"""
JSON-optimized tokenizer.

Design principles:
  1. Structural tokens: JSON grammar symbols ({, }, [, ], :, comma) each get
     a dedicated single token — no wasted subword splits on syntax.
  2. Key vocabulary: Frequently occurring JSON keys get their own tokens
     (Key(name), Key(id), etc.), massively reducing token count for
     repetitive schemas.
  3. Type-prefixed values: Values are prefixed with a type marker
     (STR:, NUM:, BOOL:, NULL) so the tokenizer preserves JSON types
     for lossless roundtrip.
  4. BPE for value content: String and number content is tokenized via
     a BPE codec trained on JSON value distributions.
  5. Nesting tokens: [OBJ_START]/[OBJ_END] and Array(N) tokens encode
     hierarchy without ambiguity.
"""

from __future__ import annotations

import json
import re
from collections import Counter
from typing import Any, Optional, Union

from json_tokenizer.bpe import BPETrainer


# ── Structural token constants ──────────────────────────────────────────
class StructuralTokens:
    """Reserved token IDs for JSON grammar elements."""

    PAD = 0
    START = 1  # start of JSON document
    END = 2  # end of JSON document
    OBJ_START = 3  # {
    OBJ_END = 4  # }
    ARR_START = 5  # [ (generic, length encoded separately)
    ARR_END = 6  # ]
    COLON = 7  # :
    COMMA = 8  # ,
    NULL = 9  # null value
    TRUE = 10  # true
    FALSE = 11  # false
    STR_DELIM = 12  # marks start/end of a string value
    NUM_PREFIX = 13  # marks start of a number value
    KEY_PREFIX = 14  # marks start of a key (if not in key vocab)
    UNK = 15  # unknown token

    # IDs 16-31 reserved for future structural tokens
    RESERVED_END = 32

    @classmethod
    def name(cls, token_id: int) -> str:
        _names = {
            0: "[PAD]",
            1: "[START]",
            2: "[END]",
            3: "{",
            4: "}",
            5: "[",
            6: "]",
            7: ":",
            8: ",",
            9: "null",
            10: "true",
            11: "false",
            12: "[STR]",
            13: "[NUM]",
            14: "[KEY]",
            15: "[UNK]",
        }
        return _names.get(token_id, f"[RESERVED_{token_id}]")


class JSONTokenizer:
    """Tokenizer optimized for JSON structures.

    Encodes JSON into a compact token sequence with:
      - Single tokens for structural elements
      - Dedicated key tokens for common keys
      - BPE subword tokens for string/number values
      - Full roundtrip fidelity (encode → decode == original)

    Usage:
        tokenizer = JSONTokenizer()
        tokenizer.train_from_json_files(["data1.json", "data2.json"])
        ids = tokenizer.encode('{"name": "Alice", "age": 30}')
        decoded = tokenizer.decode(ids)
    """

    def __init__(
        self,
        bpe_vocab_size: int = 4096,
        max_key_vocab: int = 1024,
        min_key_freq: int = 2,
        bpe_min_freq: int = 2,
    ):
        self.bpe_vocab_size = bpe_vocab_size
        self.max_key_vocab = max_key_vocab
        self.min_key_freq = min_key_freq
        self.bpe_min_freq = bpe_min_freq

        # Key vocabulary: key_string → token_id
        self._key_to_id: dict[str, int] = {}
        self._id_to_key: dict[int, str] = {}
        self._key_offset = StructuralTokens.RESERVED_END

        # BPE for values
        self._bpe = BPETrainer(vocab_size=bpe_vocab_size, min_frequency=bpe_min_freq)
        self._bpe_offset = 0  # set after key vocab is built

        # Full vocab
        self._id_to_token: dict[int, str] = {}
        self._token_to_id: dict[str, int] = {}
        self._trained = False

    @property
    def vocab_size(self) -> int:
        """Total vocabulary size."""
        if not self._trained:
            return StructuralTokens.RESERVED_END
        return self._bpe_offset + len(self._bpe.vocab)

    # ── Training ────────────────────────────────────────────────────────

    def train(self, json_objects: list[Any]) -> None:
        """Train the tokenizer from a list of parsed JSON objects.

        Extracts keys for the key vocabulary and values for BPE training.

        Args:
            json_objects: List of parsed JSON values (dicts, lists, primitives).
        """
        key_counter: Counter[str] = Counter()
        value_strings: list[str] = []

        for obj in json_objects:
            self._extract_keys_and_values(obj, key_counter, value_strings)

        # Build key vocabulary from most common keys
        top_keys = [
            k
            for k, count in key_counter.most_common(self.max_key_vocab)
            if count >= self.min_key_freq
        ]

        self._key_to_id = {}
        self._id_to_key = {}
        for i, key in enumerate(top_keys):
            tid = self._key_offset + i
            self._key_to_id[key] = tid
            self._id_to_key[tid] = key

        # BPE offset is after key vocab
        self._bpe_offset = self._key_offset + len(self._key_to_id)

        # Train BPE on value strings
        if value_strings:
            self._bpe.train(value_strings)

        # Build full vocab lookup
        self._build_vocab_lookup()
        self._trained = True

    def train_from_json_strings(self, json_strings: list[str]) -> None:
        """Train from raw JSON strings."""
        objects = []
        for s in json_strings:
            try:
                objects.append(json.loads(s))
            except json.JSONDecodeError:
                continue
        self.train(objects)

    def train_from_json_files(self, file_paths: list[str]) -> None:
        """Train from JSON files (one JSON object per file, or JSONL)."""
        objects = []
        for path in file_paths:
            with open(path) as f:
                content = f.read().strip()
                # Try as single JSON object
                try:
                    obj = json.loads(content)
                    if isinstance(obj, list):
                        objects.extend(obj)
                    else:
                        objects.append(obj)
                    continue
                except json.JSONDecodeError:
                    pass
                # Try as JSONL
                for line in content.splitlines():
                    line = line.strip()
                    if line:
                        try:
                            objects.append(json.loads(line))
                        except json.JSONDecodeError:
                            continue
        self.train(objects)

    def _extract_keys_and_values(
        self,
        obj: Any,
        key_counter: Counter[str],
        value_strings: list[str],
    ) -> None:
        """Recursively extract keys and value strings from a JSON object."""
        if isinstance(obj, dict):
            for key, value in obj.items():
                key_counter[key] += 1
                # Also train BPE on key strings (they appear as values too)
                value_strings.append(key)
                self._extract_keys_and_values(value, key_counter, value_strings)
        elif isinstance(obj, list):
            for item in obj:
                self._extract_keys_and_values(item, key_counter, value_strings)
        elif isinstance(obj, str):
            value_strings.append(obj)
        elif isinstance(obj, (int, float)):
            value_strings.append(str(obj))
        # bool and None don't need BPE (they're structural tokens)

    def _build_vocab_lookup(self) -> None:
        """Build the complete id↔token mappings."""
        self._id_to_token = {}
        self._token_to_id = {}

        # Structural tokens
        for i in range(StructuralTokens.RESERVED_END):
            name = StructuralTokens.name(i)
            self._id_to_token[i] = name
            self._token_to_id[name] = i

        # Key tokens
        for key, tid in self._key_to_id.items():
            token_name = f"Key({key})"
            self._id_to_token[tid] = token_name
            self._token_to_id[token_name] = tid

        # BPE tokens
        for bpe_token, bpe_id in self._bpe.vocab.items():
            full_id = self._bpe_offset + bpe_id
            self._id_to_token[full_id] = f"BPE({bpe_token})"
            self._token_to_id[f"BPE({bpe_token})"] = full_id

    # ── Encoding ────────────────────────────────────────────────────────

    def encode(self, json_input: Union[str, Any]) -> list[int]:
        """Encode a JSON string or parsed object into token IDs.

        Args:
            json_input: Either a JSON string or an already-parsed Python object.

        Returns:
            List of integer token IDs.
        """
        if isinstance(json_input, str):
            try:
                obj = json.loads(json_input)
            except json.JSONDecodeError:
                raise ValueError(f"Invalid JSON: {json_input[:100]}...")
        else:
            obj = json_input

        tokens = [StructuralTokens.START]
        self._encode_value(obj, tokens)
        tokens.append(StructuralTokens.END)
        return tokens

    def _encode_value(self, value: Any, tokens: list[int]) -> None:
        """Recursively encode a JSON value into tokens."""
        if isinstance(value, dict):
            self._encode_object(value, tokens)
        elif isinstance(value, list):
            self._encode_array(value, tokens)
        elif isinstance(value, str):
            self._encode_string(value, tokens)
        elif isinstance(value, bool):
            # Must check bool before int (bool is subclass of int in Python)
            tokens.append(StructuralTokens.TRUE if value else StructuralTokens.FALSE)
        elif isinstance(value, (int, float)):
            self._encode_number(value, tokens)
        elif value is None:
            tokens.append(StructuralTokens.NULL)
        else:
            tokens.append(StructuralTokens.UNK)

    def _encode_object(self, obj: dict, tokens: list[int]) -> None:
        """Encode a JSON object."""
        tokens.append(StructuralTokens.OBJ_START)
        for i, (key, value) in enumerate(obj.items()):
            if i > 0:
                tokens.append(StructuralTokens.COMMA)
            self._encode_key(key, tokens)
            tokens.append(StructuralTokens.COLON)
            self._encode_value(value, tokens)
        tokens.append(StructuralTokens.OBJ_END)

    def _encode_array(self, arr: list, tokens: list[int]) -> None:
        """Encode a JSON array."""
        tokens.append(StructuralTokens.ARR_START)
        for i, item in enumerate(arr):
            if i > 0:
                tokens.append(StructuralTokens.COMMA)
            self._encode_value(item, tokens)
        tokens.append(StructuralTokens.ARR_END)

    def _encode_key(self, key: str, tokens: list[int]) -> None:
        """Encode a JSON key — uses key vocab if available, else BPE."""
        if key in self._key_to_id:
            tokens.append(self._key_to_id[key])
        else:
            tokens.append(StructuralTokens.KEY_PREFIX)
            bpe_ids = self._bpe.encode_to_ids(key)
            tokens.extend(self._bpe_offset + bid for bid in bpe_ids)

    def _encode_string(self, value: str, tokens: list[int]) -> None:
        """Encode a JSON string value."""
        tokens.append(StructuralTokens.STR_DELIM)
        if value:  # don't BPE-encode empty strings
            bpe_ids = self._bpe.encode_to_ids(value)
            tokens.extend(self._bpe_offset + bid for bid in bpe_ids)
        tokens.append(StructuralTokens.STR_DELIM)

    def _encode_number(self, value: Union[int, float], tokens: list[int]) -> None:
        """Encode a JSON number value."""
        tokens.append(StructuralTokens.NUM_PREFIX)
        # Preserve int vs float distinction
        if isinstance(value, float) and value == int(value) and "." in str(value):
            text = str(value)
        elif isinstance(value, int):
            text = str(value)
        else:
            text = repr(value)
        bpe_ids = self._bpe.encode_to_ids(text)
        tokens.extend(self._bpe_offset + bid for bid in bpe_ids)

    # ── Decoding ────────────────────────────────────────────────────────

    def decode(self, token_ids: list[int]) -> str:
        """Decode token IDs back to a JSON string.

        Args:
            token_ids: List of integer token IDs from encode().

        Returns:
            JSON string faithful to the original.
        """
        obj = self._decode_to_object(token_ids)
        return json.dumps(obj, ensure_ascii=False)

    def decode_to_object(self, token_ids: list[int]) -> Any:
        """Decode token IDs back to a Python object."""
        return self._decode_to_object(token_ids)

    def _decode_to_object(self, token_ids: list[int]) -> Any:
        """Parse token IDs back into a Python object."""
        # Strip START/END
        ids = list(token_ids)
        if ids and ids[0] == StructuralTokens.START:
            ids = ids[1:]
        if ids and ids[-1] == StructuralTokens.END:
            ids = ids[:-1]

        result, _ = self._parse_value(ids, 0)
        return result

    def _parse_value(self, ids: list[int], pos: int) -> tuple[Any, int]:
        """Parse a single value starting at position pos."""
        if pos >= len(ids):
            return None, pos

        tid = ids[pos]

        if tid == StructuralTokens.OBJ_START:
            return self._parse_object(ids, pos)
        elif tid == StructuralTokens.ARR_START:
            return self._parse_array(ids, pos)
        elif tid == StructuralTokens.STR_DELIM:
            return self._parse_string(ids, pos)
        elif tid == StructuralTokens.NUM_PREFIX:
            return self._parse_number(ids, pos)
        elif tid == StructuralTokens.NULL:
            return None, pos + 1
        elif tid == StructuralTokens.TRUE:
            return True, pos + 1
        elif tid == StructuralTokens.FALSE:
            return False, pos + 1
        else:
            return None, pos + 1

    def _parse_object(self, ids: list[int], pos: int) -> tuple[dict, int]:
        """Parse a JSON object from token IDs."""
        assert ids[pos] == StructuralTokens.OBJ_START
        pos += 1
        result: dict[str, Any] = {}

        while pos < len(ids) and ids[pos] != StructuralTokens.OBJ_END:
            if ids[pos] == StructuralTokens.COMMA:
                pos += 1
                continue

            # Parse key
            key, pos = self._parse_key(ids, pos)

            # Expect colon
            if pos < len(ids) and ids[pos] == StructuralTokens.COLON:
                pos += 1

            # Parse value
            value, pos = self._parse_value(ids, pos)
            result[key] = value

        if pos < len(ids) and ids[pos] == StructuralTokens.OBJ_END:
            pos += 1

        return result, pos

    def _parse_array(self, ids: list[int], pos: int) -> tuple[list, int]:
        """Parse a JSON array from token IDs."""
        assert ids[pos] == StructuralTokens.ARR_START
        pos += 1
        result: list[Any] = []

        while pos < len(ids) and ids[pos] != StructuralTokens.ARR_END:
            if ids[pos] == StructuralTokens.COMMA:
                pos += 1
                continue

            value, pos = self._parse_value(ids, pos)
            result.append(value)

        if pos < len(ids) and ids[pos] == StructuralTokens.ARR_END:
            pos += 1

        return result, pos

    def _parse_key(self, ids: list[int], pos: int) -> tuple[str, int]:
        """Parse a key from token IDs."""
        tid = ids[pos]

        # Check key vocabulary
        if tid in self._id_to_key:
            return self._id_to_key[tid], pos + 1

        # KEY_PREFIX → BPE-encoded key
        if tid == StructuralTokens.KEY_PREFIX:
            pos += 1
            bpe_tokens: list[str] = []
            while pos < len(ids) and ids[pos] >= self._bpe_offset:
                bpe_id = ids[pos] - self._bpe_offset
                bpe_tokens.append(self._bpe.id_to_token(bpe_id))
                pos += 1
                # Stop before COLON
                if pos < len(ids) and ids[pos] == StructuralTokens.COLON:
                    break
            return self._bpe.decode_tokens(bpe_tokens), pos

        return f"<unknown_key_{tid}>", pos + 1

    def _parse_string(self, ids: list[int], pos: int) -> tuple[str, int]:
        """Parse a string value from token IDs."""
        assert ids[pos] == StructuralTokens.STR_DELIM
        pos += 1

        bpe_tokens: list[str] = []
        while pos < len(ids) and ids[pos] != StructuralTokens.STR_DELIM:
            bpe_id = ids[pos] - self._bpe_offset
            bpe_tokens.append(self._bpe.id_to_token(bpe_id))
            pos += 1

        # Skip closing delimiter
        if pos < len(ids) and ids[pos] == StructuralTokens.STR_DELIM:
            pos += 1

        return self._bpe.decode_tokens(bpe_tokens), pos

    def _parse_number(self, ids: list[int], pos: int) -> tuple[Union[int, float], int]:
        """Parse a number value from token IDs."""
        assert ids[pos] == StructuralTokens.NUM_PREFIX
        pos += 1

        bpe_tokens: list[str] = []
        while pos < len(ids):
            tid = ids[pos]
            if tid < self._bpe_offset:
                break  # hit a structural token
            bpe_id = tid - self._bpe_offset
            bpe_tokens.append(self._bpe.id_to_token(bpe_id))
            pos += 1

        text = self._bpe.decode_tokens(bpe_tokens).strip()
        try:
            if "." in text or "e" in text.lower():
                return float(text), pos
            return int(text), pos
        except ValueError:
            return 0, pos

    # ── Inspection / Debug ──────────────────────────────────────────────

    def decode_tokens_readable(self, token_ids: list[int]) -> list[str]:
        """Convert token IDs to human-readable token names."""
        result: list[str] = []
        for tid in token_ids:
            if tid in self._id_to_token:
                result.append(self._id_to_token[tid])
            elif tid in self._id_to_key:
                result.append(f"Key({self._id_to_key[tid]})")
            else:
                bpe_id = tid - self._bpe_offset
                token_str = self._bpe.id_to_token(bpe_id)
                result.append(f"BPE({repr(token_str)})")
        return result

    def token_count(self, json_input: Union[str, Any]) -> int:
        """Count tokens for a JSON input without materializing full list."""
        return len(self.encode(json_input))

    # ── Persistence ─────────────────────────────────────────────────────

    def save(self, directory: str) -> None:
        """Save the full tokenizer state to a directory."""
        import os

        os.makedirs(directory, exist_ok=True)

        # Save BPE model
        self._bpe.save(os.path.join(directory, "bpe_model.json"))

        # Save key vocabulary and config
        config = {
            "version": "json-tokenizer-v1",
            "bpe_vocab_size": self.bpe_vocab_size,
            "max_key_vocab": self.max_key_vocab,
            "min_key_freq": self.min_key_freq,
            "bpe_min_freq": self.bpe_min_freq,
            "key_vocab": self._key_to_id,
            "key_offset": self._key_offset,
            "bpe_offset": self._bpe_offset,
        }
        with open(os.path.join(directory, "tokenizer_config.json"), "w") as f:
            json.dump(config, f, indent=2)

    @classmethod
    def load(cls, directory: str) -> "JSONTokenizer":
        """Load a trained tokenizer from a directory."""
        import os

        with open(os.path.join(directory, "tokenizer_config.json")) as f:
            config = json.load(f)

        tokenizer = cls(
            bpe_vocab_size=config["bpe_vocab_size"],
            max_key_vocab=config["max_key_vocab"],
            min_key_freq=config["min_key_freq"],
            bpe_min_freq=config["bpe_min_freq"],
        )

        # Restore key vocab
        tokenizer._key_to_id = config["key_vocab"]
        tokenizer._id_to_key = {int(v): k for k, v in config["key_vocab"].items()}
        tokenizer._key_offset = config["key_offset"]
        tokenizer._bpe_offset = config["bpe_offset"]

        # Load BPE
        tokenizer._bpe = BPETrainer.load(os.path.join(directory, "bpe_model.json"))

        tokenizer._build_vocab_lookup()
        tokenizer._trained = True
        return tokenizer