import json from functools import reduce from pathlib import Path from typing import TypedDict import toml import heurams.kernel.particles as pt from ...utils.lict import Lict class RepoManifest(TypedDict): title: str author: str desc: str class Repo: file_mapping = { "schedule": "schedule.toml", "payload": "payload.toml", "algodata": "algodata.json", "manifest": "manifest.toml", "typedef": "typedef.toml", } type_mapping = { "schedule": "dict", "payload": "lict", "algodata": "lict", "manifest": "dict", "typedef": "dict", } default_save_list = ["algodata"] def __init__( self, schedule: dict, payload: Lict, manifest: dict, typedef: dict, algodata: Lict, source=None, ) -> None: self.schedule: dict = schedule self.manifest: RepoManifest = manifest # type: ignore self.typedef: dict = typedef self.payload: Lict = payload self.algodata: Lict = algodata self.source: Path | None = source # 若存在, 指向 repo 所在 dir self.database = { "schedule": self.schedule, "payload": self.payload, "manifest": self.manifest, "typedef": self.typedef, "algodata": self.algodata, "source": self.source, } self.generate_particles_data() def generate_particles_data(self): self.nucleonic_data_lict = Lict( initlist=list(map(self._nucleonic_proc, self.payload)) ) self.orbitic_data = self.schedule self.ident_index = self.nucleonic_data_lict.keys() for i in self.ident_index: self.algodata.append_new((i, {})) self.electronic_data_lict = self.algodata def _nucleonic_proc(self, unit): ident = unit[0] common = self.typedef["common"] return (ident, (unit[1], common)) @staticmethod def _merge(value): def inner(x): return (x, value) return inner def __len__(self): return len(self.payload) def __repr__(self): from pprint import pformat s = pformat(self.database, indent=4) return s def persist_to_repodir( self, save_list: list | None = None, source: Path | None = None ): if save_list == None: save_list = self.default_save_list if self.source != None and source == None: source = self.source if source == None: raise FileNotFoundError("不存在仓库到文件的映射") source.mkdir(parents=True, exist_ok=False) for keyname in save_list: filename = self.file_mapping[keyname] with open(source / filename, "w") as f: try: dict_data = self.database[keyname].dicted_data except: dict_data = dict(self.database[keyname]) if filename.endswith("toml"): toml.dump(dict_data, f) elif filename.endswith("json"): json.dump(dict_data, f) else: raise ValueError(f"不支持的文件类型: {filename}") def export_to_single_dict(self): return self.database @classmethod def create_new_repo(cls, source=None): default_database = { "schedule": {}, "payload": Lict([]), "algodata": Lict([]), "manifest": {}, "typedef": {}, "source": source, } return Repo(**default_database) @classmethod def create_from_repodir(cls, source: Path): database = {} for keyname, filename in cls.file_mapping.items(): with open(source / filename, "r") as f: loaded: dict if filename.endswith("toml"): loaded = toml.load(f) elif filename.endswith("json"): loaded = json.load(f) else: raise ValueError(f"不支持的文件类型: {filename}") if cls.type_mapping[keyname] == "lict": database[keyname] = Lict(list(loaded.items())) elif cls.type_mapping[keyname] == "dict": database[keyname] = loaded else: raise ValueError(f"不支持的数据容器: {cls.type_mapping[keyname]}") database["source"] = source return Repo(**database) @classmethod def create_from_single_dict(cls, dictdata, source: Path | None = None): database = dictdata database["source"] = source return Repo(**database) @classmethod def check_repodir(cls, source: Path): try: cls.create_from_repodir(source) return 1 except: return 0 @classmethod def probe_vaild_repos_in_dir(cls, folder: Path): lst = list() for i in folder.iterdir(): if i.is_dir(): if cls.check_repodir(i): lst.append(i) return lst