├── .github └── workflows │ └── build-image.yml ├── .gitignore ├── .gitmodules ├── .python-version ├── API.md ├── Dockerfile ├── LICENSE ├── MaterialPlanning.py ├── README.md ├── data └── .gitkeep ├── demo.ipynb ├── main.py ├── owned.txt ├── price.txt ├── pyproject.toml ├── required.txt ├── requirements.txt ├── server.py ├── setup.py └── uv.lock /.github/workflows/build-image.yml: -------------------------------------------------------------------------------- 1 | name: Build Docker Image 2 | 3 | on: 4 | push: 5 | # trigger on any tag push 6 | tags: 7 | - "**" 8 | concurrency: 9 | group: ${{ github.ref }} 10 | cancel-in-progress: true 11 | 12 | jobs: 13 | build: 14 | runs-on: ubuntu-latest 15 | steps: 16 | - uses: actions/checkout@v2 17 | 18 | - name: Get Tag Version 19 | id: get_version 20 | run: | 21 | export TRUNCATED_GITHUB_SHA=$(echo ${{ github.sha }} | cut -c1-7); 22 | echo "VERSION=${GITHUB_REF/refs\/tags\//}+${TRUNCATED_GITHUB_SHA}" >> $GITHUB_ENV 23 | echo "GIT_TAG=${GITHUB_REF/refs\/tags\//}" >> $GITHUB_ENV 24 | 25 | - name: Build and Publish to Registry 26 | uses: elgohr/Publish-Docker-Github-Action@3.04 27 | with: 28 | name: penguin-statistics/planner-backend 29 | username: ${{ github.actor }} 30 | password: ${{ secrets.GITHUB_TOKEN }} 31 | registry: ghcr.io 32 | tags: "latest,${{ env.GIT_TAG }}" 33 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | __pycache__/ 2 | data/*.json 3 | .DS_Store 4 | -------------------------------------------------------------------------------- /.gitmodules: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/penguin-statistics/ArkPlanner/fe71975323fb635a296c5a0d0fdcbd82b19d122a/.gitmodules -------------------------------------------------------------------------------- /.python-version: -------------------------------------------------------------------------------- 1 | 3.13 2 | -------------------------------------------------------------------------------- /API.md: -------------------------------------------------------------------------------- 1 | # ArkPlanner API 2 | 3 | > Request URL: [https://planner.penguin-stats.io/plan](https://planner.penguin-stats.io/) 4 | > 5 | > Request Method: ```POST``` 6 | 7 | ## Post Parameters 8 | 9 | - ```owned```: *dict*({item_name(*str*): count(*int*)}) 10 | 11 | *default: {}* 12 | 13 | A dict of items owned, where keys are item names, i.e. 'D32钢', values are numbers of items owned. 14 | - ```required```: *dict*({item_name(*str*): count(*int*)}) 15 | 16 | *default: {}* 17 | 18 | A dict of items required, where keys are item names, i.e. 'D32钢', values are numbers of items required. 19 | - ```extra_outc```: *boolean* 20 | 21 | *default: False* 22 | 23 | Whether extra outcome of convertion is considered. 24 | - ```convertion_dr```: *float* **NEW** 25 | 26 | *default: 0.18* 27 | 28 | The drop rate of extra outcome. 29 | - ```exp_demand```: *boolean* or *int* 30 | 31 | *default: True* 32 | 33 | Whether Battle Record (作战记录) is considered valuable. If True, requirement of Battle Record is set to ```1e9```. If input is an integer, the requirement of experiment is set to be euqal to the input. 34 | - ```gold_demand```: *boolean* or *int* 35 | 36 | *default: True* 37 | 38 | Whether LMD (龙门币) is considered valuable. If True, requirement of LMD is set to ```1e9```. If False, the value of Pure Gold is also considered 0. If input is an integer, the requirement of LMD is set to be euqal to the input. 39 | - ```exclude```: list(str) 40 | 41 | *default: []* 42 | 43 | Stages banned during calculation. Example: ```['1-7', 'SA-5']``` 44 | - ```store```: *boolean* 45 | 46 | *default: False* 47 | 48 | Whether to response green and yellow ticket values in stores. 49 | 50 | - ```input_lang```: *string* **NEW** 51 | - ```output_lang```: *string* **NEW** 52 | 53 | Languages of input and output data. Available Languages: ```['zh', 'en', 'ja', 'ko']```, and ```'id'``` for item ids. 54 | Default value: ```input_lang = 'zh', output_lang = 'zh'``` 55 | 56 | - ```server```: *string* **NEW** 57 | 58 | Using active stages from this server. Available Servers: ```['CN', 'US', 'JP', 'KR']```. 59 | Default value: ```server = 'CN'``` 60 | 61 | 62 | ## Response Parameters 63 | - ```cost``` : *int* 64 | 65 | Expected sanity cost. 66 | - ```gcost``` : *int* 67 | 68 | Expected gold cost in convertion. 69 | - ```gold``` : *int* 70 | 71 | Expected gold gain in farming. 72 | - ```exp``` : *int* 73 | 74 | Expected exp gain in farming. Pure Gold not included. 75 | - ```stages```: *list(stage*) 76 | 77 | ``` 78 | stage = { 79 | 'stage': str, # stage name, eg. '1-7' 80 | 'count': int, # times to farm 81 | 'items': dict{str: int} # item_name: item_count 82 | } 83 | ``` 84 | 85 | Stages recommended to farm. 86 | - ```syntheses```: *list(synthesis)* 87 | 88 | ``` 89 | synthesis= { 90 | 'target': str, # target item name 91 | 'count': int, # times to convert 92 | 'materials': dict{str: int} # converted_item_name: item_count 93 | } 94 | ``` 95 | 96 | Convertions recommended. 97 | - ```values```: *dict* {level *(str)*: value *(dict)* } 98 | 99 | ``` 100 | value = { 101 | 'name': str, # item name 102 | 'value': float # item value 103 | } 104 | ``` 105 | 106 | Item values. 107 | - ```green```: *dict* {item *(str)*: value *(float)* } 108 | - ```yellow```: *dict* {item *(str)*: value *(float)* } 109 | 110 | Value of one piece of green/yellow ticket when buying target items in the store. 111 | 112 | -------------------------------------------------------------------------------- /Dockerfile: -------------------------------------------------------------------------------- 1 | FROM python:3.10.2-slim-bullseye 2 | 3 | LABEL org.opencontainers.image.source = "https://github.com/penguin-statistics/ArkPlanner" 4 | 5 | COPY . . 6 | 7 | RUN apt-get update && apt-get install -y \ 8 | tini 9 | # Tini is now available at /usr/bin/tini 10 | 11 | RUN pip install --no-cache-dir -r requirements.txt 12 | 13 | EXPOSE 8020 14 | 15 | ENTRYPOINT ["/usr/bin/tini", "--"] 16 | CMD [ "python", "-m", "sanic", "server.app", "--host=0.0.0.0", "--port=8020", "--workers=2" ] -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2019 Yaochen Xie 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /MaterialPlanning.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import urllib.request, json, time, os, copy, sys 3 | from scipy.optimize import linprog 4 | from collections import defaultdict as ddict 5 | 6 | global penguin_url, headers, LanguageMap 7 | penguin_url = 'https://penguin-stats.io/PenguinStats/api/v2/' 8 | headers = {'User-Agent':'ArkPlanner'} 9 | LanguageMap = {'CN': 'zh', 'US': 'en', 'JP': 'ja', 'KR': 'ko'} 10 | 11 | Price = dict() 12 | with open('price.txt', 'r', encoding='utf8') as f: 13 | for line in f.readlines(): 14 | name, value = line.split() 15 | Price[name] = int(value) 16 | 17 | class MaterialPlanning(object): 18 | def __init__(self, 19 | filter_freq=200, 20 | filter_stages=[], 21 | url_stats='result/matrix?show_closed_zone=true', 22 | url_rules='formula', 23 | path_stats='data/matrix.json', 24 | path_rules='data/formula.json', 25 | update=False, 26 | banned_stages={}, 27 | # expValue=30, 28 | # ConvertionDR=0.18, 29 | display_main_only=True): 30 | """ 31 | Object initialization. 32 | Args: 33 | filter_freq: int or None. The lowest frequence that we consider. 34 | No filter will be applied if None. 35 | url_stats: string. url to the dropping rate stats data. 36 | url_rules: string. url to the composing rules data. 37 | path_stats: string. local path to the dropping rate stats data. 38 | path_rules: string. local path to the composing rules data. 39 | """ 40 | self.banned_stages = banned_stages # for debugging 41 | self.display_main_only = display_main_only 42 | self.ConvertionDR = 0.18 # send actual convertion_dr in get_plan 43 | 44 | self.update(force=update, 45 | filter_freq=filter_freq, 46 | filter_stages=filter_stages, 47 | url_stats=url_stats, 48 | url_rules=url_rules, 49 | path_stats=path_stats, 50 | path_rules=path_rules) 51 | 52 | def get_item_id(self): 53 | items = get_json('items') 54 | item_array, item_id_to_name = [], {} 55 | item_name_to_id = {'id': {}, 56 | 'zh': {}, 57 | 'en': {}, 58 | 'ja': {}, 59 | 'ko': {}} 60 | 61 | additional_items = [ 62 | {'itemId': '4001', 'name_i18n': {'ko': '용문폐', 'ja': '龍門幣', 'en': 'LMD', 'zh': '龙门币'}}, 63 | {'itemId': '0010', 'name_i18n': {'ko': '작전기록', 'ja': '作戦記録', 'en': 'Battle Record', 'zh': '作战记录'}} 64 | ] 65 | for x in items + additional_items: 66 | item_array.append(x['itemId']) 67 | item_id_to_name.update({x['itemId']: {'id': x['itemId'], 68 | 'zh': x['name_i18n']['zh'], 69 | 'en': x['name_i18n']['en'], 70 | 'ja': x['name_i18n']['ja'], 71 | 'ko': x['name_i18n']['ko']}}) 72 | item_name_to_id['id'].update({x['itemId']: x['itemId']}) 73 | item_name_to_id['zh'].update({x['name_i18n']['zh']: x['itemId']}) 74 | item_name_to_id['en'].update({x['name_i18n']['en']: x['itemId']}) 75 | item_name_to_id['ja'].update({x['name_i18n']['ja']: x['itemId']}) 76 | item_name_to_id['ko'].update({x['name_i18n']['ko']: x['itemId']}) 77 | 78 | self.item_array = item_array 79 | self.item_id_to_name = item_id_to_name 80 | self.item_name_to_id = item_name_to_id 81 | self.item_dct_rv = {v: k for k, v in enumerate(item_array)} # from id to idx 82 | self.item_name_rv = {item_id_to_name[v]['zh']: k for k, v in enumerate(item_array)} # from (zh) name to idx 83 | 84 | 85 | def _pre_processing(self, material_probs): 86 | """ 87 | Compute costs, convertion rules and items probabilities from requested dictionaries. 88 | Args: 89 | material_probs: List of dictionaries recording the dropping info per stage per item. 90 | Keys of instances: ["itemID", "times", "itemName", "quantity", "apCost", "stageCode", "stageID"]. 91 | convertion_rules: List of dictionaries recording the rules of composing. 92 | Keys of instances: ["id", "name", "level", "source", "madeof"]. 93 | """ 94 | # construct item id projections. 95 | # construct stage id projections. 96 | stage_array = [] 97 | for drop in material_probs['matrix']: 98 | if drop['stageId'] not in stage_array: 99 | stage_array.append(drop['stageId']) 100 | stage_dct_rv = {v: k for k, v in enumerate(stage_array)} 101 | servers = ['CN', 'US', 'JP', 'KR'] 102 | # CN have to be the first one, which contain all possible stages 103 | languages = ['zh', 'en', 'ja', 'ko'] 104 | 105 | valid_stages = {server: [False]*len(stage_array) for server in servers} 106 | stage_code = {server: ['' for _ in stage_array] for server in servers} 107 | complete_stage_list = {server: [] for server in servers} 108 | stage_update_list = {server: [] for server in servers} 109 | stages = {} 110 | stage_name_rv = {lang: {} for lang in languages} 111 | stage_id_to_name = {} 112 | for server in servers: 113 | try: 114 | stages[server] = get_json(f'stages?server={server}') 115 | stages[server] = [stage for stage in stages[server] if stage['existence'][server]['exist']] 116 | except Exception as e: 117 | print(f'Failed to load server {server}, Error: {e}') 118 | return -1 119 | for stage in stages[server]: 120 | if stage['code'] not in complete_stage_list[server]: 121 | complete_stage_list[server].append(stage['code']) 122 | if stage['stageId'] not in stage_dct_rv or 'dropInfos' not in stage: 123 | if stage['code'][:2] in ['SK', 'AP', 'CE', 'LS', 'PR']: 124 | stage_update_list[server].append(stage) 125 | continue 126 | valid_stages[server][stage_dct_rv[stage['stageId']]] = True 127 | stage_code[server][stage_dct_rv[stage['stageId']]] = stage['code_i18n'][LanguageMap[server]] 128 | for lang in languages: 129 | stagecode = stage['code_i18n'][lang] 130 | if stagecode not in stage_name_rv[lang]: 131 | stage_name_rv[lang][stagecode] = [] 132 | stage_name_rv[lang][stagecode].append(stage_dct_rv[stage['stageId']]) 133 | stage_id_to_name[stage['stageId']] = {lang: stage['code_i18n'][lang] for lang in languages} 134 | # Fix KeyError('id') 135 | stage_id_to_name[stage['stageId']]["id"] = stage['stageId'] 136 | 137 | try: 138 | self.get_item_id() 139 | except Exception as e: 140 | print(f'Failed to load item list, Error: {e}') 141 | return -1 142 | 143 | self.complete_stage_list = complete_stage_list 144 | self.stage_array = stage_array 145 | self.stage_dct_rv = stage_dct_rv 146 | self.stage_code = stage_code 147 | self.valid_stages = valid_stages 148 | self.stage_name_rv = stage_name_rv 149 | self.stage_id_to_name = stage_id_to_name 150 | 151 | # To format dropping records into sparse probability matrix 152 | self.cost_lst = np.zeros(len(self.stage_array)) 153 | 154 | for server in servers: 155 | for stage in stages[server]: 156 | if stage['stageId'] in self.stage_dct_rv: 157 | self.cost_lst[self.stage_dct_rv[stage['stageId']]] = stage['apCost'] 158 | 159 | for server in servers: 160 | #print([stage['code'] for stage in stage_update_list[server]]) 161 | for stage in stage_update_list[server]: 162 | if stage['stageId'] not in self.stage_array: 163 | self.stage_array.append(stage['stageId']) 164 | self.stage_dct_rv.update({stage['stageId']: len(self.stage_array)-1}) 165 | for a_server in servers: 166 | self.valid_stages[a_server].append(False) 167 | self.stage_code[a_server].append('') 168 | self.cost_lst = np.append(self.cost_lst, stage['apCost']) 169 | self.valid_stages[server][stage_dct_rv[stage['stageId']]] = True 170 | self.stage_code[server][stage_dct_rv[stage['stageId']]] = stage['code_i18n'][LanguageMap[server]] 171 | for lang in languages: 172 | stagecode = stage['code_i18n'][lang] 173 | if stagecode not in stage_name_rv[lang]: 174 | self.stage_name_rv[lang][stagecode] = [] 175 | self.stage_name_rv[lang][stagecode].append(stage_dct_rv[stage['stageId']]) 176 | self.stage_id_to_name[stage['stageId']] = {lang: stage['code_i18n'][lang] for lang in languages} 177 | self.stage_id_to_name[stage['stageId']]["id"] = stage['stageId'] 178 | 179 | self.stage_array = np.array(self.stage_array) 180 | self.probs_matrix = np.zeros([len(self.stage_array), len(self.item_array)]) 181 | 182 | for drop in material_probs['matrix']: 183 | try: 184 | end = drop.get('end', None) 185 | if end is not None and round(time.time()*1000) >= end: 186 | continue 187 | self.probs_matrix[self.stage_dct_rv[drop['stageId']], self.item_dct_rv[drop['itemId']]] = drop['quantity']/float(drop['times']) 188 | except: 189 | print(f'Failed to parse {drop}. (出现此条请带报错信息联系根派)') 190 | 191 | # 添加所有关卡的龙门币掉落 192 | for k, stage in enumerate(self.stage_array): 193 | self.probs_matrix[k, self.item_name_rv['龙门币']] = self.cost_lst[k]*12 194 | self.update_droprate() 195 | 196 | # To build equivalence relationship from convert_rule_dct. 197 | self.update_convertion() 198 | self.convertions_dct = {} 199 | convertion_matrix = [] 200 | convertion_outc_matrix = [] 201 | convertion_cost_lst = [] 202 | for rule in self.convertion_rules: 203 | convertion = np.zeros(len(self.item_array)) 204 | convertion[self.item_name_rv[rule['name']]] = 1 205 | 206 | comp_dct = {comp['name']:comp['count'] for comp in rule['costs']} 207 | self.convertions_dct[rule['name']] = comp_dct 208 | for iname in comp_dct: 209 | convertion[self.item_name_rv[iname]] -= comp_dct[iname] 210 | convertion[self.item_name_rv['龙门币']] -= rule['goldCost'] 211 | convertion_matrix.append(copy.deepcopy(convertion)) 212 | 213 | outc_dct = {outc['name']:outc['count'] for outc in rule['extraOutcome']} 214 | outc_wgh = {outc['name']:outc['weight'] for outc in rule['extraOutcome']} 215 | weight_sum = float(rule['totalWeight']) 216 | for iname in outc_dct: 217 | convertion[self.item_name_rv[iname]] += outc_dct[iname]*self.ConvertionDR*outc_wgh[iname]/weight_sum 218 | convertion_outc_matrix.append(convertion) 219 | convertion_cost_lst.append(1e-8 * rule['goldCost']) 220 | # a small factor, since here we do not know whether we demand gold or not 221 | 222 | self.convertion_matrix = np.array(convertion_matrix) 223 | self.convertion_outc_matrix = np.array(convertion_outc_matrix) 224 | self.convertion_cost_lst = convertion_cost_lst 225 | 226 | 227 | def _set_lp_parameters(self): 228 | """ 229 | Object initialization. 230 | Args: 231 | convertion_matrix: matrix of shape [n_rules, n_items]. 232 | Each row represent a rule. 233 | convertion_cost_lst: list. Cost in equal value to the currency spent in convertion. 234 | probs_matrix: sparse matrix of shape [n_stages, n_items]. 235 | Items per clear (probabilities) at each stage. 236 | cost_lst: list. Costs per clear at each stage. 237 | """ 238 | assert len(self.probs_matrix)==len(self.cost_lst) 239 | assert len(self.convertion_matrix)==len(self.convertion_cost_lst) 240 | assert self.probs_matrix.shape[1]==self.convertion_matrix.shape[1] 241 | 242 | 243 | def update(self, 244 | filter_freq=200, 245 | filter_stages=[], 246 | url_stats='result/matrix?show_closed_zone=true', 247 | url_rules='formula', 248 | path_stats='data/matrix.json', 249 | path_rules='data/formula.json', 250 | force=True): 251 | """ 252 | To update parameters when probabilities change or new items added. 253 | Args: 254 | url_stats: string. url to the dropping rate stats data. 255 | url_rules: string. url to the composing rules data. 256 | path_stats: string. local path to the dropping rate stats data. 257 | path_rules: string. local path to the composing rules data. 258 | """ 259 | print(f'Start to update data {time.asctime(time.localtime(time.time()))}.') 260 | if not force: # if not force to update, try loading data from file. 261 | try: 262 | material_probs, self.convertion_rules = load_data(path_stats, path_rules) 263 | except: # loading failed, try loading from server. 264 | force = True 265 | if force: # load from server. 266 | try: 267 | print('Requesting data from web resources (i.e., penguin-stats.io)...', end=' ') 268 | material_probs, self.convertion_rules = request_data(penguin_url+url_stats, penguin_url+url_rules, path_stats, path_rules) 269 | print('done.') 270 | except: 271 | return 272 | 273 | if filter_freq: 274 | filtered_probs = [] 275 | for drop in material_probs['matrix']: 276 | if drop['times']>=filter_freq and drop['stageId'] not in filter_stages: 277 | filtered_probs.append(drop) 278 | material_probs['matrix'] = filtered_probs 279 | 280 | if self._pre_processing(material_probs) != -1: 281 | self._set_lp_parameters() 282 | 283 | 284 | def _get_plan_no_prioties(self, demand_lst, outcome, gold_demand, exp_demand, convertion_dr, probs_matrix, convertion_matrix, convertion_outc_matrix, cost_lst, convertion_cost_lst): 285 | """ 286 | To solve linear programming problem without prioties. 287 | Args: 288 | demand_lst: list of materials demand. Should include all items (zero if not required). 289 | Returns: 290 | strategy: list of required clear times for each stage. 291 | fun: estimated total cost. 292 | """ 293 | if convertion_dr != 0.18: 294 | convertion_outc_matrix = (convertion_outc_matrix - convertion_matrix)/0.18*convertion_dr+convertion_matrix 295 | A_ub = (np.vstack([probs_matrix, convertion_outc_matrix]) 296 | if outcome else np.vstack([probs_matrix, convertion_matrix])).T 297 | cost = (np.hstack([cost_lst, convertion_cost_lst])) 298 | assert np.any(cost_lst>=0) 299 | 300 | excp_factor = 1.0 301 | dual_factor = 1.0 302 | 303 | while excp_factor>1e-7: 304 | solution = linprog(c=cost, 305 | A_ub=-A_ub, 306 | b_ub=-np.array(demand_lst)*excp_factor, 307 | method='interior-point') 308 | if solution.status != 4: 309 | break 310 | 311 | excp_factor /= 10.0 312 | 313 | while dual_factor>1e-7: 314 | dual_solution = linprog(c=-np.array(demand_lst)*excp_factor*dual_factor, 315 | A_ub=A_ub.T, 316 | b_ub=cost, 317 | method='interior-point') 318 | if solution.status != 4: 319 | break 320 | 321 | dual_factor /= 10.0 322 | 323 | 324 | return solution, dual_solution, excp_factor 325 | 326 | 327 | def get_plan(self, requirement_dct={}, deposited_dct={}, 328 | print_output=True, outcome=False, gold_demand=True, exp_demand=True, exclude=[], 329 | store=False, convertion_dr=0.18, input_lang='zh', output_lang='zh', server='CN'): 330 | """ 331 | User API. Computing the material plan given requirements and owned items. 332 | Args: 333 | requirement_dct: dictionary. Contain only required items with their numbers. 334 | deposit_dct: dictionary. Contain only owned items with their numbers. 335 | """ 336 | status_dct = {0: 'Optimization terminated successfully. ', 337 | 1: 'Iteration limit reached. ', 338 | 2: 'Problem appears to be infeasible. ', 339 | 3: 'Problem appears to be unbounded. ', 340 | 4: 'Numerical difficulties encountered.'} 341 | 342 | demand_lst = np.zeros(len(self.item_array)) 343 | for k, v in requirement_dct.items(): 344 | demand_lst[self.item_dct_rv[self.item_name_to_id[input_lang][k]]] = v 345 | if gold_demand: 346 | try: 347 | demand_lst[self.item_name_rv['龙门币']] = 1e9 if gold_demand is True else int(gold_demand) 348 | except: 349 | demand_lst[self.item_name_rv['龙门币']] = 1e9 350 | if exp_demand: 351 | try: 352 | demand_lst[self.item_name_rv['作战记录']] = 1e9 if exp_demand is True else int(exp_demand) 353 | except: 354 | demand_lst[self.item_name_rv['作战记录']] = 1e9 355 | for k, v in deposited_dct.items(): 356 | demand_lst[self.item_dct_rv[self.item_name_to_id[input_lang][k]]] -= v 357 | 358 | if gold_demand == False and exp_demand == True: 359 | # 如果不需要龙门币 并 需要经验, 就删掉赤金到经验的转化 360 | convertion_matrix = self.convertion_matrix[:-1] 361 | convertion_outc_matrix = self.convertion_outc_matrix[:-1] 362 | convertion_cost_lst = self.convertion_cost_lst[:-1] 363 | else: 364 | convertion_matrix = self.convertion_matrix 365 | convertion_outc_matrix = self.convertion_outc_matrix 366 | convertion_cost_lst = self.convertion_cost_lst 367 | 368 | def alive(stage): 369 | if stage in exclude: 370 | return False 371 | if self.stage_code[server][self.stage_dct_rv[stage]] in exclude: 372 | return False 373 | return self.valid_stages[server][self.stage_dct_rv[stage]] 374 | 375 | 376 | is_stage_alive = [alive(stage) for stage in self.stage_array] 377 | stage_array = self.stage_array[is_stage_alive] 378 | cost_lst = self.cost_lst[is_stage_alive] 379 | probs_matrix = self.probs_matrix[is_stage_alive] 380 | stage_dct_rv = {v:k for k,v in enumerate(stage_array)} 381 | 382 | solution, dual_solution, excp_factor = self._get_plan_no_prioties( 383 | demand_lst, outcome, gold_demand, exp_demand, convertion_dr, probs_matrix, 384 | convertion_matrix, convertion_outc_matrix, cost_lst, convertion_cost_lst) 385 | x, status = solution.x/excp_factor, solution.status 386 | y, slack = dual_solution.x, dual_solution.slack 387 | n_looting, n_convertion = x[:len(cost_lst)], x[len(cost_lst):] 388 | 389 | if status != 0: 390 | raise ValueError(status_dct[status]) 391 | 392 | values = [{"level":'1', "items":[]}, 393 | {"level":'2', "items":[]}, 394 | {"level":'3', "items":[]}, 395 | {"level":'4', "items":[]}, 396 | {"level":'5', "items":[]}] 397 | 398 | item_values = dict() 399 | 400 | for i, item in enumerate(self.item_array): 401 | if y[i] >= 0 and '作战记录' not in self.item_id_to_name[item]['zh'] and\ 402 | self.item_id_to_name[item]['zh'] not in ['龙门币', '赤金', '碳', '碳素', '碳素组', '经验', '家具'] and\ 403 | '技巧概要' not in self.item_id_to_name[item]['zh']: 404 | if y[i]>0.1: 405 | item_value = { 406 | "name": self.item_id_to_name[item][output_lang], 407 | "value": '%.2f'%y[i] 408 | } 409 | else: 410 | item_value = { 411 | "name": self.item_id_to_name[item][output_lang], 412 | "value": '%.5f'%(y[i]) 413 | } 414 | if self.item_array[i][-1] in '12345' and len(self.item_array[i]) == 5: 415 | values[int(self.item_array[i][-1])-1]['items'].append(item_value) 416 | item_values[item] = y[i] 417 | 418 | for group in values: 419 | group["items"] = sorted(group["items"], key=lambda k: float(k['value']), reverse=True) 420 | 421 | cost = np.dot(x[:len(cost_lst)], cost_lst) 422 | gcost = -np.dot(x[len(cost_lst):], convertion_matrix[:, self.item_name_rv['龙门币']]) 423 | gold = np.dot(n_looting, probs_matrix[:, self.item_name_rv['龙门币']]) 424 | exp = np.dot(n_looting, probs_matrix[:, self.item_name_rv['基础作战记录']])*200 +\ 425 | np.dot(n_looting, probs_matrix[:, self.item_name_rv['初级作战记录']])*400 +\ 426 | np.dot(n_looting, probs_matrix[:, self.item_name_rv['中级作战记录']])*1000 +\ 427 | np.dot(n_looting, probs_matrix[:, self.item_name_rv['作战记录']]) 428 | 429 | stages = [] 430 | for i, t in enumerate(n_looting): 431 | if t >= 0.1: 432 | stage_name = stage_array[i] 433 | if self.is_gold_or_exp(stage_name): 434 | cost -= t*cost_lst[i] 435 | gold -= t*probs_matrix[i, self.item_name_rv['龙门币']] 436 | exp -= t*(probs_matrix[i, self.item_name_rv['基础作战记录']]*200 + 437 | probs_matrix[i, self.item_name_rv['初级作战记录']]*400 + 438 | probs_matrix[i, self.item_name_rv['中级作战记录']]*1000 + 439 | probs_matrix[i, self.item_name_rv['作战记录']]) 440 | if self.stage_code['CN'][self.stage_dct_rv[stage_name]][:2] in ['SK', 'AP', 'CE', 'LS', 'PR'] and\ 441 | self.display_main_only: 442 | continue 443 | target_items = np.where(probs_matrix[i]>0.02)[0] 444 | items = {self.item_id_to_name[self.item_array[idx]][output_lang]: float2str(probs_matrix[i, idx]*t) 445 | for idx in target_items if len(self.item_array[idx])==5 and self.item_array[idx] != 'furni'} 446 | stage = { 447 | "stageId": stage_array[i], 448 | "stage": self.stage_id_to_name[stage_array[i]][output_lang], 449 | "count": float2str(t), 450 | "items": items 451 | } 452 | stages.append(stage) 453 | 454 | 455 | syntheses = [] 456 | for i,t in enumerate(n_convertion): 457 | if t >= 0.1: 458 | target_item = self.item_array[np.argmax(convertion_matrix[i])] 459 | if self.item_id_to_name[target_item]['zh'] in ['作战记录', '龙门币']: 460 | # 不显示经验和龙门币的转化 461 | continue 462 | materials = {self.item_id_to_name[self.item_name_to_id['zh'][k]][output_lang]: f'{v * t:.1f}' 463 | for k, v in self.convertions_dct[self.item_id_to_name[target_item]['zh']].items()} 464 | synthesis = { 465 | "target": self.item_id_to_name[target_item][output_lang], 466 | "count": str(int(t+0.9)), 467 | "materials": materials 468 | } 469 | syntheses.append(synthesis) 470 | 471 | res = { 472 | "cost": int(cost), 473 | "gcost": int(gcost), 474 | 'gold': int(gold), 475 | 'exp': int(exp), 476 | "stages": stages, 477 | "syntheses": syntheses, 478 | "values": list(reversed(values)) 479 | } 480 | 481 | if store: 482 | green = {item['name']: '%.3f' % (float(item['value'])/Price[self.item_id_to_name[self.item_name_to_id[output_lang][item['name']]]['zh']]) for item in values[2]['items']} 483 | yellow = {item['name']: '%.3f' % (float(item['value'])/Price[self.item_id_to_name[self.item_name_to_id[output_lang][item['name']]]['zh']]) for item in values[3]['items']} 484 | 485 | res.update({'green': green, 486 | 'yellow': yellow}) 487 | 488 | if print_output: 489 | print('Estimated total cost: %d, gold: %d, exp: %d.'%(res['cost'], res['gold'], res['exp'])) 490 | print('Loot at following stages:') 491 | for stage in stages: 492 | display_lst = [k + '(%s) '%stage['items'][k] for k in stage['items']] 493 | print('Stage ' + self.stage_code[server][self.stage_dct_rv[stage['stageId']]] 494 | + '(%s times) ===> '%stage['count'] + ', '.join(display_lst)) 495 | 496 | print('\nSynthesize following items:') 497 | for synthesis in syntheses: 498 | display_lst = [k + '(%s) '%synthesis['materials'][k] for k in synthesis['materials']] 499 | print(synthesis['target'] + '(%s) <=== '%synthesis['count'] 500 | + ', '.join(display_lst)) 501 | 502 | print('\nItems Values:') 503 | for i, group in reversed(list(enumerate(values))): 504 | display_lst = ['%s:%s'%(item['name'], item['value']) for item in group['items']] 505 | print('Level %d items: '%(i+1)) 506 | print(', '.join(display_lst)) 507 | return res 508 | 509 | def is_gold_or_exp(self, stage_name): 510 | return self.stage_code['CN'][self.stage_dct_rv[stage_name]][:2] in ['LS', 'CE'] 511 | 512 | def update_droprate(self): 513 | self.update_droprate_processing('1-1', '龙门币', 660, 'update') 514 | self.update_droprate_processing('2-7', '龙门币', 1500, 'update') 515 | self.update_droprate_processing('3-6', '龙门币', 2040, 'update') 516 | self.update_droprate_processing('4-1', '龙门币', 2700, 'update') 517 | self.update_droprate_processing('6-1', '龙门币', 1216, 'update') 518 | self.update_droprate_processing('7-3', '龙门币', 1216, 'update') 519 | self.update_droprate_processing('R8-1', '龙门币', 2700, 'update') 520 | self.update_droprate_processing('R8-4', '龙门币', 1216, 'update') 521 | self.update_droprate_processing('9-2', '龙门币', 2700, 'update') 522 | self.update_droprate_processing('9-3', '龙门币', 1216, 'update') 523 | self.update_droprate_processing('10-8', '龙门币', 3480, 'update') 524 | 525 | self.update_droprate_processing('S2-2', '龙门币', 1020, 'update') 526 | self.update_droprate_processing('S4-6', '龙门币', 3480, 'update') 527 | self.update_droprate_processing('S5-2', '龙门币', 2700, 'update') 528 | self.update_droprate_processing('S5-3', '龙门币', 1216, 'update') 529 | self.update_droprate_processing('S5-5', '龙门币', 1216, 'update') 530 | self.update_droprate_processing('S6-2', '龙门币', 1216, 'update') 531 | self.update_droprate_processing('S6-4', '龙门币', 2700, 'update') 532 | self.update_droprate_processing('S7-1', '龙门币', 2700, 'update') 533 | self.update_droprate_processing('S7-2', '龙门币', 1216, 'update') 534 | 535 | self.update_droprate_processing('CE-1', '龙门币', 1700, 'update') 536 | self.update_droprate_processing('CE-2', '龙门币', 2800, 'update') 537 | self.update_droprate_processing('CE-3', '龙门币', 4100, 'update') 538 | self.update_droprate_processing('CE-4', '龙门币', 5700, 'update') 539 | self.update_droprate_processing('CE-5', '龙门币', 7500, 'update') 540 | self.update_droprate_processing('CE-6', '龙门币', 10000, 'update') 541 | 542 | self.update_droprate_processing('LS-6', '高级作战记录', 4, 'update') 543 | self.update_droprate_processing('LS-6', '中级作战记录', 2, 'update') 544 | 545 | #self.update_droprate_processing('LS-1', '作战记录', 1600, 'update') 546 | #self.update_droprate_processing('LS-2', '作战记录', 2800, 'update') 547 | #self.update_droprate_processing('LS-3', '作战记录', 3900, 'update') 548 | #self.update_droprate_processing('LS-4', '作战记录', 5900, 'update') 549 | #self.update_droprate_processing('LS-5', '作战记录', 7400, 'update') 550 | 551 | def update_convertion_processing(self, target_item: tuple, cost: int, source_item: dict, extraOutcome: dict): 552 | ''' 553 | target_item: (item, itemCount) 554 | cost: number of 龙门币 555 | source_item: {item: itemCount} 556 | extraOutcome: {outcome: {item: weight}, rate, totalWeight} 557 | ''' 558 | toAppend = dict() 559 | Outcome, rate, totalWeight = extraOutcome 560 | toAppend['costs'] = [{'count':x[1]/target_item[1], 'id':self.item_name_rv[x[0]], 'name':x[0]} for x in source_item.items()] 561 | toAppend['extraOutcome'] = [{'count': rate, 'id': self.item_name_rv[x[0]], 'name': x[0], 'weight': x[1]/target_item[1]} for x in Outcome.items()] 562 | toAppend['goldCost'] = cost/target_item[1] 563 | toAppend['id'] = self.item_name_to_id['zh'][target_item[0]] 564 | toAppend['name'] = target_item[0] 565 | toAppend['totalWeight'] = totalWeight 566 | self.convertion_rules.append(toAppend) 567 | 568 | def update_convertion(self): 569 | # 之前的TODO: 考虑芯片/基建材料的不同副产物掉落 <- 不做了, 一般人不用planner做芯片规划 570 | self.update_convertion_processing(('作战记录', 200), 0, {'基础作战记录': 1}, ({}, 0, 1)) 571 | self.update_convertion_processing(('作战记录', 400), 0, {'初级作战记录': 1}, ({}, 0, 1)) 572 | self.update_convertion_processing(('作战记录', 1000), 0, {'中级作战记录': 1}, ({}, 0, 1)) 573 | self.update_convertion_processing(('作战记录', 2000), 0, {'高级作战记录': 1}, ({}, 0, 1)) 574 | # 这里一定保证这一条在最后! 575 | # ENSURE THIS LINE IS THE LAST LINE! 576 | self.update_convertion_processing(('作战记录', 400), 0, {'赤金': 1}, ({}, 0, 1)) 577 | 578 | def update_stage_processing(self, stage_name: str, cost: int, code: str) -> None: 579 | if code in self.stage_array: 580 | print(f'stage {stage_name} already included') 581 | self.stage_array.append(code) 582 | self.stage_dct_rv.update({code: len(self.stage_array)-1}) 583 | if stage_name not in self.stage_name_rv['zh']: 584 | self.stage_name_rv['zh'][stage_name] = [] 585 | self.stage_name_rv['zh'][stage_name].append(len(self.stage_array)-1) 586 | 587 | self.cost_lst = np.append(self.cost_lst, cost) 588 | servers = ['CN', 'US', 'JP', 'KR'] 589 | for server in servers: 590 | self.stage_code[server].append(stage_name) 591 | self.valid_stages[server].append(True) 592 | 593 | def update_droprate_processing(self, stage, item, droprate, mode='add'): 594 | # update droprate for all stages that has code $stage 595 | if stage not in self.stage_name_rv['zh']: 596 | if stage not in self.complete_stage_list['CN']: 597 | print(f'stage {stage} not found') 598 | return 599 | if item not in self.item_name_rv: 600 | print(f'item {item} not found') 601 | return 602 | for stageid in self.stage_name_rv['zh'][stage]: 603 | itemid = self.item_name_rv[item] 604 | if mode == 'add': 605 | self.probs_matrix[stageid][itemid] += droprate 606 | elif mode == 'update': 607 | self.probs_matrix[stageid][itemid] = droprate 608 | 609 | 610 | def get_json(s): 611 | req = urllib.request.Request(penguin_url + s, None, headers) 612 | with urllib.request.urlopen(req, timeout=5) as response: 613 | return json.loads(response.read().decode()) 614 | 615 | def Cartesian_sum(arr1, arr2): 616 | arr_r = [] 617 | for arr in arr1: 618 | arr_r.append(arr+arr2) 619 | arr_r = np.vstack(arr_r) 620 | return arr_r 621 | 622 | def float2str(x, offset=0.5): 623 | 624 | if x < 1.0: 625 | out = '%.1f'%x 626 | else: 627 | out = '%d'%(int(x+offset)) 628 | return out 629 | 630 | def request_data(url_stats, url_rules, save_path_stats, save_path_rules): 631 | """ 632 | To request probability and convertion rules from web resources and store at local. 633 | Args: 634 | url_stats: string. url to the dropping rate stats data. 635 | url_rules: string. url to the composing rules data. 636 | save_path_stats: string. local path for storing the stats data. 637 | save_path_rules: string. local path for storing the composing rules data. 638 | Returns: 639 | material_probs: dictionary. Content of the stats json file. 640 | convertion_rules: dictionary. Content of the rules json file. 641 | """ 642 | try: 643 | os.mkdir(os.path.dirname(save_path_stats)) 644 | except: 645 | pass 646 | try: 647 | os.mkdir(os.path.dirname(save_path_rules)) 648 | except: 649 | pass 650 | 651 | req = urllib.request.Request(url_stats, None, headers) 652 | with urllib.request.urlopen(req, timeout=5) as response: 653 | material_probs = json.loads(response.read().decode()) 654 | with open(save_path_stats, 'w') as outfile: 655 | json.dump(material_probs, outfile) 656 | 657 | req = urllib.request.Request(url_rules, None, headers) 658 | with urllib.request.urlopen(req, timeout=5) as response: 659 | response = urllib.request.urlopen(req) 660 | convertion_rules = json.loads(response.read().decode()) 661 | with open(save_path_rules, 'w') as outfile: 662 | json.dump(convertion_rules, outfile) 663 | 664 | return material_probs, convertion_rules 665 | 666 | def load_data(path_stats, path_rules): 667 | """ 668 | To load stats and rules data from local directories. 669 | Args: 670 | path_stats: string. local path to the stats data. 671 | path_rules: string. local path to the composing rules data. 672 | Returns: 673 | material_probs: dictionary. Content of the stats json file. 674 | convertion_rules: dictionary. Content of the rules json file. 675 | """ 676 | with open(path_stats) as json_file: 677 | material_probs = json.load(json_file) 678 | with open(path_rules) as json_file: 679 | convertion_rules = json.load(json_file) 680 | 681 | return material_probs, convertion_rules 682 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | Penguin Statistics - Logo 4 | 5 | # Penguin Statistics - ArkPlanner 6 | 7 | > :heart: ArkPlanner is not possible without any of the initial founders, [@ycremar](https://github.com/ycremar) and [@SQRPI](https://github.com/SQRPI). They both contributed a whole lot to this project to make ArkPlanner eventually possible. 8 | > 9 | > This repository previously was a fork of the original ycremar/ArkPlanner repository, but later @ycremar decided to transfer the ownership to Penguin Statistics. 10 | 11 | [Web App](https://penguin-stats.io/planner) is now available at Penguin Statistics. 12 | 13 | > The previous web app have been replaced with the integrated [Planner](https://penguin-stats.io/planner) in Penguin Statistics to further integrate the experience. The previous frontend app is built from [ycremar/ArkPlanner-FrontEnd](https://github.com/ycremar/ArkPlanner-FrontEnd) and is based on the initial [vanilla version](https://ak.inva.land/) implemented by [@invisiblearts](https://github.com/invisiblearts). 14 | 15 | 明日方舟最优刷图策略规划工具，基于开源的掉落统计数据、素材合成规则以及线性规划实现。由于混合掉落、额外掉落副本的存在且各种材料掉落概率不同，在材料需求较复杂时，要刷哪些副本并不直观，大多情况下需要通过比较复杂的计算得到最优解。同时，了解刷所需材料预计消耗多少体力也会帮助你更好的规划体力。原理：将素材合成也看作一种掉落在约束中加以考虑（目标材料掉落 1，消耗的材料掉落为 -1），其 cost 为 0 或合成所需代币的等价体力消耗。 16 | 17 | ArkPlanner is a tiny python tool for the mobile game Arknights. The variety of items dropping at different stages and the complicate synthesize system make it difficult to make the most efficient plan to obtain items. ArkPlanner helps you to make the optimal plan for any given combinations of the required item based on open-sourced stats data and items synthesize rules, and linear programming algorithms. 18 | 19 | _Note: the linear programming is based on the items dropping expectations estimated by the existing samples. Due to the randomness, divergence may occur especially when you require a small number of items._ 20 | 21 | ## Use ArkPlanner via HTTP API - 通过 HTTP API 调用 ArkPlanner 22 | 23 | [API ReadMe](https://github.com/penguin-statistics/ArkPlanner/blob/master/API.md) 24 | 25 | ## Use ArkPlanner via Command Line - 通过命令行调用 ArkPlanner 26 | 27 | ### 安装说明 - Installation 28 | 29 | **_1. 环境配置 - Environment requirements_** 30 | 31 | 需要安装 Python 3.5 以上版本。Web 服务器则需要 3.6 以上。Windows 系统可通过[此链接](https://www.anaconda.com/distribution/)安装 Anaconda。强烈推荐使用 Jupyter notebook，详情请百度。 32 | 33 | Python >= 3.5 (3.6 for web server) Required. For Windows users, I recommend installing [Anaconda](https://www.anaconda.com/distribution/). Jupyter notebook is highly recommended. Google it for more details. 34 | 35 | **_2. 安装 - Installation_** 36 | 37 | 在命令行中执行以下命令，或手动下载解压。Run the following commands in command lines. 38 | 39 | ``` 40 | git clone https://github.com/ycremar/ArkPlanner.git 41 | cd ArkPlanner 42 | python setup.py install 43 | ``` 44 | 45 | _Note: 如何打开命令行？Windows 下可从 Anaconda 或 Win+R 开启运行对话框，输入 cmd 并回车。Mac 下 control+空格并搜索“终端”/“Terminal”。_ 46 | 47 | ### 使用说明 - Usage 48 | 49 | --- 50 | 51 | **_1. 在命令行中使用_** 52 | 53 | - 找到 _required.txt_ 以及 _owned.txt_ 两个文件，在 _required.txt_ 中列出你所需要的材料以及数量，材料和数量间空格隔开，多个材料用回车隔开，在 _owned.txt_ 中列出你现有的材料及数目，格式同上。 54 | 55 | Find and edit the files _required.txt_ and _owned.txt_. List the items you need and you already have. Seperate item name and quatity by space and two items by return. For example: 56 | 57 | 例如： 58 | 59 | ``` 60 | 双极纳米片 4 61 | RMA70-24 5 62 | ``` 63 | 64 | - 修改完成后保存并关闭，在命令行中运行 65 | 66 | Then save the files and run the following command in your command line: 67 | 68 | ``` 69 | python main.py 70 | ``` 71 | 72 | 你将看到如下输出 73 | 74 | You shall find some outputs like this: 75 | 76 | ``` 77 | Optimization terminated successfully, Computed in 0.0324 seconds, 78 | Estimated total sanity cost <----（预计消耗的总体力） 79 | Farm at following stages: <----（以下是你要刷哪些副本以及次数） 80 | Stage 3-1 (5 times) ===> 双酮(1), 酮凝集组(2) 81 | Stage 4-10 (9 times) ===> 源岩(2), 固源岩(3), 全新装置(2), 赤金(1) 82 | Stage 1-7 (59 times) ===> 源岩(7), 固源岩(75), 破损装置(2), 酯原料(4), 代糖(4), 异铁碎片(2), 双酮(3) 83 | Stage 2-10 (47 times) ===> 代糖(7), 糖(6), 异铁碎片(4), 异铁(4), 双酮(6), 酮凝集(4), RMA70-12(13) 84 | Stage S3-1 (12 times) ===> 代糖(1), 糖(19), 异铁碎片(1), 异铁(1), 双酮(1), 酮凝集(2) 85 | Synthesize following items: <----（以下是你要合成哪些材料以及次数） 86 | 双极纳米片(4) <=== 改量装置(4) , 白马醇(8) 87 | RMA70-24(5) <=== RMA70-12(5) , 固源岩组(10) , 酮凝集组(5) 88 | 白马醇(8) <=== 扭转醇(8) , 糖组(8) , RMA70-12(8) 89 | 改量装置(3) <=== 全新装置(3) , 固源岩组(6) , 研磨石(3) 90 | 酮凝集组(2) <=== 酮凝集(8) 91 | 糖组(7) <=== 糖(28) 92 | 固源岩组(16) <=== 固源岩(80) 93 | 酮凝集(4) <=== 双酮(12) 94 | 糖(4) <=== 代糖(12) 95 | 固源岩(3) <=== 源岩(9) 96 | ``` 97 | 98 | - 由于数据中记录较少的副本掉落偏差较大，因此代码中默认过滤掉统计频次低于 200 的记录，如需修改，可在 _main.py_ 中将第 6 行改为 99 | 100 | My code filters the records by their frequency from Penguin-Stats since records with low frequency may cause bias. To customize your filter, replace line 6 in _main.py_ with 101 | 102 | ``` 103 | mp = MaterialPlanning(filter_freq=n) 104 | ``` 105 | 106 | n 为你想自定义的频次下限，0 则为不过滤。 107 | 108 | where n is the lower bound of acceptable frequence. If n=0, no filter will be applied. 109 | 110 | **_2. Jupyter Notebook 或在你自己的代码中调用_** 111 | 112 | 参考*demo.ipynb*中的用法。 113 | 114 | Please refer to _demo.ipynb_. 115 | 116 | **_3. 运行 Web 服务器_** 117 | `python server.py` 将在 127.0.0.1 监听 8000 端口，可供调试。 118 | 119 | 然而，对于生产环境，建议使用`python -m sanic server.app --host= --port= --workers=`，以获得更好的性能和灵活性。 120 | 121 | For debugging, simply run `python server.py`, which spins up a server listening at `http://127.0.0.1:8000`. 122 | 123 | For deployment, however, `python -m sanic server.app --host= --port= --workers=` is recommended for better performance and flexibility. 124 | 125 | **_4. 更新数据_** 126 | 127 | 如果发生官方暗改掉率或材料、地图更新等情况，可直接删除文件夹 data，并重新运行。 128 | 129 | If new items or stages are updated, delete the data folder and run the following command as usual. 130 | 131 | ``` 132 | python main.py 133 | ``` 134 | 135 | ## 鸣谢 - Acknowledgement 136 | 137 | 数据来源： 138 | 139 | - 明日方舟企鹅物流数据统计 [penguin-stats.io](https://penguin-stats.io/) 140 | 141 | - 明日方舟工具箱 [ak.graueneko.xyz](https://ak.graueneko.xyz/) 142 | 143 | ## 贡献者 - Contributors 144 | 145 | 本项目由以下贡献者完成。我们欢迎任何贡献者 Pull Request！ 146 | 147 | [![Contributors](https://contrib.rocks/image?repo=penguin-statistics/ArkPlanner)](https://github.com/penguin-statistics/ArkPlanner/graphs/contributors) 148 | -------------------------------------------------------------------------------- /data/.gitkeep: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/penguin-statistics/ArkPlanner/fe71975323fb635a296c5a0d0fdcbd82b19d122a/data/.gitkeep -------------------------------------------------------------------------------- /demo.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [ 8 | { 9 | "name": "stdout", 10 | "output_type": "stream", 11 | "text": [ 12 | "Requesting data from web resources (i.e., penguin-stats.io and ak.graueneko.xyz)... done.\n" 13 | ] 14 | } 15 | ], 16 | "source": [ 17 | "from MaterialPlanning import MaterialPlanning\n", 18 | "mp = MaterialPlanning()" 19 | ] 20 | }, 21 | { 22 | "cell_type": "code", 23 | "execution_count": 2, 24 | "metadata": {}, 25 | "outputs": [ 26 | { 27 | "name": "stdout", 28 | "output_type": "stream", 29 | "text": [ 30 | "Optimization terminated successfully, Computed in 0.0495 seconds,\n", 31 | "Estimated total cost 1581\n", 32 | "Loot at following stages:\n", 33 | "Stage 2-10 (45 times) ===> RMA70-12(13), 异铁(4), 酮凝集(4), 异铁碎片(3), 糖(6), 代糖(7), 双酮(6)\n", 34 | "Stage S3-1 (13 times) ===> 异铁(1), 酮凝集(2), 异铁碎片(1), 糖(19), 代糖(1), 双酮(1)\n", 35 | "Stage 1-7 (60 times) ===> 异铁碎片(2), 代糖(4), 双酮(3), 破损装置(2), 酯原料(4), 源岩(7), 固源岩(76)\n", 36 | "Stage 3-1 (5 times) ===> 双酮(1), 酮凝集组(2)\n", 37 | "Stage 4-10 (9 times) ===> 源岩(2), 固源岩(3), 全新装置(3)\n", 38 | "Synthesize following items:\n", 39 | "双极纳米片(4) <=== 改量装置(4) , 白马醇(8) \n", 40 | "RMA70-24(5) <=== RMA70-12(5) , 固源岩组(10) , 酮凝集组(5) \n", 41 | "白马醇(8) <=== 扭转醇(8) , 糖组(8) , RMA70-12(8) \n", 42 | "改量装置(3) <=== 全新装置(3) , 固源岩组(6) , 研磨石(3) \n", 43 | "酮凝集组(2) <=== 酮凝集(8) \n", 44 | "糖组(7) <=== 糖(28) \n", 45 | "固源岩组(16) <=== 固源岩(80) \n", 46 | "酮凝集(4) <=== 双酮(12) \n", 47 | "糖(4) <=== 代糖(12) \n", 48 | "固源岩(3) <=== 源岩(9) \n" 49 | ] 50 | } 51 | ], 52 | "source": [ 53 | "requirement = {'双极纳米片':4, 'RMA70-24':5}\n", 54 | "owned = {'扭转醇':58, '研磨石':45}\n", 55 | "mp.get_plan(requirement, owned)" 56 | ] 57 | }, 58 | { 59 | "cell_type": "code", 60 | "execution_count": 3, 61 | "metadata": { 62 | "scrolled": false 63 | }, 64 | "outputs": [ 65 | { 66 | "name": "stdout", 67 | "output_type": "stream", 68 | "text": [ 69 | "Optimization terminated successfully, Computed in 0.0556 seconds,\n", 70 | "Estimated total cost 1336\n", 71 | "Loot at following stages:\n", 72 | "Stage 1-7 (57 times) ===> 异铁碎片(2), 代糖(4), 双酮(3), 破损装置(1), 酯原料(3), 源岩(7), 固源岩(72)\n", 73 | "Stage 4-2 (2 times) ===> 糖组(1)\n", 74 | "Stage 4-5 (16 times) ===> 酮凝集(1), 双酮(6), 酯原料(6), 聚酸酯(1), 酮凝集组(5)\n", 75 | "Stage 3-2 (8 times) ===> 源岩(1), 聚酸酯(1), 固源岩(1), 轻锰矿(2)\n", 76 | "Stage 3-4 (9 times) ===> 酯原料(1), 源岩(1), 聚酸酯(1), 固源岩(1), 全新装置(2)\n", 77 | "Stage S4-1 (16 times) ===> 异铁(2), 异铁碎片(2), 糖(3), 代糖(3), 异铁组(5)\n", 78 | "Stage 2-6 (2 times) ===> 源岩(1)\n", 79 | "Synthesize following items:\n", 80 | "聚合剂(4) <=== 提纯源岩(4) , 异铁块(4) , 酮阵列(4) \n", 81 | "酮阵列(3) <=== 酮凝集组(6) , 糖组(3) , 轻锰矿(3) \n", 82 | "异铁块(3) <=== 异铁组(6) , 全新装置(3) , 聚酸酯组(3) \n", 83 | "提纯源岩(4) <=== 固源岩组(16) \n", 84 | "酮凝集组(1) <=== 酮凝集(4) \n", 85 | "异铁组(1) <=== 异铁(4) \n", 86 | "聚酸酯组(2) <=== 聚酸酯(8) \n", 87 | "糖组(1) <=== 糖(4) \n", 88 | "固源岩组(16) <=== 固源岩(80) \n", 89 | "装置(1) <=== 破损装置(3) \n", 90 | "酮凝集(3) <=== 双酮(9) \n", 91 | "异铁(1) <=== 异铁碎片(3) \n", 92 | "聚酸酯(4) <=== 酯原料(12) \n", 93 | "糖(2) <=== 代糖(6) \n", 94 | "固源岩(3) <=== 源岩(9) \n" 95 | ] 96 | } 97 | ], 98 | "source": [ 99 | "requirement_dct = {'聚合剂':4}\n", 100 | "mp.get_plan(requirement_dct)" 101 | ] 102 | }, 103 | { 104 | "cell_type": "code", 105 | "execution_count": 4, 106 | "metadata": {}, 107 | "outputs": [ 108 | { 109 | "name": "stdout", 110 | "output_type": "stream", 111 | "text": [ 112 | "Optimization terminated successfully, Computed in 0.0460 seconds,\n", 113 | "Estimated total cost 568\n", 114 | "Loot at following stages:\n", 115 | "Stage GT-5 (37 times) ===> 扭转醇(25)\n", 116 | "Synthesize following items:\n" 117 | ] 118 | } 119 | ], 120 | "source": [ 121 | "requirement_dct = {'扭转醇':25}\n", 122 | "mp.get_plan(requirement_dct)" 123 | ] 124 | }, 125 | { 126 | "cell_type": "code", 127 | "execution_count": 5, 128 | "metadata": { 129 | "scrolled": true 130 | }, 131 | "outputs": [ 132 | { 133 | "name": "stdout", 134 | "output_type": "stream", 135 | "text": [ 136 | "Optimization terminated successfully, Computed in 0.0429 seconds,\n", 137 | "Estimated total cost 572\n", 138 | "Loot at following stages:\n", 139 | "Stage 1-7 (2 times) ===> 固源岩(2)\n", 140 | "Stage 3-2 (8 times) ===> 源岩(1), 聚酸酯(1), 固源岩(1), 轻锰矿(3)\n", 141 | "Stage 2-8 (36 times) ===> 异铁碎片(11), 代糖(10), 双酮(6), 异铁组(8)\n", 142 | "Synthesize following items:\n", 143 | "异铁组(1) <=== 异铁(4) \n", 144 | "异铁(3) <=== 异铁碎片(9) \n" 145 | ] 146 | } 147 | ], 148 | "source": [ 149 | "requirement_dct = {'异铁组':10, '轻锰矿':3, '固源岩':5}\n", 150 | "mp.get_plan(requirement_dct)" 151 | ] 152 | }, 153 | { 154 | "cell_type": "code", 155 | "execution_count": null, 156 | "metadata": {}, 157 | "outputs": [], 158 | "source": [] 159 | } 160 | ], 161 | "metadata": { 162 | "kernelspec": { 163 | "display_name": "Python 3", 164 | "language": "python", 165 | "name": "python3" 166 | }, 167 | "language_info": { 168 | "codemirror_mode": { 169 | "name": "ipython", 170 | "version": 3 171 | }, 172 | "file_extension": ".py", 173 | "mimetype": "text/x-python", 174 | "name": "python", 175 | "nbconvert_exporter": "python", 176 | "pygments_lexer": "ipython3", 177 | "version": "3.7.2" 178 | }, 179 | "varInspector": { 180 | "cols": { 181 | "lenName": 16, 182 | "lenType": 16, 183 | "lenVar": 40 184 | }, 185 | "kernels_config": { 186 | "python": { 187 | "delete_cmd_postfix": "", 188 | "delete_cmd_prefix": "del ", 189 | "library": "var_list.py", 190 | "varRefreshCmd": "print(var_dic_list())" 191 | }, 192 | "r": { 193 | "delete_cmd_postfix": ") ", 194 | "delete_cmd_prefix": "rm(", 195 | "library": "var_list.r", 196 | "varRefreshCmd": "cat(var_dic_list()) " 197 | } 198 | }, 199 | "types_to_exclude": [ 200 | "module", 201 | "function", 202 | "builtin_function_or_method", 203 | "instance", 204 | "_Feature" 205 | ], 206 | "window_display": false 207 | } 208 | }, 209 | "nbformat": 4, 210 | "nbformat_minor": 2 211 | } 212 | -------------------------------------------------------------------------------- /main.py: -------------------------------------------------------------------------------- 1 | import sys, codecs 2 | from MaterialPlanning import * 3 | 4 | 5 | if __name__ == '__main__': 6 | #if '-fe' in sys.argv: 7 | # filter_stages = ['GT-{}'.format(i) for i in range(1,7)] 8 | #else: 9 | # filter_stages = [] 10 | mp = MaterialPlanning(update=False) 11 | 12 | with codecs.open('required.txt', 'r', 'utf-8') as f: 13 | required_dct = {} 14 | for line in f.readlines(): 15 | required_dct[line.split(' ')[0]] = int(line.split(' ')[1]) 16 | 17 | with codecs.open('owned.txt', 'r', 'utf-8') as f: 18 | owned_dct = {} 19 | for line in f.readlines(): 20 | owned_dct[line.split(' ')[0]] = int(line.split(' ')[1]) 21 | 22 | mp.get_plan(required_dct, owned_dct, print_output='zh', outcome=True, 23 | gold_demand=True, exp_demand=True, store=True, output_lang='ja', server='CN') 24 | -------------------------------------------------------------------------------- /owned.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/penguin-statistics/ArkPlanner/fe71975323fb635a296c5a0d0fdcbd82b19d122a/owned.txt -------------------------------------------------------------------------------- /price.txt: -------------------------------------------------------------------------------- 1 | 异铁块 15 2 | 酮阵列 15 3 | 三水锰矿 10 4 | 改量装置 20 5 | 糖聚块 10 6 | 五水研磨石 10 7 | 聚酸酯块 10 8 | RMA70-24 15 9 | 白马醇 10 10 | 聚合凝胶 15 11 | 炽合金块 15 12 | 提纯源岩 10 13 | 全新装置 45 14 | RMA70-12 45 15 | 研磨石 40 16 | 凝胶 40 17 | 炽合金 35 18 | 酮凝集组 35 19 | 轻锰矿 35 20 | 异铁组 35 21 | 扭转醇 30 22 | 聚酸酯组 30 23 | 糖组 30 24 | 固源岩组 25 25 | 招聘许可 15 26 | 寻访凭证 450 27 | 芯片助剂 15 28 | 晶体电路 15 29 | 晶体元件 30 30 | 化合切削液 40 31 | 半自然溶剂 40 32 | 精炼溶剂 15 33 | 切削原液 15 34 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [project] 2 | name = "arkplanner" 3 | version = "1.1.4" 4 | description = "ArkPlanner backend inside Penguin Statistics" 5 | readme = "README.md" 6 | requires-python = ">=3.10" 7 | dependencies = [ 8 | "click>=8.1.8", 9 | "numpy>=2.2.0", 10 | "sanic>=25.3.0", 11 | "sanic-ext>=24.12.0", 12 | "scipy>=1.15.2", 13 | ] 14 | -------------------------------------------------------------------------------- /required.txt: -------------------------------------------------------------------------------- 1 | 聚合剂 524 2 | 双极纳米片 581 3 | D32钢 522 4 | 晶体电子单元 534 5 | 提纯源岩 925 6 | 糖聚块 829 7 | 聚酸酯块 801 8 | 异铁块 979 9 | 酮阵列 991 10 | 改量装置 891 11 | 白马醇 987 12 | 三水锰矿 837 13 | 五水研磨石 876 14 | RMA70-24 921 15 | 晶体电路 903 16 | 精炼溶剂 854 17 | 切削原液 838 -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | numpy>=2.2.0 2 | sanic>=25.3.0 3 | scipy>=1.15.2 4 | click>=8.1.8 5 | sanic-ext>=24.12.0 6 | -------------------------------------------------------------------------------- /server.py: -------------------------------------------------------------------------------- 1 | import asyncio 2 | 3 | import click 4 | from sanic import Sanic, response 5 | from sanic_ext import Extend 6 | from MaterialPlanning import MaterialPlanning 7 | 8 | app = Sanic('ArkPlanner') 9 | app.config.CORS_ORIGINS = '*' 10 | Extend(app) 11 | 12 | app.static('/', './ArkPlannerWeb/index.html', name='web_index') 13 | app.static('/css', './ArkPlannerWeb/css', name='css') 14 | app.static('/fonts', './ArkPlannerWeb/fonts', name='fonts') 15 | app.static('/img', './ArkPlannerWeb/img', name='img') 16 | app.static('/js', './ArkPlannerWeb/js', name='js') 17 | 18 | @app.before_server_start 19 | async def init_mp(app): 20 | app.ctx.mp = MaterialPlanning() 21 | 22 | @app.get('/', name='index') 23 | async def index(request): 24 | return response.redirect("https://penguin-stats.io/planner") 25 | 26 | @app.get('/_health', name='_health') 27 | async def health(request): 28 | return response.json({"status": "ok"}) 29 | 30 | @app.post('/plan', name='plan') 31 | async def plan(request): 32 | try: 33 | input_data = request.json 34 | except: 35 | return response.json({'error': True, 'reason': 'Uninterpretable input'}) 36 | 37 | # get value by key or default 38 | # weak type checking only 39 | owned_dct = input_data.get('owned', {}) 40 | required_dct = input_data.get('required', {}) 41 | 42 | extra_outc = input_data.get('extra_outc', False) 43 | convertion_dr = input_data.get('convertion_dr', 0.18) 44 | exp_demand = input_data.get('exp_demand', True) 45 | gold_demand = input_data.get('gold_demand', True) 46 | exclude = input_data.get('exclude', []) 47 | 48 | store = input_data.get('store', False) 49 | input_lang = input_data.get('input_lang', 'zh') 50 | output_lang = input_data.get('output_lang', 'zh') 51 | server = input_data.get('server', 'CN') 52 | 53 | try: 54 | dct = app.ctx.mp.get_plan( 55 | required_dct, owned_dct, False, 56 | outcome=extra_outc, 57 | exp_demand=exp_demand, 58 | gold_demand=gold_demand, 59 | exclude=exclude, 60 | store=store, 61 | convertion_dr=convertion_dr, 62 | input_lang=input_lang, 63 | output_lang=output_lang, 64 | server=server 65 | ) 66 | except ValueError as e: 67 | return response.json({'error': True, 'reason': f'{e}'}) 68 | except Exception as e: 69 | return response.json({'error': True, 'reason': f'{e}'}) 70 | return response.json(dct) 71 | 72 | 73 | @app.after_server_start 74 | async def update_each_half_hour(app, loop): 75 | while True: 76 | app.ctx.mp.update() 77 | await asyncio.sleep(30 * 60) 78 | 79 | 80 | @click.command() 81 | @click.option('-h', '--host', default='127.0.0.1', help='Binding address') 82 | @click.option('-p', '--port', default=8000, help='Binding port') 83 | @click.option('-w', '--workers', default=1, help='Number of worker') 84 | @click.option('--debug', is_flag=True, default=False, help='Trigger Sanic debug mode') 85 | @click.option('--log', is_flag=True, default=False, help='Trigger Sanic request log(will slows server)') 86 | def start_server(host, port, workers, debug, log): 87 | app.run(host=host, port=port, workers=workers, debug=debug, access_log=log) 88 | 89 | if __name__ == '__main__': 90 | start_server() 91 | -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | import os 2 | from setuptools import setup 3 | 4 | # Utility function to read the README file. 5 | # Used for the long_description. It's nice, because now 1) we have a top level 6 | # README file and 2) it's easier to type in the README file than to put a raw 7 | # string in below ... 8 | def read(fname): 9 | return open(os.path.join(os.path.dirname(__file__), fname)).read() 10 | 11 | setup( 12 | name = "Arknight AutoPlanner", 13 | version = "0.0.4", 14 | author = "YC.Remar", 15 | author_email = "ethan.ycx@gmail.com", 16 | description = ("A tiny program that helps on material planning in Arknight"), 17 | # url = "http://packages.python.org/an_example_pypi_project", 18 | install_requires=[ 19 | "numpy", 20 | "scipy", 21 | "sanic" 22 | ], 23 | ) -------------------------------------------------------------------------------- /uv.lock: -------------------------------------------------------------------------------- 1 | version = 1 2 | revision = 1 3 | requires-python = ">=3.10" 4 | 5 | [[package]] 6 | name = "aiofiles" 7 | version = "24.1.0" 8 | source = { registry = "https://pypi.org/simple" } 9 | sdist = { url = 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