Some update

data_prep.ipynb

@@ -1,165 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "dc45342a",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31mJupyter cannot be started. Error attempting to locate Jupyter: Running cells with 'Python 3.12.2' requires the notebook package.\n",
-      "\u001b[1;31mInstall 'jupyter and notebook' into the Python environment. \n",
-      "\u001b[1;31mCommand: 'python -m pip install jupyter notebook -U\n",
-      "\u001b[1;31mor\n",
-      "\u001b[1;31mconda install jupyter notebook -U'\n",
-      "\u001b[1;31mClick <a href='https://aka.ms/installJupyterForVSCode'>here</a> for more info."
-     ]
-    }
-   ],
-   "source": [
-    "import orjson\n",
-    "from tqdm import tqdm\n",
-    "\n",
-    "INPUT = \"datasets/gh_25_github_io_repos_collapsed.jsonl\"\n",
-    "OUTPUT = \"datasets/gh_25_github_io_repos_filtered.jsonl\"\n",
-    "\n",
-    "USEFUL_EXTS = {\n",
-    "    \".html\", \".css\", \".js\", \".ts\", \".tsx\", \".jsx\",\n",
-    "    \".vue\", \".astro\", \".scss\", \".sass\", \".less\", \".py\"\n",
-    "}\n",
-    "\n",
-    "NON_USEFUL_EXTS = {\n",
-    "    \".md\", \".rst\", \".txt\"\n",
-    "}\n",
-    "\n",
-    "CONFIG_EXTS = {\n",
-    "    \".yml\", \".yaml\", \".json\", \".toml\"\n",
-    "}\n",
-    "\n",
-    "MIN_TOTAL_FILES = 10\n",
-    "MIN_TOTAL_SIZE = 100_000\n",
-    "MIN_USEFUL_FRACTION = 0.7\n",
-    "MAX_NON_USEFUL_FRACTION = 0.2\n",
-    "\n",
-    "\n",
-    "def is_good_web_repo(obj):\n",
-    "    paths = obj[\"file_path\"]\n",
-    "    sizes = obj[\"size\"]\n",
-    "\n",
-    "    total_files = len(paths)\n",
-    "    total_size = sum(sizes)\n",
-    "\n",
-    "    if total_files < MIN_TOTAL_FILES:\n",
-    "        return False\n",
-    "    if total_size < MIN_TOTAL_SIZE:\n",
-    "        return False\n",
-    "\n",
-    "    useful = non_useful = config = 0\n",
-    "\n",
-    "    for p in paths:\n",
-    "        p = p.lower()\n",
-    "        if any(p.endswith(ext) for ext in USEFUL_EXTS):\n",
-    "            useful += 1\n",
-    "        elif any(p.endswith(ext) for ext in NON_USEFUL_EXTS):\n",
-    "            non_useful += 1\n",
-    "        elif any(p.endswith(ext) for ext in CONFIG_EXTS):\n",
-    "            config += 1\n",
-    "\n",
-    "    useful_frac = useful / total_files\n",
-    "    non_useful_frac = non_useful / total_files\n",
-    "\n",
-    "    if non_useful_frac > MAX_NON_USEFUL_FRACTION:\n",
-    "        return False\n",
-    "\n",
-    "    return useful_frac >= MIN_USEFUL_FRACTION\n",
-    "\n",
-    "\n",
-    "kept = 0\n",
-    "with open(INPUT, \"rb\") as fin, open(OUTPUT, \"wb\") as fout:\n",
-    "    for line in tqdm(fin, desc=\"Filtering repos\"):\n",
-    "        obj = orjson.loads(line)\n",
-    "        if is_good_web_repo(obj):\n",
-    "            fout.write(orjson.dumps(obj) + b\"\\n\")\n",
-    "            kept += 1\n",
-    "\n",
-    "print(f\"✅ Kept {kept} high-quality web repos\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4da42790",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from datasets import load_dataset\n",
-    "\n",
-    "# Load your dataset (replace with the actual dataset path or name)\n",
-    "ds = load_dataset(\"Ayush-Singh/stack-githubio-live\", split=\"train\")\n",
-    "\n",
-    "USEFUL_WEB_LANGS = {\n",
-    "    \"HTML\", \"CSS\", \"JavaScript\", \"TypeScript\", \"TSX\", \"JSX\",\n",
-    "    \"Vue\", \"Astro\", \"SCSS\", \"Sass\", \"Less\", \"Python\"\n",
-    "}\n",
-    "\n",
-    "NON_USEFUL_DOMINANT_LANGS = {\n",
-    "    \"Markdown\", \"RMarkdown\", \"R\", \"Jupyter Notebook\"\n",
-    "}\n",
-    "\n",
-    "MIN_USEFUL_FRACTION = 0.7\n",
-    "MIN_TOTAL_FILES = 5\n",
-    "MIN_TOTAL_LINES = 2000\n",
-    "\n",
-    "def is_prod_web_repo(repo):\n",
-    "    lang_frac = repo.get(\"repo_language_fraction_dict\", {})\n",
-    "    \n",
-    "    useful_fraction = sum(\n",
-    "        frac for lang, frac in lang_frac.items() if lang in USEFUL_WEB_LANGS and frac\n",
-    "    )\n",
-    "    \n",
-    "    non_useful_fraction = sum(\n",
-    "        frac for lang, frac in lang_frac.items() if lang in NON_USEFUL_DOMINANT_LANGS and frac\n",
-    "    )\n",
-    "    \n",
-    "    if non_useful_fraction > 0.2:\n",
-    "        return False\n",
-    "    if repo.get(\"repo_total_files\", 0) < MIN_TOTAL_FILES:\n",
-    "        return False\n",
-    "    if repo.get(\"repo_total_num_lines\", 0) < MIN_TOTAL_LINES:\n",
-    "        return False\n",
-    "    \n",
-    "    return useful_fraction >= MIN_USEFUL_FRACTION\n",
-    "\n",
-    "# Filter HF dataset\n",
-    "prod_web_repos = ds.filter(is_prod_web_repo)\n",
-    "\n",
-    "print(f\"Found {len(prod_web_repos)} production-level web repos\")"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "DeepLearning",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.16"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}

gh_25_stack_heuristic_hexo_static_jekyll_dataset/stack_githubio_cwv_heuristic_results.jsonl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7182cd6f082ff51e8b88b5a8faae6cfcbfb32fc8df00925b20300180bc6d463b
+oid sha256:f17aab05d9d0e68cc683a00b784b8cc52b342c4d1802a065fb691efbe6fc15b0
 size 32324582

successful_visual_verified_repos.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e41e128918becfb25ba95a835cba5e207e3606e11b70b967d85a622e92fd3cef
+size 384340