Update parquet files

README.md

@@ -1,164 +0,0 @@
----
-annotations_creators:
-  - no-annotation
-language_creators:
-  - crowdsourced
-license:
-  - cc-by-sa-4.0
-task_categories:
-  - text-generation
-  - fill-mask
-task_ids:
-  - language-modeling
-  - masked-language-modeling
-source_datasets:
-  - original
-language:
-  - en
-
-configs:
-- config_name: default
-  data_files:
-  - split: final
-    path: "data/Fandom-v0.5.jsonl"
-  - split: raw-pre-roblox
-    path: "v2.5-chunks/*.jsonl"
-  - split: raw-post-roblox
-    path: "v2.5-chunks-roblox-filter/*.jsonl"
-
-pretty_name: Fanatic Fandom
----
-
-# Dataset Card for Fanatic Fandom
-
-![](FandomWaifu.png "SD-Generated image styled in the same essence with fandom's logo")
-
-*Waifu to catch your attention.*
-
-## Dataset Details
-
-### Dataset Description
-
-*Fanatic Fandom* is a cleaned dataset of a raw scrape of fandom wikis. We crawled all the publicly available wikis and crawled each page.  
-Filtering to a total amount of tokens of **~7.43B** (llama-2-7b-chat-tokenizer) / **~6.27B** (RWKV Tokenizer) from primarily English language.
-
-- **Curated by:** KaraKaraWitch
-- **Funded by [optional]:** Recursal.ai (I work there lol)
-- **Shared by [optional]:** KaraKaraWitch
-- **Language(s) (NLP):** Primarily English
-- **License:** cc-by-sa-4.0
-
-### Dataset Sources [optional]
-
-- **Source Data:** [https://fandom.com/](https://fandom.com/) (Bot Crawled.)
-
-### Processing and Filtering
-
-We detail the following steps involved in scraping, indexing and cleaning fandom wikis to the html content files. Here's a breakdown of the process:
-
-1. **Wiki Identification:**
-    - `WikisIndexer.py` script retrieves a list of wikis from `https://community.fandom.com/Special:NewWikis`.
-
-2. **Page Indexing:**
-    - `IndexFandomPages.py` script utilizes the MediaWiki API (`api.php`) to gather a list of pages per each wiki.
-
-3. **Page Fetching:**
-    - `WikiPageFetcher.py` script utilizes the MediaWiki API (`api.php`) to render the render the wiki page and save it to a large JSONL file.
-    - Additionally, any wikis with less than 5 pages are not scrapped due to assumed low-quality.
-
-4. **Data Chunking:**
-    - A single large JSONL file containing all fetched pages is split into smaller, more manageable chunks.
-    - This is in preparation from the 4th step.
-
-5. **Roblox Wiki Removal:**
-    - The `RobloxWikiFilter.py` script identifies and removes Roblox wikis due to the high volume of low-quality content they often generate. This filtering step simplifies the subsequent stub article removal process.
-    - From quick napkin math: around 15.2% (Comparing Step 3 and Step 4 results) of fandom wikis are Roblox data.
-
-6. **Content Transformation:**
-    - HTML content is converted to Markdown format. The conversion process removes unnecessary elements like figures, stub article notices, and other irrelevant data.
-
-**Note:** Due to the passage of time (approximately 3 months as of May 6, 2024), the specific details of the crawling process may be a little hazy. The primary challenge encountered was the significant time required to complete the crawling operation.
-
-### Data Splits
-
-There are 3 splits for this dataset:
-
-- final
-  - Contains the final 25GB jsonl file.
-  - You probably want this for training.
-- raw-pre-roblox
-  - Raw files, **before** Roblox filtering.
-  - Use this if you want to start from scratch and don't want to crawl fandom again.
-- raw-post-roblox
-  - Raw files, **after** Roblox filtering.
-  - Roblox wikis removed.
-  - Use this if you want to start from scratch and don't want to crawl fandom again.
-
-### Data Keys
-
-For this dataset, we have included most of the various steps for the dataset. They are listed as such below:
-
-- `fandom_wikis_210224.csv`
-  - A CSV file containing a list of wikis found when scrapping from `Special:NewWikis` on 21/02/2024
-  - The key is as follows: `Sub Domain,Name of Wiki,Path name,0`
-  - The stray zero can be ignored as it does not serve any purpose.
-- `fandom_wikis_pages_210224_v2.jsonl`
-  - Contains a jsonl list of wiki pages per each wiki.
-  - Each jsonl has the following keys:
-  - domain: str [The subdomain.]
-  - path: str [Path to `api.php`. Which can be different for different languages]
-  - pages: list[str] [A list of strings containing page names]
-- `v2.5-chunks` [folder]
-  - Contains all the pages fetched from the list in `fandom_wikis_pages_210224_v2.jsonl`
-  - The original file it was from is `fandom_wikis_pages_contents_210224_v2.jsonl`, which is 283.44GB in size and can't be uploaded to HF.
-  - Each jsonl has the following keys:
-  - domain: str [The subdomain.]
-  - path: str [Path to `api.php`. Which can be different for different languages]
-  - pages: str [Page name]
-  - content: raw response from api.php
-- `v2.5-chunks-roblox-filter` [folder]
-  - Contains files after roblox has been filtered.
-  - Each jsonl has the following keys:
-    - domain: str [The subdomain.]
-    - path: str [Path to `api.php`. Which can be different for different languages]
-    - pages: str [Page name]
-    - content: raw response from api.php
-- `fandom-v0.5.jsonl` [file]
-  - Jsonl file containing the fully processed text.
-  - Each jsonl has the following keys:
-    - text: str [The text content.]
-    - meta: dict[str,str] [dictionary of metadata]
-      - title: str [The page/name]
-      - domain: str [The subdomain.]
-      - cats: str [Categories. Extracted and unused.]
-      - removed: list[str] [A list of removed stubs / html content]
-
-- `roblox.domains.txt` [Extras]
-  - A txt list of Roblox domains.
-
-### Dataset Curators
-
-KaraKaraWitch. (I typically hangout in PygmalionAI discord, sometimes EleutherAI. If something is wrong, `@karakarawitch` on discord.)
-
-I'd be happy if you could spread the word and recommend this dataset for your use cases `:)`
-
-### Licensing Information
-
-Most of all fandom user-created content are licensed under CC-BY-SA unless otherwise noted. By that assumption, we did not include any figures or images as they typically are not licensed under the CC-BY-SA license.
-
-### Citation Information
-
-```
-@ONLINE{fantaticfandom,
-  title         = {FanaticFandom},
-  author        = {KaraKaraWitch, recursal.ai},
-  year          = {2023},
-  howpublished  = {\url{TBD}},
-}
-```
-
-### Special Thanks
-
-- [undeleted](https://huggingface.co/undeleted) from RyokoAI for providing initial scripts to base stuff on.  
-  I eventually decided to write my own scraper while taking inspiration from their code.
-- [Google / Gemini]... I'm horrible at writing professional stuff lol.

Scripts/HTML2Markdown.py

@@ -1,451 +0,0 @@
-import multiprocessing
-import pathlib
-import re
-import string
-import traceback
-from multiprocessing import Queue
-
-import markdownify
-import orjson
-import tqdm
-from bs4 import BeautifulSoup, Comment, NavigableString, Tag
-from markdownify import chomp
-
-if __name__ == "__main__":
-    multiprocessing.set_start_method("forkserver")
-
-
-queue = Queue(maxsize=64)
-
-
-class WikiConverter(markdownify.MarkdownConverter):
-    def convert_a(self, el, text, convert_as_inline):
-        prefix, suffix, text = chomp(text)
-        if not text:
-            return ""
-        return "%s%s%s" % (prefix, text, suffix)
-
-    integer_rgx = re.compile("^[0-9]*$")
-
-    @staticmethod
-    def is_intable(string: str):
-        if not string or not string.isdigit():
-            return False
-        if WikiConverter.integer_rgx.match(string):
-            return True
-
-    def convert_img(self, el, text, convert_as_inline):
-        convert_as_inline = True
-        if (
-            convert_as_inline
-            and el.parent.name not in self.options["keep_inline_images_in"]
-        ):
-            return ""
-        return ""
-
-    def convert_li(self, el, text, convert_as_inline):
-        parent = el.parent
-        if parent is not None and parent.name == "ol":
-            start = parent.get("start")
-            if start and WikiConverter.is_intable(start.strip()):
-                start = int(start.strip())
-            else:
-                start = 1
-            bullet = "%s." % (start + parent.index(el))
-        else:
-            depth = -1
-            while el:
-                if el.name == "ul":
-                    depth += 1
-                el = el.parent
-            bullets = self.options["bullets"]
-            bullet = bullets[depth % len(bullets)]
-        return "%s %s\n" % (bullet, (text or "").strip())
-
-
-wk = WikiConverter()
-
-
-def table_filtration(input_soup: BeautifulSoup, title):
-    for table in input_soup.select("table"):
-        tds = len(table.find_all("td"))
-        texsize = len(table.get_text().replace(" ", ""))
-        if tds >= texsize and texsize < 50:
-            table.decompose()
-        if tds > 20:
-            # print("Decompose Excessive td")
-            table.decompose()
-            # print(table.get_text().replace(" ", ""))
-            # print("Removing table from", title, ". TD exceeds Content")
-    return input_soup
-
-
-def soup_data(data: BeautifulSoup, title: str):
-    soup = data
-
-    # Navigation elements
-    [toc.decompose() for toc in soup.find_all("div", attrs={"class": "toc"})]
-    [toc.decompose() for toc in soup.select("[class*='nav']")]
-    # [toc.decompose() for toc in soup.select(".navbox")]
-    # Edit Section
-    [element.decompose() for element in soup.select(".mw-editsection")]
-    # Remove styles
-    [element.decompose() for element in soup.select("style")]
-
-    [element.decompose() for element in soup.select("sup.reference")]
-    # star-citizen.wiki.
-    [element.decompose() for element in soup.select(".thumbcaption")]
-    # Images and pictures are not under licenses typically.
-    [toc.decompose() for toc in soup.select("audio")]
-    [toc.decompose() for toc in soup.select("picture")]
-    [toc.decompose() for toc in soup.select("img")]
-    [toc.decompose() for toc in soup.select("[class*='video']")]
-    # Blazblue.wiki
-    [toc.decompose() for toc in soup.select("[class*='tooltip']")]
-    [toc.decompose() for toc in soup.select("video")]
-
-    [
-        toc.decompose()
-        for toc in soup.select(".no-featured-video .featured-video-player-container")
-    ]
-    # print(soup)
-    cleaned_soup = table_filtration(soup, title)
-    composed_data = (
-        re.sub(r"\n\s*\n", "\n\n", wk.convert_soup(cleaned_soup))
-        .replace("\n |\n|", " |\n")
-        .strip()
-    )
-    return composed_data
-
-
-raw_puncts = string.punctuation + "｛｝（）［］【】、，゠＝…‥。「」『』〝〟"
-
-puncts = str.maketrans("", "", raw_puncts)
-
-cpl = re.compile(r"\n\s*\n")
-
-dbg_q = multiprocessing.Queue()
-
-
-def debug_queue():
-    try:
-        with open("debug.txt", "w", encoding="utf-8") as f:
-            while True:
-                z = dbg_q.get()
-                if z is None or z == "None":
-                    break
-                f.write(z + "\n")
-                f.flush()
-    except Exception as e:
-        print(e)
-
-
-# Filters based on classes
-msgbox = set(["mbox", "notice", "hidden", "plainlinks"])
-msgbox2 = set(["mbox", "notice", "stub-box", "plainlinks"])
-msgbox3 = set(["notice", "metadata", "plainlinks"])
-# Aggressive class filter.
-msgbox_agressive = set(
-    [
-        "mbox-w",
-        "mbox",
-        "msgbox",
-        "notice-container",
-        "notice",
-        "message-box",
-        "boilerplate",
-        "ambox",
-        "ombox",
-    ]
-)
-
-wikistub = set(["wikistub"])
-
-
-def get_text_cleaned(elem):
-    return (
-        cpl.sub("\n\n", elem.get_text(" "))
-        .replace("\n", " ")
-        .replace("  ", " ")
-        .replace("  ", " ")
-        .lower()
-    )
-
-
-def get_plain_text_clean(data: str):
-    return (
-        cpl.sub("\n\n", data.translate(puncts))
-        .replace("\n", " ")
-        .replace("  ", " ")
-        .replace("  ", " ")
-        .lower()
-    )
-
-
-t_stubs = 0
-f_stubs = 0
-
-t_lock = multiprocessing.Lock()
-
-
-def t_inc(idx: int):
-    global t_stubs
-    with t_lock:
-        t_stubs += idx
-
-
-f_lock = multiprocessing.Lock()
-
-
-def f_inc(idx: int):
-    global f_stubs
-    with f_lock:
-        f_stubs += idx
-
-
-def stub_removal(soup: str, debug=None):
-    b_soup = BeautifulSoup(soup, "lxml")
-    a = get_text_cleaned(b_soup)
-    if "this article is a stub" in a:
-        parser = b_soup.select_one(".mw-parser-output")
-        if parser is None:
-            return b_soup, []
-        pruned = []
-        for child in parser.children:
-            if child is None:
-                continue
-            if isinstance(child, Comment):
-                continue
-            if isinstance(child, NavigableString):
-                # print("Nav string?")
-                # print(child)
-                # print("===========")
-                continue
-            if not isinstance(child, Tag):
-                # print(type(child))
-                continue
-            classes = set(i.lower() for i in child.get("class", []))
-            styles = child.get("style", "")
-            has_border = False
-            if styles:
-                styles = {
-                    i.split(":")[0]: ":".join(i.split(":")[1:])
-                    for i in child.get("style", "").split(";")
-                }
-
-                has_border = any(
-                    [
-                        styles.get("border"),
-                        styles.get("border-width") and styles.get("border-style"),
-                        styles.get("border-top"),
-                        styles.get("border-bottom"),
-                        styles.get("border-left"),
-                        styles.get("border-right"),
-                        styles.get("background"),
-                    ]
-                )
-                # print(styles)
-
-            child_text = get_text_cleaned(child)
-            has_stub_word = "stub" in child_text and "this article" in child_text
-            c_name = "" if not child.name else child.name
-
-            if not has_stub_word:
-                continue
-            if (
-                len(classes.intersection(msgbox)) == len(msgbox)
-                or len(classes.intersection(msgbox2)) == len(msgbox2)
-                or len(classes.intersection(msgbox3)) == len(msgbox3)
-            ):  # Seems to be safe.
-                child.decompose()
-                pruned.append("mbox")
-            elif len(classes.intersection(msgbox_agressive)) > 0:  # Aggressive
-                child.decompose()
-                # dbg_q.put(f'[I aggressive "mbox3_aggressive" prune]: {debug}')
-                pruned.append("mbox3_aggressive")
-            elif len(classes.intersection(wikistub)) == 1:  # Seems to be safe.
-                child.decompose()
-                pruned.append("wikistub[gods-games-we-play]")
-            elif "table" in c_name:  # Bit risky, but i guess it works?
-                pruned.append("table[stub-word]")
-                child.decompose()
-            elif "dl" in c_name:  # Seems to be safe.
-                if len(child.find_all("dd", recursive=False)) == 1:
-                    pruned.append("dl > dd")
-                    child.decompose()
-            elif "div" in c_name:
-                inner_elements = [
-                    i for i in child.find_all(recursive=False) if isinstance(i, Tag)
-                ]
-                if len(inner_elements) == 0:
-                    # print(child.find_all(recursive=False))
-                    # dbg_q.put(f"[No Inner Element()?]: {len(inner_elements)}")
-                    continue
-                stub_inner = get_text_cleaned(inner_elements[0])
-                has_stub_word = "stub" in stub_inner and "this article"
-
-                if len(inner_elements) == 0 or len(inner_elements) > 2:
-                    # dbg_q.put(
-                    #     f"[W No Prune len()? has_stub_word]: {debug} {has_stub_word} {len(inner_elements)}"
-                    # )
-                    continue
-                if (
-                    inner_elements[0].name
-                    and inner_elements[0].name == "table"
-                    and has_stub_word
-                ):
-                    pruned.append("table[stub-word]")
-                    child.decompose()
-                elif has_border and inner_elements[0].name.lower() in [
-                    "div",
-                    "p",
-                    "span",
-                ]:
-                    # dbg_q.put(f'[I Risky "has_border" prune]: {debug}')
-                    pruned.append("risky[border]")
-                else:
-                    # dbg_q.put(
-                    #     f"[W No Prune div? has_stub_word]: {debug} {has_stub_word} {inner_elements[0].name}"
-                    # )
-                    pruned.append("?")
-            elif "p" in c_name:  # Really risky. will try logging it first.
-                child.decompose()
-                # dbg_q.put(f'[I Risky "p" prune]: {debug}')
-                f_inc(1)
-                pruned.append("risky[p]")
-            elif "center" in c_name:  # Really risky. will try logging it first.
-                # dbg_q.put(f'[I Risky "center" prune]: {debug}')
-                child.decompose()
-                f_inc(1)
-                pruned.append("risky[center]")
-        if pruned:
-            t_inc(len(pruned))
-            # print("Pruned", pruned, debug)
-            return b_soup, pruned
-        else:
-            # dbg_q.put(f"[W No Prune?]: {debug}")
-            # print(f"[W No Prune?]: {debug}")
-            return b_soup, []
-
-    return b_soup, []
-
-
-def writer(fp: str, writer_queue: multiprocessing.Queue):
-    pbar = tqdm.tqdm()
-    try:
-        with open(fp, "wb") as fl:
-            while True:
-                q = writer_queue.get(block=True)
-                if q is None or isinstance(q, str) and q == "None":
-                    print("Q Empty, exit.")
-                    break
-                elif isinstance(q, bytes):
-                    fl.write(q)
-                    fl.write(b"\n")
-                pbar.update(1)
-    except Exception as e:
-        print("Writer Crashed?")
-        traceback.print_exception(e)
-
-
-def mt_fn(bytes_data: bytes, write_queue: multiprocessing.Queue):
-    data = orjson.loads(bytes_data)
-    dbg = f"domain: {data['domain']} title: {data['page']}"
-    if "parse" not in data["content"]:
-        print(
-            "Missing parse content",
-            "domain",
-            data["domain"],
-            "title",
-            data["page"],
-        )
-        return
-    lower_title = data["page"].lower()
-    if (
-        lower_title.startswith("forum:")
-        or lower_title.startswith("discussion:")
-        or lower_title.startswith("thread:")
-        or lower_title.startswith("comments:")
-        or lower_title.startswith("comment:")
-    ):
-        return
-    if lower_title.endswith("gallery"):
-        return
-    soup = data["content"]["parse"]["text"]["*"]
-    cats = ",".join([z["*"] for z in data["content"]["parse"]["categories"]]).lower()
-    unstubbed_soup, removed = stub_removal(soup, debug=dbg)
-    text = soup_data(unstubbed_soup, data["page"])
-    unpunct = get_plain_text_clean(text)
-    if len(unpunct) > 64:
-        # print(text[:64])
-        write_queue.put(
-            orjson.dumps(
-                {
-                    "text": text,
-                    "meta": {
-                        "title": data["page"],
-                        "domain": data["domain"],
-                        "cats": cats,
-                        "removed": removed,
-                    },
-                }
-            )
-        )
-
-
-def err_handler(e):
-    if "KeyboardInterrupt" not in str(e):
-        traceback.print_exception(e)
-
-
-def main():
-    with multiprocessing.Pool(processes=64) as pool:
-        managed = multiprocessing.Manager()
-        writer_out = managed.Queue()
-        write_proc = multiprocessing.Process(
-            target=writer, args=("test.jsonl", writer_out), daemon=False
-        )
-        # debug_tasks.start()
-        write_proc.start()
-
-        tasks = []
-        for file in pathlib.Path("v2.5-chunks-roblox-filter").iterdir():
-            with open(file, "rb") as f:
-                iter_wrapper = f  # tqdm.tqdm(f)
-                for line in iter_wrapper:
-                    tasks.append(
-                        pool.apply_async(
-                            mt_fn, args=(line, writer_out), error_callback=err_handler
-                        )
-                    )
-
-                    if len(tasks) >= 100000:
-                        print("Waiting for Chunked task to complete.")
-                        for task in tasks:
-                            if task.ready():
-                                continue
-                            task.wait()
-                        tasks = []
-            print("[I] ========== Task gen done", file)
-        print("Waiting for Chunked task to complete.")
-        for task in tasks:
-            if task.ready():
-                continue
-            task.wait()
-        print("Cleanup")
-        # print("Stubs", t_stubs, "FStubs", f_stubs)
-        dbg_q.put("None")
-        # debug_tasks.join()
-        writer_out.put("None")
-        # while not writer_out.empty():
-        #     print(f"Waiting for empty writer {writer_out.qsize()} items left")
-        #     time.sleep(5)
-
-        write_proc.join()
-
-        pool.close()
-        pool.join()
-
-
-if __name__ == "__main__":
-    main()

Scripts/IndexFandomPages.py

@@ -1,241 +0,0 @@
-#!/usr/bin/env python3
-# License: MIT
-# Copyright (C) 2024, Shinon.
-# Code inspiration from Ronsor Labs. Licensed as below.
-# License: AGPL 3.0
-# Copyright (C) 2023, 2024 Ronsor Labs.
-import asyncio
-import concurrent.futures as conc
-import csv
-import pathlib
-import random
-import urllib.parse
-
-import aiofile
-import httpx
-import orjson
-import tqdm
-from bs4 import BeautifulSoup
-
-from proxy_magic_session import get_async_session
-
-CONCURRENT_WORKERS = 128
-
-executor = conc.ProcessPoolExecutor(max_workers=64)
-
-queue = asyncio.Queue(maxsize=1048576)
-
-WIKI_LIST = pathlib.Path("fandom_wikis_210224.csv")
-OUPUT_JSONL = pathlib.Path("fandom_wikis_pages_210224_v2.jsonl")
-
-
-def parse_special_index(html_text: str):
-    doc = BeautifulSoup(html_text, "lxml")
-
-    page_list_li = doc.select("ul.mw-allpages-chunk li a")
-    page_list = set()
-    for page_item in page_list_li:
-        page_title = page_item.get("title", "")
-        if not page_title or page_title is None:
-            print("[W] no page title?")
-            continue
-        if page_title.lower().rstrip().endswith("(redirect)"):
-            continue
-        else:
-            page_list.add(page_item["title"])
-    page_list = list(page_list)
-
-    next_url = doc.select(".mw-allpages-nav a")
-    if next_url is None or len(next_url) == 0:
-        next_url = None
-    else:
-        candidates = next_url
-        next_url = None
-        for x in candidates:
-            if "next page" in x.text.lower():
-                if "index.php" not in x["href"].lower():
-                    next_url = x["href"].split("=", 1)
-                    next_url[1] = urllib.parse.quote_plus(
-                        next_url[1].replace("+", "__SAFE_PLUS__")
-                    ).replace("__SAFE_PLUS__", "+")
-                    next_url = "=".join(next_url)
-                else:
-                    next_url = x["href"]
-
-    return page_list, next_url
-
-
-async def domain_procesor(domain: str, path: str):
-    session: httpx.AsyncClient = get_async_session()
-    loop = asyncio.get_running_loop()
-    session.cookies.clear()
-    session.headers["user-agent"] = (
-        "Mozilla/6.2 (compatible; Microsoft Chrome 137.0; Apple Gecko 47.0 in AOL Firefox 37.6) Google Toolbar/1.3"
-    )
-    print(f"[I] Processing: https://{domain}{path}Special:AllPages")
-    tries = 10
-    # pbar = tqdm.tqdm(desc=f"{domain}")
-    data = None
-    while True:
-        try:
-            data = await session.get(
-                f"https://{domain}{path}Special:AllPages", follow_redirects=True
-            )
-            if data.status_code != 200:
-                if data.status_code == 410:
-                    break
-
-                # print(f"https://{domain}{path}Special:AllPages", data.status_code)
-                continue
-            break
-        except httpx.TransportError as e:
-            await session.aclose()
-            session: httpx.AsyncClient = get_async_session()
-            print(f"[W] Retry TransportError https://{domain}{path} {e}")
-            await asyncio.sleep(1)
-            tries -= 1
-        except httpx.HTTPError as e:
-            print(f"[W] Uncaught Exception Retry... https://{domain}{path} | {e}")
-            await session.aclose()
-            session: httpx.AsyncClient = get_async_session()
-            # print(f"[W] Retry TransportError https://{domain}{path} {e}")
-            await asyncio.sleep(1)
-            tries -= 1
-        except Exception as e:
-            print(f"[W] Uncaught Exception https://{domain}{path} | {e}")
-            break
-        if tries <= 0:
-            print(f"[W] Tries Exceeded https://{domain}{path}")
-            break
-
-    if tries <= 0 or data is None:
-        return
-    if data.status_code == 410:
-        return
-
-    # Handle redirected domains
-    domain = data.url.host
-
-    page_list, next_url = await loop.run_in_executor(
-        executor, parse_special_index, data.text
-    )
-    # pbar.update(len(page_list))
-    while next_url:
-        tries = 10
-        data = None
-        while True:
-            try:
-                data = await session.get(
-                    f"https://{domain}{next_url}", follow_redirects=True
-                )
-                if data.status_code != 200:
-                    if data.status_code == 410:
-                        break
-                    print(f"https://{domain}{next_url}", data.status_code)
-                    continue
-                break
-            except httpx.TransportError as e:
-                await session.aclose()
-                session: httpx.AsyncClient = get_async_session()
-                print(f"[W2] Retry TransportError https://{domain}{next_url} {e}")
-                await asyncio.sleep(1)
-                tries -= 1
-            except httpx.HTTPError as e:
-                print(
-                    f"[W2] Uncaught Exception Retry... https://{domain}{next_url} | {e}"
-                )
-                await session.aclose()
-                session: httpx.AsyncClient = get_async_session()
-                # print(f"[W] Retry TransportError https://{domain}{path} {e}")
-                await asyncio.sleep(1)
-                tries -= 1
-            except Exception as e:
-                print(f"[W2] Uncaught Exception https://{domain}{next_url} | {e}")
-                break
-            if tries <= 0:
-                print(f"[W2] Tries Exceeded https://{domain}{next_url}")
-                break
-        if tries <= 0 or data is None:
-            return
-        if data.status_code == 410:
-            return
-        new_page_list, next_url = await loop.run_in_executor(
-            executor, parse_special_index, data.text
-        )
-        # pbar.update(len(new_page_list))
-        page_list.extend(new_page_list)
-    # pbar.close()
-    print(f"[I] Done: {domain} | {len(page_list)}")
-    await session.aclose()
-    return page_list
-
-
-export_queue = asyncio.Queue(CONCURRENT_WORKERS + 1)
-
-
-async def compiler_worker():
-    loop = asyncio.get_running_loop()
-    async with aiofile.async_open(OUPUT_JSONL, "ab") as f:
-        while True:
-            page_data = await export_queue.get()
-            if page_data is None:
-                break
-            domain, pages, path = page_data
-            print(f"[I] Dump: {domain}")
-            fi = {"domain": domain, "path": path, "pages": pages}
-            bytes_data = await loop.run_in_executor(executor, orjson.dumps, fi)
-            await f.write(bytes_data)
-            await f.write(b"\n")
-            print(f"[I] OKDump: {domain}")
-
-
-async def worker():
-    await asyncio.sleep(random.uniform(1, CONCURRENT_WORKERS / 60))
-    while True:
-        domain_root = await queue.get()
-        if domain_root is None:
-            break
-        domain, _, path, __ = domain_root
-        if path == "":
-            path = "/wiki/"
-        if "vpn-restricted" in domain:
-            continue
-        pages = await domain_procesor(domain, path)
-        if pages is None:
-            continue
-        await export_queue.put((domain, pages, path))
-
-
-async def main():
-    loop = asyncio.get_running_loop()
-    workers = [loop.create_task(worker()) for _ in range(CONCURRENT_WORKERS)]
-    writer = loop.create_task(compiler_worker())
-
-    seen_domains = set()
-    if OUPUT_JSONL.exists():
-        print("[I] Fetching seen domains...")
-        with open(OUPUT_JSONL, "rb") as f:
-            for line in tqdm.tqdm(f, desc="Domains Parsed"):
-                seen_domains.add(orjson.loads(line)["domain"])
-
-    with open(WIKI_LIST) as f:
-        reader = csv.reader(f)
-        for line in reader:
-            if len(line) == 0:
-                continue
-            domain, friendly_name, path, has_scraped = line
-            if domain[0] == "#":
-                continue
-            if domain in seen_domains:
-                continue
-            await queue.put((domain, friendly_name, path, has_scraped))
-    for _ in range(CONCURRENT_WORKERS + 1):
-        await queue.put(None)
-
-    await asyncio.gather(*workers)
-    await export_queue.put(None)
-    await asyncio.gather(writer)
-
-
-if __name__ == "__main__":
-    asyncio.run(main())

Scripts/RobloxWikiFilter.py

@@ -1,111 +0,0 @@
-# Purging roblox domain games base of word matching
-# - Shinon
-import multiprocessing
-import re
-from bs4 import BeautifulSoup
-import orjson
-import pathlib
-import typer
-from sqlitedict import SqliteDict
-
-cpl = re.compile(r"(roblox | roblox)", flags=re.IGNORECASE)
-
-app = typer.Typer()
-
-def filter_worker(
-    chunked_jsonl: pathlib.Path, out_file: pathlib.Path, index_file: pathlib.Path
-):
-    domains = set([i.strip() for i in index_file.read_text().split("\n") if i.strip()])
-    with open(chunked_jsonl, "rb") as f, open(out_file, "wb") as out_fp:
-        for line in f:
-            data = orjson.loads(line)
-            if data["domain"] in domains:
-                continue
-            out_fp.write(line)
-
-
-def roblox_worker(file: pathlib.Path, index_file: pathlib.Path, txt_file: pathlib.Path):
-    with SqliteDict(index_file) as fout:
-        with open(file, "rb") as f:
-            sync_time = 0
-            for line in f:
-                data = orjson.loads(line)
-                # dbg = f"domain: {data['domain']} title: {data['page']}"
-                if "parse" not in data["content"]:
-                    print(
-                        "Missing parse content",
-                        "domain",
-                        data["domain"],
-                        "title",
-                        data["page"],
-                    )
-                    continue
-                soup = data["content"]["parse"]["text"]["*"]
-                composed_soup = (
-                    re.sub(r"\n\s*\n", "\n\n", BeautifulSoup(soup, "lxml").get_text())
-                    .replace("\n", "")
-                    .strip()
-                )
-                robloxed = len(cpl.findall(composed_soup))
-                if data["domain"] not in fout:
-                    fout[data["domain"]] = 0
-                fout[data["domain"]] += robloxed
-                sync_time += 1
-                if sync_time % 10000 == 0 and sync_time != 0:
-                    fout.commit()
-            fout.commit()
-        with open(txt_file, "wb") as f:
-            for domain, roblox_count in fout.iteritems():
-                if roblox_count >= 2:
-                    print(domain)
-                    f.write(domain.encode() + b"\n")
-
-
-def err_cb(e):
-    print(e)
-
-@app.command()
-def index(folder:pathlib.Path,index_folder:pathlib.Path):
-    with multiprocessing.Pool(processes=64) as pool:
-        fn = []
-        for file in pathlib.Path(folder).iterdir():
-            fn.append(
-                pool.apply_async(
-                    roblox_worker,
-                    args=(
-                        pathlib.Path("v2.5-chunks") / f"{file.name}",
-                        index_folder / f"{file.stem}.sqlite",
-                        index_folder / f"{file.name}.domains.txt",
-                    ),
-                    error_callback=err_cb,
-                )
-            )
-        for task in fn:
-            task.wait()
-        pool.close()
-        pool.join()
-
-@app.command()
-def main(folder:pathlib.Path,output_folder:pathlib.Path,domains_txt:pathlib.Path):
-    with multiprocessing.Pool(processes=64) as pool:
-        fn = []
-        for file in folder.iterdir():
-            fn.append(
-                pool.apply_async(
-                    filter_worker,
-                    args=(
-                        file,
-                        output_folder / f"{file.name}.jsonl",
-                        domains_txt
-                    ),
-                    error_callback=err_cb,
-                )
-            )
-        for task in fn:
-            task.wait()
-        pool.close()
-        pool.join()
-
-app()
-
-# main()

Scripts/WikiPageFetcher.py

@@ -1,157 +0,0 @@
-#!/usr/bin/env python3
-# License: MIT
-# Copyright (C) 2024, Shinon.
-# Code inspiration from Ronsor Labs. Licensed as below.
-# License: AGPL 3.0
-# Copyright (C) 2023, 2024 Ronsor Labs.
-
-# Fetches pages and page content from a page list
-
-import asyncio
-import concurrent.futures as conc
-import pathlib
-import urllib.parse
-
-import aiofile
-import httpx
-import orjson
-
-from proxy_magic_session import get_async_session
-
-CONCURRENT_WORKERS = 128
-
-executor = conc.ProcessPoolExecutor(max_workers=64)
-
-pages_queue = asyncio.Queue(maxsize=1048576)
-output_queue = asyncio.Queue(maxsize=int(CONCURRENT_WORKERS*1.5))
-
-INPUT_JSONL = pathlib.Path("fandom_wikis_pages_210224_v2.jsonl")
-OUPUT_JSONL = pathlib.Path("fandom_wikis_pages_contents_210224_v2.jsonl")
-
-
-async def retry_url(url: str):
-    loop = asyncio.get_running_loop()
-    session: httpx.AsyncClient = get_async_session()
-    session.cookies.clear()
-    session.headers[
-        "user-agent"
-    ] = "Mozilla/6.2 (compatible; Microsoft Chrome 137.0; Apple Gecko 47.0 in AOL Firefox 37.6) Google Toolbar/1.3"
-    tries = 10
-    data = None
-    while True:
-        try:
-            data = await session.post(url, follow_redirects=True)
-            if data.status_code >= 300 and data.status_code < 500 and data.status_code != 403:
-                if data.status_code == 410:
-                    break
-                print(f"[W] RetryRequest | {url} {data.status_code}")
-                continue
-            try:
-                await loop.run_in_executor(executor, orjson.loads, data.content)
-            except Exception:
-                continue
-            break
-        except httpx.TransportError as e:
-            await session.aclose()
-            session: httpx.AsyncClient = get_async_session()
-            print(f"[W] Retry TransportError {url} {e}")
-            await asyncio.sleep(1)
-            tries -= 1
-        except httpx.HTTPError as e:
-            print(f"[W] Uncaught Exception Retry... {url} | {e}")
-            await session.aclose()
-            session: httpx.AsyncClient = get_async_session()
-            await asyncio.sleep(1)
-            tries -= 1
-        except Exception as e:
-            print(f"[W] Uncaught Exception {url} | {e}")
-            break
-        if tries <= 0:
-            print(f"[W] Tries Exceeded {url}")
-            break
-    await session.aclose()
-    if tries <= 0:
-        return
-    return data
-
-
-async def HTMLWorker():
-    loop = asyncio.get_running_loop()
-    while True:
-        data = await pages_queue.get()
-        if data is None:
-            break
-        domain, path, page = data
-        query_params = {
-            "action": "parse",
-            "format": "json",
-            "page": page,
-            "prop": "text|langlinks|categories|links|templates|images|externallinks|sections|revid|displaytitle|iwlinks|properties|parsewarnings|wikitext",
-        }
-        print(f"[I] HTMLW | {domain} {page} query.")
-        response = await retry_url(
-            f"https://{domain}{path}api.php?{urllib.parse.urlencode(query_params)}"
-        )
-        if response and response.status_code == 200:
-            print(f"[I] HTMLW | {domain} {page} dumped.")
-            await output_queue.put(
-                {
-                    "domain": domain,
-                    "path": path,
-                    "page": page,
-                    "content": await loop.run_in_executor(
-                        executor, orjson.loads, response.content
-                    ),
-                }
-            )
-
-
-async def jsonl_writer():
-    loop = asyncio.get_running_loop()
-    async with aiofile.async_open(OUPUT_JSONL, "wb") as f:
-        while True:
-            dict_data: dict = await output_queue.get()
-            if dict_data is None:
-                break
-            print(f"[I] Dump: {dict_data['domain']}{dict_data['path']}{dict_data['page']}")
-            bytes_data = await loop.run_in_executor(executor,orjson.dumps, dict_data)
-            await f.write(bytes_data)
-            await f.write(b"\n")
-
-
-async def main():
-    loop = asyncio.get_running_loop()
-    workers = [loop.create_task(HTMLWorker()) for _ in range(CONCURRENT_WORKERS)]
-    writer = loop.create_task(jsonl_writer())
-    with open(INPUT_JSONL, "rb") as f:
-        line = f.readline()
-        for line in f:
-            if line:
-                domain_data = orjson.loads(line)
-                page_count = len(domain_data["pages"])
-                if page_count <= 5:
-                    print(f"[I] Skip {domain_data['domain']} due to low page count.")
-                    continue
-                for page in domain_data["pages"]:
-                    await pages_queue.put(
-                        (domain_data["domain"], domain_data["path"][:-5], page)
-                    )
-        for _ in range(CONCURRENT_WORKERS):
-            await pages_queue.put(None)
-    while True:
-        done_workers = 0
-        for worker in workers:
-            if worker.done():
-                done_workers += 1
-        if done_workers != CONCURRENT_WORKERS:
-            print(f"\r{done_workers} / {CONCURRENT_WORKERS} are completed.")
-            await asyncio.sleep(60)
-        else:
-            break
-    # await asyncio.gather(*workers)
-    await output_queue.put(None)
-    print("Sent shutdown to Jsonl writer.")
-    await asyncio.gather(writer)
-
-if __name__ == "__main__":
-    asyncio.run(main())

Scripts/WikisIndexer.py

@@ -1,70 +0,0 @@
-#!/usr/bin/env python3
-# License: MIT
-# Copyright (C) 2024, Shinon.
-
-# Retrieves a full list of wikis to be scraped
-
-import asyncio
-import csv
-import urllib.parse
-
-from bs4 import BeautifulSoup
-
-from proxy_magic_session import get_async_session
-
-
-async def main():
-    with open("fandom_wikis_210224.csv", "w", newline="") as f:
-        writer = csv.writer(f)
-        session = get_async_session()
-        root = "https://community.fandom.com"
-        r = await session.get(f"{root}/wiki/Special:NewWikis?limit=500")
-        if r.status_code == 200:
-            nrow = 0
-            soup = BeautifulSoup(r.text, "lxml")
-            for doms in soup.select(".mw-spcontent li > a"):
-                href: str = doms.get("href", "")
-                if href:
-                    parsed = urllib.parse.urlparse(href)
-
-                    domain = parsed.netloc
-                    if parsed.path.strip("/"):
-                        sp = f"{parsed.path}wiki/"
-                    else:
-                        sp = "/wiki/"
-                    print("Add wiki:", domain, "|", doms.get_text().strip())
-                    writer.writerow([domain, doms.get_text().strip(), sp, 0])
-                    nrow += 1
-            next_page = soup.find("a", attrs={"rel": "next", "class": "mw-nextlink"})
-            if next_page:
-                next_page_url = f'{root}{next_page.get("href")}'
-            else:
-                next_page_url = None
-            while next_page_url:
-                nrow = 0
-                r = await session.get(next_page_url)
-                soup = BeautifulSoup(r.text, "lxml")
-                for doms in soup.select(".mw-spcontent li > a"):
-                    href: str = doms.get("href", "")
-                    if href:
-                        parsed = urllib.parse.urlparse(href)
-
-                        domain = parsed.netloc
-                        if parsed.path.strip("/"):
-                            sp = f"{parsed.path}wiki/"
-                        else:
-                            sp = "/wiki/"
-                        print("Add wiki:", domain, "|", doms.get_text().strip())
-                        writer.writerow([domain, doms.get_text().strip(), sp, 0])
-                        nrow += 1
-                next_page = soup.find(
-                    "a", attrs={"rel": "next", "class": "mw-nextlink"}
-                )
-                if next_page:
-                    next_page_url = f'{root}{next_page.get("href")}'
-                else:
-                    next_page_url = None
-                print(next_page_url)
-
-
-asyncio.run(main())

data/Fandom-v0.5.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f0c66575d06311ea94497ff4f62651c7b99e918ec27bbb166d49f38590591837
-size 25083924695

FandomWaifu.png → default/partial-train/0000.parquet

@@ -1,3 +1,3 @@
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-oid sha256:28c7d0bf6b483d6135308bf4c530e72dfab85973824702f6020475355f2d7f3d
-size 750240
+oid sha256:e56a01af099dcdf82920d7222b995bd66be335fda1a810671609aa716497835e
+size 261269940

v2.5-chunks-roblox-filter/fandom-ac.jsonl → default/partial-train/0001.parquet

@@ -1,3 +1,3 @@
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-size 3253909135
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+size 257377614

v2.5-chunks-roblox-filter/fandom-aa.jsonl → default/partial-train/0002.parquet

@@ -1,3 +1,3 @@
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-size 3076260389
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+size 259413806

v2.5-chunks-roblox-filter/fandom-ab.jsonl → default/partial-train/0003.parquet

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-size 2988982948
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+size 250552144

default/partial-train/0004.parquet

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+size 247534999

default/partial-train/0005.parquet

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+size 242068141

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default/partial-train/0009.parquet

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v2.5-chunks-roblox-filter/fandom-ad.jsonl

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v2.5-chunks-roblox-filter/fandom-ae.jsonl

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v2.5-chunks-roblox-filter/fandom-af.jsonl

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v2.5-chunks-roblox-filter/fandom-ag.jsonl

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