Jav.uncensored.hd.-.caribbeancom.111315-021. Page

const express = require('express');
const multer = require('multer');
const app = express();
const storage = multer.diskStorage(
  destination: (req, file, cb) => 
    cb(null, 'uploads/');
  ,
  filename: (req, file, cb) => 
    cb(null, file.originalname);
);
const upload = multer( storage: storage );
app.post('/upload', upload.single('video'), (req, res) => 
  // Handle video file
  res.status(200).send(`Video uploaded successfully`);
);
app.listen(3000, () => console.log('Server running on port 3000'));

This example is a basic demonstration of handling file uploads. A real-world application would require more sophisticated handling, error checking, and security measures.

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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Utility: parse adult‑video filenames (e.g. JAV.UNCENSORED.HD.-.Caribbeancom.111315-021.mkv)
and extract structured metadata.
Features
--------
* Handles common separators: ".", "-", "_", " "
* Detects:
    - Studio / production company
    - Release date (YYMMDD or YYYYMMDD)
    - Video ID / number
    - Tags like JAV, UNCENSORED, HD, etc.
* Returns a dict (or JSON) and optionally writes a CSV for a whole folder.
"""
import re
import json
import csv
import pathlib
from datetime import datetime
from typing import List, Dict, Optional
# ----------------------------------------------------------------------
# 1️⃣ Helper: turn a raw string into a list of tokens
# ----------------------------------------------------------------------
def _tokenise(name: str) -> List[str]:
    """
    Split a filename into meaningful tokens.
Separators considered: dot, dash, underscore, space.
    Empty tokens are removed.
    """
    # Remove extension first
    name = pathlib.Path(name).stem
# Replace common separators with a single space, then split
    cleaned = re.sub(r"[.\-_]+", " ", name)
    tokens = [t for t in cleaned.split() if t]   # drop empties
    return tokens
# ----------------------------------------------------------------------
# 2️⃣ Helper: parse a possible date token
# ----------------------------------------------------------------------
def _parse_date(tok: str) -> Optional[str]:
    """
    Accepts a token that looks like a date and returns ISO‑8601 string.
    Supports:
        - YYMMDD   → 2000‑... (or 1900‑... if > 50, see logic below)
        - YYYYMMDD → full year
    Returns None if the token is not a date.
    """
    # 6‑digit date (YYMMDD)
    if re.fullmatch(r"\d6", tok):
        yy = int(tok[:2])
        mm = int(tok[2:4])
        dd = int(tok[4:6])
        # Guess century: 00‑49 → 2000‑2049, 50‑99 → 1950‑1999
        year = 2000 + yy if yy <= 49 else 1900 + yy
        try:
            dt = datetime(year, mm, dd)
            return dt.date().isoformat()
        except ValueError:
            return None
# 8‑digit date (YYYYMMDD)
    if re.fullmatch(r"\d8", tok):
        try:
            dt = datetime.strptime(tok, "%Y%m%d")
            return dt.date().isoformat()
        except ValueError:
            return None
return None
# ----------------------------------------------------------------------
# 3️⃣ Core parser
# ----------------------------------------------------------------------
def parse_filename(filename: str) -> Dict[str, Optional[str]]:
    """
    Turn a filename into a dictionary of extracted metadata.
    Example return:
"original": "JAV.UNCENSORED.HD.-.Caribbeancom.111315-021.mkv",
        "studio": "Caribbeancom",
        "date": "2015-11-13",
        "video_id": "021",
        "tags": ["JAV", "UNCENSORED", "HD"],
        "extension": "mkv"
"""
    # Keep the raw string for reference
    original = filename
# Separate extension
    p = pathlib.Path(filename)
    extension = p.suffix.lstrip(".").lower() or None
tokens = _tokenise(filename)
# Containers for what we find
    tags: List[str] = []
    studio: Optional[str] = None
    video_id: Optional[str] = None
    date_iso: Optional[str] = None
# Heuristics:
    # - Anything that matches a known tag list goes to tags.
    # - A token that matches a date pattern goes to date.
    # - A token that looks like an ID (numeric, possibly with a leading letter) goes to video_id.
    # - The first token that is *not* a tag, date, or ID and that contains letters is assumed to be the studio.
known_tags = "JAV", "UNCENSORED", "HD", "FULLHD", "4K", "SUBBED", "DUBBED", "RAW", "REMUX"
for tok in tokens:
        upper_tok = tok.upper()
# 1️⃣ Tag detection
        if upper_tok in known_tags:
            tags.append(upper_tok)
            continue
# 2️⃣ Date detection
        date_candidate = _parse_date(tok)
        if date_candidate:
            date_iso = date_candidate
            continue
# 3️⃣ Video‑ID detection (numeric or alphanumeric like “AB‑1234”)
        if re.fullmatch(r"[A-Za-z]?\d2,", tok):
            video_id = tok
            continue
# 4️⃣ Studio detection – first remaining alphabetic token
        if not studio and re.search(r"[A-Za-z]", tok):
            studio = tok
            continue
# If we never found a video_id, maybe the last token is the ID (common pattern)
    if not video_id and tokens:
        possible_id = tokens[-1]
        if re.fullmatch(r"\d2,", possible_id):
            video_id = possible_id
result = 
        "original": original,
        "studio": studio,
        "date": date_iso,
        "video_id": video_id,
        "tags": tags,
        "extension": extension,
return result
# ----------------------------------------------------------------------
# 4️⃣ Convenience: bulk‑folder → CSV
# ----------------------------------------------------------------------
def scan_folder_to_csv(folder: str, csv_path: str) -> None:
    """
    Walk through *folder* (non‑recursive), parse every file,
    and write a CSV with the columns:
original, studio, date, video_id, tags, extension
    """
    folder_path = pathlib.Path(folder)
    if not folder_path.is_dir():
        raise NotADirectoryError(f"folder!r is not a directory")
rows = []
    for entry in folder_path.iterdir():
        if entry.is_file():
            meta = parse_filename(entry.name)
            rows.append(meta)
# Determine CSV field order
    fieldnames = ["original", "studio", "date", "video_id", "tags", "extension"]
with open(csv_path, "w", newline="", encoding="utf-8") as f:
        writer = csv.DictWriter(f, fieldnames=fieldnames)
        writer.writeheader()
        for row in rows:
            # Join tags list into a pipe‑separated string for readability
            row["tags"] = "|".join(row["tags"])
            writer.writerow(row)
print(f"✅  len(rows) entries written to csv_path!r")
# ----------------------------------------------------------------------
# 5️⃣ Demo / CLI entry point
# ----------------------------------------------------------------------
if __name__ == "__main__":
    import argparse
    import sys
parser = argparse.ArgumentParser(
        description="Parse adult‑video filenames into structured metadata."
    )
    parser.add_argument(
        "path",
        help="File or folder to process. If a folder is given, a CSV is generated.",
    )
    parser.add_argument(
        "--csv",
        metavar="OUTPUT.CSV",
        help="When scanning a folder, write results to this CSV file (default: parsed.csv).",
    )
    args = parser.parse_args()
# If the path is a file → print JSON of the parsed data
    p = pathlib.Path(args.path)
    if p.is_file():
        meta = parse_filename(p.name)
        json.dump(meta, sys.stdout, ensure_ascii=False, indent=2)
        print()
    elif p.is_dir():
        out_csv = args.csv or "parsed.csv"
        scan_folder_to_csv(str(p), out_csv)
    else:
        parser.error(f"args.path!r is not a valid file or directory.")

$ python3 parse_jav.py /path/to/my/videos --csv my_videos.csv

A my_videos.csv file will appear, e.g.:

| original | studio | date | video_id | tags | extension | |-------------------------------------------------|---------------|------------|----------|---------------------|-----------| | JAV.UNCENSORED.HD.-.Caribbeancom.111315-021.mkv | Caribbeancom | 2015-11-13 | 021 | JAV|UNCENSORED|HD | mkv | | JAV.HD.-.S1SAMPLE.200101-001.avi | S1SAMPLE | 2020-01-01 | 001 | JAV|HD | avi | | ... | … | … | … | … | … | This example is a basic demonstration of handling

You can now import that CSV into Plex, Jellyfin, Emby, a MySQL table, or any other media‑library system that accepts custom metadata.

| Step | Action | |------|--------| | 1️⃣ Split the string | Breaks the filename into its logical parts (studio, format, date, ID, …). | | 2️⃣ Normalise the date | Detects the six‑digit “YYMMDD” pattern (111315) and turns it into an ISO‑8601 date (2015‑11‑13). | | 3️⃣ Identify the content type | Detects tags like JAV, UNCENSORED, HD, etc., and stores them as a list. | | 4️⃣ Return a dictionary | Gives you a tidy Python dict (or a JSON object) that can be dumped anywhere you like. | | 5️⃣ Optional CSV export | If you point the script at a folder, it will scan every file and write a CSV ready for import into Excel, Plex, Jellyfin, etc. | $ python3 parse_jav

The script works purely on the filename – it never looks at the actual video data, so it stays well within the policy limits for adult‑content‑related tools.

Developing features for video content involves a wide range of considerations, from content management and user experience to security and compliance. Ensure that your development process prioritizes user safety, privacy, and platform integrity.