import enum import json from collections.abc import Sequence from typing import Any, Dict, List, Optional, TypeVar, Union import requests from fasthtml.common import Select from loguru import logger from monsterui.franken import ( Card, CardTitle, Div, Grid, LabelCheckboxX, Option, ) from pydantic.fields import ComputedFieldInfo, FieldInfo from pydantic_core import PydanticUndefined from akkudoktoreos.config.config import ConfigEOS from akkudoktoreos.core.pydantic import PydanticBaseModel from akkudoktoreos.server.dash.components import ( HTMX_INCLUDE, ConfigCard, ConfigSection, Input, ) from akkudoktoreos.server.dash.context import request_url_for from akkudoktoreos.server.dash.eosstatus import eos_pvlib_cec_names, eos_server_address from akkudoktoreos.server.dash.itemscard import ConfigItemsCard from akkudoktoreos.server.dash.mapcard import ConfigMapCard from akkudoktoreos.server.dash.uihints import ( LAZY_OPTIONS_SOURCES, UI_HINTS, register_lazy_options_source, resolve_form_factory, ) T = TypeVar("T") # Latest configuration update results # Dictionary of config names and associated dictionary with keys "value", "result", "error", "open". config_update_latest: dict[str, dict[str, Optional[Union[str, bool]]]] = {} # Current state of config displayed config_visible: dict[str, dict] = { "config-visible-read-only": { "label": "Configuration (read-only)", "visible": False, }, } def get_nested_value( dictionary: Union[Dict[str, Any], List[Any]], keys: Sequence[Union[str, int]], default: Optional[T] = None, ) -> Union[Any, T]: """Retrieve a nested value from a dictionary or list using a sequence of keys. Args: dictionary (Union[Dict[str, Any], List[Any]]): The nested dictionary or list to search. keys (Sequence[Union[str, int]]): A sequence of keys or indices representing the path to the desired value. default (Optional[T]): A value to return if the path is not found. Returns: Union[Any, T]: The value at the specified nested path, or the default value if not found. Raises: TypeError: If the input is not a dictionary or list, or if keys are not a sequence. KeyError: If a key is not found in a dictionary. IndexError: If an index is out of range in a list. """ if not isinstance(dictionary, (dict, list)): raise TypeError("The first argument must be a dictionary or list") if not isinstance(keys, Sequence): raise TypeError("Keys must be provided as a sequence (e.g., list, tuple)") if not keys: return dictionary try: # Traverse the structure current = dictionary for key in keys: if isinstance(current, dict): current = current[str(key)] elif isinstance(current, list): current = current[int(key)] else: raise KeyError(f"Invalid key or index: {key}") return current except (KeyError, IndexError, TypeError): return default def get_field_extra_dict( subfield_info: Union[FieldInfo, ComputedFieldInfo], ) -> Dict[str, Any]: """Extract json_schema_extra. Extract regardless of whether it is defined directly on the field (Pydantic v2) or inherited from v1 compatibility wrappers. Always returns a dictionary. """ # Pydantic v2 location extra = getattr(subfield_info, "json_schema_extra", None) if isinstance(extra, dict): return extra # Pydantic v1 compatibility fallbacks fi = getattr(subfield_info, "field_info", None) if fi is not None: extra = getattr(fi, "json_schema_extra", None) if isinstance(extra, dict): return extra return {} def get_description( subfield_info: Union[FieldInfo, ComputedFieldInfo], extra: Dict[str, Any], ) -> str: """Fetch description. Priority: 1) json_schema_extra["description"] 2) field_info.description 3) empty string """ if "description" in extra: return str(extra["description"]) desc = getattr(subfield_info, "description", None) return str(desc) if desc is not None else "" def get_deprecated( subfield_info: Union[FieldInfo, ComputedFieldInfo], extra: Dict[str, Any], ) -> Optional[Any]: """Fetch deprecated. Priority: 1) json_schema_extra["deprecated"] 2) field_info.deprecated 3) None """ if "deprecated" in extra: return extra["deprecated"] return getattr(subfield_info, "deprecated", None) def get_scope( extra: Dict[str, Any], ) -> Optional[list[str]]: """Fetch x-scope. Returns the value of json_schema_extra["x-scope"] as a list of strings, or None if not set. """ scope = extra.get("x-scope") if scope is None: return None if isinstance(scope, list): return [str(s) for s in scope] return [str(scope)] def get_default_value(field_info: Union[FieldInfo, ComputedFieldInfo], regular_field: bool) -> Any: """Retrieve the default value of a field as a JSON-safe Python object. Handles both ``default`` and ``default_factory`` fields, and converts the resulting value to a JSON-safe representation before returning. This covers all non-primitive default types encountered in the EOS config models: Pydantic model instances, lists of models, enums, ``Path`` objects, and anything else that plain ``json.dumps`` would reject. For computed fields or fields with no default of any kind, a sentinel string is returned instead. Args: field_info: The field metadata from Pydantic. regular_field: ``True`` for a ``FieldInfo`` (regular field), ``False`` for a ``ComputedFieldInfo``. Returns: A JSON-safe Python object (dict, list, str, int, float, bool, or ``None``) representing the field default, or ``"N/A"`` when no meaningful default exists. """ import pathlib if not regular_field or not isinstance(field_info, FieldInfo): return "N/A" # Resolve the raw default — prefer plain default, fall back to factory if field_info.default is not PydanticUndefined: val = field_info.default elif field_info.default_factory is not None: try: val = field_info.get_default(call_default_factory=True) except Exception: return "" else: return "" def _to_json_safe(v: Any) -> Any: """Recursively convert a value to a JSON-safe type.""" if v is None or isinstance(v, (bool, int, float, str)): return v if isinstance(v, PydanticBaseModel): return v.model_dump(mode="json") if isinstance(v, enum.Enum): return v.value if isinstance(v, pathlib.PurePath): return str(v) if isinstance(v, dict): return {str(k): _to_json_safe(w) for k, w in v.items()} if isinstance(v, (list, tuple, set, frozenset)): return [_to_json_safe(item) for item in v] # Last resort: str() — at minimum json.dumps won't crash return str(v) return _to_json_safe(val) def resolve_nested_types(field_type: Any, parent_types: list[str]) -> list[tuple[Any, list[str]]]: """Resolve nested types within a field and return their structure. Args: field_type (Any): The type of the field to resolve. parent_types (List[str]): A list of parent type names. Returns: List[tuple[Any, List[str]]]: A list of tuples containing resolved types and their parent hierarchy. """ resolved_types: list[tuple[Any, list[str]]] = [] origin = getattr(field_type, "__origin__", field_type) if origin is Union: for arg in getattr(field_type, "__args__", []): if arg is not type(None): resolved_types.extend(resolve_nested_types(arg, parent_types)) else: resolved_types.append((field_type, parent_types)) return resolved_types def create_config_details( model: type[PydanticBaseModel] | type[ConfigEOS], values: dict, values_prefix: list[str] = [] ) -> dict[str, dict]: """Generate configuration details based on provided values and model metadata. Args: model: An EOS model or the top-level settings class to extract configuration from. values (dict): A dictionary containing the current configuration values. values_prefix (list[str]): A list of parent type names that prefixes the model values in the values. Returns: dict[dict]: A dictionary of configuration details, each represented as a dictionary. """ config_details: dict[str, dict] = {} def extract_nested_models( subfield_info: Union[ComputedFieldInfo, FieldInfo], parent_types: list[str], visited: frozenset, ) -> None: nonlocal values, values_prefix regular_field = isinstance(subfield_info, FieldInfo) subtype = ( subfield_info.annotation if isinstance(subfield_info, FieldInfo) else subfield_info.return_type ) nested_types = resolve_nested_types(subtype, []) found_basic = False for nested_type, nested_parent_types in nested_types: if not isinstance(nested_type, type) or not issubclass(nested_type, PydanticBaseModel): if found_basic: continue extra = get_field_extra_dict(subfield_info) config: dict[str, Optional[Any]] = {} config["name"] = ".".join(values_prefix + parent_types) config["value"] = json.dumps( get_nested_value(values, values_prefix + parent_types, "") ) config["default"] = json.dumps(get_default_value(subfield_info, regular_field)) config["description"] = get_description(subfield_info, extra) config["deprecated"] = get_deprecated(subfield_info, extra) config["scope"] = get_scope(extra) if isinstance(subfield_info, ComputedFieldInfo): config["read-only"] = "ro" type_description = str(subfield_info.return_type) else: config["read-only"] = "rw" type_description = str(subfield_info.annotation) config["type"] = ( type_description.replace("typing.", "") .replace("pathlib.", "") .replace("NoneType", "None") .replace("", "float") ) config_details[str(config["name"])] = config found_basic = True else: if nested_type in visited: # Genuine cycle along this path (self-referential model) — stop # recursing here, but do NOT block sibling branches elsewhere. continue new_parent_types = parent_types + nested_parent_types new_visited = visited | {nested_type} for nested_field_name, nested_field_info in list( nested_type.model_fields.items() ) + list(nested_type.model_computed_fields.items()): extract_nested_models( nested_field_info, new_parent_types + [nested_field_name], new_visited, ) for field_name, field_info in list(model.model_fields.items()) + list( model.model_computed_fields.items() ): extract_nested_models(field_info, [field_name], frozenset()) return config_details def get_config(eos_host: str, eos_port: Union[str, int]) -> dict[str, Any]: """Fetch configuration data from the specified EOS server. Args: eos_host (str): The hostname of the EOS server. eos_port (Union[str, int]): The port of the EOS server. Returns: dict[str, Any]: A dict of configuration data. """ server = f"http://{eos_host}:{eos_port}" # Get current configuration from server try: result = requests.get(f"{server}/v1/config", timeout=10) result.raise_for_status() config = result.json() except requests.exceptions.HTTPError as e: config = {} detail = result.json()["detail"] warning_msg = f"Can not retrieve configuration from {server}: {e}, {detail}" logger.warning(warning_msg) return config def config_matches_search(config: dict, search: str) -> bool: if not search: return True return ( search in config["name"].lower() or search in config["description"].lower() or search in config["type"].lower() or search in config["value"].lower() ) # --------------------- # Lazy Options Handling # --------------------- def _fetch_cec_names(kind: str) -> tuple[str, ...]: """Fetch CEC module or inverter names from the EOS server. Cached per kind for the EOSdash process lifetime — the CEC database is static. Args: kind: "modules" or "inverters". """ global eos_server_address, eos_pvlib_cec_names if kind in eos_pvlib_cec_names: # Already cached return eos_pvlib_cec_names[kind] if eos_server_address is None: logger.warning( f"EOS server address not yet known: `{eos_server_address}`; cannot fetch CEC {kind}" ) return () host, port = eos_server_address # host = "127.0.0.1" # port = 8503 server = f"http://{host}:{port}" path = f"/v1/prediction/pvforecast/pvlib/{kind}" try: result = requests.get(f"{server}{path}", timeout=10) result.raise_for_status() data = result.json() names = tuple(data) if isinstance(data, list) else tuple(data.keys()) eos_pvlib_cec_names[kind] = names except requests.exceptions.RequestException as e: logger.warning(f"Can not retrieve CEC {kind} from {server}: {e}") return () logger.info(f"Fetched CEC {kind}") return names def _cec_modules_source() -> list[str]: return list(_fetch_cec_names("modules")) def _cec_inverters_source() -> list[str]: return list(_fetch_cec_names("inverters")) register_lazy_options_source("pvlib.modules", _cec_modules_source) register_lazy_options_source("pvlib.inverters", _cec_inverters_source) def config_options( options_source: str, search: str, select_id: str, name: str, current: str ) -> Select: """Return a filtered, capped