [nordjyllandnews], [relig], [nota], [health_hovedstaden] | 2.00B       |
-| Other (No attribution required) | [retsinformationdk], [domsdatabasen]                                                                                                                                                                                                                                           | 904.61M     |
-| Other (Attribution required)    | [ai-aktindsigt], [ncc_maalfrid], [ncc_parliament], [dannet], [gutenberg]                                                                                                                                                                                                       | 515.61M     |
-| **Total**                       |                                                                                                                                                                                                                                                                                | 5.83B       |
+| License                         | Sources                                                                                                                                                                                                                                                                             | N. Tokens   |
+|:--------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------|
+| CC-BY-SA 4.0                    | [cellar], [enevaeldens_nyheder], [eur-lex-sum-da], [fm-udgivelser], [memo], [tv2r], [jvj], [depbank]                                                                                                                                                                                | 2.41B       |
+| CC-0                            | [grundtvig], [danske-taler], [ncc_books], [ncc_newspaper], [miljoeportalen], [opensubtitles], [ep], [ft], [wikisource], [spont], [adl], [hest], [skat], [retspraksis], [wikibooks], [botxt], [naat], [synne], [wikipedia], [nordjyllandnews], [relig], [nota], [health_hovedstaden] | 2.06B       |
+| Other (No attribution required) | [retsinformationdk], [domsdatabasen]                                                                                                                                                                                                                                                | 904.61M     |
+| Other (Attribution required)    | [ai-aktindsigt], [ncc_maalfrid], [ncc_parliament], [dannet], [gutenberg]                                                                                                                                                                                                            | 515.61M     |
+| **Total**                       |                                                                                                                                                                                                                                                                                     | 5.88B       |
 
 [ai-aktindsigt]: data/ai-aktindsigt/ai-aktindsigt.md
 [cellar]: data/cellar/cellar.md
@@ -409,7 +409,7 @@ These license is applied to the constituent data, i.e., the text. The collection
 [depbank]: data/depbank/depbank.md
 [naat]: data/naat/naat.md
 [synne]: data/synne/synne.md
-[wiki]: data/wiki/wiki.md
+[wikipedia]: data/wikipedia/wikipedia.md
 [nordjyllandnews]: data/nordjyllandnews/nordjyllandnews.md
 [relig]: data/relig/relig.md
 [nota]: data/nota/nota.md
@@ -487,10 +487,10 @@ You can learn more about each dataset by pressing the link in the first column.
 | [hest]                | Samples from the Danish debate forum www.heste-nettet.dk                                                                                                                               | Social Media | 389.32M     | [CC-0]                 |
 | [ncc_parliament]      | Collections from the Norwegian parliament in Danish. Extracted from the [Norwegian Colossal Corpus](https://huggingface.co/datasets/NbAiLab/NCC) derived from ocr                      | Other        | 338.87M     | [NLOD 2.0]             |
 | [opensubtitles]       | Danish subsection of [OpenSubtitles](https://opus.nlpl.eu/OpenSubtitles/corpus/version/OpenSubtitles)                                                                                  | Conversation | 271.60M     | [CC-0]                 |
+| [wikipedia]           | The Danish subsection of [wikipedia](https://en.wikipedia.org/wiki/Main_Page)                                                                                                          | Encyclopedic | 173.33M     | [CC-0]                 |
 | [ai-aktindsigt]       | Multiple web scrapes from municipality websites collected as a part of the [AI-aktindsigt](https://ai-aktindsigt.dk) project                                                           | Web          | 139.23M     | [Apache 2.0]           |
 | [miljoeportalen]      | Data from [Danmarks Miljøportalen](https://www.miljoeportal.dk/om-danmarks-miljoeportal/) (Denmark's Environment Portal)                                                               | Web          | 127.38M     | [CC-0]                 |
 | [skat]                | Skat is the Danish tax authority. This dataset contains content from its website skat.dk                                                                                               | Legal        | 122.11M     | [CC-0]                 |
-| [wiki]                | The Danish subsection of [wikipedia](https://en.wikipedia.org/wiki/Main_Page)                                                                                                          | Encyclopedic | 122.00M     | [CC-0]                 |
 | [ft]                  | Records from all meetings of The Danish parliament (Folketinget) in the parliament hall                                                                                                | Conversation | 114.09M     | [CC-0]                 |
 | [memo]                | The MeMo corpus comprising almost all Danish novels from the period 1870-1899, known as the Modern Breakthrough                                                                        | Books        | 113.74M     | [CC-BY-SA 4.0]         |
 | [ep]                  | The Danish subsection of [Europarl](https://aclanthology.org/2005.mtsummit-papers.11/)                                                                                                 | Conversation | 100.84M     | [CC-0]                 |
@@ -505,10 +505,10 @@ You can learn more about each dataset by pressing the link in the first column.
 | [tv2r]                | Contemporary Danish newswire articles published between 2010 and 2019                                                                                                                  | News         | 21.67M      | [CC-BY-SA 4.0]         |
 | [grundtvig]           | The complete collection of [Grundtvig](https://en.wikipedia.org/wiki/N._F._S._Grundtvig) (1783-1872) one of Denmark’s most influential figures                                         | Books        | 10.53M      | [CC-0]                 |
 | [danske-taler]        | Danish Speeches from [dansketaler.dk](https://www.dansketaler.dk)                                                                                                                      | Conversation | 8.72M       | [CC-0]                 |
+| [wikibooks]           | The Danish Subsection of [Wikibooks](https://www.wikibooks.org)                                                                                                                        | Books        | 7.63M       | [CC-0]                 |
 | [nota]                | The text only part of the [Nota lyd- og tekstdata](https://sprogteknologi.dk/dataset/nota-lyd-og-tekstdata) dataset                                                                    | Readaloud    | 7.30M       | [CC-0]                 |
 | [gutenberg]           | The Danish subsection from Project [Gutenberg](https://www.gutenberg.org)                                                                                                              | Books        | 6.76M       | [Gutenberg]            |
-| [wikibooks]           | The Danish Subsection of [Wikibooks](https://www.wikibooks.org)                                                                                                                        | Books        | 6.24M       | [CC-0]                 |
-| [wikisource]          | The Danish subsection of [Wikisource](https://en.wikisource.org/wiki/Main_Page)                                                                                                        | Encyclopedic | 5.34M       | [CC-0]                 |
+| [wikisource]          | The Danish subsection of [Wikisource](https://en.wikisource.org/wiki/Main_Page)                                                                                                        | Encyclopedic | 6.28M       | [CC-0]                 |
 | [jvj]                 | The works of the Danish author and poet, [Johannes V. Jensen](https://da.wikipedia.org/wiki/Johannes_V._Jensen)                                                                        | Books        | 3.55M       | [CC-BY-SA 4.0]         |
 | [spont]               | Conversational samples collected as a part of research projects at Aarhus University                                                                                                   | Conversation | 1.56M       | [CC-0]                 |
 | [dannet]              | [DanNet](https://cst.ku.dk/projekter/dannet) is a Danish WordNet                                                                                                                       | Other        | 1.48M       | [DanNet 1.0]           |
@@ -518,7 +518,7 @@ You can learn more about each dataset by pressing the link in the first column.
 | [naat]                | Danish speeches from 1930-2022                                                                                                                                                         | Conversation | 286.68K     | [CC-0]                 |
 | [depbank]             | The Danish subsection of the [Universal Dependencies Treebank](https://github.com/UniversalDependencies/UD_Danish-DDT)                                                                 | Other        | 185.45K     | [CC-BY-SA 4.0]         |
 | [synne]               | Dataset collected from [synnejysk forening's website](https://www.synnejysk.dk), covering the Danish dialect sønderjysk                                                                | Other        | 52.02K      | [CC-0]                 |
-| **Total**             |                                                                                                                                                                                        |              | 5.83B       |                        |
+| **Total**             |                                                                                                                                                                                        |              | 5.88B       |                        |
 
 [ai-aktindsigt]: data/ai-aktindsigt/ai-aktindsigt.md
 [cellar]: data/cellar/cellar.md
@@ -552,7 +552,7 @@ You can learn more about each dataset by pressing the link in the first column.
 [depbank]: data/depbank/depbank.md
 [naat]: data/naat/naat.md
 [synne]: data/synne/synne.md
-[wiki]: data/wiki/wiki.md
+[wikipedia]: data/wikipedia/wikipedia.md
 [nordjyllandnews]: data/nordjyllandnews/nordjyllandnews.md
 [relig]: data/relig/relig.md
 [nota]: data/nota/nota.md

data/wiki/descriptive_stats.json

@@ -1,9 +0,0 @@
-{
-  "number_of_samples": 264433,
-  "number_of_tokens": 122002149,
-  "min_length_tokens": 3,
-  "max_length_tokens": 83123,
-  "number_of_characters": 366763808,
-  "min_length_characters": 5,
-  "max_length_characters": 247835
-}

data/wikibooks/create.py

@@ -0,0 +1,254 @@
+# /// script
+# requires-python = ">=3.12"
+# dependencies = [
+#     "datasets",
+#     "mediawiki-dump",
+#     "mwparserfromhell",
+#     "pandas",
+#     "requests",
+#     "tqdm",
+#     "transformers",
+#     "dynaword"
+# ]
+# [tool.uv.sources]
+# dynaword = { git = "https://huggingface.co/datasets/danish-foundation-models/danish-dynaword", rev = "00e7f2aee7f7ad2da423419f77ecbb9c0536de0d" }
+# ///
+import bz2
+import datetime
+import json
+import logging
+import os
+import re
+import subprocess
+import sys
+import threading
+
+from mediawiki_dump.dumps import IteratorDump
+from mediawiki_dump.reader import DumpReaderArticles
+
+from mwparserfromhell import parse
+
+import requests
+from tqdm import tqdm
+import pandas as pd
+
+from datasets import Dataset
+from transformers import AutoTokenizer
+from concurrent.futures import ProcessPoolExecutor
+from functools import partial
+from typing import Any, Tuple
+
+from dynaword.process_dataset import (
+    add_token_count,
+    ensure_column_order,
+    remove_duplicate_text,
+    remove_empty_texts,
+)
+
+logger = logging.getLogger(__name__)
+logging.basicConfig(
+    level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
+)
+source = "wikibooks"
+
+
+class WtfNodeBridge:
+    """
+    Persistent Node bridge to wtf_wikipedia.
+    Call .parse(wikitext, lang=None) -> (text, is_redirect)
+    Remember to call .close() when done.
+    """
+
+    def __init__(
+        self, node_script_path: str = "parser/wtf_bridge.js", node_cmd: str = "node"
+    ):
+        self.proc = subprocess.Popen(
+            [node_cmd, node_script_path],
+            stdin=subprocess.PIPE,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.PIPE,
+            text=True,
+            encoding="utf-8",
+            bufsize=1,
+        )
+        self._lock = threading.Lock()
+
+        # background thread to log stderr (helpful for debugging)
+        def _drain_stderr(p):
+            try:
+                for line in p.stderr:
+                    logger.warning("wtf_node stderr: %s", line.rstrip())
+            except Exception:
+                pass
+
+        t = threading.Thread(target=_drain_stderr, args=(self.proc,), daemon=True)
+        t.start()
+
+    def parse(self, wikitext: str, lang: str | None = None) -> Tuple[str, bool]:
+        if self.proc.poll() is not None:
+            raise RuntimeError("Node bridge process has exited")
+        payload = {"wikitext": wikitext}
+        if lang:
+            payload["lang"] = lang
+        line = json.dumps(payload, ensure_ascii=False)
+        with self._lock:
+            # write and flush a single JSON line
+            try:
+                self.proc.stdin.write(line + "\n")
+                self.proc.stdin.flush()
+            except BrokenPipeError as e:
+                raise RuntimeError("Broken pipe writing to node bridge") from e
+
+            # read exactly one JSON line back
+            out_line = self.proc.stdout.readline()
+            if not out_line:
+                raise RuntimeError("No response from node bridge (it may have exited)")
+            res = json.loads(out_line)
+            if res.get("error"):
+                # choose to either raise or return empty text; here we raise
+                raise RuntimeError("Node bridge error: " + res["error"])
+            return res.get("text", ""), bool(res.get("isRedirect", False))
+
+    def close(self):
+        try:
+            if self.proc.stdin:
+                self.proc.stdin.close()
+        except Exception:
+            pass
+        try:
+            self.proc.terminate()
+            self.proc.wait(timeout=3)
+        except Exception:
+            try:
+                self.proc.kill()
+            except Exception:
+                pass
+
+
+def download_wiki_dump(url: str, file_path: str):
+    """
+    Downloads a file from a URL with a progress bar.
+
+    Args:
+        url (str): The URL of the file to download.
+        file_path (str): The local path to save the file.
+    """
+    print(f"Downloading {url} to {file_path}...")
+    try:
+        with requests.get(url, stream=True) as r:
+            r.raise_for_status()
+            total_size = int(r.headers.get("content-length", 0))
+            block_size = 8192  # 8 Kibibytes
+
+            with (
+                open(file_path, "wb") as f,
+                tqdm(
+                    total=total_size, unit="B", unit_scale=True, desc="Downloading"
+                ) as pbar,
+            ):
+                for chunk in r.iter_content(chunk_size=block_size):
+                    if chunk:  # filter out keep-alive chunks
+                        f.write(chunk)
+                        pbar.update(len(chunk))
+        logger.info("\nDownload complete.")
+    except requests.exceptions.RequestException as e:
+        logger.error(f"\nError downloading file: {e}")
+        sys.exit(1)
+
+
+def get_content(file_name: str):
+    with bz2.open(file_name, mode="r") as fp:
+        yield from fp
+
+
+def process_dump_to_parquet(bz2_file_path: str, parquet_file_path: str):
+    dump = IteratorDump(iterator=get_content(file_name=bz2_file_path))
+    pages = DumpReaderArticles().read(dump)
+    articles = []
+    today = datetime.datetime.now().strftime("%Y-%m-%d")
+
+    bridge = WtfNodeBridge("parser/wtf_bridge.js")
+    try:
+        for page in tqdm(pages):
+            try:
+                plain_text, is_redirect = bridge.parse(page.content, lang="da")
+            except Exception as exc:
+                logger.warning(
+                    "wtf parse failed for page %s: %s -- falling back to mwparserfromhell",
+                    getattr(page, "title", "<unknown>"),
+                    exc,
+                )
+                plain_text = parse(page.content).strip_code().strip()
+                is_redirect = plain_text.startswith("REDIRECT")
+
+            if is_redirect:
+                continue
+
+            # Additional cleanup if you like (wtf.text() already removes a lot)
+            plain_text = re.sub(
+                r"thumb(?:\|(?:left|right|center|\d+px)*)*\|[^\n]*", "", plain_text
+            ).strip()
+
+            if len(plain_text) == 0:
+                logger.warning("Skipping empty article")
+                continue
+
+            date = datetime.datetime.strptime(
+                page.timestamp, "%Y-%m-%dT%H:%M:%SZ"
+            ).strftime("%Y-%m-%d")
+
+            articles.append(
+                {
+                    "id": f"{source}_{page.page_id}",
+                    "source": source,
+                    "created": f"{date}, {date}",
+                    "text": f"{page.title}\n{plain_text}",
+                    "added": today,
+                }
+            )
+    finally:
+        bridge.close()
+
+    df = pd.DataFrame(articles)
+    ds = Dataset.from_pandas(df)
+    ds = add_token_count(ds)
+    ds = remove_empty_texts(ds)
+    ds = remove_duplicate_text(ds)
+    ds = ensure_column_order(ds)
+    ds.to_parquet(parquet_file_path, compression="snappy")
+
+
+def main():
+    """
+    Main function to orchestrate the download and processing.
+    """
+    # --- Configuration ---
+    # URL for the latest Danish Wikipedia articles dump
+    WIKI_DUMP_URL = f"https://dumps.wikimedia.org/da{source}/latest/da{source}-latest-pages-articles.xml.bz2"
+
+    # Local file paths
+    DOWNLOADED_BZ2_FILE = f"tmp/da{source}-latest-pages-articles.xml.bz2"
+    OUTPUT_PARQUET_FILE = f"{source}.parquet"
+
+    # --- Execution ---
+    # 1. Download the dump file
+    if not os.path.exists(DOWNLOADED_BZ2_FILE):
+        download_wiki_dump(WIKI_DUMP_URL, DOWNLOADED_BZ2_FILE)
+    else:
+        print(f"File '{DOWNLOADED_BZ2_FILE}' already exists. Skipping download.")
+
+    # 2. Process the dump and save to Parquet
+    process_dump_to_parquet(DOWNLOADED_BZ2_FILE, OUTPUT_PARQUET_FILE)
+
+    # 3. (Optional) Clean up the downloaded file
+    # If you want to keep the bz2 file, comment out the next line.
+    print(f"Cleaning up by removing '{DOWNLOADED_BZ2_FILE}'...")
+    os.remove(DOWNLOADED_BZ2_FILE)
+
+    print("\nScript finished successfully.")
+
+
+if __name__ == "__main__":
+    # Before running, make sure you have the required libraries installed:
+    # pip install requests mwparserfromhell pandas pyarrow
+    main()

data/wikibooks/descriptive_stats.json

@@ -1,9 +1,9 @@
 {
-  "number_of_samples": 1268,
-  "number_of_tokens": 6237322,
-  "min_length_tokens": 4,
-  "max_length_tokens": 365886,
-  "number_of_characters": 17525790,
-  "min_length_characters": 6,
-  "max_length_characters": 1007458
+  "number_of_samples": 1734,
+  "number_of_tokens": 7632997,
+  "min_length_tokens": 8,
+  "max_length_tokens": 368880,
+  "number_of_characters": 21572592,
+  "min_length_characters": 21,
+  "max_length_characters": 1019370
 }

data/wikibooks/parser/package-lock.json

@@ -0,0 +1,724 @@
+{
+  "name": "parser",
+  "version": "1.0.0",
+  "lockfileVersion": 3,
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+      "license": "BSD-2-Clause"
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+      "dependencies": {
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+      "license": "MIT",
+      "dependencies": {
+        "isomorphic-unfetch": "^3.1.0",
+        "path-exists-cli": "2.0.0"
+      },
+      "bin": {
+        "wtf_wikipedia": "cli.js"
+      },
+      "engines": {
+        "node": ">=12.0.0"
+      }
+    },
+    "node_modules/yallist": {
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+      "license": "ISC"
+    },
+    "node_modules/yargs-parser": {
+      "version": "20.2.9",
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+      "license": "ISC",
+      "engines": {
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+      }
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+    "node_modules/yocto-queue": {
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+      "license": "MIT",
+      "engines": {
+        "node": ">=10"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/sindresorhus"
+      }
+    }
+  }
+}

data/wikibooks/parser/package.json

@@ -0,0 +1,16 @@
+{
+  "name": "parser",
+  "version": "1.0.0",
+  "description": "",
+  "main": "index.js",
+  "scripts": {
+    "test": "echo \"Error: no test specified\" && exit 1"
+  },
+  "keywords": [],
+  "author": "",
+  "license": "ISC",
+  "type": "commonjs",
+  "dependencies": {
+    "wtf_wikipedia": "^10.4.0"
+  }
+}

data/wikibooks/parser/wtf_bridge.js

@@ -0,0 +1,39 @@
+// wtf_bridge.js
+// Usage: node wtf_bridge.js
+// Reads newline-delimited JSON from stdin: {"wikitext":"...","lang":"da"}
+// Writes newline-delimited JSON to stdout: {"text":"...","isRedirect":false} or {"error":"..."}
+const wtf = require('wtf_wikipedia');
+const readline = require('readline');
+
+const rl = readline.createInterface({
+  input: process.stdin,
+  output: process.stdout,
+  terminal: false
+});
+
+process.on('uncaughtException', (err) => {
+  // emit as JSON so Python can see it
+  try {
+    process.stdout.write(JSON.stringify({ error: String(err && err.stack || err) }) + '\n');
+  } catch (e) {}
+  process.exit(1);
+});
+
+rl.on('line', (line) => {
+  (async () => {
+    try {
+      const payload = JSON.parse(line);
+      const wikitext = payload.wikitext || '';
+      const lang = payload.lang || null;
+
+      // parse wikitext into a document (sync)
+      const doc = lang ? wtf(wikitext, lang) : wtf(wikitext);
+      const text = (doc && typeof doc.text === 'function') ? doc.text() : '';
+      const isRedirect = (doc && typeof doc.isRedirect === 'function') ? doc.isRedirect() : false;
+
+      process.stdout.write(JSON.stringify({ text, isRedirect }) + '\n');
+    } catch (err) {
+      process.stdout.write(JSON.stringify({ error: String(err && err.stack || err) }) + '\n');
+    }
+  })();
+});

data/wikibooks/wikibooks.md

@@ -28,9 +28,9 @@ The Danish Subsection of [Wikibooks](https://www.wikibooks.org).
 
 
 <!-- START-DESC-STATS -->
-- **Number of samples**: 1.27K
-- **Number of tokens (Llama 3)**: 6.24M
-- **Average document length in tokens (min, max)**: 4.92K (4, 365.89K)
+- **Number of samples**: 1.73K
+- **Number of tokens (Llama 3)**: 7.63M
+- **Average document length in tokens (min, max)**: 4.40K (8, 368.88K)
 <!-- END-DESC-STATS -->
 
 
@@ -42,12 +42,12 @@ An example from the dataset looks as follows.
 <!-- START-SAMPLE -->
 ```py
 {
-  "id": "wikibooks_1125",
-  "text": "Spilinfo.\nSpillet er lavet af Blizzard Entertainment.\nDet er efterfølgeren til Diablo 1, og der er k[...]",
+  "id": "wikibooks_7",
+  "text": "Boghylde:Hobbies\nHobbies er alle de aktiviteter vi giver os ud i, uden at forvente et afkast ud over[...]",
   "source": "wikibooks",
-  "added": "2021-03-28",
-  "created": "2019-01-01, 2021-01-01",
-  "token_count": 937
+  "added": "2025-08-18",
+  "created": "2006-06-20, 2006-06-20",
+  "token_count": 95
 }
 ```
 
@@ -73,6 +73,20 @@ An entry in the dataset consists of the following fields:
 <!-- END-DATASET PLOTS -->
 
 
+### Processing
+
+For this dataset we have pulled the latest [database dump from wikimedia](https://dumps.wikimedia.org/dawikibooks/latest/) and extracted the texts using the [wtf_wikipedia](https://github.com/spencermountain/wtf_wikipedia/tree/dev) parser. 
+
+Because the parser is written in javascript you need to have Node.js installed on you machine. 
+
+To run the `create.py` file you first need to do:
+
+```bash
+$ cd parser/ && npm install && cd ..
+```
+
+We chose to use `wtf_wikipedia` because out of the other parsers we tested this was the imperically best one. We tested `mwparserfromhell`, `mediawiki_dump`, `wikiextractor`, and `wtf_wikipedia`. It seemed that the others still produced some sort of artifacts from the parsing of wikicode.
+
 ## Additional Information
 
 

data/wikibooks/wikibooks.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ff6360814c2c5c432995416956ecd6e716f104e4a5d867afae2ce9e4f1f59c36
-size 11267762
+oid sha256:143ce3ed06be9e576d9e0a35eb674595bb835cee162e84884d3c9f45c34dab40
+size 13481948

data/wikipedia/create.py

@@ -0,0 +1,259 @@
+# /// script
+# requires-python = ">=3.12"
+# dependencies = [
+#     "datasets",
+#     "mediawiki-dump",
+#     "mwparserfromhell",
+#     "pandas",
+#     "requests",
+#     "tqdm",
+#     "transformers",
+#     "dynaword"
+# ]
+# [tool.uv.sources]
+# dynaword = { git = "https://huggingface.co/datasets/danish-foundation-models/danish-dynaword", rev = "00e7f2aee7f7ad2da423419f77ecbb9c0536de0d" }
+# ///
+import bz2
+import datetime
+import json
+import logging
+import os
+from pathlib import Path
+import re
+import subprocess
+import sys
+import threading
+
+from mediawiki_dump.dumps import IteratorDump
+from mediawiki_dump.reader import DumpReaderArticles
+
+from mwparserfromhell import parse
+
+import requests
+from tqdm import tqdm
+import pandas as pd
+
+from datasets import Dataset
+from transformers import AutoTokenizer
+from concurrent.futures import ProcessPoolExecutor
+from functools import partial
+from typing import Any, Tuple
+
+from dynaword.process_dataset import (
+    add_token_count,
+    ensure_column_order,
+    remove_duplicate_text,
+    remove_empty_texts,
+)
+
+logger = logging.getLogger(__name__)
+source = "wiki"
+
+
+class WtfNodeBridge:
+    """
+    Persistent Node bridge to wtf_wikipedia.
+    Call .parse(wikitext, lang=None) -> (text, is_redirect)
+    Remember to call .close() when done.
+    """
+
+    def __init__(
+        self, node_script_path: str = "parser/wtf_bridge.js", node_cmd: str = "node"
+    ):
+        self.proc = subprocess.Popen(
+            [node_cmd, node_script_path],
+            stdin=subprocess.PIPE,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.PIPE,
+            text=True,
+            encoding="utf-8",
+            bufsize=1,
+        )
+        self._lock = threading.Lock()
+
+        # background thread to log stderr (helpful for debugging)
+        def _drain_stderr(p):
+            try:
+                for line in p.stderr:
+                    logger.warning("wtf_node stderr: %s", line.rstrip())
+            except Exception:
+                pass
+
+        t = threading.Thread(target=_drain_stderr, args=(self.proc,), daemon=True)
+        t.start()
+
+    def parse(self, wikitext: str, lang: str | None = None) -> Tuple[str, bool]:
+        if self.proc.poll() is not None:
+            raise RuntimeError("Node bridge process has exited")
+        payload = {"wikitext": wikitext}
+        if lang:
+            payload["lang"] = lang
+        line = json.dumps(payload, ensure_ascii=False)
+        with self._lock:
+            # write and flush a single JSON line
+            try:
+                self.proc.stdin.write(line + "\n")
+                self.proc.stdin.flush()
+            except BrokenPipeError as e:
+                raise RuntimeError("Broken pipe writing to node bridge") from e
+
+            # read exactly one JSON line back
+            out_line = self.proc.stdout.readline()
+            if not out_line:
+                raise RuntimeError("No response from node bridge (it may have exited)")
+            res = json.loads(out_line)
+            if res.get("error"):
+                # choose to either raise or return empty text; here we raise
+                raise RuntimeError("Node bridge error: " + res["error"])
+            return res.get("text", ""), bool(res.get("isRedirect", False))
+
+    def close(self):
+        try:
+            if self.proc.stdin:
+                self.proc.stdin.close()
+        except Exception:
+            pass
+        try:
+            self.proc.terminate()
+            self.proc.wait(timeout=3)
+        except Exception:
+            try:
+                self.proc.kill()
+            except Exception:
+                pass
+
+
+def download_wiki_dump(url: str, file_path: str):
+    """
+    Downloads a file from a URL with a progress bar.
+
+    Args:
+        url (str): The URL of the file to download.
+        file_path (str): The local path to save the file.
+    """
+    print(f"Downloading {url} to {file_path}...")
+    try:
+        with requests.get(url, stream=True) as r:
+            r.raise_for_status()
+            total_size = int(r.headers.get("content-length", 0))
+            block_size = 8192  # 8 Kibibytes
+
+            with (
+                open(file_path, "wb") as f,
+                tqdm(
+                    total=total_size, unit="B", unit_scale=True, desc="Downloading"
+                ) as pbar,
+            ):
+                for chunk in r.iter_content(chunk_size=block_size):
+                    if chunk:  # filter out keep-alive chunks
+                        f.write(chunk)
+                        pbar.update(len(chunk))
+        logger.info("\nDownload complete.")
+    except requests.exceptions.RequestException as e:
+        logger.error(f"\nError downloading file: {e}")
+        sys.exit(1)
+
+
+def get_content(file_name: str):
+    with bz2.open(file_name, mode="r") as fp:
+        yield from fp
+
+
+def process_dump_to_parquet(bz2_file_path: str, parquet_file_path: str):
+    dump = IteratorDump(iterator=get_content(file_name=bz2_file_path))
+    pages = DumpReaderArticles().read(dump)
+    articles = []
+    today = datetime.datetime.now().strftime("%Y-%m-%d")
+
+    bridge = WtfNodeBridge("parser/wtf_bridge.js")
+    try:
+        for page in tqdm(pages):
+            try:
+                plain_text, is_redirect = bridge.parse(page.content, lang="da")
+            except Exception as exc:
+                logger.warning(
+                    "wtf parse failed for page %s: %s -- falling back to mwparserfromhell",
+                    getattr(page, "title", "<unknown>"),
+                    exc,
+                )
+                plain_text = parse(page.content).strip_code().strip()
+                is_redirect = plain_text.startswith("REDIRECT")
+
+            if is_redirect:
+                continue
+
+            # Additional cleanup if you like (wtf.text() already removes a lot)
+            plain_text = re.sub(
+                r"thumb(?:\|(?:left|right|center|\d+px)*)*\|[^\n]*", "", plain_text
+            ).strip()
+
+            if len(plain_text) == 0:
+                logger.warning("Skipping empty article")
+                continue
+
+            date = datetime.datetime.strptime(
+                page.timestamp, "%Y-%m-%dT%H:%M:%SZ"
+            ).strftime("%Y-%m-%d")
+
+            articles.append(
+                {
+                    "id": f"{source}_{page.page_id}",
+                    "source": source,
+                    "created": f"{date}, {date}",
+                    "text": f"{page.title}\n{plain_text}",
+                    "added": today,
+                }
+            )
+    finally:
+        bridge.close()
+
+    df = pd.DataFrame(articles)
+    ds = Dataset.from_pandas(df)
+    ds = add_token_count(ds)
+    ds = remove_empty_texts(ds)
+    ds = remove_duplicate_text(ds)
+    ds = ensure_column_order(ds)
+    ds.to_parquet(parquet_file_path, compression="snappy")
+
+
+def main():
+    """
+    Main function to orchestrate the download and processing.
+    """
+    # --- Configuration ---
+    # URL for the latest Danish Wikipedia articles dump
+    WIKI_DUMP_URL = f"https://dumps.wikimedia.org/da{source}/latest/da{source}-latest-pages-articles.xml.bz2"
+
+    # Local file paths
+    DOWNLOADED_BZ2_FILE = f"tmp/da{source}-latest-pages-articles.xml.bz2"
+    OUTPUT_PARQUET_FILE = f"wikipedia.parquet"
+
+    # --- Execution ---
+    # 1. Download the dump file
+    if not os.path.exists(DOWNLOADED_BZ2_FILE):
+        download_wiki_dump(WIKI_DUMP_URL, DOWNLOADED_BZ2_FILE)
+    else:
+        logger.info(f"File '{DOWNLOADED_BZ2_FILE}' already exists. Skipping download.")
+
+    # 2. Process the dump and save to Parquet
+    process_dump_to_parquet(DOWNLOADED_BZ2_FILE, OUTPUT_PARQUET_FILE)
+
+    # 3. (Optional) Clean up the downloaded file
+    # If you want to keep the bz2 file, comment out the next line.
+    logger.info(f"Cleaning up by removing '{DOWNLOADED_BZ2_FILE}'...")
+    os.remove(DOWNLOADED_BZ2_FILE)
+
+    logger.info("\nScript finished successfully.")
+
+
+if __name__ == "__main__":
+    log_path = Path(__file__).parent / f"{source}.log"
+    logging.basicConfig(
+        level=logging.INFO,
+        format="%(asctime)s - %(levelname)s - %(message)s",
+        handlers=[
+            logging.StreamHandler(),
+            logging.FileHandler(log_path),
+        ],
+    )
+    main()

data/wikipedia/descriptive_stats.json

@@ -0,0 +1,9 @@
+{
+  "number_of_samples": 309641,
+  "number_of_tokens": 173334040,
+  "min_length_tokens": 8,
+  "max_length_tokens": 107351,
+  "number_of_characters": 518132934,
+  "min_length_characters": 13,
+  "max_length_characters": 321469
+}

data/wikipedia/parser/package-lock.json

@@ -0,0 +1,724 @@
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+  "version": "1.0.0",
+  "lockfileVersion": 3,
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+      "version": "1.0.0",
+      "license": "ISC",
+      "dependencies": {
+        "wtf_wikipedia": "^10.4.0"
+      }
+    },
+    "node_modules/@babel/code-frame": {
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+      "license": "MIT",
+      "dependencies": {
+        "@babel/helper-validator-identifier": "^7.27.1",
+        "js-tokens": "^4.0.0",
+        "picocolors": "^1.1.1"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/helper-validator-identifier": {
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+      "license": "MIT",
+      "engines": {
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+    "node_modules/@types/minimist": {
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+}

data/wikipedia/parser/package.json

@@ -0,0 +1,16 @@
+{
+  "name": "parser",
+  "version": "1.0.0",
+  "description": "",
+  "main": "index.js",
+  "scripts": {
+    "test": "echo \"Error: no test specified\" && exit 1"
+  },
+  "keywords": [],
+  "author": "",
+  "license": "ISC",
+  "type": "commonjs",
+  "dependencies": {
+    "wtf_wikipedia": "^10.4.0"
+  }
+}

data/wikipedia/parser/wtf_bridge.js

@@ -0,0 +1,39 @@
+// wtf_bridge.js
+// Usage: node wtf_bridge.js
+// Reads newline-delimited JSON from stdin: {"wikitext":"...","lang":"da"}
+// Writes newline-delimited JSON to stdout: {"text":"...","isRedirect":false} or {"error":"..."}
+const wtf = require('wtf_wikipedia');
+const readline = require('readline');
+
+const rl = readline.createInterface({
+  input: process.stdin,
+  output: process.stdout,
+  terminal: false
+});
+
+process.on('uncaughtException', (err) => {
+  // emit as JSON so Python can see it
+  try {
+    process.stdout.write(JSON.stringify({ error: String(err && err.stack || err) }) + '\n');
+  } catch (e) {}
+  process.exit(1);
+});
+
+rl.on('line', (line) => {
+  (async () => {
+    try {
+      const payload = JSON.parse(line);
+      const wikitext = payload.wikitext || '';
+      const lang = payload.lang || null;
+
+      // parse wikitext into a document (sync)
+      const doc = lang ? wtf(wikitext, lang) : wtf(wikitext);
+      const text = (doc && typeof doc.text === 'function') ? doc.text() : '';
+      const isRedirect = (doc && typeof doc.isRedirect === 'function') ? doc.isRedirect() : false;
+
+      process.stdout.write(JSON.stringify({ text, isRedirect }) + '\n');
+    } catch (err) {
+      process.stdout.write(JSON.stringify({ error: String(err && err.stack || err) }) + '\n');
+    }
+  })();
+});

data/wikipedia/wiki.log

@@ -0,0 +1,5 @@
+2025-08-18 19:13:08,960 - INFO - Parsing XML dump...
+2025-08-18 19:13:09,118 - WARNING - Skipping empty article
+2025-08-18 19:13:11,361 - WARNING - Skipping empty article
+2025-08-18 19:13:12,764 - WARNING - Skipping empty article
+2025-08-18 19:13:13,945 - WARNING - Skipping empty article

data/{wiki/wiki.md → wikipedia/wikipedia.md}

@@ -30,9 +30,9 @@ You can read more about wikipedia on their [about](https://en.wikipedia.org/wiki
 
 
 <!-- START-DESC-STATS -->
-- **Number of samples**: 264.43K
-- **Number of tokens (Llama 3)**: 122.00M
-- **Average document length in tokens (min, max)**: 461.372631252529 (3, 83.12K)
+- **Number of samples**: 309.64K
+- **Number of tokens (Llama 3)**: 173.33M
+- **Average document length in tokens (min, max)**: 559.79 (8, 107.35K)
 <!-- END-DESC-STATS -->
 
 
@@ -44,12 +44,12 @@ An example from the dataset looks as follows.
 <!-- START-SAMPLE -->
 ```py
 {
-  "id": "wiki_366127",
-  "text": "Vimoutiers er en kommune i departementet Orne i Basse-Normandie regionen i det nordvestlige Frankrig[...]",
+  "id": "wiki_2",
+  "text": "Arkæologi\nArkæologi er studiet af tidligere tiders menneskelige aktivitet, primært gennem studiet af[...]",
   "source": "wiki",
-  "added": "2021-03-28",
-  "created": "2019-01-01, 2021-01-01",
-  "token_count": 126
+  "added": "2025-08-18",
+  "created": "2024-06-16, 2024-06-16",
+  "token_count": 3380
 }
 ```
 
@@ -74,6 +74,21 @@ An entry in the dataset consists of the following fields:
 <!-- END-DATASET PLOTS -->
 
 
+### Processing
+
+For this dataset we have pulled the latest [database dump from wikimedia](https://dumps.wikimedia.org/dawiki/latest/) and extracted the texts using the [wtf_wikipedia](https://github.com/spencermountain/wtf_wikipedia/tree/dev) parser. 
+
+
+
+Because the parser is written in javascript you need to have Node.js installed on you machine. 
+
+To run the `create.py` file you first need to do:
+
+```bash
+$ cd parser/ && npm install && cd ..
+```
+
+We chose to use `wtf_wikipedia` because out of the other parsers we tested this was the imperically best one. We tested `mwparserfromhell`, `mediawiki_dump`, `wikiextractor`, and `wtf_wikipedia`. It seemed that the others still produced some sort of artifacts from the parsing of wikicode.
 
 ## Additional Information
 

data/{wiki/wiki.parquet → wikipedia/wikipedia.parquet}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b141c49429bbdca99ee7edc21f5cf2065935cbd0d7b342fae62ea8c305f6d901
-size 242613795
+oid sha256:d0a8f27f66a761017e155b7820366227cd75566379aa755611f53e9299ed8717
+size 318870452

data/wikisource/create.py

@@ -0,0 +1,254 @@
+# /// script
+# requires-python = ">=3.12"
+# dependencies = [
+#     "datasets",
+#     "mediawiki-dump",
+#     "mwparserfromhell",
+#     "pandas",
+#     "requests",
+#     "tqdm",
+#     "transformers",
+#     "dynaword"
+# ]
+# [tool.uv.sources]
+# dynaword = { git = "https://huggingface.co/datasets/danish-foundation-models/danish-dynaword", rev = "00e7f2aee7f7ad2da423419f77ecbb9c0536de0d" }
+# ///
+import bz2
+import datetime
+import json
+import logging
+import os
+import re
+import subprocess
+import sys
+import threading
+
+from mediawiki_dump.dumps import IteratorDump
+from mediawiki_dump.reader import DumpReaderArticles
+
+from mwparserfromhell import parse
+
+import requests
+from tqdm import tqdm
+import pandas as pd
+
+from datasets import Dataset
+from transformers import AutoTokenizer
+from concurrent.futures import ProcessPoolExecutor
+from functools import partial
+from typing import Any, Tuple
+
+from dynaword.process_dataset import (
+    add_token_count,
+    ensure_column_order,
+    remove_duplicate_text,
+    remove_empty_texts,
+)
+
+logger = logging.getLogger(__name__)
+logging.basicConfig(
+    level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
+)
+source = "wikisource"
+
+
+class WtfNodeBridge:
+    """
+    Persistent Node bridge to wtf_wikipedia.
+    Call .parse(wikitext, lang=None) -> (text, is_redirect)
+    Remember to call .close() when done.
+    """
+
+    def __init__(
+        self, node_script_path: str = "parser/wtf_bridge.js", node_cmd: str = "node"
+    ):
+        self.proc = subprocess.Popen(
+            [node_cmd, node_script_path],
+            stdin=subprocess.PIPE,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.PIPE,
+            text=True,
+            encoding="utf-8",
+            bufsize=1,
+        )
+        self._lock = threading.Lock()
+
+        # background thread to log stderr (helpful for debugging)
+        def _drain_stderr(p):
+            try:
+                for line in p.stderr:
+                    logger.warning("wtf_node stderr: %s", line.rstrip())
+            except Exception:
+                pass
+
+        t = threading.Thread(target=_drain_stderr, args=(self.proc,), daemon=True)
+        t.start()
+
+    def parse(self, wikitext: str, lang: str | None = None) -> Tuple[str, bool]:
+        if self.proc.poll() is not None:
+            raise RuntimeError("Node bridge process has exited")
+        payload = {"wikitext": wikitext}
+        if lang:
+            payload["lang"] = lang
+        line = json.dumps(payload, ensure_ascii=False)
+        with self._lock:
+            # write and flush a single JSON line
+            try:
+                self.proc.stdin.write(line + "\n")
+                self.proc.stdin.flush()
+            except BrokenPipeError as e:
+                raise RuntimeError("Broken pipe writing to node bridge") from e
+
+            # read exactly one JSON line back
+            out_line = self.proc.stdout.readline()
+            if not out_line:
+                raise RuntimeError("No response from node bridge (it may have exited)")
+            res = json.loads(out_line)
+            if res.get("error"):
+                # choose to either raise or return empty text; here we raise
+                raise RuntimeError("Node bridge error: " + res["error"])
+            return res.get("text", ""), bool(res.get("isRedirect", False))
+
+    def close(self):
+        try:
+            if self.proc.stdin:
+                self.proc.stdin.close()
+        except Exception:
+            pass
+        try:
+            self.proc.terminate()
+            self.proc.wait(timeout=3)
+        except Exception:
+            try:
+                self.proc.kill()
+            except Exception:
+                pass
+
+
+def download_wiki_dump(url: str, file_path: str):
+    """
+    Downloads a file from a URL with a progress bar.
+
+    Args:
+        url (str): The URL of the file to download.
+        file_path (str): The local path to save the file.
+    """
+    print(f"Downloading {url} to {file_path}...")
+    try:
+        with requests.get(url, stream=True) as r:
+            r.raise_for_status()
+            total_size = int(r.headers.get("content-length", 0))
+            block_size = 8192  # 8 Kibibytes
+
+            with (
+                open(file_path, "wb") as f,
+                tqdm(
+                    total=total_size, unit="B", unit_scale=True, desc="Downloading"
+                ) as pbar,
+            ):
+                for chunk in r.iter_content(chunk_size=block_size):
+                    if chunk:  # filter out keep-alive chunks
+                        f.write(chunk)
+                        pbar.update(len(chunk))
+        logger.info("\nDownload complete.")
+    except requests.exceptions.RequestException as e:
+        logger.error(f"\nError downloading file: {e}")
+        sys.exit(1)
+
+
+def get_content(file_name: str):
+    with bz2.open(file_name, mode="r") as fp:
+        yield from fp
+
+
+def process_dump_to_parquet(bz2_file_path: str, parquet_file_path: str):
+    dump = IteratorDump(iterator=get_content(file_name=bz2_file_path))
+    pages = DumpReaderArticles().read(dump)
+    articles = []
+    today = datetime.datetime.now().strftime("%Y-%m-%d")
+
+    bridge = WtfNodeBridge("parser/wtf_bridge.js")
+    try:
+        for page in tqdm(pages):
+            try:
+                plain_text, is_redirect = bridge.parse(page.content, lang="da")
+            except Exception as exc:
+                logger.warning(
+                    "wtf parse failed for page %s: %s -- falling back to mwparserfromhell",
+                    getattr(page, "title", "<unknown>"),
+                    exc,
+                )
+                plain_text = parse(page.content).strip_code().strip()
+                is_redirect = plain_text.startswith("REDIRECT")
+
+            if is_redirect:
+                continue
+
+            # Additional cleanup if you like (wtf.text() already removes a lot)
+            plain_text = re.sub(
+                r"thumb(?:\|(?:left|right|center|\d+px)*)*\|[^\n]*", "", plain_text
+            ).strip()
+
+            if len(plain_text) == 0:
+                logger.warning("Skipping empty article")
+                continue
+
+            date = datetime.datetime.strptime(
+                page.timestamp, "%Y-%m-%dT%H:%M:%SZ"
+            ).strftime("%Y-%m-%d")
+
+            articles.append(
+                {
+                    "id": f"{source}_{page.page_id}",
+                    "source": source,
+                    "created": f"{date}, {date}",
+                    "text": f"{page.title}\n{plain_text}",
+                    "added": today,
+                }
+            )
+    finally:
+        bridge.close()
+
+    df = pd.DataFrame(articles)
+    ds = Dataset.from_pandas(df)
+    ds = add_token_count(ds)
+    ds = remove_empty_texts(ds)
+    ds = remove_duplicate_text(ds)
+    ds = ensure_column_order(ds)
+    ds.to_parquet(parquet_file_path, compression="snappy")
+
+
+def main():
+    """
+    Main function to orchestrate the download and processing.
+    """
+    # --- Configuration ---
+    # URL for the latest Danish Wikipedia articles dump
+    WIKI_DUMP_URL = f"https://dumps.wikimedia.org/da{source}/latest/da{source}-latest-pages-articles.xml.bz2"
+
+    # Local file paths
+    DOWNLOADED_BZ2_FILE = f"tmp/da{source}-latest-pages-articles.xml.bz2"
+    OUTPUT_PARQUET_FILE = f"{source}.parquet"
+
+    # --- Execution ---
+    # 1. Download the dump file
+    if not os.path.exists(DOWNLOADED_BZ2_FILE):
+        download_wiki_dump(WIKI_DUMP_URL, DOWNLOADED_BZ2_FILE)
+    else:
+        print(f"File '{DOWNLOADED_BZ2_FILE}' already exists. Skipping download.")
+
+    # 2. Process the dump and save to Parquet
+    process_dump_to_parquet(DOWNLOADED_BZ2_FILE, OUTPUT_PARQUET_FILE)
+
+    # 3. (Optional) Clean up the downloaded file
+    # If you want to keep the bz2 file, comment out the next line.
+    print(f"Cleaning up by removing '{DOWNLOADED_BZ2_FILE}'...")
+    os.remove(DOWNLOADED_BZ2_FILE)
+
+    print("\nScript finished successfully.")
+
+
+if __name__ == "__main__":
+    # Before running, make sure you have the required libraries installed:
+    # pip install requests mwparserfromhell pandas pyarrow
+    main()

data/wikisource/descriptive_stats.json

@@ -1,9 +1,9 @@
 {
-  "number_of_samples": 2419,
-  "number_of_tokens": 5344862,
-  "min_length_tokens": 5,
-  "max_length_tokens": 218362,
-  "number_of_characters": 15478618,
-  "min_length_characters": 10,
-  "max_length_characters": 613148
+  "number_of_samples": 3004,
+  "number_of_tokens": 6275973,
+  "min_length_tokens": 17,
+  "max_length_tokens": 261099,
+  "number_of_characters": 18286474,
+  "min_length_characters": 54,
+  "max_length_characters": 754270
 }

data/wikisource/parser/package-lock.json

@@ -0,0 +1,724 @@
+{
+  "name": "parser",
+  "version": "1.0.0",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "parser",
+      "version": "1.0.0",
+      "license": "ISC",
+      "dependencies": {
+        "wtf_wikipedia": "^10.4.0"
+      }
+    },
+    "node_modules/@babel/code-frame": {
+      "version": "7.27.1",
+      "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.27.1.tgz",
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+      "license": "MIT",
+      "dependencies": {
+        "@babel/helper-validator-identifier": "^7.27.1",
+        "js-tokens": "^4.0.0",
+        "picocolors": "^1.1.1"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/helper-validator-identifier": {
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+      "license": "MIT",
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@types/minimist": {
+      "version": "1.2.5",
+      "resolved": "https://registry.npmjs.org/@types/minimist/-/minimist-1.2.5.tgz",
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+      "license": "MIT"
+    },
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+      "resolved": "https://registry.npmjs.org/validate-npm-package-license/-/validate-npm-package-license-3.0.4.tgz",
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+      "dependencies": {
+        "spdx-correct": "^3.0.0",
+        "spdx-expression-parse": "^3.0.0"
+      }
+    },
+    "node_modules/webidl-conversions": {
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+      "license": "BSD-2-Clause"
+    },
+    "node_modules/whatwg-url": {
+      "version": "5.0.0",
+      "resolved": "https://registry.npmjs.org/whatwg-url/-/whatwg-url-5.0.0.tgz",
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+      "license": "MIT",
+      "dependencies": {
+        "tr46": "~0.0.3",
+        "webidl-conversions": "^3.0.0"
+      }
+    },
+    "node_modules/wtf_wikipedia": {
+      "version": "10.4.0",
+      "resolved": "https://registry.npmjs.org/wtf_wikipedia/-/wtf_wikipedia-10.4.0.tgz",
+      "integrity": "sha512-yRxTiBURj2LW5HWAe+T7bCV2x45C/qTqcknUTmInKmB9cmLSxR6Nh44rB9K+nfNiydtjc3HLHwYWxMuHZtpVSQ==",
+      "hasInstallScript": true,
+      "license": "MIT",
+      "dependencies": {
+        "isomorphic-unfetch": "^3.1.0",
+        "path-exists-cli": "2.0.0"
+      },
+      "bin": {
+        "wtf_wikipedia": "cli.js"
+      },
+      "engines": {
+        "node": ">=12.0.0"
+      }
+    },
+    "node_modules/yallist": {
+      "version": "4.0.0",
+      "resolved": "https://registry.npmjs.org/yallist/-/yallist-4.0.0.tgz",
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+      "license": "ISC"
+    },
+    "node_modules/yargs-parser": {
+      "version": "20.2.9",
+      "resolved": "https://registry.npmjs.org/yargs-parser/-/yargs-parser-20.2.9.tgz",
+      "integrity": "sha512-y11nGElTIV+CT3Zv9t7VKl+Q3hTQoT9a1Qzezhhl6Rp21gJ/IVTW7Z3y9EWXhuUBC2Shnf+DX0antecpAwSP8w==",
+      "license": "ISC",
+      "engines": {
+        "node": ">=10"
+      }
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+    "node_modules/yocto-queue": {
+      "version": "0.1.0",
+      "resolved": "https://registry.npmjs.org/yocto-queue/-/yocto-queue-0.1.0.tgz",
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+      "license": "MIT",
+      "engines": {
+        "node": ">=10"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/sindresorhus"
+      }
+    }
+  }
+}

data/wikisource/parser/package.json

@@ -0,0 +1,16 @@
+{
+  "name": "parser",
+  "version": "1.0.0",
+  "description": "",
+  "main": "index.js",
+  "scripts": {
+    "test": "echo \"Error: no test specified\" && exit 1"
+  },
+  "keywords": [],
+  "author": "",
+  "license": "ISC",
+  "type": "commonjs",
+  "dependencies": {
+    "wtf_wikipedia": "^10.4.0"
+  }
+}

data/wikisource/parser/wtf_bridge.js

@@ -0,0 +1,39 @@
+// wtf_bridge.js
+// Usage: node wtf_bridge.js
+// Reads newline-delimited JSON from stdin: {"wikitext":"...","lang":"da"}
+// Writes newline-delimited JSON to stdout: {"text":"...","isRedirect":false} or {"error":"..."}
+const wtf = require('wtf_wikipedia');
+const readline = require('readline');
+
+const rl = readline.createInterface({
+  input: process.stdin,
+  output: process.stdout,
+  terminal: false
+});
+
+process.on('uncaughtException', (err) => {
+  // emit as JSON so Python can see it
+  try {
+    process.stdout.write(JSON.stringify({ error: String(err && err.stack || err) }) + '\n');
+  } catch (e) {}
+  process.exit(1);
+});
+
+rl.on('line', (line) => {
+  (async () => {
+    try {
+      const payload = JSON.parse(line);
+      const wikitext = payload.wikitext || '';
+      const lang = payload.lang || null;
+
+      // parse wikitext into a document (sync)
+      const doc = lang ? wtf(wikitext, lang) : wtf(wikitext);
+      const text = (doc && typeof doc.text === 'function') ? doc.text() : '';
+      const isRedirect = (doc && typeof doc.isRedirect === 'function') ? doc.isRedirect() : false;
+
+      process.stdout.write(JSON.stringify({ text, isRedirect }) + '\n');
+    } catch (err) {
+      process.stdout.write(JSON.stringify({ error: String(err && err.stack || err) }) + '\n');
+    }
+  })();
+});

data/wikisource/wikisource.md

@@ -28,9 +28,9 @@ The Danish subsection of [Wikisource](https://en.wikisource.org/wiki/Main_Page).
 
 
 <!-- START-DESC-STATS -->
-- **Number of samples**: 2.42K
-- **Number of tokens (Llama 3)**: 5.34M
-- **Average document length in tokens (min, max)**: 2.21K (5, 218.36K)
+- **Number of samples**: 3.00K
+- **Number of tokens (Llama 3)**: 6.28M
+- **Average document length in tokens (min, max)**: 2.09K (17, 261.10K)
 <!-- END-DESC-STATS -->
 
 
@@ -42,12 +42,12 @@ An example from the dataset looks as follows.
 <!-- START-SAMPLE -->
 ```py
 {
-  "id": "wikisource_4804",
-  "text": "&lt;poem&gt;\nKæmpehøjen.\nJeg har stået på mindets høje,\nfølt dets vemodsdybe lyst\nmed en tåre i mit [...]",
+  "id": "wikisource_1292",
+  "text": "Dejlig er den himmel blå\nDejlig er den himmel blå, lyst det er at se derpå, hvor de gyldne stjerner [...]",
   "source": "wikisource",
-  "added": "2021-03-28",
-  "created": "1700-01-01, 2022-01-01",
-  "token_count": 1025
+  "added": "2025-08-18",
+  "created": "2022-04-18, 2022-04-18",
+  "token_count": 1243
 }
 ```
 
@@ -72,6 +72,20 @@ An entry in the dataset consists of the following fields:
 <!-- END-DATASET PLOTS -->
 
 
+### Processing
+
+For this dataset we have pulled the latest [database dump from wikimedia](https://dumps.wikimedia.org/dawikisource/latest/) and extracted the texts using the [wtf_wikipedia](https://github.com/spencermountain/wtf_wikipedia/tree/dev) parser. 
+
+Because the parser is written in javascript you need to have Node.js installed on you machine. 
+
+To run the `create.py` file you first need to do:
+
+```bash
+$ cd parser/ && npm install && cd ..
+```
+
+We chose to use `wtf_wikipedia` because out of the other parsers we tested this was the imperically best one. We tested `mwparserfromhell`, `mediawiki_dump`, `wikiextractor`, and `wtf_wikipedia`. It seemed that the others still produced some sort of artifacts from the parsing of wikicode.
+
 ## Additional Information
 
 

data/wikisource/wikisource.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:adc3206d75182f54ac5019e8cba8e87d07f0b84e64e47ecf6fe6a0003ca3d8bc
-size 9493193
+oid sha256:b6a0405062f691a38eb39cd834281511abf1da0199b08ee9806a7b632e6a055c
+size 10996692

descriptive_stats.json

@@ -1,9 +1,9 @@
 {
-  "number_of_samples": 5554217,
-  "number_of_tokens": 5829657307,
+  "number_of_samples": 5600476,
+  "number_of_tokens": 5883315984,
   "min_length_tokens": 2,
   "max_length_tokens": 9812841,
-  "number_of_characters": 17614232708,
+  "number_of_characters": 17772456492,
   "min_length_characters": 1,
   "max_length_characters": 37287484
 }

images/tokens_over_time.html

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 <head><meta charset="utf-8" /></head>
 <body>
     <div>                        <script type="text/javascript">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>
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pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "dynaword"
-version = "1.2.8"
+version = "1.2.10"
 description = "project code for the danish dynaword project"
 readme = "README.md"
 requires-python = ">=3.12,<3.13" # 3.13 have issues with spacy and pytorch

src/dynaword/descriptive_stats.py

@@ -41,7 +41,7 @@ class DescriptiveStatsOverview:
     @property
     def average_document_length_tokens(self) -> float:
         return (
-            self.number_of_tokens / self.number_of_samples
+            round(self.number_of_tokens / self.number_of_samples, 2)
             if self.number_of_samples > 0
             else 0.0
         )
@@ -49,7 +49,7 @@ class DescriptiveStatsOverview:
     @property
     def average_document_length_characters(self) -> float:
         return (
-            self.number_of_characters / self.number_of_samples
+            round(self.number_of_characters / self.number_of_samples, 2)
             if self.number_of_samples > 0
             else 0.0
         )

src/dynaword/process_dataset.py

@@ -17,14 +17,13 @@ logger = logging.getLogger(__name__)
 def _tokenize_function(
     examples: dict[str, Any], tokenizer: AutoTokenizer
 ) -> dict[str, Any]:
-    token_count = [
-        len(tokens)
-        for tokens in tokenizer(examples[ColumnNames.text.value], padding=False)[  # type: ignore
-            "input_ids"
-        ]
-    ]
-    examples[ColumnNames.token_count.value] = token_count
-    return examples
+    encodings = tokenizer(
+        examples["text"],
+        padding=False,
+        truncation=False,
+        return_length=True,  # much faster, avoids storing all IDs
+    )  # type: ignore
+    return {"token_count": encodings["length"]}
 
 
 def add_token_count(

test_results.log

@@ -1,6 +1,6 @@
 ============================= test session starts ==============================
 platform darwin -- Python 3.12.0, pytest-8.3.4, pluggy-1.5.0
-rootdir: /Users/au561649/Github/danish-dynaword
+rootdir: /Users/kristianjensen/Documents/danish-dynaword
 configfile: pyproject.toml
 plugins: anyio-4.9.0
 collected 346 items
@@ -20,7 +20,7 @@ src/tests/test_unique_ids.py .                                           [100%]
 
 =============================== warnings summary ===============================
 src/tests/test_quality/test_short_texts.py: 38 warnings
-  /Users/au561649/Github/danish-dynaword/.venv/lib/python3.12/site-packages/datasets/utils/_dill.py:385: DeprecationWarning: co_lnotab is deprecated, use co_lines instead.
+  /Users/kristianjensen/Documents/danish-dynaword/.venv/lib/python3.12/site-packages/datasets/utils/_dill.py:385: DeprecationWarning: co_lnotab is deprecated, use co_lines instead.
 
 -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
-============ 345 passed, 1 skipped, 38 warnings in 65.92s (0:01:05) ============
+============ 345 passed, 1 skipped, 38 warnings in 89.12s (0:01:29) ============