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How to use dump_json method in lisa
Best Python code snippet using lisa_python
api_data.py
Source:api_data.py 
...79 ('name_kanji', data['name']),80 ]) for reading, data in readings.items()]81def CJK_compatibility(character):82 return u'\uF900' <= literal(character) <= u'\uFAFF'83def dump_json(filename, obj):84 with open(filename, 'w', encoding='utf8') as f:85 ujson.dump(obj, f, ensure_ascii=False)86def main():87 VERSION_PATH = 'v1'88 SITE_PATH = f'out/site'89 OUT_PATH = f'out/{VERSION_PATH}'90 KANJI_DIR = f'{OUT_PATH}/kanji/'91 WORD_DIR = f'{OUT_PATH}/words/'92 READING_DIR = f'{OUT_PATH}/reading/'93 JOUYOU_GRADES = [1, 2, 3, 4, 5, 6, 8]94 JINMEIYOU_GRADES = [9, 10]95 kanjidic_root = etree.parse('kanjidic2.xml')96 jmdict_entries = etree.parse('JMDict').xpath('//entry')97 characters = kanjidic_root.xpath('./character')98 kanji_to_entries = word_dict(jmdict_entries)99 kanjis = [100 kanji_data(character)101 for character in characters102 if not CJK_compatibility(character)103 ]104 readings = reading_data(kanjis)105 all_kanji = [kanji['kanji'] for kanji in kanjis]106 words = {}107 for kanji in kanjis:108 dump_json(KANJI_DIR + kanji['kanji'], kanji)109 try:110 entries = tuple(kanji_to_entries[kanji['kanji']])111 dump_json(WORD_DIR + kanji['kanji'], entries)112 words[kanji['kanji']] = entries113 except KeyError:114 continue115 for reading in readings:116 dump_json(READING_DIR + reading['reading'], reading)117 jouyou_kanji = [118 kanji['kanji']119 for kanji in kanjis120 if kanji['grade'] in JOUYOU_GRADES121 ]122 jinmeiyou_kanji = [123 kanji['kanji']124 for kanji in kanjis125 if kanji['grade'] in JINMEIYOU_GRADES126 ]127 dump_json(KANJI_DIR + 'all', all_kanji)128 dump_json(KANJI_DIR + 'jouyou', jouyou_kanji)129 dump_json(KANJI_DIR + 'joyo', jouyou_kanji)130 dump_json(KANJI_DIR + 'jinmeiyou', jinmeiyou_kanji)131 dump_json(KANJI_DIR + 'jinmeiyo', jinmeiyou_kanji)132 with ZipFile(f'{SITE_PATH}/kanjiapi_full.zip', 'w', compression=ZIP_DEFLATED) as archive:133 api_data_download = {134 'kanjis': {kanji['kanji']: kanji for kanji in kanjis},135 'readings': {reading['reading']: reading for reading in readings},136 'words': words,137 }138 json_filename = f'{SITE_PATH}/kanjiapi_full.json'139 dump_json(json_filename, api_data_download)140 archive.write(json_filename, arcname='kanjiapi_full.json')141 os.remove(json_filename)142 for grade_numeral in JOUYOU_GRADES:143 grade_kanji = [144 kanji['kanji']145 for kanji in kanjis146 if kanji['grade'] == grade_numeral147 ]...
views.py
Source:views.py
...10def index(request):11 return render(request, "api-index.html")12def malaria(request):13 if not validate_API(request.GET.get("key", "~~~")):14 return HttpResponse(dump_json({"success": False, "error": "Invalid Creds", "test_type": "malaria", "message": None}))15 try:16 img_url = request.GET.get("img_url", None)17 if img_url:18 img_data = get_image_data(img_url)19 img_data = preprocess_malaria(img_data)20 test_result = malaria_model.predict([[img_data]])21 confidence_score = test_result[0][test_result.argmax()] * 10022 if test_result.argmax() == 0:23 test_message = "Malaria Negative with {:.2f}% confidence".format(confidence_score)24 result = "Negative"25 else:26 test_message = "Malaria Positive with {:.2f}% confidence".format(confidence_score)27 result = "Positive"28 else:29 return HttpResponse(dump_json({"success": False, "test_type": "malaria", "error": "No image url was provided", "message": None}))30 return HttpResponse(dump_json({"success": True, "error": None, "test_type": "malaria", "message": test_message, "result": result, "confidence": confidence_score}))31 except Exception as e:32 return HttpResponse(dump_json({"success": False, "error": "An error occured during the test", "test_type": "malaria", "message": None}))33def skin_cancer(request):34 if not validate_API(request.GET.get("key", "~~~")):35 return HttpResponse(dump_json({"success": False, "error": "Invalid Creds", "test_type": "skin_cancer", "message": None}))36 try:37 img_url = request.GET.get("img_url", None)38 if img_url:39 img_data = get_image_data(img_url)40 img_data = preprocess_skin_cancer(img_data)41 test_result = skin_cancer_model.predict([[img_data]])[0][0]42 if round(test_result) == 0:43 confidence_score = (1 - test_result) * 10044 test_message = "Detected Benign Cancer with {:.2f}% confidence".format(confidence_score)45 result = "Benign"46 else:47 confidence_score = test_result * 10048 test_message = "Detected Malignant Cancer with {:.2f}% confidence".format(confidence_score)49 result = "Malignant"50 else:51 return HttpResponse(dump_json({"success": False, "test_type": "skin_cancer", "error": "No image url was provided", "message": None}))52 return HttpResponse(dump_json({"success": True, "error": None, "test_type": "skin_cancer", "message": test_message, "result": result, "confidence": confidence_score}))53 except Exception as e:...
correct_exp.py
Source:correct_exp.py
1import json, re2import os, sys3dump_list = []4dump_json = {}5uid = 06name = ""7f1= open("dev_set.txt", mode='r', encoding='utf-8')8for line in f1:9 pairs = line.split(":")10 abbr_word = pairs[0]11 if abbr_word == "n":12 continue13 complete_word = pairs[1].strip()14 complete_word = complete_word.split(" ")15 for i in range(len(complete_word)):16 complete_word[i] = complete_word[i].split("/")[0]17 dump_json[abbr_word] = ''.join(complete_word)18f2 = open("test_set.txt", mode='r', encoding='utf-8')19for line in f2:20 pairs = line.split(":")21 abbr_word = pairs[0]22 if abbr_word == "n":23 continue24 complete_word = pairs[1].strip()25 complete_word = complete_word.split(" ")26 for i in range(len(complete_word)):27 complete_word[i] = complete_word[i].split("/")[0]28 dump_json[abbr_word] = ''.join(complete_word)29f3 = open("train_set.txt", mode='r', encoding='utf-8')30for line in f3:31 pairs = line.split(":")32 abbr_word = pairs[0]33 if abbr_word == "n":34 continue35 complete_word = pairs[1].strip()36 complete_word = complete_word.split(" ")37 for i in range(len(complete_word)):38 complete_word[i] = complete_word[i].split("/")[0]39 dump_json[abbr_word] = ''.join(complete_word)40# dicts = json.load(f)41# # å°å¤ä¸ªåå
¸ä»jsonæ件ä¸è¯»åºæ¥42# for i in dicts:43# print(i["uid"])44# print(i["name"])45# print(i["content"])46# print("========")47#48# print(pre_data)49# for i in range(len(pre_data)-1):50# # å¦æ以xls为为ç»å°¾ï¼å°±æ¯æ°å工信æ¯51#52# dump_json["uid"] = uid53# dump_json["name"] = name54# dump_json["gender"] = ""55# dump_json["nation"] = ""56# dump_json["birthday"] = ""57# dump_json["birthplace"] = ""58# dump_json["origo"] = ""59#60# dump_json["t_party"] = ""61# dump_json["t_job"] = ""62#63# dump_json["ft_edu_career"] = ""64# dump_json["ft_edu_school"] = ""65# dump_json["pt_edu_career"] = ""66# dump_json["pt_edu_school"] = ""67#68# dump_json["position"] = ""69# dump_json["rank"] = ""70# dump_json["content"] = content71#72# dump_list.append(dump_json)73# content = []74# dump_json = {}75#76#77#78#79# print(dump_list)80#81with open('abbr_pairs.json', mode='w', encoding='utf-8') as f:82 json.dump(dump_json, f, ensure_ascii=False)83#84#85# with open(data_path + '/sample_data180.json', mode='r', encoding='utf-8') as f:86# dicts = json.load(f)87# # å°å¤ä¸ªåå
¸ä»jsonæ件ä¸è¯»åºæ¥88# for i in dicts:89# print(i["uid"])90# print(i["name"])91# print(i["content"])...
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