Reset23/the-stack-v2-python · Datasets at Hugging Face

a9986072f1abd4c08e2ba430e0d507c373a99150

f0abac6fa2ec8740a63d3ad1fffd778bd317de6c

/project1/parti_min_df=2.py

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no_license

ashwinkannan94/Large-Scale-Data-Mining

3beb89072cdba3ad27c2e279c8806f8be79d333d

51df9c573f7d6f92b6c8a05007f204c6f967d267

refs/heads/master

2021-05-09T00:39:32.973665

2018-02-21T07:00:26

119,751,671

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from sklearn.datasets import fetch_20newsgroups import matplotlib.pyplot as plt from sklearn.feature_extraction.text import CountVectorizer from nltk.stem import SnowballStemmer from sklearn.feature_extraction import text from sklearn.feature_extraction.text import TfidfTransformer from sklearn.decomposition import TruncatedSVD from sklearn.decomposition import NMF import numpy as np from sklearn import metrics from sklearn.metrics import roc_curve from sklearn.linear_model import LogisticRegression # part a computer_categories = ['comp.graphics', 'comp.os.ms-windows.misc', 'comp.sys.ibm.pc.hardware', 'comp.sys.mac.hardware'] recreational_categories = ['rec.autos', 'rec.motorcycles', 'rec.sport.baseball', 'rec.sport.hockey'] computer_train = fetch_20newsgroups(subset='train', categories=computer_categories, shuffle=True, random_state=42) computer_test = fetch_20newsgroups(subset='test', categories=computer_categories, shuffle=True, random_state=42) recreational_train = fetch_20newsgroups(subset='train', categories=recreational_categories, shuffle=True, random_state=42) recreational_test = fetch_20newsgroups(subset='test', categories=recreational_categories, shuffle=True, random_state=42) train_and_test = computer_train.data + computer_test.data + recreational_train.data + recreational_test.data stop_words = text.ENGLISH_STOP_WORDS analyzer = CountVectorizer().build_analyzer() stemmer = SnowballStemmer("english") def stemmed_words(doc): return (stemmer.stem(w) for w in analyzer(doc)) train_classification = [1] * len(computer_train.data) + [-1] * len(recreational_train.data) test_classification = [1] * len(computer_test.data) + [-1] * len(recreational_test.data) count_vect = CountVectorizer(analyzer='word', min_df=2, stop_words=stop_words, tokenizer=stemmed_words) X_train_counts = count_vect.fit_transform(train_and_test) tfidf_transformer = TfidfTransformer() X_train_tfidf = tfidf_transformer.fit_transform(X_train_counts) # SVD LSI svd = TruncatedSVD(n_components=50, random_state=42) svd_lsi_tfidf = svd.fit_transform(X_train_tfidf) LSI_test_data = np.concatenate((svd_lsi_tfidf[len(computer_train.data):(len(computer_train.data) + len(computer_test.data))], svd_lsi_tfidf[(len(computer_train.data) + len(computer_test.data) + len(recreational_train.data)):])) LSI_train_data = np.concatenate((svd_lsi_tfidf[0:len(computer_train.data)], svd_lsi_tfidf[(len(computer_train.data) + len(computer_test.data)):(len(computer_train.data) + len(computer_test.data) + len(recreational_train.data))])) l1_accuracy = [] l2_accuracy = [] def logistic_regression(regularize, penalize): logistic_regression_classifier = LogisticRegression(C=regularize, penalty=penalize) logistic_regression_classifier.fit(LSI_train_data, train_classification) class_which_was_predicted = logistic_regression_classifier.predict(LSI_test_data) actual_class_passed = test_classification predict_probability = logistic_regression_classifier.predict_proba(LSI_test_data[:])[:, 1] print('Regularization term: ' + str(regularize)) print('Penalization term: ' + str(penalize)) print('Accuracy for LSI is: ' + str(metrics.accuracy_score(actual_class_passed, class_which_was_predicted))) print('Precision for LSI is: ' + str(metrics.precision_score(actual_class_passed, class_which_was_predicted, average='macro'))) print('Recall for LSI is: ' + str(metrics.recall_score(actual_class_passed, class_which_was_predicted, average='macro'))) print('Confusion matrix for LSI is: ' + str(metrics.confusion_matrix(actual_class_passed, class_which_was_predicted))) false_positive_rate_LSI, true_positive_rate_LSI, c = roc_curve(actual_class_passed, predict_probability) plt.figure(1) plt.plot(false_positive_rate_LSI, true_positive_rate_LSI) plt.plot([0, 1], [0, 1]) plt.ylabel('True Positive Rate') plt.xlabel('Flase Positive Rate') plt.title('ROC Curve of LSI Logistic Regression Classification With min_df=2') return metrics.accuracy_score(actual_class_passed, class_which_was_predicted) for x in range(-7, 7): l1_accuracy.append(logistic_regression(pow(10, x), 'l1')) l2_accuracy.append(logistic_regression(pow(10, x), 'l2')) plt.figure(2) x_labels = ['0.0000001', '0.000001', '0.00001', '0.0001', '0.001', '0.01', '0.1', '1', '10', '100', '1000', '10000', '100000', '1000000'] y_labels = ['0', '20%', '40%', '60%', '80%', '100%'] plt.plot(range(-7, 7), l1_accuracy, 's', label='l1 Norm Regularization', c='b') plt.plot(range(-7, 7), l1_accuracy, c='b') plt.plot(range(-7, 7), l2_accuracy, 'D', label='l2 Norm Regularization', c='g') plt.plot(range(-7, 7), l2_accuracy, c='g') plt.ylabel('Total Accuracy of Classification') plt.xlabel('Regularization Term') plt.title('Accuracy vs. Regularization Term') plt.show()

[ "ashwinkumar.kannan@gmail.com" ]

ashwinkumar.kannan@gmail.com

9eb8d914c3ecf4d460b4c1e5ab1915dfaaad58c3

b2db52eff7b186c16d83afc0fe0a7277648d8975

/kvak/functions/bot_updates.py

057fa8df6cbff2313b4cced205e8ac99beb9b1c4

[]

no_license

HolyHelicopter/kvak

d99cc06c4b538f1a2f3bf632ff39cd85a32c219e

3a6f5db2c7c439f8ef88627a7c37d47b258d09eb

refs/heads/master

2023-01-06T10:04:06.893331

2020-11-03T14:35:34

302,491,883

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import requests import random import datetime import time TG_URL = "https://api.telegram.org/bot1221959365:AAHAZKkaa5hJF0bchJFfVM9uT9Hhv-jOfzg/" BING_URL = "https://bing-image-search1.p.rapidapi.com/images/search?q=" BING_HEADERS = { "x-rapidapi-host": "bing-image-search1.p.rapidapi.com", "x-rapidapi-key": "fb3dd38f00msh738d9f9b25b29acp13d692jsn8859445253e3", "useQueryString": 'true' } BACKUP_QUERIES = [ 'лягушка мем', 'лягушка косплей', 'лягушка сказка', 'лягушка нарисованная', 'лягушка смешная', 'лягушка кермит' ] def bot_updates(updates): try: for update in updates: if 'message' in update: message = update['message'] chat_id = message['chat']['id'] if 'text' in message and message['text']: message_text = message['text'] lowercase_text = message_text.replace('К', 'к').replace('В', 'в').replace('А', 'а') if 'квак' in lowercase_text: words = message_text.split() words_temp = [] for word in words: if 'квак' not in word.replace('К', 'к').replace('В', 'в').replace('А', 'а'): words_temp.append(word) words = words_temp query = 'лягушка' for word in words: query += ' ' + word print(query) found_images = requests.get( BING_URL + query, headers=BING_HEADERS ).json()['value'] if not len(found_images): print('no results') backup_index = random.randint(0, len(BACKUP_QUERIES) - 1) backup_query = BACKUP_QUERIES[backup_index] print(backup_query) found_images = requests.get( BING_URL + backup_query, headers=BING_HEADERS ).json()['value'] if len(found_images): image_index = random.randint(0, len(found_images) - 1) image_url = found_images[image_index]['contentUrl'] try: requests.post( TG_URL + 'sendPhoto', { 'chat_id': chat_id, 'photo': image_url } ) except Exception as e: print(str(e)) image_index = random.randint(0, len(found_images) - 1) image_url = found_images[image_index]['contentUrl'] try: requests.post( TG_URL + 'sendPhoto', { 'chat_id': chat_id, 'photo': image_url } ) except Exception as e: pass # file_content = requests.get(image_url) # file_content = file_content.content # data = { # 'chat_id': '811288345', # } # requests.post( # "https://api.telegram.org/bot1221959365:AAHAZKkaa5hJF0bchJFfVM9uT9Hhv-jOfzg/sendPhoto", # data=data, # files={'photo': ('квак.jpg', file_content)} # ) except Exception as e: print(e) current_time = datetime.datetime.now() time_end = current_time + datetime.timedelta(hours=20) updates_response = requests.post(TG_URL + 'getUpdates').json() if 'result' in updates_response and len(updates_response['result']): last_update_id = updates_response['result'][-1]['update_id'] offset = last_update_id while current_time < time_end: updates_response = requests.post(TG_URL + 'getUpdates', {'offset': offset}).json() if 'result' in updates_response and len(updates_response['result']): updates = updates_response['result'] bot_updates(updates) last_update_id = updates[-1]['update_id'] offset = last_update_id + 1 time.sleep(10) current_time = datetime.datetime.now()

[ "holyhelicopter@yandex.ru" ]

holyhelicopter@yandex.ru

a1f924be1664e8f0574715c1ec97c9fe4238ee03

814a5ccb1e6275b604cae965cd34f4b857b198cc

/opencv-start/morphologicalTransformations.py

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no_license

Arijit02/opencv-start

ea9adfca4185ba5307000a856b7229c34f094ce0

5e3562488adc6072593b5042fdb3c8f875206cf2

refs/heads/master

2022-11-30T02:45:38.973852

2020-08-12T03:24:05

264,355,476

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import cv2 import os import numpy as np from matplotlib import pyplot as plt filePath = os.path.dirname(__file__) imagePath = os.path.join(filePath, "../images/smarties.png") img = cv2.imread(imagePath, 0) _, mask = cv2.threshold(img, 220, 255, cv2.THRESH_BINARY_INV) kernel = np.ones([3, 3], np.uint8) # kernel2 = np.ones([2, 2], np.uint8) dialation = cv2.dilate(mask, kernel, iterations=2) erosion = cv2.erode(mask, kernel, iterations=2) opening = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel, iterations=2) closing = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel, iterations=2) mg = cv2.morphologyEx(mask, cv2.MORPH_GRADIENT, kernel, iterations=2) th = cv2.morphologyEx(mask, cv2.MORPH_TOPHAT, kernel, iterations=2) titles = ['Original Image', 'Mask', 'Dialation', 'Erosion', 'Opening', 'closing', 'gradient', 'tophat'] images = [img, mask, dialation, erosion, opening, closing, mg, th] for i in range(8): plt.subplot(2, 4, i+1), plt.imshow(images[i], "gray") plt.title(titles[i]) plt.xticks([]), plt.yticks([]) plt.show()

[ "arijitjuite23@gmail.com" ]

arijitjuite23@gmail.com

046559d003fa8dab31306f89a50e26d810e7dbb2

0a3fd2d1f27712271903a593fb8acce711efe44b

/actions/admin.py

c0c12b255d956f944120c5fef81c5e5f92f42a1e

[]

no_license

SanjarRakhmonov/qwertyuiiiiiiur

018c6a60212dae6eeb4a667aeaa6a9c3320b1225

1bcf32b3d6f26cf985da0b3ccab4aaec64e93262

refs/heads/master

2021-01-19T17:25:31.827933

2017-01-28T07:34:02

82,455,802

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null

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from django.contrib import admin from .models import Action class ActionAdmin(admin.ModelAdmin): list_display = ('user', 'verb', 'target', 'date') list_filter = ('date',) search_fields = ('verb',) admin.site.register(Action, ActionAdmin)

[ "sanjarbekraxmonov@gmail.com" ]

sanjarbekraxmonov@gmail.com

a11c4102f7cd07bc3caf030828b40fd6cdbf9b43

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/nets/layers.py

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[]

no_license

xiangchao2018/Keras-Mask-RCNN

cf16e3df4fad496be1f2737879c34cfef89835d4

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refs/heads/main

2023-02-06T16:11:46.793744

2020-12-27T16:41:56

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import tensorflow as tf from keras.engine import Layer import numpy as np from utils import utils #----------------------------------------------------------# # Proposal Layer # 该部分代码用于将先验框转化成建议框 #----------------------------------------------------------# def apply_box_deltas_graph(boxes, deltas): # 计算先验框的中心和宽高 height = boxes[:, 2] - boxes[:, 0] width = boxes[:, 3] - boxes[:, 1] center_y = boxes[:, 0] + 0.5 * height center_x = boxes[:, 1] + 0.5 * width # 计算出调整后的先验框的中心和宽高 center_y += deltas[:, 0] * height center_x += deltas[:, 1] * width height *= tf.exp(deltas[:, 2]) width *= tf.exp(deltas[:, 3]) # 计算左上角和右下角的点的坐标 y1 = center_y - 0.5 * height x1 = center_x - 0.5 * width y2 = y1 + height x2 = x1 + width result = tf.stack([y1, x1, y2, x2], axis=1, name="apply_box_deltas_out") return result def clip_boxes_graph(boxes, window): """ boxes: [N, (y1, x1, y2, x2)] window: [4] in the form y1, x1, y2, x2 """ # Split wy1, wx1, wy2, wx2 = tf.split(window, 4) y1, x1, y2, x2 = tf.split(boxes, 4, axis=1) # Clip y1 = tf.maximum(tf.minimum(y1, wy2), wy1) x1 = tf.maximum(tf.minimum(x1, wx2), wx1) y2 = tf.maximum(tf.minimum(y2, wy2), wy1) x2 = tf.maximum(tf.minimum(x2, wx2), wx1) clipped = tf.concat([y1, x1, y2, x2], axis=1, name="clipped_boxes") clipped.set_shape((clipped.shape[0], 4)) return clipped class ProposalLayer(Layer): def __init__(self, proposal_count, nms_threshold, config=None, **kwargs): super(ProposalLayer, self).__init__(**kwargs) self.config = config self.proposal_count = proposal_count self.nms_threshold = nms_threshold # [rpn_class, rpn_bbox, anchors] def call(self, inputs): # 代表这个先验框内部是否有物体[batch, num_rois, 1] scores = inputs[0][:, :, 1] # 代表这个先验框的调整参数[batch, num_rois, 4] deltas = inputs[1] # [0.1 0.1 0.2 0.2]，改变数量级 deltas = deltas * np.reshape(self.config.RPN_BBOX_STD_DEV, [1, 1, 4]) # Anchors anchors = inputs[2] # 筛选出得分前6000个的框 pre_nms_limit = tf.minimum(self.config.PRE_NMS_LIMIT, tf.shape(anchors)[1]) # 获得这些框的索引 ix = tf.nn.top_k(scores, pre_nms_limit, sorted=True, name="top_anchors").indices # 获得这些框的得分 scores = utils.batch_slice([scores, ix], lambda x, y: tf.gather(x, y), self.config.IMAGES_PER_GPU) # 获得这些框的调整参数 deltas = utils.batch_slice([deltas, ix], lambda x, y: tf.gather(x, y), self.config.IMAGES_PER_GPU) # 获得这些框对应的先验框 pre_nms_anchors = utils.batch_slice([anchors, ix], lambda a, x: tf.gather(a, x), self.config.IMAGES_PER_GPU, names=["pre_nms_anchors"]) # [batch, N, (y1, x1, y2, x2)] # 对先验框进行解码 boxes = utils.batch_slice([pre_nms_anchors, deltas], lambda x, y: apply_box_deltas_graph(x, y), self.config.IMAGES_PER_GPU, names=["refined_anchors"]) # [batch, N, (y1, x1, y2, x2)] # 防止超出图片范围 window = np.array([0, 0, 1, 1], dtype=np.float32) boxes = utils.batch_slice(boxes, lambda x: clip_boxes_graph(x, window), self.config.IMAGES_PER_GPU, names=["refined_anchors_clipped"]) # 非极大抑制 def nms(boxes, scores): indices = tf.image.non_max_suppression( boxes, scores, self.proposal_count, self.nms_threshold, name="rpn_non_max_suppression") proposals = tf.gather(boxes, indices) # 如果数量达不到设置的建议框数量的话 # 就padding padding = tf.maximum(self.proposal_count - tf.shape(proposals)[0], 0) proposals = tf.pad(proposals, [(0, padding), (0, 0)]) return proposals proposals = utils.batch_slice([boxes, scores], nms, self.config.IMAGES_PER_GPU) return proposals def compute_output_shape(self, input_shape): return (None, self.proposal_count, 4) #----------------------------------------------------------# # ROIAlign Layer # 利用建议框在特征层上截取内容 #----------------------------------------------------------# def log2_graph(x): return tf.compat.v1.log(x) / tf.compat.v1.log(2.0) def parse_image_meta_graph(meta): """ 将meta里面的参数进行分割 """ image_id = meta[:, 0] original_image_shape = meta[:, 1:4] image_shape = meta[:, 4:7] window = meta[:, 7:11] # (y1, x1, y2, x2) window of image in in pixels scale = meta[:, 11] active_class_ids = meta[:, 12:] return { "image_id": image_id, "original_image_shape": original_image_shape, "image_shape": image_shape, "window": window, "scale": scale, "active_class_ids": active_class_ids, } class PyramidROIAlign(Layer): def __init__(self, pool_shape, **kwargs): super(PyramidROIAlign, self).__init__(**kwargs) self.pool_shape = tuple(pool_shape) def call(self, inputs): # 建议框的位置 boxes = inputs[0] # image_meta包含了一些必要的图片信息 image_meta = inputs[1] # 取出所有的特征层[batch, height, width, channels] feature_maps = inputs[2:] y1, x1, y2, x2 = tf.split(boxes, 4, axis=2) h = y2 - y1 w = x2 - x1 # 获得输入进来的图像的大小 image_shape = parse_image_meta_graph(image_meta)['image_shape'][0] # 通过建议框的大小找到这个建议框属于哪个特征层 image_area = tf.cast(image_shape[0] * image_shape[1], tf.float32) roi_level = log2_graph(tf.sqrt(h * w) / (224.0 / tf.sqrt(image_area))) roi_level = tf.minimum(5, tf.maximum( 2, 4 + tf.cast(tf.round(roi_level), tf.int32))) # batch_size, box_num roi_level = tf.squeeze(roi_level, 2) # Loop through levels and apply ROI pooling to each. P2 to P5. pooled = [] box_to_level = [] # 分别在P2-P5中进行截取 for i, level in enumerate(range(2, 6)): # 找到每个特征层对应box ix = tf.where(tf.equal(roi_level, level)) level_boxes = tf.gather_nd(boxes, ix) box_to_level.append(ix) # 获得这些box所属的图片 box_indices = tf.cast(ix[:, 0], tf.int32) # 停止梯度下降 level_boxes = tf.stop_gradient(level_boxes) box_indices = tf.stop_gradient(box_indices) # Result: [batch * num_boxes, pool_height, pool_width, channels] pooled.append(tf.image.crop_and_resize( feature_maps[i], level_boxes, box_indices, self.pool_shape, method="bilinear")) pooled = tf.concat(pooled, axis=0) # 将顺序和所属的图片进行堆叠 box_to_level = tf.concat(box_to_level, axis=0) box_range = tf.expand_dims(tf.range(tf.shape(box_to_level)[0]), 1) box_to_level = tf.concat([tf.cast(box_to_level, tf.int32), box_range], axis=1) # box_to_level[:, 0]表示第几张图 # box_to_level[:, 1]表示第几张图里的第几个框 sorting_tensor = box_to_level[:, 0] * 100000 + box_to_level[:, 1] # 进行排序，将同一张图里的某一些聚集在一起 ix = tf.nn.top_k(sorting_tensor, k=tf.shape( box_to_level)[0]).indices[::-1] # 按顺序获得图片的索引 ix = tf.gather(box_to_level[:, 2], ix) pooled = tf.gather(pooled, ix) # 重新reshape为原来的格式 # 也就是 # Shape: [batch, num_rois, POOL_SIZE, POOL_SIZE, channels] shape = tf.concat([tf.shape(boxes)[:2], tf.shape(pooled)[1:]], axis=0) pooled = tf.reshape(pooled, shape) return pooled def compute_output_shape(self, input_shape): return input_shape[0][:2] + self.pool_shape + (input_shape[2][-1], ) #----------------------------------------------------------# # Detection Layer # #----------------------------------------------------------# def refine_detections_graph(rois, probs, deltas, window, config): """细化分类建议并过滤重叠部分并返回最终结果探测。 Inputs: rois: [N, (y1, x1, y2, x2)] in normalized coordinates probs: [N, num_classes]. Class probabilities. deltas: [N, num_classes, (dy, dx, log(dh), log(dw))]. Class-specific bounding box deltas. window: (y1, x1, y2, x2) in normalized coordinates. The part of the image that contains the image excluding the padding. Returns detections shaped: [num_detections, (y1, x1, y2, x2, class_id, score)] where coordinates are normalized. """ # 找到得分最高的类 class_ids = tf.argmax(probs, axis=1, output_type=tf.int32) # 序号+类 indices = tf.stack([tf.range(probs.shape[0]), class_ids], axis=1) # 取出成绩 class_scores = tf.gather_nd(probs, indices) # 还有框的调整参数 deltas_specific = tf.gather_nd(deltas, indices) # 进行解码 # Shape: [boxes, (y1, x1, y2, x2)] in normalized coordinates refined_rois = apply_box_deltas_graph( rois, deltas_specific * config.BBOX_STD_DEV) # 防止超出0-1 refined_rois = clip_boxes_graph(refined_rois, window) # 去除背景 keep = tf.where(class_ids > 0)[:, 0] # 去除背景和得分小的区域 if config.DETECTION_MIN_CONFIDENCE: conf_keep = tf.where(class_scores >= config.DETECTION_MIN_CONFIDENCE)[:, 0] keep = tf.compat.v1.sets.set_intersection(tf.expand_dims(keep, 0), tf.expand_dims(conf_keep, 0)) keep = tf.compat.v1.sparse_tensor_to_dense(keep)[0] # 获得除去背景并且得分较高的框还有种类与得分 # 1. Prepare variables pre_nms_class_ids = tf.gather(class_ids, keep) pre_nms_scores = tf.gather(class_scores, keep) pre_nms_rois = tf.gather(refined_rois, keep) unique_pre_nms_class_ids = tf.unique(pre_nms_class_ids)[0] def nms_keep_map(class_id): ixs = tf.where(tf.equal(pre_nms_class_ids, class_id))[:, 0] class_keep = tf.image.non_max_suppression( tf.gather(pre_nms_rois, ixs), tf.gather(pre_nms_scores, ixs), max_output_size=config.DETECTION_MAX_INSTANCES, iou_threshold=config.DETECTION_NMS_THRESHOLD) class_keep = tf.gather(keep, tf.gather(ixs, class_keep)) gap = config.DETECTION_MAX_INSTANCES - tf.shape(class_keep)[0] class_keep = tf.pad(class_keep, [(0, gap)], mode='CONSTANT', constant_values=-1) class_keep.set_shape([config.DETECTION_MAX_INSTANCES]) return class_keep # 2. 进行非极大抑制 nms_keep = tf.map_fn(nms_keep_map, unique_pre_nms_class_ids, dtype=tf.int64) # 3. 找到符合要求的需要被保留的建议框 nms_keep = tf.reshape(nms_keep, [-1]) nms_keep = tf.gather(nms_keep, tf.where(nms_keep > -1)[:, 0]) # 4. Compute intersection between keep and nms_keep keep = tf.compat.v1.sets.set_intersection(tf.expand_dims(keep, 0), tf.expand_dims(nms_keep, 0)) keep = tf.compat.v1.sparse_tensor_to_dense(keep)[0] # 寻找得分最高的num_keep个框 roi_count = config.DETECTION_MAX_INSTANCES class_scores_keep = tf.gather(class_scores, keep) num_keep = tf.minimum(tf.shape(class_scores_keep)[0], roi_count) top_ids = tf.nn.top_k(class_scores_keep, k=num_keep, sorted=True)[1] keep = tf.gather(keep, top_ids) # Arrange output as [N, (y1, x1, y2, x2, class_id, score)] detections = tf.concat([ tf.gather(refined_rois, keep), tf.compat.v1.to_float(tf.gather(class_ids, keep))[..., tf.newaxis], tf.gather(class_scores, keep)[..., tf.newaxis] ], axis=1) # 如果达不到数量的话就padding gap = config.DETECTION_MAX_INSTANCES - tf.shape(detections)[0] detections = tf.pad(detections, [(0, gap), (0, 0)], "CONSTANT") return detections def norm_boxes_graph(boxes, shape): h, w = tf.split(tf.cast(shape, tf.float32), 2) scale = tf.concat([h, w, h, w], axis=-1) - tf.constant(1.0) shift = tf.constant([0., 0., 1., 1.]) return tf.divide(boxes - shift, scale) class DetectionLayer(Layer): def __init__(self, config=None, **kwargs): super(DetectionLayer, self).__init__(**kwargs) self.config = config def call(self, inputs): rois = inputs[0] mrcnn_class = inputs[1] mrcnn_bbox = inputs[2] image_meta = inputs[3] # 找到window的小数形式 m = parse_image_meta_graph(image_meta) image_shape = m['image_shape'][0] window = norm_boxes_graph(m['window'], image_shape[:2]) # Run detection refinement graph on each item in the batch detections_batch = utils.batch_slice( [rois, mrcnn_class, mrcnn_bbox, window], lambda x, y, w, z: refine_detections_graph(x, y, w, z, self.config), self.config.IMAGES_PER_GPU) # Reshape output # [batch, num_detections, (y1, x1, y2, x2, class_id, class_score)] in # normalized coordinates return tf.reshape( detections_batch, [self.config.BATCH_SIZE, self.config.DETECTION_MAX_INSTANCES, 6]) def compute_output_shape(self, input_shape): return (None, self.config.DETECTION_MAX_INSTANCES, 6) #----------------------------------------------------------# # Detection Target Layer # 该部分代码会输入建议框 # 判断建议框和真实框的重合情况 # 筛选出内部包含物体的建议框 # 利用建议框和真实框编码 # 调整mask的格式使得其和预测格式相同 #----------------------------------------------------------# def overlaps_graph(boxes1, boxes2): """ 用于计算boxes1和boxes2的重合程度 boxes1, boxes2: [N, (y1, x1, y2, x2)]. 返回 [len(boxes1), len(boxes2)] """ b1 = tf.reshape(tf.tile(tf.expand_dims(boxes1, 1), [1, 1, tf.shape(boxes2)[0]]), [-1, 4]) b2 = tf.tile(boxes2, [tf.shape(boxes1)[0], 1]) b1_y1, b1_x1, b1_y2, b1_x2 = tf.split(b1, 4, axis=1) b2_y1, b2_x1, b2_y2, b2_x2 = tf.split(b2, 4, axis=1) y1 = tf.maximum(b1_y1, b2_y1) x1 = tf.maximum(b1_x1, b2_x1) y2 = tf.minimum(b1_y2, b2_y2) x2 = tf.minimum(b1_x2, b2_x2) intersection = tf.maximum(x2 - x1, 0) * tf.maximum(y2 - y1, 0) b1_area = (b1_y2 - b1_y1) * (b1_x2 - b1_x1) b2_area = (b2_y2 - b2_y1) * (b2_x2 - b2_x1) union = b1_area + b2_area - intersection iou = intersection / union overlaps = tf.reshape(iou, [tf.shape(boxes1)[0], tf.shape(boxes2)[0]]) return overlaps def detection_targets_graph(proposals, gt_class_ids, gt_boxes, gt_masks, config): asserts = [ tf.Assert(tf.greater(tf.shape(proposals)[0], 0), [proposals], name="roi_assertion"), ] with tf.control_dependencies(asserts): proposals = tf.identity(proposals) # 移除之前获得的padding的部分 proposals, _ = trim_zeros_graph(proposals, name="trim_proposals") gt_boxes, non_zeros = trim_zeros_graph(gt_boxes, name="trim_gt_boxes") gt_class_ids = tf.boolean_mask(gt_class_ids, non_zeros, name="trim_gt_class_ids") gt_masks = tf.gather(gt_masks, tf.where(non_zeros)[:, 0], axis=2, name="trim_gt_masks") # Handle COCO crowds # A crowd box in COCO is a bounding box around several instances. Exclude # them from training. A crowd box is given a negative class ID. crowd_ix = tf.where(gt_class_ids < 0)[:, 0] non_crowd_ix = tf.where(gt_class_ids > 0)[:, 0] crowd_boxes = tf.gather(gt_boxes, crowd_ix) gt_class_ids = tf.gather(gt_class_ids, non_crowd_ix) gt_boxes = tf.gather(gt_boxes, non_crowd_ix) gt_masks = tf.gather(gt_masks, non_crowd_ix, axis=2) # 计算建议框和所有真实框的重合程度 [proposals, gt_boxes] overlaps = overlaps_graph(proposals, gt_boxes) # 计算和 crowd boxes 的重合程度 [proposals, crowd_boxes] crowd_overlaps = overlaps_graph(proposals, crowd_boxes) crowd_iou_max = tf.reduce_max(crowd_overlaps, axis=1) no_crowd_bool = (crowd_iou_max < 0.001) # Determine positive and negative ROIs roi_iou_max = tf.reduce_max(overlaps, axis=1) # 1. 正样本建议框和真实框的重合程度大于0.5 positive_roi_bool = (roi_iou_max >= 0.5) positive_indices = tf.where(positive_roi_bool)[:, 0] # 2. 负样本建议框和真实框的重合程度小于0.5，Skip crowds. negative_indices = tf.where(tf.logical_and(roi_iou_max < 0.5, no_crowd_bool))[:, 0] # Subsample ROIs. Aim for 33% positive # 进行正负样本的平衡 # 取出最大33%的正样本 positive_count = int(config.TRAIN_ROIS_PER_IMAGE * config.ROI_POSITIVE_RATIO) positive_indices = tf.random_shuffle(positive_indices)[:positive_count] positive_count = tf.shape(positive_indices)[0] # 保持正负样本比例 r = 1.0 / config.ROI_POSITIVE_RATIO negative_count = tf.cast(r * tf.cast(positive_count, tf.float32), tf.int32) - positive_count negative_indices = tf.random_shuffle(negative_indices)[:negative_count] # 获得正样本和负样本 positive_rois = tf.gather(proposals, positive_indices) negative_rois = tf.gather(proposals, negative_indices) # 获取建议框和真实框重合程度 positive_overlaps = tf.gather(overlaps, positive_indices) # 判断是否有真实框 roi_gt_box_assignment = tf.cond( tf.greater(tf.shape(positive_overlaps)[1], 0), true_fn = lambda: tf.argmax(positive_overlaps, axis=1), false_fn = lambda: tf.cast(tf.constant([]),tf.int64) ) # 找到每一个建议框对应的真实框和种类 roi_gt_boxes = tf.gather(gt_boxes, roi_gt_box_assignment) roi_gt_class_ids = tf.gather(gt_class_ids, roi_gt_box_assignment) # 解码获得网络应该有得预测结果 deltas = utils.box_refinement_graph(positive_rois, roi_gt_boxes) deltas /= config.BBOX_STD_DEV # 切换mask的形式[N, height, width, 1] transposed_masks = tf.expand_dims(tf.transpose(gt_masks, [2, 0, 1]), -1) # 取出对应的层 roi_masks = tf.gather(transposed_masks, roi_gt_box_assignment) # Compute mask targets boxes = positive_rois if config.USE_MINI_MASK: # Transform ROI coordinates from normalized image space # to normalized mini-mask space. y1, x1, y2, x2 = tf.split(positive_rois, 4, axis=1) gt_y1, gt_x1, gt_y2, gt_x2 = tf.split(roi_gt_boxes, 4, axis=1) gt_h = gt_y2 - gt_y1 gt_w = gt_x2 - gt_x1 y1 = (y1 - gt_y1) / gt_h x1 = (x1 - gt_x1) / gt_w y2 = (y2 - gt_y1) / gt_h x2 = (x2 - gt_x1) / gt_w boxes = tf.concat([y1, x1, y2, x2], 1) box_ids = tf.range(0, tf.shape(roi_masks)[0]) masks = tf.image.crop_and_resize(tf.cast(roi_masks, tf.float32), boxes, box_ids, config.MASK_SHAPE) # Remove the extra dimension from masks. masks = tf.squeeze(masks, axis=3) # 防止resize后的结果不是1或者0 masks = tf.round(masks) # 一般传入config.TRAIN_ROIS_PER_IMAGE个建议框进行训练， # 如果数量不够则padding rois = tf.concat([positive_rois, negative_rois], axis=0) N = tf.shape(negative_rois)[0] P = tf.maximum(config.TRAIN_ROIS_PER_IMAGE - tf.shape(rois)[0], 0) rois = tf.pad(rois, [(0, P), (0, 0)]) roi_gt_boxes = tf.pad(roi_gt_boxes, [(0, N + P), (0, 0)]) roi_gt_class_ids = tf.pad(roi_gt_class_ids, [(0, N + P)]) deltas = tf.pad(deltas, [(0, N + P), (0, 0)]) masks = tf.pad(masks, [[0, N + P], (0, 0), (0, 0)]) return rois, roi_gt_class_ids, deltas, masks def trim_zeros_graph(boxes, name='trim_zeros'): """ 如果前一步没有满POST_NMS_ROIS_TRAINING个建议框，会有padding 要去掉padding """ non_zeros = tf.cast(tf.reduce_sum(tf.abs(boxes), axis=1), tf.bool) boxes = tf.boolean_mask(boxes, non_zeros, name=name) return boxes, non_zeros class DetectionTargetLayer(Layer): """找到建议框的ground_truth Inputs: proposals: [batch, N, (y1, x1, y2, x2)]建议框 gt_class_ids: [batch, MAX_GT_INSTANCES]每个真实框对应的类 gt_boxes: [batch, MAX_GT_INSTANCES, (y1, x1, y2, x2)]真实框的位置 gt_masks: [batch, height, width, MAX_GT_INSTANCES]真实框的语义分割情况 Returns: rois: [batch, TRAIN_ROIS_PER_IMAGE, (y1, x1, y2, x2)]内部真实存在目标的建议框 target_class_ids: [batch, TRAIN_ROIS_PER_IMAGE]每个建议框对应的类 target_deltas: [batch, TRAIN_ROIS_PER_IMAGE, (dy, dx, log(dh), log(dw)]每个建议框应该有的调整参数 target_mask: [batch, TRAIN_ROIS_PER_IMAGE, height, width]每个建议框语义分割情况 """ def __init__(self, config, **kwargs): super(DetectionTargetLayer, self).__init__(**kwargs) self.config = config def call(self, inputs): proposals = inputs[0] gt_class_ids = inputs[1] gt_boxes = inputs[2] gt_masks = inputs[3] # 对真实框进行编码 names = ["rois", "target_class_ids", "target_bbox", "target_mask"] outputs = utils.batch_slice( [proposals, gt_class_ids, gt_boxes, gt_masks], lambda w, x, y, z: detection_targets_graph( w, x, y, z, self.config), self.config.IMAGES_PER_GPU, names=names) return outputs def compute_output_shape(self, input_shape): return [ (None, self.config.TRAIN_ROIS_PER_IMAGE, 4), # rois (None, self.config.TRAIN_ROIS_PER_IMAGE), # class_ids (None, self.config.TRAIN_ROIS_PER_IMAGE, 4), # deltas (None, self.config.TRAIN_ROIS_PER_IMAGE, self.config.MASK_SHAPE[0], self.config.MASK_SHAPE[1]) # masks ] def compute_mask(self, inputs, mask=None): return [None, None, None, None]

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""" Created on Apr 23, 2020 Configuration scripts for model @author: Levan Tsinadze """ from argparse import Namespace import torch from torch import nn from torch.jit import trace, ScriptModule # Config Parameters _DEF_DEVICE = 'cuda' _CPU_DEVICE = 'cpu' GPU = _DEF_DEVICE CPU = _CPU_DEVICE def init_device(conf: Namespace) -> str: """ Initialize device to bind model abd data Args: conf: configuration parameters Returns: device name """ return GPU if conf.gpu and torch.cuda.is_available() else CPU @torch.no_grad() def script_model(model: nn.Module, sizes: list) -> ScriptModule: """ Generates converts model to the cript model Args: model: model to convert sizes: sizes of input Returns: graph_model: converted model """ xs = tuple(torch.randn(1, 3, s, s, requires_grad=False) for s in sizes) graph_model = trace(model.eval(), xs) graph_model.eval() return graph_model

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/Maya/realtimeExp/Read_Csv_File_01.py

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hamin7/BCI_and_Face_Tracking

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import argparse, csv, sys from settings import * # command arguments parse = argparse.ArgumentPareser(description='csv to postgres', \ fromfile_prefix_chars="@" ) parser.add_argument('file', help='csv file to import', action='store') args = parser.parse_args() csv_file = args.file # open csv file with open(csv_file, 'rb') as csvfile: # get number of columns for line in csvfile.readlines(): array = line.split(',') first_item = array[0] num_columns = len(array) csvfile.seek(0) reader = csv.reader(csvfile, delimiter=' ') included_cols = [1, 2, 6, 7] for row in reader: content = list(row[i] for i in included_cols) print content

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#%% import matplotlib.pyplot as plt import matplotlib as mpl import numpy as np x = np.linspace(0, 30, 100) plt.plot(x * np.pi / 180, np.sin(x)) plt.xlabel('Angle [rad]') plt.ylabel('sin(x)') plt.axis('tight') plt.show()

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/project/project/urls.py

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hfaezeh/test

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from django.conf import settings from django.conf.urls.static import static from django.conf.urls import include, url from django.contrib import admin from app.views import * from users.views import * from polls.views import * from project.routers import HybridRouter # We use a single global DRF Router that routes views from all apps in project router = HybridRouter() # app views and viewsets router.register(r'tool', ToolViewSet, r"tool") router.add_api_view(r'author', url(r'^author/(?P<pk>.*)$',AuthorViewSet.as_view(), name=r"author")) router.register(r'book', BookViewSet, r"book") router.register(r'user', UserViewSet, r"user") router.register(r'user_test', UserModelViewSet, r'user_test') router.add_api_view(r'auth', url(r'^auth/$', ObtainAuthToken.as_view(), name=r"auth")) router.add_api_view(r'file', url(r'^file/(?P<pk>.*)$', FileViewSet.as_view(), name=r'file')) urlpatterns = [ # default django admin interface (currently unused) url(r'^admin/', include(admin.site.urls)), # root view of our REST api, generated by Django REST Framework's router url(r'^api/', include(router.urls, namespace='api')), # index page should be served by django to set cookies, headers etc. url(r'^$', index_view, {}, name='index'), #url(r'^api/upload', upload_file, {}, name='upload'), ] # let django built-in server serve static and media content urlpatterns += static(settings.STATIC_URL, document_root=settings.STATIC_ROOT) urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)

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/src/BluetoothPoller.py

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mehdilauters/wifiScanMap

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from threading import Lock import threading import time import subprocess import re import PrctlTool class BluetoothPoller(threading.Thread): def __init__(self, app): threading.Thread.__init__(self) self.application = app self.lock = Lock() self.stations = [] self.running = True #setting the thread running to true self.major_device_description = { 0b00000: 'miscalleneous', 0b00001: 'computer', 0b00010: 'mobile', 0b00011: 'lan', 0b00100: 'audio', 0b00101: 'peripheral', 0b00110: 'imaging', 0b00111: 'wearable', 0b01000: 'toy', 0b01001: 'health', 0b11111: 'unknown', } if self.application.args.sleep is not None: self.sleep = int(self.application.args.sleep) else: self.sleep = 1 def parse_class(self, _class): return (_class >> 8 & 0b0000000000011111) def get_major_device_description(self, major): try: return self.major_device_description[major] except: self.application.log('bluetooth', 'invalid class %s'%major) def run(self): PrctlTool.set_title('bluetooth poller') try: while self.running: cmd = ['hcitool', 'inq'] pos = self.application.getPosition() fix = pos is not None if fix: lon, lat, source = pos process = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE) process.wait() (stdoutdata, stderrdata) = process.communicate(); res = re.findall("\s(.*)\sclock.*\sclass:\s(.*)", stdoutdata) stations = [] if res is not None: for row in res: station = {} if fix: station["latitude"] = lat station["longitude"] = lon station["gps"] = source == 'gps' station['bssid'] = row[0].strip() station['manufacturer'] = self.application.getManufacturer(station['bssid']) station['class'] = int(row[1].strip(), 0) station['class_description'] = self.get_major_device_description(self.parse_class(station['class'])) cmd = ['hcitool', 'name', station['bssid']] process = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE) process.wait() (stdoutdata, stderrdata) = process.communicate(); station['name'] = stdoutdata stations.append(station) with self.lock: self.stations = stations time.sleep(self.sleep) except: self.application.log('bluetooth', 'error') def getNetworks(self): with self.lock: return self.networks def stop(self): self.running = False

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abhishekbalu/rosqt-publisher

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# -*- coding: utf-8 -*- from __future__ import print_function import argparse import os import stat import sys # find the import for catkin's python package - either from source space or from an installed underlay if os.path.exists(os.path.join('/opt/ros/jade/share/catkin/cmake', 'catkinConfig.cmake.in')): sys.path.insert(0, os.path.join('/opt/ros/jade/share/catkin/cmake', '..', 'python')) try: from catkin.environment_cache import generate_environment_script except ImportError: # search for catkin package in all workspaces and prepend to path for workspace in "/opt/ros/jade".split(';'): python_path = os.path.join(workspace, 'lib/python2.7/dist-packages') if os.path.isdir(os.path.join(python_path, 'catkin')): sys.path.insert(0, python_path) break from catkin.environment_cache import generate_environment_script code = generate_environment_script('/home/abhishek/jade_workspace/abhishek22/build/devel/env.sh') output_filename = '/home/abhishek/jade_workspace/abhishek22/build/catkin_generated/setup_cached.sh' with open(output_filename, 'w') as f: #print('Generate script for cached setup "%s"' % output_filename) f.write('\n'.join(code)) mode = os.stat(output_filename).st_mode os.chmod(output_filename, mode | stat.S_IXUSR)

[ "abhisheklokesh6008@gmail.com" ]

abhisheklokesh6008@gmail.com

6c0d5bbd04735a5cb28455fee37f5ad5beb791d7

bd1362c60313784c90013dfc9f0169e64389bf27

/scripts/asos/wind_chill_hours.py

aaccb84c833aa21cf7bbb32f0946b0e7ddf8734a

[]

no_license

ForceCry/iem

391aa9daf796591909cb9d4e60e27375adfb0eab

4b0390d89e6570b99ca83a5fa9b042226e17c1ad

refs/heads/master

2020-12-24T19:04:55.517409

2013-04-09T14:25:36

null

0

null

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py

from pyIEM import iemdb import mx.DateTime, sys i = iemdb.iemdb() asos = i['asos'] for yr in range(1973,2009): hrs = [0,0,0,0] sql = "SELECT to_char(valid, 'YYYY-MM-DD HH24') as d, min(wind_chill(tmpf,sknt)) as wc from t%s WHERE \ station = '%s' and tmpf < 32 and tmpf > -50 and sknt > 0 \ and valid > '%s-10-01' GROUP by d" % (yr, sys.argv[1], yr) rs = asos.query(sql).dictresult() for i in range(len(rs)): wc = float( rs[i]['wc'] ) if (wc < -30): hrs[0] += 1 if (wc < -20): hrs[1] += 1 if (wc < -10): hrs[2] += 1 if (wc < 0): hrs[3] += 1 sql = "SELECT to_char(valid, 'YYYY-MM-DD HH24') as d, min(wind_chill(tmpf,sknt)) as wc from t%s WHERE \ station = '%s' and tmpf < 32 and tmpf > -50 and sknt > 0 \ and valid < '%s-04-01' GROUP by d" % (yr+1, sys.argv[1], yr+1) rs = asos.query(sql).dictresult() for i in range(len(rs)): wc = float( rs[i]['wc'] ) if (wc < -30): hrs[0] += 1 if (wc < -20): hrs[1] += 1 if (wc < -10): hrs[2] += 1 if (wc < 0): hrs[3] += 1 print "%s,%s,%s,%s,%s" % (yr, hrs[0],hrs[1],hrs[2],hrs[3])

[ "akrherz@95f8c243-6001-0410-b151-932e6a9ed213" ]

akrherz@95f8c243-6001-0410-b151-932e6a9ed213

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/async_reduce/__init__.py

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[ "MIT" ]

permissive

tzoiker/async-reduce

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refs/heads/master

2020-05-05T05:12:41.177854

2019-03-31T12:53:54

2019-04-04T17:10:51

179,743,101

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MIT

2019-04-05T19:32:28

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py

from .async_reducer import AsyncReducer from .async_reduceable import async_reduceable __all__ = 'async_reduce', 'async_reduceable', async_reduce = AsyncReducer()

[ "sirkonst@gmail.com" ]

sirkonst@gmail.com

0a1230cf13d2fbd86cd3dce52b2abb63f19c142a

451e9ea8a8c4317bc03b4832d3093b8317a12e08

/weather/views.py

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[]

no_license

MehediHasanNasim/Weather-Checking-API

db73f36b1e6a800694e97ae5b0e3595945c5d0ad

49dcda33cb58371f2bc6b506cf072951d717c49d

refs/heads/main

2023-06-03T19:56:10.091400

2021-06-24T19:12:15

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from django.shortcuts import render, redirect, HttpResponseRedirect, get_object_or_404 # Create your views here. def home(request): import json import requests if request.method == "POST": zipcode = request.POST['zipcode'] #return render(request, 'home.html', {'zipcode': zipcode}) api_request = requests.get("https://www.airnowapi.org/aq/observation/zipCode/current/?format=application/json&zipCode=" + zipcode + "&distance=5&API_KEY=B2910B43-3265-49E4-BE07-40DB21B3DDDE") #https://www.airnowapi.org/aq/observation/zipCode/current/?format=application/json&zipCode=20001&distance=5&API_KEY=B2910B43-3265-49E4-BE07-40DB21B3DDDE try: api = json.loads(api_request.content) except Exception as e: api = "Error...." if api[0]['Category']['Name'] == "Good": category_description = "(0-50) Air quality is considered satisfactory" category_color = "good" elif api[0]['Category']['Name'] == "Moderate": category_description= "(51-100) Air is acceptable" category_color = "moderate" elif api[0]['Category']['Name'] == "Unhealty for Sensitive Groups": category_description= "(101-150) Risk for weak lung people" category_color = "USG" elif api[0]['Category']['Name'] == "Unhealthy": category_description= "(151-200) Everyone will have suffer in health issue" category_color = "unhealthy" elif api[0]['Category']['Name'] == "Very Unhealthy": category_description= "(201-250) it will effect seriously" category_color = "veryunhealthy" elif api[0]['Category']['Name'] == "Hazardous": category_description= "(251-300) Health warning emergency condition" category_color = "hazardous" diction= { 'api': api, 'category_description':category_description, 'category_color':category_color,} return render(request, 'home.html', context= diction) else: return render(request, 'home.html', ) def about(request): diction= {} return render(request, 'about.html', context= diction)

[ "75909031+MehediHasanNasim@users.noreply.github.com" ]

75909031+MehediHasanNasim@users.noreply.github.com

5bd01557125f2b6645afe7314023655b308fda80

0374289f671d93a0d1d2b14fd813b88a4dd81f6b

/chatbot-master/cali_main.py

7e3891c1524004352cf06a63dbf8fba2d1778c0e

[]

no_license

dhruvbabbar/chatbot

9b62d4b1e0418926e020906952a7303eca018e5e

f6b27615452625d3da04e5a2207d5a514c0d71a7

refs/heads/master

2020-03-08T03:31:36.909623

2018-05-06T13:55:56

127,893,610

0

null

2018-05-06T13:55:56

2018-04-03T10:48:43

Python

UTF-8

Python

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py

from django.shortcuts import render_to_response from django.utils.safestring import mark_safe def calendar(request, year, month): my_workouts = Workouts.objects.order_by('my_date').filter( my_date__year=year, my_date__month=month ) cal = WorkoutCalendar(my_workouts).formatmonth(year, month) return render_to_response('my_template.html', {'calendar': mark_safe(cal),})

[ "dhruvbabbar349@gmail.com" ]

dhruvbabbar349@gmail.com

675c9c10775fd79f1259f821aa47ffad8afe99ba

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/crawls/crawls/spiders/baldor.py

9e4dfdc079868243244e1595ee5d45d60340b8e5

[]

no_license

HeraskoA/crawls

a4c07858075495062319d646861f734fa7201e38

887cd844847f33178709c3abdd8a770d94e899a6

refs/heads/master

2021-01-21T14:39:32.619133

2017-10-24T14:37:11

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# -*- coding: utf-8 -*- import pandas as pd import scrapy from crawls.items import BaldorDodgeItem import re out = pd.read_csv("crawls/spiders/data/diff_baldor.csv", sep=',') catalog = [str(item).strip() for item in list(out.catalog_number)] description = list(out.description) ids = list(out.id) catalog_descr = dict(zip(catalog, description)) catalog_ids = dict(zip(catalog, ids)) class Mcr(scrapy.Spider): name = "baldor_dodge" def start_requests(self): for row in catalog: yield self.request(row) def request(self, row): url = 'http://www.baldor.com/catalog/' + row return scrapy.Request(url=url, callback=self.parse_item, dont_filter=True, meta={'row': row} ) def create_item(self, row, img, doc_name, doc_url, specs): item = BaldorDodgeItem() item['ids'] = catalog_ids[row] item['catalog_number'] = row item['description'] = catalog_descr[row] item['img'] = img item['doc_name'] = doc_name item['doc_url'] = doc_url item['specs'] = specs return item def construct_table(self, table): table = table.replace('<div class="section detail-table product-overview">', '<table>') table = re.sub(r'</div>(\n|\s)+<div class="col span_1_of_2">', '', table) table = table.replace('<div class="col span_1_of_2">', '') table = re.sub(r'</div>(\n|\s)+</div>(\n|\s)+</div>(\n|\s)+</div>', '</div></table></div>', table) table = re.sub(r'</div>(\n|\s)+<div>', '</tr><tr>', table) table = table.replace('</div></table>', '</tr></table>') table = table.replace('<div>', '<tr>') table = table.replace('<span class="label">', '<td>').replace('<span class="value">', '<td>') table = table.replace('</span>', '</td>') return table def custom_extractor(self, response, expression): data = response.xpath(expression).extract_first() return data if data else '' def parse_item(self, response): row = response.meta['row'] img = self.custom_extractor(response, '//*[@id="catalog-detail"]/img/@data-src') img = 'http://www.baldor.com' + img + '?bc=white&as=1&h=256&w=256' if img != '/api/images/451' else '' specs = self.custom_extractor(response, '//div[@data-tab="specs"]') specs = self.construct_table(specs) if specs != '' else '' key = response.xpath('//*[@id="nav-desktop-breadcrumb"]/ul/li/a/text()').extract()[-1] key_tire = 0 try: int(key.split()[-1]) except Exception: pass else: key_tire = key.replace(' ', '-') key_upper = key.upper() doc_name, doc_url = '', '' expression = '//a[@class="recordClick" and text()="%s"]' % key item = response.xpath(expression) if not item: expression = '//a[@class="recordClick" and text()="%s"]' % key_upper item = response.xpath(expression) if not item and key_tire: expression = '//a[@class="recordClick" and text()="%s"]' % key_tire item = response.xpath(expression) if not item: expression = '//a[@class="recordClick" and starts-with(text(), "%s")]' % key item = response.xpath(expression) if not item: expression = '//a[@class="recordClick" and starts-with(text(), "%s")]' % key_upper item = response.xpath(expression) if not item and key_tire: expression = '//a[@class="recordClick" and starts-with(text(), "%s")]' % key_tire item = response.xpath(expression) if not item: expression = '//a[@class="recordClick" and text()="Dodge %s"]' % key item = response.xpath(expression) if not item and key_tire: expression = '//a[@class="recordClick" and text()="Dodge %s"]' % key_tire item = response.xpath(expression) if not item: expression = '//a[@class="recordClick" and contains(text(), "Dodge") and contains(text(), "%s")]' % key item = response.xpath(expression) if not item: expression = '//a[@class="recordClick" and contains(text(), "Dodge") and contains(text(), "%s")]' % key_upper item = response.xpath(expression) if not item and key_tire: expression = '//a[@class="recordClick" and contains(text(), "Dodge") and contains(text(), "%s")]' % key_tire item = response.xpath(expression) if not item: expression = '//a[@class="recordClick" and contains(text(), "%s")]' % key item = response.xpath(expression) if not item: expression = '//a[@class="recordClick" and contains(text(), "%s")]' % key_upper item = response.xpath(expression) if not item and key_tire: expression = '//a[@class="recordClick" and contains(text(), "%s")]' % key_tire item = response.xpath(expression) if not item: key_split = key.split() for part in key_split: expression = '//a[@class="recordClick" and contains(text(), "%s")]' % part item = response.xpath(expression) if item: break if not item: item = response.xpath('//ul[@class="list-icon-document"]/li[1]/a') doc_name = self.custom_extractor(item, './text()') doc_url = item.xpath('./@href').extract_first() doc_url = response.urljoin(doc_url) if doc_url else '' return self.create_item(row, img, doc_name, doc_url, specs)

[ "andrey.herasko@gmail.com" ]

andrey.herasko@gmail.com

f0752a02362e4d75af1e71dddab5a542414153f0

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/Problem 2 2021 lab3.py

cbf1999a0654cd6cfc7b0710be6ae2ac8ba6424d

[]

no_license

jkendall5490/HELLOWORLD

8223b8dd7da9e2235763f2f0c8ca92d87e3078d6

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refs/heads/main

2023-03-24T23:01:18.978074

2021-03-18T10:26:49

303,903,360

0

null

UTF-8

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false

323

py

#shop.py def check_money(total_cost, customer_money): #Your code here if customer_money - total_cost >=0: return True else: return False #This should print False can_pay = check_money(107, 49) print(can_pay) #This should print True can_pay = check_money(6, 88) print(can_pay)

[ "noreply@github.com" ]

jkendall5490.noreply@github.com

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/7b.py

953487043bc15f1e7425b5ab966ea7d456e9c95a

[]

no_license

nathanleiby/advent-of-code-2018

9fe43a97a80290338b8724e2c07c8560f16d9d3b

047ec34ad936e33fc5d530f8403aa59983325bbc

refs/heads/master

2020-04-09T10:05:31.905048

2018-12-14T06:01:58

160,257,964

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UTF-8

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2,956

py

from toposort import toposort, toposort_flatten ex_i = { 'A': {'C'}, 'F': {'C'}, 'B': {'A'}, 'D': {'A'}, 'E': {'B', 'D', 'F'}, } ex_i_str ="""Step C must be finished before step A can begin. Step C must be finished before step F can begin. Step A must be finished before step B can begin. Step A must be finished before step D can begin. Step B must be finished before step E can begin. Step D must be finished before step E can begin. Step F must be finished before step E can begin.""" def res(inp, num_workers=2, duration_boost=0): out = [] from copy import deepcopy inp_c = deepcopy(inp) available_work = get_available_work(inp_c) ongoing_work = {} # { letter : remaining_seconds } current_second = -1 while len(inp_c): current_second += 1 # do work to_delete = [] for k in ongoing_work: ongoing_work[k] -= 1 if ongoing_work[k] == 0: to_delete.append(k) # remove complete work for k in to_delete: del(ongoing_work[k]) remove_from_graph(inp_c, k) if len(to_delete): # ONLY run this once, even if multiple deletions # update available_work, in case k unblocked new work available_work += get_available_work(inp_c) available_work = sorted(list(set(available_work))) for o in ongoing_work: available_work.remove(o) print("available_work", available_work) # get more work while len(ongoing_work) < num_workers and len(available_work) > 0: next_item = available_work[0] available_work = available_work[1:] duration = ord(next_item) - 64 + duration_boost ongoing_work[next_item] = duration # record order, more relevant to problem 7 but just in case out += next_item print("second = ", current_second) print("ongoing_work = ", ongoing_work) return ("".join(list(out)), current_second) # gets next item and mutates underlying graph to remove it def get_available_work(graph): # { { 2 , 1 }, { 3 } , { 4 , 5 } } => { 1 , 2 } o = list(toposort(graph)) if len(o): return sorted(list(o[0])) return [] def remove_from_graph(graph, item): # remove as a top-level key if item in graph: del(graph[item]) # remove as a dep for k in graph: dep = graph[k] if item in dep: dep.remove(item) def s_to_dag(s): out = {} lines = s.splitlines() for l in lines: first = l[5] then = l[36] if not out.get(then): out[then] = set() out[then].add(first) return out print(res(ex_i)) assert(res(ex_i) == ("CAFBDE", 15)) with open('./7-input', 'r') as f: dag = s_to_dag(f.read()) #print(dag) print("RESULT = ", res(dag, num_workers=5, duration_boost=60))

[ "nathan.leiby@clever.com" ]

nathan.leiby@clever.com

19bb961a475c9140cdf1d0f5b1b933a281056798

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/variables/ejercicio03.py

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[]

no_license

bl00p1ng/ejercicios-basicos-python

780b7050184d75f9a9af5c641bd57e2c13357a4c

53b974257d0729a00b0ee57c5eb877845784f176

refs/heads/main

2023-03-14T06:30:24.925725

2021-03-05T21:53:30

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def run(): # Ejercicio 3 # Crea las variables nombre, direction y teléfono y asígnale los valores correspondientes. Muestra los valores de # esas variables por pantalla de tal forma que el resultado del programa sea el mismo que en el ejercicio 2. name = 'Andrés Felipe López' phone = '509-684-1752' address = '2000 Calico Drive, Colville WA' print('Nombre: ' + name) print('Teléfono: ' + phone) print('Dirección: ' + address) if __name__ == '__main__': run()

[ "blooping@protonmail.com" ]

blooping@protonmail.com

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/app.py

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[]

no_license

ChanonVilaiyuk/app

2799e679dd536c3d5d6203da75ffbc4b2f6273c2

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refs/heads/master

2021-05-05T10:23:12.221159

2017-09-18T14:15:49

null

0

null

UTF-8

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false

13

py

# v001 # v002

[ "ta.animator@gmail.com" ]

ta.animator@gmail.com

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/testsuite/pnoise-gabor/run.py

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[ "BSD-3-Clause", "LicenseRef-scancode-generic-cla" ]

permissive

jeremyselan/OpenShadingLanguage

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refs/heads/master

2021-01-18T04:50:00.061446

2012-06-27T22:51:48

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#!/usr/bin/python command = oslc("../common/shaders/testpnoise.osl") command += testshade("-g 512 512 -od uint8 -o Cout out.tif -sparam noisename gabor testpnoise") outputs = [ "out.txt", "out.tif" ]

[ "lg@larrygritz.com" ]

lg@larrygritz.com

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/98. Validate Binary Search Tree.py

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[ "MIT" ]

permissive

Nriver/leetcode

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refs/heads/master

2021-06-08T20:38:24.731309

2021-05-10T02:02:35

162,373,286

1

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# -*- coding: utf-8 -*- # @Author: Zengjq # @Date: 2018-12-19 10:46:12 # @Last Modified by: Zengjq # @Last Modified time: 2019-02-20 17:00:12 class Solution: # 100% 递归最快 def isValidBST(self, root: 'TreeNode') -> 'bool': # 注意最开始启动递归的时候传的最大和最小值都要是None return self.isValid(root, None, None) def isValid(self, root, min, max): if (root == None): return True if (min != None and root.val <= min): return False if (max != None and root.val >= max): return False return self.isValid(root.left, min, root.val) and self.isValid(root.right, root.val, max) # 58% solution # 中序遍历慢 # def isValidBST(self, root: 'TreeNode') -> 'bool': # ret = self.inorder(root) # return ret == sorted(list(set(ret))) # def inorder(self, root): # if root is None: # return [] # return self.inorder(root.left) + [root.val] + self.inorder(root.right) # Tree definition found in here # https://leetcode.com/problems/recover-binary-search-tree/discuss/32539/Tree-Deserializer-and-Visualizer-for-Python class TreeNode: def __init__(self, val, left=None, right=None): self.val = val self.left = left self.right = right def __repr__(self): return 'TreeNode({})'.format(self.val) def deserialize(string): if string == '{}': return None nodes = [None if val.strip() == 'null' else TreeNode(int(val.strip())) for val in string.strip('[]{}').split(',')] kids = nodes[::-1] root = kids.pop() for node in nodes: if node: if kids: node.left = kids.pop() if kids: node.right = kids.pop() return root test_cases = (deserialize('[2, 1, 3]'), deserialize('[5, 1, 4, null, null, 3, 6]'), ) solution = Solution() for test_case in test_cases: print(solution.isValidBST(test_case))

[ "junqing.zeng@gmail.com" ]

junqing.zeng@gmail.com

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/posts/admin.py

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no_license

derrickps/getsocialproject

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refs/heads/main

2023-05-30T14:26:57.013143

2021-06-19T08:01:23

378,340,342

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null

UTF-8

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py

from django.contrib import admin from .models import Post, Comment # Register your models here. admin.site.register(Post) admin.site.register(Comment) # admin.site.register(Like) # change in admin done in apps.py

[ "psderrickit@gmail.com" ]

psderrickit@gmail.com

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/maps/recommend.py

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[]

no_license

blvck-root/restaurant_ratings

97c38f4d224ffaae3e4eb4f23990db9e2872a1ec

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refs/heads/main

2023-08-17T12:19:04.782392

2020-12-08T17:43:00

null

0

null

UTF-8

Python

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8,596

py

"""A Yelp-powered Restaurant Recommendation Program""" from abstractions import * from data import ALL_RESTAURANTS, CATEGORIES, USER_FILES, load_user_file from ucb import main, trace, interact from utils import distance, mean, zip, enumerate, sample from visualize import draw_map ################################## # Phase 2: Unsupervised Learning # ################################## def find_closest(location, centroids): """Return the centroid in centroids that is closest to location. If multiple centroids are equally close, return the first one. >>> find_closest([3.0, 4.0], [[0.0, 0.0], [2.0, 3.0], [4.0, 3.0], [5.0, 5.0]]) [2.0, 3.0] """ # BEGIN Question 3 return min(centroids, key=lambda x: distance(location, x)) # END Question 3 def group_by_first(pairs): """Return a list of pairs that relates each unique key in the [key, value] pairs to a list of all values that appear paired with that key. Arguments: pairs -- a sequence of pairs >>> example = [ [1, 2], [3, 2], [2, 4], [1, 3], [3, 1], [1, 2] ] >>> group_by_first(example) [[2, 3, 2], [2, 1], [4]] """ keys = [] for key, _ in pairs: if key not in keys: keys.append(key) return [[y for x, y in pairs if x == key] for key in keys] def group_by_centroid(restaurants, centroids): """Return a list of clusters, where each cluster contains all restaurants nearest to a corresponding centroid in centroids. Each item in restaurants should appear once in the result, along with the other restaurants closest to the same centroid. """ # BEGIN Question 4 pairs = [] # centroid-restaurant pairs for restaurant in restaurants: location = restaurant_location(restaurant) # restaurant location centroid = find_closest(location, centroids) # closest centroid to restaurant location pairs.append([centroid, restaurant]) return group_by_first(pairs) # END Question 4 def find_centroid(cluster): """Return the centroid of the locations of the restaurants in cluster.""" # BEGIN Question 5 locations = list(map(restaurant_location, cluster)) latitudes = [] longitudes = [] for loc in locations: latitudes.append(loc[0]) longitudes.append(loc[1]) return [mean(latitudes), mean(longitudes)] # END Question 5 def k_means(restaurants, k, max_updates=100): """Use k-means to group restaurants by location into k clusters.""" assert len(restaurants) >= k, 'Not enough restaurants to cluster' old_centroids, n = [], 0 # Select initial centroids randomly by choosing k different restaurants centroids = [restaurant_location(r) for r in sample(restaurants, k)] while old_centroids != centroids and n < max_updates: old_centroids = centroids # BEGIN Question 6 clusters = group_by_centroid(restaurants, centroids) centroids = [find_centroid(cluster) for cluster in clusters] # END Question 6 n += 1 return centroids ################################ # Phase 3: Supervised Learning # ################################ def find_predictor(user, restaurants, feature_fn): """Return a rating predictor (a function from restaurants to ratings), for a user by performing least-squares linear regression using feature_fn on the items in restaurants. Also, return the R^2 value of this model. Arguments: user -- A user restaurants -- A sequence of restaurants feature_fn -- A function that takes a restaurant and returns a number """ reviews_by_user = {review_restaurant_name(review): review_rating(review) for review in user_reviews(user).values()} xs = [feature_fn(r) for r in restaurants] ys = [reviews_by_user[restaurant_name(r)] for r in restaurants] # BEGIN Question 7 def sum_squares(list1, list2=None): list2 = list1 if list2 is None else list2 mean1 = mean(list1) mean2 = mean(list2) return sum([(x - mean1) * (y - mean2) for x, y in zip(list1, list2)]) # sum squares s_xx = sum_squares(xs) s_yy = sum_squares(ys) s_xy = sum_squares(xs, ys) # regression coefficients and r_squared b = s_xy / s_xx a = mean(ys) - b * mean(xs) r_squared = s_xy ** 2 / (s_xx * s_yy) # END Question 7 def predictor(restaurant): return b * feature_fn(restaurant) + a return predictor, r_squared def best_predictor(user, restaurants, feature_fns): """Find the feature within feature_fns that gives the highest R^2 value for predicting ratings by the user; return a predictor using that feature. Arguments: user -- A user restaurants -- A list of restaurants feature_fns -- A sequence of functions that each takes a restaurant """ reviewed = user_reviewed_restaurants(user, restaurants) # BEGIN Question 8 predictors = [find_predictor(user, reviewed, fn) for fn in feature_fns] return max(predictors, key=lambda x: x[1])[0] # END Question 8 def rate_all(user, restaurants, feature_fns): """Return the predicted ratings of restaurants by user using the best predictor based on a function from feature_fns. Arguments: user -- A user restaurants -- A list of restaurants feature_fns -- A sequence of feature functions """ predictor = best_predictor(user, ALL_RESTAURANTS, feature_fns) reviewed = user_reviewed_restaurants(user, restaurants) # BEGIN Question 9 def rate(restaurant): if restaurant in reviewed: return user_rating(user, restaurant_name(restaurant)) else: return predictor(restaurant) return {restaurant_name(r): rate(r) for r in restaurants} # END Question 9 def search(query, restaurants): """Return each restaurant in restaurants that has query as a category. Arguments: query -- A string restaurants -- A sequence of restaurants """ # BEGIN Question 10 return [r for r in restaurants if query in restaurant_categories(r)] # END Question 10 def feature_set(): """Return a sequence of feature functions.""" return [lambda r: mean(restaurant_ratings(r)), restaurant_price, lambda r: len(restaurant_ratings(r)), lambda r: restaurant_location(r)[0], lambda r: restaurant_location(r)[1]] @main def main(*args): import argparse parser = argparse.ArgumentParser( description='Run Recommendations', formatter_class=argparse.RawTextHelpFormatter ) parser.add_argument('-u', '--user', type=str, choices=USER_FILES, default='test_user', metavar='USER', help='user file, e.g.\n' + '{{{}}}'.format(','.join(sample(USER_FILES, 3)))) parser.add_argument('-k', '--k', type=int, help='for k-means') parser.add_argument('-q', '--query', choices=CATEGORIES, metavar='QUERY', help='search for restaurants by category e.g.\n' '{{{}}}'.format(','.join(sample(CATEGORIES, 3)))) parser.add_argument('-p', '--predict', action='store_true', help='predict ratings for all restaurants') parser.add_argument('-r', '--restaurants', action='store_true', help='outputs a list of restaurant names') args = parser.parse_args() # Output a list of restaurant names if args.restaurants: print('Restaurant names:') for restaurant in sorted(ALL_RESTAURANTS, key=restaurant_name): print(repr(restaurant_name(restaurant))) exit(0) # Select restaurants using a category query if args.query: restaurants = search(args.query, ALL_RESTAURANTS) else: restaurants = ALL_RESTAURANTS # Load a user assert args.user, 'A --user is required to draw a map' user = load_user_file('{}.dat'.format(args.user)) # Collect ratings if args.predict: ratings = rate_all(user, restaurants, feature_set()) else: restaurants = user_reviewed_restaurants(user, restaurants) names = [restaurant_name(r) for r in restaurants] ratings = {name: user_rating(user, name) for name in names} # Draw the visualization if args.k: centroids = k_means(restaurants, min(args.k, len(restaurants))) else: centroids = [restaurant_location(r) for r in restaurants] draw_map(centroids, restaurants, ratings)

[ "m.ndlovu@alustudent.com" ]

m.ndlovu@alustudent.com

c8501aec9cf89872de343889e16ce6003850dba2

d322b0ee85c61bcb8d26ad53b947ee6bba5c8453

/HW1_code/HW1.py

bc5e3fbdaed2420f5f076fc01a8aa2f7f0d5f028

[]

no_license

jwymanumich/SI650

17f15eddf08a6aedde014f9a7abc2063f7e79bb5

4e51a69ca7dfcf660da318ac38b5d64f6d8bd263

refs/heads/master

2020-07-30T14:36:52.437461

2019-09-23T23:02:44

210,265,892

0

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from collections import defaultdict import math import matplotlib.pyplot as plt import nltk from nltk.stem import * import operator import plotly.express as px import plotly.graph_objects as go import re def remove_stopwords_from_collection(collection): ''' Return a new collection with no stop words ''' collection_out = {} collection_out['Name'] = collection['Name'] collection_out['documents'] = [] for document in collection['documents']: out_document = {'line':document['line'], "words":[], 'POS':[], "STOP_WORD":[]} for index, sw in enumerate(document['STOP_WORD']): if(sw == False): out_document['words'].append(document['words'][index]) out_document['POS'].append(document['POS'][index]) collection_out['documents'].append(out_document) return collection_out def remove_stopwords_from_inverted_index(inverted_index): ''' Return a new inverted index with no stop words ''' out_inverted_index = {} for cur_word in inverted_index: if(inverted_index[cur_word]['STOP_WORD'] == "False"): out_inverted_index[cur_word] = inverted_index[cur_word] return out_inverted_index def frequency_of_stopwords(inverted_index): '''percentage of the word occurrences that are stopwords. counted from inverted_index and multipled by occurence count''' words_total = sum(inverted_index[item]['total_frequency'] for item in inverted_index) stop_words_total = sum(inverted_index[item]['total_frequency'] for item in inverted_index if inverted_index[item]['STOP_WORD'] is "True") return [stop_words_total, words_total, float(stop_words_total)/words_total] def percentage_of_capital_letters(collection): ''' Count the percentage of total characters that are upper case. This needs to use the collection to insure that we are not losing case infromation in the inverted_indes ''' upper_case_count = 0 lower_case_count = 0 for row in collection['documents']: for c in row['line']: if (c.islower() is True): lower_case_count += 1 elif (c.isupper() is True): upper_case_count += 1 return [upper_case_count, lower_case_count, float(upper_case_count)/(upper_case_count + lower_case_count)] def average_number_of_characters_per_word(inverted_index): ''' Calculate the average number of characters per word We can do this faster with the inverted_index and multiplying value by total_frequency ''' total_chars = 0 total_words = 0 for item in inverted_index: inverted_index_item = inverted_index[item] total_words += inverted_index_item['total_frequency'] total_chars += len(item) * inverted_index_item['total_frequency'] return [total_chars, total_words, float(total_chars)/total_words] def percentage_of_nouns_adjectives_verbs_adverbs_pronouns(collection): ''' Count from collection to maintain contextual information in each location. ''' noun_count = 0 adj_count = 0 verb_count = 0 adv_count = 0 pronoun_count = 0 total_words = 0 for document in collection['documents']: total_words += len(document['words']) for pos in document['POS']: if(pos.startswith("N")): noun_count += 1 elif(pos.startswith("J")): adj_count += 1 elif(pos.startswith("V")): verb_count += 1 elif(pos.startswith("RB")): adv_count += 1 elif(pos.startswith("PR") or pos.startswith("WP")): pronoun_count += 1 return {"Noun": [noun_count, total_words, float(noun_count)/total_words], "Adjective": [adj_count, total_words, float(adj_count)/total_words], "Verb": [verb_count, total_words, float(verb_count)/total_words], "Adverb": [adv_count, total_words, float(adv_count)/total_words], "Pronoun": [pronoun_count, total_words, float(pronoun_count)/total_words]} def top_nouns_verbs_adjectives(collection): ''' Count most frequent occurences of noun, verb, adj Use noun to maintain contextual information. ''' counter = {'N':defaultdict(lambda: 0), "V":defaultdict(lambda: 0), "J":defaultdict(lambda: 0)} for document in collection['documents']: for index, word in enumerate(document['words']): pos = document['POS'][index] if(pos.startswith("N")): counter['N'][word.lower()] += 1 elif(pos.startswith("V")): counter['V'][word.lower()] += 1 elif(pos.startswith("J")): counter['J'][word.lower()] += 1 response = {} for pos in [["N", "Noun"], ["V", "Verb"], ["J", "Adjectives"]]: sorted_words = sorted(counter[pos[0]].items(), key=lambda k_v: k_v[1], reverse=True) #2010 response[pos[1]] = sorted_words[0:10] return response def tfidf(collection, inverse_index): ''' ''' collection_tfidf = [] total_documents = len(collection['documents']) for document in collection['documents'][0:10]: document_tf = defaultdict(lambda: 0) document_tfidf = {} # get a list of document words and occurences for index, word in enumerate(document['words']): document_tf[word] += 1 # For each document word for word in document_tf: # Calculate the TF value # T F (t, d) = log(c(t, d) + 1) tf_value = math.log(1 + document_tf[word]) # IDF(t) = 1 + log(N/k). document_frequency = len(set(inverse_index[word]['doc_ids'])) idf = 1 + math.log(total_documents/document_frequency) # put TF and IDF for 'word' together # and store by document document_tfidf[word] = tf_value*idf # Store document tfidf information by collection collection_tfidf.append(document_tfidf) return collection_tfidf def plot_data(name, inverted_index): ''' Plat the data to a graph and a log log graph ''' x = [] y = [] # Count the number of words with each number of occurences value_count = defaultdict(lambda: 0) for key in inverted_index: value_count[int(inverted_index[key]['total_frequency'])] += 1 vocabulary = len(inverted_index) #Use unique words for k in sorted(value_count.items(), key=lambda k_v: k_v[0], reverse=True): y.append(float(k[1])/vocabulary) x.append(k[0]) plt.plot(x, y, "ro") plt.ylabel('occurences') plt.xlabel('rank order') plt.title(name) plt.show() plt.plot(x, y, "ro") plt.ylabel('log occurences') plt.xlabel('log rank order') plt.xscale('log') plt.yscale('log') plt.title(name) plt.show() def load_stop_words(): ''' Load words from the file, and strip carraige returns''' s = set() for line in open('stoplist.txt', "r", encoding="utf-8").readlines(): s.add(line.strip('\n')) return s def load_data(file_name, stop_words): ''' Load words from file, skipping items matching values in the provided set of stop_words''' stemmer = PorterStemmer() inverted_index = defaultdict(lambda: {'total_frequency' : 0, "POS":'', "STOP_WORD":'False', "doc_ids": [], "frequency":[]}) my_collection = {"Name":file_name, 'documents':[]} cur_record = 1 for line in open(file_name, "r", encoding="utf-8").readlines(): document = {'line':line, "words":[], 'POS':[], "STOP_WORD":[]} line_tok = nltk.word_tokenize(line) for word_pos in nltk.pos_tag(line_tok): cur_word = word_pos[0].lower() s = stemmer.stem(cur_word) x = re.search("[a-zA-Z]", s) if(x is not None): document['words'].append(cur_word) inverted_index_item = inverted_index[cur_word] inverted_index_item['total_frequency'] += 1 inverted_index_item['POS'] = word_pos[1] document['POS'].append(word_pos[1]) document['STOP_WORD'].append(cur_word in stop_words) if(cur_record not in inverted_index_item['doc_ids']): inverted_index_item['doc_ids'].append(cur_record) inverted_index_item['frequency'].append(1) else: index = inverted_index_item['doc_ids'].index(cur_record) inverted_index_item['frequency'][index] += 1 my_collection['documents'].append(document) cur_record += 1 for cur_word in inverted_index: if(cur_word.lower() in stop_words): inverted_index[cur_word]['STOP_WORD'] = "True" return inverted_index, my_collection global_stop_words = load_stop_words() inverted_index_medhelp, collection_medhelp = load_data("medhelp.txt", global_stop_words) inverted_index_ehr, collection_ehr = load_data("ehr.txt", global_stop_words) collection_medhelp_no_stop_words = remove_stopwords_from_collection(collection_medhelp) collection_ehr_no_stop_words = remove_stopwords_from_collection(collection_ehr) inverted_index_medhelp_no_stop_words = remove_stopwords_from_inverted_index(inverted_index_medhelp) inverted_index_ehr_no_stop_words = remove_stopwords_from_inverted_index(inverted_index_ehr) plot_data("medhelp", inverted_index_medhelp_no_stop_words) plot_data("ehr", inverted_index_ehr_no_stop_words) print("Q2.2 stats on {} and {}".format(collection_medhelp['Name'], collection_ehr['Name'])) print("Q2.2a - Frequency of Stopwords.") print("medhelp - {}".format(frequency_of_stopwords(inverted_index_medhelp)[2])) print("ehr - {}".format(frequency_of_stopwords(inverted_index_ehr)[2])) print("Q2.2b - Percentage of capital letters") print("medhelp - {}".format(percentage_of_capital_letters(collection_medhelp)[2])) print("ehr - {}".format(percentage_of_capital_letters(collection_ehr)[2])) print("Q2.2c - Average Number of Characters per word") print("medhelp - {}".format(average_number_of_characters_per_word(inverted_index_medhelp)[2])) print("ehr - {}".format(average_number_of_characters_per_word(inverted_index_ehr)[2])) print("Q2.2d - Percentage of Nouns, Adjectives, Verbs, Adverbs, and Pronouns") r1 = percentage_of_nouns_adjectives_verbs_adverbs_pronouns(collection_medhelp) r2 = percentage_of_nouns_adjectives_verbs_adverbs_pronouns(collection_ehr) for key in list(r1): print("{}\t{}\t{}".format(key, r1[key][2], r2[key][2])) print("2.2e - The Top 10 Nouns, Top 10 Verbs, and Top 10 Adjectives.") r1 = top_nouns_verbs_adjectives(collection_medhelp_no_stop_words) r2 = top_nouns_verbs_adjectives(collection_ehr_no_stop_words) for key in list(r1): print("\n{}".format(key)) for item in range(0,10): print("medhelp - {}".format(r1[key][item])) for item in range(0,10): print("ehr - {}".format(r2[key][item])) print("Q2.3 TF-IDF top scores Medhelp") for idx, document_tfidf in enumerate(tfidf(collection_medhelp_no_stop_words, inverted_index_medhelp_no_stop_words)): print("Document {}".format(idx+1)) sorted_tfidf = sorted(document_tfidf.items(), key=lambda k_v: k_v[1], reverse=True) for tfidf_item in sorted_tfidf[0:5]: print("\tword:{} values:{}".format(tfidf_item[0], tfidf_item[1])) print("Q2.3 TF-IDF top scores Ehr") for idx, document_tfidf in enumerate(tfidf(collection_ehr_no_stop_words, inverted_index_ehr_no_stop_words)): print("Document {}".format(idx+1)) sorted_tfidf = sorted(document_tfidf.items(), key=lambda k_v: k_v[1], reverse=True) for tfidf_item in sorted_tfidf[0:5]: print("\tword:{} values:{}".format(tfidf_item[0], tfidf_item[1]))

[ "jwyman@umich.edu" ]

jwyman@umich.edu

a47f2449b19e9bc97040fc3bd4879370f4bb2788

82c013d796dd9b15dab7b33952aa68ebef62e23d

/amrequest.py

661c9e75684cab9c547547f5d26075b7df84405c

[]

no_license

qwenghernaez/phil_steel

f4d92d75fa98e10c4a899285035466a5fa8bf14a

9ba5c808c4d4260cb58b7ff157a24ae195305a63

refs/heads/master

2021-01-21T08:46:33.135018

2017-05-18T05:54:26

91,641,028

0

null

2017-05-18T05:33:34

2017-05-18T02:40:26

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from odoo import models, fields, api class AMRequests(models.Model): _name = 'philsteel.amrequests' customer = fields.Char(string='Customer') status = fields.Selection([('new', 'New'), ('visited', 'Visited')], default='new', string='Request Status') illustrations = fields.One2many( 'philsteel.amrimages', 'rfam', string="Illustrations") request_number = fields.Char(string='Request Number') location = fields.Text(string='Address') name = fields.Many2one( 'philsteel.projects', 'Project Name', ondelete='cascade', required='True' ) project_type = fields.Selection([('residential', 'Residential'), ('commercial', 'Commercial'), ('industrial', 'Industrial'), ('government', 'Government'), ('institutional', 'Institutional'), ('mass_housing', 'Mass Housing')], string='Type of Project') project_site_address = fields.Text(string='Complete Project Site Address', required='True') general_contractor = fields.Many2one( 'philsteel.projectmanpower', 'Name of contractor', ondelete='cascade' ) contact_person_at_site = fields.Many2many('philsteel.sitecontacts', string='Site Contact Person', ondelete='cascade') jobsite_contact_number = fields.Char(string='Job Site Telephone or Mobile Number') product_profile = fields.Char(string='Product Profile') sc_number = fields.Char(string='SC NO') ic_number = fields.Char(string='IC NO') sq_number = fields.Char(string='SQ NO') iq_number = fields.Char(string='IQ NO') work_scope = fields.Many2many('philsteel.workscope', string='Scope of Work', ondelete='cascade') frames_trusses_installed = fields.Char(string='% Frames / Trusses Installed') purlins_installed = fields.Char(string='% Purlins Installed') sogrod_installed = fields.Char(string='% Sagrod Installed') beam_installed = fields.Char(string='% Beam Installed') floors_available_for_measurement = fields.Char(string='% No. of Floors Available for Measurement') rfm_quotation = fields.Boolean(string='Quotation') rfm_contract = fields.Boolean(string='Contact') rfm_fabrication = fields.Boolean(string='Fabrication') rfm_tech1assistance = fields.Boolean(string='Tech 1 Assistance') rfm_others = fields.Text(string='Others') ready_for_measurement_date = fields.Date(string='Date when structure ready for measurement') accomplished_by = fields.Many2one( 'philsteel.projectmanpower', 'Accomplished By', ondelete='cascade' ) date_filed = fields.Date(string='Date Filed') approved_by = fields.Many2one( 'philsteel.contacts', 'Approve By', ondelete='cascade' ) assigned_by = fields.Many2one( 'philsteel.android', 'Assigned By', ondelete='cascade', required='True' ) #image = fields.Binary() statuss = fields.Selection([ ('draft', 'Draft'), ('approved', 'Approved'), ('ongoing', 'Ongoing'), ('done', 'Done'), ], string='Status', readonly=True, copy=False, index=True, track_visibility='onchange', default='draft') @api.onchange('name') def get_proj_details(self): for record in self: record.customer = record.name.customer_name record.ic_number = record.name.ic_no record.sc_number = record.name.sc_no record.location = record.name.location record.project_type = record.name.types_of_project @api.multi def action_approved(self): for visit in self: visit.statuss = 'approved' return True @api.multi def action_ongoing(self): for visit in self: visit.statuss = 'ongoing' return True @api.multi def action_done(self): for visit in self: visit.statuss = 'done' return True # @api.model # def create(self, values): # """ # Create a new record for a model ModelName # @param values: provides a data for new record # @return: returns a id of new record # """ # if values.get('request_number', 'New') == 'New': # values['request_number'] = self.env['ir.sequence'].next_by_code('philsteel.amrequests') or 'New' # result = super(AMRequests, self).create(values) # return result class AMRImages(models.Model): _name = 'philsteel.amrimages' name = fields.Binary(string='Image') description = fields.Text(string='Description') rfam = fields.Many2one('philsteel.amrequests', ondelete='cascade', string="RFAM", required=True) new_field = fields.Binary()

[ "noreply@github.com" ]

qwenghernaez.noreply@github.com

bfe91a389a2793bab81af26924332598622638eb

14c9e16013866a59efd1981811083bd97f7ed780

/retrieve_similar_bugs.py

c2c8ee8caaa13af3ef8b28d00d3fe347ea20aae2

[]

no_license

kunchengit/TriageRobot

186bf44dec776b14cad9acf7aad0ef86658c56f2

8ad86e330eb219831fcc8d9352662221b10bedad

refs/heads/master

2021-01-10T07:57:04.775020

2015-10-16T08:48:52

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import MySQLdb import pandas import itertools import numpy as np import bm25fe import pickle import subprocess import jsd from gensim import corpora from gensim import matutils from gensim.models import ldamulticore import getpass import os def retrieve_similar_bugs(query_list, length_list, dictionary_address, topicmodel_address, rankmodel_address): print 0, getpass.getuser(), os.getcwd() conn = MySQLdb.connect(host='10.117.8.41', port=3306, user='root', passwd='vmware', db='bugfeature') cur = conn.cursor() print 1, getpass.getuser(), os.getcwd() sql = '''SELECT * FROM bugs_cpdplatform_ff''' bugs = pandas.io.sql.read_sql(sql, conn) print 2, getpass.getuser(), os.getcwd() dictionary = corpora.Dictionary.load_from_text(dictionary_address) topicmodel = ldamulticore.LdaMulticore.load(topicmodel_address) print 3, getpass.getuser(), os.getcwd() num_terms = len(dictionary) bugs['text'] = (bugs['short_desc'] +' '+ bugs['long_desc']).map(lambda x: dictionary.doc2bow(x.split())) bugs['engineer'] = (bugs['assigned_to'].map(str)+' '+bugs['needinfo']).map(lambda x: x.split()) bugs.loc[:,'short_desc'] = bugs['short_desc'].map(lambda x: matutils.corpus2dense([dictionary.doc2bow(x.split())], num_terms, 1)[:,0]) bugs.loc[:,'long_desc'] = bugs['long_desc'].map(lambda x: matutils.corpus2dense([dictionary.doc2bow(x.split())], num_terms, 1)[:,0]) appearance = np.array(list(bugs['text'].map(lambda x: matutils.corpus2dense([x], num_terms, 1)[:,0]>0))) df = appearance.sum(0) idf = np.log(bugs.shape[0]/df) avgfl = np.array([np.array(list(bugs['short_desc'])).sum(1).mean(), np.array(list(bugs['long_desc'])).sum(1).mean()]) bugs = bugs.set_index(['bug_id']) print 4, getpass.getuser(), os.getcwd() bm = bm25fe.bm25fe(K1=1.2, d_B=(0.75, 0.75), d_W = (2, 1), K3=1.2, q_B=(0.75, 0.75), q_W=(2, 1)) results = {} lines = [] for item in query_list: item = int(item) bugs['score'] = bugs.apply(lambda x: bm.score(idf, avgfl, [x[13], x[14]],[bugs.loc[item,'short_desc'], bugs.loc[item,'long_desc']]), axis = 1) bugs_sorted = bugs.sort(['score'], ascending = False).iloc[:100].reset_index() results[item] = bugs_sorted.loc[:,['bug_id']] # print results[item] # idx = 0 # lines = [] for idx in xrange(100): sim_title = bugs_sorted.iloc[idx]['short_desc'][bugs.loc[item,'short_desc']>0].sum()/max(bugs_sorted.iloc[idx]['short_desc'].sum(), 1) score = bugs_sorted.iloc[idx]['score'] # cluster = topicmodel.inference([bugs_sorted.iloc[idx]['text'], bugs.loc[item['query'],'text']]) cluster = topicmodel.inference([bugs_sorted.iloc[idx]['text'], bugs.loc[item,'text']])[0] dis_topic = jsd.JSD(cluster[0], cluster[1]) sim_hos = False if (bugs_sorted.iloc[idx]['host_op_sys'] == bugs.loc[item,'host_op_sys']) and (bugs_sorted.iloc[idx]['host_op_sys'] != 'Unknown'): sim_hos = True sim_gos = False if (bugs_sorted.iloc[idx]['guest_op_sys'] == bugs.loc[item,'guest_op_sys']) and (bugs_sorted.iloc[idx]['guest_op_sys'] != 'Unknown'): sim_gos = True sim_pd = False if (bugs_sorted.iloc[idx]['product_id'] == bugs.loc[item,'product_id']): sim_pd = True sim_cg = False if (bugs_sorted.iloc[idx]['category_id'] == bugs.loc[item,'category_id']): sim_cg = True sim_cp = False if (bugs_sorted.iloc[idx]['component_id'] == bugs.loc[item,'component_id']): sim_cp = True sim_pr = False if (bugs_sorted.iloc[idx]['priority'] == bugs.loc[item,'priority']): sim_pr = True sim_fi_pd = False if (bugs_sorted.iloc[idx]['found_in_product_id'] == bugs.loc[item,'found_in_product_id']) and (bugs_sorted.iloc[idx]['found_in_product_id'] != 0): sim_fi_pd = True sim_fi_ver = False if (bugs_sorted.iloc[idx]['found_in_version_id'] == bugs.loc[item,'found_in_version_id']) and (bugs_sorted.iloc[idx]['found_in_version_id'] != 0): sim_fi_ver = True sim_fi_ph = False if (bugs_sorted.iloc[idx]['found_in_phase_id'] == bugs.loc[item,'found_in_phase_id']) and (bugs_sorted.iloc[idx]['found_in_phase_id'] != 0): sim_fi_ph = True if (bugs_sorted.iloc[idx]['cf_security'] == bugs.loc[item,'cf_security']) and (bugs_sorted.iloc[idx]['cf_security'] ==1): sim_security = 2 elif (bugs_sorted.iloc[idx]['cf_security'] == bugs.loc[item,'cf_security']) and (bugs_sorted.iloc[idx]['cf_security'] ==0): sim_security = 1 else: sim_security = 0 sim_engineer = False if (len(set(bugs_sorted.iloc[idx]['engineer']) & set(bugs.loc[item,'engineer'])) >0): sim_engineer = True lines.append(str(0)+' qid:'+str(item)+' 1:'+str(sim_title)+' 2:'+str(score)+' 3:'+str(dis_topic)+' 4:'+str(int(sim_hos))+' 5:'+str(int(sim_gos))+' 6:'+str(int(sim_pd))+' 7:'+str(int(sim_cg))+' 8:'+str(int(sim_cp))+' 9:'+str(int(sim_pr))+' 10:'+str(int(sim_fi_pd))+' 11:'+str(int(sim_fi_ver))+' 12:'+str(int(sim_fi_ph))+' 13:'+str(sim_security)+' 14:'+str(int(sim_engineer))+' # '+str(bugs_sorted.iloc[idx]['bug_id'])+'\n') print 5, getpass.getuser(), os.getcwd() f = open('/home/TriageRobot/query.txt', 'w') f.writelines(lines) f.close() subprocess.call(('java', '-jar', '/root/chenkun/Duplicate-bugs-retrieval/RankLib-2.1-patched.jar', '-load', rankmodel_address, '-rank', '/home/TriageRobot/query.txt', '-score', '/home/TriageRobot/score.txt')) # subprocess.call(('java', '-jar', 'RankLib-2.1-patched.jar', '-load', 'AdaRank.txt', '-rank', 'query.txt', '-score', 'score.txt')) # subprocess.call(('java', '-jar', 'RankLib-2.1-patched.jar', '-load', 'RankNet.txt', '-rank', 'query.txt', '-score', 'score.txt')) score_rank = [] qid = -1 f = open('/home/TriageRobot/score.txt', 'r') for line in f: if int(line.split()[0]) != qid: if score_rank: results[qid]['score_rank'] = score_rank score_rank = [] qid = int(line.split()[0]) score_rank.append(float(line.split()[2])) else: score_rank.append(float(line.split()[2])) results[qid]['score_rank'] = score_rank f.close() # print results idx = 0 for key in results: bugs_ranked = results[key].sort(['score_rank'], ascending = False).set_index(['bug_id']) ranklist = [] i = 0 while len(ranklist) < int(length_list[idx]): # print bugs_ranked.iloc[i]['bug_id'] if bugs_ranked.index[i] != key: child = False for j in xrange(len(ranklist)): if bugs.loc[bugs_ranked.index[i],'summary'] == bugs.loc[ranklist[j],'summary']: # if len(set([bugs_ranked.index[i]]) & set(item['rel'])) > 0: # ranklist[j] = bugs_ranked.index[i] child = True break if not child: ranklist.append(bugs_ranked.index[i]) # ranklist.append(bugs_ranked.index[i]) i += 1 results[key] = ranklist idx += 1 return results def find_bug(): f = open('/home/TriageRobot/query.txt', 'w')

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root@TriageRobot-prod.(none)

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/Einarbeitung/Word2Vec/Test1/T4.py

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imbabaer/SemanticRelations

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refs/heads/master

2020-04-08T21:10:48.040347

2015-09-10T15:16:23

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import gensim, logging import os import math folder="../../../Korpora/Wikipedia/" preprocessedKorpus = folder+"enwiki-latest-pages-articles_clean.txt"; tmpPreprocessed = folder + "latest-pages-tmpPreprocessed/" if not os.path.exists(tmpPreprocessed): os.makedirs(tmpPreprocessed) #preprocessed Korpus x = 0 y=0 tmp = [] with open(preprocessedKorpus) as infile: for line in infile: if x < 100000: tmp.extend(line) x+=1 else: f = open(tmpPreprocessed+'file'+str(y),'w') for item in tmp: f.write(item) f.close() print "created: preprocessed/file"+str(y) tmp=[] x=0 y+=1 ''' lines= file.read() lenght=len(lines) numFiles = 10000 partitionSize = int(math.ceil(lenght/numFiles)) for x in range(0, numFiles): f = open(tmpPreprocessed+'file'+str(x),'w') for y in range (0,partitionSize): f.write(lines[x*partitionSize +y]) f.close() print "created: preprocessed/file"+str(x) ''' print "done."

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rubenmueller90@gmail.com

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/Exercícios Resolvidos/The Huxley/248 - Última palavra de uma frase.py

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2019-07-14T04:36:31

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frase = str(input()).split() print(frase[-1])

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guilherme.esdras@outlook.com

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/2021.1/Back_End/Semana_02/AppAnimal1.py

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felipegt56/IFPI-TDS

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refs/heads/main

2023-06-06T18:55:05.954808

2021-07-09T22:28:13

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from fastapi import FastAPI from pydantic import BaseModel from typing import List, Optional from uuid import uuid4 app = FastAPI() class Animais(BaseModel): id: Optional[str] nome: str idade: int sexo: str cor: str bd_animais: List[Animais] = [] @app.post('/animais') def Sistema_cadastro(animal: Animais): animal.id = str(uuid4()) bd_animais.append(animal) return None @app.get('/animais') def listar_animais(): return bd_animais @app.get('/animais/{animal_id}') def localizar_id(animal_id: str): for animal in bd_animais: if animal.id == animal_id: return animal return {'erro': 'Animal não encontrado'} @app.delete('/animais/{animal_id}') def deleta_id(animal_id: str): pos = -1 for index, animal in enumerate(bd_animais): if animal.id == animal_id: pos = index break if pos != -1: bd_animais.pop(pos) return {'Mensagem': 'animal removido com sucesso!'} else: return {'Erro': 'Animal não encontrado!'}

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69603279+felipegt56@users.noreply.github.com

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/tiago_public_ws/devel/lib/python2.7/dist-packages/pal_vision_msgs/msg/_LegDetections.py

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mrrocketraccoon/tiago_development

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/tiago_public_ws/devel/.private/pal_vision_msgs/lib/python2.7/dist-packages/pal_vision_msgs/msg/_LegDetections.py

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ricardoxcm@hotmail.com

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/ntpu_system/mysite/alumni/urls.py

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[]

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aron3312/ntpu_system

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2022-04-29T16:52:11.273522

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from django.conf.urls import url from alumni import views urlpatterns = [ url(r'^alumni/introduction$',views.alumni_introduction,name='alumni_introduction'), url(r'^alumni/activity$',views.alumni_activity,name='alumni_activity'), url(r'^alumni/network$',views.network,name='alumni_network') ]

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aron3313@gmail.com

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/Codeforces/Educational Codeforces Round 62 (Rated for Div. 2) - 1140/1140A-Detective Book.py

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[]

no_license

subhashreddykallam/Competitive-Programming

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2022-05-28T21:07:43.012922

2020-05-05T20:34:20

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import math from collections import deque, defaultdict from sys import stdin, stdout #input = stdin.readline # print = stdout.write listin = lambda : list(map(int, input().split())) mapin = lambda : map(int, input().split()) n = int(input()) a = listin() k = -1 count = 0 for i in range(n): k = max(k, a[i]-1) if k == i: count+=1 print(count)

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42376739+Storm1seven@users.noreply.github.com

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pingpgeti/elliot-chat-client

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refs/heads/master

2023-04-27T07:19:09.299344

2021-05-13T12:42:45

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from enum import Enum from pathlib import Path # server constants SERVER_URL = "http://localhost:5000" TABLE_SCHEMA_PATH = str(Path("app") / "database" / "schema.sql") DEFAULT_DB_PATH = "user.db" FETCH_DELAY_PERIOD = 5 # time period beetween each server data update # other PREFFERED_ENCODING = "utf-8" # crypto constants HASH_SALT = "made by wilkueti".encode(PREFFERED_ENCODING) # NEVER DO THIS!!! MAX_ONE_TIME_KEYS = 15 # length of the keyes is derived from the signal documentation SHARED_KEY_LENGTH = 32 RATCHET_STATE_KEY_LENGTH = 64 # according to crypto library docs nonce should have 96 bits AEAD_NONCE = "SEG0PPiuHAFm".encode(PREFFERED_ENCODING) BLOCK_SIZE = 128 class MainMenuOptions(Enum): MESSAGE = 0 ADD_FRIEND = 1 CHANGE_CREDENTIALS = 2 REMOVE_ACCOUNT = 3 WAITROOM = 4 EXIT = 5

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michal.wilk0@yahoo.com

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emptyflash/twitter-scraping-v2

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refs/heads/master

2023-05-24T12:47:46.187197

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2023-05-22T22:39:10

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import json import datetime import requests from bs4 import BeautifulSoup HEADERS = { "authority": "twitter.com", "accept":"application/json, text/javascript, */*; q=0.01", "accept-language":"en-US,en;q=0.9", "sec-fetch-mode":"cors", "sec-fetch-site":"same-origin", "x-asset-version":"42599c", "x-push-state-request":"true", "x-requested-with":"XMLHttpRequest", "x-twitter-active-user":"yes", "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.88 Safari/537.36", "cookie": '_twitter_sess=BAh7CSIKZmxhc2hJQzonQWN0aW9uQ29udHJvbGxlcjo6Rmxhc2g6OkZsYXNo%250ASGFzaHsABjoKQHVzZWR7ADoPY3JlYXRlZF9hdGwrCBm52dZvAToMY3NyZl9p%250AZCIlYmFkYTYxOWViNTdiM2M4MWY0OTVlOTA5MjdmOTRlOGM6B2lkIiU4ZjY2%250AYzI5YTdhZGE0NDI2MDNlMjA0M2IwMThlYmMyMw%253D%253D--a6151e23c827fa6018ae4213dbef144ff9966799; personalization_id="v1_iz/bqzAp5VjuGiJYpE9raQ=="; guest_id=v1%3A157985759055012300; ct0=a1e56bd7a069a92bc87d684d2ed82c4e; _ga=GA1.2.1641248728.1579857593; _gid=GA1.2.443586604.1579857593; tfw_exp=0; _gat=1', } def build_q(username, since, until): return f"from:{username} since:{since.isoformat()} until:{until.isoformat()} include:retweets" def extract_tweets(soup): tweet_divs = soup.select("div.tweet") tweets = [] for tweet in tweet_divs: id = tweet["data-tweet-id"] retweet_count = tweet.select_one(".ProfileTweet-action--retweet .ProfileTweet-actionCount")["data-tweet-stat-count"] favorite_count = tweet.select_one(".ProfileTweet-action--favorite .ProfileTweet-actionCount")["data-tweet-stat-count"] reply_count = tweet.select_one(".ProfileTweet-action--reply .ProfileTweet-actionCount")["data-tweet-stat-count"] tweets.append({ "id": id, "retweet_count": retweet_count, "favorite_count": favorite_count, "reply_count": reply_count, }) return tweets def timeline_search(q, max_position): params = { "vertical": "default", "f": "tweets", "q": q, "src": "typd", "include_available_features": "1", "include_entities": "1", "max_position": max_position, "reset_error_state": False, } result = requests.get("https://twitter.com/i/search/timeline", params=params, headers=HEADERS).json() soup = BeautifulSoup(result["items_html"], 'html.parser') tweets = extract_tweets(soup) min_position = result["min_position"] has_more_items = result["has_more_items"] return tweets, min_position, has_more_items def init_search(q): params = { "src": "typd", "f": "tweets", "q": q } result = requests.get("https://twitter.com/search", params=params, headers=HEADERS).json() soup = BeautifulSoup(result["page"], 'html.parser') stream = soup.select_one("div.stream-container") if stream is None: print(f"No results found for {q}") return set(), None min_position = stream["data-min-position"] tweets = extract_tweets(soup) return tweets, min_position def get_all_tweets(username, start, end, step=datetime.timedelta(days=90)): since = start tweets = [] while since != end: until = since + step if until > end: until = end q = build_q(username, since, until) init_tweets, min_position = init_search(q) tweets += init_tweets print(init_tweets) has_more_items = True while has_more_items and min_position: more_tweets, min_position, has_more_items = timeline_search(q, min_position) print(more_tweets) tweets += more_tweets since = until return tweets if __name__ == "__main__": username = "emptyflash" start = datetime.date(2009, 9, 1) end = datetime.date.today() tweets = get_all_tweets(username, start, end) import pdb; pdb.set_trace() with open(f"{username}.json", 'w') as outfile: json.dump(tweets, outfile)

[ "emptyflash@gmail.com" ]

emptyflash@gmail.com

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/my.py

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JBprojects/Tournament-Management-System

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refs/heads/master

2021-04-30T12:04:17.577780

2018-02-13T03:25:59

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UTF-8

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from urllib.request import urlopen as uReq from bs4 import BeautifulSoup as soup my_url='http://www.cricbuzz.com/cricket-match/live-scores' uClient=uReq(my_url) page_html=uClient.read() uClient.close() filename = "getcon.txt" f=open(filename,"w") f.write("") page_soup=soup(page_html, "html.parser") containers=page_soup.findAll("div",{"class":"cb-mtch-lst cb-col cb-col-100 cb-tms-itm"}) container=containers[0] c=container.div.a print("title " + c.text) b=c.text f.write(b+'\n') type=container.findAll("div",{"class":"text-gray"}) for t in type: t1=t.text print(" " + t1) f.write(t1+'\n') match=page_soup.findAll("div",{"class":"cb-col-50 cb-col"}) m=match[0].text print("status " + m) f.write(m+'\n') f.close()

[ "noreply@github.com" ]

JBprojects.noreply@github.com

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/sgss_retro_senseaware/scripts/analyzers/closest/get_ambiguous_words.py

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[]

no_license

ghpaetzold/phd-backup

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refs/heads/master

2020-12-24T16:41:21.490426

2016-04-23T14:50:07

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4,182

py

import urllib2, re, gensim from nltk.corpus import wordnet as wn import numpy as np from sklearn.decomposition import PCA exp = re.compile('<BR>([^<]*)<BR>') conn = urllib2.urlopen('http://www.enchantedlearning.com/wordlist/nounandverb.shtml') html = conn.read() ocs = [oc.strip() for oc in exp.findall(html) if len(oc.strip().split(' '))==1] ocmap = {} synmap = {} for word in ocs: syns = wn.synsets(word) ants = set([]) for syn in syns: for lemma in syn.lemmas(): ants.update(lemma.antonyms()) ocmap[word] = len(ants) synmap[word] = len(syns) words = sorted(ocmap.keys(), key=ocmap.__getitem__, reverse=True) #for word in words: # print(word + ': ' + str(synmap[word]) + ', ' + str(ocmap[word])) print('Loading...') wvmodel = '/export/data/ghpaetzold/word2vecvectors/models/word_vectors_all_100_cbow.bin' wvrmodel = '/export/data/ghpaetzold/word2vecvectors/models/word_vectors_all_100_cbow_retrofitted.bin' pwvmodel = '/export/data/ghpaetzold/word2vecvectors/models/word_vectors_all_generalized_100_cbow.bin' pwvrmodel = '/export/data/ghpaetzold/word2vecvectors/models/word_vectors_all_generalized_100_cbow_retrofitted.bin' m = gensim.models.word2vec.Word2Vec.load_word2vec_format(wvmodel, binary=True) pm = gensim.models.word2vec.Word2Vec.load_word2vec_format(pwvmodel, binary=True) mr = gensim.models.word2vec.Word2Vec.load_word2vec_format(wvrmodel, binary=True) pmr = gensim.models.word2vec.Word2Vec.load_word2vec_format(pwvrmodel, binary=True) #Select words to calculate PCA of: simmap = {} simmapr = {} selected = [] all = [] X = [] i = 0 words = ['stand'] while len(selected)<1 and i<len(words): word = words[i] print(str(word)) nvec = pm[word+'|||N'] vvec = pm[word+'|||V'] TEMsim = m.most_similar(word, topn=10) SEMsimn = pm.most_similar(word+'|||N', topn=5) SEMsimv = pm.most_similar(word+'|||V', topn=5) REMsim = mr.most_similar(word, topn=10) RSEMsimn = pmr.most_similar(word+'|||N', topn=5) RSEMsimv = pmr.most_similar(word+'|||V', topn=5) #Add it to the selected list: selected.append(word) #Add them to the similarity map: simmap[word] = TEMsim simmap[word+'|||N'] = SEMsimn simmap[word+'|||V'] = SEMsimv simmapr[word] = REMsim simmapr[word+'|||N'] = RSEMsimn simmapr[word+'|||V'] = RSEMsimv #Add them to list of words: all.append(word) all.append(word+'|||N') all.append(word+'|||V') temp = TEMsim + SEMsimn + SEMsimv for simw in temp: all.append(simw[0].strip()) all.append(word) all.append(word+'|||N') all.append(word+'|||V') temp = REMsim + RSEMsimn + RSEMsimv for simw in temp: all.append(simw[0].strip()) #Add them to X matrix: X.append(m[word]) X.append(nvec) X.append(vvec) for simw in TEMsim: X.append(m[simw[0]]) for simw in SEMsimn: X.append(pm[simw[0]]) for simw in SEMsimv: X.append(pm[simw[0]]) X.append(mr[word]) X.append(pmr[word+'|||N']) X.append(pmr[word+'|||V']) for simw in REMsim: X.append(mr[simw[0]]) for simw in RSEMsimn: X.append(pmr[simw[0]]) for simw in RSEMsimv: X.append(pmr[simw[0]]) i += 1 X = np.array(X) print('X lines: ' + str(len(X))) print('X columns: ' + str(len(X[0]))) print('All lines: ' + str(len(all))) #Calculate PCA: print('PCA...') pca = PCA(n_components=2) X = pca.fit_transform(X) #Create vector map: vecmap = {} vecmapr = {} for i in range(0, int(len(all)/2)): word = all[i] vec = X[i] vecmap[word] = vec for i in range(int(len(all)/2), len(all)): word = all[i] vec = X[i] vecmapr[word] = vec #Create files: o1 = open('similar_map.txt', 'w') o2 = open('vector_map.txt', 'w') for word in simmap: line = word + '\t' for sim in simmap[word]: line += sim[0].strip() + '\t' o1.write(line.strip() + '\n') o1.close() for word in vecmap: line = word + '\t' + str(vecmap[word][0]) + '\t' + str(vecmap[word][1]) + '\n' o2.write(line) o1.close() o2.close() o1 = open('similar_mapr.txt', 'w') o2 = open('vector_mapr.txt', 'w') for word in simmapr: line = word + '\t' for sim in simmapr[word]: line += sim[0].strip() + '\t' o1.write(line.strip() + '\n') o1.close() for word in vecmapr: line = word + '\t' + str(vecmapr[word][0]) + '\t' + str(vecmapr[word][1]) + '\n' o2.write(line) o1.close() o2.close()

[ "ghpaetzold@outlook.com" ]

ghpaetzold@outlook.com

f0045ef4ff1340561ba46f011f3a5dcb1dacc65c

feee95b58b25527a1c962931c22427b3eaf98467

/ex4.py

b100b6c40a44ff8f13f6db3541c351d76b30ed80

[]

no_license

odinokov7/3hw

d4638ba9f17e8c5dd628d5b2ff2288b5a68cc967

992c1d8591b4e06fd4042838766f4ee0f0f5f1cf

refs/heads/master

2023-03-02T21:26:48.476826

2021-02-10T16:55:28

337,789,981

0

null

2021-02-10T16:57:42

2021-02-10T16:52:27

Python

UTF-8

Python

false

444

py

x = float(input('Введите x: ')) y = int(input('Введите y: ')) if y == 0: print('y не может быть 0') elif y > 0: y = y * -1 def my_func_first_try(arg1, arg2): return arg1 ** arg2 def my_func_second_try(arg1, arg2): arg2 = abs(arg2) otv = arg1 for i in range(1, arg2): otv = otv * arg1 i += 1 return 1 / otv print(my_func_first_try(x, y)) print(my_func_second_try(x, y))

[ "odinokov7@gmail.com" ]

odinokov7@gmail.com

612cf026a12b0609b69d79e090a311dd47a04266

96e93c81addf58445f6f332f33430117f3f57306

/player.py

35d2e1515eceb20ca23a2857b7818490ca9b1e8a

[]

no_license

faisal-ahmed/Balloon-Shooter-Game

69b38f4e6ad402a863d037ba0e66ac052f1b4107

cab9942602f4cce4680ce794e9b15e0b7b75ef80

refs/heads/master

2020-04-17T08:08:35.009798

2019-01-18T12:21:38

166,399,945

0

null

UTF-8

Python

false

1,548

py

#Player Management Package from settings import * class Player(object): """docstring for Player""" PLAYER_IMAGE_URL = "myResources/images/shooter.png" HEALTHBAR_IMAGE_URL = "myResources/images/healthbar.png" HEALTH_IMAGE_URL = "myResources/images/health.png" PLAYER_POSITION = [80, 80] PLAYER_SIZE = (120, 120) def __init__(self): self.health_value = 194 #194 self.loaded_player = pygame.image.load(Player.PLAYER_IMAGE_URL) self.transformed_player = pygame.transform.scale(self.loaded_player, Player.PLAYER_SIZE) self.healthbar = pygame.image.load(Player.HEALTHBAR_IMAGE_URL) self.health = pygame.image.load(Player.HEALTH_IMAGE_URL) def rotatePlayer(self): position = pygame.mouse.get_pos() angle = math.atan2(position[1]-(Player.PLAYER_POSITION[1]+32), position[0]-(Player.PLAYER_POSITION[0]+26)) playerrot = pygame.transform.rotate(self.transformed_player, 360-angle*57.29) playerpos1 = (Player.PLAYER_POSITION[0]-playerrot.get_rect().width/2, Player.PLAYER_POSITION[1]-playerrot.get_rect().height/2) WINDOW.blit(playerrot, playerpos1) def healthBar(self): WINDOW.blit(self.healthbar, (5,5)) for health1 in range(self.health_value): WINDOW.blit(self.health, (health1+8, 8)) def drawClock(self): # 6.4 - Draw clock font = pygame.font.Font(None, 24) survivedtext = font.render(str((90000-pygame.time.get_ticks())/60000)+":"+str((90000-pygame.time.get_ticks())/1000%60).zfill(2), True, (0,0,0)) textRect = survivedtext.get_rect() textRect.topright=[635,5] WINDOW.blit(survivedtext, textRect)

[ "faisal.ahmed0001@gmail.com" ]

faisal.ahmed0001@gmail.com

1ff59f385afc8cb760932bbdfb1aaee3163dc983

f2a3f57379cb375c33442afb03baef005b92f819

/이혜은/1027/멀쩡한 사각형.py

aef05f5d6bda02145921cae85e3c9cb11f466ecb

[]

no_license

rubetyy/Algo-study

9e2d80b2edcd37c67c4c824f5e61b65be272cf06

d7165da60c98227d6f4abf18aa19cd79e006ea59

refs/heads/master

2023-09-02T05:52:41.517447

2021-11-23T04:12:04

418,523,907

0

null

UTF-8

Python

false

274

py

def solution(w,h): tmp = 0 if w <= h: until = w else: until = h for i in range(until, -1, -1): if h%i == 0 and w%i == 0: tmp = i break answer = w*h - (w+h-tmp) return answer

[ "snflo16@naver.com" ]

snflo16@naver.com

6725e52f3a46033891bb2ae6e8007889caaa26e6

81a9b528fbb79a6109a6c011cca9d59ff45dab92

/utils/sampler.py

7bacdd0f147134035948b3e1b0783f61e9cc2f55

[ "MIT" ]

permissive

lconet/binary_quality_classification

a863ee4f3a0f37bbaa1dd310f1038beb853a82fb

72530438a9e0bd3d036fdf966f3ef9881d898e3d

refs/heads/master

2022-12-21T14:21:24.919972

2020-09-23T20:35:27

null

0

null

UTF-8

Python

false

1,658

py

class Sampler(object): def __init__(self, sampler_type): self.sampler_type = type def __call__(self): if self.sampler_type = "random": pass elif self.sampler_type = "cartesian": pass return samples def cartesian_sampler(self): pass def random_sampler(self): pass @staticmethod def normal_pmf(x: np.array, mean: float, sigma: float) -> np.array: """Constructs the PMF in a Gaussian shape. Args: x (np.array): Random Variables. mean (float): Mean of the Gaussian RV. sigma (float): Standard deviation of the Gaussian RV. Returns: x (np.array): PMF in a Gaussian shape given the random variables and parameters. """ x = np.exp(-1 / 2 * ((x - mean) / sigma) ** 2) x /= np.sqrt(2 * np.pi * sigma ** 2) x /= x.sum() return x @staticmethod def reduced_normal_pmf(x: np.array, mean: float, sigma: float) -> np.array: """Constructs the PMF in a Gaussian shape. PMF value of the mean value has been assigned to 0. Args: x (np.array): Random Variables. mean (float): Mean of the Gaussian RV. sigma (float): Standard deviation of the Gaussian RV. Returns: x (np.array): PMF in a Gaussian shape given the random variables and parameters. """ x = np.exp(-1 / 2 * ((x - mean) / sigma) ** 2) x /= np.sqrt(2 * np.pi * sigma ** 2) x[mean] = 0. x /= x.sum() return x

[ "caneozester@gmail.com" ]

caneozester@gmail.com

090e36be37fd0bcd41780a1de55f790c4c445f94

7a03201ccadf7ef3dcb6cd6676bc893bf412cedf

/lecture02/numbers2.py

9f198713886971782fb4ac521fd25137c7578e1e

[]

no_license

uselesssparrow/pythonp_hw

732571321f0d1793c320d9673d7991d0007e15bb

27a3df0bc84cc74bfd9ec23a3441c7d06f4d31b0

refs/heads/master

2023-01-10T03:34:34.779957

2020-11-17T04:15:56

298,477,209

0

null

UTF-8

Python

false

1,749

py

st_in=input("Введите целое число от 0 до 99: ") if not str.isdigit(st_in): print("Введено не целое число или буквы") exit() st_in=int(st_in) if (st_in<0) or (st_in>99): #проверка диапазона print("Введено число не в диапазоне от 0 до 99") exit() num='' if (st_in//10==9): num+='девяносто' elif (st_in//10==8): num+='восемьдесят' elif (st_in//10==7): num+='семьдесят' elif (st_in//10==6): num+='шестьдесят' elif (st_in//10==5): num+='пятьдесят' elif (st_in//10==4): num+='сорок' elif (st_in//10==3): num+='тридцать' elif (st_in//10==2): num+='двадцать' if (st_in%10==9): num+=' девять' elif (st_in%10==8): num+=' восемь' elif (st_in%10==7): num+=' семь' elif (st_in%10==6): num+=' шесть' elif (st_in%10==5): num+=' пять' elif (st_in%10==4): num+=' четырe' elif (st_in%10==3): num+=' три' elif (st_in%10==2): num+=' два' elif (st_in%10==1): num+=' один' if (st_in==19): num='девятнадцать' elif (st_in==18): num='восемнадцать' elif (st_in==17): num='семнадцать' elif (st_in==16): num='шестнадцать' elif (st_in==15): num='пятнадцать' elif (st_in==14): num='четырнадцать' elif (st_in==13): num='тринадцать' elif (st_in==12): num='двенадцать' elif (st_in==11): num='одиннадцать' elif (st_in==10): num='десять' if(st_in==0): num='ноль' print(num)

[ "71866532+uselesssparrow@users.noreply.github.com" ]

71866532+uselesssparrow@users.noreply.github.com

f6b30be99b68743ed3946fedc0913932558006a1

3073334bbdf95403e07d41f66c21409fa70910fa

/pagerduty_trigger/__init__.py

96f6a607b35ab378eb4e2cd5d2ea3f099ba56c27

[]

no_license

Bhanditz/pagerduty_trigger

aa9caa09794a4fa70f2441492d666a0970aaf3c1

69d5be3df9cb7b5f94f996b0441d85b7f0d3c01f

refs/heads/master

2023-04-14T13:40:17.658586

2015-12-11T16:19:48

165,651,743

1

0

null

2023-04-04T00:14:26

2019-01-14T11:43:47

Python

UTF-8

Python

false

3,795

py

# -*- coding: utf-8 -*- ''' Pagerduty actions ''' from __future__ import absolute_import import pygerduty import logging from pagerduty_trigger import broker logger = logging.getLogger(__name__) class IncidentKeyLocked(Exception): ''' Exception for when the incident key has already been used recently ''' pass class IncidentKeyLock(object): ''' Check for if an incident was already used ''' _rconn = None def __init__(self, incident_key, settings): ''' Args: incident_key (str): unique incident key to tie to error settings (object): settings object Returns: None ''' self.incident_key = incident_key self.settings = settings @property def rconn(self): ''' Redis connection object ''' if self._rconn is None: logger.info(broker) self._rconn = broker.RedisClass(self.settings) return self._rconn def __enter__(self): ''' Create a lock on redis to decrease the number of alerts to the pagerduty api ''' logger.info('Check for redis lock: {0}'.format(self.incident_key)) # First check for a redis lock rlock_status = self.rconn.set(self.incident_key, 'locked', ex=180, nx=True) if rlock_status is None: logger.info('Redis lock already exists for incident: {0}.'.format(self.incident_key)) raise IncidentKeyLocked("IncidentKey {0} is locked via Redis".format(self.incident_key), None) return self def __exit__(self, exc_type, exc_val, exc_tb): ''' Only clean up the lock if the alert failed. This should be left to expire if there is not an error, to help keep extra calls from going through for 180 seconds. To decrease the amount of time we spend alerting pagerduty. ''' if exc_type is not None: self.rconn.delete(self.incident_key) class Pager(object): pager = None settings = None def __new__(cls, settings): ''' Cache base class Args: settings (object): pagerduty settings Returns: Pager (object): trigger incidents on pagerduty api ''' if cls.pager is None: cls.settings = settings # api_token is not actually used for what we are doing, we don't # need to auth only send to the service_key below cls.pager = pygerduty.PagerDuty(cls.settings.PAGERDUTY_SUBDOMAIN, api_token='junk') return super(Pager, cls).__new__(cls) def trigger_incident(self, description, incident_key, details=None, client=None, client_url=None): ''' Trigger an incident in the pagerduty api Args: description (str): Description on why alert is called incident_key (str): unique string for incident details (dict): dictionary with extra details client (str): arbitrary product name client_url (str): arbitrary product url Returns: bool: True if the call succeeded False if the call failed None if no call was made ''' if self.settings.PAGERDUTY_SERVICE_KEY is None: return None service_key = self.settings.PAGERDUTY_SERVICE_KEY try: with IncidentKeyLock(incident_key, self.settings): self.pager.trigger_incident(service_key, description, "trigger", details, incident_key, client=client, client_url=client_url) return True except IncidentKeyLocked: return None

[ "danielwallace@gtmanfred.com" ]

danielwallace@gtmanfred.com

654d6b5f0e13544c626b589ac4de64c67b3ca229

f48763f1080bf4e3a0efa69f1d937f6107ac8aca

/medbot_app/models.py

d8ff808779420e01cb498a6d1806fcb506636775

[]

no_license

n1az/MedBot

4a71dcc41a5d06615f8aecc6d961b165ed840542

713fe1565ddf3d23d7958bf8fad521597676873e

refs/heads/master

2023-04-29T07:21:02.932495

2023-04-12T03:09:14

275,631,345

0

1

null

UTF-8

Python

false

6,803

py

from django.db import models class Employee(models.Model): pharmacy_id = models.BigAutoField(primary_key = True) pharmacy_address = models.CharField(max_length = 254) owner_name = models.CharField(max_length = 100) pharmacy_name = models.CharField(max_length = 100) pharmacy_reg_id = models.CharField(max_length = 100) employee_password = models.CharField(max_length = 100) pharmacy_rating = models.FloatField(max_length=3, null=True) pharmacy_rating_count = models.PositiveIntegerField(default = 0) employee_email = models.EmailField(max_length = 254) employee_phone = models.CharField(max_length = 15) employee_longT = models.CharField(max_length = 20, default= "90.40") employee_latiT = models.CharField(max_length = 20, default= "20.40") def __str__(self): return self.pharmacy_name class Inventory(models.Model): """docstring for Inventory""" MUSTPRESCRIBED = 'MP' MUSTNOTPRESCRIBE = 'MNP' MEDICINESTATUS = [ (MUSTPRESCRIBED, 'Must be Prescribed'), (MUSTNOTPRESCRIBE, 'Must not be Prescribed'), ] GENERAL = 'A' BLOOD = 'B' DIGESTIVE = 'D' EYE = 'F' EAR = 'H' CIRCULATORY = 'K' MUSCULOSKELETAL = 'L' NEUROLOGICAL = 'N' PSYCHOLOGICAL = 'P' RESPIRATORY = 'R' SKIN = 'S' ENDORCRINE = 'T' UROLOGY = 'U' PREGNANCY = 'W' FEMALEGENITAL = 'X' MALEGENITAL = 'Y' SOCIALPROB = 'Z' MEDICINECATAGORIES = [ (GENERAL, 'General and unspecified'), (BLOOD, 'Blood, blood forming organs, lymphatics, spleen'), (DIGESTIVE, 'Digestive'), (EYE, 'Eye'), (EAR, 'Ear'), (CIRCULATORY, 'Circulatory'), (MUSCULOSKELETAL, 'Musculoskeletal'), (NEUROLOGICAL, 'Neorological'), (PSYCHOLOGICAL, 'Psychological'), (RESPIRATORY, 'Respiratory'), (SKIN, 'Skin'), (ENDORCRINE, 'Endocrine, metabolic and nutritional'), (UROLOGY, 'Urology'), (PREGNANCY, 'Pregnancy, childbirth, family planning'), (FEMALEGENITAL, 'Female genital system and breast'), (MALEGENITAL, 'Male genital system'), (SOCIALPROB, 'Social problems'), ] med_name = models.CharField(max_length = 200) med_id = models.BigAutoField(primary_key = True, serialize=False) med_price = models.FloatField(max_length = 10) med_quantity = models.PositiveIntegerField() med_status = models.CharField(max_length = 3, choices = MEDICINESTATUS, default=MUSTPRESCRIBED) med_catagory = models.CharField(max_length = 2, choices = MEDICINECATAGORIES, default = GENERAL) med_generic = models.CharField(max_length = 100) pharmacy_id = models.ForeignKey(Employee, on_delete = models.CASCADE) def is_upperclass(self): return self.year_in_school in {self.MUSTPRESCRIBED, self.MUSTNOTPRESCRIBE} def __str__(self): return self.med_name class Customer(models.Model): customer_name = models.CharField(max_length = 100) customer_id = models.BigAutoField(primary_key = True, serialize = False) birthdate = models.DateField() customer_address = models.CharField(max_length = 254) customer_password = models.CharField(max_length = 100) customer_email = models.EmailField(max_length = 254) customer_phone = models.CharField(max_length = 15) customer_longT = models.CharField(max_length = 20, default= "90.40") customer_latiT = models.CharField(max_length = 20, default= "20.40") def __str__(self): return self.customer_name class Delivery(models.Model): DS_id = models.AutoField(primary_key = True) DS_start_time = models.TimeField() DS_stop_time = models.TimeField() DS_capacity = models.IntegerField(default = 15) DS_status = models.BooleanField(default = True) def __str__(self): return str(self.DS_id) class Cart(models.Model): cart_id = models.BigAutoField(primary_key = True) pharmacy_id = models.ForeignKey(Employee, on_delete = models.CASCADE) customer_id = models.ForeignKey(Customer, on_delete = models.CASCADE) adding_quantity = models.IntegerField(default= 5) med_id = models.ForeignKey(Inventory, on_delete = models.CASCADE) def __str__(self): return str(self.cart_id) class OrderedCart(models.Model): order_cart_id = models.BigAutoField(primary_key = True) pharmacy_id = models.ForeignKey(Employee, on_delete = models.CASCADE) customer_id = models.ForeignKey(Customer, on_delete = models.CASCADE) adding_quantity = models.IntegerField(default= 5) med_id = models.ForeignKey(Inventory, on_delete = models.CASCADE) def __str__(self): return str(self.order_cart_id) class Order(models.Model): ONPROCESS = 'OP' ONTHEWAY = 'OTW' DELIVERED = 'DV' DELIVERYSTATUS = [ (ONPROCESS, 'Processing'), (ONTHEWAY, 'On the way'), (DELIVERED, 'Medicine Delivered') ] CASHONDELVRY = 'COD' BKASH = 'BKS' ROCKET = 'RKT' CARD = 'CRD' PAYPAL = 'PPL' PAYMENTOPTIONS = [ (CASHONDELVRY, 'Cash On Delivery'), (BKASH, 'Bkash'), (ROCKET, 'Rocket'), (CARD, 'ATM Card'), (PAYPAL, 'PayPal') ] order_id = models.BigAutoField(primary_key = True) order_date = models.DateTimeField(auto_now_add=True) pharmacy_id = models.ManyToManyField(Employee) customer_id = models.ForeignKey(Customer, on_delete = models.CASCADE) delivery_id = models.ForeignKey(Delivery, on_delete = models.CASCADE) delivery_status = models.CharField(max_length = 3, choices = DELIVERYSTATUS, default = ONPROCESS) rating = models.IntegerField() order_quantity = models.IntegerField(default= 5) med_ids = models.ManyToManyField(Inventory) order_status = models.BooleanField(default=False) order_type = models.CharField(max_length = 3, choices = PAYMENTOPTIONS, default = CASHONDELVRY) delivery_note = models.CharField(max_length = 100, default = "Call me when you arrive") order_cost = models.CharField(max_length = 10, default = "10") order_longT = models.CharField(max_length = 20, default= "90.40") order_latiT = models.CharField(max_length = 20, default= "20.40") orered_cart = models.ManyToManyField(OrderedCart) def __str__(self): return str(self.order_id) class Admin(models.Model): admin_name = models.CharField(max_length = 100) admin_password = models.CharField(max_length = 100) admin_id = models.AutoField(primary_key = True) admin_designation = models.CharField(max_length = 50) admin_phone = models.CharField(max_length = 15) admin_email = models.EmailField(max_length = 254) def __str__(self): return self.admin_name class Prescription(models.Model): pres_id = models.BigAutoField(primary_key = True) customer_id = models.ForeignKey(Customer, on_delete = models.CASCADE) pres_status = models.BooleanField(default=False) order_id = models.ForeignKey(Order, on_delete = models.CASCADE) def __str__(self): return str(self.pres_id) class Coupon(models.Model): coupon_id = models.BigAutoField(primary_key = True) coupon_code = models.CharField(max_length = 10) coupon_amount = models.IntegerField() med_id = models.ForeignKey(Inventory, on_delete = models.CASCADE) def __str__(self): return self.coupon_code

[ "muhammadniazmorshed@gmail.com" ]

muhammadniazmorshed@gmail.com

3c26872318ad21cb83b2b723de7ce8593642ae93

59d65cd3fa9e614bfd539aff88744cc2b450cf8b

/ex101 - funcao voto.py

75644343f216ad4c14cf5e36f25f2dc6fc52e3c1

[]

no_license

gerolaleticia/Voting-function

89c5cca817869e8a9fc514a85f88b1db0ce98f76

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refs/heads/master

2021-03-30T02:09:14.594967

2020-04-01T20:21:50

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py

def voto(ano): from datetime import date atual = date.today().year idade = atual - ano if atual - ano < 18 and atual - ano > 2016: print(f'Com {idade} anos o voto é OPCIONAL.') elif atual - ano >= 65: print(f'Com {idade} anos o voto é OPCIONAL.') elif atual - ano < 16: print(f'Com {idade} anos NÃO VOTA.') else: print(f'Com {idade} anos o voto é OBRIGATÓRIO.') #programa principal ano = int(input('Em que ano a pessoa nasceu? ')) voto(ano) '''def voto(ano): from datetime import date atual = date.today().year idade = atual - ano if atual - ano < 18 and atual - ano > 2016: return (f'Com {idade} anos o voto é OPCIONAL.') elif atual - ano >= 65: return (f'Com {idade} anos o voto é OPCIONAL.') elif atual - ano < 16: return (f'Com {idade} anos NÃO VOTA.') else: return (f'Com {idade} anos o voto é OBRIGATÓRIO.') #programa principal print(voto(2000))'''

[ "noreply@github.com" ]

gerolaleticia.noreply@github.com

2925862530fc1d63e4d390624948e264adb3f2ca

104baf85a7fed4bbb738e66f5a308dcf5360a201

/VQCPCB/data_processor/bach_data_processor.py

a7fe2c2b39ec95fd9cfadda58d87d528889a2ce5

[]

no_license

MGSong/vqcpc-bach

09403c217bdd5165a4609b511ef837f4a19f650a

36a772bf99a7a2aba462bd86d362b7180f08847a

refs/heads/master

2023-02-22T20:32:06.728063

2021-01-27T14:03:18

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UTF-8

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import torch from VQCPCB.data_processor.data_processor import DataProcessor from VQCPCB.utils import flatten, to_numpy class BachDataProcessor(DataProcessor): def __init__(self, embedding_size, num_events, num_tokens_per_channel): super(BachDataProcessor, self).__init__(embedding_size=embedding_size, num_events=num_events, num_tokens_per_channel=num_tokens_per_channel )

[ "crestel.leopold@gmail.com" ]

crestel.leopold@gmail.com

411a288382166b49c68b10168485d9a50dbbfaf3

d69d43fd29177e86f1ad697d158a7d4eb2c14d63

/my_dogs.py

df9572710fdd5389a08458f6babbea4034a0910c

[]

no_license

sicaramacuya/superhero-team-dueler

3a8ccc764ce75b49730e300dfe1a2ff3336ecd97

1afe77b79d5ba54ce47cac2b49d172a0576fc584

refs/heads/main

2023-02-05T20:53:07.708087

2020-12-04T21:52:09

315,133,258

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from dog import Dog my_dog = Dog('Rex', 'SuperDog') my_dog.bark() my_other_dog = Dog('Annie', 'SuperDog') print(my_other_dog.name) amigo = Dog('Amigo', 'SuperSuperDog') solo = Dog('Solo', 'SuperDuperDog') mando = Dog('Mando', 'SuperSuperDuperDog') amigo.sit() solo.roll() mando.bark()

[ "eric.morales-rodriguez@students.makeschool.com" ]

eric.morales-rodriguez@students.makeschool.com

edd73bda636781493ea4aceee5f06ca00ecb80be

61602ef53c4a4a16df06e09e91763a155807c2dc

/tests/test_scxml.py

7bb8d78843e2c1ae821268280b8956dc0d06518d

[ "MIT" ]

permissive

matEhickey/xstate-python

17265332e20caf039931900d7984860438f4e318

09f97897004d1e4f06e666fee3cdb0d55c9d91ce

refs/heads/master

2022-12-31T17:25:23.097920

2020-08-17T13:07:35

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MIT

2022-09-06T13:29:46

2020-08-17T12:13:36

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import xml.etree.ElementTree as ET from typing import Optional, Dict, List import json import pytest from xstate.scxml import scxml_to_machine test_dir = "node_modules/@scion-scxml/test-framework/test" test_groups: Dict[str, List[str]] = {"actionSend": ["send1"]} test_files = [ (f"{test_dir}/{k}/{vv}.scxml", f"{test_dir}/{k}/{vv}.json") for k, v in test_groups.items() for vv in v ] @pytest.mark.parametrize("scxml_source,scxml_test_source", test_files) def test_scxml(scxml_source, scxml_test_source): machine = scxml_to_machine(scxml_source) state = machine.initial_state with open(scxml_test_source) as scxml_test_file: scxml_test = json.load(scxml_test_file) for event_test in scxml_test.get("events"): event_to_send = event_test.get("event") event_name = event_to_send.get("name") next_configuration = event_test.get("nextConfiguration") state = machine.transition(state, event_name) assert [sn.key for sn in state.configuration] == next_configuration

[ "davidkpiano@gmail.com" ]

davidkpiano@gmail.com

17627ea9e12d3290f0494d045472dbace5088570

3794d14d99ef737217f568234058811595d9ec61

/analysis_nlp.py

27dccef1a6c62935aaef8e726679be9f26664693

[]

no_license

thepharmproject/set_of_scripts

ff109dda5556f1cf77fad0b87fe810439a8e776c

9c09a543924168424d44d3589fc3a34ea9c7c218

refs/heads/master

2023-01-28T04:16:05.990536

2020-12-11T08:09:31

294,672,197

5

1

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''' This python file includes various nlp analysis methods ''' ''' PYTHON SETUP ''' # a list of the required packages is listed here based on anaconda setup commands. # conda install seaborn # conda install scikit-learn # conda install -c conda-forge parsedatetime # conda install -c conda-forge dateparser # conda install -c conda-forge datefinder # conda install -c conda-forge textblob # conda install -c conda-forge googletrans # conda install -c conda-forge langdetect # conda install -c conda-forge geopy # conda install -c conda-forge jellyfish # conda install -c conda-forge matplotlib # conda install -c conda-forge spacy # python -m spacy download en_core_web_sm # python -m spacy download en_core_web_md # python -m spacy download el_core_news_sm # python -m spacy download el_core_news_md # python -m spacy download es_core_news_sm # python -m spacy download es_core_news_md # python -m spacy download it_core_news_sm # python -m spacy download it_core_news_md ''' LIBRARIES IMPORTED ''' import time, argparse, string, json, sys from textblob import TextBlob from googletrans import Translator from langdetect import detect import parsedatetime, dateparser, datefinder from geopy.geocoders import Nominatim, GoogleV3 from difflib import SequenceMatcher import jellyfish import spacy from spacy import displacy from spacy.matcher import Matcher, PhraseMatcher # from spacy.lang.en import English, Spanish, Italian import numpy as np import matplotlib.pyplot as plt import seaborn as sns from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer from sklearn.decomposition import NMF, LatentDirichletAllocation from collections import Counter import utilities as utils ''' ANALYSIS METHODS ''' # ****************************************************************************************** # detect language from text. a recursive approach is adopted for improved robustness. # textblob, google translate and langdetect services are used. if a service fails the result # form the next one is requested. def detect_language(text): print('* language detection') lang = None try: lang = TextBlob(text[:100]).detect_language() print('\tlanguage is (TextBlob):', lang) except: print('\tTextBlob failed') try: lang = Translator().detect(text[:100]).lang print('\tlanguage is (Google Translator):', lang,) except: print('\tGoogle Translator failed') try: lang = detect(text[:100]) print('\tlanguage is (langdetect):', lang) except: print('\tlangdetect failed') if lang is None: print('\tlanguage detection failed...') return lang # ****************************************************************************************** # detect datetime from metadata and text. a recursive approach is adopted here as well. # dateparser, datefinder and parsedatetime packages are exploited ranked from higher accuracy # to higher probability of returning a result. if the most accurate fails to detect the # datetime object, the next service is called and so on. detection is based on metadata, # where date date information is commonly present. if datetime detection fails for all # services in metadata, the same workflow is applied to text data. def detect_datetime(text, meta, lang): print('* datetime detection') # initialize results results = [] date = None print('\tmeta:', meta) if len(results) == 0: try: date = dateparser.parse(meta) if date is not None: print('\tdateparser meta:', date) results.append(str(date)) except: print('\tdateparser meta failed') if len(results) == 0: print('\tdateparser meta: none') try: dates = datefinder.find_dates(meta) for date_item in dates: date = date_item print('\tdatefinder meta:', date) results.append(str(date)) break except: print('\tdatefinder meta failed') if len(results) == 0: print('\tdatefinder meta: none') try: date = dateparser.parse(text) if date is not None: print('\tdateparser text:', date) results.append(str(date)) except: print('\tdateparser text failed') if len(results) == 0: print('\tdateparser text: none') try: dates = datefinder.find_dates(text) for date_item in dates: date = date_item print('\tdatefinder text:', date) results.append(str(date)) break except: print('\tdatefinder text failed') if len(results) == 0: print('\tdatefinder text: none') print('\tno datetime information found in text') # datetime = parsedatetime.Calendar().parse(meta) date = '' results.append(str(date)) return results[0] # ****************************************************************************************** # detect hate speech in text. three approaches are implemented (mode='strings', 'lemmas', # 'vectors','both'). the first one is based in a dictionary of terms for four different # languages, english, greek, italian and spanish. a language model is loaded (according to # the language of the text), common practices are followed (lowercasing, lemmatization, stop # word and punctuation removal), and the targeted terms are being searched in the text. if # found, text segments are denoted as "hate speech". the second one is based in word vectors # allowing for a more semantic detection. the same workflow is followed for this method as # well (lemmatization etc.). if mode is set to "both" the union of the results from all # methods is returned. def detect_hate(text, meta, lang, mode='strings'): print('* hate speech detection with mode \'{}\''.format(mode)) # initialize the results list results = [] # load the appropriate language model if mode == 'strings' or mode == 'lemmas': model_suffix = 'sm' else: model_suffix = 'md' if lang == 'en': nlp = spacy.load(lang + '_core_web_' + model_suffix) elif lang == 'el' or lang == 'es' or lang == 'it': nlp = spacy.load(lang + '_core_news_' + model_suffix) else: return '' # load the filter terms from the dictionaries - safe words and phrases, secondary words and primary words with open('Dictionaries\\dictionary_' + lang + '_s.txt', 'r', encoding='utf-8') as file: terms_list = file.read().splitlines() with open('Dictionaries\\dictionary_' + lang + '_a.txt', 'r', encoding='utf-8') as file: terms_a = file.read().splitlines() with open('Dictionaries\\dictionary_' + lang + '_b.txt', 'r', encoding='utf-8') as file: terms_b = file.read().splitlines() # synthesize phrases for term_a in terms_a: for term_b in terms_b: # find all suffixes and make all possible combinations if term_a.find("/") > 0: term_a = term_a[:term_a.find("/")] if term_b.find("/") > 0: term_b = term_b[:term_b.find("/")] # if the suffix ends with a "-" join the words instead of making a phrase if term_a[-1] =='-': terms_list.append(term_a[:-1] + term_b) else: terms_list.append(term_a + ' ' + term_b) #time_c = time.time() # print('\tload dictionary:', time_c - time_b) # find matches in text and search phrases words_token = nlp(text) # for each search phrase for terms in terms_list: # print('analyzing search term \'{}\''.format(terms)) matches = [] # for each word of the search phrase for term_token in nlp(terms): #terms.split() if len(matches) > 0 and matches[0] < 0: # break word_pos = -1 matches.append(word_pos) term_t = utils.clean_accent(term_token.text.lower()) term_tl = utils.clean_accent(term_token.lemma_.lower()) # for each word of the text for word_token in words_token: word_pos += 1 word_t = utils.clean_accent(word_token.text.lower()) word_tl = utils.clean_accent(word_token.lemma_.lower()) # string manipulation if mode == 'strings' or mode == 'both': score = SequenceMatcher(None, word_t, term_t).ratio() if lang == 'el': match = word_t.find(term_t[:max(3, len(term_t)-3)]) else: match = word_t.find(term_t[:max(3, len(term_t)-1)]) if score > 0.5 and match == 0: # print('\tstring manipulation for term \"{}\" and word \"{}\" with score {:.2f}'.format(term_token, word_token, score)) if not word_pos in matches: matches[len(matches)-1] = word_pos break # lemma manipulation if mode == 'lemmas' or mode == 'both': score = SequenceMatcher(None, word_tl, term_tl).ratio() if score > 0.5: # print('\tstring manipulation for term \"{}\" and word \"{}\" with score {:.2f}'.format(term_token, word_token, score)) if not word_pos in matches: matches[len(matches) - 1] = word_pos break # word vectors if mode == 'vectors' or mode == 'both': if word_token.has_vector and term_token.has_vector and len(word_token.text) > 5: score = term_token.similarity(word_token) if score > 0.8: # print('\tword-vector for term \"{}\" and word \"{}\" with score {:.2f}:'.format(term_token, word_token, score)) if not word_pos in matches: matches[len(matches)-1] = word_pos break # confirm matches and locate text match = True for i in range(len(matches)): if matches[i] < 0: match = False matches.sort() if match == True: # print('\tfound hate-speech for term \'{}\' positions are {}'.format(terms, matches)) # print the whole segment # results.append('') # for i in range(matches[0], matches[-1]+1): results[-1] += words_token[i].text + ' ' # print('\tpart of text:', results[-1]) # just print the word combination results.append('(') for i in range(len(matches)): results[-1] += words_token[matches[i]].text + ' ' results[-1] = results[-1][:-1] + ', ' + terms + ')' #time_d = time.time() #print('\tanalyze phrase: {:.2f}'.format(time_d - time_c)) # transform results to text results_txt = '' for result in results: # results_txt = results_txt + result + ", " results_txt = results_txt[:-2] print('\thate speech:', results_txt) return results_txt # ****************************************************************************************** # a faster implementation of the aforementioned hate speech detection. def detect_hate_fast(text, meta, lang, mode='strings'): print('* hate speech detection') # initialize the results list results = [] # load the appropriate language model if mode == 'strings' or mode == 'lemmas': model_suffix = 'sm' else: model_suffix = 'md' if lang == 'en': nlp = spacy.load(lang + '_core_web_' + model_suffix) elif lang == 'el' or lang == 'es' or lang == 'it': nlp = spacy.load(lang + '_core_news_' + model_suffix) else: return '' # load the filter terms from the dictionaries - safe words and phrases, secondary words and primary words with open('Dictionaries\\dictionary_' + lang + '_s.txt', 'r', encoding='utf-8') as file: terms_s = file.read().splitlines() with open('Dictionaries\\dictionary_' + lang + '_a.txt', 'r', encoding='utf-8') as file: terms_a = file.read().splitlines() with open('Dictionaries\\dictionary_' + lang + '_b.txt', 'r', encoding='utf-8') as file: terms_b = file.read().splitlines() for term_a in terms_a: if term_a.find("/") > 0: term_a = term_a[:term_a.find("/")] for term_b in terms_b: if term_b.find("/") > 0: term_b = term_b[:term_b.find("/")] # terms_b = list(dict.fromkeys(terms_b)) # find matches in text and search phrases matches = [] words_token = nlp(text) dict_pos = 0 for terms_t in [terms_a, terms_b]: # for each term list for terms in terms_t: word_pos = -1 term_token = nlp(terms)[0] term_t = utils.clean_accent(term_token.text.lower()) term_tl = utils.clean_accent(term_token.lemma_.lower()) # for each word of the text for word_token in words_token: word_pos += 1 word_t = utils.clean_accent(word_token.text.lower()) word_tl = utils.clean_accent(word_token.lemma_.lower()) # string manipulation if mode == 'strings' or mode == 'both': score = SequenceMatcher(None, word_t, term_t).ratio() if lang == 'el': match = word_t.find(term_t[:max(3, len(term_t)-3)]) else: match = word_t.find(term_t[:max(3, len(term_t)-1)]) if score > 0.8 and match == 0: # print('\tterm \"{}\" and word \"{}\" | score {:.2f} and position {}'.format(term_token, word_token, score, word_pos)) if not word_pos in matches: matches.append(word_pos) break # lemma manipulation if mode == 'lemmas' or mode == 'both': score = SequenceMatcher(None, word_tl, term_tl).ratio() if score > 0.75: # print('\tstring manipulation for term \"{}\" and word \"{}\" with score {:.2f}'.format(term_token, word_token, score)) if not word_pos in matches: matches.append(word_pos) break # word vectors if mode == 'vectors' or mode == 'both': if word_token.has_vector and term_token.has_vector and len(word_token.text) > 3: score = term_token.similarity(word_token) if score > 0.65: # print('\tword-vector for term \"{}\" and word \"{}\" with score {:.2f}:'.format(term_token, word_token, score)) if not word_pos in matches: matches.append(word_pos) break else: continue break # confirm matches and locate text if len(matches) == 2: results.append('(') for i in range(len(matches)): results[-1] += words_token[matches[i]].text + ' ' results[-1] = results[-1][:-1] + ')' # transform results to text results_txt = '' for result in results: # results_txt = results_txt + result + ", " results_txt = results_txt[:-2] print('\thate speech:', results_txt) return results_txt # ****************************************************************************************** # an alternative method for implementing hate speech detection. it is based on spacy's # phrase matcher. def detect_hate_matcher(text, meta, lang): file = open(data_path, 'r', encoding='utf-8') data = file.read().splitlines() file.close() counter = 0 for datum in data: # load text try: datum = json.loads(datum)['text'] counter += 1 except: print('JSON error') continue # analyze text lang = Translator().detect(datum[:100]).lang print('{}. {}'.format(counter, datum[:100])) print('The language is: {}'.format(lang)) if lang == 'el': nlp = spacy.load('el_core_news_sm') elif lang == 'es': nlp = spacy.load('es_core_news_sm') elif lang == 'it': nlp = spacy.load('it_core_news_sm') elif lang == 'en': nlp = spacy.load('en_core_web_sm') else: continue # load dictionary file = open('Dictionaries\\dictionary_' + lang + '.txt', 'r', encoding='utf-8') terms = file.read().splitlines() file.close() # token matcher # matcher = Matcher(nlp.vocab) # pattern = [{"LOWER": "κάνει μήνυση"}, {"IS_PUNCT": True}] # matcher.add("HelloWorld", None, pattern) # phrase matcher terms = ["Ερντογάν", "μήνυση", "μΗνες"] for i in range(len(terms)): for token in nlp(terms[i]): terms[i] = utils.clean_accent(token.lemma_.lower()) print(terms) # sys.exit() matcher = PhraseMatcher(nlp.vocab) patterns = [nlp.make_doc(text) for text in terms] matcher.add("TerminologyList", None, *patterns) datum_t = '' for token in nlp(datum): datum_t += utils.clean_accent(token.lemma_.lower()) + ' ' print(datum_t) doc = nlp(datum_t) matches = matcher(doc) for match_id, start, end in matches: string_id = nlp.vocab.strings[match_id] # Get string representation span = doc[start:end] # The matched span print(match_id, string_id, start, end, span.text) # html = displacy.render(doc, style="ent", page=True, options={"ents": ["EVENT"]}) # print(terms_t) # print(datum_t) time.sleep(3) # ****************************************************************************************** # a simple approach for suggesting frequent words found in texts. this can help for expanding # the list of terms found in the dictionaries for filtering data for hate speech. this method # can be used in texts that already have been marked as "hate speech". def detect_terms(text, meta, lang): print('* term detection') # initialize results results = [] # load the appropriate spacy model and isolate terms named entity gpe, loc, fac, org if lang == 'en': nlp = spacy.load('en_core_web_sm') elif lang == 'el' or lang == 'es' or lang == 'it': nlp = spacy.load(lang + '_core_news_sm') else: return # remove stopwords, punctuation marks and make characters lowercase words = [token.lemma_.lower() for token in nlp(text) if token.is_stop != True and token.is_punct != True] # count frequency of words word_freq = Counter(words) common_words = word_freq.most_common(5) # print('\t', common_words) # filter frequent terms for common_word in common_words: if common_word[1] >= 3 and len(common_word[0]) >= 3: results.append(common_word[0]) # print('\tcommnon word:', common_word[0]) # transform results to text results_txt = '' for result in results: # results_txt = results_txt + result + ", " results_txt = results_txt[:-2] print('\tcommnon words:', results_txt) return results_txt # ****************************************************************************************** # a method for detecting geolocation from text. geopy with nominatim geocoder are used. # entities in the following ranking are preferred: GPE (countries, cities, states), LOC # (mountains, bodies of water), FAC (buildings, airports, highways etc.), ORG (companies, # agancies, institutions etc.). def detect_location(text, meta, lang): print('* location detection') # initialize results results = [] # load the nominatim geopy geocoder n = Nominatim(user_agent="http") # load the appropriate spacy model and isolate terms named entity gpe, loc, fac, org if lang == 'en': nlp = spacy.load('en_core_web_sm') elif lang == 'el' or lang == 'es' or lang == 'it': nlp = spacy.load(lang + '_core_news_sm') else: return ents = nlp(text).ents # find gpe entities if len(results) == 0: for ent in ents: # print(ent.text, ent.start_char, ent.end_char, ent.label_) #label_ -> ORG, GPE, MONEY if ent.label_ == 'GPE': geo = n.geocode(ent.text, language='en') if geo is not None: results.append([ent.text, geo.raw["display_name"].split(",")[-1], geo.raw["lat"], geo.raw["lon"]]) # print('\tpossible locations (GPE):', results[-1]) # try for fac entities if len(results) == 0: for ent in ents: if ent.label_ == 'FAC': geo = n.geocode(ent.text, language='en') if geo is not None: results.append([ent.text, geo.raw["display_name"].split(",")[-1], geo.raw["lat"], geo.raw["lon"]]) # print('\tpossible locations (FAC):', results[-1]) # try for org entities if len(results) == 0: for ent in ents: if ent.label_ == 'ORG': geo = n.geocode(ent.text, language='en') if geo is not None: results.append([ent.text, geo.raw["display_name"].split(",")[-1], geo.raw["lat"], geo.raw["lon"]]) # print('\tpossible locations (ORG):', results[-1]) # try for loc entities if len(results) == 0: for ent in ents: if ent.label_ == 'LOC': geo = n.geocode(ent.text, language='en') if geo is not None: results.append([ent.text, geo.raw["display_name"].split(",")[-1], geo.raw["lat"], geo.raw["lon"]]) # print('\tpossible locations (LOC):', results[-1]) # estimate only one location words = [] for result in results: words.append(utils.clean_whitespaces(result[1])) word_freq = Counter(words) common_words = word_freq.most_common(5) results = [] for common_word in common_words: results.append(common_word[0]) # break #print('\testimated location:', results) # transform results to text results_txt = '' for result in results: # results_txt = results_txt + result + ", " results_txt = results_txt[:-2] print('\testimated locations:', results_txt) return results_txt # ****************************************************************************************** # a pilot method for executing sentiment analysis. it will be used as the base for the # upcoming sentiment analysis methods. def analyze_sentiment(text, meta, lang): nlp = English() # We only want the tokenizer, so no need to load a model matcher = Matcher(nlp.vocab) pos_emoji = ["😀", "😃", "😂", "🤣", "😊", "😍"] # Positive emoji neg_emoji = ["😞", "😠", "😩", "😢", "😭", "😒"] # Negative emoji # Add patterns to match one or more emoji tokens pos_patterns = [[{"ORTH": emoji}] for emoji in pos_emoji] neg_patterns = [[{"ORTH": emoji}] for emoji in neg_emoji] # Function to label the sentiment def label_sentiment(matcher, doc, i, matches): match_id, start, end = matches[i] if doc.vocab.strings[match_id] == "HAPPY": # Don't forget to get string! doc.sentiment += 0.1 # Add 0.1 for positive sentiment elif doc.vocab.strings[match_id] == "SAD": doc.sentiment -= 0.1 # Subtract 0.1 for negative sentiment matcher.add("HAPPY", label_sentiment, *pos_patterns) # Add positive pattern matcher.add("SAD", label_sentiment, *neg_patterns) # Add negative pattern # Add pattern for valid hashtag, i.e. '#' plus any ASCII token matcher.add("HASHTAG", None, [{"ORTH": "#"}, {"IS_ASCII": True}]) doc = nlp("Hello world 😀 #MondayMotivation") matches = matcher(doc) for match_id, start, end in matches: string_id = doc.vocab.strings[match_id] # Look up string ID span = doc[start:end] print(string_id, span.text) # ****************************************************************************************** # a method for tfidf (term frequency–inverse document frequency) with nmf (non-negative # matrix factorization) or lda (latent dirichlet allocation) is deployed for topic modeling. # a list of topics is created based on a corpus of text items. detected topics and most # common terms are printed. 'mode' can be set to 'nmf' or 'lda'. enable 'plot' to get graphs # for common terms found in texts. def topic_modeling(corpus, mode='nmf', plot=False): # detect language language = detect_language(corpus[0]) print('* topic modeling') # initialize results results = [] results_txt = '' # remove unwanted words if language == 'en': # stop_words = 'english' elif language == 'es': # stop_words = ["0","1","2","3","4","5","6","7","8","9","_","a","actualmente","acuerdo","adelante","ademas","además","adrede","afirmó","agregó","ahi","ahora","ahí","al","algo","alguna","algunas","alguno","algunos","algún","alli","allí","alrededor","ambos","ampleamos","antano","antaño","ante","anterior","antes","apenas","aproximadamente","aquel","aquella","aquellas","aquello","aquellos","aqui","aquél","aquélla","aquéllas","aquéllos","aquí","arriba","arribaabajo","aseguró","asi","así","atras","aun","aunque","ayer","añadió","aún","b","bajo","bastante","bien","breve","buen","buena","buenas","bueno","buenos","c","cada","casi","cerca","cierta","ciertas","cierto","ciertos","cinco","claro","comentó","como","con","conmigo","conocer","conseguimos","conseguir","considera","consideró","consigo","consigue","consiguen","consigues","contigo","contra","cosas","creo","cual","cuales","cualquier","cuando","cuanta","cuantas","cuanto","cuantos","cuatro","cuenta","cuál","cuáles","cuándo","cuánta","cuántas","cuánto","cuántos","cómo","d","da","dado","dan","dar","de","debajo","debe","deben","debido","decir","dejó","del","delante","demasiado","demás","dentro","deprisa","desde","despacio","despues","después","detras","detrás","dia","dias","dice","dicen","dicho","dieron","diferente","diferentes","dijeron","dijo","dio","donde","dos","durante","día","días","dónde","e","ejemplo","el","ella","ellas","ello","ellos","embargo","empleais","emplean","emplear","empleas","empleo","en","encima","encuentra","enfrente","enseguida","entonces","entre","era","erais","eramos","eran","eras","eres","es","esa","esas","ese","eso","esos","esta","estaba","estabais","estaban","estabas","estad","estada","estadas","estado","estados","estais","estamos","estan","estando","estar","estaremos","estará","estarán","estarás","estaré","estaréis","estaría","estaríais","estaríamos","estarían","estarías","estas","este","estemos","esto","estos","estoy","estuve","estuviera","estuvierais","estuvieran","estuvieras","estuvieron","estuviese","estuvieseis","estuviesen","estuvieses","estuvimos","estuviste","estuvisteis","estuviéramos","estuviésemos","estuvo","está","estábamos","estáis","están","estás","esté","estéis","estén","estés","ex","excepto","existe","existen","explicó","expresó","f","fin","final","fue","fuera","fuerais","fueran","fueras","fueron","fuese","fueseis","fuesen","fueses","fui","fuimos","fuiste","fuisteis","fuéramos","fuésemos","g","general","gran","grandes","gueno","h","ha","haber","habia","habida","habidas","habido","habidos","habiendo","habla","hablan","habremos","habrá","habrán","habrás","habré","habréis","habría","habríais","habríamos","habrían","habrías","habéis","había","habíais","habíamos","habían","habías","hace","haceis","hacemos","hacen","hacer","hacerlo","haces","hacia","haciendo","hago","han","has","hasta","hay","haya","hayamos","hayan","hayas","hayáis","he","hecho","hemos","hicieron","hizo","horas","hoy","hube","hubiera","hubierais","hubieran","hubieras","hubieron","hubiese","hubieseis","hubiesen","hubieses","hubimos","hubiste","hubisteis","hubiéramos","hubiésemos","hubo","i","igual","incluso","indicó","informo","informó","intenta","intentais","intentamos","intentan","intentar","intentas","intento","ir","j","junto","k","l","la","lado","largo","las","le","lejos","les","llegó","lleva","llevar","lo","los","luego","lugar","m","mal","manera","manifestó","mas","mayor","me","mediante","medio","mejor","mencionó","menos","menudo","mi","mia","mias","mientras","mio","mios","mis","misma","mismas","mismo","mismos","modo","momento","mucha","muchas","mucho","muchos","muy","más","mí","mía","mías","mío","míos","n","nada","nadie","ni","ninguna","ningunas","ninguno","ningunos","ningún","no","nos","nosotras","nosotros","nuestra","nuestras","nuestro","nuestros","nueva","nuevas","nuevo","nuevos","nunca","o","ocho","os","otra","otras","otro","otros","p","pais","para","parece","parte","partir","pasada","pasado","paìs","peor","pero","pesar","poca","pocas","poco","pocos","podeis","podemos","poder","podria","podriais","podriamos","podrian","podrias","podrá","podrán","podría","podrían","poner","por","por 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elif language == 'it': # stop_words = ["a","abbastanza","abbia","abbiamo","abbiano","abbiate","accidenti","ad","adesso","affinché","agl","agli","ahime","ahimè","ai","al","alcuna","alcuni","alcuno","all","alla","alle","allo","allora","altre","altri","altrimenti","altro","altrove","altrui","anche","ancora","anni","anno","ansa","anticipo","assai","attesa","attraverso","avanti","avemmo","avendo","avente","aver","avere","averlo","avesse","avessero","avessi","avessimo","aveste","avesti","avete","aveva","avevamo","avevano","avevate","avevi","avevo","avrai","avranno","avrebbe","avrebbero","avrei","avremmo","avremo","avreste","avresti","avrete","avrà","avrò","avuta","avute","avuti","avuto","basta","ben","bene","benissimo","brava","bravo","buono","c","caso","cento","certa","certe","certi","certo","che","chi","chicchessia","chiunque","ci","ciascuna","ciascuno","cima","cinque","cio","cioe","cioè","circa","citta","città","ciò","co","codesta","codesti","codesto","cogli","coi","col","colei","coll","coloro","colui","come","cominci","comprare","comunque","con","concernente","conclusione","consecutivi","consecutivo","consiglio","contro","cortesia","cos","cosa","cosi","così","cui","d","da","dagl","dagli","dai","dal","dall","dalla","dalle","dallo","dappertutto","davanti","degl","degli","dei","del","dell","della","delle","dello","dentro","detto","deve","devo","di","dice","dietro","dire","dirimpetto","diventa","diventare","diventato","dopo","doppio","dov","dove","dovra","dovrà","dovunque","due","dunque","durante","e","ebbe","ebbero","ebbi","ecc","ecco","ed","effettivamente","egli","ella","entrambi","eppure","era","erano","eravamo","eravate","eri","ero","esempio","esse","essendo","esser","essere","essi","ex","fa","faccia","facciamo","facciano","facciate","faccio","facemmo","facendo","facesse","facessero","facessi","facessimo","faceste","facesti","faceva","facevamo","facevano","facevate","facevi","facevo","fai","fanno","farai","faranno","fare","farebbe","farebbero","farei","faremmo","faremo","fareste","faresti","farete","farà","farò","fatto","favore","fece","fecero","feci","fin","finalmente","finche","fine","fino","forse","forza","fosse","fossero","fossi","fossimo","foste","fosti","fra","frattempo","fu","fui","fummo","fuori","furono","futuro","generale","gente","gia","giacche","giorni","giorno","giu","già","gli","gliela","gliele","glieli","glielo","gliene","grande","grazie","gruppo","ha","haha","hai","hanno","ho","i","ie","ieri","il","improvviso","in","inc","indietro","infatti","inoltre","insieme","intanto","intorno","invece","io","l","la","lasciato","lato","le","lei","li","lo","lontano","loro","lui","lungo","luogo","là","ma","macche","magari","maggior","mai","male","malgrado","malissimo","me","medesimo","mediante","meglio","meno","mentre","mesi","mezzo","mi","mia","mie","miei","mila","miliardi","milioni","minimi","mio","modo","molta","molti","moltissimo","molto","momento","mondo","ne","negl","negli","nei","nel","nell","nella","nelle","nello","nemmeno","neppure","nessun","nessuna","nessuno","niente","no","noi","nome","non","nondimeno","nonostante","nonsia","nostra","nostre","nostri","nostro","novanta","nove","nulla","nuovi","nuovo","o","od","oggi","ogni","ognuna","ognuno","oltre","oppure","ora","ore","osi","ossia","ottanta","otto","paese","parecchi","parecchie","parecchio","parte","partendo","peccato","peggio","per","perche","perchè","perché","percio","perciò","perfino","pero","persino","persone","però","piedi","pieno","piglia","piu","piuttosto","più","po","pochissimo","poco","poi","poiche","possa","possedere","posteriore","posto","potrebbe","preferibilmente","presa","press","prima","primo","principalmente","probabilmente","promesso","proprio","puo","pure","purtroppo","può","qua","qualche","qualcosa","qualcuna","qualcuno","quale","quali","qualunque","quando","quanta","quante","quanti","quanto","quantunque","quarto","quasi","quattro","quel","quella","quelle","quelli","quello","quest","questa","queste","questi","questo","qui","quindi","quinto","realmente","recente","recentemente","registrazione","relativo","riecco","rispetto","salvo","sara","sarai","saranno","sarebbe","sarebbero","sarei","saremmo","saremo","sareste","saresti","sarete","sarà","sarò","scola","scopo","scorso","se","secondo","seguente","seguito","sei","sembra","sembrare","sembrato","sembrava","sembri","sempre","senza","sette","si","sia","siamo","siano","siate","siete","sig","solito","solo","soltanto","sono","sopra","soprattutto","sotto","spesso","sta","stai","stando","stanno","starai","staranno","starebbe","starebbero","starei","staremmo","staremo","stareste","staresti","starete","starà","starò","stata","state","stati","stato","stava","stavamo","stavano","stavate","stavi","stavo","stemmo","stessa","stesse","stessero","stessi","stessimo","stesso","steste","stesti","stette","stettero","stetti","stia","stiamo","stiano","stiate","sto","su","sua","subito","successivamente","successivo","sue","sugl","sugli","sui","sul","sull","sulla","sulle","sullo","suo","suoi","tale","tali","talvolta","tanto","te","tempo","terz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elif language == 'el': # stop_words = 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# perform the analysis no_features = 1000 no_top_words = 3 no_topics = 3 if mode == 'nmf': # tfidf vectorizer and nmf vectorizer = TfidfVectorizer(max_df=0.95, min_df=2, max_features=no_features, stop_words=stop_words) tfidf = vectorizer.fit_transform(corpus) feature_names = vectorizer.get_feature_names() model = NMF(n_components=no_topics, random_state=1, alpha=.1, l1_ratio=.5, init='nndsvd').fit(tfidf) elif mode == 'lda': # count vectorizer and LDA vectorizer = CountVectorizer(max_df=0.95, min_df=2, max_features=no_features, stop_words=stop_words) tf = vectorizer.fit_transform(corpus) feature_names = vectorizer.get_feature_names() model = LatentDirichletAllocation(n_components=no_topics, max_iter=5, learning_method='online', learning_offset=50., random_state=0).fit(tf) else: print('\tplease select a valid option for mode (\"tfidf-nmf\" or \"tf-lda\")') return None, None # display common words if plot: vectorizer = CountVectorizer(max_df=0.95, min_df=2, max_features=no_features, stop_words=stop_words) tf = vectorizer.fit_transform(corpus) bigram_vectorizer = CountVectorizer(ngram_range=(2, 2), stop_words=stop_words) bigrams = bigram_vectorizer.fit_transform(corpus) trigram_vectorizer = CountVectorizer(ngram_range=(3, 3), stop_words=stop_words) trigrams = trigram_vectorizer.fit_transform(corpus) n_top = 10 plot_common_words(tf, vectorizer,n_top,'words') plot_common_words(bigrams, bigram_vectorizer, n_top, 'bigrams') plot_common_words(trigrams, trigram_vectorizer, n_top, 'trigrams') # print topics for topic_idx, topic in enumerate(model.components_): # print("\ttopic %d:" % (topic_idx+1), ', '.join([tfidf_feature_names[i] for i in topic.argsort()[:-no_top_words - 1:-1]])) results_txt = results_txt + '(' for i in topic.argsort()[:-no_top_words - 1:-1]: # results.append(tfidf_feature_names[i]) results_txt = results_txt + feature_names[i] + ', ' results_txt = results_txt[:-2] + '), ' results_txt = results_txt[:-2] print('\ttopics detected via {}: {}'.format(mode, results_txt)) return results, results_txt # ****************************************************************************************** # a method for topic modeling along with named entity detection. common entities are # returned. 'mode' can be set to 'nmf' or 'lda'. def entity_modeling(corpus, mode='nmf'): # detect language language = detect_language(corpus[0]) print('* entity modeling') # initialize results results = [] results_txt = '' # remove unwanted words if language == 'en': # stop_words = 'english' elif language == 'es': # stop_words = ["0","1","2","3","4","5","6","7","8","9","_","a","actualmente","acuerdo","adelante","ademas","además","adrede","afirmó","agregó","ahi","ahora","ahí","al","algo","alguna","algunas","alguno","algunos","algún","alli","allí","alrededor","ambos","ampleamos","antano","antaño","ante","anterior","antes","apenas","aproximadamente","aquel","aquella","aquellas","aquello","aquellos","aqui","aquél","aquélla","aquéllas","aquéllos","aquí","arriba","arribaabajo","aseguró","asi","así","atras","aun","aunque","ayer","añadió","aún","b","bajo","bastante","bien","breve","buen","buena","buenas","bueno","buenos","c","cada","casi","cerca","cierta","ciertas","cierto","ciertos","cinco","claro","comentó","como","con","conmigo","conocer","conseguimos","conseguir","considera","consideró","consigo","consigue","consiguen","consigues","contigo","contra","cosas","creo","cual","cuales","cualquier","cuando","cuanta","cuantas","cuanto","cuantos","cuatro","cuenta","cuál","cuáles","cuándo","cuánta","cuántas","cuánto","cuántos","cómo","d","da","dado","dan","dar","de","debajo","debe","deben","debido","decir","dejó","del","delante","demasiado","demás","dentro","deprisa","desde","despacio","despues","después","detras","detrás","dia","dias","dice","dicen","dicho","dieron","diferente","diferentes","dijeron","dijo","dio","donde","dos","durante","día","días","dónde","e","ejemplo","el","ella","ellas","ello","ellos","embargo","empleais","emplean","emplear","empleas","empleo","en","encima","encuentra","enfrente","enseguida","entonces","entre","era","erais","eramos","eran","eras","eres","es","esa","esas","ese","eso","esos","esta","estaba","estabais","estaban","estabas","estad","estada","estadas","estado","estados","estais","estamos","estan","estando","estar","estaremos","estará","estarán","estarás","estaré","estaréis","estaría","estaríais","estaríamos","estarían","estarías","estas","este","estemos","esto","estos","estoy","estuve","estuviera","estuvierais","estuvieran","estuvieras","estuvieron","estuviese","estuvieseis","estuviesen","estuvieses","estuvimos","estuviste","estuvisteis","estuviéramos","estuviésemos","estuvo","está","estábamos","estáis","están","estás","esté","estéis","estén","estés","ex","excepto","existe","existen","explicó","expresó","f","fin","final","fue","fuera","fuerais","fueran","fueras","fueron","fuese","fueseis","fuesen","fueses","fui","fuimos","fuiste","fuisteis","fuéramos","fuésemos","g","general","gran","grandes","gueno","h","ha","haber","habia","habida","habidas","habido","habidos","habiendo","habla","hablan","habremos","habrá","habrán","habrás","habré","habréis","habría","habríais","habríamos","habrían","habrías","habéis","había","habíais","habíamos","habían","habías","hace","haceis","hacemos","hacen","hacer","hacerlo","haces","hacia","haciendo","hago","han","has","hasta","hay","haya","hayamos","hayan","hayas","hayáis","he","hecho","hemos","hicieron","hizo","horas","hoy","hube","hubiera","hubierais","hubieran","hubieras","hubieron","hubiese","hubieseis","hubiesen","hubieses","hubimos","hubiste","hubisteis","hubiéramos","hubiésemos","hubo","i","igual","incluso","indicó","informo","informó","intenta","intentais","intentamos","intentan","intentar","intentas","intento","ir","j","junto","k","l","la","lado","largo","las","le","lejos","les","llegó","lleva","llevar","lo","los","luego","lugar","m","mal","manera","manifestó","mas","mayor","me","mediante","medio","mejor","mencionó","menos","menudo","mi","mia","mias","mientras","mio","mios","mis","misma","mismas","mismo","mismos","modo","momento","mucha","muchas","mucho","muchos","muy","más","mí","mía","mías","mío","míos","n","nada","nadie","ni","ninguna","ningunas","ninguno","ningunos","ningún","no","nos","nosotras","nosotros","nuestra","nuestras","nuestro","nuestros","nueva","nuevas","nuevo","nuevos","nunca","o","ocho","os","otra","otras","otro","otros","p","pais","para","parece","parte","partir","pasada","pasado","paìs","peor","pero","pesar","poca","pocas","poco","pocos","podeis","podemos","poder","podria","podriais","podriamos","podrian","podrias","podrá","podrán","podría","podrían","poner","por","por 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elif language == 'it': # stop_words = ["a","abbastanza","abbia","abbiamo","abbiano","abbiate","accidenti","ad","adesso","affinché","agl","agli","ahime","ahimè","ai","al","alcuna","alcuni","alcuno","all","alla","alle","allo","allora","altre","altri","altrimenti","altro","altrove","altrui","anche","ancora","anni","anno","ansa","anticipo","assai","attesa","attraverso","avanti","avemmo","avendo","avente","aver","avere","averlo","avesse","avessero","avessi","avessimo","aveste","avesti","avete","aveva","avevamo","avevano","avevate","avevi","avevo","avrai","avranno","avrebbe","avrebbero","avrei","avremmo","avremo","avreste","avresti","avrete","avrà","avrò","avuta","avute","avuti","avuto","basta","ben","bene","benissimo","brava","bravo","buono","c","caso","cento","certa","certe","certi","certo","che","chi","chicchessia","chiunque","ci","ciascuna","ciascuno","cima","cinque","cio","cioe","cioè","circa","citta","città","ciò","co","codesta","codesti","codesto","cogli","coi","col","colei","coll","coloro","colui","come","cominci","comprare","comunque","con","concernente","conclusione","consecutivi","consecutivo","consiglio","contro","cortesia","cos","cosa","cosi","così","cui","d","da","dagl","dagli","dai","dal","dall","dalla","dalle","dallo","dappertutto","davanti","degl","degli","dei","del","dell","della","delle","dello","dentro","detto","deve","devo","di","dice","dietro","dire","dirimpetto","diventa","diventare","diventato","dopo","doppio","dov","dove","dovra","dovrà","dovunque","due","dunque","durante","e","ebbe","ebbero","ebbi","ecc","ecco","ed","effettivamente","egli","ella","entrambi","eppure","era","erano","eravamo","eravate","eri","ero","esempio","esse","essendo","esser","essere","essi","ex","fa","faccia","facciamo","facciano","facciate","faccio","facemmo","facendo","facesse","facessero","facessi","facessimo","faceste","facesti","faceva","facevamo","facevano","facevate","facevi","facevo","fai","fanno","farai","faranno","fare","farebbe","farebbero","farei","faremmo","faremo","fareste","faresti","farete","farà","farò","fatto","favore","fece","fecero","feci","fin","finalmente","finche","fine","fino","forse","forza","fosse","fossero","fossi","fossimo","foste","fosti","fra","frattempo","fu","fui","fummo","fuori","furono","futuro","generale","gente","gia","giacche","giorni","giorno","giu","già","gli","gliela","gliele","glieli","glielo","gliene","grande","grazie","gruppo","ha","haha","hai","hanno","ho","i","ie","ieri","il","improvviso","in","inc","indietro","infatti","inoltre","insieme","intanto","intorno","invece","io","l","la","lasciato","lato","le","lei","li","lo","lontano","loro","lui","lungo","luogo","là","ma","macche","magari","maggior","mai","male","malgrado","malissimo","me","medesimo","mediante","meglio","meno","mentre","mesi","mezzo","mi","mia","mie","miei","mila","miliardi","milioni","minimi","mio","modo","molta","molti","moltissimo","molto","momento","mondo","ne","negl","negli","nei","nel","nell","nella","nelle","nello","nemmeno","neppure","nessun","nessuna","nessuno","niente","no","noi","nome","non","nondimeno","nonostante","nonsia","nostra","nostre","nostri","nostro","novanta","nove","nulla","nuovi","nuovo","o","od","oggi","ogni","ognuna","ognuno","oltre","oppure","ora","ore","osi","ossia","ottanta","otto","paese","parecchi","parecchie","parecchio","parte","partendo","peccato","peggio","per","perche","perchè","perché","percio","perciò","perfino","pero","persino","persone","però","piedi","pieno","piglia","piu","piuttosto","più","po","pochissimo","poco","poi","poiche","possa","possedere","posteriore","posto","potrebbe","preferibilmente","presa","press","prima","primo","principalmente","probabilmente","promesso","proprio","puo","pure","purtroppo","può","qua","qualche","qualcosa","qualcuna","qualcuno","quale","quali","qualunque","quando","quanta","quante","quanti","quanto","quantunque","quarto","quasi","quattro","quel","quella","quelle","quelli","quello","quest","questa","queste","questi","questo","qui","quindi","quinto","realmente","recente","recentemente","registrazione","relativo","riecco","rispetto","salvo","sara","sarai","saranno","sarebbe","sarebbero","sarei","saremmo","saremo","sareste","saresti","sarete","sarà","sarò","scola","scopo","scorso","se","secondo","seguente","seguito","sei","sembra","sembrare","sembrato","sembrava","sembri","sempre","senza","sette","si","sia","siamo","siano","siate","siete","sig","solito","solo","soltanto","sono","sopra","soprattutto","sotto","spesso","sta","stai","stando","stanno","starai","staranno","starebbe","starebbero","starei","staremmo","staremo","stareste","staresti","starete","starà","starò","stata","state","stati","stato","stava","stavamo","stavano","stavate","stavi","stavo","stemmo","stessa","stesse","stessero","stessi","stessimo","stesso","steste","stesti","stette","stettero","stetti","stia","stiamo","stiano","stiate","sto","su","sua","subito","successivamente","successivo","sue","sugl","sugli","sui","sul","sull","sulla","sulle","sullo","suo","suoi","tale","tali","talvolta","tanto","te","tempo","terz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elif language == 'el': # stop_words = ["ένα","έναν","ένας","αι","ακομα","ακομη","ακριβως","αληθεια","αληθινα","αλλα","αλλαχου","αλλες","αλλη","αλλην","αλλης","αλλιως","αλλιωτικα","αλλο","αλλοι","αλλοιως","αλλοιωτικα","αλλον","αλλος","αλλοτε","αλλου","αλλους","αλλων","αμα","αμεσα","αμεσως","αν","ανα","αναμεσα","αναμεταξυ","ανευ","αντι","αντιπερα","αντις","ανω","ανωτερω","αξαφνα","απ","απεναντι","απο","αποψε","από","αρα","αραγε","αργα","αργοτερο","αριστερα","αρκετα","αρχικα","ας","αυριο","αυτα","αυτες","αυτεσ","αυτη","αυτην","αυτης","αυτο","αυτοι","αυτον","αυτος","αυτοσ","αυτου","αυτους","αυτουσ","αυτων","αφοτου","αφου","αἱ","αἳ","αἵ","αὐτόσ","αὐτὸς","αὖ","α∆ιακοπα","βεβαια","βεβαιοτατα","γάρ","γα","γα^","γε","γι","για","γοῦν","γρηγορα","γυρω","γὰρ","δ'","δέ","δή","δαί","δαίσ","δαὶ","δαὶς","δε","δεν","δι","δι'","διά","δια","διὰ","δὲ","δὴ","δ’","εαν","εαυτο","εαυτον","εαυτου","εαυτους","εαυτων","εγκαιρα","εγκαιρως","εγω","ειθε","ειμαι","ειμαστε","ειναι","εις","εισαι","εισαστε","ειστε","ειτε","ειχα","ειχαμε","ειχαν","ειχατε","ειχε","ειχες","ει∆εμη","εκ","εκαστα","εκαστες","εκαστη","εκαστην","εκαστης","εκαστο","εκαστοι","εκαστον","εκαστος","εκαστου","εκαστους","εκαστων","εκει","εκεινα","εκεινες","εκεινεσ","εκεινη","εκεινην","εκεινης","εκεινο","εκεινοι","εκεινον","εκεινος","εκεινοσ","εκεινου","εκεινους","εκεινουσ","εκεινων","εκτος","εμας","εμεις","εμενα","εμπρος","εν","ενα","εναν","ενας","ενος","εντελως","εντος","εντωμεταξυ","ενω","ενός","εξ","εξαφνα","εξης","εξισου","εξω","επ","επί","επανω","επειτα","επει∆η","επι","επισης","επομενως","εσας","εσεις","εσενα","εστω","εσυ","ετερα","ετεραι","ετερας","ετερες","ετερη","ετερης","ετερο","ετεροι","ετερον","ετερος","ετερου","ετερους","ετερων","ετουτα","ετουτες","ετουτη","ετουτην","ετουτης","ετουτο","ετουτοι","ετουτον","ετουτος","ετουτου","ετουτους","ετουτων","ετσι","ευγε","ευθυς","ευτυχως","εφεξης","εχει","εχεις","εχετε","εχθες","εχομε","εχουμε","εχουν","εχτες","εχω","εως","εἰ","εἰμί","εἰμὶ","εἰς","εἰσ","εἴ","εἴμι","εἴτε","ε∆ω","η","ημασταν","ημαστε","ημουν","ησασταν","ησαστε","ησουν","ηταν","ητανε","ητοι","ηττον","η∆η","θα","ι","ιι","ιιι","ισαμε","ισια","ισως","ισωσ","ι∆ια","ι∆ιαν","ι∆ιας","ι∆ιες","ι∆ιο","ι∆ιοι","ι∆ιον","ι∆ιος","ι∆ιου","ι∆ιους","ι∆ιων","ι∆ιως","κ","καί","καίτοι","καθ","καθε","καθεμια","καθεμιας","καθενα","καθενας","καθενος","καθετι","καθολου","καθως","και","κακα","κακως","καλα","καλως","καμια","καμιαν","καμιας","καμποσα","καμποσες","καμποση","καμποσην","καμποσης","καμποσο","καμποσοι","καμποσον","καμποσος","καμποσου","καμποσους","καμποσων","κανεις","κανεν","κανενα","κανεναν","κανενας","κανενος","καποια","καποιαν","καποιας","καποιες","καποιο","καποιοι","καποιον","καποιος","καποιου","καποιους","καποιων","καποτε","καπου","καπως","κατ","κατά","κατα","κατι","κατιτι","κατοπιν","κατω","κατὰ","καὶ","κι","κιολας","κλπ","κοντα","κτλ","κυριως","κἀν","κἂν","λιγακι","λιγο","λιγωτερο","λογω","λοιπα","λοιπον","μέν","μέσα","μή","μήτε","μία","μα","μαζι","μακαρι","μακρυα","μαλιστα","μαλλον","μας","με","μεθ","μεθαυριο","μειον","μελει","μελλεται","μεμιας","μεν","μερικα","μερικες","μερικοι","μερικους","μερικων","μεσα","μετ","μετά","μετα","μεταξυ","μετὰ","μεχρι","μη","μην","μηπως","μητε","μη∆ε","μιά","μια","μιαν","μιας","μολις","μολονοτι","μοναχα","μονες","μονη","μονην","μονης","μονο","μονοι","μονομιας","μονος","μονου","μονους","μονων","μου","μπορει","μπορουν","μπραβο","μπρος","μἐν","μὲν","μὴ","μὴν","να","ναι","νωρις","ξανα","ξαφνικα","ο","οι","ολα","ολες","ολη","ολην","ολης","ολο","ολογυρα","ολοι","ολον","ολονεν","ολος","ολοτελα","ολου","ολους","ολων","ολως","ολως∆ιολου","ομως","ομωσ","οποια","οποιαν","οποιαν∆ηποτε","οποιας","οποιας∆ηποτε","οποια∆ηποτε","οποιες","οποιες∆ηποτε","οποιο","οποιοι","οποιον","οποιον∆ηποτε","οποιος","οποιος∆ηποτε","οποιου","οποιους","οποιους∆ηποτε","οποιου∆ηποτε","οποιο∆ηποτε","οποιων","οποιων∆ηποτε","οποι∆ηποτε","οποτε","οποτε∆ηποτε","οπου","οπου∆ηποτε","οπως","οπωσ","ορισμενα","ορισμενες","ορισμενων","ορισμενως","οσα","οσα∆ηποτε","οσες","οσες∆ηποτε","οση","οσην","οσην∆ηποτε","οσης","οσης∆ηποτε","οση∆ηποτε","οσο","οσοι","οσοι∆ηποτε","οσον","οσον∆ηποτε","οσος","οσος∆ηποτε","οσου","οσους","οσους∆ηποτε","οσου∆ηποτε","οσο∆ηποτε","οσων","οσων∆ηποτε","οταν","οτι","οτι∆ηποτε","οτου","ου","ουτε","ου∆ε","οχι","οἱ","οἳ","οἷς","οὐ","οὐδ","οὐδέ","οὐδείσ","οὐδεὶς","οὐδὲ","οὐδὲν","οὐκ","οὐχ","οὐχὶ","οὓς","οὔτε","οὕτω","οὕτως","οὕτωσ","οὖν","οὗ","οὗτος","οὗτοσ","παλι","παντοτε","παντου","παντως","παρ","παρά","παρα","παρὰ","περί","περα","περι","περιπου","περισσοτερο","περσι","περυσι","περὶ","πια","πιθανον","πιο","πισω","πλαι","πλεον","πλην","ποια","ποιαν","ποιας","ποιες","ποιεσ","ποιο","ποιοι","ποιον","ποιος","ποιοσ","ποιου","ποιους","ποιουσ","ποιων","πολυ","ποσες","ποση","ποσην","ποσης","ποσοι","ποσος","ποσους","ποτε","που","πουθε","πουθενα","ποῦ","πρεπει","πριν","προ","προκειμενου","προκειται","προπερσι","προς","προσ","προτου","προχθες","προχτες","πρωτυτερα","πρόσ","πρὸ","πρὸς","πως","πωσ","σαν","σας","σε","σεις","σημερα","σιγα","σου","στα","στη","στην","στης","στις","στο","στον","στου","στους","στων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# perform the analysis no_features = 1000 no_topics = 5 no_top_words = 10 if mode == 'nmf': tfidf_vectorizer = TfidfVectorizer(max_df=0.95, min_df=2, max_features=no_features, stop_words=stop_words) tfidf = tfidf_vectorizer.fit_transform(corpus) feature_names = tfidf_vectorizer.get_feature_names() model = NMF(n_components=no_topics, random_state=1, alpha=.1, l1_ratio=.5, init='nndsvd').fit(tfidf) elif mode == 'lda': tf_vectorizer = CountVectorizer(max_df=0.95, min_df=2, max_features=no_features, stop_words=stop_words) tf = tf_vectorizer.fit_transform(corpus) feature_names = tf_vectorizer.get_feature_names() model = LatentDirichletAllocation(n_components=no_topics, max_iter=5, learning_method='online', learning_offset=50., random_state=0).fit(tf) else: print('\tplease select a valid option for mode (\"tfidf-nmf\" or \"tf-lda\")') return None, None # form the intermediate results for topic_idx, topic in enumerate(model.components_): # print("\ttopic %d:" % (topic_idx+1), ', '.join([feature_names[i] for i in topic.argsort()[:-no_top_words - 1:-1]])) for i in topic.argsort()[:-no_top_words - 1:-1]: # results.append(feature_names[i]) results_txt = results_txt + ' ' + feature_names[i] # print(results_txt) # load the appropriate spacy model and isolate terms named entity gpe, loc, fac, org if language == 'en': nlp = spacy.load('en_core_web_sm') elif language in ['el', 'es', 'it']: nlp = spacy.load(language + '_core_news_sm') else: return for ent in nlp(results_txt).ents: # if ent.label_ in ['GPE', 'FAC', 'ORG', 'LOC']: results.append(ent.text) # reform results results_txt = '' for result in results: results_txt = results_txt + result + ', ' results_txt = results_txt[:-2] print('\tcommon entities found:', results_txt) return results, results_txt ''' HELPER METHODS ''' # ****************************************************************************************** # a helper method for topic modeling methods to list the detected topics. def print_topics(model, feature_names, no_top_words): for topic_idx, topic in enumerate(model.components_): print("Topic %d:" % (topic_idx)) print(" ".join([feature_names[i] for i in topic.argsort()[:-no_top_words - 1:-1]])) # ****************************************************************************************** # a helper method for topic modeling methods to plot most common words. def plot_common_words(count_data, count_vectorizer,n_top, n_grams_string): sns.set_style('whitegrid') words = count_vectorizer.get_feature_names() total_counts = np.zeros(len(words)) for t in count_data: total_counts += t.toarray()[0] count_dict = (zip(words, total_counts)) count_dict = sorted(count_dict, key=lambda x: x[1], reverse=True)[0:n_top] words = [w[0] for w in count_dict] counts = [w[1] for w in count_dict] x_pos = np.arange(len(words)) plt.figure(2, figsize=(15, 15 / 1.6180)) plt.subplot(title=str(n_top)+' most common '+n_grams_string) sns.set_context("notebook", font_scale=1.25, rc={"lines.linewidth": 2.5}) sns.barplot(x_pos, counts, palette='husl') plt.xticks(x_pos, words, rotation=90) plt.xlabel('words') plt.ylabel('counts') plt.show() # Initialise the count vectorizer with the English stop words ''' SUPPLEMENTARY METHODS ''' # ****************************************************************************************** # a method primarily for testing various workflows and techniques. it is mostly based on the # spacy library for executiong common nlp tasks. def analyze_syntax(text): print('Syntax analysis') print(' ') word = TextBlob(text) lang = word.detect_language() print('The language is:', lang) if lang == 'el': nlp = spacy.load('el_core_news_sm') elif lang == 'es': nlp = spacy.load('es_core_news_sm') elif lang == 'it': nlp = spacy.load('it_core_news_sm') else: nlp = spacy.load('en_core_web_sm') nlp_text = nlp(text) # Extract sentences sentences = list(nlp_text.sents) print(' ') print('Sentences:', len(sentences)) for sentence in sentences: # print('#', sentence) # Extract tokens print(' ') print('Tokens:', len(nlp_text)) print('Lemma | Root | POS | Position | Shape | Alphabetic? | Stop? ') for token in nlp_text: print('#', token.text, token.lemma_, token.pos_, token.dep_, token.shape_, token.is_alpha, token.is_stop) # spacy.explain(token.tag_)token.tag_ # Noun chunks print(' ') print('Noun chunks analysis') print('Chunk | Root | POS | Head ') for chunk in nlp_text.noun_chunks: print('#', chunk.text, ' | ', chunk.root.text, ' | ', chunk.root.dep_, ' | ', chunk.root.head.text) print(' ') print(' ')

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#!/home/ubuntu/yonggari/bin/python2 # -*- coding: utf-8 -*- import re import sys from flask.cli import main if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit(main())

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import sys sys.stdin = open("5648_input.txt") # 상하좌우 dr = (-1, 1, 0, 0) dc = (0, 0, -1, 1) def bfs(): global Q result = 0 while Q: info = dict() qlen = len(Q) for _ in range(qlen): r, c, d, k = Q.pop(0) nr = r + dr[d] * 0.5 nc = c + dc[d] * 0.5 # 격자 밖으로 나가면 더이상 충돌할 수 없기 때문에 그냥 두기 if not (0 <= nr < 2001 and 0 <= nc < 2001): continue if (nr, nc) not in info.keys(): # 첫 방문인 경우 info[(nr, nc)] = [d, k] else: # 이미 어떤 원자가 간 곳이면 info[(nr, nc)][0] = -1 info[(nr, nc)][1] += k for (r, c), (d, k) in info.items(): if d == -1: # 처음 도착해 충돌된 원자 소멸 처리 result += k else: Q.append((r, c, d, k)) return result T = int(input()) for tc in range(T): N = int(input()) Q = [] for i in range(N): c, r, d, k = map(int, input().split()) # 격자를 수학적으로 일반적인 이차원 배열에 놓인 위치로 계산 r = 2000 - (1000 + r) c = (1000 + c) Q.append((r, c, d, k)) print("#{} {}".format(tc + 1, bfs()))

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from django.conf import settings from urlparse import urljoin import requests from requests.exceptions import RequestException import logging endpoint = settings.SPIN_DOCKER_ENDPOINT auth = (settings.SPIN_DOCKER_USERNAME, settings.SPIN_DOCKER_PASSWORD) logger = logging.getLogger(__name__) def make_request(method, resource, data=None): url = urljoin(endpoint, resource) try: if method == 'GET': r = requests.get(url, auth=auth, ) elif method == 'POST': r = requests.post(url, auth=auth, data=data) elif method == 'PATCH': r = requests.patch(url, auth=auth, data=data) elif method == 'DELETE': r = requests.delete(url, auth=auth) except RequestException: logger.error('Spin-docker error at resource: %s' % resource) return None try: response = r.json() except ValueError: logger.error('Spin-docker returned invalid JSON: %s %s %s' % (resource, r.status_code, r.text)) return None return response def get(resource): return make_request('GET', resource) def post(resource, data): return make_request('POST', resource, data) def patch(resource, data): return make_request('PATCH', resource, data) def delete(resource): return make_request('DELETE', resource)

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INVALID_OCTET = [ "f", # Too few digits "fff", # Too many digits "g" # Invalid digit ] OCTET = [ ("A0", "a0", 160, "10100000", "00000101"), ("a0", "a0", 160, "10100000", "00000101"), ("B1", "b1", 177, "10110001", "10001101"), ("b1", "b1", 177, "10110001", "10001101"), ("C2", "c2", 194, "11000010", "01000011"), ("c2", "c2", 194, "11000010", "01000011"), ("D3", "d3", 211, "11010011", "11001011"), ("d3", "d3", 211, "11010011", "11001011"), ("E4", "e4", 228, "11100100", "00100111"), ("e4", "e4", 228, "11100100", "00100111"), ("F5", "f5", 245, "11110101", "10101111"), ("f5", "f5", 245, "11110101", "10101111") ] INVALID_IDENTIFIER = [ "0a", # Too few digits "0a1b2c3d4e5f6", # Too many digits "0a1b2c3d4e5g", # Invalid digit "-0a-1b-2c-3d-4e-5f", # Leading hyphen "0a-1b-2c-3d-4e-5f-", # Trailing hyphen "0a-1b-2c-3d-4e5f", # Missing hyphen ":0a:1b:2c:3d:4e:5f", # Leading colon "0a:1b:2c:3d:4e:5f:", # Trailing colon "0a:1b:2c:3d:4e5f", # Missing colon ".0a1b.2c3d.4e5f", # Leading dot "0a1b.2c3d.4e5f.", # Trailing dot "0a1b.2c3d4e5f" # Missing dot ] EUI = [ ( "a0b1c2d3e4f5", # Plain notation (lowercase) "a0b1c2d3e4f5", 176685338322165, "101000001011000111000010110100111110010011110101", "000001011000110101000011110010110010011110101111", ("a0b1c2", "d3e4f5"), ("a0b1c2d3e", "4f5"), "a0b1c2d3e4f5", "a0-b1-c2-d3-e4-f5", "a0:b1:c2:d3:e4:f5", "a0b1.c2d3.e4f5" ), ( "A0B1C2D3E4F5", # Plain notation (uppercase) "a0b1c2d3e4f5", 176685338322165, "101000001011000111000010110100111110010011110101", "000001011000110101000011110010110010011110101111", ("a0b1c2", "d3e4f5"), ("a0b1c2d3e", "4f5"), "a0b1c2d3e4f5", "a0-b1-c2-d3-e4-f5", "a0:b1:c2:d3:e4:f5", "a0b1.c2d3.e4f5" ), ( "a0-b1-c2-d3-e4-f5", # Hyphen notation (lowercase) "a0b1c2d3e4f5", 176685338322165, "101000001011000111000010110100111110010011110101", "000001011000110101000011110010110010011110101111", ("a0b1c2", "d3e4f5"), ("a0b1c2d3e", "4f5"), "a0b1c2d3e4f5", "a0-b1-c2-d3-e4-f5", "a0:b1:c2:d3:e4:f5", "a0b1.c2d3.e4f5" ), ( "A0-B1-C2-D3-E4-F5", # Hyphen notation (uppercase) "a0b1c2d3e4f5", 176685338322165, "101000001011000111000010110100111110010011110101", "000001011000110101000011110010110010011110101111", ("a0b1c2", "d3e4f5"), ("a0b1c2d3e", "4f5"), "a0b1c2d3e4f5", "a0-b1-c2-d3-e4-f5", "a0:b1:c2:d3:e4:f5", "a0b1.c2d3.e4f5" ), ( "a0:b1:c2:d3:e4:f5", # Colon notation (lowercase) "a0b1c2d3e4f5", 176685338322165, "101000001011000111000010110100111110010011110101", "000001011000110101000011110010110010011110101111", ("a0b1c2", "d3e4f5"), ("a0b1c2d3e", "4f5"), "a0b1c2d3e4f5", "a0-b1-c2-d3-e4-f5", "a0:b1:c2:d3:e4:f5", "a0b1.c2d3.e4f5" ), ( "A0:B1:C2:D3:E4:F5", # Colon notation (uppercase) "a0b1c2d3e4f5", 176685338322165, "101000001011000111000010110100111110010011110101", "000001011000110101000011110010110010011110101111", ("a0b1c2", "d3e4f5"), ("a0b1c2d3e", "4f5"), "a0b1c2d3e4f5", "a0-b1-c2-d3-e4-f5", "a0:b1:c2:d3:e4:f5", "a0b1.c2d3.e4f5" ), ( "a0b1.c2d3.e4f5", # Dot notation (lowercase) "a0b1c2d3e4f5", 176685338322165, "101000001011000111000010110100111110010011110101", "000001011000110101000011110010110010011110101111", ("a0b1c2", "d3e4f5"), ("a0b1c2d3e", "4f5"), "a0b1c2d3e4f5", "a0-b1-c2-d3-e4-f5", "a0:b1:c2:d3:e4:f5", "a0b1.c2d3.e4f5" ), ( "A0B1.C2D3.E4F5", # Dot notation (uppercase) "a0b1c2d3e4f5", 176685338322165, "101000001011000111000010110100111110010011110101", "000001011000110101000011110010110010011110101111", ("a0b1c2", "d3e4f5"), ("a0b1c2d3e", "4f5"), "a0b1c2d3e4f5", "a0-b1-c2-d3-e4-f5", "a0:b1:c2:d3:e4:f5", "a0b1.c2d3.e4f5" ) ] ELI = [ ( "0a1b2c3d4e5f", # Plain notation (lowercase) "0a1b2c3d4e5f", 11111822610015, "000010100001101100101100001111010100111001011111", "010100001101100000110100101111000111001011111010", ("0a1b2c", "3d4e5f"), ("0a1b2c3d4", "e5f"), "0a1b2c3d4e5f", "0a-1b-2c-3d-4e-5f", "0a:1b:2c:3d:4e:5f", "0a1b.2c3d.4e5f" ), ( "0A1B2C3D4E5F", # Plain notation (uppercase) "0a1b2c3d4e5f", 11111822610015, "000010100001101100101100001111010100111001011111", "010100001101100000110100101111000111001011111010", ("0a1b2c", "3d4e5f"), ("0a1b2c3d4", "e5f"), "0a1b2c3d4e5f", "0a-1b-2c-3d-4e-5f", "0a:1b:2c:3d:4e:5f", "0a1b.2c3d.4e5f" ), ( "0a-1b-2c-3d-4e-5f", # Hyphen notation (lowercase) "0a1b2c3d4e5f", 11111822610015, "000010100001101100101100001111010100111001011111", "010100001101100000110100101111000111001011111010", ("0a1b2c", "3d4e5f"), ("0a1b2c3d4", "e5f"), "0a1b2c3d4e5f", "0a-1b-2c-3d-4e-5f", "0a:1b:2c:3d:4e:5f", "0a1b.2c3d.4e5f" ), ( "0A-1B-2C-3D-4E-5F", # Hyphen notation (uppercase) "0a1b2c3d4e5f", 11111822610015, "000010100001101100101100001111010100111001011111", "010100001101100000110100101111000111001011111010", ("0a1b2c", "3d4e5f"), ("0a1b2c3d4", "e5f"), "0a1b2c3d4e5f", "0a-1b-2c-3d-4e-5f", "0a:1b:2c:3d:4e:5f", "0a1b.2c3d.4e5f" ), ( "0a:1b:2c:3d:4e:5f", # Colon notation (lowercase) "0a1b2c3d4e5f", 11111822610015, "000010100001101100101100001111010100111001011111", "010100001101100000110100101111000111001011111010", ("0a1b2c", "3d4e5f"), ("0a1b2c3d4", "e5f"), "0a1b2c3d4e5f", "0a-1b-2c-3d-4e-5f", "0a:1b:2c:3d:4e:5f", "0a1b.2c3d.4e5f" ), ( "0A:1B:2C:3D:4E:5F", # Colon notation (uppercase) "0a1b2c3d4e5f", 11111822610015, "000010100001101100101100001111010100111001011111", "010100001101100000110100101111000111001011111010", ("0a1b2c", "3d4e5f"), ("0a1b2c3d4", "e5f"), "0a1b2c3d4e5f", "0a-1b-2c-3d-4e-5f", "0a:1b:2c:3d:4e:5f", "0a1b.2c3d.4e5f" ), ( "0a1b.2c3d.4e5f", # Dot notation (lowercase) "0a1b2c3d4e5f", 11111822610015, "000010100001101100101100001111010100111001011111", "010100001101100000110100101111000111001011111010", ("0a1b2c", "3d4e5f"), ("0a1b2c3d4", "e5f"), "0a1b2c3d4e5f", "0a-1b-2c-3d-4e-5f", "0a:1b:2c:3d:4e:5f", "0a1b.2c3d.4e5f" ), ( "0A1B.2C3D.4E5F", # Dot notation (uppercase) "0a1b2c3d4e5f", 11111822610015, "000010100001101100101100001111010100111001011111", "010100001101100000110100101111000111001011111010", ("0a1b2c", "3d4e5f"), ("0a1b2c3d4", "e5f"), "0a1b2c3d4e5f", "0a-1b-2c-3d-4e-5f", "0a:1b:2c:3d:4e:5f", "0a1b.2c3d.4e5f" ) ] NULL_EUI = [ ( "ffffffffffff", # Plain notation (lowercase) "ffffffffffff", 281474976710655, "111111111111111111111111111111111111111111111111", "111111111111111111111111111111111111111111111111", ("ffffff", "ffffff"), ("fffffffff", "fff"), "ffffffffffff", "ff-ff-ff-ff-ff-ff", "ff:ff:ff:ff:ff:ff", "ffff.ffff.ffff" ), ( "FFFFFFFFFFFF", # Plain notation (uppercase) "ffffffffffff", 281474976710655, "111111111111111111111111111111111111111111111111", "111111111111111111111111111111111111111111111111", ("ffffff", "ffffff"), ("fffffffff", "fff"), "ffffffffffff", "ff-ff-ff-ff-ff-ff", "ff:ff:ff:ff:ff:ff", "ffff.ffff.ffff" ), ( "ff-ff-ff-ff-ff-ff", # Hyphen notation (lowercase) "ffffffffffff", 281474976710655, "111111111111111111111111111111111111111111111111", "111111111111111111111111111111111111111111111111", ("ffffff", "ffffff"), ("fffffffff", "fff"), "ffffffffffff", "ff-ff-ff-ff-ff-ff", "ff:ff:ff:ff:ff:ff", "ffff.ffff.ffff" ), ( "FF-FF-FF-FF-FF-FF", # Hyphen notation (uppercase) "ffffffffffff", 281474976710655, "111111111111111111111111111111111111111111111111", "111111111111111111111111111111111111111111111111", ("ffffff", "ffffff"), ("fffffffff", "fff"), "ffffffffffff", "ff-ff-ff-ff-ff-ff", "ff:ff:ff:ff:ff:ff", "ffff.ffff.ffff" ), ( "ff:ff:ff:ff:ff:ff", # Colon notation (lowercase) "ffffffffffff", 281474976710655, "111111111111111111111111111111111111111111111111", "111111111111111111111111111111111111111111111111", ("ffffff", "ffffff"), ("fffffffff", "fff"), "ffffffffffff", "ff-ff-ff-ff-ff-ff", "ff:ff:ff:ff:ff:ff", "ffff.ffff.ffff" ), ( "FF:FF:FF:FF:FF:FF", # Colon notation (uppercase) "ffffffffffff", 281474976710655, "111111111111111111111111111111111111111111111111", "111111111111111111111111111111111111111111111111", ("ffffff", "ffffff"), ("fffffffff", "fff"), "ffffffffffff", "ff-ff-ff-ff-ff-ff", "ff:ff:ff:ff:ff:ff", "ffff.ffff.ffff" ), ( "ffff.ffff.ffff", # Dot notation (lowercase) "ffffffffffff", 281474976710655, "111111111111111111111111111111111111111111111111", "111111111111111111111111111111111111111111111111", ("ffffff", "ffffff"), ("fffffffff", "fff"), "ffffffffffff", "ff-ff-ff-ff-ff-ff", "ff:ff:ff:ff:ff:ff", "ffff.ffff.ffff" ), ( "FFFF.FFFF.FFFF", # Dot notation (uppercase) "ffffffffffff", 281474976710655, "111111111111111111111111111111111111111111111111", "111111111111111111111111111111111111111111111111", ("ffffff", "ffffff"), ("fffffffff", "fff"), "ffffffffffff", "ff-ff-ff-ff-ff-ff", "ff:ff:ff:ff:ff:ff", "ffff.ffff.ffff" ) ] INVALID_ADDRESS = INVALID_IDENTIFIER BROADCAST = "ffffffffffff" MULTICAST = "0180c2000000" # Link-Layer Discovery Protocol UAA_UNICAST = "a0b1c2d3e4f5" LAA_UNICAST = "aab1c2d3e4f5"

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# copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import sys import paddle from paddlespeech.s2t.utils.log import Log logger = Log(__name__).getlog() # A global variable to record the number of calling times for profiler # functions. It is used to specify the tracing range of training steps. _profiler_step_id = 0 # A global variable to avoid parsing from string every time. _profiler_options = None class ProfilerOptions(object): ''' Use a string to initialize a ProfilerOptions. The string should be in the format: "key1=value1;key2=value;key3=value3". For example: "profile_path=model.profile" "batch_range=[50, 60]; profile_path=model.profile" "batch_range=[50, 60]; tracer_option=OpDetail; profile_path=model.profile" ProfilerOptions supports following key-value pair: batch_range - a integer list, e.g. [100, 110]. state - a string, the optional values are 'CPU', 'GPU' or 'All'. sorted_key - a string, the optional values are 'calls', 'total', 'max', 'min' or 'ave. tracer_option - a string, the optional values are 'Default', 'OpDetail', 'AllOpDetail'. profile_path - a string, the path to save the serialized profile data, which can be used to generate a timeline. exit_on_finished - a boolean. ''' def __init__(self, options_str): assert isinstance(options_str, str) self._options = { 'batch_range': [10, 20], 'state': 'All', 'sorted_key': 'total', 'tracer_option': 'Default', 'profile_path': '/tmp/profile', 'exit_on_finished': True } self._parse_from_string(options_str) def _parse_from_string(self, options_str): if not options_str: return for kv in options_str.replace(' ', '').split(';'): key, value = kv.split('=') if key == 'batch_range': value_list = value.replace('[', '').replace(']', '').split(',') value_list = list(map(int, value_list)) if len(value_list) >= 2 and value_list[0] >= 0 and value_list[ 1] > value_list[0]: self._options[key] = value_list elif key == 'exit_on_finished': self._options[key] = value.lower() in ("yes", "true", "t", "1") elif key in [ 'state', 'sorted_key', 'tracer_option', 'profile_path' ]: self._options[key] = value def __getitem__(self, name): if self._options.get(name, None) is None: raise ValueError( "ProfilerOptions does not have an option named %s." % name) return self._options[name] def add_profiler_step(options_str=None): ''' Enable the operator-level timing using PaddlePaddle's profiler. The profiler uses a independent variable to count the profiler steps. One call of this function is treated as a profiler step. Args: profiler_options - a string to initialize the ProfilerOptions. Default is None, and the profiler is disabled. ''' if options_str is None: return global _profiler_step_id global _profiler_options if _profiler_options is None: _profiler_options = ProfilerOptions(options_str) logger.info(f"Profiler: {options_str}") logger.info(f"Profiler: {_profiler_options._options}") if _profiler_step_id == _profiler_options['batch_range'][0]: paddle.utils.profiler.start_profiler(_profiler_options['state'], _profiler_options['tracer_option']) elif _profiler_step_id == _profiler_options['batch_range'][1]: paddle.utils.profiler.stop_profiler(_profiler_options['sorted_key'], _profiler_options['profile_path']) if _profiler_options['exit_on_finished']: sys.exit(0) _profiler_step_id += 1

[ "zhtclz@foxmail.com" ]

zhtclz@foxmail.com

3ac1365a8800ed508c6f33e04084810988bc2508

b0948c315a879a6fd6ae5542ed4146e54ba4f0d2

/Some analytics/Analytics_diagram_all.py

d3a6a1b604bd360243b9207e06e065692e27586d

[]

no_license

Borys1307/Borys

8fe05ee757c54f19d4f5ef82cf1dbb92264dd5cf

5a29299717d695609d960473f8ba4d9576f6384d

refs/heads/master

2020-06-14T02:13:04.886772

2020-03-23T12:40:26

194,863,210

0

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Python

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py

import pandas as pd import matplotlib.pyplot as plt import numpy as np import json name = [] number = [] with open('C:/Users/chernyshov/Python/data.json', 'r') as fp: resp = json.load(fp) for i in resp['result']['StableDedicated']['Manual']['WhereReported'].items(): name.append(i[0]) number.append(i[1]) data = {'Tracker' : name, 'count':number } cold_lost = pd.DataFrame(data) total = (resp['result']['StableDedicated']['Manual']['Total']) print(total) cold_lost = (cold_lost.sort_values(by = ['count'], ascending = False)) cold_lost = cold_lost.reset_index(drop=True) cold_lost.index = np.arange(1,len(cold_lost)+1) percent = dict() for i in cold_lost['Tracker']: percent[i] = cold_lost.loc[cold_lost['Tracker'] == i].iloc[0]['count']/total*100 print(percent) diagram for all answer = pd.DataFrame(percent, index = [0]) dpi = 80 plt.figure(dpi = dpi, figsize = (640 / dpi, 480 / dpi) ) plt.pie(answer.values[0], autopct='%.2f', radius = 1.5, ); plt.legend( bbox_to_anchor = (-0.36, -0.17, 1.25, 0.25), loc = 'lower left', labels = answer.keys()) plt.savefig('C:/Users/chernyshov/Python/Plots/Percentage_to_total.png') plt.show() print(cold_lost)

[ "noreply@github.com" ]

Borys1307.noreply@github.com

818f9e6e2b44bf243ecb781eeedf33adb72cda9c

02ca588d6c8f5b4223071b80b27b98a0abd1f5ee

/woocommerce.py

ba1b1671e16ff162ec5a69e62cc67d1588f66d9c

[]

no_license

phamjmanh/v32

00528b8799a6381529b8778e470c68d6cc4a5f83

e550d8e6167413523197592385c8e4b9a146f22e

refs/heads/main

2023-02-11T11:05:50.175775

2021-01-04T07:01:35

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py

import copy import csv import re from collections import defaultdict from urllib.parse import unquote import chardet from cartmigration.libs.utils import * from cartmigration.models.cart.wordpress import LeCartWordpress # tested with woocommerce335 class LeCartWoocommerce(LeCartWordpress): WARNING_VARIANT_LIMIT = 100 def __init__(self, data = None): super().__init__(data) self.product_types = dict() self.is_variant_limit = False def display_config_source(self): parent = super().display_config_source() url_query = self.get_connector_url('query') self._notice['src']['language_default'] = 1 self._notice['src']['category_root'] = 1 storage_cat_data = dict() storage_cat_data[self._notice['src']['language_default']] = 0 self._notice['src']['store_category'] = storage_cat_data self._notice['src']['support']['site_map'] = False self._notice['src']['support']['category_map'] = False self._notice['src']['support']['attribute_map'] = False self._notice['src']['support']['wpml'] = False self._notice['src']['support']['yoast_seo'] = False self._notice['src']['support']['manufacturers'] = False self._notice['src']['support']['product_bundle'] = False self._notice['src']['support']['customer_point_rewards'] = False self._notice['src']['support']['addons'] = False self._notice['src']['support']['plugin_pre_ord'] = False self._notice['src']['support']['plugin_order_status'] = False self._notice['src']['support']['custom_order_status'] = False query_active_plugins = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_options WHERE option_name = 'active_plugins'" } active_plugins = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query_active_plugins)}) active_langs = list() if active_plugins and active_plugins['data']: active_plugin = active_plugins['data'][0] active_plugin_v = active_plugin['option_value'] if active_plugin_v: active_plugin_v_data = php_unserialize(active_plugin_v) if active_plugin_v_data and isinstance(active_plugin_v_data, dict): active_plugin_v_data = list(active_plugin_v_data.values()) if active_plugin_v_data: if "woocommerce-multilingual/wpml-woocommerce.php" in active_plugin_v_data: self._notice['src']['support']['wpml'] = True query_active_languages = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_options` WHERE `option_name` = 'icl_sitepress_settings'" } options_data = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query_active_languages)}) if options_data and options_data['data']: option_value = php_unserialize(options_data['data'][0]['option_value']) if option_value and 'default_language' in option_value: self._notice['src']['language_default'] = option_value['default_language'] active_langs = option_value['active_languages'].values() else: self._notice['src']['support']['wpml'] = False if 'woocommerce-brand/main.php' in active_plugin_v_data or "wc-brand/woocommerce-brand.php" in active_plugin_v_data or 'woocommerce-brands/woocommerce-brands.php' in active_plugin_v_data or 'perfect-woocommerce-brands/perfect-woocommerce-brands.php' in active_plugin_v_data: self._notice['src']['support']['manufacturers'] = True if "wordpress-seo/wp-seo.php" in active_plugin_v_data: self._notice['src']['support']['yoast_seo'] = True if "woo-product-bundle-premium/index.php" in active_plugin_v_data or 'woo-product-bundle/index.php' in active_plugin_v_data: self._notice['src']['support']['product_bundle'] = True if "woocommerce-points-and-rewards/woocommerce-points-and-rewards.php" in active_plugin_v_data: self._notice['src']['support']['customer_point_rewards'] = True if "themedelights-addons/themedelights-addons.php" in active_plugin_v_data or "woocommerce-product-addons/woocommerce-product-addons.php" in active_plugin_v_data: self._notice['src']['support']['addons'] = True if active_plugin_v_data and (("woocommerce-sequential-order-numbers/woocommerce-sequential-order-numbers.php" in active_plugin_v_data) or ("custom-order-numbers-for-woocommerce/custom-order-numbers-for-woocommerce.php" in active_plugin_v_data) or ("sequential-order-numbers-for-woocommerce/sequential-order-numbers.php" in active_plugin_v_data) or ("woocommerce-sequential-order-numbers-pro/woocommerce-sequential-order-numbers-pro.php" in active_plugin_v_data) or ("woocommerce-sequential-order-numbers-pro/woocommerce-sequential-order-numbers.php" in active_plugin_v_data)): self._notice['src']['support']['plugin_pre_ord'] = True if active_plugin_v_data and 'woocommerce-order-status-manager/woocommerce-order-status-manager.php' in active_plugin_v_data: self._notice['src']['support']['plugin_order_status'] = True if active_plugin_v_data and 'woocommerce-status-actions/woocommerce-status-actions.php' in active_plugin_v_data: self._notice['src']['support']['custom_order_status'] = True queries_config = { 'orders_status': { 'type': 'select', # 'query': "SELECT * FROM `_DBPRF_term_taxonomy` AS term_taxonomy LEFT JOIN _DBPRF_terms AS terms ON term_taxonomy.term_id = terms.term_id WHERE term_taxonomy.taxonomy = 'shop_order_status'", 'query': "SELECT DISTINCT(`post_status`) FROM `_DBPRF_posts` WHERE `post_type` = 'shop_order'", }, 'permalink_structure': { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_options` WHERE option_name = 'woocommerce_permalinks' OR option_name = 'category_base'", } } if self._notice['src']['support']['wpml']: queries_config['wpml'] = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_icl_languages` WHERE code IN " + self.list_to_in_condition(active_langs) } queries_config['default_lang'] = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_options` o LEFT JOIN _DBPRF_icl_languages il ON o.option_value = il.default_locale WHERE o.`option_name` = 'WPLANG'" } if self._notice['src']['support']['plugin_order_status']: queries_config['orders_status']['query'] = "SELECT * FROM `_DBPRF_posts` WHERE `post_type` = 'wc_order_status'" if self._notice['src']['support']['custom_order_status']: queries_config['orders_status']['query'] = "SELECT * FROM `_DBPRF_posts` WHERE `post_type` = 'wc_custom_statuses' AND `post_status` = 'publish'" config = self.get_connector_data(url_query, { 'serialize': True, 'query': json.dumps(queries_config) }) language_data = dict() order_status_data = dict() product_base = 'product' product_category_base = 'product-category' category_base = '' if config and config['result'] == 'success': if config['data']['orders_status']: for order_status_row in config['data']['orders_status']: # order_status_id = 'wc-' + order_status_row['name'].lower() # order_status_data[order_status_id] = order_status_row['name'] if self._notice['src']['support']['custom_order_status']: order_status_id = 'wc-' + to_str(order_status_row['post_name']) order_status_data[order_status_id] = order_status_row['post_title'] elif self._notice['src']['support']['plugin_order_status']: order_status_id = order_status_row['post_name'] order_status_data[order_status_id] = order_status_row['post_title'] else: order_status_id = order_status_row['post_status'] order_status_data[order_status_id] = self.get_order_status_label(order_status_row['post_status']) else: order_status_data = { 'wc-pending': 'Pending payment', 'wc-processing': 'Processing', 'wc-on-hold': 'On hold', 'wc-completed': 'Completed', 'wc-cancelled': 'Cancelled', 'wc-refunded': 'Refunded', 'wc-failed': 'Failed' } if self._notice['src']['support']['wpml']: if not self._notice['src']['language_default'] and 'default_lang' in config['data'] and config['data'][ 'default_lang']: for lang_default_row in config['data']['default_lang']: if lang_default_row['code']: self._notice['src']['language_default'] = lang_default_row['code'] if 'wpml' in config['data']: if config['data']['wpml']: for lang_row in config['data']['wpml']: lang_id = lang_row["code"] language_data[lang_id] = lang_row['english_name'] else: lang_id = 'en' language_data[lang_id] = "Default language" else: lang_id = 1 language_data[lang_id] = "Default language" if config['data']['permalink_structure']: product_base_data = get_row_from_list_by_field(config['data']['permalink_structure'], 'option_name', 'woocommerce_permalinks') category_base_data = get_row_from_list_by_field(config['data']['permalink_structure'], 'option_name', 'category_base') if product_base_data: option_value_data = php_unserialize(product_base_data['option_value']) if option_value_data: product_base = get_value_by_key_in_dict(option_value_data, 'product_base', 'product') product_category_base = get_value_by_key_in_dict(option_value_data, 'category_base', 'product-category') if category_base_data: category_base = category_base_data['option_value'] self._notice['src']['config']['category_base'] = product_category_base self._notice['src']['config']['product_category_base'] = product_category_base self._notice['src']['config']['product_base'] = product_base self._notice['src']['support']['language_map'] = True self._notice['src']['languages'] = language_data self._notice['src']['order_status'] = order_status_data self._notice['src']['support']['order_status_map'] = True self._notice['src']['support']['country_map'] = False self._notice['src']['support']['add_new'] = True self._notice['src']['support']['site_map'] = False self._notice['src']['support']['customer_group_map'] = False self._notice['src']['support']['languages_select'] = True self._notice['src']['support']['order_state_map'] = True self._notice['src']['support']['seo'] = True if self.is_woo2woo(): self._notice['src']['support']['cus_pass'] = False else: self._notice['src']['support']['cus_pass'] = True self._notice['src']['support']['coupons'] = True self._notice['src']['support']['pages'] = True self._notice['src']['support']['seo_301'] = True self._notice['src']['config']['seo_module'] = self.get_list_seo() return response_success() def display_config_target(self): url_query = self.get_connector_url('query') self._notice['target']['language_default'] = 1 self._notice['target']['category_root'] = 1 storage_cat_data = dict() storage_cat_data[self._notice['target']['language_default']] = 0 self._notice['target']['store_category'] = storage_cat_data self._notice['target']['support']['site_map'] = False self._notice['target']['support']['category_map'] = False self._notice['target']['support']['attribute_map'] = False self._notice['target']['support']['wpml'] = False self._notice['target']['support']['wpml_currency'] = False self._notice['target']['support']['product_bundle'] = False self._notice['target']['support']['yoast_seo'] = False self._notice['target']['support']['addons'] = False self._notice['target']['support']['customer_point_rewards'] = False self._notice['target']['support']['polylang'] = False self._notice['target']['support']['polylang_product'] = False self._notice['target']['support']['polylang_category'] = False self._notice['target']['support']['plugin_woo_admin'] = False self._notice['target']['support']['custom_order_status'] = False self._notice['target']['currency_map'] = dict() query_active_plugins = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_options WHERE option_name = 'active_plugins'" } active_plugins = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query_active_plugins)}) active_langs = list() if active_plugins and active_plugins['data']: active_plugin = active_plugins['data'][0] active_plugin_v = active_plugin['option_value'] if active_plugin_v: active_plugin_v_data = php_unserialize(active_plugin_v) if active_plugin_v_data and isinstance(active_plugin_v_data, dict): active_plugin_v_data = list(active_plugin_v_data.values()) if active_plugin_v_data and "woocommerce-multilingual/wpml-woocommerce.php" in active_plugin_v_data: self._notice['target']['support']['wpml'] = True query_active_languages = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_options` WHERE `option_name` = 'icl_sitepress_settings'" } options_data = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query_active_languages)}) if options_data and options_data['data']: option_value = php_unserialize(options_data['data'][0]['option_value']) if option_value and 'default_language' in option_value: self._notice['target']['language_default'] = option_value['default_language'] active_langs = option_value['active_languages'].values() query_active_currency = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_options` WHERE `option_name` = '_wcml_settings'" } options_currency_data = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query_active_currency)}) if options_currency_data and options_currency_data['data']: currency_value = php_unserialize(options_currency_data['data'][0]['option_value']) if currency_value and 'enable_multi_currency' in currency_value and to_int(currency_value['enable_multi_currency']) >= 2: self._notice['target']['support']['wpml_currency'] = True if 'default_currencies' in currency_value and currency_value['default_currencies']: self._notice['target']['currency_map'] = currency_value['default_currencies'] else: self._notice['target']['support']['wpml_currency'] = False woo_brands = [ {'name': 'woocommerce-brand/main.php'}, {'name': 'wc-brand/woocommerce-brand.php'}, {'name': 'martfury-addons/martfury-addons.php', 'taxonomy': 'product_brand'}, {'name': 'woocommerce-brands/woocommerce-brands.php', 'taxonomy': 'product_brand'}, {'name': 'brands-for-woocommerce/woocommerce-brand.php', 'taxonomy': 'berocket_brand'}, {'name': 'perfect-woocommerce-brands/main.php', 'taxonomy': 'pwb-brand'}, {'name': 'perfect-woocommerce-brands/perfect-woocommerce-brands.php', 'taxonomy': 'pwb-brand'}, ] self._notice['target']['config']['brand_taxonomy'] = 'product_brand' for brand in woo_brands: if brand['name'] in active_plugin_v_data: self._notice['target']['support']['plugin_manufacturers'] = True if brand.get('taxonomy'): self._notice['target']['config']['brand_taxonomy'] = brand['taxonomy'] break # if ('woocommerce-brand/main.php' in active_plugin_v_data) or ("wc-brand/woocommerce-brand.php" in active_plugin_v_data) or ('woocommerce-brands/woocommerce-brands.php' in active_plugin_v_data) or ('brands-for-woocommerce/woocommerce-brand.php' in active_plugin_v_data): # self._notice['target']['support']['manufacturers'] = True if active_plugin_v_data and (("woocommerce-sequential-order-numbers/woocommerce-sequential-order-numbers.php" in active_plugin_v_data) or ("custom-order-numbers-for-woocommerce/custom-order-numbers-for-woocommerce.php" in active_plugin_v_data) or ("sequential-order-numbers-for-woocommerce/sequential-order-numbers.php" in active_plugin_v_data) or ("woocommerce-sequential-order-numbers-pro/woocommerce-sequential-order-numbers-pro.php" in active_plugin_v_data)): self._notice['target']['support']['plugin_pre_ord'] = True if active_plugin_v_data and "wordpress-seo/wp-seo.php" in active_plugin_v_data: self._notice['target']['support']['yoast_seo'] = True if "themedelights-addons/themedelights-addons.php" in active_plugin_v_data or "woocommerce-product-addons/woocommerce-product-addons.php" in active_plugin_v_data: self._notice['target']['support']['addons'] = True if "leurlrewrite/leurlrewrite.php" in active_plugin_v_data: self._notice['target']['support']['plugin_seo'] = True self._notice['target']['support']['plugin_seo_301'] = True if "leprespass/leprespass.php" in active_plugin_v_data: self._notice['target']['support']['plugin_cus_pass'] = True if "woocommerce-admin/woocommerce-admin.php" in active_plugin_v_data: self._notice['target']['support']['plugin_woo_admin'] = True # query_check_seo = { # 'type': 'select', # 'query': "SHOW TABLES LIKE '_DBPRF_lecm_rewrite';" # } # check_table_exit = self.select_data_connector(query_check_seo, 'seo') # if check_table_exit['result'] == 'success' and to_len(check_table_exit['data']) > 0: # self._notice['target']['support']['seo_301'] = True if "woo-product-bundle-premium/index.php" in active_plugin_v_data or 'woo-product-bundle/index.php' in active_plugin_v_data: self._notice['target']['support']['product_bundle'] = True if "woocommerce-points-and-rewards/woocommerce-points-and-rewards.php" in active_plugin_v_data: self._notice['target']['support']['customer_point_rewards'] = True # if 'polylang/polylang.php' in active_plugin_v_data and 'polylang-wc/polylang-wc.php' in active_plugin_v_data: if 'polylang/polylang.php' in active_plugin_v_data: self._notice['target']['support']['polylang'] = True if 'woocommerce-status-actions/woocommerce-status-actions.php' in active_plugin_v_data: self._notice['target']['support']['custom_order_status'] = True queries_config = { 'orders_status': { 'type': 'select', # 'query': "SELECT DISTINCT(`post_status`) FROM `_DBPRF_posts` WHERE `post_type` = 'shop_order'", 'query': "SELECT * FROM `_DBPRF_term_taxonomy` AS term_taxonomy LEFT JOIN _DBPRF_terms AS terms ON term_taxonomy.term_id = terms.term_id WHERE term_taxonomy.taxonomy = 'shop_order_status'", }, } if self._notice['target']['support']['wpml']: queries_config['wpml'] = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_icl_languages` WHERE code IN " + self.list_to_in_condition(active_langs) } queries_config['default_lang'] = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_options` o LEFT JOIN _DBPRF_icl_languages il ON o.option_value = il.default_locale WHERE o.`option_name` = 'WPLANG' and o.`option_value` != '' " } if self._notice['target']['support']['polylang']: queries_config['polylang'] = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_terms` as t LEFT JOIN `_DBPRF_term_taxonomy` as tx ON t.term_id = tx.term_id WHERE tx.taxonomy = 'language'" } queries_config['polylang_categories'] = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_terms` as t LEFT JOIN `_DBPRF_term_taxonomy` as tx ON t.term_id = tx.term_id WHERE tx.taxonomy = 'term_language'" } if self._notice['target']['support']['custom_order_status']: queries_config['custom_order_status'] = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_posts` WHERE `post_type` = 'wc_custom_statuses' AND `post_status` = 'publish'" } config = self.select_multiple_data_connector(queries_config) if 'polylang' in config['data'] and not config['data']['polylang']: self._notice['target']['support']['polylang'] = False language_data = dict() order_status_data = dict() polylang_products = dict() polylang_categories = dict() if config and config['result'] == 'success': if self._notice['target']['support']['custom_order_status'] and config['data']['custom_order_status'] and to_len(config['data']['custom_order_status']) > 0: for order_status_row in config['data']['custom_order_status']: order_status_id = 'wc-' + to_str(order_status_row['post_name']) order_status_data[order_status_id] = order_status_row['post_title'] elif config['data']['orders_status'] and to_len(config['data']['orders_status']) > 0: for order_status_row in config['data']['orders_status']: order_status_id = 'wc-' + to_str(order_status_row['name']).lower() order_status_data[order_status_id] = order_status_row['name'] # order_status_id = order_status_row['post_status'] # order_status_data[order_status_id] = self.get_order_status_label(order_status_row['post_status']) else: order_status_data = { 'wc-pending': 'Pending payment', 'wc-processing': 'Processing', 'wc-on-hold': 'On hold', 'wc-completed': 'Completed', 'wc-cancelled': 'Cancelled', 'wc-refunded': 'Refunded', 'wc-failed': 'Failed' } if self._notice['target']['support']['wpml']: if not self._notice['target']['language_default'] and 'default_lang' in config['data'] and config['data']['default_lang']: for lang_default_row in config['data']['default_lang']: if lang_default_row['code']: self._notice['target']['language_default'] = lang_default_row['code'] if 'wpml' in config['data']: if config['data']['wpml']: for lang_row in config['data']['wpml']: lang_id = lang_row["code"] language_data[lang_id] = lang_row['english_name'] else: lang_id = 'en' language_data[lang_id] = "Default language" elif self._notice['target']['support']['polylang']: if not self._notice['target']['language_default'] and 'default_lang' in config['data'] and config['data']['default_lang']: for lang_default_row in config['data']['default_lang']: if lang_default_row['code']: self._notice['target']['language_default'] = lang_default_row['code'] if 'polylang' in config['data']: if config['data']['polylang']: self._notice['target']['language_default'] = 'en' for lang_row in config['data']['polylang']: lang_id = lang_row['slug'] language_data[lang_id] = lang_row['name'] lang_product = lang_row['slug'] polylang_products[lang_product] = lang_row['term_taxonomy_id'] if config['data']['polylang_categories']: for lang_row in config['data']['polylang_categories']: lang_category = lang_row['slug'].replace('pll_', '') polylang_categories[lang_category] = lang_row['term_taxonomy_id'] else: lang_id = 'en' language_data[lang_id] = "Default language" else: lang_id = 1 language_data[lang_id] = "Default language" else: order_status_data = { 'wc-pending': 'Pending payment', 'wc-processing': 'Processing', 'wc-on-hold': 'On hold', 'wc-completed': 'Completed', 'wc-cancelled': 'Cancelled', 'wc-refunded': 'Refunded', 'wc-failed': 'Failed' } lang_id = 1 language_data[lang_id] = "Default language" self._notice['target']['support']['manufacturers'] = True self._notice['target']['support']['check_manufacturers'] = True # self._notice['target']['support']['yoast_seo'] = False self._notice['target']['support']['pre_ord'] = True self._notice['target']['support']['check_pre_ord'] = True self._notice['target']['support']['seo'] = True self._notice['target']['support']['check_seo'] = True self._notice['target']['support']['seo_301'] = True self._notice['target']['support']['check_seo_301'] = True self._notice['target']['support']['cus_pass'] = True self._notice['target']['support']['check_cus_pass'] = True self._notice['target']['support']['language_map'] = True self._notice['target']['languages'] = language_data self._notice['target']['order_status'] = order_status_data self._notice['target']['support']['order_status_map'] = True self._notice['target']['support']['country_map'] = False self._notice['target']['support']['add_new'] = True self._notice['target']['support']['coupons'] = True self._notice['target']['support']['blogs'] = True self._notice['target']['support']['pages'] = True self._notice['target']['support']['site_map'] = False self._notice['target']['support']['pre_prd'] = False self._notice['target']['support']['pre_cus'] = False self._notice['target']['support']['img_des'] = True self._notice['target']['support']['customer_group_map'] = False self._notice['target']['support']['languages_select'] = True self._notice['target']['support']['update_latest_data'] = True self._notice['target']['config']['entity_update']['products'] = True self._notice['target']['support']['polylang_product'] = polylang_products self._notice['target']['support']['polylang_category'] = polylang_categories return response_success() def get_query_display_import_source(self, update = False): compare_condition = ' > ' if update: compare_condition = ' <= ' prefix = self._notice['src']['config']['table_prefix'] if self._notice['src']['config'].get('site_id'): prefix = to_str(prefix).replace(to_str(self._notice['src']['config'].get('site_id')) + '_', '') queries = { 'taxes': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_options WHERE option_name = 'woocommerce_tax_classes'", }, 'manufacturers': { 'type': 'select', 'query': "SELECT COUNT(1) AS count FROM _DBPRF_term_taxonomy WHERE (taxonomy = 'product_brand' OR taxonomy = 'brand' OR taxonomy = 'pwb-brand') AND term_id " + compare_condition + to_str(self._notice['process']['manufacturers']['id_src']), }, 'categories': { 'type': 'select', 'query': "SELECT COUNT(1) AS count FROM _DBPRF_term_taxonomy WHERE taxonomy = 'product_cat' AND term_id " + compare_condition + to_str(self._notice['process']['categories']['id_src']), }, 'products': { 'type': 'select', 'query': "SELECT COUNT(1) AS count FROM _DBPRF_posts WHERE post_type = 'product' AND post_status NOT IN ('inherit','auto-draft') AND ID " + compare_condition + to_str( self._notice['process']['products']['id_src']), }, 'customers': { 'type': 'select', 'query': "SELECT COUNT(1) AS count FROM " + prefix + "users u LEFT JOIN " + prefix + "usermeta um ON u.ID = um.user_id WHERE (um.meta_key = '_DBPRF_capabilities' AND um.meta_value LIKE '%customer%' OR um.meta_value LIKE '%subscriber%') AND u.ID " + compare_condition + to_str( self._notice['process']['customers']['id_src']), }, 'orders': { 'type': 'select', 'query': "SELECT COUNT(1) AS count FROM _DBPRF_posts WHERE post_type = 'shop_order' AND post_status NOT IN ('inherit','auto-draft') AND ID " + compare_condition + to_str( self._notice['process']['orders']['id_src']), }, 'reviews': { 'type': 'select', 'query': "SELECT COUNT(1) AS count FROM _DBPRF_comments AS cm,_DBPRF_posts AS p WHERE cm.comment_post_ID = p.ID AND p.post_type = 'product' AND cm.comment_ID " + compare_condition + to_str( self._notice['process']['reviews']['id_src']), }, 'pages': { 'type': 'select', 'query': "SELECT COUNT(1) AS count FROM _DBPRF_posts WHERE post_type = 'page' AND ID " + compare_condition + to_str(self._notice['process']['pages']['id_src']), }, 'coupons': { 'type': 'select', 'query': "SELECT COUNT(1) AS count FROM _DBPRF_posts WHERE post_type = 'shop_coupon' AND ID " + compare_condition + to_str(self._notice['process']['coupons']['id_src']), }, 'blogs': { 'type': 'select', 'query': "SELECT COUNT(1) AS count FROM _DBPRF_posts WHERE post_type = 'post' AND ID " + compare_condition + to_str(self._notice['process']['blogs']['id_src']), }, } if self._notice['src']['support']['wpml']: queries['categories'] = { 'type': 'select', # 'query': "SELECT COUNT(1) AS count FROM _DBPRF_term_taxonomy tt LEFT JOIN _DBPRF_icl_translations il ON tt.term_id = il.element_id " # "WHERE tt.term_id and il.`source_language_code` is NULL and il.`element_type` = 'tax_product_cat' and tt.taxonomy = 'product_cat' and tt.term_id > " + to_str( # self._notice['process']['categories']['id_src']), 'query': "SELECT COUNT(1) AS count FROM _DBPRF_term_taxonomy tt LEFT JOIN _DBPRF_icl_translations il ON tt.term_taxonomy_id = il.element_id " "WHERE il.`element_type` = 'tax_product_cat' and il.`source_language_code` IS NULL and tt.taxonomy = 'product_cat' and tt.term_taxonomy_id " + compare_condition + to_str(self._notice['process']['categories']['id_src']), } queries['products'] = { 'type': 'select', # 'query': "SELECT COUNT(1) AS count FROM _DBPRF_posts p LEFT JOIN _DBPRF_icl_translations il ON p.ID = il.element_id " # "WHERE p.`ID` and il.`source_language_code` is NULL and il.`element_type` = 'post_product' and p.post_type = 'product' AND p.post_status NOT IN ('inherit','auto-draft') AND p.ID > " + to_str( # self._notice['process']['products']['id_src']), 'query': "SELECT COUNT(1) AS count FROM _DBPRF_posts p LEFT JOIN _DBPRF_icl_translations il ON p.ID = il.element_id " "WHERE il.`source_language_code` is NULL and il.`element_type` = 'post_product' and p.post_type = 'product' AND p.post_status NOT IN ('inherit','auto-draft') AND p.ID " + compare_condition + to_str(self._notice['process']['products']['id_src']), } return queries def display_import_source(self): if self._notice['config']['add_new']: self.display_recent_data() queries = self.get_query_display_import_source() count = self.get_connector_data(self.get_connector_url('query'), { 'serialize': True, 'query': json.dumps(queries) }) if (not count) or (count['result'] != 'success'): return response_error() real_totals = dict() for key, row in count['data'].items(): total = 0 if key == 'taxes': if row and to_len(row) > 0: taxes = row[0]['option_value'].splitlines() total = (to_len(taxes) + 1) if taxes else 1 else: total = self.list_to_count_import(row, 'count') real_totals[key] = total for key, total in real_totals.items(): self._notice['process'][key]['total'] = total return response_success() def display_update_source(self): queries = self.get_query_display_import_source(True) count = self.select_multiple_data_connector(queries, 'count') if (not count) or (count['result'] != 'success'): return response_error() real_totals = dict() for key, row in count['data'].items(): total = 0 if key == 'taxes': if row and to_len(row) > 0: taxes = row[0]['option_value'].splitlines() total = (to_len(taxes) + 1) if taxes else 1 else: total = self.list_to_count_import(row, 'count') real_totals[key] = total for key, total in real_totals.items(): self._notice['process'][key]['total_update'] = total return response_success() def display_import_target(self): return response_success() def prepare_import_target(self): parent = super().prepare_import_target() if parent['result'] != 'success': return parent query_active_plugins = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_options WHERE option_name = 'active_plugins'" } active_plugins = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query_active_plugins)}) if active_plugins and active_plugins['data']: active_plugin = active_plugins['data'][0] active_plugin_v = active_plugin['option_value'] if active_plugin_v: active_plugin_v_data = php_unserialize(active_plugin_v) if active_plugin_v_data and isinstance(active_plugin_v_data, dict): active_plugin_v_data = list(active_plugin_v_data.values()) if active_plugin_v_data and "woocommerce-multilingual/wpml-woocommerce.php" in active_plugin_v_data: self._notice['target']['support']['wpml'] = True query_active_languages = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_options` WHERE `option_name` = 'icl_sitepress_settings'" } options_data = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query_active_languages)}) if options_data and options_data['data']: option_value = php_unserialize(options_data['data'][0]['option_value']) if option_value and 'default_language' in option_value: self._notice['target']['language_default'] = option_value['default_language'] woo_brands = [ {'name': 'woocommerce-brand/main.php'}, {'name': 'wc-brand/woocommerce-brand.php'}, {'name': 'woocommerce-brands/woocommerce-brands.php'}, {'name': 'brands-for-woocommerce/woocommerce-brand.php', 'taxonomy': 'berocket_brand'}, {'name': 'perfect-woocommerce-brands/main.php', 'taxonomy': 'pwb-brand'}, ] for brand in woo_brands: if brand['name'] in active_plugin_v_data: self._notice['target']['support']['plugin_manufacturers'] = False if brand.get('taxonomy'): self._notice['target']['config']['brand_taxonomy'] = brand['taxonomy'] break if active_plugin_v_data and (("woocommerce-sequential-order-numbers/woocommerce-sequential-order-numbers.php" in active_plugin_v_data) or ("custom-order-numbers-for-woocommerce/custom-order-numbers-for-woocommerce.php" in active_plugin_v_data) or ("sequential-order-numbers-for-woocommerce/sequential-order-numbers.php" in active_plugin_v_data)): self._notice['target']['support']['plugin_pre_ord'] = True if active_plugin_v_data and "wordpress-seo/wp-seo.php" in active_plugin_v_data: self._notice['target']['support']['yoast_seo'] = True if "themedelights-addons/themedelights-addons.php" in active_plugin_v_data or "woocommerce-product-addons/woocommerce-product-addons.php" in active_plugin_v_data: self._notice['target']['support']['addons'] = True if "leurlrewrite/leurlrewrite.php" in active_plugin_v_data: self._notice['target']['support']['plugin_seo'] = True self._notice['target']['support']['plugin_seo_301'] = True if "leprespass/leprespass.php" in active_plugin_v_data: self._notice['target']['support']['plugin_cus_pass'] = True if "woo-product-bundle-premium/index.php" in active_plugin_v_data: self._notice['target']['support']['product_bundle'] = True if "woocommerce-admin/woocommerce-admin.php" in active_plugin_v_data: self._notice['target']['support']['plugin_woo_admin'] = True if self._notice['config']['seo'] or self._notice['config']['seo_301']: query = self.dict_to_create_table_sql(self.lecm_rewrite_table_construct()) self.query_data_connector({'type': 'query', 'query': query['query']}) if self._notice['target']['support']['wpml'] or self._notice['target']['support'].get('polylang'): add_column = "ALTER TABLE " + self.get_table_name(TABLE_MAP) + " ADD `lang` VARCHAR(255)" self.query_raw(add_column) add_column = "ALTER TABLE _DBPRF_lecm_rewrite ADD `lang` VARCHAR(255)" self.query_data_connector({'type': 'query', 'query': add_column}) return response_success() def display_confirm_target(self): self._notice['target']['clear']['function'] = 'clear_target_taxes' self._notice['target']['clear_demo']['function'] = 'clear_target_products_demo' return response_success() # TODO clear demo def clear_target_manufacturers_demo(self): next_clear = { 'result': 'process', 'function': 'clear_target_categories_demo', } self._notice['target']['clear_demo'] = next_clear if not self._notice['config']['manufacturers']: return next_clear where = { 'migration_id': self._migration_id, 'type': self.TYPE_MANUFACTURER } manufacturers = self.select_obj(TABLE_MAP, where) manufacturer_ids = list() if manufacturers['result'] == 'success': manufacturer_ids = duplicate_field_value_from_list(manufacturers['data'], 'id_desc') if not manufacturer_ids: return next_clear manufacturer_id_con = self.list_to_in_condition(manufacturer_ids) taxonomy_meta_table = 'termmeta' collections_query = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_term_taxonomy` WHERE taxonomy = 'product_brand' OR taxonomy = 'brand' OR taxonomy = 'pwb-brand' AND term_id IN " + manufacturer_id_con } manufacturers = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(collections_query)}) if manufacturers['data']: all_queries = list() taxonomy_ids = duplicate_field_value_from_list(manufacturers['data'], 'term_taxonomy_id') all_queries.append({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_" + taxonomy_meta_table + "` WHERE term_id IN " + manufacturer_id_con }) all_queries.append({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_terms` WHERE term_id IN " + manufacturer_id_con }) all_queries.append({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_term_taxonomy` WHERE term_taxonomy_id IN " + self.list_to_in_condition( taxonomy_ids) }) if all_queries: self.import_multiple_data_connector(all_queries, 'cleardemo') return self._notice['target']['clear_demo'] def clear_target_categories_demo(self): next_clear = { 'result': 'process', 'function': 'clear_target_products_demo', } self._notice['target']['clear_demo'] = next_clear if not self._notice['config']['categories']: return next_clear where = { 'migration_id': self._migration_id, 'type': self.TYPE_CATEGORY } categories = self.select_obj(TABLE_MAP, where) category_ids = list() if categories['result'] == 'success': category_ids = duplicate_field_value_from_list(categories['data'], 'id_desc') if not category_ids: return next_clear category_id_con = self.list_to_in_condition(category_ids) taxonomy_meta_table = 'termmeta' collections_query = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_term_taxonomy` WHERE taxonomy = 'product_cat' OR taxonomy = 'post_cat' AND term_id IN " + category_id_con } categories = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(collections_query)}) if categories['data']: all_queries = list() taxonomy_ids = duplicate_field_value_from_list(categories['data'], 'term_taxonomy_id') all_queries.append({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_" + taxonomy_meta_table + "` WHERE term_id IN " + category_id_con }) all_queries.append({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_terms` WHERE term_id IN " + category_id_con }) all_queries.append({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_term_taxonomy` WHERE term_taxonomy_id IN " + self.list_to_in_condition( taxonomy_ids) }) if self._notice['target']['support']['wpml']: clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_icl_translations` " "WHERE element_type = 'tax_product_cat' AND element_id IN " + category_id_con }) }) if self._notice['config']['seo'] or self._notice['config']['seo_301']: clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_lecm_rewrite` where type = 'category' and type_id IN " + category_id_con }) }) if all_queries: self.import_multiple_data_connector(all_queries, 'cleardemo') return next_clear def clear_target_products_demo(self): next_clear = { 'result': 'process', 'function': 'clear_target_orders_demo', } if not self._notice['config']['products']: self._notice['target']['clear_demo'] = next_clear return next_clear where = { 'migration_id': self._migration_id, 'type': self.TYPE_PRODUCT } products = self.select_page(TABLE_MAP, where, self.LIMIT_CLEAR_DEMO) product_ids = list() if products['result'] == 'success': product_ids = duplicate_field_value_from_list(products['data'], 'id_desc') if not product_ids: self._notice['target']['clear_demo'] = next_clear return next_clear product_id_con = self.list_to_in_condition(product_ids) collections_query = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_posts` " "WHERE ID IN " + product_id_con + " OR post_parent IN " + product_id_con } products = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(collections_query)}) all_post_id = list() if products['data']: all_post_id = duplicate_field_value_from_list(products['data'], 'ID') all_collections_query = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_posts` " "WHERE ID IN " + self.list_to_in_condition(all_post_id) } clear_table = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(all_collections_query)}) all_meta_query = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_post_meta`" " WHERE post_id IN " + self.list_to_in_condition(all_post_id) } clear_table = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(all_meta_query)}) where = { 'migration_id': self._migration_id, 'type': self.TYPE_OPTION } attibutes = self.select_obj(TABLE_MAP, where) attibutes_ids = list() attibutes_codes = list() if attibutes['result'] == 'success': attibutes_ids = duplicate_field_value_from_list(attibutes['data'], 'id_desc') attibutes_codes = duplicate_field_value_from_list(attibutes['data'], 'value') if attibutes_ids: del_transient_attr_query = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_woocommerce_attribute_taxonomies` WHERE attribute_id IN " + self.list_to_in_condition( attibutes_ids) } self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(del_transient_attr_query)}) term_query = { "type": "select", "query": "SELECT * FROM `_DBPRF_term_taxonomy` tt LEFT JOIN `_DBPRF_terms` t ON tt.term_id = t.term_id " "WHERE tt.taxonomy IN " + self.list_to_in_condition(attibutes_codes) } terms = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(term_query)}) if (terms['data']): term_ids = duplicate_field_value_from_list(terms['data'], 'term_id') taxonomy_ids = duplicate_field_value_from_list(terms['data'], 'term_taxonomy_id') del_transient_attr_query = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_term_taxonomy` WHERE term_taxonomy_id IN " + self.list_to_in_condition( taxonomy_ids) } self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(del_transient_attr_query)}) del_transient_attr_query = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_terms` WHERE term_id IN " + self.list_to_in_condition( term_ids) } self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(del_transient_attr_query)}) if self._notice['target']['support']['wpml']: clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_icl_translations` " "WHERE element_type = 'post_product' AND element_id IN " + product_id_con }) }) if self._notice['config']['seo'] or self._notice['config']['seo_301']: clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_lecm_rewrite` where type = 'product' and type_id IN " + product_id_con }) }) self.delete_map_demo(self.TYPE_PRODUCT, product_ids) if product_ids and to_len(product_ids) < self.LIMIT_CLEAR_DEMO: self._notice['target']['clear_demo'] = next_clear return next_clear return self._notice['target']['clear_demo'] def clear_target_customers_demo(self): next_clear = { 'result': 'process', 'function': 'clear_target_orders_demo', } self._notice['target']['clear_demo'] = next_clear if not self._notice['config']['customers']: return next_clear where = { 'migration_id': self._migration_id, 'type': self.TYPE_CUSTOMER } customers = self.select_obj(TABLE_MAP, where) customer_ids = list() if customers['result'] == 'success': customer_ids = duplicate_field_value_from_list(customers['data'], 'id_desc') if not customer_ids: return next_clear customer_id_con = self.list_to_in_condition(customer_ids) del_user_query = "DELETE FROM _DBPRF_users WHERE ID IN " + customer_id_con clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': del_user_query }) }) if (not clear_table) or (clear_table['result'] != 'success') or (not clear_table['data']): self.log("Clear data failed. Error: Could not empty customers ", 'clear') del_user_meta_query = "DELETE FROM _DBPRF_usermeta WHERE user_id IN " + customer_id_con clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': del_user_meta_query }) }) if self._notice['target']['support'].get('plugin_woo_admin') or self.convert_version(self._notice['target']['config']['version'], 2) > 399: del_customer_lookup_query = "DELETE FROM _DBPRF_wc_customer_lookup WHERE user_id IN " + customer_id_con clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': del_customer_lookup_query }) }) return next_clear def clear_target_orders_demo(self): next_clear = { 'result': 'success', 'function': 'clear_target_reviews_demo', } if not self._notice['config']['orders']: self._notice['target']['clear_demo'] = next_clear return next_clear where = { 'migration_id': self._migration_id, 'type': self.TYPE_ORDER } orders = self.select_page(TABLE_MAP, where, self.LIMIT_CLEAR_DEMO) order_ids = list() if orders['result'] == 'success': order_ids = duplicate_field_value_from_list(orders['data'], 'id_desc') if not order_ids: self._notice['target']['clear_demo'] = next_clear return next_clear all_collections_query = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_posts` WHERE post_type IN ('shop_order', 'shop_order_refund') AND ID IN " + self.list_to_in_condition( order_ids) } clear_table = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(all_collections_query)}) # clear meta post(orders) all_meta_query = { 'type': 'select', 'query': "DELETE FROM `_DBPRF_post_meta` WHERE post_id IN " + self.list_to_in_condition(order_ids) } clear_table = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(all_meta_query)}) self.delete_map_demo(self.TYPE_ORDER, order_ids) if order_ids and to_len(order_ids) < self.LIMIT_CLEAR_DEMO: self._notice['target']['clear_demo'] = next_clear return next_clear return self._notice['target']['clear_demo'] def clear_target_reviews_demo(self): next_clear = { 'result': 'success', 'function': 'clear_target_pages_demo', } self._notice['target']['clear_demo'] = next_clear if not self._notice['config']['reviews']: return next_clear where = { 'migration_id': self._migration_id, 'type': self.TYPE_REVIEW } reviews = self.select_obj(TABLE_MAP, where) review_ids = list() if reviews['result'] == 'success': review_ids = duplicate_field_value_from_list(reviews['data'], 'id_desc') if not review_ids: return next_clear tables = [ 'commentmeta', 'comments' ] for table in tables: where = '' if table == 'comments': where = " WHERE comment_ID IN " + self.list_to_in_condition(review_ids) if table == 'commentmeta': where = " WHERE comment_id IN " + self.list_to_in_condition(review_ids) clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_" + table + "`" + where }) }) if (not clear_table) or (clear_table['result'] != 'success'): self.log("Clear data failed. Error: Could not empty table " + table, 'clear') continue # TODO: clear def clear_target_taxes(self): next_clear = { 'result': 'process', 'function': 'clear_target_manufacturers', 'msg': '' } if not self._notice['config']['taxes']: self._notice['target']['clear'] = next_clear return next_clear tables = [ 'options', 'woocommerce_tax_rates', 'woocommerce_tax_rate_locations', 'wc_tax_rate_classes' ] for table in tables: if table == 'options': clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': "UPDATE `_DBPRF_" + table + "` SET `option_value` = '' WHERE `option_name` = 'woocommerce_tax_classes'" }) }) continue clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_" + table + "` WHERE 1" }) }) if (not clear_table) or (clear_table['result'] != 'success'): self.log("Clear data failed. Error: Could not empty table " + table, 'clear') continue self._notice['target']['clear'] = next_clear return next_clear def clear_target_manufacturers(self): next_clear = { 'result': 'process', 'function': 'clear_target_categories', 'msg': '' } if not self._notice['config']['manufacturers']: self._notice['target']['clear'] = next_clear return next_clear taxonomy_meta_table = 'termmeta' taxonomy = 'berocket_brand' if self._notice['target']['config'].get('brand_taxonomy'): taxonomy = self._notice['target']['config']['brand_taxonomy'] # all_collections_query = { # 'type': 'select', # 'query': "SELECT * FROM `_DBPRF_term_taxonomy` WHERE taxonomy = 'product_brand' OR taxonomy = 'brand' OR taxonomy = 'pwb-brand' LIMIT 200" # } # manufacturers = self.get_connector_data(self.get_connector_url('query'), # {'query': json.dumps(all_collections_query)}) tables = ['termmeta', 'terms', 'term_relationships', 'term_taxonomy'] for table in tables: where = '' if table in ['termmeta', 'terms']: where = " term_id IN (SELECT term_id FROM `_DBPRF_term_taxonomy` WHERE taxonomy = " + self.escape(taxonomy) + " )" if table in ['term_relationships']: where = " term_taxonomy_id IN (SELECT term_taxonomy_id FROM `_DBPRF_term_taxonomy` WHERE taxonomy = " + self.escape(taxonomy) + " )" if table == 'term_taxonomy': where = " taxonomy = " + self.escape(taxonomy) query = "DELETE FROM `_DBPRF_" + table + "` WHERE " + where clear_table = self.query_data_connector({'type': 'delete', 'query': query}) if (not clear_table) or (clear_table['result'] != 'success'): self.log("Clear data failed. Error: Could not empty table " + table, 'clear') continue # if manufacturers: # while manufacturers['data']: # if not manufacturers: # return next_clear # term_ids = duplicate_field_value_from_list(manufacturers['data'], 'term_id') # all_queries = list() # taxonomy_ids = duplicate_field_value_from_list(manufacturers['data'], 'term_taxonomy_id') # all_queries.append({ # 'type': 'query', # 'query': "DELETE FROM `_DBPRF_" + taxonomy_meta_table + "` WHERE term_id IN " + self.list_to_in_condition( # term_ids) # }) # all_queries.append({ # 'type': 'query', # 'query': "DELETE FROM `_DBPRF_terms` WHERE term_id IN " + self.list_to_in_condition( # term_ids) # }) # all_queries.append({ # 'type': 'query', # 'query': "DELETE FROM `_DBPRF_term_taxonomy` WHERE term_taxonomy_id IN " + self.list_to_in_condition( # taxonomy_ids) # }) # if all_queries: # self.import_multiple_data_connector(all_queries, 'cleardemo') # all_collections_query = { # 'type': 'select', # 'query': "SELECT * FROM `_DBPRF_term_taxonomy` WHERE taxonomy = 'product_brand' OR taxonomy = 'brand' OR taxonomy = 'pwb-brand' LIMIT 200" # } # manufacturers = self.get_connector_data(self.get_connector_url('query'), # {'query': json.dumps(all_collections_query)}) if self._notice['target']['support']['yoast_seo']: query_wpseo = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_options` WHERE `option_name` = 'wpseo_taxonomy_meta'" } options_data = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query_wpseo)}) if options_data and options_data['data']: option_value = php_unserialize(options_data['data'][0]['option_value']) if taxonomy in option_value: option_value[taxonomy] = dict() data_set = { 'option_value': php_serialize(option_value) } where = { 'option_id': options_data['data'][0]['option_id'], 'option_name': 'wpseo_taxonomy_meta' } update_query = self.create_update_query_connector('options', data_set, where) wpseo_taxonomy_clear = self.import_data_connector(update_query, 'manufacturer') self._notice['target']['clear'] = next_clear return next_clear def clear_target_categories(self): next_clear = { 'result': 'process', 'function': 'clear_target_products', 'msg': '' } if not self._notice['config']['categories']: self._notice['target']['clear'] = next_clear return next_clear taxonomy_meta_table = 'termmeta' while self._check_categories_exists(): all_collections_query = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_term_taxonomy` WHERE taxonomy = 'product_cat' OR taxonomy = 'post_cat' LIMIT 200" } categories = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(all_collections_query)}) if not categories: return next_clear term_ids = duplicate_field_value_from_list(categories['data'], 'term_id') taxonomy_ids = duplicate_field_value_from_list(categories['data'], 'term_taxonomy_id') taxnomy_query = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_" + taxonomy_meta_table + "` WHERE term_id IN " + self.list_to_in_condition( term_ids) } self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(taxnomy_query)}) self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_terms` WHERE term_id IN " + self.list_to_in_condition( term_ids) })}) self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_term_taxonomy` WHERE term_taxonomy_id IN " + self.list_to_in_condition( taxonomy_ids) }) }) # end for if self._notice['target']['support']['wpml']: clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_icl_translations` where element_type = 'tax_product_cat'" }) }) if self._notice['config']['seo'] or self._notice['config']['seo_301']: clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_lecm_rewrite` where type = 'category'" }) }) if self._notice['target']['support']['yoast_seo']: query_wpseo = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_options` WHERE `option_name` = 'wpseo_taxonomy_meta'" } options_data = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query_wpseo)}) if options_data and options_data['data']: option_value = php_unserialize(options_data['data'][0]['option_value']) if 'product_cat' in option_value: option_value['product_cat'] = dict() data_set = { 'option_value': php_serialize(option_value) } where = { 'option_id': options_data['data'][0]['option_id'], 'option_name': 'wpseo_taxonomy_meta' } update_query = self.create_update_query_connector('options', data_set, where) wpseo_taxonomy_clear = self.import_data_connector(update_query, 'category') self._notice['target']['clear'] = next_clear return self._notice['target']['clear'] def _check_categories_exists(self): all_collections_query = { 'type': 'select', 'query': "SELECT term_taxonomy_id FROM `_DBPRF_term_taxonomy` WHERE taxonomy = 'product_cat' OR taxonomy = 'post_cat' LIMIT 1" } categories = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(all_collections_query)}) return True if categories['data'] else False def _check_product_exists(self): all_collections_query = { 'type': 'select', 'query': "SELECT ID FROM `_DBPRF_posts` WHERE post_type IN ('product', 'product_variation') LIMIT 1" } # products = self.get_connector_data(self.get_connector_url('query'), # {'query': json.dumps(all_collections_query)}) products = self.select_data_connector(all_collections_query, 'products') return True if products['data'] else False def _check_attributes_exists(self): all_collections_query = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_woocommerce_attribute_taxonomies` ORDER BY attribute_id LIMIT 200" } products = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(all_collections_query)}) return True if products['data'] else False def clear_target_products(self): next_clear = { 'result': 'process', 'function': 'clear_target_customers', 'msg': '' } if not self._notice['config']['products']: self._notice['target']['clear'] = next_clear return next_clear while self._check_product_exists(): # clear posts(product) # clear meta post(product) all_collections_query = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_posts` WHERE post_type IN('product', 'product_variation')" } clear_table = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(all_collections_query)}) if (not clear_table) or (clear_table['result'] != 'success') or (not clear_table['data']): self.log("Clear data failed. Error: Could not empty products", 'clear') continue all_meta_query = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_postmeta` WHERE post_id NOT IN (SELECT ID FROM _DBPRF_posts)" } clear_table = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(all_meta_query)}) if (not clear_table) or (clear_table['result'] != 'success'): self.log("Clear data failed. Error: Could not empty products", 'clear') continue # clear attributes del_transient_attr_query = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_options` WHERE option_name = '_transient_wc_attribute_taxonomies'" } clear_table = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(del_transient_attr_query)}) while self._check_attributes_exists(): product_attribute_query = { "type": "select", "query": "SELECT * FROM `_DBPRF_woocommerce_attribute_taxonomies` ORDER BY attribute_id LIMIT 200" } attributes = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(product_attribute_query)}) if (attributes['data']): attribute_ids = duplicate_field_value_from_list(attributes['data'], 'attribute_id') attribute_names = duplicate_field_value_from_list(attributes['data'], 'attribute_name') attribute_names_condition = "('pa_" + "','pa_".join(attribute_names) + "')" del_transient_attr_query = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_woocommerce_attribute_taxonomies` WHERE attribute_id IN " + self.list_to_in_condition( attribute_ids) } self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(del_transient_attr_query)}) term_query = { "type": "select", "query": "SELECT * FROM `_DBPRF_term_taxonomy` tt LEFT JOIN `_DBPRF_terms` t ON tt.term_id = t.term_id " "WHERE tt.taxonomy IN " + attribute_names_condition } terms = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(term_query)}) if (terms['data']): term_ids = duplicate_field_value_from_list(terms['data'], 'term_id') taxonomy_ids = duplicate_field_value_from_list(terms['data'], 'term_taxonomy_id') del_transient_attr_query = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_term_taxonomy` WHERE term_taxonomy_id IN " + self.list_to_in_condition( taxonomy_ids) } self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(del_transient_attr_query)}) del_transient_attr_query = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_terms` WHERE term_id IN " + self.list_to_in_condition( term_ids) } self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(del_transient_attr_query)}) if self._notice['target']['support']['wpml']: clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_icl_translations` where element_type IN ('post_product','post_product_variation'" }) }) if self._notice['config']['seo'] or self._notice['config']['seo_301']: clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_lecm_rewrite` where type = 'product'" }) }) self._notice['target']['clear'] = next_clear return self._notice['target']['clear'] def clear_target_customers(self): next_clear = { 'result': 'process', 'function': 'clear_target_orders', 'msg': '' } if not self._notice['config']['customers']: self._notice['target']['clear'] = next_clear return next_clear # "DELETE FROM `wp_usermeta` # WHERE meta_key IN ('wp_capabilities', 'wp_capabilities') AND meta_value = 'a:1:{s:8:"customer";b:1;}'" del_user_query = "DELETE _DBPRF_users FROM _DBPRF_users " \ "LEFT JOIN _DBPRF_usermeta ON _DBPRF_users.ID = _DBPRF_usermeta.user_id " \ "WHERE _DBPRF_usermeta.meta_key IN ('_DBPRF_capabilities', '_DBPRF_capabilities') " \ "AND _DBPRF_usermeta.meta_value = 'a:1:{s:8:\"customer\";b:1;}'" clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': del_user_query }) }) if (not clear_table) or (clear_table['result'] != 'success') or (not clear_table['data']): self.log("Clear data failed. Error: Could not empty customers ", 'clear') del_user_meta_query = "DELETE _DBPRF_usermeta FROM _DBPRF_usermeta " \ "LEFT JOIN _DBPRF_users ON _DBPRF_usermeta.user_id = _DBPRF_users.ID WHERE _DBPRF_users.ID IS NULL" clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': del_user_meta_query }) }) # # if self._notice['target']['support'].get('plugin_woo_admin') or self.convert_version(self._notice['target']['config']['version'], 2) > 399: del_customer_lookup_query = "DELETE _DBPRF_wc_customer_lookup FROM _DBPRF_wc_customer_lookup LEFT JOIN _DBPRF_users ON _DBPRF_wc_customer_lookup.user_id = _DBPRF_users.ID WHERE _DBPRF_users.ID IS NULL" clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': del_customer_lookup_query }) }) self._notice['target']['clear'] = next_clear return self._notice['target']['clear'] def _check_order_exists(self): all_collections_query = { 'type': 'select', 'query': "SELECT ID FROM `_DBPRF_posts` WHERE post_type IN ('shop_order', 'shop_order_refund') LIMIT 1" } products = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(all_collections_query)}) return True if products['data'] else False def clear_target_orders(self): next_clear = { 'result': 'process', 'function': 'clear_target_reviews', 'msg': '' } if not self._notice['config']['orders']: self._notice['target']['clear'] = next_clear return next_clear while self._check_order_exists(): # clear posts(orders) all_collections_query = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_posts` WHERE post_type IN ('shop_order', 'shop_order_refund')" } clear_table = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(all_collections_query)}) if (not clear_table) or (clear_table['result'] != 'success'): self.log("Clear data failed. Error: Could not empty products", 'clear') continue # clear meta post(orders) all_meta_query = { 'type': 'select', 'query': "DELETE `_DBPRF_postmeta` FROM `_DBPRF_post_meta` pm LEFT JOIN `_DBPRF_posts` p ON p.ID = pm.meta_id" " WHERE p.ID IS NULL" } clear_table = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(all_meta_query)}) if (not clear_table) or (clear_table['result'] != 'success'): self.log("Clear data failed. Error: Could not empty products", 'clear') continue self._notice['target']['clear'] = next_clear return self._notice['target']['clear'] def clear_target_reviews(self): next_clear = { 'result': 'process', 'function': 'clear_target_blogs', 'msg': '' } if not self._notice['config']['reviews']: self._notice['target']['clear'] = next_clear return next_clear tables = [ 'commentmeta', 'comments' ] for table in tables: self._notice['target']['clear']['result'] = 'process' self._notice['target']['clear']['function'] = 'clear_target_reviews' clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_" + table + "`" }) }) if (not clear_table) or (clear_table['result'] != 'success'): self.log("Clear data failed. Error: Could not empty table " + table, 'clear') continue self._notice['target']['clear'] = next_clear return self._notice['target']['clear'] # def clear_target_blogs(self): # next_clear = { # 'result': 'process', # 'function': 'clear_target_coupons', # 'msg': '' # } # self._notice['target']['clear'] = next_clear # if not self._notice['config'].get('blogs'): # return next_clear # all_queries = { # 'term': { # 'type': 'delete', # 'query': 'DELETE FROM _DBPRF_terms WHERE term_id IN (SELECT term_id FROM _DBPRF_term_taxonomy WHERE taxonomy IN ' + self.list_to_in_condition(['category', 'post_tag']) + ')' # }, # 'term_taxonomy': { # 'type': 'delete', # 'query': 'DELETE FROM _DBPRF_term_taxonomy WHERE taxonomy IN ' + self.list_to_in_condition(['category', 'post_tag']) # }, # 'term_relationship': { # 'type': 'delete', # 'query': 'DELETE FROM _DBPRF_term_relationships WHERE object_id IN (SELECT ID FROM _DBPRF_posts WHERE post_type = "post")' # }, # 'postmeta': { # 'type': 'delete', # 'query': 'DELETE FROM _DBPRF_postmeta WHERE post_id IN (SELECT ID FROM _DBPRF_posts WHERE post_type = "post")' # }, # 'posts': { # 'type': 'delete', # 'query': 'DELETE FROM _DBPRF_posts WHERE post_type = "post"' # }, # } # delete = self.query_multiple_data_connector(all_queries, 'clear_blog') # return next_clear def clear_target_coupons(self): next_clear = { 'result': 'process', 'function': 'clear_target_pages', 'msg': '' } self._notice['target']['clear'] = next_clear if not self._notice['config']['coupons']: return next_clear tables = [ 'postmeta', 'posts' ] for table in tables: where = ' post_type = "shop_coupon"' if table == 'postmeta': where = ' post_id IN (SELECT ID FROM _DBPRF_posts WHERE post_type = "shop_coupon")' clear_table = self.get_connector_data(self.get_connector_url('query'), { 'query': json.dumps({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_" + table + "` WHERE " + where }) }) if (not clear_table) or (clear_table['result'] != 'success'): self.log("Clear data failed. Error: Could not empty table " + table, 'clear') continue return next_clear # def clear_target_pages(self): # next_clear = { # 'result': 'process', # 'function': '', # 'msg': '' # } # self._notice['target']['clear'] = next_clear # if not self._notice['config']['pages']: # return next_clear # tables = [ # 'postmeta', # 'posts' # ] # for table in tables: # where = ' post_type = "page"' # if table == 'postmeta': # where = ' post_id IN (SELECT ID FROM _DBPRF_posts WHERE post_type = "page")' # clear_table = self.get_connector_data(self.get_connector_url('query'), { # 'query': json.dumps({ # 'type': 'query', 'query': "DELETE FROM `_DBPRF_" + table + "` WHERE " + where # }) # }) # if (not clear_table) or (clear_table['result'] != 'success'): # self.log("Clear data failed. Error: Could not empty table " + table, 'clear') # continue # return next_clear # TODO: TAX def prepare_taxes_import(self): return self def prepare_taxes_export(self): return self def get_taxes_main_export(self): id_src = self._notice['process']['taxes']['id_src'] limit = self._notice['setting']['taxes'] query = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_options WHERE option_name = 'woocommerce_tax_classes'" } # taxes = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query)}) taxes = self.select_data_connector(query, 'taxes') if not taxes or taxes['result'] != 'success': return response_error('could not get taxes main to export') list_taxes = response_success() if taxes['data'] and to_len(taxes['data']) > 0: list_taxes['data'] = list() for tax in taxes['data']: _taxes = tax['option_value'].splitlines() if _taxes: tmp_taxes = [ { 'id': 1, 'name': 'Standard' } ] i = 2 for tax_name in _taxes: tax_data = dict() tax_data['id'] = i tax_data['name'] = tax_name tmp_taxes.append(tax_data) i += 1 list_taxes['data'].extend(tmp_taxes) return list_taxes def get_taxes_ext_export(self, taxes): url_query = self.get_connector_url('query') tax_product_class_names = duplicate_field_value_from_list(taxes['data'], 'name') tax_names = list() for class_name in tax_product_class_names: _class_name = to_str(class_name).lower() _class_name = _class_name.replace(' ', '-') tax_names.append(_class_name) taxes_ext_queries = { 'tax_rates': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_woocommerce_tax_rates WHERE 1" # tax_rate_class IN " + self.list_to_in_condition(tax_names), } } # taxes_ext = self.get_connector_data(url_query, {'serialize': True, 'query': json.dumps(taxes_ext_queries)}) taxes_ext = self.select_multiple_data_connector(taxes_ext_queries, 'taxes') if not taxes_ext or taxes_ext['result'] != 'success': return response_error() tax_zone_ids = duplicate_field_value_from_list(taxes_ext['data']['tax_rates'], 'tax_rate_id') taxes_ext_rel_queries = { 'tax_rates_location': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_woocommerce_tax_rate_locations WHERE tax_rate_id IN " + self.list_to_in_condition( tax_zone_ids), } } # taxes_ext_rel = self.get_connector_data(url_query, # {'serialize': True, 'query': json.dumps(taxes_ext_rel_queries)}) taxes_ext_rel = self.select_multiple_data_connector(taxes_ext_rel_queries, 'taxes') if not taxes_ext_rel or taxes_ext_rel['result'] != 'success': return response_error() taxes_ext = self.sync_connector_object(taxes_ext, taxes_ext_rel) return taxes_ext def convert_tax_export(self, tax, taxes_ext): tax_zones = list() tax_rate_class_1 = to_str(tax['name']).lower() tax_rate_class_1 = tax_rate_class_1.replace(' ', '-') if tax['name'] == 'Standard': tax_rate_class_1 = '' src_tax_rate = get_list_from_list_by_field(taxes_ext['data']['tax_rates'], 'tax_rate_class', tax_rate_class_1) if src_tax_rate and to_len(src_tax_rate) > 0: for tax_rate in src_tax_rate: tax_zone = self.construct_tax_zone() # tax_zone = self.addConstructDefault(tax_zone) tax_zone['id'] = tax_rate['tax_rate_id'] tax_zone['name'] = tax_rate['tax_rate_name'] tax_zone_country = self.construct_tax_zone_country() tax_zone_country['name'] = self.get_country_name_by_code(tax_rate['tax_rate_country']) if tax_rate['tax_rate_country'] else '' tax_zone_country['code'] = get_value_by_key_in_dict(tax_rate, 'tax_rate_country', '') tax_zone_country['country_code'] = get_value_by_key_in_dict(tax_rate, 'tax_rate_country', '') tax_zone['country'] = tax_zone_country tax_zone_state = self.construct_tax_zone_state() tax_zone_state['name'] = '' tax_zone_state['code'] = get_value_by_key_in_dict(tax_rate, 'tax_rate_state', '') tax_zone_state['state_code'] = get_value_by_key_in_dict(tax_rate, 'tax_rate_state', '') tax_zone['state'] = tax_zone_state tax_zone['rate'] = self.construct_tax_zone_rate() tax_zone['rate']['id'] = tax_rate['tax_rate_id'] tax_zone['rate']['name'] = tax_rate['tax_rate_name'] tax_zone['rate']['code'] = tax_rate['tax_rate_class'] tax_zone['rate']['rate'] = tax_rate['tax_rate'] tax_rates_locations = get_list_from_list_by_field(taxes_ext['data']['tax_rates_location'], 'tax_rate_id', tax_rate['tax_rate_id']) tax_zone_city = get_list_from_list_by_field(tax_rates_locations, 'location_type', 'city') tax_zone['postcode'] = get_row_value_from_list_by_field(tax_rates_locations, 'location_type', 'postcode', 'location_code') if tax_zone_city: for _tax_zone_city in tax_zone_city: tax_zone['city'] += _tax_zone_city['location_code'] + ';' tax_zone['priority'] = tax_rate['tax_rate_priority'] tax_zone['compound'] = True if tax_rate['tax_rate_compound'] and to_int(tax_rate['tax_rate_compound']) == 1 else False tax_zone['is_shipping'] = True if tax_rate['tax_rate_shipping'] and to_int(tax_rate['tax_rate_shipping']) == 1 else False tax_zones.append(tax_zone) tax_product = self.construct_tax_product() tax_product = self.add_construct_default(tax_product) tax_code = to_str(tax['name']).lower() tax_code = tax_code.replace(' ', '-') tax_product['name'] = tax['name'] tax_product['code'] = tax_code tax_product['created_at'] = get_current_time() tax_product['updated_at'] = get_current_time() tax_products = [tax_product] tax_data = self.construct_tax() tax_data = self.add_construct_default(tax_data) # id_src = self._notice['process']['taxes']['id_src'] tax_data['id'] = tax['id'] tax_data['code'] = tax_code # tax['name'] tax_data['name'] = tax['name'] tax_data['created_at'] = get_current_time() tax_data['updated_at'] = get_current_time() tax_data['tax_zones'] = tax_zones tax_data['tax_products'] = tax_products return response_success(tax_data) def get_tax_id_import(self, convert, tax, taxes_ext): # id_src = self._notice['process']['taxes']['id_src'] return tax['id'] def check_tax_import(self, convert, tax, taxes_ext): return True if self.get_map_field_by_src(self.TYPE_TAX, convert['id'], convert['code']) else False def router_tax_import(self, convert, tax, taxes_ext): return response_success('tax_import') def before_tax_import(self, convert, tax, taxes_ext): return response_success() def tax_import(self, convert, tax, taxes_ext): slug = self.sanitize_title(convert['name']) if convert['name'] != 'Standard': query = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_options WHERE option_name = 'woocommerce_tax_classes'" } taxes = self.select_data_connector(query, 'taxes') if taxes and taxes['data']: old_tax_data = taxes['data'][0] new_option_value = old_tax_data['option_value'] + '\n' + convert['name'] if old_tax_data['option_value'] else convert['name'] query_update = { 'type': 'query', 'query': "UPDATE `_DBPRF_options` SET `option_value` = '" + new_option_value + "' WHERE `option_name` = 'woocommerce_tax_classes'" } taxes = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query_update)}) else: tax_data = { 'option_name': 'woocommerce_tax_classes', 'option_value': convert['name'], 'autoload': 'yes' } tax_query = self.create_insert_query_connector('options', tax_data) tax_import = self.import_tax_data_connector(tax_query, True, convert['id']) if self.convert_version(self._notice['target']['config']['version'], 2) >= 370: tax_rate_classes = { 'name': convert['name'], 'slug': slug } tax_rate_classes_query = self.create_insert_query_connector('wc_tax_rate_classes', tax_rate_classes) tax_rate_classes_import = self.import_data_connector(tax_rate_classes_query, 'wc_tax_rate_classes') tax_code = to_str(convert['name']).lower() tax_code = self.sanitize_title(tax_code.replace(' ', '-')) self.insert_map(self.TYPE_TAX, convert['id'], 0, convert['code'], tax_code) return response_success(convert['id']) def after_tax_import(self, tax_id, convert, tax, taxes_ext): if convert['tax_zones']: tax_code = to_str(convert['name']).lower() tax_code = tax_code.replace(' ', '-') for tax_zone in convert['tax_zones']: tax_rate = { 'tax_rate_country': tax_zone['country']['country_code'], 'tax_rate_state': tax_zone['state']['state_code'] if tax_zone['state']['state_code'] else '*', 'tax_rate': tax_zone['rate']['rate'] if tax_zone['rate']['rate'] else '*', 'tax_rate_name': tax_zone['rate']['name'] if tax_zone['rate']['name'] else 'Tax', 'tax_rate_priority': tax_zone.get('priority', 1), 'tax_rate_compound': 1 if tax_zone.get('compound') else 0, 'tax_rate_shipping': 1 if tax_zone.get('is_shipping') else 0, 'tax_rate_order': 0, 'tax_rate_class': '' if convert['name'] == 'Standard' else self.convert_attribute_code(tax_code) } tax_rate_query = self.create_insert_query_connector('woocommerce_tax_rates', tax_rate) tax_rate_import = self.import_data_connector(tax_rate_query, 'tax') if get_value_by_key_in_dict(tax_zone, 'postcode', False): location_postcode = { 'location_code': get_value_by_key_in_dict(tax_zone, 'postcode', ''), 'tax_rate_id': tax_rate_import, 'location_type': 'postcode' } self.import_data_connector( self.create_insert_query_connector('woocommerce_tax_rate_locations', location_postcode), 'tax') if get_value_by_key_in_dict(tax_zone, 'city', False): tax_zone_city = tax_zone['city'].split(';') if tax_zone_city: for _tax_zone_city in tax_zone_city: if _tax_zone_city != '' and _tax_zone_city != ' ': location_city = { 'location_code': get_value_by_key_in_dict(tax_zone, 'city', ''), 'tax_rate_id': tax_rate_import, 'location_type': 'city' } self.import_data_connector(self.create_insert_query_connector('woocommerce_tax_rate_locations', location_city), 'tax') return response_success() def addition_tax_import(self, convert, tax, taxes_ext): return response_success() # TODO: MANUFACTURER def prepare_manufacturers_import(self): return self def prepare_manufacturers_export(self): return self def get_manufacturers_main_export(self): id_src = self._notice['process']['manufacturers']['id_src'] limit = self._notice['setting']['manufacturers'] query = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_term_taxonomy as tx LEFT JOIN _DBPRF_terms AS t ON t.term_id = tx.term_id" " WHERE (tx.taxonomy = 'product_brand' OR tx.taxonomy = 'brand' OR tx.taxonomy = 'pwb-brand') AND tx.term_id > " + to_str( id_src) + " ORDER BY tx.term_id ASC LIMIT " + to_str(limit) } # manufacturers = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query)}) manufacturers = self.select_data_connector(query, 'manufacturers') if not manufacturers or manufacturers['result'] != 'success': return response_error('could not get manufacturers main to export') return manufacturers def get_manufacturers_ext_export(self, manufacturers): url_query = self.get_connector_url('query') category_ids = duplicate_field_value_from_list(manufacturers['data'], 'term_id') cart_version = self.convert_version(self._notice['src']['config']['version'], 2) manufacturers_ext_queries = { 'all_category': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_term_taxonomy as tx LEFT JOIN _DBPRF_terms AS t ON t.term_id = tx.term_id WHERE tx.taxonomy = 'product_cat' AND tx.term_id > 0 " } } if cart_version > 223: manufacturers_ext_queries['woocommerce_termmeta'] = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_termmeta WHERE term_id IN " + self.list_to_in_condition( category_ids) + " AND meta_key IN ('order', 'thumbnail_id', 'display_type')" } else: manufacturers_ext_queries['woocommerce_termmeta'] = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_woocommerce_termmeta WHERE woocommerce_term_id IN " + self.list_to_in_condition( category_ids) + " AND meta_key IN ('order', 'thumbnail_id', 'display_type')" } manufacturers_ext_queries['brand_taxonomy_images'] = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_options WHERE option_name IN " + self.brand_image_in_condition(category_ids) } # manufacturers_ext = self.get_connector_data(url_query, { # 'serialize': True, # 'query': json.dumps(manufacturers_ext_queries) # }) manufacturers_ext = self.select_multiple_data_connector(manufacturers_ext_queries, 'manufacturers') if not manufacturers_ext or manufacturers_ext['result'] != 'success': return response_warning() thumb_id_list = get_list_from_list_by_field(manufacturers_ext['data']['woocommerce_termmeta'], 'meta_key', 'thumbnail_id') thumbnail_ids = duplicate_field_value_from_list(thumb_id_list, 'meta_value') thumb_ids_query = self.list_to_in_condition(thumbnail_ids) manufacturers_ext_rel_queries = { 'post_meta': { 'type': 'select', 'query': "SELECT p.ID, p.post_title, pm.meta_value, p.guid FROM _DBPRF_posts AS p " "LEFT JOIN _DBPRF_postmeta AS pm ON pm.post_id = p.ID AND pm.meta_key = '_wp_attached_file' WHERE p.ID IN " + thumb_ids_query } } # add custom if manufacturers_ext_rel_queries: # manufacturers_ext_rel = self.get_connector_data(url_query, { # 'serialize': True, # 'query': json.dumps(manufacturers_ext_rel_queries) # }) manufacturers_ext_rel = self.select_multiple_data_connector(manufacturers_ext_rel_queries, 'manufacturers') if not manufacturers_ext_rel or manufacturers_ext_rel['result'] != 'success': return response_error() manufacturers_ext = self.sync_connector_object(manufacturers_ext, manufacturers_ext_rel) return manufacturers_ext def convert_manufacturer_export(self, manufacturer, manufacturers_ext): manufacturer_data = self.construct_manufacturer() manufacturer_data = self.add_construct_default(manufacturer_data) manufacturer_path = manufacturer_url = img_label = '' cart_version = self.convert_version(self._notice['src']['config']['version'], 2) manufacturer_src = False if cart_version > 223: manufacturer_src = get_list_from_list_by_field(manufacturers_ext['data']['woocommerce_termmeta'], 'term_id', manufacturer['term_id']) else: manufacturer_src = get_list_from_list_by_field(manufacturers_ext['data']['woocommerce_termmeta'], 'woocommerce_term_id', manufacturer['term_id']) if manufacturer_src: manufacturer_img_id = self.get_value_metadata(manufacturer_src, 'thumbnail_id', 0) img_meta = get_list_from_list_by_field(manufacturers_ext['data']['post_meta'], 'ID', manufacturer_img_id) if img_meta: img_label = img_meta[0]['post_title'] manufacturer_path = img_meta[0]['meta_value'] manufacturer_url = to_str(img_meta[0]['guid']).replace(img_meta[0]['meta_value'], '') brand_image = get_row_value_from_list_by_field(manufacturers_ext['data']['brand_taxonomy_images'], 'option_name', "brand_taxonomy_image" + to_str(manufacturer['term_id']), 'option_value') if brand_image: manufacturer_url = brand_image manufacturer_data['id'] = manufacturer['term_id'] manufacturer_data['code'] = manufacturer['slug'] manufacturer_data['name'] = manufacturer['name'] manufacturer_data['description'] = manufacturer['description'] manufacturer_data['thumb_image']['label'] = img_label manufacturer_data['thumb_image']['url'] = manufacturer_url manufacturer_data['thumb_image']['path'] = manufacturer_path manufacturer_data['created_at'] = get_current_time() manufacturer_data['updated_at'] = get_current_time() language_id = self._notice['src']['language_default'] manufacturer_language_data = dict() manufacturer_language_data['name'] = manufacturer['name'] manufacturer_language_data['description'] = manufacturer['description'] manufacturer_data['languages'][language_id] = manufacturer_language_data manufacturer_data['manufacturer'] = manufacturer manufacturer_data['manufacturers_ext'] = manufacturers_ext return response_success(manufacturer_data) def get_manufacturer_id_import(self, convert, manufacturer, manufacturers_ext): return manufacturer['term_id'] def check_manufacturer_import(self, convert, manufacturer, manufacturers_ext): return True if self.get_map_field_by_src(self.TYPE_MANUFACTURER, convert['id']) else False def router_manufacturer_import(self, convert, manufacturer, manufacturers_ext): return response_success('manufacturer_import') def before_manufacturer_import(self, convert, manufacturer, manufacturers_ext): return response_success() def manufacturer_import(self, convert, manufacturer, manufacturers_ext): slug = self.sanitize_title(convert['name']) manufacturer_term = { 'name': convert['name'], 'slug': convert['code'] if convert['code'] else slug, 'term_group': 0, } manufacturer_term_query = self.create_insert_query_connector('terms', manufacturer_term) term_id = self.import_data_connector(manufacturer_term_query, 'category') if not term_id: return response_warning('Manufacturer ' + to_str(convert['id']) + ' import false.') taxonomy = 'berocket_brand' if self._notice['target']['config'].get('brand_taxonomy'): taxonomy = self._notice['target']['config']['brand_taxonomy'] manufacturer_taxonomy = { 'term_id': term_id, 'taxonomy': taxonomy, 'description': get_value_by_key_in_dict(convert, 'description', ''), 'parent': 0, 'count': 0 } manufacturer_taxonomy_query = self.create_insert_query_connector('term_taxonomy', manufacturer_taxonomy) manufacturer_taxonomy_import = self.import_manufacturer_data_connector(manufacturer_taxonomy_query, True, convert['id']) if not manufacturer_taxonomy_import: return response_warning('manufacturer ' + to_str(convert['id']) + ' import false.') self.insert_map(self.TYPE_MANUFACTURER, convert['id'], manufacturer_taxonomy_import, convert['code']) thumbnail_id = False cate_image = '' if convert['thumb_image']['url'] or convert['thumb_image']['path']: image_process = self.process_image_before_import(convert['thumb_image']['url'], convert['thumb_image']['path']) image_import_path = self.uploadImageConnector(image_process, self.add_prefix_path(self.make_woocommerce_image_path(image_process['path'], self.TYPE_MANUFACTURER), self._notice['target']['config']['image_manufacturer'].rstrip('/'))) if image_import_path: cate_image = self.remove_prefix_path(image_import_path, self._notice['target']['config']['image_category']) image_details = self.get_sizes(image_process['url']) thumbnail_id = self.wp_image(cate_image, image_details) if thumbnail_id: meta_insert = { 'term_id': term_id, # 'meta_key': 'thumbnail_id', 'meta_key': 'pwb_brand_image', 'meta_value': thumbnail_id } meta_query = self.create_insert_query_connector('termmeta', meta_insert) self.import_data_connector(meta_query, 'manufacturer') meta_insert = { 'term_id': term_id, # 'meta_key': 'thumbnail_id', 'meta_key': 'thumbnail_id', 'meta_value': thumbnail_id } meta_query = self.create_insert_query_connector('termmeta', meta_insert) self.import_data_connector(meta_query, 'manufacturer') meta_insert = { 'term_id': term_id, 'meta_key': 'brand_image_url', 'meta_value': self._notice['target']['cart_url'].rstrip('/') + '/wp-content/uploads/' + cate_image.lstrip('/') } meta_query = self.create_insert_query_connector('termmeta', meta_insert) self.import_data_connector(meta_query, 'manufacturer') if self.is_wpml() or self._notice['target']['support']['yoast_seo']: query_wpseo = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_options` WHERE `option_name` = 'wpseo_taxonomy_meta'" } options_data = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query_wpseo)}) if options_data and options_data['data']: option_value = php_unserialize(options_data['data'][0]['option_value']) if not option_value: option_value = dict() if taxonomy not in option_value.keys(): option_value[taxonomy] = dict() option_value[taxonomy][to_int(term_id)] = { 'wpseo_title': get_value_by_key_in_dict(convert, 'meta_title', ''), 'wpseo_desc': get_value_by_key_in_dict(convert, 'meta_description', ''), 'wpseo_linkdex': 0, 'wpseo_content_score': 0 } data_set = { 'option_value': php_serialize(option_value) } where = { 'option_id': options_data['data'][0]['option_id'], 'option_name': 'wpseo_taxonomy_meta' } self.import_data_connector(self.create_update_query_connector('options', data_set, where), 'manufacturer') else: new_option_data = { 'option_name': 'wpseo_taxonomy_meta', 'option_value': php_serialize({ taxonomy: { to_int(term_id): { 'wpseo_title': get_value_by_key_in_dict(convert, 'meta_title', ''), 'wpseo_desc': get_value_by_key_in_dict(convert, 'meta_description', ''), 'wpseo_linkdex': 0, 'wpseo_content_score': 0 } } }), 'autoload': 'yes' } self.import_data_connector(self.create_insert_query_connector('options', new_option_data), 'manufacturer') return response_success(manufacturer_taxonomy_import) def after_manufacturer_import(self, manufacturer_id, convert, manufacturer, manufacturers_ext): return response_success() def addition_manufacturer_import(self, convert, manufacturer, manufacturers_ext): return response_success() # TODO: CATEGORY def prepare_categories_import(self): parent = super().prepare_categories_import() if self._notice['config']['seo'] or self._notice['config']['seo_301']: query = self.dict_to_create_table_sql(self.lecm_rewrite_table_construct()) self.query_data_connector({'type': 'query', 'query': query['query']}) return self def prepare_categories_export(self): return self def get_categories_main_export(self): id_src = self._notice['process']['categories']['id_src'] limit = self._notice['setting']['categories'] query = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_term_taxonomy as tx LEFT JOIN _DBPRF_terms AS t ON t.term_id = tx.term_id" " WHERE tx.taxonomy = 'product_cat' AND tx.term_id > " + to_str( id_src) + " AND t.term_id IS NOT NULL ORDER BY tx.term_id ASC LIMIT " + to_str(limit) } if self._notice['src']['support']['wpml']: query = { 'type': 'select', # 'query': "SELECT * FROM _DBPRF_term_taxonomy tt " # "LEFT JOIN _DBPRF_terms AS t ON t.term_id = tt.term_id " # "LEFT JOIN _DBPRF_icl_translations il ON tt.term_id = il.element_id " # "WHERE tt.term_id and il.`source_language_code` is NULL and il.`element_type` = 'tax_product_cat' and tt.taxonomy = 'product_cat' and tt.term_id > " + to_str( # id_src) + " ORDER BY tt.term_id ASC LIMIT " + to_str(limit), 'query': "SELECT * FROM _DBPRF_term_taxonomy tt " "LEFT JOIN _DBPRF_terms AS t ON t.term_id = tt.term_id " "LEFT JOIN _DBPRF_icl_translations il ON tt.term_taxonomy_id = il.element_id " "WHERE il.`element_type` = 'tax_product_cat' and il.`source_language_code` IS NULL and tt.taxonomy = 'product_cat' and tt.term_id > " + to_str( id_src) + " ORDER BY tt.term_id ASC LIMIT " + to_str(limit), } # categories = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query)}) categories = self.select_data_connector(query, 'categories') if not categories or categories['result'] != 'success': return response_error('could not get manufacturers main to export') return categories def get_categories_ext_export(self, categories): url_query = self.get_connector_url('query') category_ids = duplicate_field_value_from_list(categories['data'], 'term_id') parent_ids = duplicate_field_value_from_list(categories['data'], 'parent') cart_version = self.convert_version(self._notice['src']['config']['version'], 2) taxonomy_type = 'product_cat' if not categories.get('is_blog') else 'category' categories_ext_queries = { 'all_category': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_term_taxonomy as tx LEFT JOIN _DBPRF_terms AS t ON t.term_id = tx.term_id WHERE tx.taxonomy = '" + taxonomy_type + "' AND tx.term_id > 0 " }, 'seo_categories': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_term_taxonomy as tx LEFT JOIN _DBPRF_terms AS t ON t.term_id = tx.term_id " "WHERE tx.taxonomy = '" + taxonomy_type + "' AND tx.term_id IN " + self.list_to_in_condition(parent_ids) } } if cart_version > 255: categories_ext_queries['woocommerce_termmeta'] = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_termmeta WHERE term_id IN " + self.list_to_in_condition( category_ids) + " AND meta_key IN ('order', 'thumbnail_id', 'display_type')" } else: categories_ext_queries['woocommerce_termmeta'] = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_woocommerce_termmeta WHERE woocommerce_term_id IN " + self.list_to_in_condition( category_ids) + " AND meta_key IN ('order', 'thumbnail_id', 'display_type')" } # add wpml if self._notice['src']['support']['wpml']: categories_ext_queries['icl_translations'] = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_icl_translations WHERE element_type = 'tax_product_cat' and element_id IN " + self.list_to_in_condition( category_ids) } # categories_ext = self.get_connector_data(url_query, { # 'serialize': True, # 'query': json.dumps(categories_ext_queries) # }) categories_ext = self.get_connector_data(url_query, { 'serialize': True, 'query': json.dumps(categories_ext_queries) }) if not categories_ext or categories_ext['result'] != 'success': return response_warning() thumb_id_list = get_list_from_list_by_field(categories_ext['data']['woocommerce_termmeta'], 'meta_key', 'thumbnail_id') thumbnail_ids = duplicate_field_value_from_list(thumb_id_list, 'meta_value') thumb_ids_query = self.list_to_in_condition(thumbnail_ids) categories_ext_rel_queries = { 'post_meta': { 'type': 'select', 'query': "SELECT p.ID, p.post_title, pm.meta_value, p.guid FROM _DBPRF_posts AS p " "LEFT JOIN _DBPRF_postmeta AS pm ON pm.post_id = p.ID AND pm.meta_key = '_wp_attached_file' WHERE p.ID IN " + thumb_ids_query } # 'seo_category': array( # 'type': 'select', # 'query': "SELECT * FROM _DBPRF_options WHERE option_id = 235866", # ), } if self._notice['src']['support']['wpml']: trids = duplicate_field_value_from_list(categories_ext['data']['icl_translations'], 'trid') categories_ext_rel_queries['wpml_category_lang'] = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_icl_translations il " "LEFT JOIN _DBPRF_term_taxonomy as tx ON il.element_id = tx.term_id " "LEFT JOIN _DBPRF_terms AS t ON t.term_id = tx.term_id " "WHERE il.element_type = 'tax_product_cat' and il.trid IN " + self.list_to_in_condition(trids) } # add seo # if (self._notice['config']['seo']){ # ext_rel_seo_queries = model_seo->getCategoriesSeoExtRelQuery(this, categories, categories_ext) # categories_ext_rel_queries = array_merge(categories_ext_rel_queries, ext_rel_seo_queries) # } # add custom if categories_ext_rel_queries: # categories_ext_rel = self.get_connector_data(url_query, { # 'serialize': True, # 'query': json.dumps(categories_ext_rel_queries) # }) categories_ext_rel = self.select_multiple_data_connector(categories_ext_rel_queries, 'categories') if not categories_ext_rel or categories_ext_rel['result'] != 'success': return response_error() categories_ext = self.sync_connector_object(categories_ext, categories_ext_rel) return categories_ext def convert_category_export(self, category, categories_ext): category_data = self.construct_category() if not self.blog_running else self.construct_blog_category() # category_data = self.add_construct_default(category_data) parent = self.construct_category_parent() if not self.blog_running else self.construct_blog_category() parent['id'] = 0 if category['parent'] and to_int(category['parent']) > 0: parent_data = self.get_category_parent(category['parent']) if parent_data['result'] == 'success' and parent_data['data']: parent = parent_data['data'] category_path = img_meta = category_url = img_label = '' cart_version = self.convert_version(self._notice['src']['config']['version'], 2) if cart_version > 255: category_src = get_list_from_list_by_field(categories_ext['data']['woocommerce_termmeta'], 'term_id', category['term_id']) else: category_src = get_list_from_list_by_field(categories_ext['data']['woocommerce_termmeta'], 'woocommerce_term_id', category['term_id']) if category_src: category_img_id = self.get_value_metadata(category_src, 'thumbnail_id', 0) img_meta = get_list_from_list_by_field(categories_ext['data']['post_meta'], 'ID', category_img_id) if img_meta: img_label = img_meta[0]['post_title'] category_path = to_str(img_meta[0]['meta_value']) category_url = to_str(img_meta[0]['guid']).replace(category_path, '') category_data['id'] = category['term_id'] category_data['code'] = category['slug'] category_data['name'] = category['name'] category_data['description'] = category['description'] category_data['parent'] = parent category_data['active'] = True category_data['thumb_image']['label'] = img_label category_data['thumb_image']['url'] = category_url category_data['thumb_image']['path'] = category_path category_data['sort_order'] = 1 category_data['created_at'] = get_current_time() category_data['updated_at'] = get_current_time() category_data['category'] = category category_data['categories_ext'] = categories_ext # todo: woo2woo category_data['display_type'] = self.get_value_metadata(category_src, 'display_type', '') if self._notice['src']['support']['wpml']: trid = get_row_value_from_list_by_field(categories_ext['data']['icl_translations'], 'element_id', category['term_taxonomy_id'], 'trid') if trid: languages_data = get_list_from_list_by_field(categories_ext['data']['wpml_category_lang'], 'trid', trid) if languages_data: for language_data in languages_data: category_new_data = self.construct_category_lang() category_new_data['id'] = language_data['term_id'] category_new_data['code'] = language_data['slug'] category_new_data['name'] = language_data['name'] category_new_data['description'] = language_data['description'] if to_int(language_data['term_id']) == to_int(category['term_id']): category_data['language_default'] = language_data['language_code'] elif 'language_default' not in category_data and not language_data['source_language_code']: category_data['language_default'] = language_data['language_code'] category_data['languages'][language_data['language_code']] = category_new_data else: category_language_data = self.construct_category_lang() language_id = self._notice['src']['language_default'] category_language_data['name'] = category['name'] category_language_data['description'] = category['description'] category_data['languages'][language_id] = category_language_data query_wpseo = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_options` WHERE `option_name` = 'wpseo_taxonomy_meta'" } options_data = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query_wpseo)}) if options_data and options_data['data']: option_value = php_unserialize(options_data['data'][0]['option_value']) if option_value and 'product_cat' in option_value: if to_int(category['term_id']) in option_value['product_cat']: category_data['meta_title'] = get_value_by_key_in_dict(option_value['product_cat'][to_int(category['term_id'])], 'wpseo_title', '') category_data['meta_description'] = get_value_by_key_in_dict(option_value['product_cat'][to_int(category['term_id'])], 'wpseo_desc', '') category_data['meta_keyword'] = get_value_by_key_in_dict(option_value['product_cat'][to_int(category['term_id'])], 'wpseo_focuskw', '') # if self._notice['config']['seo']: detect_seo = self.detect_seo() category_data['seo'] = getattr(self, 'categories_' + detect_seo)(category, categories_ext) return response_success(category_data) def get_category_parent(self, parent_id): type_map = self.TYPE_CATEGORY if not self.blog_running else self.TYPE_CATEGORY_BLOG category_exist = self.select_map(self._migration_id, type_map, parent_id) if category_exist: return response_success({ 'id': parent_id, 'code': '' }) taxonomy_type = 'product_cat' if not self.blog_running else 'category' query = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_term_taxonomy as tx LEFT JOIN _DBPRF_terms AS t ON t.term_id = tx.term_id " "WHERE tx.taxonomy = '" + taxonomy_type + "' AND tx.term_id = " + to_str(parent_id) } if self._notice['src']['support']['wpml']: query = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_term_taxonomy tt LEFT JOIN _DBPRF_terms AS t ON t.term_id = tt.term_id " "LEFT JOIN _DBPRF_icl_translations il ON tt.term_taxonomy_id = il.element_id " "WHERE il.`element_type` = 'tax_product_cat' AND il.`source_language_code` IS NULL AND tt.taxonomy = '" + taxonomy_type + "' and tt.term_id = " + to_str(parent_id), } categories = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query)}) if not categories or categories['result'] != 'success': return response_error('could not get category parent to export') if categories and categories['data']: category = categories['data'][0] categories_ext = self.get_categories_ext_export(categories) category_convert = self.convert_category_export(category, categories_ext) return category_convert return response_error('could not get category parent to export') def get_category_id_import(self, convert, category, categories_ext): return category['term_id'] def check_category_import(self, convert, category, categories_ext): id_imported = self.get_map_field_by_src(self.TYPE_CATEGORY, convert['id'], convert['code'], lang = self._notice['target']['language_default']) return True if id_imported else False def router_category_import(self, convert, category, categories_ext): return response_success('category_import') def before_category_import(self, convert, category, categories_ext): return response_success() def category_import(self, convert, category, categories_ext): slug = self.sanitize_title(convert['name']) language_code = convert.get('language_code') if self.is_wpml() and not language_code or (self.is_polylang() and not language_code): language_code = self._notice['target']['language_default'] category_term = { 'name': convert['name'], 'slug': convert['code'] if convert['code'] else slug, 'term_group': 0, } category_term_query = self.create_insert_query_connector('terms', category_term) term_id = self.import_data_connector(category_term_query, 'category') if not term_id: return response_warning('category' + to_str(convert['id']) + ' import false.') taxonomy = 'product_cat' category_taxonomy = { 'term_id': term_id, 'taxonomy': taxonomy, 'description': get_value_by_key_in_dict(convert, 'description', ''), 'parent': 0, 'count': 0 } category_taxonomy_query = self.create_insert_query_connector('term_taxonomy', category_taxonomy) category_taxonomy_import = self.import_category_data_connector(category_taxonomy_query, True, convert['id']) if not category_taxonomy_import: return response_warning('manufacturer ' + to_str(convert['id']) + ' import false.') self.insert_map(self.TYPE_CATEGORY, convert['id'], category_taxonomy_import, slug, term_id, convert['name'],language_code) all_queries = list() meta_insert = { 'term_id': term_id, 'meta_key': 'display_type', 'meta_value': convert.get('display_type', '') } all_queries.append(self.create_insert_query_connector('termmeta', meta_insert)) if all_queries: self.import_multiple_data_connector(all_queries, 'category') return response_success() def get_new_trid(self): query = { 'type': 'select', 'query': "SELECT max(trid) as trid FROM _DBPRF_icl_translations" } trid = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query)}) new_trid = 1 if trid['data']: new_trid = to_int(trid['data'][0]['trid']) + 1 return new_trid def after_category_import(self, category_id, convert, category, categories_ext): return response_success() def addition_category_import(self, convert, category, categories_ext): return response_success() # TODO: PRODUCT def prepare_products_import(self): parent = super().prepare_products_import() if self._notice['config']['seo'] or self._notice['config']['seo_301']: query = self.dict_to_create_table_sql(self.lecm_rewrite_table_construct()) self.query_data_connector({'type': 'query', 'query': query['query']}) if not self._notice['config']['add_new']: file_name = get_pub_path() + '/media/' + to_str(self._migration_id) + '/variants.csv' if os.path.isfile(file_name): os.remove(file_name) return self def prepare_products_export(self): return self def get_products_main_export(self): id_src = self._notice['process']['products']['id_src'] limit = self._notice['setting']['products'] query = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_posts WHERE ID > " + to_str(id_src) + " AND post_type = 'product' AND post_status NOT IN ('inherit','auto-draft') ORDER BY ID ASC LIMIT " + to_str(limit), } if self._notice['src']['support']['wpml']: query = { 'type': 'select', # 'query': "SELECT * FROM _DBPRF_posts p LEFT JOIN _DBPRF_icl_translations il ON p.ID = il.element_id " # "WHERE il.`element_type` = 'post_product' and il.`source_language_code` is NULL and p.ID and p.ID > " + to_str( # id_src) + " AND p.post_type = 'product' AND p.post_status NOT IN ('inherit','auto-draft') ORDER BY p.ID ASC LIMIT " + to_str( # limit), 'query': "SELECT * FROM _DBPRF_posts p LEFT JOIN _DBPRF_icl_translations il ON p.ID = il.element_id " "WHERE il.`source_language_code` is NULL and il.`element_type` = 'post_product' AND p.ID > " + to_str( id_src) + " AND p.post_type = 'product' AND p.post_status NOT IN ('inherit','auto-draft') ORDER BY p.ID ASC LIMIT " + to_str( limit), } # products = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query)}) products = self.select_data_connector(query, 'products') if not products or products['result'] != 'success': return response_error() return products def get_products_ext_export(self, products): url_query = self.get_connector_url('query') product_ids = duplicate_field_value_from_list(products['data'], 'ID') product_id_con = self.list_to_in_condition(product_ids) # product_id_query = self.product_to_in_condition_seourl(product_ids) linked = self.product_to_in_condition_linked(product_ids) product_ext_queries = { 'post_variant': { 'type': "select", 'query': "SELECT * FROM _DBPRF_posts WHERE post_type = 'product_variation' AND post_parent IN " + product_id_con, }, 'term_relationship': { 'type': "select", 'query': "SELECT * FROM _DBPRF_term_relationships AS tr " "LEFT JOIN _DBPRF_term_taxonomy AS tx ON tx.term_taxonomy_id = tr.term_taxonomy_id " "LEFT JOIN _DBPRF_terms AS t ON t.term_id = tx.term_id " "WHERE tr.object_id IN " + product_id_con, }, 'post_grouped': { 'type': "select", 'query': "SELECT * FROM _DBPRF_posts WHERE post_parent IN " + product_id_con + " AND post_type = 'product'", }, 'parent_link': { 'type': "select", 'query': "SELECT * FROM _DBPRF_postmeta WHERE meta_key IN ('_upsell_ids','_crosssell_ids') AND meta_value " + linked }, } if self._notice['src']['support']['wpml']: product_ext_queries['icl_translations'] = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_icl_translations WHERE element_type = 'post_product' and element_id IN " + product_id_con } # products_ext = self.get_connector_data(url_query, { # 'serialize': True, 'query': json.dumps(product_ext_queries) # }) products_ext = self.select_multiple_data_connector(product_ext_queries, 'products') if (not products_ext) or products_ext['result'] != 'success': return response_error() pro_child_ids = duplicate_field_value_from_list(products_ext['data']['post_variant'], 'ID') all_product_ids = self.list_to_in_condition(list(set(pro_child_ids + product_ids))) variant_id_query = self.list_to_in_condition(pro_child_ids) taxonomy_duplicate = duplicate_field_value_from_list(products_ext['data']['term_relationship'], 'taxonomy') attrs_taxonomy = self.get_list_from_list_by_field_as_first_key(taxonomy_duplicate, '', 'pa_') attrs_name = list() for attr_taxonomy in attrs_taxonomy: attrs_name.append(self.substr_replace(attr_taxonomy, '', 0, 3)) attr_name_query = self.list_to_in_condition(attrs_name) attr_values = duplicate_field_value_from_list(products_ext['data']['term_relationship'], 'term_id') attr_values_query = self.list_to_in_condition(attr_values) product_ext_rel_queries = { 'post_meta': { 'type': "select", 'query': "SELECT * FROM _DBPRF_postmeta WHERE post_id IN " + all_product_ids, }, 'woocommerce_attribute_taxonomies': { 'type': "select", 'query': "SELECT * FROM _DBPRF_woocommerce_attribute_taxonomies WHERE attribute_name IN " + attr_name_query, }, 'variation_term_relationship': { 'type': "select", 'query': "SELECT * FROM _DBPRF_term_relationships AS tr " "LEFT JOIN _DBPRF_term_taxonomy AS tx ON tx.term_taxonomy_id = tr.term_taxonomy_id " "LEFT JOIN _DBPRF_terms AS t ON t.term_id = tx.term_id " "WHERE tr.object_id IN " + variant_id_query, }, 'term_attribute': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_terms WHERE term_id IN " + attr_values_query, } } if self._notice['src']['support']['wpml']: trids = duplicate_field_value_from_list(products_ext['data']['icl_translations'], 'trid') product_ext_rel_queries['wpml_product_lang'] = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_icl_translations il " "LEFT JOIN _DBPRF_posts as p ON il.element_id = p.ID " "WHERE il.element_type = 'post_product' and il.trid IN " + self.list_to_in_condition(trids) } product_ext_rel_queries['wpml_product_meta'] = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_postmeta WHERE post_id IN (SELECT element_id FROM _DBPRF_icl_translations WHERE element_type = 'post_product' and trid IN " + self.list_to_in_condition(trids) + ")" } product_ext_rel_queries['wpml_term_relationship'] = { 'type': "select", 'query': "SELECT * FROM _DBPRF_term_relationships AS tr " "LEFT JOIN _DBPRF_term_taxonomy AS tx ON tx.term_taxonomy_id = tr.term_taxonomy_id " "LEFT JOIN _DBPRF_terms AS t ON t.term_id = tx.term_id WHERE tr.object_id IN (SELECT element_id FROM _DBPRF_icl_translations WHERE element_type = 'post_product' and trid IN " + self.list_to_in_condition(trids) + ")", } product_ext_rel_queries['attributes_icl_translations'] = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_icl_translations il " "LEFT JOIN _DBPRF_term_taxonomy as tx ON il.element_id = tx.term_id " "LEFT JOIN _DBPRF_terms AS t ON t.term_id = tx.term_id " "WHERE il.element_type IN " + self.wpml_attributes_to_in_condition( attrs_taxonomy) } # products_ext_rel = self.get_connector_data(url_query, { # 'serialize': True, 'query': json.dumps(product_ext_rel_queries) products_ext_rel = self.select_multiple_data_connector(product_ext_rel_queries, 'products') if (not products_ext_rel) or products_ext_rel['result'] != 'success': return response_error() thumbnail_id_list = get_list_from_list_by_field(products_ext_rel['data']['post_meta'], 'meta_key', '_thumbnail_id') thumbnail_ids = duplicate_field_value_from_list(thumbnail_id_list, 'meta_value') gallery_ids = gallery_ids_src = list() gallery_list = get_list_from_list_by_field(products_ext_rel['data']['post_meta'], 'meta_key', '_product_image_gallery') if gallery_list: for gallery in gallery_list: if 'meta_value' in gallery and gallery['meta_value']: images_ids = gallery['meta_value'].split(',') if images_ids: gallery_ids = list(set(gallery_ids + images_ids)) for id in gallery_ids: if id != '': gallery_ids_src.append(id) all_images_ids = list(set(thumbnail_ids + gallery_ids_src)) all_images_ids_query = self.list_to_in_condition(all_images_ids) product_ext_rel_third_queries = { 'image': { 'type': 'select', 'query': "SELECT p.ID, p.post_title, pm.meta_value, p.guid FROM _DBPRF_posts AS p " "LEFT JOIN _DBPRF_postmeta AS pm ON pm.post_id = p.ID AND pm.meta_key = '_wp_attached_file' " "WHERE p.ID IN " + all_images_ids_query, } } products_ext_third = self.get_connector_data(url_query, { 'serialize': True, 'query': json.dumps(product_ext_rel_third_queries) }) if (not products_ext_third) or products_ext_third['result'] != 'success': return response_error() products_ext1 = self.sync_connector_object(products_ext_rel, products_ext_third) products_ext = self.sync_connector_object(products_ext, products_ext1) return products_ext def convert_product_export(self, product, products_ext): product_meta = get_list_from_list_by_field(products_ext['data']['post_meta'], 'post_id', product['ID']) product_data = self.construct_product() product_data = self.add_construct_default(product_data) product_data['id'] = product['ID'] product_data['code'] = product['post_name'] product_data['sku'] = self.get_value_metadata(product_meta, '_sku') # todo: get type prd virtual product_type = get_row_value_from_list_by_field(product_meta, 'meta_key', '_virtual', 'meta_value') if product_type == 'yes': product_data['type'] = 'virtual' product_price = '' if to_decimal(self.get_value_metadata(product_meta, '_regular_price', 0.0000)) > 0: product_price = self.get_value_metadata(product_meta, '_regular_price', 0.0000) else: product_price = self.get_value_metadata(product_meta, '_price', 0.0000) if product_price == '' or product_price == self.get_value_metadata(product_meta, '_min_variation_sale_price', 0.0000): product_price = self.get_value_metadata(product_meta, '_min_variation_regular_price', 0.0000) if product_price == '' or not product_price: product_price = 0 product_data['price'] = product_price product_data['weight'] = self.get_value_metadata(product_meta, '_weight', 0.0000) product_data['length'] = self.get_value_metadata(product_meta, '_length', 0.0000) product_data['width'] = self.get_value_metadata(product_meta, '_width', 0.0000) product_data['height'] = self.get_value_metadata(product_meta, '_height', 0.0000) product_data['status'] = True if product['post_status'] == "publish" else False product_data['manage_stock'] = True if self.get_value_metadata(product_meta, '_manage_stock', 'no') == "yes" else False if self.is_woo2woo(): product_data['is_in_stock'] = self.get_value_metadata(product_meta, '_stock_status', 'instock') product_data['sold_individually'] = self.get_value_metadata(product_meta, '_sold_individually', '') product_data['purchase_note'] = self.get_value_metadata(product_meta, '_purchase_note', '') else: product_data['is_in_stock'] = True if self.get_value_metadata(product_meta, '_stock_status', 'instock') == "instock" else False product_data['qty'] = to_int(to_decimal(self.get_value_metadata(product_meta, '_stock', 0))) if to_decimal(self.get_value_metadata(product_meta, '_stock', 0)) > 0 else 0 product_data['created_at'] = convert_format_time(product['post_date']) product_data['updated_at'] = convert_format_time(product['post_modified']) product_data['name'] = product['post_title'] product_data['description'] = product['post_content'] product_data['short_description'] = product['post_excerpt'] product_data['menu_order'] = product['menu_order'] product_data['sort_order'] = product['menu_order'] product_data['backorders'] = self.get_value_metadata(product_meta, '_backorders', 'no') product_data['meta_description'] = self.get_value_metadata(product_meta, '_yoast_wpseo_metadesc', '') product_data['meta_title'] = self.get_value_metadata(product_meta, '_yoast_wpseo_title', '') if product_data['meta_title']: product_data['meta_title'] = product_data['meta_title'].replace('%%title%%', product_data['name']).replace('%%page%%', '').replace('%%sep%%', '-').replace('%%sitename%%', '') # image_ thumbnail_id = self.get_value_metadata(product_meta, '_thumbnail_id', 0) if thumbnail_id: thumbnail_src = get_list_from_list_by_field(products_ext['data']['image'], 'ID', thumbnail_id) if thumbnail_src: product_data['thumb_image']['label'] = thumbnail_src[0]['post_title'] product_data['thumb_image']['url'] = self._notice['src']['cart_url'].rstrip('/') + '/wp-content/uploads/' + to_str(thumbnail_src[0]['meta_value']).lstrip('/') product_data['thumb_image']['url'] = to_str(product_data['thumb_image']['url']).replace('uploads/uploads', 'uploads') gallery_ids = self.get_value_metadata(product_meta, '_product_image_gallery', '') if gallery_ids: gallery_ids = gallery_ids.split(',') for gallery_id in gallery_ids: image_gallery_src = get_list_from_list_by_field(products_ext['data']['image'], 'ID', gallery_id) product_image_data = self.construct_product_image() if image_gallery_src: product_image_data['label'] = image_gallery_src[0]['post_title'] product_image_data['url'] = self._notice['src']['cart_url'].rstrip('/') + '/wp-content/uploads/' + image_gallery_src[0]['meta_value'].lstrip('/') product_image_data['url'] = to_str(product_image_data['url']).replace('uploads/uploads', 'uploads') product_data['images'].append(product_image_data) sale_price = self.get_value_metadata(product_meta, '_sale_price', '') if sale_price != '': product_data['special_price']['price'] = to_decimal(sale_price) start_date = self.get_value_metadata(product_meta, '_sale_price_dates_from', '') if start_date: product_data['special_price']['start_date'] = convert_format_time(start_date) end_date = self.get_value_metadata(product_meta, '_sale_price_dates_to', '') if end_date: product_data['special_price']['end_date'] = convert_format_time(self.get_value_metadata(product_meta, '_sale_price_dates_to', '')) else: product_data['special_price']['price'] = self.get_value_metadata(product_meta, '_min_variation_sale_price', 0.0000) if not product_data['special_price']['price']: product_data['special_price']['price'] = 0 crosssell_ids = self.get_value_metadata(product_meta, '_crosssell_ids', '') if crosssell_ids: crosssell_ids_data = php_unserialize(crosssell_ids) if crosssell_ids_data: for crosssell_id in crosssell_ids_data: relation = self.construct_product_relation() relation['id'] = crosssell_id relation['type'] = self.PRODUCT_CROSS product_data['relate']['children'].append(relation) parent_crosssell_list = get_list_from_list_by_field(products_ext['data']['parent_link'], 'meta_key', '_crosssell_ids') if parent_crosssell_list: for parent_crosssell in parent_crosssell_list: if parent_crosssell['meta_value'].find(':' + to_str(product['ID']) + ';') != -1: relation = self.construct_product_relation() relation['id'] = parent_crosssell['post_id'] relation['type'] = self.PRODUCT_CROSS product_data['relate']['parent'].append(relation) upsell_ids = self.get_value_metadata(product_meta, '_upsell_ids', '') if upsell_ids: upsell_ids_data = php_unserialize(upsell_ids) if upsell_ids_data: for upsell_id in upsell_ids_data: relation = self.construct_product_relation() relation['id'] = upsell_id relation['type'] = self.PRODUCT_UPSELL product_data['relate']['children'].append(relation) parent_upsell_list = get_list_from_list_by_field(products_ext['data']['parent_link'], 'meta_key', '_upsell_ids') if parent_upsell_list: for parent_upsell in parent_upsell_list: if parent_upsell['meta_value'].find(':' + to_str(product['ID']) + ';') != -1: relation = self.construct_product_relation() relation['id'] = parent_upsell['post_id'] relation['type'] = self.PRODUCT_UPSELL product_data['relate']['parent'].append(relation) product_data['tax']['code'] = self.get_value_metadata(product_meta, '_tax_class', 'standard') if self.get_value_metadata(product_meta, '_tax_status', 'taxable') != 'none' else None product_data['tax']['status'] = self.get_value_metadata(product_meta, '_tax_status', 'taxable') # category product term_relationship = get_list_from_list_by_field(products_ext['data']['term_relationship'], 'object_id', product['ID']) category_src = get_list_from_list_by_field(term_relationship, 'taxonomy', 'product_cat') if category_src: for product_category in category_src: product_category_data = self.construct_product_category() product_category_data['id'] = product_category['term_id'] product_category_data['code'] = product_category['slug'] product_data['categories'].append(product_category_data) if self._notice['src']['support']['manufacturers']: manu_src = get_row_from_list_by_field(term_relationship, 'taxonomy', 'product_brand') if not manu_src: manu_src = get_row_from_list_by_field(term_relationship, 'taxonomy', 'pwb-brand') if manu_src: product_manufacturer_data = dict() product_manufacturer_data['id'] = manu_src['term_id'] product_manufacturer_data['name'] = manu_src['name'] product_manufacturer_data['code'] = manu_src['slug'] product_data['manufacturer'] = product_manufacturer_data # tags product_tags = get_list_from_list_by_field(term_relationship, 'taxonomy', 'product_tag') if product_tags: tags = list() for product_tag in product_tags: tags.append(product_tag['name']) if tags: product_data['tags'] = ','.join(tags) # if self._notice['config']['seo']: detect_seo = self.detect_seo() product_data['seo'] = getattr(self, 'products_' + detect_seo)(product, products_ext) # TODO: convert product languages if self._notice['src']['support']['wpml']: trid = get_row_value_from_list_by_field(products_ext['data']['icl_translations'], 'element_id', product['ID'], 'trid') if trid: language_datas = get_list_from_list_by_field(products_ext['data']['wpml_product_lang'], 'trid', trid) if language_datas: for language_data in language_datas: if not language_data['post_title']: continue meta_language_datas = get_list_from_list_by_field(products_ext['data']['wpml_product_meta'], 'post_id', language_data['ID']) term_relationship_language = get_list_from_list_by_field(products_ext['data']['wpml_term_relationship'], 'object_id', language_data['ID']) product_new_data = self.construct_product_lang() product_new_data['name'] = language_data['post_title'] product_new_data['code'] = language_data['post_name'] product_new_data['description'] = language_data['post_content'] product_new_data['short_description'] = language_data['post_excerpt'] product_new_data['meta_description'] = self.get_value_metadata(meta_language_datas, '_yoast_wpseo_metadesc', '') product_new_data['meta_title'] = self.get_value_metadata(meta_language_datas, '_yoast_wpseo_title', '') if product_new_data['meta_title']: product_new_data['meta_title'] = product_new_data['meta_title'].replace('%%title%%', product_new_data['name']).replace('%%page%%', '').replace('%%sep%%', '-').replace('%%sitename%%', '') wpml_product_tags = get_list_from_list_by_field(term_relationship_language, 'taxonomy', 'product_tag') if wpml_product_tags: wpml_tags = list() for wpml_product_tag in wpml_product_tags: wpml_tags.append(wpml_product_tag['name']) if wpml_tags: product_new_data['tags'] = ','.join(wpml_tags) if not language_data['source_language_code']: product_data['language_default'] = language_data['language_code'] product_data['languages'][language_data['language_code']] = product_new_data else: product_language_data = self.construct_product_lang() product_language_data['name'] = product['post_title'] product_language_data['description'] = product['post_content'] product_language_data['short_description'] = product['post_excerpt'] language_id = self._notice['src']['language_default'] product_data['languages'][language_id] = product_language_data # attribute product product_child_src = get_list_from_list_by_field(products_ext['data']['post_variant'], 'post_parent', product['ID']) # todo: attribute product_attribute = get_row_value_from_list_by_field(product_meta, 'meta_key', '_product_attributes', 'meta_value') product_attribute = php_unserialize(product_attribute) if isinstance(product_attribute, str): product_attribute = php_unserialize(product_attribute) src_option_values = get_list_from_list_by_field(products_ext['data']['term_relationship'], 'object_id', product['ID']) attribute_variants = list() if product_attribute: for attribute_key, attribute in product_attribute.items(): if to_int(attribute.get('is_taxonomy')) > 0: woo_attribute = get_row_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', to_str(attribute_key).replace('pa_', '')) if not woo_attribute: woo_attribute = get_row_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', to_str(attribute['name']).replace('pa_', '')) else: woo_attribute = None if woo_attribute: # attributes attribute_data = self.construct_product_attribute() attribute_data['option_id'] = woo_attribute['attribute_id'] option_code = to_str(woo_attribute['attribute_name']).lower() attribute_data['option_code'] = option_code.strip() attribute_data['option_type'] = woo_attribute['attribute_type'] attribute_data['option_name'] = woo_attribute['attribute_label'] attribute_data['option_group'] = woo_attribute['attribute_orderby'] attribute_data['is_visible'] = attribute.get('is_visible', 'visible') attribute_data['is_variation'] = True if to_int(attribute.get('is_variation')) == 1 else False attribute_data['is_taxonomy'] = True if to_int(attribute.get('is_taxonomy')) == 1 else False # attribute language attribute_language_data = self.construct_product_option_lang() attribute_language_data['option_name'] = woo_attribute['attribute_label'] language_id = self._notice['src']['language_default'] attribute_data['option_languages'][language_id] = attribute_language_data # attribute values tmp_values = list() desc = list() for option_value in src_option_values: attribute_name = 'pa_' + to_str(woo_attribute['attribute_name']).lower() if 'taxonomy' in option_value: if option_value['taxonomy'] == attribute_name: woo_term_values = get_list_from_list_by_field( products_ext['data']['term_attribute'], 'term_id', option_value['term_id']) if woo_term_values: for woo_term in woo_term_values: attribute_value = woo_term['name'] if woo_attribute['attribute_type'] in ['select', 'alg_wc_civs_image']: option_values = to_str(woo_term['name']).split('|') if option_values and to_len(option_values) > 1: attribute_value = ';'.join(option_values) tmp_values.append(attribute_value) desc.append(option_value['description']) values = list(map(lambda x: x.strip(), tmp_values)) if values and to_len(values) > 1: attribute_data['option_type'] = self.OPTION_MULTISELECT attribute_data['option_value_name'] = ';'.join(values) attribute_data['option_value_description'] = ';'.join(desc) attribute_data['option_value_languages'][self._notice['src']['language_default']] = { 'option_value_name': ';'.join(values) } if (to_int(attribute.get('is_variation')) == 1 or to_str(attribute.get('variation')) == 'yes') and not self.is_woo2woo(): attribute_variants.append(attribute_data) else: product_data['attributes'].append(attribute_data) else: if ('is_visible' in attribute and to_int(attribute['is_visible']) == 1) or ('visible' in attribute and attribute['visible'] == 'yes'): attribute_data = self.construct_product_attribute() attribute_data['option_id'] = None option_code = to_str(attribute['name']).lower() attribute_data['option_code'] = option_code.lower().strip() attribute_data['option_type'] = 'text' attribute_data['option_name'] = attribute['name'] attribute_data['option_group'] = 'menu_order' attribute_data['is_visible'] = attribute.get('is_visible', 'visible') attribute_data['is_variation'] = True if to_int(attribute.get('is_variation')) == 1 else False # attribute language attribute_language_data = self.construct_product_option_lang() attribute_language_data['option_name'] = attribute['name'] language_id = self._notice['src']['language_default'] attribute_data['option_languages'][language_id] = attribute_language_data # attribute values attribute_value = attribute['value'] if attribute_value and attribute_value != '': option_values = list() if isinstance(attribute_value, dict): for key, attr_value in attribute_value.items(): option_values.append(attr_value) else: option_values = attribute_value.split('|') if option_values and to_len(option_values) > 1: attribute_data['option_type'] = 'multiselect' option_values = list(map(lambda x: x.strip(), option_values)) attribute_value = ';'.join(option_values) attribute_data['option_value_name'] = attribute_value attribute_data['option_value_languages'][self._notice['src']['language_default']] = { 'option_value_name': attribute_value } # product_data['attributes'].append(attribute_data) else: attribute_data = self.construct_product_attribute() attribute_data['option_id'] = None option_code = to_str(attribute['name']).lower() attribute_data['option_code'] = option_code.lower().strip() attribute_data['option_type'] = 'text' attribute_data['option_name'] = attribute['name'] attribute_data['option_group'] = 'menu_order' attribute_data['is_visible'] = attribute.get('is_visible', 'visible') attribute_data['is_variation'] = True if to_int(attribute.get('is_variation')) == 1 else False # attribute language attribute_language_data = self.construct_product_option_lang() attribute_language_data['option_name'] = attribute['name'] language_id = self._notice['src']['language_default'] attribute_data['option_languages'][language_id] = attribute_language_data # attribute values option_values = attribute['value'] if option_values != '': option_values = option_values.split('|') if option_values and to_len(option_values) > 1: attribute_data['option_type'] = self.OPTION_MULTISELECT option_values = list(map(lambda x: x.strip(), option_values)) option_values = ';'.join(option_values) attribute_data['option_value_name'] = option_values attribute_data['option_value_languages'][self._notice['src']['language_default']] = { 'option_value_name': option_values } if (to_int(attribute.get('is_variation')) == 1 or to_str(attribute.get('variation')) == 'yes') and not self.is_woo2woo(): attribute_variants.append(attribute_data) else: product_data['attributes'].append(attribute_data) # end # todo: plugin add-ons if self._notice['src']['support'].get('addons') and not self.is_woo2woo(): product_addons = get_row_value_from_list_by_field(product_meta, 'meta_key', '_product_addons', 'meta_value') product_addons = php_unserialize(product_addons) if product_addons and to_len(product_addons) > 0: for product_addon in product_addons: if not product_addon.get('options') or to_len(product_addon['options']) == 0: continue if product_addon.get('type') == 'radiobutton': option_type = self.OPTION_RADIO else: option_type = self.OPTION_SELECT product_option = self.construct_product_option() product_option['code'] = self.convert_attribute_code(product_addon.get('name')) product_option['option_code'] = self.convert_attribute_code(product_addon.get('name')) product_option['option_name'] = product_addon.get('name') product_option['type'] = option_type product_option['position'] = product_addon.get('position') product_option['required'] = True if product_addon.get('required') and to_int(product_addon.get('required')) == 1 else False product_addon_options = list() if isinstance(product_addon.get('options'), dict): for key, product_addon_value in product_addon['options'].items(): product_addon_options.append(product_addon_value) else: product_addon_options = product_addon.get('options') for product_addon_value in product_addon_options: product_option_value = self.construct_product_option_value() product_option_value['code'] = self.convert_attribute_code(product_addon_value.get('label')) product_option_value['option_value_code'] = self.convert_attribute_code(product_addon_value.get('label')) product_option_value['option_value_name'] = product_addon_value.get('label') product_option_value['option_value_price'] = product_addon_value.get('price') if 'Color' in product_addon.get('name', '') or 'Colour' in product_addon.get('name', ''): if 'RNBP' in product_addon_value.get('label', ''): product_option_value['thumb_image']['path'] = self.convert_attribute_code(to_str(product_addon_value.get('label')).replace(' (RNBP)', '')) + '.jpg' product_option_value['thumb_image']['url'] = self._notice['src']['cart_url'].rstrip('/') + '/assets/blind-images/rnbp/' product_option['values'].append(product_option_value) product_data['options'].append(product_option) # todo: downloadable product_downloadables = get_row_value_from_list_by_field(product_meta, 'meta_key', '_downloadable_files', 'meta_value') product_downloadables = php_unserialize(product_downloadables) if product_downloadables: product_data['type'] = self.PRODUCT_DOWNLOAD for key, product_downloadable in product_downloadables.items(): download_data = self.construct_product_downloadable() download_data['limit'] = get_row_value_from_list_by_field(product_meta, 'meta_key', '_download_limit', 'meta_value') download_data['max_day'] = get_row_value_from_list_by_field(product_meta, 'meta_key', '_download_expiry', 'meta_value') name_file = to_str(product_downloadable['file']).split('/') if product_downloadable.get('file') else None if self._notice['src']['cart_url'] in product_downloadable['file'] and name_file: download_data['name'] = to_str(product_downloadable['file']).split('/') download_data['path'] = 'woocommerce/' + to_str(name_file[to_len(name_file) - 1]).lower() else: download_data['name'] = product_downloadable['name'] download_data['path'] = product_downloadable['file'] # Thieu max_day,limit product_data['downloadable'].append(download_data) # todo: group product child_group_product = self.get_value_metadata(product_meta, '_children', '') if child_group_product: child_group_product = php_unserialize(child_group_product) if child_group_product and to_len(child_group_product) > 0: for child_group_product_id in child_group_product: product_data['group_child_ids'].append({ 'id': child_group_product_id }) product_data['type'] = self.PRODUCT_GROUP # todo: child product product_child_src = get_list_from_list_by_field(products_ext['data']['post_variant'], 'post_parent', product['ID']) all_child = dict() child_attributes = dict() if product_child_src: product_data['type'] = self.PRODUCT_CONFIG for product_child in product_child_src: child_attributes[product_child['ID']] = dict() child_data = self.construct_product_child() child_data = self.add_construct_default(child_data) child_meta = get_list_from_list_by_field(products_ext['data']['post_meta'], 'post_id', product_child['ID']) child_data['id'] = product_child['ID'] child_data['sku'] = self.get_value_metadata(child_meta, '_sku', '') if self.get_value_metadata(child_meta, '_sku', '') else self.get_value_metadata(product_meta, '_sku', '') child_data['code'] = product_child['post_name'] child_product_price = '' if self.get_value_metadata(child_meta, '_regular_price', ''): child_product_price = self.get_value_metadata(child_meta, '_regular_price') else: if self.get_value_metadata(child_meta, '_price', ''): child_product_price = self.get_value_metadata(child_meta, '_price', 0.0000) else: child_product_price = 0 if child_product_price == '' or not child_product_price: child_product_price = 0 child_data['price'] = child_product_price child_data['weight'] = self.get_value_metadata(child_meta, '_weight') if self.get_value_metadata(child_meta, '_weight') else product_data['weight'] child_data['length'] = self.get_value_metadata(child_meta, '_length') if self.get_value_metadata(child_meta, '_length') else product_data['length'] child_data['width'] = self.get_value_metadata(child_meta, '_width') if self.get_value_metadata(child_meta, '_width') else product_data['width'] child_data['height'] = self.get_value_metadata(child_meta, '_height') if self.get_value_metadata(child_meta, '_height') else product_data['height'] child_data['status'] = True if product_child['post_status'] == "publish" else False child_data['manage_stock'] = True if self.get_value_metadata(child_meta, '_manage_stock') == 'yes' else False if self.is_woo2woo(): child_data['is_in_stock'] = self.get_value_metadata(child_meta, '_stock_status', 'instock') child_data['sold_individually'] = self.get_value_metadata(child_meta, '_sold_individually', '') child_data['purchase_note'] = self.get_value_metadata(child_meta, '_purchase_note', '') else: child_data['is_in_stock'] = True if self.get_value_metadata(child_meta, '_stock_status', 'instock') == "instock" else False child_data['qty'] = to_int(to_decimal(self.get_value_metadata(child_meta, '_stock'))) if self.get_value_metadata(child_meta, '_stock') else 0 child_data['created_at'] = convert_format_time(product_child['post_date']) child_data['updated_at'] = convert_format_time(product_child['post_modified']) child_data['name'] = product_child['post_title'] child_data['description'] = self.get_value_metadata(child_meta, '_variation_description') child_data['tax']['code'] = self.get_value_metadata(child_meta, '_tax_class', 'standard') child_data['short_description'] = '' # image_ thumbnail_id = self.get_value_metadata(child_meta, '_thumbnail_id') if thumbnail_id: thumbnail_src = get_list_from_list_by_field(products_ext['data']['image'], 'ID', thumbnail_id) if thumbnail_src: child_data['thumb_image']['label'] = thumbnail_src[0]['post_title'] child_data['thumb_image']['path'] = thumbnail_src[0]['meta_value'] child_data['thumb_image']['url'] = to_str(thumbnail_src[0]['guid']).replace(thumbnail_src[0]['meta_value'], '') sale_price = self.get_value_metadata(child_meta, '_sale_price') if sale_price != '': child_data['special_price']['price'] = sale_price child_data['special_price']['start_date'] = convert_format_time(self.get_value_metadata(child_meta, '_sale_price_dates_from')) child_data['special_price']['end_date'] = convert_format_time(self.get_value_metadata(child_meta, '_sale_price_dates_to')) child_product_language_data = self.construct_product_lang() child_product_language_data['name'] = product_child['post_title'] child_product_language_data['description'] = self.get_value_metadata(child_meta, '_variation_description') child_product_language_data['short_description'] = product_child['post_excerpt'] language_id = self._notice['src']['language_default'] child_data['languages'][language_id] = child_product_language_data attr_child = self.get_list_from_list_by_field_as_first_key(child_meta, 'meta_key', 'attribute_') child_data['options'] = list() child_data['attributes'] = list() for attribute in attr_child: # attribute attribute_child_data = self.construct_product_attribute() attr_name = to_str(attribute['meta_key']).replace('attribute_', '') element_type = 'tax_' + attr_name attr_name = attr_name.replace('pa_', '') attr_name = attr_name.strip() option_id = get_row_value_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', attr_name, 'attribute_id') attribute_child_data['option_id'] = option_id if option_id else '' option_name = get_row_value_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', attr_name, 'attribute_label') attribute_child_data['option_name'] = option_name if option_name else attr_name option_code = get_row_value_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', attr_name, 'attribute_name') attribute_child_data['option_code'] = option_code if option_code else attr_name.lower() option_type = get_row_value_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', attr_name, 'attribute_type') # attribute_child_data['option_type'] = option_type if option_type else 'select' attribute_child_data['option_type'] = self.OPTION_SELECT option_group = get_row_value_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', attr_name, 'attribute_orderby') attribute_child_data['option_group'] = option_group if option_group else 'menu_order' # attribute language child_attribute_language_data = self.construct_product_option_lang() child_attribute_language_data['option_name'] = attribute_child_data['option_name'] language_id = self._notice['src']['language_default'] attribute_child_data['option_languages'][language_id] = child_attribute_language_data # values attribute_child_data['option_value_id'] = get_row_value_from_list_by_field(products_ext['data']['term_attribute'], 'slug', attribute['meta_value'], 'term_id') option_value_name = get_row_value_from_list_by_field(products_ext['data']['term_attribute'], 'slug', attribute['meta_value'], 'name') attribute_child_data['option_value_name'] = get_row_value_from_list_by_field(products_ext['data']['term_attribute'], 'slug', attribute['meta_value'], 'name') if get_row_value_from_list_by_field(products_ext['data']['term_attribute'], 'slug', attribute['meta_value'], 'name') else attribute['meta_value'] attribute_child_data['option_value_code'] = to_str(attribute['meta_value']).lower() attribute_child_data['option_value_description'] = get_row_value_from_list_by_field(products_ext['data']['term_relationship'], 'slug', attribute['meta_value'], 'description') if get_row_value_from_list_by_field(products_ext['data']['term_relationship'], 'slug', attribute['meta_value'], 'description') else '' language_id = self._notice['src']['language_default'] child_attribute_value_language_data = self.construct_product_option_value_lang() child_attribute_value_language_data['option_value_name'] = get_row_value_from_list_by_field(products_ext['data']['term_attribute'], 'slug', attribute['meta_value'], 'name') if get_row_value_from_list_by_field(products_ext['data']['term_attribute'], 'slug', attribute['meta_value'], 'name') else attribute['meta_value'] attribute_child_data['option_value_languages'][language_id] = child_attribute_value_language_data child_data['attributes'].append(attribute_child_data) # options child_option_data = self.construct_product_option() child_option_data['id'] = get_row_value_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', attr_name, 'attribute_id') child_option_data['code'] = get_row_value_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', attr_name, 'attribute_name') if get_row_value_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', attr_name, 'attribute_name') else attr_name.lower() child_option_data['option_name'] = get_row_value_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', attr_name, 'attribute_label') if get_row_value_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', attr_name, 'attribute_label') else attr_name child_option_data['option_code'] = child_option_data['code'] child_option_data['option_group'] = get_row_value_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', attr_name, 'attribute_orderby') if get_row_value_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', attr_name, 'attribute_orderby') else 'menu_order' # child_option_data['option_type'] = self.OPTION_SELECT child_option_data['option_type'] = get_row_value_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', attr_name, 'attribute_type') if get_row_value_from_list_by_field(products_ext['data']['woocommerce_attribute_taxonomies'], 'attribute_name', attr_name, 'attribute_type') else 'select' child_option_data['required'] = 1 # option language child_option_language_data = self.construct_product_option_lang() child_option_language_data['option_name'] = attr_name language_id = self._notice['src']['language_default'] child_option_data['option_languages'][language_id] = child_option_language_data # value option child_option_value_data = self.construct_product_option_value() child_option_value_data['id'] = get_row_value_from_list_by_field(products_ext['data']['term_attribute'], 'slug', attribute['meta_value'], 'term_id') child_option_value_data['code'] = attribute['meta_value'] child_option_value_data['option_value_code'] = attribute['meta_value'] child_option_value_data['option_value_name'] = get_row_value_from_list_by_field(products_ext['data']['term_attribute'], 'slug', attribute['meta_value'], 'name') if get_row_value_from_list_by_field(products_ext['data']['term_attribute'], 'slug', attribute['meta_value'], 'name') else child_option_value_data['code'] child_option_value_data['option_value_description'] = get_row_value_from_list_by_field(products_ext['data']['term_relationship'], 'slug', attribute['meta_value'], 'description') if get_row_value_from_list_by_field(products_ext['data']['term_relationship'], 'slug', attribute['meta_value'], 'name') else '' # value language child_option_value_language_data = self.construct_product_option_value_lang() child_option_value_language_data['option_value_name'] = get_row_value_from_list_by_field(products_ext['data']['term_attribute'], 'slug', attribute['meta_value'], 'name') language_id = self._notice['src']['language_default'] child_option_value_data['option_value_languages'][language_id] = child_option_value_language_data child_option_data['values'].append(child_option_value_data) child_attributes[product_child['ID']][child_option_data['option_name']] = child_option_value_data['option_value_name'] all_child[to_str(product_child['ID'])] = child_data # todo: bundle product - product bundle plugin: WPC Product Bundles for WooCommerce (Premium) if self._notice['src']['support']['product_bundle']: product_data['bundle_selection'] = list() product_bundles = get_row_value_from_list_by_field(product_meta, 'meta_key', 'woosb_ids', 'meta_value') if product_bundles: product_data['type'] = self.PRODUCT_BUNDLE product_bundle_list = to_str(product_bundles).split(',') if product_bundle_list and to_len(product_bundle_list) > 0: for product_bundle_child in product_bundle_list: product_bundle_ids = to_str(product_bundle_child).split('/') if product_bundle_ids and to_len(product_bundle_ids) > 0: product_bundle_data = { 'product_id': product_bundle_ids[0], 'selection_qty': product_bundle_ids[1] if to_len(product_bundle_ids) > 1 else 1 } product_data['bundle_selection'].append(product_bundle_data) if self.is_woo2woo(): product_data['children'] = list(all_child.values()) else: len_child = 1 for attribute_variant in attribute_variants: len_child *= to_len(attribute_variant['option_value_name'].split(';')) options_src = dict() for attribute_variant in attribute_variants: values = to_str(attribute_variant['option_value_name']).split(';') option_data = self.construct_product_option() option_data['id'] = attribute_variant['option_id'] option_data['option_name'] = attribute_variant['option_name'] option_data['option_code'] = attribute_variant['option_code'] option_data['option_type'] = 'select' for value in values: if len_child > self.VARIANT_LIMIT: option_data_value = self.construct_product_option_value() option_data_value['option_value_name'] = value option_data['values'].append(option_data_value) opt_val = { 'option_name': attribute_variant['option_name'], 'option_code': attribute_variant['option_code'], 'option_languages': attribute_variant['option_languages'], 'option_id': attribute_variant['option_id'], 'option_value_name': value, } if attribute_variant['option_name'] not in options_src: options_src[attribute_variant['option_name']] = list() options_src[attribute_variant['option_name']].append(opt_val) if len_child > self.VARIANT_LIMIT: product_data['options'].append(option_data) if len_child <= self.VARIANT_LIMIT and child_attributes: combinations = self.combination_from_multi_dict(options_src) list_child = list() if combinations: for combination in combinations: if not combination: continue children_id = None check_any = False for child_id, child in child_attributes.items(): if self.check_sync_child(child, combination) and child_id not in list_child: children_id = child_id list_child.append(child_id) break if not children_id: for child_id, child in child_attributes.items(): if self.check_sync_child(child, combination, True) and child_id not in list_child: children_id = child_id check_any = True break if not children_id: continue child = copy.deepcopy(all_child[children_id]) child['attributes'] = list() for attribute in combination: attribute_data = self.construct_product_attribute() attribute_data['option_name'] = attribute['option_name'] attribute_data['option_code'] = attribute['option_code'] attribute_data['option_languages'] = attribute['option_languages'] attribute_data['option_id'] = attribute['option_id'] attribute_data['option_value_name'] = attribute['option_value_name'] child['attributes'].append(attribute_data) product_data['children'].append(child) else: if attribute_variants: product_data['attributes'] = attribute_variants return response_success(product_data) def get_product_id_import(self, convert, product, products_ext): return product['ID'] def check_product_import(self, convert, product, products_ext): language_code = convert.get('language') if self.is_wpml() and not language_code: language_code = self._notice['target']['language_default'] product_id = self.get_map_field_by_src(self.TYPE_PRODUCT, convert['id'], convert['code'], language_code) all_queries = list() data_attr = dict() if convert['attributes']: position = 0 for attribute in convert['attributes']: check_attribute_exist = True if self.select_map(self._migration_id, self.TYPE_ATTR, None, None, attribute['option_name'], None, None, language_code) else False if check_attribute_exist == False: data_attribute = { 'attribute_name': attribute['option_code'], 'attribute_label': attribute['option_code'], 'attribute_type': attribute['option_type'], 'attribute_orderby': 'menu_order', 'attribute_public': attribute['option_name'], } attribute_query = self.create_insert_query_connector('woocommerce_attribute_taxonomies', data_attribute) attribute_map_id = self.import_product_data_connector(attribute_query, True, convert['id']) if not attribute_map_id: return response_error('Attribute ' + to_str(attribute['option_id']) + ' import false.') self.insert_map(self.TYPE_ATTR, attribute['option_id'], attribute_map_id, attribute['option_code'],) else: attribute_map_id = self.get_map_field_by_src(self.TYPE_ATTR, attribute['option_id'], attribute['option_code']) check_attribute_value_exist = True if self.select_map(self._migration_id, self.TYPE_ATTR_VALUE, None, None, attribute['option_value_name'], None, None, language_code) else False if check_attribute_value_exist == False: data_attribute_value = { 'name': self.sanitize_title(attribute['option_value_name']), 'slug': self.sanitize_title(attribute['option_value_name']), 'term_group': 0, } attribute_value_query = self.create_insert_query_connector('terms', data_attribute_value) attribute_value_id = self.import_product_data_connector(attribute_value_query, True, convert['id']) if not attribute_value_id: return response_error('Attribute Value' + to_str(attribute['option_id']) + ' import false.') self.insert_map(self.TYPE_ATTR_VALUE, attribute_map_id, attribute_value_id, self.sanitize_title(attribute['option_value_name']), ) else: attribute_value_id = self.get_map_field_by_src(self.TYPE_ATTR_VALUE, attribute_map_id, self.sanitize_title(attribute['option_value_name'])) attr_taxonomy = 'pa_' + attribute['option_code'] check_attribute_term_exist = True if self.select_map(self._migration_id, self.TYPE_ATTR_OPTION, attribute_value_id, None, None, None, None, language_code) else False if check_attribute_term_exist == False: data_attribute_term = { 'term_id': attribute_value_id, 'taxonomy': attr_taxonomy, 'description': '', 'parent': 0, 'count': 0, } data_attribute_term_query = self.create_insert_query_connector('term_taxonomy', data_attribute_term) term_taxonomy_id = self.import_product_data_connector(data_attribute_term_query, True, convert['id']) self.insert_map(self.TYPE_ATTR_OPTION, attribute_value_id, term_taxonomy_id, attr_taxonomy) else: term_taxonomy_id = self.get_map_field_by_src(self.TYPE_ATTR_OPTION, attribute_value_id, attr_taxonomy) data_terms_relationship = { 'object_id': product_id, 'term_taxonomy_id': term_taxonomy_id, 'term_order': 0 } all_queries.append(self.create_insert_query_connector('term_relationships', data_terms_relationship)) data_attr[attr_taxonomy] = { 'name': attr_taxonomy, 'value': attribute['option_value_name'], 'position': position, 'is_visible': 1, 'is_variation': 0, 'is_taxonomy': 1 } position += 1 if data_attr: data_update = { 'post_id': product_id, 'meta_key': '_product_attributes', 'meta_value': php_serialize(data_attr) } where = { 'post_id': product_id, 'meta_key': '_product_attributes' } all_queries.append(self.create_update_query_connector('postmeta', data_update, where)) if all_queries: self.import_multiple_data_connector(all_queries, 'products') return self.get_map_field_by_src(self.TYPE_PRODUCT, convert['id'], convert['code'], lang = self._notice['target']['language_default']) def update_latest_data_product(self, product_id, convert, product, products_ext): all_query = list() language_code = convert.get('language_code') if self.is_wpml() and not language_code: language_code = self._notice['target']['language_default'] # todo: update product name # begin product_query = self.create_update_query_connector("posts", {'ID': product_id, 'post_title': convert['name']}, {'ID': product_id}) all_query.append(product_query) # end old_url_key = self.get_map_field_by_src(self.TYPE_PRODUCT, convert['id'], convert['code'], 'code_desc') # todo: update product category # begin category_desc = self.select_all_category_map() all_categories = list() for category in convert['categories']: category_id = self.get_map_field_by_src(self.TYPE_CATEGORY, category['id'], category['code'], lang = language_code) if not category_id: category_id = self.get_map_field_by_src(self.TYPE_CATEGORY, None, category['code'], lang = language_code) if not category_id: category_id = self.get_map_field_by_src(self.TYPE_CATEGORY, category['id'], None, lang = language_code) if category_id: all_categories.append(category_id) all_categories = list(set(all_categories)) # todo: delete old category product query_cate = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_term_relationships` WHERE `object_id` = " + to_str(product_id) + " AND `term_taxonomy_id` IN " + self.list_to_in_condition(category_desc) + "" } self.query_data_connector(query_cate, 'update_product') for cate_id in all_categories: query_cate_prod = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_term_relationships` WHERE `object_id` = " + to_str(product_id) + " AND `term_taxonomy_id` = " + to_str(cate_id) + "" } check_product_category = self.select_data_connector(query_cate_prod, 'category_product') if (not check_product_category) or check_product_category['result'] != 'success' or (to_len(check_product_category['data']) == 0): category_data = { 'object_id': product_id, 'term_taxonomy_id': cate_id, 'term_order': 0 } category_query = self.create_insert_query_connector("term_relationships", category_data) all_query.append(category_query) # End stock_status = 'instock' if 'is_in_stock' in convert: stock_status = 'instock' if convert['is_in_stock'] else 'outofstock' else: stock_status = 'outofstock' if convert['manage_stock'] else 'instock' tax_class = '' if convert['tax']['id'] or convert['tax']['code']: tax_class = self.get_map_field_by_src(self.TYPE_TAX, convert['tax']['id'], convert['tax']['code'], field = 'code_desc') product_meta = { '_stock_status': stock_status, '_downloadable': "yes" if convert['type'] == self.PRODUCT_DOWNLOAD else "no", '_virtual': "yes" if convert['type'] == self.PRODUCT_VIRTUAL else "no", '_regular_price': convert['price'], '_sale_price': convert['special_price']['price'] if convert['special_price']['price'] and (self.to_timestamp(convert['special_price']['end_date']) > time.time() or (convert['special_price']['end_date'] == '0000-00-00' or convert['special_price']['end_date'] == '0000-00-00 00:00:00') or convert['special_price']['end_date'] == '' or convert['special_price']['end_date'] == None) else "", '_tax_status': convert['tax'].get('status', ("taxable" if to_int(convert['tax']['id']) or convert['tax']['code'] else "none")), '_tax_class': tax_class if tax_class else '', '_weight': convert['weight'] if convert['weight'] else '', '_length': convert['length'] if convert['length'] else '', '_width': convert['width'] if convert['width'] else '', '_height': convert['height'] if convert['height'] else '', '_sku': convert['sku'], '_price': convert['special_price']['price'] if convert['special_price']['price'] and (self.to_timestamp(convert['special_price']['end_date']) > time.time() or (convert['special_price']['end_date'] == '0000-00-00' or convert['special_price']['end_date'] == '0000-00-00 00:00:00' or convert['special_price']['end_date'] == '' or convert['special_price']['end_date'] == None)) else convert['price'], '_manage_stock': "yes" if convert['manage_stock'] or convert['manage_stock'] == True else "no", '_stock': convert['qty'] if convert['qty'] else 0, # 'show_on_pos': '1' if convert['pos'] else 0, } if convert['special_price']['start_date'] and (self.to_timestamp(convert['special_price']['end_date']) > time.time() or (convert['special_price']['end_date'] == '0000-00-00' or convert['special_price']['end_date'] == '0000-00-00 00:00:00' or convert['special_price']['end_date'] == '' or convert['special_price']['end_date'] == None)): product_meta['_sale_price_dates_from'] = self.to_timestamp(convert['special_price']['start_date']) if convert['special_price']['end_date'] and (self.to_timestamp(convert['special_price']['end_date']) > time.time() or (convert['special_price']['end_date'] == '0000-00-00' or convert['special_price']['end_date'] == '0000-00-00 00:00:00' or convert['special_price']['end_date'] == '' or convert['special_price']['end_date'] == None)): product_meta['_sale_price_dates_to'] = self.to_timestamp(convert['special_price']['end_date']) if 'group_prices' in convert and to_len(convert['group_prices']) > 0: product_meta['wholesale_customer_wholesale_price'] = convert['group_prices'][0]['price'] all_meta_queries = list() for meta_key, meta_value in product_meta.items(): meta_insert = { 'post_id': product_id, 'meta_key': meta_key, 'meta_value': meta_value } if meta_key == '_sale_price_dates_from' or meta_key == '_sale_price_dates_to': query_meta_key = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_postmeta` WHERE `post_id` = " + to_str(product_id) + " AND `meta_key` = " + to_str(meta_key) + "" } check_meta_key = self.select_data_connector(query_meta_key, 'postmeta') if (not check_meta_key) or check_meta_key['result'] != 'success' or (not check_meta_key['data']) or (to_len(check_meta_key['data']) == 0): sale_price_data = { 'post_id': product_id, 'meta_key': meta_key, 'meta_value': meta_value } meta_price_query = self.create_insert_query_connector("postmeta", sale_price_data) all_query.append(meta_price_query) meta_query = self.create_update_query_connector("postmeta", meta_insert, {'post_id': product_id, 'meta_key': meta_key}) all_query.append(meta_query) # todo: update children children_list = list() option_list = list() if convert['children']: children_list = convert['children'] else: if convert['options']: option_list = convert['options'] if self.count_child_from_option(convert['options']) <= self.VARIANT_LIMIT: children_list = self.convert_option_to_child(option_list, convert) if children_list and to_len(children_list) <= self.VARIANT_LIMIT: for key_child, product_child in enumerate(children_list): children_id = self.get_map_field_by_src(self.TYPE_CHILD, product_child['id'], product_child['code'], lang = language_code) if not children_id: continue if product_child.get('is_in_stock'): child_stock_status = 'instock' if product_child['is_in_stock'] else 'outofstock' else: child_stock_status = 'outofstock' if product_child['manage_stock'] else 'instock' children_meta = { '_stock_status': child_stock_status, '_sku': product_child['sku'] if product_child['sku'] else '', '_weight': product_child['weight'] if product_child['weight'] else '', '_length': product_child['length'] if product_child['length'] else '', '_width': product_child['width'] if product_child['width'] else '', '_height': product_child['height'] if product_child['height'] else '', '_manage_stock': "yes" if product_child['manage_stock'] else "no", '_stock': product_child['qty'] if product_child['qty'] else 0, '_regular_price': product_child['price'], '_sale_price': product_child['special_price']['price'] if product_child['special_price']['price'] and (self.to_timestamp(product_child['special_price']['end_date']) > time.time() or (product_child['special_price']['end_date'] == '0000-00-00' or product_child['special_price']['end_date'] == '0000-00-00 00:00:00' or convert['special_price']['end_date'] == '' or convert['special_price']['end_date'] == None)) else product_child['price'], '_price': product_child['special_price']['price'] if product_child['special_price']['price'] and (self.to_timestamp(product_child['special_price']['end_date']) > time.time() or (product_child['special_price']['end_date'] == '0000-00-00' or product_child['special_price']['end_date'] == '0000-00-00 00:00:00' or convert['special_price']['end_date'] == '' or convert['special_price']['end_date'] == None)) else product_child['price'], } if product_child['special_price']['price'] and (self.to_timestamp(product_child['special_price']['end_date']) > time.time() or (product_child['special_price']['end_date'] == '0000-00-00' or product_child['special_price']['end_date'] == '0000-00-00 00:00:00' or convert['special_price']['end_date'] == '' or convert['special_price']['end_date'] == None)): if product_child['special_price']['start_date']: children_meta['_sale_price_dates_from'] = self.to_timestamp(product_child['special_price']['start_date']) if product_child['special_price']['end_date']: children_meta['_sale_price_dates_to'] = self.to_timestamp(product_child['special_price']['end_date']) for meta_key, meta_value in children_meta.items(): meta_insert_child = { 'post_id': children_id, 'meta_key': meta_key, 'meta_value': meta_value } if meta_key == '_sale_price_dates_from' or meta_key == '_sale_price_dates_to': query_meta_key = { 'type': 'select', 'query': "SELECT * FROM `_DBPRF_postmeta` WHERE `post_id` = " + to_str(children_id) + " AND `meta_key` = " + to_str(meta_key) + "" } check_meta_key = self.select_data_connector(query_meta_key, 'postmeta') if (not check_meta_key) or check_meta_key['result'] != 'success' or (not check_meta_key['data']) or (to_len(check_meta_key['data']) == 0): sale_price_data = { 'post_id': children_id, 'meta_key': meta_key, 'meta_value': meta_value } meta_price_query = self.create_insert_query_connector("postmeta", sale_price_data) all_query.append(meta_price_query) meta_query_child = self.create_update_query_connector('postmeta', meta_insert_child, {'post_id': children_id, 'meta_key': meta_key}) all_query.append(meta_query_child) # todo: seo # begin if self.is_exist_lecm_rewrite(): if (self._notice['config']['seo'] or self._notice['config']['seo_301']) and convert['seo']: delete_query = list() delete_query.append(self.create_delete_query_connector('lecm_rewrite', {'type': 'product', 'type_id': product_id})) self.query_multiple_data_connector(delete_query) for seo_url in convert['seo']: if not seo_url['request_path']: continue if old_url_key != seo_url['request_path'].replace(' ', ''): query_check = { 'link': seo_url['request_path'] } if self.is_wpml() and convert.get('language_code'): query_check['lang'] = convert['language_code'] seo_query = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_lecm_rewrite WHERE " + self.dict_to_where_condition(query_check) } check_seo_exit = self.select_data_connector(seo_query, 'lecm_rewrite') if check_seo_exit and check_seo_exit['result'] == 'success' and to_len(check_seo_exit['data']) > 0: continue else: le_url_rewrite = { 'link': to_str(seo_url['request_path']).rstrip('/'), 'type': 'product', 'type_id': product_id } if self.is_wpml(): le_url_rewrite['lang'] = convert.get('language_code') if self._notice['config']['seo_301']: le_url_rewrite['redirect_type'] = 301 self.import_data_connector(self.create_insert_query_connector("lecm_rewrite", le_url_rewrite), 'seo_product') self.import_multiple_data_connector(all_query, 'update_product') if self.is_wpml() and not convert.get('language_code'): where_product_wpml = { 'migration_id': self._migration_id, 'type': 'product', } if convert['id']: where_product_wpml['id_src'] = convert['id'] else: where_product_wpml['code'] = convert['code'] product_wpml = self.select_obj(TABLE_MAP, where_product_wpml) if product_wpml['result'] == 'success' and product_wpml['data']: for product_wpml_row in product_wpml['data']: if product_wpml_row['id_desc'] == product_id or not product_wpml_row.get('lang'): continue convert_wpml = self.get_convert_data_language(convert, target_language_id = language_code) convert_wpml['language_code'] = product_wpml_row['lang'] self.update_latest_data_product(product_wpml_row['id_desc'], convert_wpml, product, products_ext) return response_success() # đọc cái này là làm được bài oke oke def update_product_after_demo(self, product_id, convert, product, products_ext): language_code = convert.get('language_code') if self.is_wpml() and not language_code: language_code = self._notice['target']['language_default'] all_queries = list() query_delete = { 'type': 'delete', 'query': 'DELETE FROM _DBPRF_term_relationships WHERE object_id = ' + to_str(product_id) + ' AND term_taxonomy_id IN (SELECT term_taxonomy_id FROM _DBPRF_term_taxonomy WHERE taxonomy IN ' + self.list_to_in_condition(['product_brand', 'product_cat']) + ')' } all_queries.append(query_delete) # category all_categories = list() if convert['categories']: for category in convert['categories']: category_id = self.get_map_field_by_src(self.TYPE_CATEGORY, category['id'], category['code'], language_code) if not category_id: category_id = self.get_map_field_by_src(self.TYPE_CATEGORY, None, category['code'], language_code) if not category_id: category_id = self.get_map_field_by_src(self.TYPE_CATEGORY, category['id'], None, language_code) if category_id: all_categories.append(category_id) all_categories = list(set(all_categories)) for cate_id in all_categories: category_data = { 'object_id': product_id, 'term_taxonomy_id': cate_id, 'term_order': 0 } category_query = self.create_insert_query_connector("term_relationships", category_data) all_queries.append(category_query) if self._notice['target']['support']['manufacturers']: if convert['manufacturer']['id'] or convert['manufacturer']['name']: manufacturer_id = self.get_map_field_by_src(self.TYPE_MANUFACTURER, convert['manufacturer']['id']) if not manufacturer_id: manufacturer_id = self.get_map_field_by_src(self.TYPE_MANUFACTURER, None, convert['manufacturer']['id']) if manufacturer_id: relationship_data = { 'object_id': product_id, 'term_taxonomy_id': manufacturer_id, 'term_order': 0 } category_query = self.create_insert_query_connector("term_relationships", relationship_data) all_queries.append(category_query) elif convert['manufacturer']['name']: slug = self.sanitize_title(convert['manufacturer']['name']) manufacturer_term = { 'name': convert['manufacturer']['name'], 'slug': slug, 'term_group': 0, } manufacturer_term_query = self.create_insert_query_connector('terms', manufacturer_term) term_id = self.import_data_connector(manufacturer_term_query, 'manufacturer') if not term_id: return response_warning('Manufacturer ' + to_str(convert['id']) + ' import false.') manufacturer_taxonomy = { 'term_id': term_id, 'taxonomy': 'product_brand', 'description': '', 'parent': 0, 'count': 0 } manufacturer_taxonomy_query = self.create_insert_query_connector('term_taxonomy', manufacturer_taxonomy) manufacturer_taxonomy_import = self.import_manufacturer_data_connector(manufacturer_taxonomy_query, True, convert['id']) if manufacturer_taxonomy_import: relationship_data = { 'object_id': product_id, 'term_taxonomy_id': manufacturer_id, 'term_order': 0 } relationship_query = self.create_insert_query_connector("term_relationships", relationship_data) all_queries.append(relationship_query) self.insert_map(self.TYPE_MANUFACTURER, convert['manufacturer']['id'], manufacturer_taxonomy_import, convert['manufacturer']['name']) if convert['tax']['id'] or convert['tax']['code']: tax_class = self.get_map_field_by_src(self.TYPE_TAX, convert['tax']['id'], convert['tax']['code'], 'code_desc') if tax_class: meta_insert = { 'post_id': product_id, 'meta_key': '_tax_class', 'meta_value': tax_class } where_meta = { 'post_id': product_id, 'meta_key': '_tax_class', } all_queries.append(self.create_update_query_connector('postmeta', meta_insert, where_meta)) self.import_multiple_data_connector(all_queries, 'update_product') return response_success() def router_product_import(self, convert, product, products_ext): return response_success('product_import') def before_product_import(self, convert, product, products_ext): return response_success() def product_import(self, convert, product, products_ext): self.log(product, 'queries') all_query = list() language_code = convert.get('language_code') if self.is_wpml() and not language_code: language_code = self._notice['target']['language_default'] code_name = convert['name'] code_name = self.sanitize_title(code_name).strip('-') if self.is_wpml() and language_code: code_name = code_name + '-' + language_code check_slug_exist = True while check_slug_exist: check_slug_exist = True if self.select_map(self._migration_id, self.TYPE_PRODUCT, None, None, None,code_name, None, language_code) else False if check_slug_exist: code_name += to_str(get_value_by_key_in_dict(convert, 'id', '')) product_data = { 'post_author': 1, 'post_date': convert['created_at'] if convert['created_at'] and '0000-00-00' not in convert['created_at'] else get_current_time(), 'post_date_gmt': convert['created_at'] if convert['created_at'] and '0000-00-00' not in convert['created_at'] else get_current_time(), 'post_title': convert['name'], 'post_status': 'publish', 'ping_status': 'open', 'post_name': code_name[:200], 'post_modified': convert['created_at'] if convert['created_at'] and '0000-00-00' not in convert['created_at'] else get_current_time(), 'post_modified_gmt': convert['created_at'] if convert['created_at'] and '0000-00-00' not in convert['created_at'] else get_current_time(), 'post_parent': '', 'post_type': 'product', 'comment_count': 0, 'guid': '', 'post_content_filtered': '', 'post_excerpt': convert['short_description'], 'to_ping': '', 'pinged': '', # 'post_parent': 0, 'post_content': convert['description'], 'menu_order': get_value_by_key_in_dict(convert, 'sort_order', 0) } product_data_query = self.create_insert_query_connector('posts', product_data) product_id = self.import_product_data_connector(product_data_query, True, convert['id']) if not product_id: return response_error('Product ' + to_str(convert['id']) + ' import false.') self.insert_map(self.TYPE_PRODUCT, convert['id'], product_id, convert['name'], code_name, None, language_code) return response_success(product_id) def after_product_import(self, product_id, convert, product, products_ext): self.log(product_id, 'product_id') self.log(convert, 'convert_after_pro_import') language_code = convert.get('language_code') if self.is_wpml() and not language_code or (self.is_polylang() and not language_code): language_code = self._notice['target']['language_default'] all_queries = list() thumbnail_id = False if convert['thumb_image']['path']: image_process = self.process_image_before_import(convert['thumb_image']['url'], convert['thumb_image']['path']) image_import_path = self.uploadImageConnector(image_process, self.add_prefix_path(self.make_woocommerce_image_path(image_process['path']), self._notice['target']['config']['image_product'].rstrip('/'))) if image_import_path: product_image = self.remove_prefix_path(image_import_path, self._notice['target']['config']['image_product']) image_details = self.get_sizes(image_process['url']) thumbnail_id = self.wp_image(product_image, image_details, convert['thumb_image'].get('label', '')) if thumbnail_id and self.is_wpml(): all_queries.append(self.get_query_img_wpml(thumbnail_id, language_code)) gallery_ids = list() if convert['images']: for image in convert['images']: image_process = self.process_image_before_import(image['url'], image['path']) image_import_path = self.uploadImageConnector(image_process, self.add_prefix_path(self.make_woocommerce_image_path(image_process['path']), self._notice['target']['config']['image_product'].rstrip('/'))) if image_import_path: product_image = self.remove_prefix_path(image_import_path, self._notice['target']['config']['image_product']) image_details = self.get_sizes(image_process['url']) img_id = self.wp_image(product_image, image_details, image['label']) if img_id: gallery_ids.append(img_id) if self.is_wpml(): all_queries.append(self.get_query_img_wpml(img_id, language_code)) stock_status = 'instock' product_meta = { '_product_attributes': php_serialize(list()), '_sku': convert['sku'], '_stock_status': stock_status, '_weight': convert['weight'] if convert['weight'] else '', '_length': convert['length'] if convert['length'] else '', '_width': convert['width'] if convert['width'] else '', '_height': convert['height'] if convert['height'] else '', '_price': convert['special_price']['price'], '_stock': convert['qty'] if convert['qty'] else 0, '_thumbnail_id': thumbnail_id if thumbnail_id else '', '_manage_stock': 'yes' if convert['manage_stock'] or convert['manage_stock'] == True else 'no', } all_meta_queries = list() for meta_key, meta_value in product_meta.items(): meta_insert = { 'post_id': product_id, 'meta_key': meta_key, 'meta_value': meta_value } meta_query = self.create_insert_query_connector("postmeta", meta_insert) all_meta_queries.append(meta_query) if all_meta_queries: self.import_multiple_data_connector(all_meta_queries, 'products') all_categories = list() if convert['categories']: for category in convert['categories']: category_id = self.get_map_field_by_src(self.TYPE_CATEGORY, category['id'], category['code'], language_code) if not category_id: category_id = self.get_map_field_by_src(self.TYPE_CATEGORY, None, category['code'], language_code) if not category_id: category_id = self.get_map_field_by_src(self.TYPE_CATEGORY, category['id'], None, language_code) if category_id: all_categories.append(category_id) all_categories = list(set(all_categories)) for cate_id in all_categories: category_data = { 'object_id': product_id, 'term_taxonomy_id': cate_id, 'term_order': 0 } category_query = self.create_insert_query_connector("term_relationships", category_data) all_queries.append(category_query) if all_queries: self.import_multiple_data_connector(all_queries, 'product') return response_success() def addition_product_import(self, convert, product, products_ext): return response_success() def finish_product_import(self): if self.is_variant_limit: self._notice['config']['variant_limit'] = True return response_success() # TODO: CUSTOMER # def prepare_customers_import(self): # return self # def prepare_customers_export(self): # return self def prepare_customers_import(self): if self._notice['config'].get('cus_pass'): delete_query = { 'type': 'query', 'query': "DELETE FROM `_DBPRF_options` WHERE option_name = 'LEPP_TYPE' OR option_name = 'LEPP_URL'" } config_delete = self.import_data_connector(delete_query) all_queries = list() type_data = { 'option_name': 'LEPP_TYPE', 'option_value': self._notice['src']['cart_type'], 'autoload': 'yes' } type_query = self.create_insert_query_connector('options', type_data) all_queries.append(type_query) url_data = { 'option_name': 'LEPP_URL', 'option_value': self._notice['src']['cart_url'], 'autoload': 'yes' } url_query = self.create_insert_query_connector('options', url_data) all_queries.append(url_query) if all_queries: self.import_multiple_data_connector(all_queries, 'customer') return self def get_customers_main_export(self): id_src = self._notice['process']['customers']['id_src'] limit = self._notice['setting']['customers'] prefix = self._notice['src']['config']['table_prefix'] if self._notice['src']['config'].get('site_id'): prefix = to_str(prefix).replace(to_str(self._notice['src']['config'].get('site_id')) + '_', '') query = { 'type': 'select', 'query': "SELECT * FROM " + prefix + "users u LEFT JOIN " + prefix + "usermeta um ON u.ID = um.user_id WHERE (um.meta_key = '_DBPRF_capabilities' AND um.meta_value LIKE '%customer%' OR um.meta_value LIKE '%subscriber%') AND ID > " + to_str(id_src) + " ORDER BY ID ASC LIMIT " + to_str(limit) } # customers = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query)}) customers = self.select_data_connector(query, 'customers') if not customers or customers['result'] != 'success': return response_error() return customers def get_customers_ext_export(self, customers): url_query = self.get_connector_url('query') customers_ids = duplicate_field_value_from_list(customers['data'], 'ID') customer_ext_queries = { 'user_meta': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_usermeta WHERE user_id IN " + self.list_to_in_condition( customers_ids), } } if self._notice['src']['support'].get('customer_point_rewards'): customer_ext_queries['wc_points_rewards_user_points'] = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_wc_points_rewards_user_points WHERE (order_id IS NULL OR order_id = '') AND user_id IN " + self.list_to_in_condition(customers_ids), } customer_ext_queries['wc_points_rewards_user_points_log'] = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_wc_points_rewards_user_points_log WHERE (order_id IS NULL OR order_id = '') AND user_id IN " + self.list_to_in_condition(customers_ids), } # customers_ext = self.get_connector_data(url_query, # {'serialize': True, 'query': json.dumps(customer_ext_queries)}) customers_ext = self.select_multiple_data_connector(customer_ext_queries, 'customers') if not customers_ext or customers_ext['result'] != 'success': return response_error() return customers_ext def convert_customer_export(self, customer, customers_ext): customer_data = self.construct_customer() customer_data = self.add_construct_default(customer_data) customer_data['id'] = customer['ID'] customer_data['code'] = customer['user_login'] customer_data['username'] = customer['user_nicename'] customer_data['email'] = customer['user_email'] customer_data['password'] = customer['user_pass'] customer_data['website'] = customer['user_url'] customer_data['user_url'] = customer['user_url'] customer_data['active'] = True customer_data['created_at'] = convert_format_time(customer['user_registered']) customer_meta = get_list_from_list_by_field(customers_ext['data']['user_meta'], 'user_id', customer['ID']) customer_data['first_name'] = get_row_value_from_list_by_field(customer_meta, 'meta_key', 'first_name', 'meta_value') customer_data['last_name'] = get_row_value_from_list_by_field(customer_meta, 'meta_key', 'last_name', 'meta_value') prefix = self._notice['src']['config']['table_prefix'] capabilities = to_str(prefix) + '_capabilities' customer_data['capabilities'] = get_row_value_from_list_by_field(customer_meta, 'meta_key', capabilities, 'meta_value') # billing address_data = self.construct_customer_address() address_data['code'] = to_str(customer['ID']) + "_1" address_data['first_name'] = get_row_value_from_list_by_field(customer_meta, 'meta_key', 'billing_first_name', 'meta_value') address_data['last_name'] = get_row_value_from_list_by_field(customer_meta, 'meta_key', 'billing_last_name', 'meta_value') address_data['address_1'] = get_row_value_from_list_by_field(customer_meta, 'meta_key', 'billing_address_1', 'meta_value') address_data['address_2'] = get_row_value_from_list_by_field(customer_meta, 'meta_key', 'billing_address_2', 'meta_value') address_data['city'] = get_row_value_from_list_by_field(customer_meta, 'meta_key', 'billing_city', 'meta_value') address_data['postcode'] = get_row_value_from_list_by_field(customer_meta, 'meta_key', 'billing_postcode', 'meta_value') address_data['telephone'] = get_row_value_from_list_by_field(customer_meta, 'meta_key', 'billing_phone', 'meta_value') address_data['company'] = get_row_value_from_list_by_field(customer_meta, 'meta_key', 'billing_company', 'meta_value') address_data['fax'] = get_row_value_from_list_by_field(customer_meta, 'meta_key', 'billing_fax', 'meta_value') address_data['country']['country_code'] = get_row_value_from_list_by_field(customer_meta, 'meta_key', 'billing_country', 'meta_value') address_data['country']['code'] = address_data['country']['country_code'] address_data['country']['name'] = self.get_country_name_by_code(address_data['country']['country_code']) address_data['state']['state_code'] = get_row_value_from_list_by_field(customer_meta, 'meta_key', 'billing_state', 'meta_value') address_data['state']['code'] = address_data['state']['state_code'] address_data['default']['billing'] = True if address_data['address_1'] or address_data['address_2']: customer_data['address'].append(address_data) # shipping shipping_address = self.get_list_from_list_by_field_as_first_key(customer_meta, 'meta_key', 'shipping_') if shipping_address: shipping_data = self.construct_customer_address() shipping_data['code'] = to_str(customer['ID']) + "_2" shipping_data['first_name'] = get_row_value_from_list_by_field(shipping_address, 'meta_key', 'shipping_first_name', 'meta_value') shipping_data['last_name'] = get_row_value_from_list_by_field(shipping_address, 'meta_key', 'shipping_last_name', 'meta_value') shipping_data['address_1'] = get_row_value_from_list_by_field(shipping_address, 'meta_key', 'shipping_address_1', 'meta_value') shipping_data['address_2'] = get_row_value_from_list_by_field(shipping_address, 'meta_key', 'shipping_address_2', 'meta_value') shipping_data['city'] = get_row_value_from_list_by_field(shipping_address, 'meta_key', 'shipping_city', 'meta_value') shipping_data['postcode'] = get_row_value_from_list_by_field(shipping_address, 'meta_key', 'shipping_postcode', 'meta_value') shipping_data['telephone'] = get_row_value_from_list_by_field(shipping_address, 'meta_key', 'shipping_phone', 'meta_value') shipping_data['company'] = get_row_value_from_list_by_field(shipping_address, 'meta_key', 'shipping_company', 'meta_value') shipping_data['fax'] = get_row_value_from_list_by_field(shipping_address, 'meta_key', 'shipping_fax', 'meta_value') shipping_data['country']['country_code'] = get_row_value_from_list_by_field(shipping_address, 'meta_key', 'shipping_country', 'meta_value') shipping_data['country']['code'] = shipping_data['country']['country_code'] shipping_data['country']['name'] = self.get_country_name_by_code(shipping_data['country']['code']) shipping_data['state']['state_code'] = get_row_value_from_list_by_field(shipping_address, 'meta_key', 'shipping_state', 'meta_value') shipping_data['state']['code'] = shipping_data['state']['state_code'] shipping_data['default']['shipping'] = True if shipping_data['address_1'] or shipping_data['address_2']: customer_data['address'].append(shipping_data) # customer_data['first_name'] = customer_data['first_name'] if customer_data['first_name']: address_data['first_name'] # customer_data['last_name'] = customer_data['last_name'] if customer_data['last_name']: address_data['last_name'] # TODO: Plugin WooCommerce Points and Rewards if self._notice['src']['support'].get('customer_point_rewards'): customer_point_rewards = dict() customer_point_rewards['reward_point'] = list() customer_point_rewards['reward_point_log'] = list() customer_point_rewards['points_balance'] = get_row_value_from_list_by_field(customer_meta, 'meta_key', 'wc_points_balance', 'meta_value') wc_points_rewards_user_points = get_list_from_list_by_field(customers_ext['data']['wc_points_rewards_user_points'], 'user_id', customer['ID']) if wc_points_rewards_user_points: for points_rewards_user_points in wc_points_rewards_user_points: reward_point = dict() reward_point['points'] = points_rewards_user_points['points'] reward_point['points_balance'] = points_rewards_user_points['points_balance'] reward_point['order_id'] = points_rewards_user_points['order_id'] reward_point['created_at'] = points_rewards_user_points['date'] customer_point_rewards['reward_point'].append(reward_point) wc_points_rewards_user_points_log = get_list_from_list_by_field(customers_ext['data']['wc_points_rewards_user_points_log'], 'user_id', customer['ID']) if wc_points_rewards_user_points_log: for points_rewards_user_points_log in wc_points_rewards_user_points_log: reward_point_log = dict() reward_point_log['points'] = points_rewards_user_points_log['points'] reward_point_log['type'] = points_rewards_user_points_log['type'] reward_point_log['user_points_id'] = points_rewards_user_points_log['user_points_id'] reward_point_log['order_id'] = points_rewards_user_points_log['order_id'] reward_point_log['admin_user_id'] = points_rewards_user_points_log['admin_user_id'] reward_point_log['data'] = points_rewards_user_points_log['data'] reward_point_log['created_at'] = points_rewards_user_points_log['date'] customer_point_rewards['reward_point_log'].append(reward_point_log) customer_data['point_rewards'] = customer_point_rewards return response_success(customer_data) def get_customer_id_import(self, convert, customer, customers_ext): return customer['ID'] def check_customer_import(self, convert, customer, customers_ext): return True if self.get_map_field_by_src(self.TYPE_CUSTOMER, convert['id'], convert['code']) else False def router_customer_import(self, convert, customer, customers_ext): return response_success('customer_import') def before_customer_import(self, convert, customer, customers_ext): return response_success() def customer_import(self, convert, customer, customers_ext): customer_users = { 'user_login': convert['username'], 'user_pass': convert['password'], 'user_nicename': convert['first_name'], 'user_email': convert['email'], 'user_url': '', 'user_registered': 0, 'user_activation_key': "0", 'user_status': 0, 'display_name': convert['last_name'] + ' ' + convert['first_name'], } customer_users_query = self.create_insert_query_connector('users', customer_users) customer_id = self.import_data_connector(customer_users_query, 'customer') if not customer_id: return response_warning('customer' + to_str(convert['id']) + ' import false.') return response_success(customer_id) def get_new_trid(self): query = { 'type': 'select', 'query': "SELECT max(trid) as trid FROM _DBPRF_icl_translations" } trid = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query)}) new_trid = 1 if trid['data']: new_trid = to_int(trid['data'][0]['trid']) + 1 return new_trid def after_customer_import(self, customer_id, convert, customer, customers_ext): a = 1 customer_meta = { 'billing_first_name': convert['first_name'], 'billing_last_name': convert['last_name'], 'billing_company': convert['address'][0]['company'], 'billing_address_1': convert['address'][0]['address_1'], 'billing_address_2': convert['address'][0]['address_2'], 'billing_city': convert['address'][0]['city'], 'billing_postcode': '', 'billing_country': '', 'billing_state': convert['address'][0]['state'], 'billing_phone': convert['address'][0]['telephone'], 'shipping_first_name': convert['first_name'], 'shipping_last_name': convert['last_name'], 'shipping_company': convert['address'][0]['company'], 'shipping_address_1': convert['address'][0]['address_1'], 'shipping_address_2': convert['address'][0]['address_2'], 'shipping_city': convert['address'][0]['city'], 'shipping_postcode': '', 'shipping_country': '', 'billing_state': convert['address'][0]['state'], 'billing_phone': convert['address'][0]['telephone'], } all_meta_queries = list() for meta_key, meta_value in customer_meta.items(): meta_insert = { 'post_id': customer_id, 'meta_key': meta_key, 'meta_value': meta_value } meta_query = self.create_insert_query_connector("postmeta", meta_insert) all_meta_queries.append(meta_query) if all_meta_queries: self.import_multiple_data_connector(all_meta_queries, 'products') return response_success() def addition_customer_import(self, convert, customer, customers_ext): return response_success() # TODO: ORDER def prepare_orders_import(self): return self def prepare_orders_export(self): return self def get_orders_main_export(self): id_src = self._notice['process']['orders']['id_src'] limit = self._notice['setting']['orders'] query = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_posts WHERE post_type = 'shop_order' AND post_status NOT IN ('inherit','auto-draft') AND ID > " + to_str( id_src) + " ORDER BY ID ASC LIMIT " + to_str(limit) } # orders = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query)}) orders = self.select_data_connector(query, 'orders') if not orders or orders['result'] != 'success': return response_error() return orders def get_orders_ext_export(self, orders): url_query = self.get_connector_url('query') order_ids = duplicate_field_value_from_list(orders['data'], 'ID') customer_ext_queries = { 'woocommerce_order_items': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_woocommerce_order_items WHERE order_id IN " + self.list_to_in_condition( order_ids), }, 'order_note': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_comments WHERE comment_post_ID IN " + self.list_to_in_condition( order_ids), }, 'order_refund': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_posts WHERE post_type = 'shop_order_refund' AND post_parent IN " + self.list_to_in_condition( order_ids), }, 'order_meta': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_postmeta WHERE post_id IN " + self.list_to_in_condition(order_ids), }, } orders_ext = self.select_multiple_data_connector(customer_ext_queries, 'orders') if not orders_ext or orders_ext['result'] != 'success': return response_error() # product_option_value_ids = duplicate_field_value_from_list(orders_ext['data']['order_option'], 'product_option_value_id') # order_recurrings = duplicate_field_value_from_list(orders_ext['data']['order_recurring'], 'order_recurring_id') order_item_ids = duplicate_field_value_from_list(orders_ext['data']['woocommerce_order_items'], 'order_item_id') comment_ids = duplicate_field_value_from_list(orders_ext['data']['order_note'], 'comment_ID') refund_ids = duplicate_field_value_from_list(orders_ext['data']['order_refund'], 'ID') post_meta_ids = list(set(refund_ids + order_ids)) cus_list = get_list_from_list_by_field(orders_ext['data']['order_meta'], 'meta_key', '_customer_user') cus_ids = list() if cus_list: cus_ids = duplicate_field_value_from_list(cus_list, 'meta_value') orders_ext_rel_queries = { 'woocommerce_order_itemmeta': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_woocommerce_order_itemmeta WHERE order_item_id IN " + self.list_to_in_condition(order_item_ids), }, 'order_note_meta': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_commentmeta WHERE comment_id IN " + self.list_to_in_condition(comment_ids), }, 'postmeta': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_postmeta WHERE post_id IN " + self.list_to_in_condition(post_meta_ids), }, 'user': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_users WHERE ID IN " + self.list_to_in_condition(cus_ids), }, 'user_meta': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_usermeta WHERE meta_key IN ('first_name','last_name') AND user_id IN " + self.list_to_in_condition(cus_ids), } } if self._notice['src']['support'].get('customer_point_rewards'): orders_ext_rel_queries['wc_points_rewards_user_points'] = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_wc_points_rewards_user_points WHERE order_id IN " + self.list_to_in_condition(order_ids), } orders_ext_rel_queries['wc_points_rewards_user_points_log'] = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_wc_points_rewards_user_points_log WHERE order_id IN " + self.list_to_in_condition(order_ids), } orders_ext_rel = self.select_multiple_data_connector(orders_ext_rel_queries, 'orders') if not orders_ext_rel or orders_ext_rel['result'] != 'success': return response_error() orders_ext = self.sync_connector_object(orders_ext, orders_ext_rel) pro_list = get_list_from_list_by_field(orders_ext_rel['data']['woocommerce_order_itemmeta'], 'meta_key', '_product_id') pro_ids = duplicate_field_value_from_list(pro_list, 'meta_value') orders_ext_third_rel_queries = { 'products_meta': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_postmeta WHERE post_id IN " + self.list_to_in_condition(pro_ids), }, } orders_ext_third_rel = self.get_connector_data(url_query, {'serialize': True, 'query': json.dumps(orders_ext_third_rel_queries)}) if not orders_ext_third_rel or orders_ext_third_rel['result'] != 'success': return response_error() orders_ext = self.sync_connector_object(orders_ext, orders_ext_third_rel) return orders_ext def convert_order_export(self, order, orders_ext): order_data = self.construct_order() order_data = self.add_construct_default(order_data) order_data['id'] = order['ID'] order_data['status'] = order['post_status'] # order data order_items = get_list_from_list_by_field(orders_ext['data']['woocommerce_order_items'], 'order_id', order['ID']) shipping = get_row_from_list_by_field(order_items, 'order_item_type', 'shipping') taxes = get_list_from_list_by_field(order_items, 'order_item_type', 'tax') tax_names = list() total_tax = 0.0 if taxes: tax_names = duplicate_field_value_from_list(taxes, 'order_item_name') for tax in taxes: order_tax_metas = get_list_from_list_by_field(orders_ext['data']['woocommerce_order_itemmeta'], 'order_item_id', tax['order_item_id']) total_tax += to_decimal(self.get_value_metadata(order_tax_metas, 'tax_amount', 0.0)) total_tax += to_decimal(self.get_value_metadata(order_tax_metas, 'shipping_tax_amount', 0.0)) if 'postmeta' in orders_ext['data']: order_meta = get_list_from_list_by_field(orders_ext['data']['postmeta'], 'post_id', order['ID']) else: order_meta = get_list_from_list_by_field(orders_ext['data']['order_meta'], 'post_id', order['ID']) ord_number = get_row_value_from_list_by_field(order_meta, 'meta_key', '_order_number', 'meta_value') if ord_number and self._notice['src']['support'].get('plugin_pre_ord'): order_data['order_number'] = ord_number order_data['tax']['title'] = '|'.join(tax_names) if tax_names else 'Tax' order_data['tax']['amount'] = total_tax if total_tax else self.get_value_metadata(order_meta, '_order_tax', 0.0000) order_data['shipping']['title'] = shipping['order_item_name'] if shipping else 'Shipping' order_data['shipping']['amount'] = self.get_value_metadata(order_meta, '_order_shipping', 0.0000) # _order_shipping_tax discount_title = get_row_value_from_list_by_field(order_items, 'order_item_type', 'coupon', 'order_item_name') order_data['discount']['title'] = discount_title if discount_title else 'Discount' order_data['discount']['amount'] = self.get_value_metadata(order_meta, '_cart_discount', 0.0000) order_data['total']['title'] = 'Total' order_data['total']['amount'] = self.get_value_metadata(order_meta, '_order_total', 0.0000) order_data['subtotal']['title'] = 'Total' order_data['subtotal']['amount'] = to_decimal(self.get_value_metadata(order_meta, '_order_total', 0.0000)) - to_decimal(self.get_value_metadata(order_meta, '_cart_discount', 0.0000)) - to_decimal(order_data['tax']['amount']) - to_decimal(order_data['shipping']['amount']) order_data['currency'] = self.get_value_metadata(order_meta, '_order_currency', 'meta_value') order_data['created_at'] = convert_format_time(order['post_date']) order_data['updated_at'] = convert_format_time(order['post_modified']) # order customer order_customer = self.construct_order_customer() order_customer = self.add_construct_default(order_customer) order_customer_src = self.get_value_metadata(order_meta, '_customer_user', 'meta_value') if order_customer_src and to_int(order_customer_src) > 0: customer_src = get_row_from_list_by_field(orders_ext['data']['user'], 'ID', order_customer_src) customer_meta_src = get_list_from_list_by_field(orders_ext['data']['user_meta'], 'user_id', order_customer_src) if customer_src: order_customer['id'] = order_customer_src order_customer['code'] = get_value_by_key_in_dict(customer_src, 'user_login', '') order_customer['email'] = get_value_by_key_in_dict(customer_src, 'user_email', self.get_value_metadata(order_meta, '_billing_email', 'meta_value')) order_customer['username'] = get_value_by_key_in_dict(customer_src, 'display_name', '') order_customer['first_name'] = self.get_value_metadata(customer_meta_src, 'first_name', self.get_value_metadata(order_meta, '_billing_first_name', '')) order_customer['last_name'] = self.get_value_metadata(customer_meta_src, 'last_name', self.get_value_metadata(order_meta, '_billing_last_name', '')) else: order_customer['email'] = self.get_value_metadata(order_meta, '_billing_email', 'meta_value') order_customer['username'] = order_customer['email'] order_customer['first_name'] = self.get_value_metadata(order_meta, '_billing_first_name', '') order_customer['last_name'] = self.get_value_metadata(order_meta, '_billing_last_name', '') order_data['customer'] = order_customer # TODO: Plugin WooCommerce Points and Rewards if self._notice['src']['support'].get('customer_point_rewards'): customer_point_rewards = dict() customer_point_rewards['reward_point'] = list() customer_point_rewards['reward_point_log'] = list() wc_points_rewards_user_points = get_list_from_list_by_field(orders_ext['data']['wc_points_rewards_user_points'], 'order_id', order['ID']) if wc_points_rewards_user_points: for points_rewards_user_points in wc_points_rewards_user_points: reward_point = dict() reward_point['points'] = points_rewards_user_points['points'] reward_point['points_balance'] = points_rewards_user_points['points_balance'] reward_point['user_id'] = points_rewards_user_points['user_id'] reward_point['created_at'] = points_rewards_user_points['date'] customer_point_rewards['reward_point'].append(reward_point) wc_points_rewards_user_points_log = get_list_from_list_by_field(orders_ext['data']['wc_points_rewards_user_points_log'], 'order_id', order['ID']) if wc_points_rewards_user_points_log: for points_rewards_user_points_log in wc_points_rewards_user_points_log: reward_point_log = dict() reward_point_log['points'] = points_rewards_user_points_log['points'] reward_point_log['type'] = points_rewards_user_points_log['type'] reward_point_log['user_points_id'] = points_rewards_user_points_log['user_points_id'] reward_point_log['user_id'] = points_rewards_user_points_log['user_id'] reward_point_log['admin_user_id'] = points_rewards_user_points_log['admin_user_id'] reward_point_log['data'] = points_rewards_user_points_log['data'] reward_point_log['created_at'] = points_rewards_user_points_log['date'] customer_point_rewards['reward_point_log'].append(reward_point_log) order_data['point_rewards'] = customer_point_rewards # customer address customer_address = self.construct_order_address() customer_address = self.add_construct_default(customer_address) customer_address['first_name'] = self.get_value_metadata(order_meta, '_billing_first_name', '') customer_address['last_name'] = self.get_value_metadata(order_meta, '_billing_last_name', '') customer_address['email'] = self.get_value_metadata(order_meta, '_billing_email', '') customer_address['address_1'] = self.get_value_metadata(order_meta, '_billing_address_1', '') customer_address['address_2'] = self.get_value_metadata(order_meta, '_billing_address_2', '') customer_address['city'] = self.get_value_metadata(order_meta, '_billing_city', '') customer_address['postcode'] = self.get_value_metadata(order_meta, '_billing_postcode', '') customer_address['telephone'] = self.get_value_metadata(order_meta, '_billing_phone', '') customer_address['company'] = self.get_value_metadata(order_meta, '_billing_company', '') customer_address['country']['code'] = self.get_value_metadata(order_meta, '_billing_country', '') customer_address['country']['country_code'] = self.get_value_metadata(order_meta, '_billing_country', '') customer_address['country']['name'] = self.get_country_name_by_code(customer_address['country']['country_code']) customer_address['state']['state_code'] = self.get_value_metadata(order_meta, '_billing_state', '') customer_address['state']['code'] = customer_address['state']['state_code'] order_data['customer_address'] = customer_address # billing address order_billing = self.construct_order_address() order_billing = self.add_construct_default(order_billing) order_billing['first_name'] = self.get_value_metadata(order_meta, '_billing_first_name', '') order_billing['last_name'] = self.get_value_metadata(order_meta, '_billing_last_name', '') order_billing['email'] = self.get_value_metadata(order_meta, '_billing_email', '') order_billing['address_1'] = self.get_value_metadata(order_meta, '_billing_address_1', '') order_billing['address_2'] = self.get_value_metadata(order_meta, '_billing_address_2', '') order_billing['city'] = self.get_value_metadata(order_meta, '_billing_city', '') order_billing['postcode'] = self.get_value_metadata(order_meta, '_billing_postcode', '') order_billing['telephone'] = self.get_value_metadata(order_meta, '_billing_phone', '') order_billing['company'] = self.get_value_metadata(order_meta, '_billing_company', '') order_billing['country']['code'] = self.get_value_metadata(order_meta, '_billing_country', '') order_billing['country']['country_code'] = self.get_value_metadata(order_meta, '_billing_country', '') order_billing['country']['name'] = self.get_country_name_by_code(order_billing['country']['country_code']) order_billing['state']['state_code'] = self.get_value_metadata(order_meta, '_billing_state', '') order_billing['state']['code'] = order_billing['state']['state_code'] order_billing['code'] = self.convert_attribute_code(to_str(order_billing['first_name']) + '-' + to_str(order_billing['last_name']) + '-' + to_str(order_billing['address_1']) + '-' + to_str(order_billing['address_2'])) order_data['billing_address'] = order_billing # shipping address order_delivery = self.construct_order_address() order_delivery = self.add_construct_default(order_delivery) order_delivery['first_name'] = self.get_value_metadata(order_meta, '_shipping_first_name', '') order_delivery['last_name'] = self.get_value_metadata(order_meta, '_shipping_last_name', '') order_delivery['email'] = self.get_value_metadata(order_meta, '_shipping_email', '') order_delivery['address_1'] = self.get_value_metadata(order_meta, '_shipping_address_1', '') order_delivery['address_2'] = self.get_value_metadata(order_meta, '_shipping_address_2', '') order_delivery['city'] = self.get_value_metadata(order_meta, '_shipping_city', '') order_delivery['postcode'] = self.get_value_metadata(order_meta, '_shipping_postcode', '') order_delivery['telephone'] = self.get_value_metadata(order_meta, '_shipping_phone', '') if self.get_value_metadata(order_meta, '_shipping_phone', '') else self.get_value_metadata(order_meta, '_shipping_Phone_No', '') order_delivery['company'] = self.get_value_metadata(order_meta, '_shipping_company', '') order_delivery['country']['code'] = self.get_value_metadata(order_meta, '_shipping_country', '') order_delivery['country']['country_code'] = self.get_value_metadata(order_meta, '_shipping_country', '') order_delivery['country']['name'] = self.get_country_name_by_code(order_delivery['country']['country_code']) order_delivery['state']['state_code'] = self.get_value_metadata(order_meta, '_shipping_state', '') order_delivery['state']['code'] = order_delivery['state']['state_code'] order_delivery['code'] = self.convert_attribute_code(to_str(order_delivery['first_name']) + '-' + to_str(order_delivery['last_name']) + '-' + to_str(order_delivery['address_1']) + '-' + to_str(order_delivery['address_2'])) order_data['shipping_address'] = order_delivery # order_data['user_history'] = self.get_value_metadata(order_meta, '_user_history', '') order_products = get_list_from_list_by_field(order_items, 'order_item_type', 'line_item') order_items = list() for order_product in order_products: order_product_metas = get_list_from_list_by_field(orders_ext['data']['woocommerce_order_itemmeta'], 'order_item_id', order_product['order_item_id']) qty = self.get_value_metadata(order_product_metas, '_qty', 1) if to_int(qty) == 0: qty = 1 order_item_subtotal = self.get_value_metadata(order_product_metas, '_line_subtotal', 0.0000) order_item = self.construct_order_item() order_item = self.add_construct_default(order_item) order_item['id'] = order_product['order_item_id'] order_item['product']['id'] = self.get_value_metadata(order_product_metas, '_variation_id', self.get_value_metadata(order_product_metas, '_product_id', 0)) order_item['product']['code'] = self.get_value_metadata(order_product_metas, '_product_code', 0) product_meta = get_list_from_list_by_field(orders_ext['data']['products_meta'], 'post_id', order_item['product']['id']) order_item['product']['sku'] = self.get_value_metadata(product_meta, '_sku', '') order_item['product']['name'] = order_product['order_item_name'] order_item['qty'] = to_decimal(qty) if qty != '' else 1 order_item['price'] = to_decimal(order_item_subtotal) / to_decimal(qty) if (qty != 0 and qty != '') else 0 order_item['original_price'] = to_decimal(order_item_subtotal) / to_decimal(qty) if (qty != 0 and qty != '') else 0 order_item['tax_amount'] = self.get_value_metadata(order_product_metas, '_line_tax', 0.0000) order_item['subtotal'] = order_item_subtotal order_item['total'] = self.get_value_metadata(order_product_metas, '_line_total', 0.0000) order_item['options'] = list() if order_product['order_item_type'] == 'line_item': order_item_options = list() keys = {'_qty', '_tax_class', '_product_id', '_variation_id', '_line_subtotal', '_line_subtotal_tax', '_line_total', '_line_tax', '_line_tax_data', '_original_order_item_id'} for order_product_meta in order_product_metas: if order_product_meta['meta_key'] not in keys: order_item_option = self.construct_order_item_option() # order_item_option['option_name'] = order_product_meta['meta_key'] order_item_option['option_name'] = unquote(order_product_meta['meta_key']) if order_item_option['option_name'] and 'pa_' in order_item_option['option_name']: continue order_item_option['option_value_name'] = order_product_meta['meta_value'] # unquote(order_product['order_item_name']) order_item_options.append(order_item_option) order_item['options'] = order_item_options order_items.append(order_item) order_data['items'] = order_items order_notes = get_list_from_list_by_field(orders_ext['data']['order_note'], 'comment_post_ID', order['ID']) order_history = list() for order_note in order_notes: order_note_meta = get_list_from_list_by_field(orders_ext['data']['order_note_meta'], 'comment_id', order_note['comment_ID']) order_history = self.construct_order_history() order_history = self.add_construct_default(order_history) order_history['id'] = order_note['comment_ID'] order_history['status'] = order_note['comment_approved'] order_history['comment'] = order_note['comment_content'] order_history['notified'] = self.get_value_metadata(order_note_meta, 'is_customer_note', False) order_history['created_at'] = convert_format_time(order_note['comment_date']) order_data['history'].append(order_history) order_payment = self.construct_order_payment() order_payment = self.add_construct_default(order_payment) order_payment['id'] = order['ID'] order_payment['method'] = self.get_value_metadata(order_meta, '_payment_method') order_payment['title'] = self.get_value_metadata(order_meta, '_payment_method_title') # custom order_number plugin WooCommerce Sequential Order Numbers # order_data['order_number'] = self.get_value_metadata(order_meta, '_order_number', '') # order_data['order_number_formatted'] = self.get_value_metadata(order_meta, '_order_number_formatted', '') # order_data['order_number_meta'] = self.get_value_metadata(order_meta, '_order_number_meta', '') order_data['payment'] = order_payment return response_success(order_data) def get_order_id_import(self, convert, order, orders_ext): return order['ID'] def check_order_import(self, convert, order, orders_ext): return self.get_map_field_by_src(self.TYPE_ORDER, convert['id'], convert['code']) def update_order_after_demo(self, order_id, convert, order, orders_ext): all_queries = list() delete_query = list() # order item delete_query_child = { 'type': 'delete', 'query': 'DELETE FROM _DBPRF_woocommerce_order_itemmeta WHERE order_item_id IN (SELECT order_item_id FROM _DBPFF_woocommerce_order_items WHERE order_id = ' + to_str(order_id) + ')' } delete_query.append(delete_query_child) delete_query.append(self.create_delete_query_connector('woocommerce_order_items', {'order_id': order_id})) self.import_multiple_data_connector(delete_query, 'delete_ord_update') order_items = convert['items'] for item in order_items: order_item_data = { 'order_item_name': item['product']['name'], 'order_item_type': 'line_item', 'order_id': order_id } order_item_query = self.create_insert_query_connector("woocommerce_order_items", order_item_data) order_item_id = self.import_data_connector(order_item_query, 'order') product_id = self.get_map_field_by_src(self.TYPE_PRODUCT, item['product']['id']) if not product_id: product_id = self.get_map_field_by_src(self.TYPE_PRODUCT, None, item['product']['id']) if not product_id: product_id = 0 order_item_meta = { '_qty': item['qty'], '_tax_class': '', '_product_id': product_id, '_variation_id': '', '_line_subtotal': item['subtotal'], '_line_total': item['total'], '_line_subtotal_tax': 0, '_line_tax': 0, '_line_tax_data': php_serialize({ 'total': 0, 'subtotal': 0 }), } for meta_key, meta_value in order_item_meta.items(): meta_insert = { 'order_item_id': order_item_id, 'meta_key': meta_key, 'meta_value': meta_value } meta_query = self.create_insert_query_connector("woocommerce_order_itemmeta", meta_insert) all_queries.append(meta_query) for option in item['options']: meta_insert = { 'order_item_id': order_item_id, 'meta_key': option['option_name'], 'meta_value': option['option_value_name'] } meta_query = self.create_insert_query_connector("woocommerce_order_itemmeta", meta_insert) all_queries.append(meta_query) return response_success() def router_order_import(self, convert, order, orders_ext): return response_success('order_import') def before_order_import(self, convert, order, orders_ext): return response_success() def order_import(self, convert, order, orders_ext): order_post = { 'post_author' : 1, 'post_date' : convert.get('created_at') if convert.get('created_at') else get_current_time(), 'post_date_gmt' : convert['updated_at'] if convert['updated_at'] is not None else get_current_time(), 'post_content' : '', 'post_excerpt': '', 'post_status': 'wc-completed', 'ping_status': 'closed', 'post_password': '', 'post_name': '', 'to_ping': '', 'pinged': '', 'post_modified': convert.get('created_at') if convert.get('created_at') else get_current_time(), 'post_modified_gmt': convert['updated_at'] if convert['updated_at'] is not None else get_current_time(), 'post_content_filtered': '', 'post_parent': '', 'guid': '', 'menu_order': '', 'post_type': 'shop_order', 'post_mime_type': '', 'comment_count': '', } order_post_query = self.create_insert_query_connector('posts', order_post) customer_id = self.import_data_connector(order_post_query, 'order') if not customer_id: return response_warning('order' + to_str(convert['id']) + ' import false.') return response_success() def after_order_import(self, order_id, convert, order, orders_ext): order_post = { 'post_author': 1, 'post_date': convert['created_at'] if convert['created_at'] else get_current_time(), 'post_date_gmt': convert['created_at'] if convert['created_at'] else get_current_time(), 'post_content': '', 'post_title': 'Order', 'post_excerpt': '', 'post_status': 'wc-completed', 'comment_status': 'open', 'ping_status': 'closed', 'post_name': 'order', 'to_ping': '', 'pinged': '', 'post_modified': convert['updated_at'] if convert['updated_at'] else get_current_time(), 'post_modified_gmt': convert['updated_at'] if convert['updated_at'] else get_current_time(), 'post_content_filtered': '', 'post_parent': 0, 'guid': '', 'menu_order': 0, 'post_type': 'shop_order', 'comment_count': 0, } order_query = self.create_insert_query_connector('posts', order_post) order_id = self.import_order_data_connector(order_query, 'order') if not order_id: return response_warning('Order ' + to_str(convert['id']) + ' import false.') self.insert_map(self.TYPE_ORDER, convert['id'], order_id, convert['code']) return response_success(order_id) def after_order_import(self, order_id, convert, order, orders_ext): all_queries = list() billing_address = convert['billing_address'] shipping_address = convert['shipping_address'] order_meta = { '_billing_first_name': billing_address['first_name'], '_billing_last_name': billing_address['last_name'], '_billing_company': billing_address['company'], '_billing_address_1': billing_address['address_1'], '_billing_address_2': billing_address['address_2'], '_billing_city': billing_address['city'], '_billing_state': get_value_by_key_in_dict(billing_address['state'], 'state_code', billing_address['state']['name']) if billing_address and billing_address['state'] else '', '_billing_country': get_value_by_key_in_dict(billing_address['country'], 'country_code', '') if billing_address and billing_address['country'] else '', '_billing_postcode': billing_address['postcode'], '_billing_phone': billing_address['telephone'], '_shipping_first_name': shipping_address['first_name'], '_shipping_last_name': shipping_address['last_name'], '_shipping_company': shipping_address['company'], '_shipping_address_1': shipping_address['address_1'], '_shipping_address_2': shipping_address['address_2'], '_shipping_city': shipping_address['city'], '_shipping_state': get_value_by_key_in_dict(shipping_address['state'], 'state_code', billing_address['state']['name']) if billing_address and billing_address['state'] else '', '_shipping_country': get_value_by_key_in_dict(shipping_address['country'], 'country_code', '') if billing_address and billing_address['country'] else '', '_shipping_postcode': shipping_address['postcode'], '_shipping_phone': shipping_address['telephone'], '_order_total': convert['total']['amount'], } for meta_key, meta_value in order_meta.items(): meta_insert = { 'post_id': order_id, 'meta_key': meta_key, 'meta_value': meta_value } meta_query = self.create_insert_query_connector("postmeta", meta_insert) all_queries.append(meta_query) order_items = convert['items'] for item in order_items: order_item_data = { 'order_item_name': item['product']['name'], 'order_item_type': 'line_item', 'order_id': order_id } order_item_query = self.create_insert_query_connector("woocommerce_order_items", order_item_data) order_item_id = self.import_data_connector(order_item_query, 'order') product_id = self.get_map_field_by_src(self.TYPE_PRODUCT, item['product']['id'], item['product']['code']) if self.is_wpml(): product_id = self.get_map_field_by_src(self.TYPE_PRODUCT, item['product']['id'], item['product']['code'], self._notice['target']['language_default']) else: product_id = 0 subtotal = item.get('subtotal', to_decimal(item['price']) * to_int(item['qty'])) if to_int(subtotal) == 0: subtotal = item['price'] order_item_meta = { '_qty': item['qty'], '_tax_class': '', '_product_id': product_id, '_variation_id': '', '_line_subtotal': subtotal, '_line_total': subtotal, '_line_subtotal_tax': 0, '_line_tax': 0, '_line_tax_data': php_serialize({ 'total': 0, 'subtotal': 0 }) } if product_id == 0 and item['product']['sku']: order_item_meta['SKU'] = item['product']['sku'] for meta_key, meta_value in order_item_meta.items(): meta_insert = { 'order_item_id': order_item_id, 'meta_key': meta_key, 'meta_value': meta_value } meta_query = self.create_insert_query_connector("woocommerce_order_itemmeta", meta_insert) all_queries.append(meta_query) for option in item['options']: meta_insert = { 'order_item_id': order_item_id, 'meta_key': option['option_name'], 'meta_value': option['option_value_name'] } meta_query = self.create_insert_query_connector("woocommerce_order_itemmeta", meta_insert) all_queries.append(meta_query) if all_queries: self.import_multiple_data_connector(all_queries, 'order') return response_success() def addition_order_import(self, convert, order, orders_ext): return response_success() # TODO: REVIEW def prepare_reviews_import(self): return self def prepare_reviews_export(self): return self def get_reviews_main_export(self): id_src = self._notice['process']['reviews']['id_src'] limit = self._notice['setting']['reviews'] query = { 'type': 'select', 'query': "SELECT cm.*, p.post_type FROM _DBPRF_comments AS cm " "LEFT JOIN _DBPRF_posts AS p ON p.ID = cm.comment_post_ID " "WHERE p.post_type = 'product' AND cm.comment_ID > " + to_str( id_src) + " ORDER BY cm.comment_ID ASC LIMIT " + to_str(limit) } # reviews = self.get_connector_data(self.get_connector_url('query'), {'query': json.dumps(query)}) reviews = self.select_data_connector(query, 'reviews') if not reviews or reviews['result'] != 'success': return response_error() return reviews def get_product_download_data(self, product_id): query = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_postmeta WHERE meta_key = '_downloadable_files' AND post_id = " + to_str(product_id) } products = self.select_data_connector(query, 'products') if not products or products['result'] != 'success' or len(products['data']) == 0: return None return php_unserialize(products['data'][0]['meta_value']) def get_download_data(self, product_id): query = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_postmeta WHERE post_id = " + to_str(product_id) } products = self.select_data_connector(query, 'products') if not products or products['result'] != 'success' or len(products['data']) == 0: return None download_data = dict() for data in products['data']: if data['meta_key'] in ['_download_expiry', '_download_limit']: download_data[data['meta_key']] = data['meta_value'] if to_int(data['meta_value']) > 0 else None return download_data def get_reviews_ext_export(self, reviews): url_query = self.get_connector_url('query') reviews_ids = duplicate_field_value_from_list(reviews['data'], 'comment_ID') product_ids = duplicate_field_value_from_list(reviews['data'], 'comment_post_ID') review_ext_queries = { 'comment_meta': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_commentmeta WHERE comment_id IN " + self.list_to_in_condition( reviews_ids), }, 'product_info': { 'type': 'select', 'query': "SELECT * FROM _DBPRF_posts WHERE ID IN " + self.list_to_in_condition(product_ids), } } # reviews_ext = self.get_connector_data(url_query, {'serialize': True, 'query': json.dumps(review_ext_queries)}) reviews_ext = self.select_multiple_data_connector(review_ext_queries, 'reviews') if not reviews_ext or reviews_ext['result'] != 'success': return response_error() return reviews_ext def convert_review_export(self, review, reviews_ext): review_data = self.construct_review() # review_data = self.add(review_data) review_data['id'] = review['comment_ID'] product_info = get_row_from_list_by_field(reviews_ext['data']['product_info'], 'ID', review['comment_post_ID']) review_data['product']['id'] = review['comment_post_ID'] if product_info: review_data['product']['code'] = product_info['post_name'] review_data['product']['name'] = product_info['post_title'] review_data['customer']['id'] = review['user_id'] review_data['customer']['code'] = review['comment_author_email'] review_data['customer']['name'] = review['comment_author'] review_data['title'] = '' review_data['content'] = review['comment_content'] rv_status = { '0': 2, # pending '1': 1, # approved 'spam': 3 # not approved } review_data['status'] = rv_status.get(to_str(review['comment_approved']), 'spam') review_data['created_at'] = convert_format_time(review['comment_date']) review_data['updated_at'] = convert_format_time(review['comment_date']) rating = self.construct_review_rating() review_meta = get_list_from_list_by_field(reviews_ext['data']['comment_meta'], 'comment_id', review['comment_ID']) rating['id'] = get_row_value_from_list_by_field(review_meta, 'comment_id', review['comment_ID'], 'meta_id') rating['rate_code'] = 'default' rating['rate'] = self.get_value_metadata(review_meta, 'rating', 5) review_data['rating'].append(rating) return response_success(review_data) def get_review_id_import(self, convert, review, reviews_ext): return review['comment_ID'] def check_review_import(self, convert, review, reviews_ext): return True if self.get_map_field_by_src(self.TYPE_REVIEW, convert['id'], convert['code']) else False def router_review_import(self, convert, review, reviews_ext): return response_success('review_import') def before_review_import(self, convert, review, reviews_ext): return response_success() def review_import(self, convert, review, reviews_ext): lang_code = self._notice['target']['language_default'] if convert.get('store_id'): lang_code = self._notice['map']['languages'].get(to_str(convert['store_id'])) product_id = False if convert['product']['id'] or convert['product']['code']: if self.is_wpml(): product_id = self.get_map_field_by_src(self.TYPE_PRODUCT, convert['product']['id'], convert['product']['code'], lang = lang_code) else: product_id = self.get_map_field_by_src(self.TYPE_PRODUCT, convert['product']['id'], convert['product']['code']) if not product_id: product_id = self.get_map_field_by_src(self.TYPE_PRODUCT, None, convert['product']['code'], lang = lang_code) if not product_id: msg = self.warning_import_entity('Review', convert['id'], convert['code'], 'product of review not exists.') return response_error(msg) customer_id = 0 if convert['customer']['id'] or convert['customer']['code']: customer_id = self.get_map_field_by_src(self.TYPE_CUSTOMER, convert['customer']['id']) if not customer_id: customer_id = 0 rv_status = { '2': 0, # pedding '1': 1, # approved '3': 'spam', # not approved '0': 0 } review_data = { 'comment_post_ID': product_id, 'comment_author': convert['customer']['name'], 'comment_author_email': '', 'comment_date': convert.get('created_at') if convert.get('created_at') else get_current_time(), 'comment_date_gmt': convert['updated_at'] if convert['updated_at'] is not None else get_current_time(), 'comment_content': convert['content'] if convert['content'] else '', 'comment_karma': 0, 'comment_approved': rv_status.get(str(convert['status']), 'spam'), 'comment_parent': 0, 'comment_type': "review", 'user_id': customer_id } review_query = self.create_insert_query_connector("comments", review_data) review_id = self.import_review_data_connector(review_query, True, convert['id']) if not review_id: msg = self.warning_import_entity('Review', convert['id'], convert['code']) return response_error(msg) self.insert_map(self.TYPE_REVIEW, convert['id'], review_id, convert['code']) return response_success(review_id) def after_review_import(self, review_id, convert, review, reviews_ext): ratings = convert['rating'] for rating in ratings: comment_meta = { 'rating': to_int(rating['rate']) } for meta_key, meta_value in comment_meta.items(): meta_insert = { 'comment_id': review_id, 'meta_key': meta_key, 'meta_value': meta_value } meta_query = self.create_insert_query_connector("commentmeta", meta_insert) self.import_data_connector(meta_query, 'review') return response_success() def addition_review_import(self, convert, review, reviews_ext): return response_success() # TODO: Page def check_page_import(self, convert, page, pages_ext): return True if self.get_map_field_by_src(self.TYPE_PAGE, convert['id'], convert['code'], lang = self._notice['target']['language_default']) else False def page_import(self, convert, page, pages_ext): language_code = convert.get('language_code') if self.is_wpml() and not language_code: language_code = self._notice['target']['language_default'] code_name = convert['title'] code_name = self.sanitize_title(code_name).strip('-') if self.is_wpml() and language_code: code_name = code_name + '-' + language_code check_slug_exist = True while check_slug_exist: check_slug_exist = True if self.select_map(self._migration_id, self.TYPE_PAGE, None, None, None, code_name, None, language_code) else False if check_slug_exist: code_name += to_str(get_value_by_key_in_dict(convert, 'id', '')) parent_id = self.get_map_field_by_src(self.TYPE_PAGE, to_int(convert['parent_id']), None, language_code) if not parent_id: parent_id = 0 data = { 'post_author': 1, 'post_date': convert['created_at'] if convert['created_at'] and '0000-00-00' not in convert['created_at'] else get_current_time(), 'post_date_gmt': convert['created_at'] if convert['created_at'] and '0000-00-00' not in convert['created_at'] else get_current_time(), 'post_content': convert['content'] if convert['content'] else "", 'post_title': convert['title'], 'post_status': 'publish' if convert['status'] else 'trash', 'comment_status': convert.get('comment_status', 'open'), 'ping_status': 'open', 'post_name': code_name[:200], 'post_modified': convert['created_at'] if convert['created_at'] and '0000-00-00' not in convert['created_at'] else get_current_time(), 'post_modified_gmt': convert['created_at'] if convert['created_at'] and '0000-00-00' not in convert['created_at'] else get_current_time(), 'post_parent': parent_id, 'post_type': 'page', 'comment_count': 0, 'guid': '', 'post_excerpt': '', 'to_ping': '', 'pinged': '', 'post_content_filtered': '', 'menu_order': get_value_by_key_in_dict(convert, 'sort_order', 0) } page_query = self.create_insert_query_connector('posts', data) page_id = self.import_page_data_connector(page_query, True, convert['id']) if not page_id: return response_error('Page ' + to_str(convert['id']) + ' import false.') self.insert_map(self.TYPE_PAGE, convert['id'], page_id, convert['title'], code_name, None, language_code) return response_success(page_id) def after_page_import(self, page_id, convert, page, pages_ext): # data = { # 'guid': self._notice['target']['cart_url'] + '?p=' + str(page_id) # } # where_id = { # 'id': page_id # } # update_query = self.create_update_query_connector('posts', data, where_id) # self.import_data_connector(update_query, 'page') # data_meta = { # 'post_id': page_id, # 'meta_key': '_edit_lock', # 'meta_value': int(time.time()), # } # self.import_page_data_connector(self.create_insert_query_connector('postmeta', data_meta), True, convert['id']) # thumbnail_id = False # if convert['images']: # for image in convert['images']: # image_process = self.process_image_before_import(image['url'], image.get('path', '')) # image_import_path = self.uploadImageConnector(image_process, self.add_prefix_path(self.make_woocommerce_image_path(image_process['path']), self._notice['target']['config']['image_product'].rstrip('/'))) # if image_import_path: # product_image = self.remove_prefix_path(image_import_path, self._notice['target']['config']['image_product']) # image_details = self.get_sizes(image_process['url']) # thumbnail_id = self.wp_image(product_image, image_details) # postmeta = dict() # if thumbnail_id: # postmeta['_thumbnail_id'] = thumbnail_id # for meta_key, value in postmeta.items(): # postmeta_data = { # 'post_id': page_id, # 'meta_key': meta_key, # 'meta_value': value # } # self.import_page_data_connector(self.create_insert_query_connector('postmeta', postmeta_data), True, convert['id']) # data_revision = { # 'post_author': 1, # 'post_date': convert['created_at'] if convert['created_at'] and '0000-00-00' not in convert['created_at'] else get_current_time(), # 'post_date_gmt': convert['created_at'] if convert['created_at'] and '0000-00-00' not in convert['created_at'] else get_current_time(), # 'post_content': convert['content'], # 'post_title': convert['title'], # 'post_status': 'inherit', # 'comment_status': 'closed', # 'ping_status': 'closed', # 'post_name': str(page_id) + '-revision-v1', # 'post_modified': convert['created_at'] if convert['created_at'] and '0000-00-00' not in convert['created_at'] else get_current_time(), # 'post_modified_gmt': convert['created_at'] if convert['created_at'] and '0000-00-00' not in convert['created_at'] else get_current_time(), # 'post_parent': page_id, # 'menu_order': get_value_by_key_in_dict(convert, 'sort_order', 0), # 'post_type': 'revision', # 'comment_count': 0, # 'guid': self._notice['target']['cart_url'] + '/2019/08/27/' + str(page_id) + '-revision-v1', # 'post_excerpt': '', # 'to_ping': '', # 'pinged': '', # 'post_content_filtered': '' # } # self.import_page_data_connector(self.create_insert_query_connector('posts', data_revision), True, convert['id']) super().after_page_import(page_id, convert, page, pages_ext) if self.is_wpml(): source_language_code = self._notice['target']['language_default'] language_code = convert.get('language_code') if not language_code: language_code = source_language_code source_language_code = None trid = convert.get('trid') if not trid: trid = self.get_new_trid() wpml_default = { 'element_type': 'post_page', 'element_id': page_id, 'trid': trid, 'language_code': language_code, 'source_language_code': source_language_code } self.import_data_connector(self.create_insert_query_connector("icl_translations", wpml_default), 'page') if not convert.get('language_code'): list_target_id = list() for src_language_id, target_language_id in self._notice['map']['languages'].items(): if target_language_id in list_target_id or to_str(target_language_id) == to_str(self._notice['target']['language_default']): continue list_target_id.append(target_language_id) page_lang = self.get_convert_data_language(convert, src_language_id) page_lang['trid'] = trid page_lang['language_code'] = target_language_id page_import = self.page_import(page_lang, page, pages_ext) if page_import['result'] == 'success': self.after_page_import(page_import['data'], page_lang, page, pages_ext) return response_success() # TODO: Coupon def prepare_coupons_import(self): return response_success() def prepare_coupons_export(self): return self def get_coupons_main_export(self): id_src = self._notice['process']['coupons']['id_src'] limit = self._notice['setting']['coupons'] query = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_posts WHERE ID > " + to_str(id_src) + " AND post_type = 'shop_coupon' ORDER BY ID ASC LIMIT " + to_str(limit), } coupons = self.select_data_connector(query, 'coupons') if not coupons or coupons['result'] != 'success': return response_error() return coupons def get_coupons_ext_export(self, coupons): coupon_ids = duplicate_field_value_from_list(coupons['data'], 'ID') coupon_id_con = self.list_to_in_condition(coupon_ids) coupon_ext_queries = { 'postmeta': { 'type': "select", 'query': "SELECT * FROM _DBPRF_postmeta WHERE post_id IN " + coupon_id_con }, } coupons_ext = self.select_multiple_data_connector(coupon_ext_queries, 'products') if (not coupons_ext) or coupons_ext['result'] != 'success': return response_error() return coupons_ext def convert_coupon_export(self, coupon, coupons_ext): coupon_data = self.construct_coupon() coupon_data['id'] = coupon['ID'] postmeta = get_list_from_list_by_field(coupons_ext['data']['postmeta'], 'post_id', coupon['ID']) coupon_data['code'] = coupon['post_title'] coupon_data['title'] = coupon['post_name'] coupon_data['description'] = coupon['post_excerpt'] coupon_data['status'] = True if coupon['post_status'] == 'publish' else False coupon_data['created_at'] = convert_format_time(coupon['post_date']) coupon_data['updated_at'] = convert_format_time(coupon['post_modified']) coupon_data['to_date'] = convert_format_time(self.get_value_metadata(postmeta, 'date_expires')) if not coupon_data['to_date']: coupon_data['to_date'] = convert_format_time(self.get_value_metadata(postmeta, 'expiry_date')) coupon_data['min_spend'] = self.get_value_metadata(postmeta, 'minimum_amount') if to_str(self.get_value_metadata(postmeta, 'minimum_amount')) != 'None' else None coupon_data['max_spend'] = self.get_value_metadata(postmeta, 'maximum_amount') if to_str(self.get_value_metadata(postmeta, 'maximum_amount')) != 'None' else None coupon_data['times_used'] = self.get_value_metadata(postmeta, 'usage_count') coupon_data['usage_limit'] = self.get_value_metadata(postmeta, 'usage_limit', 0) coupon_data['discount_amount'] = self.get_value_metadata(postmeta, 'coupon_amount') coupon_data['usage_per_customer'] = self.get_value_metadata(postmeta, 'usage_limit_per_user') coupon_data['type'] = self.PERCENT if self.get_value_metadata(postmeta, 'discount_type') == 'percent' else self.FIXED coupon_data['simple_free_shipping'] = 1 if self.get_value_metadata(postmeta, 'free_shipping') == 'yes' else 0 coupon_data['limit_usage_to_x_items'] = self.get_value_metadata(postmeta, 'limit_usage_to_x_items') product_ids = self.get_value_metadata(postmeta, 'product_ids') if product_ids: coupon_data['products'] = to_str(product_ids).split(',') category_ids = self.get_value_metadata(postmeta, 'product_categories') if category_ids: category_ids = php_unserialize(category_ids) if category_ids: coupon_data['categories'] = category_ids return response_success(coupon_data) def get_coupon_id_import(self, convert, coupon, coupons_ext): return coupon['ID'] def check_coupon_import(self, convert, coupon, coupons_ext): return True if self.get_map_field_by_src(self.TYPE_COUPON, convert['id'], convert['code']) else False def router_coupon_import(self, convert, coupon, coupons_ext): return response_success('coupon_import') def before_coupon_import(self, convert, coupon, coupons_ext): return response_success() def coupon_import(self, convert, coupon, coupons_ext): coupon_data = { 'post_author': 1, 'post_date': convert['created_at'] if convert['created_at'] and '0000-00-00' not in convert['created_at'] else get_current_time(), 'post_date_gmt': convert['created_at'] if convert['created_at'] and '0000-00-00' not in convert['created_at'] else get_current_time(), 'post_content': '', 'post_title': convert['code'] if convert['code'] else convert['title'], 'post_excerpt': self.change_img_src_in_text(get_value_by_key_in_dict(convert, 'description', '')), 'post_status': "publish" if convert['status'] else "draft", 'comment_status': 'open', 'ping_status': 'closed', 'post_password': '', 'post_name': self.strip_html_tag(convert['title']), 'to_ping': '', 'pinged': '', 'post_modified': convert['updated_at'] if convert and convert['updated_at'] and '0000-00-00' not in convert['updated_at'] else get_current_time(), 'post_modified_gmt': convert['updated_at'] if convert and convert['updated_at'] and '0000-00-00' not in convert['updated_at'] else get_current_time(), 'post_content_filtered': '', 'post_parent': 0, 'guid': self._notice['target']['cart_url'] + "/?post_type=shop_coupon&p=", 'menu_order': convert.get('menu_order', 0), 'post_type': "shop_coupon", 'post_mime_type': '', 'comment_count': 0 } coupon_query = self.create_insert_query_connector('posts', coupon_data) coupon_import = self.import_data_connector(coupon_query, 'coupons', convert['id']) if not coupon_import: return response_error() self.insert_map(self.TYPE_COUPON, convert['id'], coupon_import, convert['code']) return response_success(coupon_import) def after_coupon_import(self, coupon_id, convert, coupon, coupons_ext): all_queries = list() product_ids = convert.get('products') if product_ids: product_id_map_arr = list() for product_id in product_ids: map_product_id = self.get_map_field_by_src(self.TYPE_PRODUCT, product_id) if map_product_id and map_product_id not in product_id_map_arr: product_id_map_arr.append(to_str(map_product_id)) if product_id_map_arr: product_ids = ','.join(product_id_map_arr) else: product_ids = None category_ids = convert.get('categories') cate_id_map_arr = list() if category_ids: for category_id in category_ids: map_cate_id = self.get_map_field_by_src(self.TYPE_CATEGORY, category_id) if map_cate_id and map_cate_id not in cate_id_map_arr: cate_id_map_arr.append(to_str(map_cate_id)) # if product_id_map_arr: # product_ids = ','.join(cate_id_map_arr) # else: # product_ids = None coupon_meta = { 'discount_type': 'percent' if convert['type'] == self.PERCENT else 'fixed_cart' if convert['type'] == self.FIXED else 'fixed_product', 'coupon_amount': convert['discount_amount'], 'usage_limit': convert['usage_limit'], 'usage_limit_per_user': convert['usage_per_customer'], 'free_shipping': 'yes' if 'simple_free_shipping' in convert and to_str(to_int(convert['simple_free_shipping'])) == '1' else 'no', 'usage_count': convert['times_used'], 'date_expires': convert['to_date'] if (convert['to_date'] and convert['to_date'] != '0000-00-00 00:00:00') else '', 'minimum_amount': convert['min_spend'], 'maximum_amount': convert['max_spend'], 'product_ids': product_ids if product_ids else None, 'product_categories': php_serialize(cate_id_map_arr) if cate_id_map_arr else '', 'customer_email': php_serialize(convert.get('customer')), 'limit_usage_to_x_items': convert.get('limit_usage_to_x_items', 0), } for meta_key, meta_value in coupon_meta.items(): meta_insert = { 'post_id': coupon_id, 'meta_key': meta_key, 'meta_value': str(meta_value).replace(')', '').replace(',', '').replace("'", '') } meta_query = self.create_insert_query_connector("postmeta", meta_insert) all_queries.append(meta_query) all_queries.append(self.create_update_query_connector('posts', {'guid': self._notice['target']['cart_url'] + "/?post_type=shop_coupon&p=" + to_str(coupon_id)}, {'ID': coupon_id})) self.import_multiple_data_connector(all_queries, 'coupons') return response_success() def addition_coupon_import(self, convert, coupon, coupons_ext): return response_success() def display_finish_target(self): migration_id = self._migration_id recent_exist = self.select_row(TABLE_RECENT, {'migration_id': migration_id}) notice = json.dumps(self._notice) if recent_exist: self.update_obj(TABLE_RECENT, {'notice': notice}, {'migration_id': migration_id}) else: self.insert_obj(TABLE_RECENT, {'notice': notice, 'migration_id': migration_id}) target_cart_type = self._notice['target']['cart_type'] target_setup_type = self.target_cart_setup(target_cart_type) # if target_setup_type == 'connector': token = self._notice['target']['config']['token'] url = self.get_connector_url('clearcache', token) self.get_connector_data(url) all_queries = list() all_queries.append({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_options` WHERE option_name = 'product_cat_children'" }) all_queries.append({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_options` WHERE option_name = '_transient_wc_attribute_taxonomies'" }) all_queries.append({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_options` WHERE `option_name` LIKE '%_transient_timeout_wc_report_customers%'" }) all_queries.append({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_options` WHERE `option_name` LIKE '%_transient_wc_report_customers%'" }) all_queries.append({ 'type': 'query', 'query': "DELETE FROM `_DBPRF_options` WHERE option_name = 'urlrewrite_type'" }) all_queries.append({ 'type': 'query', 'query': "UPDATE `_DBPRF_posts` SET `comment_count`= (SELECT COUNT(comment_ID) FROM `_DBPRF_comments` WHERE `_DBPRF_comments`.comment_post_ID = `_DBPRF_posts`.ID AND `_DBPRF_comments`.comment_approved = 1) WHERE `post_type` IN ('product', 'post')" }) all_queries.append({ 'type': 'query', 'query': "UPDATE `_DBPRF_postmeta` SET `meta_value`= (SELECT COUNT(comment_ID) FROM `_DBPRF_comments` WHERE `_DBPRF_comments`.comment_post_ID = `_DBPRF_postmeta`.post_id AND `_DBPRF_comments`.comment_approved = 1) WHERE `meta_key` = '_wc_review_count'" }) all_queries.append({ 'type': 'query', 'query': "UPDATE `_DBPRF_postmeta` SET `meta_value`= (SELECT AVG(cmta.`meta_value`) FROM `_DBPRF_comments` AS cmt LEFT JOIN `_DBPRF_commentmeta` AS cmta ON cmt.`comment_ID` = cmta.`comment_ID` WHERE cmt.`comment_post_ID` = `_DBPRF_postmeta`.`post_id` AND cmt.comment_approved = 1 AND cmta.`meta_key` = 'rating') WHERE `meta_key` = '_wc_average_rating'" }) # all_queries.append({ # 'type': 'query', # 'query': "UPDATE `_DBPRF_term_taxonomy` tt " # "SET tt.count = (SELECT COUNT( *) as total " # "FROM _DBPRF_term_relationships r JOIN _DBPRF_posts p ON r.object_id = p.ID " # "WHERE r.term_taxonomy_id = tt.term_taxonomy_id AND p.post_type = 'product' AND p.post_parent = '') " # "WHERE tt.taxonomy IN('product_cat', 'product_type', 'product_tag', 'product_brand')" # }) all_queries.append({ 'type': 'query', 'query': "UPDATE `_DBPRF_term_taxonomy` AS tt SET tt.count = (SELECT COUNT(1) AS total FROM _DBPRF_term_relationships AS tr WHERE tt.term_taxonomy_id = tr.term_taxonomy_id AND tr.object_id IN (SELECT ID FROM _DBPRF_posts WHERE post_type = 'product'))" }) clear_cache = self.import_multiple_data_connector(all_queries) option_data = { 'option_name': 'urlrewrite_type', 'option_value': 'urlrewrite', 'autoload': 'yes' } if self._notice['support'].get('seo_301'): option_data = { 'option_name': 'urlrewrite_type', 'option_value': 'url301', 'autoload': 'yes' } option_query = self.create_insert_query_connector('options', option_data) option_import = self.import_data_connector(option_query, 'options') return response_success() def substr_replace(self, subject, replace, start, length): if length == None: return subject[:start] + replace elif length < 0: return subject[:start] + replace + subject[length:] else: return subject[:start] + replace + subject[start + length:] def add_construct_default(self, construct): construct['site_id'] = 1 construct['language_id'] = self._notice['src']['language_default'] return construct def get_term_by_name(self, data): query = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_term_taxonomy AS tt " "LEFT JOIN _DBPRF_terms AS t ON t.term_id = tt.term_id " "WHERE tt.taxonomy = 'product_visibility' AND t.name = '" + data + "'" } product_taxonomy = self.select_data_connector(query) if product_taxonomy['result'] == 'success' and product_taxonomy['data']: return product_taxonomy['data'][0]['term_taxonomy_id'] return None def get_product_type(self, product_type): if not self.product_types: query = { 'type': 'select', 'query': "SELECT * FROM _DBPRF_term_taxonomy AS tt " "LEFT JOIN _DBPRF_terms AS t ON t.term_id = tt.term_id " "WHERE tt.taxonomy = 'product_type'" } product_types = self.select_data_connector(query) if product_types['result'] == 'success' and product_types['data']: for product_type_row in product_types['data']: self.product_types[product_type_row['slug']] = product_type_row['term_taxonomy_id'] return self.product_types.get(product_type, 2) def import_category_parent(self, convert_parent, lang_code = None): category_type = self.TYPE_CATEGORY if convert_parent.get('is_blog'): category_type = self.TYPE_CATEGORY_BLOG parent_exists = self.get_map_field_by_src(category_type, convert_parent['id'], convert_parent['code'], lang_code) if parent_exists: return response_success(parent_exists) if self.is_wpml() and lang_code: convert_parent['language_code'] = lang_code for src_language_id, target_language_id in self._notice['map']['languages'].items(): if to_str(lang_code) == to_str(target_language_id): lang_data = convert_parent if to_str(src_language_id) in convert_parent['languages'] and convert_parent['languages'][to_str(src_language_id)]: lang_data = convert_parent['languages'][to_str(src_language_id)] convert_parent['name'] = lang_data['name'] convert_parent['description'] = lang_data['description'] convert_parent['short_description'] = lang_data['short_description'] convert_parent['meta_title'] = lang_data['meta_title'] convert_parent['meta_keyword'] = lang_data['meta_keyword'] convert_parent['meta_description'] = lang_data['meta_description'] convert_parent['url_key'] = lang_data.get('url_key', '') category = get_value_by_key_in_dict(convert_parent, 'category', dict()) categories_ext = get_value_by_key_in_dict(convert_parent, 'categories_ext', dict()) category_parent_import = self.category_import(convert_parent, category, categories_ext) self.after_category_import(category_parent_import['data'], convert_parent, category, categories_ext) return category_parent_import def get_list_from_list_by_field_as_first_key(self, list_data, field = '', first_key = ''): result = list() if isinstance(list_data, dict): for key, row in list_data.items(): if field in row: if row[field].find(first_key) == 0: result.append(row) else: if field and to_str(field) != '': for row in list_data: if field in row: if row[field].find(first_key) == 0: result.append(row) else: for row in list_data: if row: v_index = row.find(first_key) if v_index == 0: result.append(row) return result def process_image_before_import(self, url, path): if not path: full_url = url path = strip_domain_from_url(url) else: full_url = join_url_path(url, path) if path and path.find('/wp-content/uploads/') != -1: newpath = path.split('/wp-content/uploads/') if newpath and to_len(newpath) > 1: path = newpath[1] path = re.sub(r"[^a-zA-Z0-9.-_()]", '', path) full_url = self.parse_url(full_url) return { 'url': full_url, 'path': path } def wpml_attributes_to_in_condition(self, list_keys): if not list_keys: return "('null')" result = "('tax_" + "','tax_".join([str(k) for k in list_keys]) + "')" return result def brand_image_in_condition(self, term_ids): if not term_ids: return "('null')" result = "('brand_taxonomy_image" + "','brand_taxonomy_image".join([str(k) for k in term_ids]) + "')" return result def detect_seo(self): return 'default_seo' def categories_default_seo(self, category, categories_ext): result = list() seo_cate = self.construct_seo_category() seo_cate['request_path'] = self._notice['src']['config']['product_category_base'].strip('/') + '/' + to_str(category['slug']) seo_cate['default'] = True result.append(seo_cate) return result def products_default_seo(self, product, products_ext): result = list() if self._notice['src']['config']['product_base'].find('%product_cat%') != -1: term_relationship = get_list_from_list_by_field(products_ext['data']['term_relationship'], 'object_id', product['ID']) category_src = get_list_from_list_by_field(term_relationship, 'taxonomy', 'product_cat') if category_src: for product_category in category_src: seo_product = self.construct_seo_product() seo_product['request_path'] = self._notice['src']['config']['product_base'].strip('/') + '/' + to_str(product_category['slug']) + '/' + to_str(product['post_name']) seo_product['category_id'] = product_category['term_id'] result.append(seo_product) else: seo_product = self.construct_seo_product() seo_product['request_path'] = self._notice['src']['config']['product_base'].strip('/') + '/' + to_str(product['post_name']) seo_product['default'] = True result.append(seo_product) if product['post_name']: seo_product = self.construct_seo_product() seo_product['request_path'] = to_str(product['post_name']) seo_product['default'] = True result.append(seo_product) return result def get_order_status_label(self, order_status): if not order_status: return '' order_status = order_status.replace('wc-', '') order_status = order_status.replace('-', ' ') order_status = order_status.capitalize() return order_status def get_woo_attribute_id(self, pro_attr_code, attribute_name, language_code = None, language_attribute_data = None, attribute_type = 'select'): # if to_str(pro_attr_code)[0:3] != 'pa_': # pro_attr_code = "pa_" + pro_attr_code # if self.is_wpml() and language_code != self._notice['target']['language_default']: # attribute_data_default = self.get_convert_data_language(language_attribute_data, None, self._notice['target']['language_default'], 'option_languages') # option_lang_name = attribute_data_default.get('option_name') # if not option_lang_name: # option_lang_name = attribute_data_default.get('attribute_name') # if option_lang_name: pro_attr_code = urllib.parse.unquote(pro_attr_code) woo_attribute_id = self.get_map_field_by_src(self.TYPE_ATTR, None, 'pa_' + pro_attr_code) # if woo_attribute_id: # return woo_attribute_id if not woo_attribute_id: attribute_data = { 'attribute_name': pro_attr_code, 'attribute_type': attribute_type } attribute_result = self.select_data_connector(self.create_select_query_connector('woocommerce_attribute_taxonomies', attribute_data)) woo_attribute_id = None if attribute_result and attribute_result['data']: woo_attribute_id = attribute_result['data'][0]['attribute_id'] if not woo_attribute_id: pro_attr_data = { 'attribute_name': pro_attr_code, 'attribute_label': attribute_name, 'attribute_type': attribute_type, 'attribute_orderby': "menu_order", 'attribute_public': 0, } woo_attribute_id = self.import_data_connector(self.create_insert_query_connector('woocommerce_attribute_taxonomies', pro_attr_data), 'products') if woo_attribute_id: self.insert_map(self.TYPE_ATTR, None, woo_attribute_id, 'pa_' + pro_attr_code) if woo_attribute_id: if self.is_wpml(): attribute_data_lang = self.get_convert_data_language(language_attribute_data, None, language_code, 'option_languages') option_lang_name = attribute_data_lang.get('option_name') if not option_lang_name: option_lang_name = attribute_data_lang.get('attribute_name') if option_lang_name != attribute_name: translate_id = self.get_map_field_by_src('translate', woo_attribute_id, None, language_code) if not translate_id: translate_query = { 'icl_strings': self.create_select_query_connector('icl_strings', {'value': attribute_name, 'name': 'taxonomy singular name: ' + attribute_name}), 'icl_string_translations': { 'type': 'select', 'query': "select * from _DBPRF_icl_string_translations where string_id in (" + self.create_select_query_connector('icl_strings', {'value': attribute_name, 'name': 'taxonomy singular name: ' + attribute_name}, 'id')['query'] + ")" } } select = self.select_multiple_data_connector(translate_query) if select['result'] == 'success': icl_string_id = None is_tranlate = False if not select['data']['icl_strings']: icl_strings_data = { 'language': self._notice['target']['language_default'], 'context': 'WordPress', 'name': 'taxonomy singular name: ' + attribute_name, 'value': attribute_name, 'string_package_id': None, 'wrap_tag': '', 'type': 'LINE', 'title': None, 'status': 2, 'gettext_context': '', 'domain_name_context_md5': hashlib.md5(to_str('WordPresstaxonomy singular name: ' + attribute_name).encode()), 'translation_priority': 'optional', 'word_count': None } icl_string_id = self.import_product_data_connector(self.create_insert_query_connector('icl_strings', icl_strings_data)) else: icl_string = select['data']['icl_strings'][0] if icl_string['language'] != language_code: icl_string_id = icl_string['id'] check = get_row_from_list_by_field(select['data']['icl_string_translations'], 'language', language_code) is_tranlate = True if check else False else: is_tranlate = True if icl_string_id and not is_tranlate: icl_string_translations_data = { 'string_id': icl_string_id, 'language': language_code, 'status': 10, 'value': option_lang_name, 'translator_id': None, 'translation_service': '', 'batch_id': 0, 'translation_date': get_current_time() } icl_string_translation_id = self.import_product_data_connector(self.create_insert_query_connector('icl_string_translations', icl_string_translations_data)) if icl_string_translation_id: self.insert_map('translate', woo_attribute_id, icl_string_translation_id, None, None, None, language_code) return woo_attribute_id def get_woo_attribute_value(self, attribute_value, pro_attr_code, language_code = None, attribute_data = None, desc = ''): pro_attr_code = urllib.parse.unquote(pro_attr_code) if self.is_wpml(): value_data = self.get_convert_data_language(attribute_data, None, language_code, 'option_value_languages') if value_data: attribute_value = value_data['option_value_name'] attribute_value = to_str(attribute_value)[:200] slug_default = self.get_slug_attr(attribute_data) slug = self.get_slug_attr(attribute_data, language_code) opt_value_id = None # if opt_value_exist: # return opt_value_exist['id_desc'] # opt_value_exist = self.select_map(self._migration_id, self.TYPE_ATTR_VALUE, None, None, 'pa_' + pro_attr_code, None, slug) opt_value_exist = self.select_map(self._migration_id, self.TYPE_ATTR_VALUE, None, None, 'pa_' + pro_attr_code, None, slug, language_code) if opt_value_exist: if not self.is_wpml() or not language_code or language_code == self._notice['target']['language_default']: return opt_value_exist['id_desc'] else: opt_value_id = opt_value_exist['id_desc'] if not opt_value_id: query = { 'type': 'select', 'query': 'SELECT * FROM _DBPRF_terms AS term LEFT JOIN _DBPRF_term_taxonomy AS taxonomy ON term.term_id = taxonomy.term_id WHERE term.name = ' + self.escape(attribute_value) + " AND taxonomy.taxonomy = " + self.escape('pa_' + pro_attr_code) } attribute_result = self.select_data_connector(query) if attribute_result and attribute_result['data']: opt_value_id = attribute_result['data'][0]['term_taxonomy_id'] if not opt_value_id: if self.is_wpml() and language_code != self._notice['target']['language_default']: new_slug = slug_default + '-' + to_str(language_code) if slug == slug_default else slug else: new_slug = slug_default value_term = { 'name': attribute_value, 'slug': new_slug, 'term_group': 0, } term_id = self.import_product_data_connector(self.create_insert_query_connector('terms', value_term), 'products') value_term_taxonomy = { 'term_id': term_id, 'taxonomy': 'pa_' + pro_attr_code, 'description': desc, 'parent': 0, 'count': 0 } opt_value_id = self.import_product_data_connector(self.create_insert_query_connector('term_taxonomy', value_term_taxonomy), 'products') if opt_value_id: self.insert_map(self.TYPE_ATTR_VALUE, None, opt_value_id, 'pa_' + pro_attr_code, None, slug, language_code) if opt_value_id: if self.is_wpml(): attribute_data_lang = self.get_convert_data_language(attribute_data, None, language_code, 'option_value_languages') if attribute_data_lang['option_value_name'] != attribute_value: translate_query = { 'icl_translations': { 'type': 'select', 'query': 'select * from _DBPRF_icl_translations where trid in (select trid from wp_icl_translations where ' + self.dict_to_where_condition({'element_id': opt_value_id, 'element_type': 'tax_pa_' + pro_attr_code}) + ')' }, 'term': { 'type': 'select', 'query': 'SELECT * FROM _DBPRF_terms AS term LEFT JOIN _DBPRF_term_taxonomy AS taxonomy ON term.term_id = taxonomy.term_id WHERE term.name = ' + self.escape(attribute_data_lang['option_value_name']) + " AND taxonomy.taxonomy = " + self.escape('pa_' + pro_attr_code) } } select = self.select_multiple_data_connector(translate_query) if select['result'] == 'success': trid = None is_tranlate = False if not select['data']['icl_translations']: trid = self.get_new_trid() icl_translations_data = { 'language_code': self._notice['target']['language_default'], 'element_type': 'tax_pa_' + pro_attr_code, 'element_id': opt_value_id, 'trid': trid, 'source_language_code': None, } icl_translation_id = self.import_product_data_connector(self.create_insert_query_connector('icl_translations', icl_translations_data)) else: icl_translations = select['data']['icl_translations'][0] trid = icl_translations['trid'] check = get_row_from_list_by_field(select['data']['icl_translations'], 'language_code', language_code) is_tranlate = True if check else False if trid and not is_tranlate: new_slug = slug_default + '-' + to_str(language_code) if slug != slug_default else slug_default value_term = { 'name': attribute_data_lang['option_value_name'], 'slug': new_slug, 'term_group': 0, } term_id = self.import_product_data_connector(self.create_insert_query_connector('terms', value_term), 'products') value_term_taxonomy = { 'term_id': term_id, 'taxonomy': 'pa_' + pro_attr_code, 'description': desc, 'parent': 0, 'count': 0 } opt_value_id = self.import_product_data_connector(self.create_insert_query_connector('term_taxonomy', value_term_taxonomy), 'products') if opt_value_id: icl_translations_data = { 'language_code': language_code, 'element_type': 'tax_pa_' + pro_attr_code, 'element_id': opt_value_id, 'trid': trid, 'source_language_code': self._notice['target']['language_default'], } self.import_product_data_connector(self.create_insert_query_connector('icl_translations', icl_translations_data)) self.insert_map(self.TYPE_ATTR_VALUE, None, opt_value_id, 'pa_' + pro_attr_code, None, slug, language_code) return opt_value_id def to_timestamp(self, value, str_format = '%Y-%m-%d %H:%M:%S'): try: timestamp = to_int(time.mktime(time.strptime(value, str_format))) if timestamp: return timestamp return to_int(time.time()) except: return to_int(time.time()) def get_map_field_by_src(self, map_type = None, id_src = None, code_src = None, lang = None, field = 'id_desc'): if not self.is_wpml() and not self.is_polylang() or map_type in [self.TYPE_PATH_IMAGE, self.TYPE_IMAGE]: return super().get_map_field_by_src(map_type, id_src, code_src, field) if not id_src and not code_src: return False _migration_id = self._migration_id # if id_src: # code_src = None # else: # code_src = None map_data = self.select_map(_migration_id, map_type, id_src, None, code_src, None, None, lang) if not map_data: return False return map_data.get(field, False) def select_map(self, _migration_id = None, map_type = None, id_src = None, id_desc = None, code_src = None, code_desc = None, value = None, lang = None): if not self.is_wpml() and not self.is_polylang() or map_type in [self.TYPE_PATH_IMAGE, self.TYPE_IMAGE]: return super().select_map(_migration_id, map_type, id_src, id_desc, code_src, code_desc, value) where = dict() if _migration_id: where['migration_id'] = _migration_id if map_type: where['type'] = map_type if id_src: where['id_src'] = id_src if id_desc: where['id_desc'] = id_desc if code_src: where['code_src'] = code_src if code_desc: where['code_desc'] = code_desc if value: where['value'] = value if (self.is_wpml() or self.is_polylang()) and map_type in [self.TYPE_CATEGORY, self.TYPE_PRODUCT, self.TYPE_ATTR, self.TYPE_ATTR_VALUE]: where['lang'] = lang if not where: return None result = self.select_obj(TABLE_MAP, where) try: data = result['data'][0] except Exception as e: data = None return data def insert_map(self, map_type = None, id_src = None, id_desc = None, code_src = None, code_desc = None, value = None, lang = None): if to_int(id_src) == 0 and to_str(id_src) != '0': id_src = None data_inset = { 'migration_id': self._migration_id, 'type': map_type, 'id_src': id_src, 'code_src': code_src, 'id_desc': id_desc, 'code_desc': code_desc, 'value': value, } if self.is_wpml() or self.is_polylang(): data_inset['lang'] = lang insert = self.insert_obj(TABLE_MAP, data_inset) if (not insert) or (insert['result'] != 'success'): return False return insert['data'] def is_wpml(self): return self._notice[self.get_type()]['support'].get('wpml') def is_polylang(self): return self._notice[self.get_type()]['support'].get('polylang') def get_convert_data_language(self, convert, src_language_id = None, target_language_id = None, key_language = 'languages'): if not self.is_wpml() and not self.is_polylang(): return convert list_language_data = convert.get(key_language) if not list_language_data: return convert language_data = None if src_language_id: if list_language_data.get(to_str(src_language_id)): language_data = list_language_data[to_str(src_language_id)] elif target_language_id: for src_id, data in list_language_data.items(): if self._notice['map']['languages'].get(to_str(src_id)) == target_language_id: language_data = data break if not language_data: return convert for key_lang, value in language_data.items(): if not value: continue if key_lang == 'option_value_name' and convert.get('option_type') == self.OPTION_MULTISELECT and 'position_option' in convert: value_lang = to_str(value).split(';') if len(value_lang) > to_int(convert.get('position_option')): value = value_lang[to_int(convert.get('position_option'))] convert[key_lang] = value return convert def get_pro_attr_code_default(self, option): if self.is_wpml(): option = self.get_convert_data_language(option, None, self._notice['target']['language_default'], 'option_languages') pro_attr_code = to_str(option['option_name']).lower() # attribute_name = option['option_name'] pro_attr_code = pro_attr_code.replace(' ', '_') if option['option_code']: pro_attr_code = to_str(option['option_code']).lower() pro_attr_code = pro_attr_code.replace(' ', '_') pro_attr_code_len = 28 check_encode = chardet.detect(pro_attr_code.encode()) if check_encode['encoding'] != 'ascii': pro_attr_code = pro_attr_code[0:14] pro_attr_code_len = 200 pro_attr_code = self.sanitize_title(pro_attr_code, pro_attr_code_len) return pro_attr_code def get_slug_attr(self, option_value, language_code = None): if option_value['option_value_code']: return self.sanitize_title(to_str(option_value['option_value_code'])).lower() attribute_value = option_value['option_value_name'] if self.is_wpml(): if not language_code: language_code = self._notice['target']['language_default'] value_data = self.get_convert_data_language(option_value, None, language_code, 'option_value_languages') if value_data: attribute_value = value_data['option_value_name'] return self.sanitize_title(to_str(attribute_value).lower()) def get_key_check_default(self, attributes): key_check = '' for children_attribute in attributes: if self.is_wpml(): children_attribute = self.get_convert_data_language(children_attribute, None, self._notice['target']['language_default'], 'option_value_languages') if key_check: key_check += '|' key_check += to_str(children_attribute['option_name']) + ':' + to_str(children_attribute['option_value_name']) return key_check def lecm_rewrite_table_construct(self): return { 'table': '_DBPRF_lecm_rewrite', 'rows': { 'id': 'INT(11) NOT NULL AUTO_INCREMENT PRIMARY KEY', 'link': 'VARCHAR(255)', 'type': 'VARCHAR(255)', 'type_id': 'INT(11)', 'redirect_type': 'SMALLINT(5)', }, } def is_woo2woo(self): return self._notice['src']['cart_type'] == self._notice['target']['cart_type'] def check_sync_child(self, child, combination, check_any = False): for attribute in combination: if not check_any: if to_str(child.get(attribute['option_name'])) != to_str(attribute['option_value_name']): if to_str(child.get(to_str(attribute['option_code']).replace(' ', '-'))) != to_str(attribute['option_value_name']): return False elif to_str(child.get(attribute['option_name'])) and to_str(child.get(to_str(attribute['option_code']).replace(' ', '-'))) != to_str(attribute['option_value_name']): return False return True def select_all_category_map(self): where = dict() where['migration_id'] = self._migration_id where['type'] = self.TYPE_CATEGORY if not self.blog_running else self.TYPE_CATEGORY_BLOG result = self.select_obj(TABLE_MAP, where) data = list() if result['result'] == 'success' and result['data']: data = result['data'] result_data = list() if data: for row in data: value = row['id_desc'] result_data.append(value) return result_data def create_file_variant_limit(self): file_path = get_pub_path() + '/media/' + to_str(self._migration_id) if not os.path.exists(file_path): os.makedirs(file_path, mode = 0o777) file_name = file_path + '/variants.csv' column = ['src_id', 'target_id', 'name', 'sku', 'variants'] with open(file_name, mode = 'a') as employee_file: employee_writer = csv.writer(employee_file, delimiter = ',', quotechar = '"', quoting = csv.QUOTE_MINIMAL) employee_writer.writerow(column) return def warning_variant_limit(self, convert): if convert['id']: product = "#" + to_str(convert['id']) else: product = ': ' + to_str(convert['code']) self.sleep_time(0, 'variant', True, msg = product) def log_variant_limit(self, product_id, convert, variants): self.is_variant_limit = True file_name = get_pub_path() + '/media/' + to_str(self._migration_id) + '/variants.csv' if not os.path.isfile(file_name): self.create_file_variant_limit() column = [convert['id'] if convert['id'] else convert['code'], product_id, convert['name'], convert['sku'], variants] with open(file_name, mode = 'a') as employee_file: employee_writer = csv.writer(employee_file, delimiter = ',', quotechar = '"', quoting = csv.QUOTE_MINIMAL) employee_writer.writerow(column) return def check_slug_exist(self, slug = None): select = { 'slug': slug, } category_data = self.select_data_connector(self.create_select_query_connector('terms', select)) try: term_id = category_data['data'][0]['term_id'] except Exception: term_id = False return term_id def get_query_img_wpml(self, img_id, language_code): source_language_code = self._notice['target']['language_default'] default_language_code = language_code if source_language_code == default_language_code: default_language_code = source_language_code source_language_code = None trid = self.get_new_trid() wpml_img_data = { 'element_type': 'post_attachment', 'element_id': img_id, 'trid': trid, 'language_code': default_language_code, 'source_language_code': source_language_code } wpml_img_query = self.create_insert_query_connector("icl_translations", wpml_img_data) return wpml_img_query def check_exist_code_product(self, code_product): check = self.select_data_connector(self.create_select_query_connector('posts', {'posttype'})) def _get_customer_lookup_id(self, user_id): if not user_id: return 0 select = { 'user_id': user_id, } customer_lookup_data = self.select_data_connector(self.create_select_query_connector('wc_customer_lookup', select)) try: customer_lookup_id = customer_lookup_data['data'][0]['customer_id'] except Exception: customer_lookup_id = 0 return customer_lookup_id

[ "noreply@github.com" ]

phamjmanh.noreply@github.com

c20964abbec15db7585fd3751381d8fa15369663

615e9f144757adb7bf5c7f339416207d61937f72

/Input/eingabe_gehalt.py

fa72b411532a187e3687427ce28b1246bdc8717e

[]

no_license

sewei9/Python-Fundamentals

8b6e608606bad598ac0ead6b913a11d380a7186c

b1dc4fcfcfc70ff6c43cdfbedfe78f006f05d8db

refs/heads/master

2020-06-05T03:21:40.618410

2020-02-07T10:16:39

192,296,257

0

null

2020-02-07T10:16:40

2019-06-17T07:27:17

Python

UTF-8

Python

false

336

py

#Eingabe Bruttogehalt print("Bitte geben Sie ihr Bruttogehalt in Euro an:") xgh = float(input()) # Eingabe in Zahl umwandeln zahl = int(xgh) # Berechnung des Bruttogehalts steuern = xgh * 0.18 bg = xgh - xgh * 0.18 #Ausgabe Bruttogehalt print("Ihre Steuerabgaben belaufen sich auf:", steuern) print("Ihr Nettogehalt beträgt:", bg)

[ "sebastian.weiss2@ikea.com" ]

sebastian.weiss2@ikea.com

0f265b3a2d2b97a028449761d2a6938118f65810

969cbaccd694c60b92eb14a3a3c51908bfb8217a

/kalkulator.py

eb221766207c846589c27df5ad2928b162cd434d

[]

no_license

Asia1506/kalkulator_if_2016

9ff2a1b82d2d1693ae69a379a96e6f1394fee801

891f38aac62a913be18bcf28a1ace40a5af49358

refs/heads/master

2021-01-01T04:55:52.968136

2016-05-10T18:15:21

58,479,869

0

null

UTF-8

Python

false

172

py

def get_info(): print("To jest program kalkulator. Autor: UEP") def dodawanie(a,b): return a+ b get_info() a = int(input()) b = int(input()) print(dodawanie(a,b))

[ "student@student.ue.poznan.pl" ]

student@student.ue.poznan.pl

66d3fe033d3d270d2c2da8ee4f9ac89370418fb2

0db05f7b843e8450bafd5ae23f8f70f9a9a8c151

/Src/StdLib/Lib/test/test_importhooks.py

1245cb9b7966882ffda9795583482614056031a7

[ "LicenseRef-scancode-unknown-license-reference", "Apache-2.0" ]

permissive

IronLanguages/ironpython2

9c7f85bd8e6bca300e16f8c92f6384cecb979a6a

d00111890ce41b9791cb5bc55aedd071240252c4

refs/heads/master

2023-01-21T21:17:59.439654

2023-01-13T01:52:15

91,620,472

1,171

288

Apache-2.0

2023-01-13T01:52:16

2017-05-17T21:11:51

Python

UTF-8

Python

false

8,432

py

import sys import imp import os import unittest from test import test_support test_src = """\ def get_name(): return __name__ def get_file(): return __file__ """ absimp = "import sub\n" relimp = "from . import sub\n" deeprelimp = "from .... import sub\n" futimp = "from __future__ import absolute_import\n" reload_src = test_src+"""\ reloaded = True """ test_co = compile(test_src, "<???>", "exec") reload_co = compile(reload_src, "<???>", "exec") test2_oldabs_co = compile(absimp + test_src, "<???>", "exec") test2_newabs_co = compile(futimp + absimp + test_src, "<???>", "exec") test2_newrel_co = compile(relimp + test_src, "<???>", "exec") test2_deeprel_co = compile(deeprelimp + test_src, "<???>", "exec") test2_futrel_co = compile(futimp + relimp + test_src, "<???>", "exec") test_path = "!!!_test_!!!" class TestImporter: modules = { "hooktestmodule": (False, test_co), "hooktestpackage": (True, test_co), "hooktestpackage.sub": (True, test_co), "hooktestpackage.sub.subber": (True, test_co), "hooktestpackage.oldabs": (False, test2_oldabs_co), "hooktestpackage.newabs": (False, test2_newabs_co), "hooktestpackage.newrel": (False, test2_newrel_co), "hooktestpackage.sub.subber.subest": (True, test2_deeprel_co), "hooktestpackage.futrel": (False, test2_futrel_co), "sub": (False, test_co), "reloadmodule": (False, test_co), } def __init__(self, path=test_path): if path != test_path: # if out class is on sys.path_hooks, we must raise # ImportError for any path item that we can't handle. raise ImportError self.path = path def _get__path__(self): raise NotImplementedError def find_module(self, fullname, path=None): if fullname in self.modules: return self else: return None def load_module(self, fullname): ispkg, code = self.modules[fullname] mod = sys.modules.setdefault(fullname,imp.new_module(fullname)) mod.__file__ = "<%s>" % self.__class__.__name__ mod.__loader__ = self if ispkg: mod.__path__ = self._get__path__() exec code in mod.__dict__ return mod class MetaImporter(TestImporter): def _get__path__(self): return [] class PathImporter(TestImporter): def _get__path__(self): return [self.path] class ImportBlocker: """Place an ImportBlocker instance on sys.meta_path and you can be sure the modules you specified can't be imported, even if it's a builtin.""" def __init__(self, *namestoblock): self.namestoblock = dict.fromkeys(namestoblock) def find_module(self, fullname, path=None): if fullname in self.namestoblock: return self return None def load_module(self, fullname): raise ImportError, "I dare you" class ImpWrapper: def __init__(self, path=None): if path is not None and not os.path.isdir(path): raise ImportError self.path = path def find_module(self, fullname, path=None): subname = fullname.split(".")[-1] if subname != fullname and self.path is None: return None if self.path is None: path = None else: path = [self.path] try: file, filename, stuff = imp.find_module(subname, path) except ImportError: return None return ImpLoader(file, filename, stuff) class ImpLoader: def __init__(self, file, filename, stuff): self.file = file self.filename = filename self.stuff = stuff def load_module(self, fullname): mod = imp.load_module(fullname, self.file, self.filename, self.stuff) if self.file: self.file.close() mod.__loader__ = self # for introspection return mod class ImportHooksBaseTestCase(unittest.TestCase): def setUp(self): self.path = sys.path[:] self.meta_path = sys.meta_path[:] self.path_hooks = sys.path_hooks[:] sys.path_importer_cache.clear() self.modules_before = sys.modules.copy() def tearDown(self): sys.path[:] = self.path sys.meta_path[:] = self.meta_path sys.path_hooks[:] = self.path_hooks sys.path_importer_cache.clear() sys.modules.clear() sys.modules.update(self.modules_before) class ImportHooksTestCase(ImportHooksBaseTestCase): def doTestImports(self, importer=None): import hooktestmodule import hooktestpackage import hooktestpackage.sub import hooktestpackage.sub.subber self.assertEqual(hooktestmodule.get_name(), "hooktestmodule") self.assertEqual(hooktestpackage.get_name(), "hooktestpackage") self.assertEqual(hooktestpackage.sub.get_name(), "hooktestpackage.sub") self.assertEqual(hooktestpackage.sub.subber.get_name(), "hooktestpackage.sub.subber") if importer: self.assertEqual(hooktestmodule.__loader__, importer) self.assertEqual(hooktestpackage.__loader__, importer) self.assertEqual(hooktestpackage.sub.__loader__, importer) self.assertEqual(hooktestpackage.sub.subber.__loader__, importer) TestImporter.modules['reloadmodule'] = (False, test_co) import reloadmodule self.assertFalse(hasattr(reloadmodule,'reloaded')) TestImporter.modules['reloadmodule'] = (False, reload_co) imp.reload(reloadmodule) self.assertTrue(hasattr(reloadmodule,'reloaded')) import hooktestpackage.oldabs self.assertEqual(hooktestpackage.oldabs.get_name(), "hooktestpackage.oldabs") self.assertEqual(hooktestpackage.oldabs.sub, hooktestpackage.sub) import hooktestpackage.newrel self.assertEqual(hooktestpackage.newrel.get_name(), "hooktestpackage.newrel") self.assertEqual(hooktestpackage.newrel.sub, hooktestpackage.sub) import hooktestpackage.sub.subber.subest as subest self.assertEqual(subest.get_name(), "hooktestpackage.sub.subber.subest") self.assertEqual(subest.sub, hooktestpackage.sub) import hooktestpackage.futrel self.assertEqual(hooktestpackage.futrel.get_name(), "hooktestpackage.futrel") self.assertEqual(hooktestpackage.futrel.sub, hooktestpackage.sub) import sub self.assertEqual(sub.get_name(), "sub") import hooktestpackage.newabs self.assertEqual(hooktestpackage.newabs.get_name(), "hooktestpackage.newabs") self.assertEqual(hooktestpackage.newabs.sub, sub) def testMetaPath(self): i = MetaImporter() sys.meta_path.append(i) self.doTestImports(i) def testPathHook(self): sys.path_hooks.append(PathImporter) sys.path.append(test_path) self.doTestImports() def testBlocker(self): mname = "exceptions" # an arbitrary harmless builtin module test_support.unload(mname) sys.meta_path.append(ImportBlocker(mname)) self.assertRaises(ImportError, __import__, mname) @unittest.skipIf(sys.platform == 'cli', 'No module named parser.') def testImpWrapper(self): i = ImpWrapper() sys.meta_path.append(i) sys.path_hooks.append(ImpWrapper) mnames = ("colorsys", "urlparse", "distutils.core", "compiler.misc") for mname in mnames: parent = mname.split(".")[0] for n in sys.modules.keys(): if n.startswith(parent): del sys.modules[n] with test_support.check_warnings(("The compiler package is deprecated " "and removed", DeprecationWarning)): for mname in mnames: m = __import__(mname, globals(), locals(), ["__dummy__"]) m.__loader__ # to make sure we actually handled the import def test_main(): test_support.run_unittest(ImportHooksTestCase) if __name__ == "__main__": test_main()

[ "pawel.jasinski@gmail.com" ]

pawel.jasinski@gmail.com

04b1094f65b4a4fc7502ed6377fbc11d675ebac1

0d3bcb7078b5985f5ce2dd00583045d24dffebb0

/Exercise-1/RANSAC.py

8ae1470b38978b61d0c5aa87728d6a68c4e6ba6c

[]

no_license

umerjamil16/RoboND-Perception-Exercises

544687dafbd91971cf07fab42d1eeeae76f90422

c71e70cdd15c12804e78461417f6a1772c31a89a

refs/heads/master

2020-05-24T12:38:16.450120

2019-05-17T19:46:09

187,272,489

0

null

UTF-8

Python

false

2,063

py

# Import PCL module import pcl # Load Point Cloud file cloud = pcl.load_XYZRGB('tabletop.pcd') # Voxel Grid filter # Create a VoxelGrid filter object for our input point cloud vox = cloud.make_voxel_grid_filter() # Choose a voxel (also known as leaf) size # Note: this (1) is a poor choice of leaf size # Experiment and find the appropriate size! LEAF_SIZE = 1 # Set the voxel (or leaf) size vox.set_leaf_size(LEAF_SIZE, LEAF_SIZE, LEAF_SIZE) # Call the filter function to obtain the resultant downsampled point cloud cloud_filtered = vox.filter() filename = 'voxel_downsampled.pcd' pcl.save(cloud_filtered, filename) # PassThrough filter # Create a PassThrough filter object. passthrough = cloud_filtered.make_passthrough_filter() # Assign axis and range to the passthrough filter object. filter_axis = 'z' passthrough.set_filter_field_name(filter_axis) axis_min = 0 axis_max = 2 passthrough.set_filter_limits(axis_min, axis_max) # Finally use the filter function to obtain the resultant point cloud. cloud_filtered = passthrough.filter() filename = 'pass_through_filtered.pcd' pcl.save(cloud_filtered, filename) # RANSAC plane segmentation # Create the segmentation object seg = cloud_filtered.make_segmenter() # Set the model you wish to fit seg.set_model_type(pcl.SACMODEL_PLANE) seg.set_method_type(pcl.SAC_RANSAC) # Max distance for a point to be considered fitting the model # Experiment with different values for max_distance # for segmenting the table max_distance = 1 seg.set_distance_threshold(max_distance) # Call the segment function to obtain set of inlier indices and model coefficients inliers, coefficients = seg.segment() # Extract inliers extracted_inliers = cloud_filtered.extract(inliers, negative=False) # Save pcd for table # pcl.save(cloud, filename) filename = 'extracted_inliers.pcd' pcl.save(extracted_inliers, filename) # Extract outliers extracted_outliers = cloud_filtered.extract(inliers, negative=True) # Save pcd for tabletop objects filename = 'extracted_outliers.pcd' pcl.save(extracted_outliers, filename)

[ "umerjamil16@gmail.com" ]

umerjamil16@gmail.com

4d0c4be14b6b09ec3251c2838bcf588741ca742d

803cf1530759df60c247e7e6594bba0dae5ac72e

/notes_graphomaniac/urls.py

ee88eafd13ecb24d5866a5725931b81dc5104e8b

[]

no_license

annalitvin/GraphomaniacNotes

f016873d4ec4acfb9397f4c84005ea92f1c04858

1d699c2b0111e7c1340e9a0a5c530abbf4da6ea0

refs/heads/master

2020-03-19T12:55:47.221439

2018-06-08T02:07:44

136,550,467

1

0

null

UTF-8

Python

false

314

py

from django.urls import path, include from . import views urlpatterns = [ path('', views.index, name='index'), path('add_notes/', views.NoteFormView.as_view(), name='note_input'), path('notes/', views.NotesListView.as_view(), name='notes_list'), path('success/', views.success, name='success') ]

[ "litvin_any@ukr.net" ]

litvin_any@ukr.net

6ad19c82856fa6ac2a65b8bb061e10acfa66d584

91ccebfe1afcec9fe91e33d7951eedb73a115f37

/Sina_spider/Sina_spider/pipelines.py

a30ffdff77f6aed04bb7843c4e9146df6d1629d2

[]

no_license

weinuonuo/python

30a96c692b4e3a4cbaf1603ee3dc3fc7f513498e

77aaa584277a33fe347d7d2ea495352d26aec6f7

refs/heads/master

2021-01-23T05:30:01.673276

2018-01-22T14:46:36

102,471,348

0

null

2017-09-05T11:09:19

null

UTF-8

Python

false

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# -*- coding: utf-8 -*- # Define your item pipelines here # # Don't forget to add your pipeline to the ITEM_PIPELINES setting # See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html import pymongo from . import items import logging class MongoDBPipleline(object): def __init__(self): clinet = pymongo.MongoClient("localhost", 27017) db = clinet["Sina"] self.Information = db["Information"] self.Tweets = db["Tweets"] self.Relationships = db["Relationships"] self.Comments = db["Comments"] self.Reposts = db['Reposts'] def process_item(self, item, spider): """ 判断item的类型，并作相应的处理，再入数据库 """ if isinstance(item, items.InformationItem): try: logging.warning("向数据库存入个人信息...") self.Information.insert(dict(item)) except Exception: logging.warning("数据已存在，存入个人信息失败/(ㄒoㄒ)/~~") pass elif isinstance(item, items.TweetsItem): try: logging.warning("向数据库存入微博信息...") self.Tweets.insert(dict(item)) except Exception: logging.warning("数据已存在，存入微博信息数据失败/(ㄒoㄒ)/~~") pass elif isinstance(item, items.RelationshipsItem): try: logging.warning("向数据库存入关系数据信息...") self.Relationships.insert(dict(item)) except Exception: logging.warning("数据已存在，存入两者关系数据失败/(ㄒoㄒ)/~~") pass elif isinstance(item,items.CommentsItem): try: logging.warning("向数据库存入微博评论信息...") self.Comments.insert(dict(item)) except Exception: logging.warning("数据已存在，存入数据库失败...") pass elif isinstance(item,items.RepostsItem): try: logging.warning("向数据库存入微博转发信息...") self.Reposts.insert(dict(item)) except Exception: logging.warning("数据已存在，存入数据库失败...") pass return item # class MyImagesPipeline(ImagesPipeline): # def file_path(self, request, response=None, info=None): # image_guid = request.url.split('/')[-1] # return 'full/%s' % (image_guid) # def get_media_requests(self, item, info): # if isinstance(item, items.InformationItem): # for image_url in item['img_url']: # yield Request(image_url) # def item_completed(self, results, item, info): # image_paths = [x['path'] for ok, x in results if ok] # if not image_paths: # raise DropItem("Item contains no images") # return item

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weinuonuo.noreply@github.com

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/tensor_practicing/tensor_reshaping.py

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harisyammnv/streamlit-ml-apps

0e2ed85f12ccdc8315f55946a4a1c20586ee372e

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refs/heads/master

2023-02-08T07:04:50.548867

2020-12-20T13:13:07

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2020-12-20T13:13:08

2020-10-11T17:09:09

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import torch x = torch.arange(9) x_re = x.view(3, 3) # for contiguous tensors x_re = x.reshape(3, 3) # use this to be safe print(x_re) y = x_re.t() print(y) x1 = torch.rand((2, 5)) x2 = torch.rand((2, 5)) print(torch.cat((x1, x2), dim=0).shape) print(torch.cat((x1, x2), dim=1).shape) z = x_re.view(-1) # flatten print(z) batch = 64 x = torch.rand((batch, 2, 5)) z = x.view(batch, -1) print(z.shape) z = x.permute(0, 2, 1) # transpose for multiple dimensions print(z.shape) x = torch.arange(10) print(x.unsqueeze(0).shape) print(x.unsqueeze(1).shape) print(x.unsqueeze(0).unsqueeze(1).shape)

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harisyam.bphc@gmail.com

b931c19a220aa8fe84a292b316cf0cb51fbce4ee

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/is_bst.py

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[]

no_license

alaouiib/DS_and_Algorithms_Training

a248d429c7ff02b6bad268e7132b31e67656441c

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refs/heads/main

2023-03-30T19:40:39.339035

2021-03-31T20:05:37

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import unittest # complexity O(n) Time and Space def is_binary_search_tree(root): # Determine if the tree is a valid binary search tree # idea (inspired by interviewcake): ## We do a depth-first walk through the tree, ## testing each node for validity as we go. ## If a node appears in the left subtree of an ancestor, ## it must be less than that ancestor. ## If a node appears in the right subtree of an ancestor, ## it must be greater than that ancestor. node_and_bounds_stack = [(root,-float('inf'),float('inf'))] while len(node_and_bounds_stack): node, lower_bound, upper_bound = node_and_bounds_stack.pop() # 2 cases, node or leaf. # If this node is invalid, we return false right away if node.value <= lower_bound or node.value >= upper_bound: return False if node.left: # This node must be less than the current node node_and_bounds_stack.append([node.left,lower_bound,node.value]) # This node must be greater than the current node if node.right: node_and_bounds_stack.append([node.right,node.value,upper_bound]) return True # Tests (by interview cake) class Test(unittest.TestCase): class BinaryTreeNode(object): def __init__(self, value): self.value = value self.left = None self.right = None def insert_left(self, value): self.left = Test.BinaryTreeNode(value) return self.left def insert_right(self, value): self.right = Test.BinaryTreeNode(value) return self.right def test_valid_full_tree(self): tree = Test.BinaryTreeNode(50) left = tree.insert_left(30) right = tree.insert_right(70) left.insert_left(10) left.insert_right(40) right.insert_left(60) right.insert_right(80) result = is_binary_search_tree(tree) self.assertTrue(result) def test_both_subtrees_valid(self): tree = Test.BinaryTreeNode(50) left = tree.insert_left(30) right = tree.insert_right(80) left.insert_left(20) left.insert_right(60) right.insert_left(70) right.insert_right(90) result = is_binary_search_tree(tree) self.assertFalse(result) def test_descending_linked_list(self): tree = Test.BinaryTreeNode(50) left = tree.insert_left(40) left_left = left.insert_left(30) left_left_left = left_left.insert_left(20) left_left_left.insert_left(10) result = is_binary_search_tree(tree) self.assertTrue(result) def test_out_of_order_linked_list(self): tree = Test.BinaryTreeNode(50) right = tree.insert_right(70) right_right = right.insert_right(60) right_right.insert_right(80) result = is_binary_search_tree(tree) self.assertFalse(result) def test_one_node_tree(self): tree = Test.BinaryTreeNode(50) result = is_binary_search_tree(tree) self.assertTrue(result) unittest.main(verbosity=2)

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/create_root_csv_pp_WH.py

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no_license

FFFreitas/Root-Numpy-Pandas

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2020-03-27T06:56:56.412727

2018-08-26T04:53:08

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#!/usr/bin/python import sys import ROOT import numpy as np from ROOT import TLorentzVector import csv import pandas as pd from ROOT import TFile, TTree from rootpy.io import root_open from rootpy.tree import Tree, TreeChain from rootpy.plotting import Hist from rootpy.plotting import Hist2D from rootpy.extern.six.moves import range from root_numpy import hist2array, root2array from itertools import combinations, permutations if len(sys.argv) < 2: print " Usage: Example1.py input_file" sys.exit(1) ROOT.gSystem.Load("/home/felipe/madanalysis5_1_5/tools/delphes/libDelphes") inputFile = sys.argv[1] # Create chain of root trees chain1 = ROOT.TChain("Delphes") chain1.Add(inputFile) # Create object of class ExRootTreeReader treeReader = ROOT.ExRootTreeReader(chain1) numberOfEntries = treeReader.GetEntries() # create new root file root_name = raw_input("name of new root: ") csv_name = raw_input("name of new csv: ") f = root_open(root_name, "recreate") tree = Tree("test") tree.create_branches({'PT_l': 'F', 'MT_VH': 'F', 'PT_VH': 'F', 'PT_W': 'F', 'Cos_lw': 'F', 'DPHI_lmet': 'F', 'met': 'F', 'PT_b1': 'F', 'PT_b2': 'F', 'PT_lj1': 'F', 'PT_lj2': 'F', 'Eta_H': 'F', 'Phi_H': 'F', 'M_H': 'F', 'MT_W': 'F', 'Cos_Hb1': 'F', 'PT_H': 'F', }) # Get pointers to branches used in this analysis branchJet = treeReader.UseBranch("Jet") branchElectron = treeReader.UseBranch("Electron") branchMuon = treeReader.UseBranch("Muon") branchPhoton = treeReader.UseBranch("Photon") branchMET = treeReader.UseBranch("MissingET") #################################################################### # Loop over all events for entry in range(0, numberOfEntries): # Load selected branches with data from specified event treeReader.ReadEntry(entry) ########################################################################################################## eletrons = sorted(branchElectron, key=lambda Electron: Electron.PT, reverse=True) missing = sorted(branchMET, key=lambda MisingET: MisingET.MET, reverse=True) elec1 = eletrons[0] eletron1 = ROOT.TLorentzVector() eletron1.SetPtEtaPhiE(elec1.PT,elec1.Eta,elec1.Phi,elec1.P4().E()) met = ROOT.TLorentzVector() met.SetPtEtaPhiE(missing[0].P4().Pt(),missing[0].P4().Eta(),missing[0].P4().Phi(),missing[0].P4().E()) bjato1 = ROOT.TLorentzVector() bjato2 = ROOT.TLorentzVector() jato1 = ROOT.TLorentzVector() jato2 = ROOT.TLorentzVector() #################################################################################### bjets, ljets = [], [] for n in xrange(branchJet.GetEntries()): if branchJet.At(n).BTag == 1: bjets.append(branchJet.At(n)) else: ljets.append(branchJet.At(n)) if len(bjets) >= 2: bjets = sorted(bjets, key=lambda BJet: BJet.P4().Pt(), reverse=True) else: continue if len(ljets) >= 2: ljets = sorted(ljets, key=lambda Jet: Jet.P4().Pt(), reverse=True) else: continue #################################################################################### jato1.SetPtEtaPhiE(ljets[0].P4().Pt(),ljets[0].P4().Eta(),ljets[0].P4().Phi(),ljets[0].P4().E()) jato2.SetPtEtaPhiE(ljets[1].P4().Pt(),ljets[1].P4().Eta(),ljets[1].P4().Phi(),ljets[1].P4().E()) #################################################################################### bjato1.SetPtEtaPhiE(bjets[0].P4().Pt(),bjets[0].P4().Eta(),bjets[0].P4().Phi(),bjets[0].P4().E()) bjato2.SetPtEtaPhiE(bjets[1].P4().Pt(),bjets[1].P4().Eta(),bjets[1].P4().Phi(),bjets[1].P4().E()) #################################################################################### if 115 < (bjato1 + bjato2).M() < 135: tree.PT_l = (eletron1).Pt() tree.met = np.abs(met.Mt()) tree.PT_b1 = (bjato1).Pt() tree.PT_b2 = (bjato2).Pt() tree.PT_lj1 = jato1.Pt() tree.PT_lj2 = jato2.Pt() tree.PT_H = (bjato1 + bjato2).Pt() tree.Eta_H = (bjato1 + bjato2).Eta() W = ROOT.TLorentzVector() W = (eletron1 + met) tree.DPHI_lmet = np.abs(eletron1.DeltaPhi(met)) tree.MT_W = np.sqrt(2*np.abs(met.Et())*np.abs(eletron1.Pt())*(1-np.cos(eletron1.DeltaPhi(met)))) tree.PT_W = W.Pt() H = ROOT.TLorentzVector() H = (bjato1 + bjato2) tree.MT_VH = (W + H).Mt() #H.Mt() + np.sqrt(2*np.abs(met.Et())*np.abs(eletron1.Pt())*(1-np.cos(eletron1.DeltaPhi(met)))) tree.PT_VH = ((bjato1 + bjato2) + (eletron1 + met)).Pt() tree.Phi_H = H.Phi() tree.M_H = H.M() #########################boosted objects######################################################### Wtob = ROOT.TLorentzVector() Wtob.SetPxPyPzE(W.Px(),W.Py(),W.Pz(),W.E()) Wboost = ROOT.TVector3() Wboost = Wtob.BoostVector() v = Wboost.Unit() Htob = ROOT.TLorentzVector() Htob.SetPxPyPzE(H.Px(),H.Py(),H.Pz(),H.E()) Hboost = ROOT.TVector3() Hboost = Htob.BoostVector() ang = Hboost.Unit() bjato1.Boost(-Hboost) tree.Cos_Hb1 = np.cos(bjato1.Angle(ang)) eletron1.Boost(-Wboost) tree.Cos_lw = np.cos(eletron1.Angle(v)) tree.Fill() ############################################### tree.write() f.close() #create the csv output to_convert = root2array(root_name,'test') df_conv = pd.DataFrame(to_convert) df_conv.to_csv( csv_name + '.csv', index=False, header= df_conv.keys(), mode='w', sep=' ')

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permissive

zgreat/transient

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refs/heads/master

2021-05-30T10:49:40.529829

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from os import environ from flask import Flask, jsonify, request, send_file from transient.lib.database import session app = Flask(__name__) def run(): host = environ.get("HOST", "127.0.0.1") port = int(environ.get("PORT", 3000)) debug = environ.get("DEBUG", False) app.run(host=host, port=port, debug=debug) @app.route("/") def get_root(): return "Sup?" @app.route("/ping") def get_ping(): return "pong" @app.route("/payments", methods=['POST']) def post_payment(): from transient.services.payments import create_payment try: payment = create_payment(**request.json) session.add(payment) session.commit() except: session.rollback() return jsonify({ 'success': False }) else: return jsonify({ 'success': True, 'payment': payment.to_dict() }) finally: session.remove() @app.route("/transactions", methods=['POST']) def post_transaction(): from transient.services.transactions import create_transaction try: transaction = create_transaction(**request.json) session.add(transaction) session.commit() except Exception, e: session.rollback() return jsonify({ 'success': False }) else: return jsonify({ 'success': True, 'transaction': transaction.to_dict() }) finally: session.remove() @app.route("/payments/<payment_id>/qrcode.png", methods=['GET']) def get_qrcode(payment_id): from transient.services.payments import get_payment_qrcode image = get_payment_qrcode(payment_id) return serve_pil_image(image, "png") @app.teardown_appcontext def shutdown_session(exception=None): session.remove() def serve_pil_image(pil_img, img_format="jpeg"): from StringIO import StringIO img_io = StringIO() pil_img.save(img_io, img_format.upper()) img_io.seek(0) return send_file(img_io, mimetype='image/%s' % (img_format.lower()))

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/main.py

3f2f0e3391b498dd6648bf65c69d964360f63fa8

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YaSlavar/numerical_method

cb7fb1bd8720daf0581e13bf752bcf4f1bb133a6

d98577af099430bed9163aae338947b00f446b5d

refs/heads/master

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from math import * class Integral: def __init__(self, a, b, eps, step, func): """ Вычисление определенных интегралов численными методами :param a: левый предел интегрирования (float) :param b: правый предел интегрирования (float) :param eps: погрешность вычисления (float) :param step: шаг сканирования (float) :param func: вычисляемая функция (str) """ self.func = func self.a = a self.b = b self.eps = eps self.step = step eps_str = '{:f}'.format(self.eps) eps_str = eps_str.rstrip("0") self.after_dicimal = len(eps_str.split(".")[1]) def function(self, x): exec("x={}\nres={}".format(x, self.func)) return locals()['res'] def Metod_Levych_Pryamougolnikov(self, a, b, step): h = (b - a) / step x = a summ = 0 detision = "integral = {}*(".format(step) for i in range(int(h)): f_x = round(self.function(x), self.after_dicimal) summ += f_x print("x={} f(x)={}".format(x, f_x)) if i+1 == h: detision += "{})".format(f_x) else: detision += "{} + ".format(f_x) x += step summ = summ * step print("{} = {}".format(detision, round(summ, self.after_dicimal))) def Metod_Srednich_Pryamougolnikov(self, a, b, step): h = (b - a) / step x = a + (step / 2) summ = 0 detision = "integral = {}*(".format(step) for i in range(int(h)): f_x = round(self.function(x), self.after_dicimal) summ += f_x print("x={} f(x)={}".format(x, f_x)) if i + 1 == h: detision += "{})".format(f_x) else: detision += "{} + ".format(f_x) x += step summ = summ * step print("{} = {}".format(detision, round(summ, self.after_dicimal))) def Metod_Pravych_Pryamougolnikov(self, a, b, step): h = (b - a) / step x = a + step summ = 0 detision = "integral = {}*(".format(step) for i in range(int(h)): f_x = round(self.function(x), self.after_dicimal) summ += f_x print("x={} f(x)={}".format(x, f_x)) if i + 1 == h: detision += "{})".format(f_x) else: detision += "{} + ".format(f_x) x += step summ = summ * step print("{} = {}".format(detision, round(summ, self.after_dicimal))) def Metod_Trapeciy(self, a, b, step): h = (b - a) / step x = a summ = 0 detision = "integral = {}*(f0_fn__2 + (".format(step) for i in range(1, int(h)+1): x += step f_x = round(self.function(x), self.after_dicimal) print("x={} f(x)={}".format(x, f_x)) if i < h - 1: summ += f_x detision += "{} + ".format(f_x) elif i < h: summ += f_x detision += "{})".format(f_x) elif i == h: break f0_fn__2 = (round(self.function(a), self.after_dicimal) + round(self.function(x), self.after_dicimal)) / 2 detision = detision.replace("f0_fn__2", "({} + {}) / 2".format(round(self.function(a), self.after_dicimal), round(self.function(x), self.after_dicimal))) summ += f0_fn__2 summ = summ * step print("{} = {}".format(detision, round(summ, self.after_dicimal))) def Metod_Parabol(self, a, b, step): h = (b - a) / step step_6 = step / 6 x = a summ = 0 detision = "integral = {}/6 * (".format(h) f_0 = round(self.function(x), self.after_dicimal) summ += f_0 detision += "{} + ".format(f_0) print("x={} f(x)={}".format(x, f_0)) for i in range(1, int(h) * 2): x += step / 2 f_x = round(self.function(x), self.after_dicimal) if i % 2 is not 0: summ += f_x * 4 detision += "4*({}) + ".format(f_x) else: summ += f_x * 2 detision += "2*({}) + ".format(f_x) print("x={} f(x)={}".format(x, f_x)) x += step / 2 f_n = round(self.function(x), self.after_dicimal) summ += f_n summ = summ * step_6 detision += "{})".format(f_n) print("x={} f(x)={}".format(x, f_n)) print("{} = {}".format(detision, round(summ, self.after_dicimal))) def run(self): print('ВЫЧИСЛЕНИЕ ОПРЕДЕЛЕННЫХ ИНТЕГРАЛОВ\n\n') print('\nМетод левых прямоугольников\n') self.Metod_Levych_Pryamougolnikov(self.a, self.b, self.step) print('\nМетод средних прямоугольников\n') self.Metod_Srednich_Pryamougolnikov(self.a, self.b, self.step) print('\nМетод правых прямоугольников\n') self.Metod_Pravych_Pryamougolnikov(self.a, self.b, self.step) print('\nМетод трапеций\n') self.Metod_Trapeciy(self.a, self.b, self.step) print('\nМетод парабол\n') self.Metod_Parabol(self.a, self.b, self.step) class Polynome: def __init__(self, _fns, _fns1, _fns2, _a_b, _eps): """ Решение нелинейных уравнений :param _fns: исходная функция (str) :param _fns1: первая производная функции (str) :param _fns2: вотрая производная функции (str) :param _a_b: отрезок на котором предположительно есть корни (tuple) :param _eps: погрешность (float) """ self.fns = _fns self.fns_1 = _fns1 self.fns_2 = _fns2 self.a = _a_b[0] self.b = _a_b[1] self.eps = _eps @staticmethod def func(funcs, x): exec("x={}\nres={}".format(x, funcs)) return locals()['res'] def run(self): after_dicimal = 5 ab = [self.a, self.b] if self.func(self.fns, ab[0]) * self.func(self.fns, ab[1]) < 0: # Метод половинного деления print("Метод половинного деления") print("Дано: \n[{},{}]\n f(a) = {}, f(b) = {}\n" .format(ab[0], ab[1], self.func(self.fns, ab[0]), self.func(self.fns, ab[1]))) i = 1 while True: c = round(((ab[0] + ab[1]) / 2), after_dicimal) print("Итерация {} \nc({}) = ({}+({}))/2 = {}\nf(c{}) = {}\n\n[{},{}][{},{}]" .format(i, i, ab[0], ab[1], c, i, round(self.func(self.fns, c), after_dicimal), ab[0], c, c, ab[1])) if self.func(self.fns, ab[0]) * self.func(self.fns, c) < 0: ab[1] = round(c, after_dicimal) elif self.func(self.fns, ab[1]) * self.func(self.fns, c) < 0: ab[0] = round(c, after_dicimal) i += 1 if fabs(ab[0] - ab[1]) < 2 * self.eps: c = (ab[0] + ab[1]) / 2 f_c = self.func(self.fns, c) print("Значение функции: {} в точке: {}\n\n".format(round(f_c, after_dicimal), round(c, after_dicimal))) break # Метод хорд и касательных ab = [self.a, self.b] print("Метод хорд и касательных") f_a = self.func(self.fns, ab[0]) f_b = self.func(self.fns, ab[1]) f_2_a = self.func(self.fns_2, ab[0]) f_2_b = self.func(self.fns_2, ab[1]) print("Дано: \n[{},{}]\nf(a) = {}, f(b) = {}\nf''(a) = {}, f''(b) = {}\n" .format(ab[0], ab[1], self.func(self.fns, ab[0]), self.func(self.fns, ab[1]), self.func(self.fns_2, ab[0]), self.func(self.fns_2, ab[1]))) if abs(f_a - f_2_a) < abs(f_b - f_2_b): print("Для касательных используем [a.. , т.к. F''(a) ,ближе к краям отрезка") kas = self.a hord = self.b else: print("Для касательных используем ..b] , т.к. F''(b) ,ближе к краям отрезка") kas = self.b hord = self.a while True: hord_out = "hord = {} - (({} - ({}))*F({})) / (F({}) - F({}))\n"\ .format(round(hord, after_dicimal), round(kas, after_dicimal), round(hord, after_dicimal), round(hord, after_dicimal), round(kas, after_dicimal), round(hord, after_dicimal)) hord_out += " = {} - (({} - ({}))*{}) / ({} - {})"\ .format(round(hord, after_dicimal), round(kas, after_dicimal), round(hord, after_dicimal), round(self.func(self.fns, hord), after_dicimal), round(self.func(self.fns, kas), after_dicimal), round(self.func(self.fns, hord), after_dicimal)) print(hord_out) hord = round(hord - ((kas - hord)*self.func(self.fns, hord)) / (self.func(self.fns, kas) - self.func(self.fns, hord)), after_dicimal) print(" = {}".format(hord)) kas_out = "kasat = {} - (F({}) / F'({}))\n"\ .format(round(kas, after_dicimal), round(kas, after_dicimal), round(kas, after_dicimal)) kas_out += " = {} - ({} / {})" \ .format(round(kas, after_dicimal), round(self.func(self.fns, kas)), round(self.func(self.fns_1, kas), after_dicimal)) print(kas_out) kas = round(kas - (self.func(self.fns, kas) / self.func(self.fns_1, kas)), after_dicimal) print(" = {}".format(kas)) print("[{},{}]".format(hord, kas)) if fabs(hord - kas) < 2 * self.eps: answer = (hord + kas) / 2 print("Ответ: ", answer) break else: print("На данном отрезке корня нет") if __name__ == "__main__": fns_type = input("integral or polynome: ") if fns_type in ["i", "integral", "интеграл"]: fns = input("Введите функцию: ") a_b = tuple(map(float, input("Введите предел интегрирования [a b] через пробел: ").split())) eps = float(input("Введите погрешность: ")) step = float(input("Введите шаг: ")) # fns = "(x*x)/pow((1+x), 3)" # a_b = [0, 2.5] # eps = 0.00001 # step = 0.5 integ = Integral(a_b[0], a_b[1], eps, step, fns) integ.run() else: fns = input("Введите функцию: ") fns1 = input("Введите первую производную функции: ") fns2 = input("Введите вторую производную функции: ") a_b = tuple(map(int, input("Введите отрензок [a b] на котором есть корень: ").split())) eps = float(input("Введите погрешность: ")) # fns = "x*x*x-15*x+6" # fns1 = "3*x*x-15" # fns2 = "6*x" # a_b = [1, 0] # eps = 0.001 pol = Polynome(fns, fns1, fns2, a_b, eps) pol.run()

[ "50412722+YaSlavar@users.noreply.github.com" ]

50412722+YaSlavar@users.noreply.github.com

1407bc24e92e4f55c6f3995b2048cd89cb29cd65

82304008e8359460c7e3dd634addc6657c32e529

/[HW 3] python-challenge/PyBank/main.py

6f1e05b85257cd349a84734104a96907f9bb7947

[]

no_license

jamesnguyen0/datasciwork

013819ca6ac83fe9b8e3ce7783c58a175fbecb4a

a520910e4b5124e73a5c4ed4cc88e0f6b6ee1cd7

refs/heads/master

2022-11-30T01:13:39.609617

2020-08-05T01:57:25

271,149,751

0

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UTF-8

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2,282

py

#libraries import os import csv #variables months = 0 netChange = 0 avgChange = 0 maxIncrease = ["", 0] maxDecrease = ["", 0] #change calculations current = 0 previous = 0 changeInChange = 0 #read files pybank_csv = os.path.join("Resources","budget_data.csv") with open(pybank_csv) as csvfile: csvreader = csv.reader(csvfile, delimiter = ",") #skip header header = next(csvreader) #loop through each row for row in csvreader: #basic calculations months += 1 netChange += int(row[1]) current = int(row[1]) #don't execute if current is first value in list if not(previous == 0): changeInChange = current - previous #sum the change in changes avgChange += changeInChange if changeInChange > int(maxIncrease[1]): maxIncrease[0] = row[0] maxIncrease[1] = changeInChange if changeInChange < int(maxDecrease[1]): maxDecrease[0] = row[0] maxDecrease[1] = changeInChange previous = int(row[1]) #calculate true average avgChange = round(avgChange/(months - 1), 2) #output to console print("Financial Analysis") print("----------------------------") print(f"Total Months: {months}") print(f"Total: ${netChange}") print(f"Average Change: ${avgChange}") print(f"Greatest Increase in Profits: {maxIncrease[0]} (${maxIncrease[1]})") print(f"Greatest Decrease in Profits: {maxDecrease[0]} (${maxDecrease[1]})") #prep text for output to .txt text = [] text.append("Financial Analysis") text.append("----------------------------") text.append("Total Months: " + str(months)) text.append("Total: $" + str(netChange)) text.append("Average Change: $" + str(avgChange)) text.append("Greatest Increase in Profits: " + maxIncrease[0] + " $(" + str(maxIncrease[1]) + ")") text.append("Greatest Decrease in Profits: " + maxDecrease[0] + " $(" + str(maxDecrease[1]) + ")") outputtext = zip(text) #write files output_file = os.path.join("Analysis","PyBank_analysis.txt") with open(output_file, 'w') as datafile: writer = csv.writer(datafile, lineterminator='\n') writer.writerows(outputtext)

[ "jamesnguyen0@gmail.com" ]

jamesnguyen0@gmail.com

7c9a95200bd62582f4e0c5a22ee69a05a45879cd

66dace688df266de641c6e1bc7e48fdf0e403382

/mysite/settings.py

72c3e2775f6332d1152aed8f3d071ff2fb8e5d97

[]

no_license

dendenthen/mysite

27291d6766c197a00fe70cb871e61267a78a46a3

213f26e99839247d7e3d93c22f77c8e555e063d0

refs/heads/master

2021-04-28T16:31:42.727331

2018-02-22T01:40:29

122,016,409

0

null

UTF-8

Python

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3,118

py

""" Django settings for mysite project. Generated by 'django-admin startproject' using Django 2.0.2. For more information on this file, see https://docs.djangoproject.com/en/2.0/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.0/ref/settings/ """ import os # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.0/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = '_d4rr%1+@v&&+f*0q97s)#ke13n$_w#phjpj4r9lrlt!rnis9!' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = [] # Application definition INSTALLED_APPS = [ 'polls.apps.PollsConfig', 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', ] MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'mysite.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'mysite.wsgi.application' # Database # https://docs.djangoproject.com/en/2.0/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Password validation # https://docs.djangoproject.com/en/2.0/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/2.0/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/2.0/howto/static-files/ STATIC_URL = '/static/'

[ "dennis.alan.herbert@gmail.com" ]

dennis.alan.herbert@gmail.com

bb3c3a2fa1d72003f265ef1a73b9a36e5ea55b08

6b5e514aa031e19ad1574b3415ee091f71549ed7

/lale/lib/autogen/one_hot_encoder.py

b4c0c2df965bbd39464bb7bd7e9c6df55be5d876

[ "LicenseRef-scancode-unknown-license-reference", "Apache-2.0" ]

permissive

noushi/lale

e3db3e3b7e4a4e4b5eda13303c50245612eec370

5ba5612737beee5fb2a387eb5f6f9bdec7ffb878

refs/heads/master

2020-12-04T06:48:13.365418

2019-12-29T11:42:42

null

0

null

UTF-8

Python

false

4,463

py

from sklearn.preprocessing._encoders import OneHotEncoder as SKLModel import lale.helpers import lale.operators from numpy import nan, inf class OneHotEncoderImpl(): def __init__(self, categories=None, sparse=True, dtype=None, handle_unknown='error', n_values=None, categorical_features=None): self._hyperparams = { 'categories': categories, 'sparse': sparse, 'dtype': dtype, 'handle_unknown': handle_unknown, 'n_values': n_values, 'categorical_features': categorical_features} def fit(self, X, y=None): self._sklearn_model = SKLModel(**self._hyperparams) if (y is not None): self._sklearn_model.fit(X, y) else: self._sklearn_model.fit(X) return self def transform(self, X): return self._sklearn_model.transform(X) _hyperparams_schema = { '$schema': 'http://json-schema.org/draft-04/schema#', 'description': 'inherited docstring for OneHotEncoder Encode categorical integer features as a one-hot numeric array.', 'allOf': [{ 'type': 'object', 'required': ['categories', 'sparse', 'dtype', 'handle_unknown', 'n_values', 'categorical_features'], 'relevantToOptimizer': ['sparse'], 'additionalProperties': False, 'properties': { 'categories': { 'XXX TODO XXX': "'auto' or a list of lists/arrays of values, default='auto'.", 'description': 'Categories (unique values) per feature:', 'enum': [None], 'default': None}, 'sparse': { 'type': 'boolean', 'default': True, 'description': 'Will return sparse matrix if set True else will return an array.'}, 'dtype': { 'XXX TODO XXX': 'number type, default=np.float', 'description': 'Desired dtype of output.'}, 'handle_unknown': { 'XXX TODO XXX': "'error' or 'ignore', default='error'.", 'description': 'Whether to raise an error or ignore if an unknown categorical feature', 'enum': ['error'], 'default': 'error'}, 'n_values': { 'XXX TODO XXX': "'auto', int or array of ints, default='auto'", 'description': 'Number of values per feature.', 'enum': [None], 'default': None}, 'categorical_features': { 'XXX TODO XXX': "'all' or array of indices or mask, default='all'", 'description': 'Specify what features are treated as categorical.', 'enum': [None], 'default': None}, }}], } _input_fit_schema = { '$schema': 'http://json-schema.org/draft-04/schema#', 'description': 'Fit OneHotEncoder to X.', 'type': 'object', 'properties': { 'X': { 'type': 'array', 'items': { 'type': 'array', 'items': { 'type': 'number'}, }, 'description': 'The data to determine the categories of each feature.'}, }, } _input_transform_schema = { '$schema': 'http://json-schema.org/draft-04/schema#', 'description': 'Transform X using one-hot encoding.', 'type': 'object', 'properties': { 'X': { 'type': 'array', 'items': { 'type': 'array', 'items': { 'type': 'number'}, }, 'description': 'The data to encode.'}, }, } _output_transform_schema = { '$schema': 'http://json-schema.org/draft-04/schema#', 'description': 'Transformed input.', 'XXX TODO XXX': 'sparse matrix if sparse=True else a 2-d array', } _combined_schemas = { '$schema': 'http://json-schema.org/draft-04/schema#', 'description': 'Combined schema for expected data and hyperparameters.', 'type': 'object', 'tags': { 'pre': [], 'op': ['transformer'], 'post': []}, 'properties': { 'hyperparams': _hyperparams_schema, 'input_fit': _input_fit_schema, 'input_transform': _input_transform_schema, 'output_transform': _output_transform_schema}, } if (__name__ == '__main__'): lale.helpers.validate_is_schema(_combined_schemas) OneHotEncoder = lale.operators.make_operator(OneHotEncoderImpl, _combined_schemas)

[ "shinnar@us.ibm.com" ]

shinnar@us.ibm.com

dbc12ce824ed5e10927e596c234bf9f282022d55

b14176e6931c9cb3e9606147e82cf888efa1e09e

/Strings/Verkefni2-move-first3-to-last.py

cdc9113152ea31d91dab825c1f17628c402149af

[]

no_license

antonbui/Forritun2018

735d7659d99804352564f9a2c6fd015e3a7b1b94

792fc22dfaef9501644964d1cb14f5afc722b6cb

refs/heads/master

2020-03-28T23:53:43.476691

2018-09-21T17:43:26

149,314,255

0

null

UTF-8

Python

false

125

py

s = input("Input a string: ") # your code here firstthree = s[0:3] news = s.replace(firstthree, "") print(news + firstthree)

[ "anton17@ru.is" ]

anton17@ru.is

1cd578338746f8fe8cfdfa8f7ea6d3b386d104cb

d8b131edbfb69c09e4a208f70a9e47e30db8fcde

/two_sum.py

0c905272cc35c02901ae7a9eda929eb57440c778

[]

no_license

prade02/leetcode

06bf499ca02704d288e47870cf07378678187d5c

c20c44e76e08d7b257af780caf9147544a821152

refs/heads/main

2023-04-14T00:51:18.517231

2021-04-22T06:23:18

331,373,605

0

null

UTF-8

Python

false

551

py

""" Approach 1: a + b = c, a - c = b, c is target, a and b is from the list, so for every a in the list search if b exists, if so a and b forms c(target) iterate through the list, get a, in the inner iteration, start from i+1 - since sum of elements can not be same. so search for elements after i. """ def twoSum(nums, target): _len = len(nums) for i in range(_len): search_for = target - nums[i] for j in range(i+1, _len): if nums[j] == search_for: return [i, j] x = [3,3] print(twoSum(x, 6))

[ "prade.ycsm@gmail.com" ]

prade.ycsm@gmail.com

c8fc332424dfa6d376d0b6e7e732f5aa75d4f1d7

016bf8064e3c5e39c1130ad05ad0f3df6fb8c41c

/Seção 13 - Leitura e Escrita em Arquivos/18/main.py

812a06e542a4b8c4e75aab7abbf75d961e4f9fcd

[]

no_license

JGilba/Python_Exercices

0f0f82ec00150e492010086d54b78f92bf591993

940b464f5cdc67455cecefbc9b222c362f6e97f2

refs/heads/master

2022-03-26T09:17:06.201848

2020-01-14T16:33:44

null

0

null

UTF-8

Python

false

192

py

with open('compras.txt') as arq: preco = 0 for produto in arq.readlines(): preco += float(produto[produto.find(';')+1::]) print(f'O preço total a se pagar é R$ {preco:.2f}')

[ "pierrevieiraggg@gmail.com" ]

pierrevieiraggg@gmail.com

87f170cd5ad6e328d576ba48bab8098cc0888823

2f829f30be536594b70b602a9aa25feea20bd13d

/card.py

e11ae6cbf93513e1be9d4769d45b89c21e8f2eb9

[]

no_license

Adi0687/App10_PythonOOP

6fd9df205d8304734c42741f535f28805cee7aa3

ca42f56d504dd80eb7516c67f08ab4c1953a8de0

refs/heads/master

2023-08-27T00:45:26.905682

2021-10-29T16:08:43

null

0

null

UTF-8

Python

false

2,128

py

import sqlite3 from seat import Seat class Card: database = "banking.db" def __init__(self, type, number, cvc, holder, price): self.price = price self.type = type self.number = number self.cvc = cvc self.holder = holder def validate(self): connection = sqlite3.connect(self.database) cursor = connection.cursor() cursor.execute(""" SELECT type,number,cvc,holder FROM Card WHERE "type"=? """, [self.type]) card_details = cursor.fetchall() connection.close() cardtype = card_details[0][0] cardnumber = card_details[0][1] cardcvc = card_details[0][2] cardholder = card_details[0][3] if self.number == cardnumber and self.cvc == cardcvc and self.holder == cardholder: return True else: return False def _balance(self): connection = sqlite3.connect(self.database) cursor = connection.cursor() cursor.execute(""" SELECT balance FROM Card WHERE "type"=? """, [self.type]) balance = cursor.fetchall() connection.close() return float(balance[0][0]) def balance_available(self): balance_parsed = self._balance() if balance_parsed - self.price > 0: return True else: return False def charge_card(self): charge_amount = self._balance() - self.price connection = sqlite3.connect(self.database) connection.execute(""" UPDATE "Card" SET "balance" = ? WHERE "type" = ? """, [charge_amount, self.type]) connection.commit() connection.close() if __name__ == "__main__": card = Card(type="visa".capitalize(), number=1234567, cvc=133, holder="John Smith", price=5000.0) if card.validate(): if card.balance_available(): card.charge_card() else: print("Not enough money!") else: print("One of card details entered are invalid")

[ "ferozeaadil@gmail.com" ]

ferozeaadil@gmail.com

6e6b9abbb3a7ac78b74896eae31114c069d3684a

9cae0e2129f0f3bef362ee187fa713a475f9ce87

/Heuristica + CPLEX/Euristica Problema 1/data.py

7284b190b008a170d722070ea2855b535dc2baa6

[]

no_license

dvarasm/Optimizacion-Rutas

b281c3e7236f177b77cd2753f2c930e13b916fa4

7fbc77e8f0a8ad43fc995efccfefab35cc16e2d4

refs/heads/master

2020-03-28T07:14:39.100115

2018-12-11T14:05:31

147,889,509

0

null

UTF-8

Python

false

5,504

py

# -*- coding: utf-8 -*- from __future__ import unicode_literals costos=[#matriz que contiene las distancias entre ciudades 33x33 [0,141,305,266,719,598,1074,1240,1842,1577,1995,2004,2022,2090,2190,2150,2397,2339,2437,2487,2502,2532,2564,2712,2601,2882,2935,3233,2962,3698,4268,5056,5052], [141,0,441,397,850,740,1205,1372,1973,1708,2127,2136,2153,2222,2321,2281,2528,2471,2569,2618,2634,2664,2697,2843,2733,3013,3066,3364,3094,3829,4399,5187,5184], [305,441,0,55,316,388,795,961,1563,1298,1716,1725,1743,1811,1911,1871,2118,2060,2158,2208,2224,2254,2287,2433,2322,2603,2653,2954,2683,3419,3989,4777,4773], [266,397,55,0,451,331,806,973,1574,1309,1728,1737,1754,1823,1922,1882,2129,2072,2170,2219,2235,2265,2298,2444,2334,2614,2667,2965,2695,3430,4000,4788,4785], [719,850,316,451,0,217,373,539,1140,876,1294,1103,1320,1389,1489,1448,1695,1638,1736,1785,1801,1831,1864,2011,1900,2181,2233,2532,2261,2996,3566,4355,4351], [598,740,388,331,217,0,572,538,1340,1075,1494,1503,1520,1588,1688,1648,1895,1838,1936,1985,2001,2031,2064,2210,2100,2380,2433,2731,2460,3196,3766,4321,4318], [1074,1205,795,806,373,572,0,166,768,403,921,930,948,1016,1116,1076,1323,1265,1364,1413,1429,1459,1492,1638,1527,1808,1861,2159,1888,2624,3194,3982,3978], [1240,1372,961,973,539,538,166,0,612,348,766,575,792,861,961,920,1167,1110,1208,1257,1273,1103,1336,1482,1372,1652,1705,2003,1733,2468,3038,3826,3823], [1842,1973,1563,1574,1140,1340,768,612,0,266,241,250,268,336,436,396,643,585,684,733,749,779,812,958,847,1128,1181,1479,1208,1944,2514,3302,3298], [1577,1708,1298,1309,876,1075,403,348,266,0,420,429,446,515,615,574,821,764,862,911,927,957,990,1137,1026,1306,1359,1658,1387,2122,2692,3480,3477], [1995,2127,1716,1728,1294,1494,921,766,241,420,0,145,69,133,284,192,439,382,480,529,545,575,608,754,644,924,977,1275,1005,1740,2310,3098,3095], [2004,2136,1725,1737,1303,1503,930,575,250,429,145,0,126,162,223,222,469,412,510,559,575,605,638,784,674,954,1007,1305,1034,1770,2340,3128,3125], [2022,2153,1743,1754,1320,1520,948,792,268,446,69,126,0,81,224,140,387,330,428,477,493,523,556,703,592,872,925,1224,953,1688,2258,3046,3043], [2090,2222,1811,1823,1389,1588,1016,861,336,515,133,162,81,0,246,133,380,323,421,470,486,516,549,695,585,865,918,1216,946,1681,2251,3039,3036], [2190,2321,1911,1922,1489,1688,1116,961,436,615,284,223,224,246,0,154,158,221,319,368,384,414,447,594,483,764,816,1115,844,1579,2149,2938,2934], [2150,2281,1871,1882,1448,1648,1076,920,396,574,192,222,140,133,154,0,250,193,291,340,356,386,419,566,455,735,788,1087,816,1551,2121,2909,2906], [2397,2528,2118,2129,1695,1895,1323,1167,643,821,439,469,387,380,158,250,0,193,291,340,356,386,419,566,455,735,788,1087,816,1551,2121,2909,2906], [2339,2471,2060,2072,1638,1838,1265,1110,585,764,382,412,330,323,221,193,193,0,105,154,170,200,233,380,269,549,602,901,630,1365,1935,2723,2720], [2437,2569,2158,2170,1736,1936,1364,1208,684,862,480,510,428,421,319,291,291,105,0,45,68,98,131,282,171,452,504,803,532,1264,1834,2622,2622], [2487,2618,2208,2219,1785,1985,1413,1257,733,911,529,559,477,470,368,340,340,154,45,0,79,113,148,256,145,426,478,777,506,1241,1811,2600,2596], [2502,2634,2224,2235,1801,2001,1429,1273,749,927,545,575,493,486,384,356,356,170,68,79,0,43,78,266,155,436,488,787,516,1251,1821,2610,2606], [2532,2664,2254,2265,1831,2031,1459,1303,779,957,575,605,523,516,414,386,386,200,98,113,43,0,33,292,149,462,515,813,543,1278,1848,2636,2633], [2564,2697,2287,2298,1864,2064,1492,1336,812,990,608,638,556,549,447,419,419,233,131,148,78,33,0,258,134,428,481,779,508,1244,1814,2602,2598], [2712,2843,2433,2444,2011,2210,1638,1482,958,1137,754,784,703,695,594,566,566,380,282,256,266,292,258,0,131,169,222,520,250,985,1555,2343,2340], [2601,2733,2322,2334,1900,2100,1527,1372,847,1026,644,674,592,585,483,455,455,269,171,145,155,149,134,131,0,300,353,651,380,1116,1686,2474,2470], [2882,3013,2603,2614,2181,2380,1808,1652,1128,1306,924,954,872,865,764,735,735,549,452,426,436,462,428,169,300,0,82,381,110,845,1415,2204,2200], [2935,3066,2653,2667,2233,2433,1861,1705,1181,1359,977,1007,925,918,816,788,788,602,504,478,488,515,481,222,353,82,0,314,43,778,1348,2136,2033], [3233,3364,2954,2965,2532,2731,2159,2003,1479,1658,1275,1305,1224,1216,1115,1087,1087,901,803,777,787,813,779,520,651,381,314,0,274,705,1552,2340,2337], [2962,3094,2683,2695,2261,2460,1888,1733,1208,1387,1005,1034,953,946,844,816,816,630,532,506,516,543,508,250,380,110,43,274,0,739,1309,2097,2094], [3698,3829,3419,3430,2996,3196,2624,2468,1944,2122,1740,1770,1688,1681,1579,1551,1551,1365,1264,1241,1251,1278,1244,985,1116,845,778,705,739,0,410,1473,1470], [4268,4399,3989,4000,3566,3766,3194,3038,2514,2692,2310,2340,2258,2251,2149,2121,2121,1935,1834,1811,1821,1848,1814,1555,1686,1415,1348,1552,1309,410,0,1282,1452], [5056,5187,4777,4788,4355,4321,3982,3826,3302,3480,3098,3128,3046,3039,2938,2909,2909,2723,2622,2600,2610,2636,2602,2343,2474,2204,2136,2340,2097,1473,1282,0,47], [5052,5184,4773,4785,4351,4318,3978,3823,3298,3477,3095,3125,3043,3036,2934,2906,2906,2720,2622,2596,2606,2633,2598,2340,2470,2200,2033,2337,2094,1470,1452,47,0] ] #lista con el nombre de las ciudades de 1...33 ciudades=['ARICA', 'PUTRE','IQUIQUE','POZO ALMONTE','ANTOFAGASTA','CALAMA','CHAÑARAL','COPIAPO','ILLAPEL','COQUIMBO','LOS ANDES','VALPARAISO','LAMPA','SAN JOSE DE MAIPO', 'PICHILEMU','RENGO','CONSTITUCION','LINARES','CHILLAN','PEMUCO','FLORIDA','CONCEPCION','CORONEL','TEMUCO','ANGOL','VALDIVIA','LA UNION','CASTRO','OSORNO','PUERTO AYSEN','COCHRANE','PUNTA ARENAS','PORVENIR']

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__author__ = 'krishnaa' import urllib2 import base64 import sys def getToken(url,login,passwd,method): handler = urllib2.HTTPSHandler() opener = urllib2.build_opener(handler) url = url + '/api/sessions' request = urllib2.Request(url) base64string = base64.encodestring('%s:%s' % (login, passwd))[:-1] authheader = "Basic %s" % base64string request.add_header("Authorization", authheader) request.add_header("Accept",'application/*+xml;version=5.5') request.get_method = lambda: method try: connection = opener.open(request) except urllib2.HTTPError,e: connection = e if connection.code == 200: data = connection.read() print "Session code " authtoken = connection.info().getheader('x-vcloud-authorization') #print "Data :", data else: print "Unauthorized..." print "ERROR", connection.code, connection.read() sys.exit(1) return authtoken

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#!/usr/bin/env python # -*- coding: utf-8 -*- ''' @Time : 2018/8/23 上午8:41 @Author : fanyuexiang @Site : @File : AdaLineGD.py @Software: PyCharm @version: 1.0 @describe: 自适应线性神经元（Adaline） ''' import numpy as np class AdaLineGD(object): def __init__(self, eta = 0.01, n_iter = 50): self.eta = eta self.n_iter = n_iter def fit(self, X, y): self.w_ = np.zeros(X.shape[1]+1) self.cost_ = [] for i in range(self.n_iter): # 批量更新权重，批量梯度下降 output = self.net_input(X=X) errors = (y-output) self.w_[1:] += self.eta * X.T.dot(errors) self.w_[0] += self.eta * errors.sum() cost = (errors ** 2).sum() / 2.0 self.cost_.append(cost) return self def net_input(self,X): z = self.w_[1:] + self.w_[0] return np.dot(X, self.w_[1:]) + self.w_[0] def predict(self,X): return np.where(self.net_input(X) >= 0.0, 1, -1)

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# -*- coding: utf-8 -*- """ 作者：向永源说明: cupy 函数输入变量是device变量，输出也是device变量！！！切记！DEVICE中为防止FFT失败，输入前用 astype(np.xxxx) 进行类型转换！！！更新： 2019-10-15 2019-11-22 2019-11-26 2019-12-26 """ import math import numpy as np import astropy.io.fits as fits import os import numpy.fft as fft import imageio import cv2 import matplotlib.pyplot as plt import matplotlib.animation as animation from matplotlib.animation import PillowWriter import scipy.ndimage as ndm from collections import Counter import numpy.random as rand from numpy import sinc import cupy as cp ####================================================= 文件操作 ''' 读一帧简单格式的fits文件参数：文件名返回： [数据，头文件] ''' def readfits(filename): data=fits.getdata(filename) header=fits.getheader(filename) return [data,header] ''' 保存一帧简单格式的fits文件参数：文件名，数据，头文件备注：hdr=fits.Header() 是默认变量，当调用函数时候无hdr,则默然创建一个头文件调用： xyy.writefits(filename, data, hdr), xyy.writefits(filename, data) 返回： FITS文件 ''' def writefits(filename, data, hdr=fits.Header()): if os.path.exists(filename): os.remove(filename) fits.writeto(filename, data, hdr) ''' 寻找目录下所有的文件参数：主路径，文件名包含的字符返回：所有含指定字符串的文件列表 ''' def file_search(dirname,filt): result=[] for maindir, subdir, file_name_list in os.walk(dirname): for filename in file_name_list: apath=os.path.join(maindir, filename) if filt in apath: result.append(apath) return result ''' 寻找目录下所有的子目录参数：主路径返回：所有子目录的列表 ''' def subdir_search(dirname): result=[] for maindir, subdir, file_name_list in os.walk(dirname): for subname in subdir: apath=os.path.join(maindir, subname) result.append(apath) return result ''' 创建文件夹参数：tmppath ''' def mkdir(tmppath): if os.path.exists(tmppath): pass else: os.makedirs(tmppath) ''' 目录里FITS文件打包参数：dirname 返回：cube ''' def dirfitstocube(dirname): files = file_search(dirname,'.fits') zsize = len(files) data = fits.getdata(files[0]) xsize = data.shape[0] ysize = data.shape[1] cube = np.empty([zsize,xsize,ysize], dtype = data.dtype) for i in range(zsize): data = fits.getdata(files[i]) cube[i,:,:] = data print(i) return cube ''' 子目录所有FITS求平均，并保存为FITS 参数：path 返回：addmean ''' def dirfitsaddmean(path): files = file_search(path,'.fits') zsize = len(files) if zsize == 0: print('文件夹下没有FITS文件！！！') addmean=[] if zsize >= 1: nn=zsize addmean=0 for i in range(zsize): filename=files[i] if not os.path.getsize(filename): os.remove(filename) nn=nn-1 continue data = fits.getdata(filename) addmean = addmean + data addmean = addmean/nn return addmean ######+========================================================== 图像显示和电影 ''' 显示一张图像 ''' def showimg(data): plt.close() mi=max([data.min(),data.mean()-3*data.std()]) mx=min([data.max(),data.mean()+3*data.std()]) plt.imshow(data,vmin=mi,vmax=mx,cmap='gray') return ''' 三维CUBE做成GIF 参数：cube，gif_name, nx,ny(视频的大小), gap(取图像的间隔) 返回：GIF ''' def cubetogif(cube, gif_name, nx, ny, gap): size = cube.shape zsize = size[0] xsize = size[1] ysize = size[2] xv = min(xsize,nx) yv = min(ysize,ny) zv = zsize//gap frames = np.empty([zv,xv,yv], dtype = np.uint8) for i in range(zv): data = cube[i*gap,:,:].astype(np.float32) tmp = cv2.resize(data, (xv,yv), interpolation = cv2.INTER_CUBIC) tmp0 = ((tmp-np.min(tmp))/(np.max(tmp)-np.min(tmp))*255.0).astype(np.uint8) frames[i,:,:] = tmp0 imageio.mimsave(gif_name, frames, 'GIF', duration = 0.05) return ''' 三维CUBE做成GIF,添加水印参数：cube，gif_name, gsize(画布大小)，gap(取图像的间隔), nfps 返回：GIF 备注：优于cubetogif ''' def cubetogif2(cube, gif_name, gsize, gap, nfps): fig = plt.figure(figsize = (gsize, gsize)) zsize = cube.shape[0] xsize = cube.shape[1] ysize = cube.shape[2] zv = zsize//gap frames = [] for i in range(zv): fn = i*gap data = cube[fn,:,:] im = plt.imshow(data, animated=True, cmap='gray') text = plt.text(xsize*0.15, ysize*0.85, '{:0>4d}'.format(fn), fontsize=18, style='italic', ha='left',va='bottom',wrap=True) frames.append([im,text]) ani = animation.ArtistAnimation(fig, frames, interval=100, blit=True,repeat_delay=1000) writer = PillowWriter(fps=nfps, metadata=dict(artist='Me'), bitrate=1800) ani.save(gif_name,writer=writer) return ani ''' 目录里FITS文件做成GIF,添加水印参数：dirname，gif_name, gap(取图像的间隔), nfps 返回：GIF ''' def dirfitstogif2(dirname, gif_name, gsize, gap, nfps): fig = plt.figure(figsize = (gsize, gsize)) files = file_search(dirname,['.fits']) zsize = len(files) head = fits.getheader(files[0]) xsize = head['NAXIS1'] ysize = head['NAXIS2'] zv = zsize//gap frames = [] for i in range(zv): fn = i*gap data = fits.getdata(files[i]) im = plt.imshow(data, animated=True, cmap='gray') text = plt.text(xsize*0.15, ysize*0.85, '{:0>4d}'.format(fn), fontsize=18, style='italic', ha='left',va='bottom',wrap=True) frames.append([im,text]) ani = animation.ArtistAnimation(fig, frames, interval=100, blit=True,repeat_delay=1000) writer = PillowWriter(fps=nfps, metadata=dict(artist='Me'), bitrate=1800) ani.save(gif_name,writer=writer) return ani ######========================================================= 图像相关和移动 ''' 计算相关最大值位置参数：参考图ini，目标图obj ; 如果关键字win无，则默认win=1.0 返回：最大值坐标向量（目标相对于参考的位置向量） ''' def corrmaxloc(ini, obj, win=1.0): xsize = ini.shape[0] ysize = ini.shape[1] initmp = (ini - np.mean(ini))*win inifft = fft.fft2(initmp) objtmp = (obj - np.mean(obj))*win objfft = fft.fft2(objtmp) corr = np.real(fft.fftshift(fft.ifft2(np.conj(objfft)*inifft))) maxid = np.where(corr == np.max(corr)) shiftxy = [xsize//2-maxid[0][0], ysize//2-maxid[1][0]] return shiftxy, corr ''' 计算相关最大值位置 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ GPU 参数：参考图ini_gpu，目标图obj_gpu (device 中的变量); 如果关键字win无，则默认win=1.0 返回：最大值坐标向量（目标相对于参考的位置向量） ''' def corrmaxloc_gpu(ini_gpu, obj_gpu, win=1.0): xsize = ini_gpu.shape[0] ysize = ini_gpu.shape[1] initmp = (ini_gpu - cp.mean(ini_gpu))*win inifft = cp.fft.fft2(initmp) objtmp = (obj_gpu - cp.mean(obj_gpu))*win objfft = cp.fft.fft2(objtmp) corr_gpu = cp.real(cp.fft.fftshift(cp.fft.ifft2(cp.conj(objfft)*inifft))) maxid = np.where(corr_gpu == cp.max(corr_gpu)) shiftxy = [xsize//2-maxid[0][0], ysize//2-maxid[1][0]] return shiftxy, corr_gpu ''' 计算相关最大值位置(亚像元) 参数：参考图ini，目标图obj 返回：最大值坐标向量（目标相对于参考的位置向量） ''' def corrmaxsubloc(ini, obj, win=1.0): xsize = ini.shape[0] ysize = ini.shape[1] initmp = (ini - np.mean(ini))*win inifft = fft.fft2(initmp) # objtmp = (obj - np.mean(obj))*win objfft = fft.fft2(objtmp) corr = np.real(fft.fftshift(fft.ifft2(np.conj(objfft)*inifft))) maxid = np.where(corr == np.max(corr)) dxy0 = [-xsize//2+maxid[0][0], -ysize//2+maxid[1][0]] dxy0=np.minimum(np.maximum(dxy0,[-xsize//5*2,-ysize//5*2]),[xsize//5*2,ysize//5*2]) tmp = imgshift(obj,dxy0) objtmp = (tmp - np.mean(tmp))*win objfft = fft.fft2(objtmp) corr = np.real(fft.fftshift(fft.ifft2(np.conj(objfft)*inifft))) maxid = np.where(corr == np.max(corr)) nn=3 index=np.maximum([maxid[0][0],maxid[1][0]],[nn//2,nn//2]) tmp=corr[index[0]-nn//2:index[0]-nn//2+nn,index[1]-nn//2:index[1]-nn//2+nn] tmp=tmp-np.min(tmp) cent=centroid(tmp) ddxy=[-dxy0[0]+xsize//2-index[0]+nn//2-cent[0], -dxy0[1]+ysize//2-index[1]+nn//2-cent[1]] return ddxy, corr ''' 相移定理,可用于亚像素平移参数：img，shift ( [dx,dy] ) 返回： ''' def phaseshift(img,shift): tmp=img.copy() fftimg=fft.fftshift(fft.fft2(tmp)) xsize=img.shape[0] ysize=img.shape[1] [Y,X]=np.meshgrid(np.arange(ysize)-ysize//2,np.arange(xsize)-xsize//2) tmp0=fftimg*np.exp(2.0*np.pi*(X*shift[0]/xsize+Y*shift[1]/ysize)*(-1j)) result=fft.ifft2(fft.ifftshift(tmp0)).real return result ''' 相移定理,可用于亚像素平移 ~~~~~~~~~~~ GPU 参数：img_cupy ，shift ( [dx,dy] ) 返回：结论：速度 phaseshift_cupy > imgsubshift > imgsubshift_cupy > phaseshift ''' def phaseshift_cupy(img_cupy,shift): fftimg_cupy=cp.fft.fftshift(cp.fft.fft2(img_cupy)) xsize=img_cupy.shape[0] ysize=img_cupy.shape[1] [Y,X]=cp.meshgrid(cp.arange(ysize)-ysize//2,cp.arange(xsize)-xsize//2) phas=cp.zeros([xsize,ysize],dtype=cp.complex64) phas.imag=-2.0*cp.pi*cp.add(X*shift[0]/xsize,Y*shift[1]/ysize) tmp0=cp.multiply(fftimg_cupy,cp.exp(phas)) result_cupy=cp.fft.ifft2(cp.fft.ifftshift(tmp0)).real return result_cupy ''' 亚像素平移参数：img，shift 返回：备注：结果和相移定理一毛一样! ''' def imgsubshift(img,shift): tmp = img.copy() fftimg = fft.fft2(tmp) tmp0 = ndm.fourier_shift(fftimg, shift) result = fft.ifft2(tmp0).real return result ''' 亚像素平移参数：img_cupy，shift 返回： ''' def imgsubshift_cupy(img_cupy,shift): fftimg_cupy = cp.fft.fft2(img_cupy) fftimg=cp.asnumpy(fftimg_cupy) tmp0=ndm.fourier_shift(fftimg, shift) tmp0_cupy=cp.asarray(tmp0) result_cupy=cp.fft.ifft2(tmp0_cupy).real return result_cupy ''' 二维数组的平移参数：数组，[dx, dy] 返回：平移后的数组备注：此处不宜加上@jit,运行速度不升反降 ''' def imgshift(img,dxy): imgout=np.copy(img) imgout=np.roll(imgout,int(dxy[0]),axis=0) imgout=np.roll(imgout,int(dxy[1]),axis=1) return imgout ''' 二维数组的平移 ~~~~~~~~~~~~~ GPU 参数：img_cupy，[dx, dy] (输入变量必须是 device 中的变量) 返回：平移后的数组(device 变量) ''' def imgshift_cupy(img_cupy,dxy): imgout_cupy=cp.copy(img_cupy) imgout_cupy=cp.roll(imgout_cupy,int(dxy[0]),axis=0) imgout_cupy=cp.roll(imgout_cupy,int(dxy[1]),axis=1) return imgout_cupy ''' 三维数组对齐参数：subcube，lxp, corsize, win相关的窗函数返回：nsubcube ''' def cube_align(subcube,lxp,corsize,win=1.0): zsize = subcube.shape[0] xsize = subcube.shape[1] ysize = subcube.shape[2] corstart=[(xsize-corsize[0])//2,(ysize-corsize[1])//2] ini = lxp[corstart[0]:corstart[0]+corsize[0],corstart[1]:corstart[1]+corsize[1]] nsubcube = np.zeros([zsize,xsize,ysize], dtype = subcube.dtype) for i in range(zsize): data = subcube[i,:,:].copy() obj = data[corstart[0]:corstart[0]+corsize[0],corstart[1]:corstart[1]+corsize[1]] cc,corr = corrmaxloc(ini, obj, win) nsubcube[i,:,:] = imgshift(data,[-cc[0],-cc[1]]) return nsubcube ''' 三维数组对齐（两组）参数：cube2（信噪比高），cube1（信噪比低），lxp2（参考图）, corsize, win相关的窗函数返回：cube2， cube1 ''' def twocube_align(subcube2,subcube1,lxp2,corsize,win=1.0): zsize = subcube2.shape[0] xsize = subcube2.shape[1] ysize = subcube2.shape[2] corstart=[(xsize-corsize[0])//2,(ysize-corsize[1])//2] ini = lxp2[corstart[0]:corstart[0]+corsize[0],corstart[1]:corstart[1]+corsize[1]] nsubcube2 = np.empty([zsize,xsize,ysize], dtype = subcube2.dtype) nsubcube1 = np.empty([zsize,xsize,ysize], dtype = subcube2.dtype) for i in range(zsize): data = subcube2[i,:,:].copy() obj = data[corstart[0]:corstart[0]+corsize[0],corstart[1]:corstart[1]+corsize[1]] cc,corr = corrmaxloc(ini, obj, win) nsubcube2[i,:,:] = imgshift(data,[-cc[0],-cc[1]]) data = subcube1[i,:,:].copy() nsubcube1[i,:,:] = imgshift(data,[-cc[0],-cc[1]]) return nsubcube2,nsubcube1 ''' 三维数组对齐（亚像元）参数：cube2（信噪比高），cube1（信噪比低），lxp2（参考图）, corsize, win相关的窗函数返回：cube2， cube1 ''' def twocube_align_sub(subcube2,subcube1,lxp2,corsize,win=1.0): zsize = subcube2.shape[0] xsize = subcube2.shape[1] ysize = subcube2.shape[2] corstart=[(xsize-corsize[0])//2,(ysize-corsize[1])//2] ini = lxp2[corstart[0]:corstart[0]+corsize[0],corstart[1]:corstart[1]+corsize[1]] nsubcube2 = np.empty([zsize,xsize,ysize], dtype = subcube2.dtype) nsubcube1 = np.empty([zsize,xsize,ysize], dtype = subcube2.dtype) for i in range(zsize): data = subcube2[i,:,:].copy() obj = data[corstart[0]:corstart[0]+corsize[0],corstart[1]:corstart[1]+corsize[1]] cc,corr = corrmaxsubloc(ini, obj, win) nsubcube2[i,:,:] = imgsubshift(data,[-cc[0],-cc[1]]) data = subcube1[i,:,:].copy() nsubcube1[i,:,:] = imgsubshift(data,[-cc[0],-cc[1]]) return nsubcube2,nsubcube1 ######======================================== 窗函数和滤波器 ''' #---说明：返回图像振幅和相位 #---参数： img #---返回： modul，phase ''' def imgmodpha(img): [xsize,ysize]=img.shape sp=fft.fftshift(fft.fft2(img))/xsize/ysize modul=np.abs(sp) phase=np.angle(sp) return modul,phase ''' #---说明：振幅和相位返回图像 #---参数： modul，phase #---返回： img ''' def modphaimg(modul,phase): [xsize,ysize]=modul.shape sp=modul*np.exp(0+1j*phase)*xsize*ysize img=fft.ifft2(fft.ifftshift(sp)).real return img ''' 窗函数参数：nx,ny 窗函数大小， apod切趾的比例, a0=0.5 for hanning, a0=25.0/46.0 for hamming, 当无参数winsty时，默认a0=0.5 调用：xyy.win(xsize,ysize,0.2,'hamm') 返回：win ''' def win(nx,ny,apod,winsty=0.0): if winsty == 'hann': a0=0.5 if winsty == 'hamm': a0=25.0/46.0 if winsty == 0.0: a0=0.5 nn = np.int16((apod*nx)//2*2+1) wx = a0-(1.0-a0)*np.cos(2.0*np.pi*np.arange(nn).reshape(nn,1)/(nn-1)) maxp = np.max(wx) maxid = np.where(wx == maxp) c = maxid[0][0] w1 = np.empty([nx,1], dtype = np.float32) w1[0:c]=wx[0:c] w1[c:nx-(nn-c)]=maxp w1[nx-(nn-c):nx]=wx[c:nn] nn = np.int16((apod*ny)//2*2+1) wy = a0-(1.0-a0)*np.cos(2.0*np.pi*np.arange(nn).reshape(nn,1)/(nn-1)) maxp = np.max(wy) maxid = np.where(wy == maxp) c = maxid[0][0] w2 = np.empty([ny,1], dtype = np.float32) w2[0:c]=wy[0:c] w2[c:ny-(nn-c)]=maxp w2[ny-(nn-c):ny]=wy[c:nn] win = np.dot(w1, w2.T) win=win/np.max(win) return win ''' #----说明：频域图像滤波(卷积) #----参数: data, filt #----返回： img ''' def ImgFilted(data,filt): fftobj=fft.fft2(data) fftpsf=fft.fft2(filt) img=fft.fftshift((fft.ifft2(fftobj*fftpsf))).real.astype(np.float32) return img ''' #----说明：图像功率谱推卷积 #----参数: data, sitf #----返回： img ''' def ImgPSDdeconv(data,sitf): modul,phase=imgmodpha(data) mod=np.sqrt(modul**2/(sitf+0.0001)) img=modphaimg(mod,phase) return img ''' 二维高斯函数参数：xsize，ysize，delta 返回： ''' def gaussf2d(xsize,ysize,delta): xline=np.exp(-(np.arange(xsize)-xsize//2)**2/(delta)**2.0) yline=np.exp(-(np.arange(ysize)-ysize//2)**2/(delta)**2.0) [Y,X]=np.meshgrid(yline,xline) return Y*X ######==================================================================================== 其他 ''' 圆孔参数： xsize,ysize,radus 说明：圆孔中心（xsize//2,ysize//2） ''' def circlepupil(xsize,ysize,radus): pupil=np.zeros([xsize,ysize],dtype=np.float32) [Y,X]=np.meshgrid(np.arange(ysize)-ysize//2,np.arange(xsize)-xsize//2) R=np.sqrt(Y*Y+X*X) pupil=np.where(R<=radus,1.0,0.0) return pupil ''' 图像径向求平均参数： data 返回： datanew ''' def imgradusmean(data): xsize,ysize=data.shape [Y,X]=np.meshgrid(np.arange(ysize)-ysize//2,np.arange(xsize)-xsize//2) R=np.sqrt(X*X+Y*Y) datanew=np.zeros([xsize,ysize],dtype=np.float32) datanew[xsize//2,ysize//2]=data[xsize//2,ysize//2] for i in np.arange(0,np.min([xsize,ysize])//2): mask=np.where(R<=i+1,1.0,0.0)-np.where(R<=i,1.0,0.0) val=np.sum(mask*data)/np.sum(mask) datanew=datanew+val*mask return datanew ''' 返回质心坐标参数：img 返回：[dx,dy] ''' def centroid(img): xsize=img.shape[0] ysize=img.shape[1] [Y,X]=np.meshgrid(np.arange(ysize),np.arange(xsize)) dx = np.sum(X*img)/np.sum(img) dy = np.sum(Y*img)/np.sum(img) return [dx,dy] ''' 二维数组BINNING 参数：参考图img，bins 返回：图像new ''' def imgbin(img, bins): xsize = img.shape[0] ysize = img.shape[1] newxsize = xsize//bins newysize = ysize//bins cpy = img.copy() tmp = np.empty([xsize,newysize], dtype = np.int16) for i in range(xsize): tmp[i,:] = cpy[i,:newysize*bins].reshape(-1,bins).mean(axis=1) new = np.empty([newxsize,newysize], dtype = np.int16) for i in range(newysize): new[:,i] = tmp[:newxsize*bins,i].reshape(-1,bins).mean(axis=1) return new ''' 计算两幅图像（二维矩阵）的皮尔森积矩相关系数参数：imga，imgb, 返回： ''' def prs_cor_coef(ima,imb): imga=ima.copy()/np.mean(ima) imgb=imb.copy()/np.mean(imb) cov=np.sum((imga-np.mean(imga))*(imgb-np.mean(imgb))) tha=(np.sum((imga-np.mean(imga))**2.0))**0.5 thb=(np.sum((imgb-np.mean(imgb))**2.0))**0.5 cc=cov/(tha*thb) return cc ''' #---说明：计算各点到原点（二维图像中心)）的欧式距离 #---参数： row（行数），col（列数） #---返回： array ''' def dist(row,col): [X,Y]=np.meshgrid(np.arange(col)-col//2,np.arange(row)-row//2) dist=(X**2.0+Y**2.0)**0.5 return dist ######################===================================================== 传递函数 ''' # 函数：计算特定频率下环形光瞳的传递函数, 几何算法, 归一化的自相关面积 # 参数： a：遮挡比，a=0 代表清澈圆孔径； rho：空间频率 # 返回：该频率下的归一化OTF值 ''' def ringotfcal(a, rho): if (rho < 0) or (rho > 1): return 0.0 if (a < 0) or (a > 1): return 0.0 #---------------------- r=0.5 if (rho < 2.0*r): c=2.0*math.acos(rho/(r*2.0))*r**2-rho*math.sqrt(r**2-rho**2/4.0) else: c=0.0 if (rho < 2.0*r*a): e=2.0*math.acos(rho/(a*r*2.0))*(r*a)**2-rho*math.sqrt((r*a)**2-rho**2/4.0) else: e=0.0 if (rho <= r+a*r) and (rho > r-a*r): s1=0.5*math.acos(((r*a)**2+rho**2-r**2)/(2.0*r*a*rho))*(r*a)**2 s2=0.5*math.acos((rho**2+r**2-(r*a)**2)/(2.0*r*rho))*r**2 s3=0.5*math.sin(math.acos(((r*a)**2+rho**2-r**2)/(2.0*a*r*rho)))*a*r*rho d=2.0*(s1+s2-s3) else: if rho <= r-a*r : d=math.pi*(a*r)**2 else : d=0.0 #-------------------------- h=(c+e-2*d)/(math.pi*r**2) if rho == 0 : h=1-a**2 return h ''' # 函数：计算指定环型光瞳，指定采样比例尺的望远镜OTF, a=0代表清澈圆孔径 # 返回：二维数组，OTF ''' def telotf(a, maxfre, width): half=width//2 cent=width//2 otf=np.zeros([width,width],dtype=np.float32) for i in range(width): for j in range(width): fre=np.sqrt((i-cent)**2+(j-cent)**2)/half*maxfre freq=np.minimum(fre,1.0) otf[i,j]= ringotfcal(a, freq) otf=otf/otf[cent,cent] return otf ''' # 函数：大气短曝光传递函数计算 # 返回：特定空间频率下的 OTF 值 ''' def atsotfcal(diameter, r0, fre): #otf=np.exp(-3.44*(diameter/r0*fre)**(5/3)*(1-fre**(1/3))) otf=np.exp(-3.44*(diameter/r0*fre)**(5/3)*(1-np.exp(-fre**3)*fre**(1/3))) # 此举抑制高频上翘 return otf ''' # 函数：大气短曝光传递函数计算 # 返回：二维数组 ''' def atsotf(diameter, r0, width, maxfre): half=width//2 cent=width//2 [Y,X]=np.meshgrid(np.arange(width)-half,np.arange(width)-half) fre=np.sqrt(X*X+Y*Y)/half*maxfre freq=np.minimum(fre,1.0) sotf=np.exp(-3.44*(diameter/r0*freq)**(5/3)*(1-np.exp(-freq**3)*freq**(1/3))) # 此举抑制高频上翘 sotf=sotf/sotf[cent,cent] return sotf ''' # 函数：计算综合系统短曝光传递函数 # 返回：二维数组，OTF ''' def sotf(diameter, a, r0, maxfre, width): half=width//2 cent=width//2 sotf=np.zeros([width,width],dtype=np.float32) for i in range(width): for j in range(width): fre=np.sqrt((i-cent)**2+(j-cent)**2)/half*maxfre freq=np.minimum(fre,1.0) sotf[i,j]=ringotfcal(a, freq)*atsotfcal(diameter, r0, freq) sotf=sotf/sotf[cent,cent] return sotf ''' # 函数：大气长曝光传递函数计算 # 返回：特定空间频率下的 OTF 值 ''' def atlotfcal(diameter, r0, fre): otf=np.exp(-3.44*(diameter/r0*fre)**(5/3)) return otf ''' # 函数：大气长曝光传递函数计算 # 返回：二维数组 ''' def atlotf(diameter, r0, width, maxfre): half=width//2 cent=width//2 [Y,X]=np.meshgrid(np.arange(width)-half,np.arange(width)-half) fre=np.sqrt(X*X+Y*Y)/half*maxfre freq=np.minimum(fre,1.0) lotf=np.exp(-3.44*(diameter/r0*freq)**(5/3)) lotf=lotf/lotf[cent,cent] return lotf ''' # 函数：计算综合系统长曝光传递函数 # 返回：二维数组，OTF ''' def lotf(diameter, a, r0, maxfre, width): cent=width//2 half=width//2 lotf=np.zeros([width,width],dtype=np.float32) for i in range(width): for j in range(width): fre=np.sqrt((i-cent)**2+(j-cent)**2)/half*maxfre freq=np.minimum(fre,1.0) lotf[i,j]=ringotfcal(a, freq)*atlotfcal(diameter, r0, freq) lotf=lotf/lotf[cent,cent] return lotf ''' # 说明：计算标准谱比（短曝光） # 输入： sitfdata, diameter, diaratio, maxfre, subsize, start_r0, step_r0 # 返回：三维数组 ''' def sotfsrstand(sitfdata,diameter,diaratio,maxfre,subsize,start_r0,step_r0): r0num=sitfdata.shape[0] TelOtf=telotf(diaratio, maxfre, subsize) sotfsrstand=np.zeros([r0num,subsize, subsize], dtype=np.float32) for i in range(r0num): subsitf=GetSitf(sitfdata,maxfre,subsize,i) r0=start_r0+step_r0*i AtSotf=atsotf(diameter, r0, subsize, maxfre) sotf=TelOtf*AtSotf sotfsr=sotf**2/(subsitf) sotfsr=sotfsr/sotfsr[subsize//2,subsize//2] sotfsrstand[i,:,:]=sotfsr return sotfsrstand ''' # 说明：计算标准谱比（长曝光） # 输入： sitfdata, diameter, diaratio, maxfre, subsize, start_r0, step_r0 # 返回：三维数组 ''' def lotfsrstand(sitfdata,diameter,diaratio,maxfre,subsize,start_r0,step_r0): r0num=sitfdata.shape[0] TelOtf=telotf(diaratio, maxfre, subsize) lotfsrstand=np.zeros([r0num,subsize, subsize], dtype=np.float32) for i in range(r0num): subsitf=GetSitf(sitfdata,maxfre,subsize,i) r0=start_r0+step_r0*i AtLotf=atlotf(diameter, r0, subsize, maxfre) lotf=TelOtf*AtLotf lotfsr=lotf**2/(subsitf) lotfsr=lotfsr/lotfsr[subsize//2,subsize//2] lotfsrstand[i,:,:]=lotfsr return lotfsrstand ''' # 说明：计算一组三维数组的谱比 # 输入： cubesub,winsr # 返回： sr (二维数组) ''' def cubesrcal(cubesub,winsr): srsize=cubesub.shape[1] corsize=[int(srsize*0.8),int(srsize*0.8)] #----- 计算平均帧 meanf=np.mean(cubesub,axis=0) #----- 平均帧的平均值 mfval=np.mean(meanf) #----- 以平均帧对齐 cubesubalign=cube_align(cubesub,meanf,corsize) #------------- 平均叠加帧加窗 lxp=(meanf-mfval)*winsr+mfval #----- 计算每一帧图像的均值 meanv=np.mean(cubesubalign,axis=(1,2)) mvcast=meanv[:,None,None] #----（每一帧图像-其均值）* 窗函数 + 其均值 cubesubalignwin=(cubesubalign-mvcast)*winsr+mvcast #-------傅里叶变换（得到每一帧频谱） cubesp=fft.fftshift(fft.fft2(cubesubalignwin,axes=(1,2)),axes=(1,2)) psd=Psdcubecal(cubesp) psd=psd/psd[srsize//2,srsize//2] psdnd,noise=Psdnd(psd) psdnd=psdnd/psdnd[srsize//2,srsize//2] #--------------计算平均短曝光传递函数 sotf2=np.abs(np.fft.fftshift(np.fft.fft2(lxp)))**2 sotf2=sotf2/sotf2[srsize//2,srsize//2] sotf2nd,noise2=Psdnd(sotf2) sotf2nd=sotf2nd/sotf2nd[srsize//2,srsize//2] #--------------计算谱比 sr=sotf2/(psdnd+0.0000001) sr=sr/sr[srsize//2,srsize//2] return sr,sotf2,psd,noise ''' # 说明：谱比导出r0 # 输入： sr, srarry（标准谱比）, maxfre（用于确定截止频率位置）, low（环带积分内环位置）, hig（环带积分外环位置） # 返回： r0 ''' def srdevr0(sr,srarry,maxfre,low,hig,start_r0,step_r0): srsize=sr.shape[1] [Y,X]=np.meshgrid(np.arange(srsize)-srsize//2,np.arange(srsize)-srsize//2) mask1=np.where(np.sqrt(X**2+Y**2)<=(srsize//2)/(1.0*maxfre)*hig, 1.0, 0.0) mask2=np.where(np.sqrt(X**2+Y**2)>=(srsize//2)/(1.0*maxfre)*low, 1.0, 0.0) masksr=mask1*mask2 diff1=(srarry-sr)*masksr diff2=diff1**2.0 valarr=np.sum(diff2,axis=(1,2)) idex=np.where(valarr==np.min(valarr))[0][0] r0=start_r0+step_r0*idex return r0,masksr ''' # 说明： cube分块谱比导出r0 # 输入： cubesr,srsize,winsr,sitfdata,diameter,diaratio,maxfre,low,hig,start_r0,step_r0 # 返回： r0,index ''' def cubesrdevr0(cubesr,srsize,winsr,sitfdata,diameter,diaratio,maxfre,low,hig,start_r0,step_r0): srarry=sotfsrstand(sitfdata,diameter,diaratio,maxfre,srsize,start_r0,step_r0) xnum=cubesr.shape[2]//srsize ynum=cubesr.shape[1]//srsize r0arr=[] ###corsize=[int(srsize*0.9),int(srsize*0.9)] for i in range(xnum): for j in range(ynum): cubesub=cubesr[:,i*srsize:i*srsize+srsize,i*srsize:i*srsize+srsize] ###meanf=np.mean(cubesub,axis=0) ###cubesubalign=cube_align(cubesub,meanf,corsize,win=1.0) sr,sotf2,psd,noise=cubesrcal(cubesub,winsr) sr_filter=ndm.gaussian_filter(sr, sigma=0.8) sr_filter=sr_filter/sr_filter[srsize//2,srsize//2] r0,masksr=srdevr0(sr_filter,srarry,maxfre,low,hig,start_r0,step_r0) r0arr.append(r0) r0=(Counter(r0arr).most_common(1)[0][0]).astype(np.float32) index=np.rint((r0-start_r0)/step_r0).astype(np.int) print('r0 =',r0) return r0,index ''' #----说明：计算斑点干涉术传递函数 #----参数： stfdata, Maxfre, IMsize, idx #----返回： sitf ''' def GetSitf(stfdata,maxfre,imsize,idx): sitfsize=stfdata.shape[1] mpr=(sitfsize)*(maxfre*2.0)/(imsize) [Y,X]=np.meshgrid(np.arange(imsize)-imsize//2,np.arange(imsize)-imsize//2) mprtx=np.int64(np.sqrt(X*X+Y*Y)*mpr) sitf=stfdata[idx,np.minimum(mprtx,sitfsize-1)] sitf=sitf/sitf[imsize//2,imsize//2] return sitf ''' #----说明：功率谱退卷积 #----参数: fdata, subsitf #----返回： img ''' def PsdDeconv(data,subsitf): [xsize,ysize]=data.shape datasp=fft.fftshift(fft.fft2(data))/xsize/ysize pha=np.angle(datasp) psd=np.abs(datasp)**2 mod=np.sqrt(psd/(subsitf+0.0005)) sp=mod*np.exp(0+1j*pha)*xsize*ysize img=fft.ifft2(fft.ifftshift(sp)).real return img

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#!/usr/bin/env python import os import sys import string import json import inspect from pymatgen import Structure from fireworks import Firework, Workflow, LaunchPad from pymatgen.io.vasp.interfaces import VaspInputInterface, VaspFirework, VaspWorkflow # get structure from Crystallographic Information File (CIF) s = Structure.from_file('./mp-33088_Cr2FeO4.cif') input=VaspInputInterface(s) input.NEDOS=2000 # override default or add INCAR parameter # Dump VASP Input into current directory for inspection input.write_input() # Complete definition of Firework Task(s) and add to # Firework task=VaspFirework(input) # Save specification to yaml file for later inspection # or manual add to launchpad with lpad script task.to_file("simple_task.yaml") # Adds single Firework to launchpad database task.add_fw_to_launchpad()

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from datetime import datetime from decimal import Decimal import pytest from ..exceptions import DealerDoesNotExist from ..models import Order from ..services import OrderService @pytest.mark.django_db class TestOrderService: @pytest.fixture def order_data(self): return { 'code': 'order_code', 'amount': 5000, 'date': datetime.now(), 'cpf': '38723274884' } def test_should_not_create_an_order_because_delaer_doesnt_exist( self, user, order_data ): order_data['cpf'] = '99999999999' with pytest.raises(DealerDoesNotExist): OrderService.create_order(**order_data) def test_should_create_an_order(self, order_data, user): order = OrderService.create_order(**order_data) assert order def test_order_should_generate_a_cashback(self, order_data, user): order = OrderService.create_order(**order_data) assert hasattr(order, 'cashback') @pytest.mark.parametrize( 'order_amount,expected_cashback_amount', [ (Decimal('100'), Decimal('10')), (Decimal('1000'), Decimal('100')), (Decimal('1500'), Decimal('225')), (Decimal('2000'), Decimal('400')), ] ) def test_cashback_calcs( self, order_amount, expected_cashback_amount, order_data, settings, user ): settings.FIRST_LEVEL_CASHBACK_TARGET = 1000 settings.FIRST_LEVEL_CASHBACK_PERCENT = '0.1' settings.SECOND_LEVEL_CASHBACK_TARGET = 1500 settings.SECOND_LEVEL_CASHBACK_PERCENT = '0.15' settings.THIRD_LEVEL_CASHBACK_PERCENT = '0.20' order_data['amount'] = order_amount order = OrderService.create_order(**order_data) assert order.cashback.amount == expected_cashback_amount @pytest.mark.parametrize( 'cpf,status', [ ('38723274884', Order.Status.IN_VALIDATION), ('15350946056', Order.Status.APPROVED), ], ) def test_should_return_status_validation_to_approved_cpf( self, cpf, status, order_data, user, approved_user ): order_data['cpf'] = cpf order = OrderService.create_order(**order_data) assert order.status == status

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"""time_display URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/2.2/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.contrib import admin from django.urls import path, include urlpatterns = [ path('', include('time_app1.urls')), ]

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#!/usr/bin/python3 # stage_2_swarm_gen.py # Created: 6/16/20 # Last edited: # Written by Nikhil Goyal, National Institute of Mental Health, 2019-2020 # Generate commands of the form: # $SUPPORT_SCRIPTS/stage_2/calc_avg_motion.sh $sub $ABCD_CCA_REPLICATION import os import sys fp_sub_list = sys.argv[1] # absolute path to file that contains subject ids abcd_cca_replication = sys.argv[2] # absolute path to main directory in repo (where pipeline.config located) swarm_dir = sys.argv[3] # where to output swarm file script_to_call = sys.argv[4] # name of the script to call (absolute path) subjects = [line.rstrip('\n') for line in open(fp_sub_list)] fp = os.path.join(swarm_dir,'stage_2.swarm') f_swarm = open(fp, 'w') for subject in subjects: cmd = "{} {} {}".format(script_to_call, subject, abcd_cca_replication) f_swarm.write(cmd+'\n') f_swarm.close()

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# -*- coding:utf-8 -*- DP_URL = '%sapp.finance.%s/data/stock/%s?day=&page=%s' DP_163_URL = '%squotes.%s/data/caibao/%s?reportdate=%s&sort=declaredate&order=desc&page=%s' FUND_HOLDS_URL = '%squotes.%s/hs/marketdata/service/%s?host=/hs/marketdata/service/%s&page=%s&query=start:%s;end:%s&order=desc&count=60&type=query&req=%s' XSG_URL = '%sdatainterface.%s/EM_DataCenter/%s?type=FD&sty=BST&st=3&sr=true&fd=%s&stat=%s' LHB_URL = '%sdata.%s/stock/lhb/%s.html' LHB_SINA_URL = '%s%s/q/go.php/vLHBData/kind/%s/%s?last=%s&p=%s' LHB_COLS = ['code', 'name', 'pchange', 'amount', 'buy', 'bratio', 'sell', 'sratio', 'reason'] NEW_STOCKS_URL = '%s%s/corp/view/%s?page=%s&cngem=0&orderBy=NetDate&orderType=desc' MAR_SH_HZ_URL = '%s%s/marketdata/tradedata/%s?jsonCallBack=jsonpCallback%s&isPagination=true&tabType=&pageHelp.pageSize=100&beginDate=%s&endDate=%s%s&_=%s' MAR_SH_HZ_REF_URL = '%s%s/market/dealingdata/overview/margin/' MAR_SH_MX_URL = '%s%s/marketdata/tradedata/%s?jsonCallBack=jsonpCallback%s&isPagination=true&tabType=mxtype&detailsDate=%s&pageHelp.pageSize=100&stockCode=%s&beginDate=%s&endDate=%s%s&_=%s' MAR_SZ_HZ_URL = '%s%s/szseWeb/%s?SHOWTYPE=EXCEL&ACTIONID=8&CATALOGID=1837_xxpl&txtDate=%s&tab2PAGENUM=1&ENCODE=1&TABKEY=tab1' MAR_SZ_MX_URL = '%s%s/szseWeb/%s?SHOWTYPE=EXCEL&ACTIONID=8&CATALOGID=1837_xxpl&txtDate=%s&tab2PAGENUM=1&ENCODE=1&TABKEY=tab2' MAR_SH_HZ_TAIL_URL = '&pageHelp.pageNo=%s&pageHelp.beginPage=%s&pageHelp.endPage=%s' TERMINATED_URL = '%s%s/%s?jsonCallBack=jsonpCallback%s&isPagination=true&sqlId=COMMON_SSE_ZQPZ_GPLB_MCJS_ZZSSGGJBXX_L&pageHelp.pageSize=50&_=%s' SUSPENDED_URL = '%s%s/%s?jsonCallBack=jsonpCallback%s&isPagination=true&sqlId=COMMON_SSE_ZQPZ_GPLB_MCJS_ZTSSGS_L&pageHelp.pageSize=50&_=%s' TERMINATED_T_COLS = ['COMPANY_CODE', 'COMPANY_ABBR', 'LISTING_DATE', 'CHANGE_DATE'] LHB_KINDS = ['ggtj', 'yytj', 'jgzz', 'jgmx'] LHB_GGTJ_COLS = ['code', 'name', 'count', 'bamount', 'samount', 'net', 'bcount', 'scount'] LHB_YYTJ_COLS = ['broker', 'count', 'bamount', 'bcount', 'samount', 'scount', 'top3'] LHB_JGZZ_COLS = ['code', 'name', 'bamount', 'bcount', 'samount', 'scount', 'net'] LHB_JGMX_COLS = ['code', 'name', 'date', 'bamount', 'samount', 'type'] TERMINATED_COLS = ['code', 'name', 'oDate', 'tDate'] DP_COLS = ['report_date', 'quarter', 'code', 'name', 'plan'] DP_163_COLS = ['code', 'name', 'year', 'plan', 'report_date'] XSG_COLS = ['code', 'name', 'date', 'count', 'ratio'] QUARTS_DIC = {'1':('%s-12-31', '%s-03-31'), '2':('%s-03-31', '%s-06-30'), '3':('%s-06-30', '%s-09-30'), '4':('%s-9-30', '%s-12-31')} FUND_HOLDS_COLS = ['count', 'clast', 'date', 'ratio', 'amount', 'nums','nlast', 'name', 'code'] NEW_STOCKS_COLS = ['code', 'name', 'ipo_date', 'issue_date', 'amount', 'markets', 'price', 'pe', 'limit', 'funds', 'ballot'] MAR_SH_COOKIESTR = '_gscu_1808689395=27850607moztu036' MAR_SH_HZ_COLS = ['opDate', 'rzye', 'rzmre', 'rqyl', 'rqylje', 'rqmcl', 'rzrqjyzl'] MAR_SH_MX_COLS = ['opDate', 'stockCode', 'securityAbbr', 'rzye', 'rzmre', 'rzche', 'rqyl', 'rqmcl', 'rqchl'] MAR_SZ_HZ_COLS = ['rzmre', 'rzye', 'rqmcl', 'rqyl', 'rqye', 'rzrqye'] MAR_SZ_MX_COLS = ['stockCode', 'securityAbbr', 'rzmre', 'rzye', 'rqmcl', 'rqyl', 'rqye', 'rzrqye'] MAR_SZ_HZ_MSG = 'please do not input more than a year,you can obtaining the data year by year.' MAR_SZ_HZ_MSG2 = 'start and end date all need input.'

[ "jimmysoa@sina.cn" ]

jimmysoa@sina.cn

bc618a076ffea315a02334a8d7c62eb10b73ccba

ad168daa14c475a0054779bb2f20e7a0d8aad67c

/old/SubCoordSys.py

110e91f1ab638210e052ee00c95db3175d9bfead

[]

no_license

Magnus93/BenzierPy

46a7e94031f3041a4d189172d3feca854431b846

56974241b471729f849a10b77e928fb80380956f

refs/heads/master

2021-01-20T05:15:39.084599

2018-06-11T13:59:41

101,424,502

0

null

2018-06-11T13:59:42

2017-08-25T16:57:35

Python

UTF-8

Python

false

2,054

py

import anchor02 import pygame import mouse import trans2D screen = pygame.display.set_mode((800,600)) mytimer = pygame.time.Clock() class CoordSys: def __init__(self, mv0, mv1): self.p0 = mv0 self.p1 = mv1 self.scale = 1 self.sin = 1 self.cos = 1 self.calcValues() def calcValues(self): self.scale = (trans2D.distance((self.p0.x, self.p0.y),(self.p1.x, self.p1.y)))/100.0 self.sin = trans2D.sin((self.p0.x,self.p0.y), (self.p1.x,self.p1.y)) self.cos = trans2D.cos((self.p0.x,self.p0.y), (self.p1.x,self.p1.y)) def worldToLocal(self, pWorld): #inv = inverse # pLocal(pWorld) = inv(S)*inv(R)*inv(T)*pWorld iTpW = trans2D.translate(pWorld, trans2D.negate((self.p0.x, self.p0.y))) iRiTpW = trans2D.rotateTrig(iTpW, (0,0), -self.sin, self.cos) pLocal = trans2D.scale(iRiTpW, (0,0) ,(1.0/self.scale)) return pLocal def localToWorld(self, pLocal): # pWorld(pLocal) = T*R*S*pLocal self.calcValues() SpL = trans2D.scale(pLocal, (0,0), self.scale) RSpL = trans2D.rotateTrig(SpL, (0,0), self.sin, self.cos) pWorld = trans2D.translate(RSpL, (self.p0.x, self.p0.y)) return pWorld def drawGrid(self): for i in range(0,101, 10): pWorldStart = self.localToWorld((0,i-50)) pWorldEnd = self.localToWorld((100,i-50)) pygame.draw.line(screen, 0xff0000, pWorldStart, pWorldEnd, 1) pWorldStart = self.localToWorld((i,-50)) pWorldEnd = self.localToWorld((i,50)) pygame.draw.line(screen, 0x00ff00, pWorldStart, pWorldEnd, 1) if __name__ == "__main__": circ1 = anchor02.Variable("start", 500, 400) circ2 = anchor02.Variable("end", 40, 30) coo = CoordSys(circ1, circ2) ### --- Testing world to local localto world --- a0 = (3,0) a1 = coo.localToWorld(a0) a2 = coo.worldToLocal(a1) print a0, a1, a2 print "________________________" a0 = (100,100) a1 = coo.localToWorld(a0) a2 = coo.worldToLocal(a1) print a0, a1, a2 ### while(True): screen.fill(0x222222) circ1.run() circ2.run() mouse.run() coo.drawGrid() pygame.display.flip() mytimer.tick(24)

[ "magnus.ja.gustafsson@gmail.com" ]

magnus.ja.gustafsson@gmail.com

cf8f06cbc0467e7a348a264ef447ba41dff0fe89

372647ad5f8a40754116c2b79914708e46960aef

/ivi/dicon/__init__.py

f5112f804a138755dd00d2293a646501207f3aa4

[ "MIT" ]

permissive

edupo/python-ivi

52392decb01bc89c6e1b42cbcbd1295a131e91f5

8105d8064503725dde781f0378d75db58defaecb

refs/heads/master

2020-03-31T21:06:02.059885

2018-10-04T12:34:38

152,567,486

0

MIT

2018-10-11T09:40:35

2018-10-11T09:40:32

Python

UTF-8

Python

false

1,198

py

""" Python Interchangeable Virtual Instrument Library Copyright (c) 2014-2016 Alex Forencich Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ # Programmable fiberoptic instrument from .diconGP700 import diconGP700

[ "alex@alexforencich.com" ]

alex@alexforencich.com

ede899f4c9e41b7a923550f59e07dc307499712f

4ccf9337701752fc5d11c5d4f2dc2bd75470df08

/genGcode/genGcode_simplify.py

d616e484659cfb4e4ed4639f1ddd1e1af1814660

[]

no_license

MartianSheep/Elevate_Gcode

433ca82c3dc9986ba85a9023810f5b2099f9ef10

2cea1ed402b71aef52f69c933f88815eb47347a7

refs/heads/master

2022-11-26T07:22:19.448073

2020-08-04T19:55:01

278,013,874

0

1

null

UTF-8

Python

false

3,718

py

import matplotlib.pyplot as plt import matplotlib.image as mpimg from PIL import Image from PIL import ImageFilter import numpy as np import potrace class Piture(): def __init__(self,filepath): self.img=mpimg.imread(filepath) self.h,self.w,self.c=self.img.shape self.pre=self.img self.gcode=['G28'] self.x_max=40 self.y_max=40 #----------------------convert to gray scale---------------------------- def gray_scale(self): print('RBG to gray scale...') gray = np.ones(self.img.shape) # new array for gray scale for i in range(self.h): for j in range(self.w): Y = (0.3*self.img[i,j,0]+0.59*self.img[i,j,1]+0.11*self.img[i,j,2])/255 # print(Y) gray[i,j]=np.array([Y,Y,Y]) self.pre=np.abs(gray-1) return gray #----------------------------------------------------------------------- #-----------------------Show the image on the screen--------------------------- def show(self): plt.imshow(self.pre) plt.axis('off') plt.show() #------------------------------------------------------------------------ #-----------------------Save the image--------------------------- def saveImg(self, output): plt.imshow(self.pre) plt.axis('off') plt.imsave(output + '.jpg', self.pre) print('Save ' + output + '.jpg') #------------------------------------------------------------------------ #-----------------------Generate Gcode--------------------------- def gen_gcode(self): print('generate gcode...') # bmp=potrace.Bitmap(self.pre[:,:]) # binary fill bmp=potrace.Bitmap(self.pre[:,:,0]) path=bmp.trace() flag = 0 for curve in path: ratio=self.x_max/max(self.w,self.h) #normalize for drawing machine self.gcode.append('M280 P0 S60') #抬筆 self.gcode.append('G0 X%.4f Y%.4f'%(curve.start_point[0]*ratio,curve.start_point[1]*ratio)) #移動到起始點 self.gcode.append('M280 P0 S0') #下筆 for segment in curve: # print(segment) if segment.is_corner: self.gcode.append('G1 X%.4f Y%.4f'%(segment.c[0]*ratio,segment.c[1]*ratio)) #畫至corner的轉角點 self.gcode.append('G1 X%.4f Y%.4f'%(segment.end_point[0]*ratio,segment.end_point[1]*ratio)) #畫至corner的終點 else: self.gcode.append('G1 X%.4f Y%.4f'%(segment.end_point[0]*ratio,segment.end_point[1]*ratio)) #畫至Bezier segment的終點 self.gcode.append('M280 P0 S60') #抬筆 return self.gcode #------------------------------------------------------------------------ #-----------------------Save Gcode--------------------------- def save_gcode(self): with open('output.txt','w') as f: for i in range(len(self.gcode)): f.write('%s\n'%self.gcode[i]) #-------------------------------------------------------------------- #---------------------------convert to binary image--------------------- def binary_image(self,threshold): print('converting to binary image...') self.pre[self.pre[:,:,0]>threshold] = np.array([1,1,1]) self.pre[self.pre[:,:,0]<=threshold] = np.array([0,0,0]) return self.pre #----------------------------------------------------------------------------- if __name__=='__main__': pic=Piture('img/bear.jpg') #輸入圖片的路徑 pic.gray_scale() pic.binary_image(0.75) pic.show() gcode=pic.gen_gcode() pic.save_gcode()

[ "mkmarsscience@gmail.com" ]

mkmarsscience@gmail.com

5176aef0089034410f44ffccfc4da3c492c73b89

9b8502767061c6ff1fafd62e22846a4e45780013

/locallibrary/catalog/admin.py

815e9d6073efd31df8a17417134e74c705b7ea2a

[]

no_license

zacharywendholt/personalWebsite

c5fe557f584322ca6940c96f0b95614075eb2727

d89ea60be4831e3f35e1d7efb2ae1fe7818bbeb5

refs/heads/master

2022-12-13T04:00:55.155513

2020-08-24T23:38:49

276,281,741

0

null

UTF-8

Python

false

765

py

from django.contrib import admin from .models import Author, Genre, Book, BookInstance # Register your models here. #admin.site.register(Book) class AuthorAdmin(admin.ModelAdmin): list_display = ('last_name', 'first_name', 'date_of_birth', 'date_of_death') fields = ['first_name', 'last_name', ('date_of_birth', 'date_of_death')] # Register the Admin classes for Book using the decorator @admin.register(Book) class BookAdmin(admin.ModelAdmin): list_display = ('title', 'author', 'display_genre') # Register the Admin classes for BookInstance using the decorator @admin.register(BookInstance) class BookInstanceAdmin(admin.ModelAdmin): list_filter = ('status', 'due_back') admin.site.register(Author, AuthorAdmin) admin.site.register(Genre)

[ "zacharywendholt@gmail.com" ]

zacharywendholt@gmail.com

afd85d4c73844c5cc1c8b3f534416460df5955a4

f82757475ea13965581c2147ff57123b361c5d62

/gi-stubs/repository/GUPnPDLNA/ContainerInformationClass.py

25afb71d5c36d22089d5bb91466a302acde8d762

[]

no_license

ttys3/pygobject-stubs

9b15d1b473db06f47e5ffba5ad0a31d6d1becb57

d0e6e93399212aada4386d2ce80344eb9a31db48

refs/heads/master

2022-09-23T12:58:44.526554

2020-06-06T04:15:00

269,693,287

8

2

null

2020-06-05T15:57:54

null

UTF-8

Python

false

5,687

py

# encoding: utf-8 # module gi.repository.GUPnPDLNA # from /usr/lib64/girepository-1.0/GUPnPDLNA-2.0.typelib # by generator 1.147 """ An object which wraps an introspection typelib. This wrapping creates a python module like representation of the typelib using gi repository as a foundation. Accessing attributes of the module will dynamically pull them in and create wrappers for the members. These members are then cached on this introspection module. """ # imports import gi as __gi import gi.overrides.GObject as __gi_overrides_GObject import gobject as __gobject class ContainerInformationClass(__gi.Struct): """ :Constructors: :: ContainerInformationClass() """ def __delattr__(self, *args, **kwargs): # real signature unknown """ Implement delattr(self, name). """ pass def __dir__(self, *args, **kwargs): # real signature unknown """ Default dir() implementation. """ pass def __eq__(self, *args, **kwargs): # real signature unknown """ Return self==value. """ pass def __format__(self, *args, **kwargs): # real signature unknown """ Default object formatter. """ pass def __getattribute__(self, *args, **kwargs): # real signature unknown """ Return getattr(self, name). """ pass def __ge__(self, *args, **kwargs): # real signature unknown """ Return self>=value. """ pass def __gt__(self, *args, **kwargs): # real signature unknown """ Return self>value. """ pass def __hash__(self, *args, **kwargs): # real signature unknown """ Return hash(self). """ pass def __init_subclass__(self, *args, **kwargs): # real signature unknown """ This method is called when a class is subclassed. The default implementation does nothing. It may be overridden to extend subclasses. """ pass def __init__(self): # real signature unknown; restored from __doc__ pass def __le__(self, *args, **kwargs): # real signature unknown """ Return self<=value. """ pass def __lt__(self, *args, **kwargs): # real signature unknown """ Return self<value. """ pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass def __ne__(self, *args, **kwargs): # real signature unknown """ Return self!=value. """ pass def __reduce_ex__(self, *args, **kwargs): # real signature unknown """ Helper for pickle. """ pass def __reduce__(self, *args, **kwargs): # real signature unknown """ Helper for pickle. """ pass def __repr__(self, *args, **kwargs): # real signature unknown """ Return repr(self). """ pass def __setattr__(self, *args, **kwargs): # real signature unknown """ Implement setattr(self, name, value). """ pass def __sizeof__(self, *args, **kwargs): # real signature unknown """ Size of object in memory, in bytes. """ pass def __str__(self, *args, **kwargs): # real signature unknown """ Return str(self). """ pass def __subclasshook__(self, *args, **kwargs): # real signature unknown """ Abstract classes can override this to customize issubclass(). This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached). """ pass def __weakref__(self, *args, **kwargs): # real signature unknown pass get_mime = property(lambda self: object(), lambda self, v: None, lambda self: None) # default get_mpeg_version = property(lambda self: object(), lambda self, v: None, lambda self: None) # default get_packet_size = property(lambda self: object(), lambda self, v: None, lambda self: None) # default get_profile = property(lambda self: object(), lambda self, v: None, lambda self: None) # default get_variant = property(lambda self: object(), lambda self, v: None, lambda self: None) # default is_system_stream = property(lambda self: object(), lambda self, v: None, lambda self: None) # default parent_class = property(lambda self: object(), lambda self, v: None, lambda self: None) # default _reserved = property(lambda self: object(), lambda self, v: None, lambda self: None) # default __class__ = None # (!) real value is "<class 'gi.types.StructMeta'>" __dict__ = None # (!) real value is "mappingproxy({'__info__': StructInfo(ContainerInformationClass), '__module__': 'gi.repository.GUPnPDLNA', '__gtype__': <GType void (4)>, '__dict__': <attribute '__dict__' of 'ContainerInformationClass' objects>, '__weakref__': <attribute '__weakref__' of 'ContainerInformationClass' objects>, '__doc__': None, 'parent_class': <property object at 0x7f6784734680>, 'get_mpeg_version': <property object at 0x7f67847347c0>, 'get_packet_size': <property object at 0x7f6784734860>, 'get_profile': <property object at 0x7f6784734950>, 'is_system_stream': <property object at 0x7f6784734a90>, 'get_variant': <property object at 0x7f6784734b80>, 'get_mime': <property object at 0x7f6784734c70>, '_reserved': <property object at 0x7f6784734d60>})" __gtype__ = None # (!) real value is '<GType void (4)>' __info__ = StructInfo(ContainerInformationClass)

[ "ttys3@outlook.com" ]

ttys3@outlook.com

daff8e5c7182e4ea01be7a0621eb5665a0140644

ec37e0ad19acc36372171a17dccb4a95da38ac24

/TemaSI1/km_server/km.py

177c0da68c3bf39a543da58a68908a9f3b4ca2f4

[]

no_license

tuguimadalinaa/Homework1-SI

586ad876aae37c8acabf0af6c6835d7c6f34c1f7

58e631f7899902d4cf9f03a225161d23cae0898a

refs/heads/main

2023-01-04T04:31:45.635851

2020-11-03T07:53:21

306,423,718

0

null

UTF-8

Python

false

2,419

py

import socket import time import random import Crypto from Crypto.Cipher import AES from Crypto.Util.Padding import pad data_for_server = {'TCP_IP': '127.0.0.1', 'TCP_PORT': 3000, "BUFFER_SIZE": 1024} AES_data = {'K3': b'1234567891234568', 'iv': b'\xad\xbe\xf6\xc2\xb3p\x10I\xc6\x96 M\xb9\xa1\x96b'} mode = None KM = dict() KM["CBC_key"] = b'abcdabcdabcdabcd' KM["OFB_key"] = b'abcdabcdabcdabcd' KM["KEY_3"] = AES_data["K3"] print("Km server started") def get_encryption_type(): data = ["CBC", "OFB"] return random.choice(data) while 1: s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.bind((data_for_server["TCP_IP"], data_for_server['TCP_PORT'])) s.listen(1) conn, addr = s.accept() data = conn.recv(data_for_server["BUFFER_SIZE"]) data = data.decode() if not data: break print("Node KM received data: ", data) if data == "CBC": mode = "CBC" aes = AES.new(AES_data["K3"], AES.MODE_ECB) aes_key = aes.encrypt(pad(KM["CBC_key"], AES.block_size)) conn.send(aes_key) time.sleep(1) aes = AES.new(AES_data["K3"], AES.MODE_ECB) aes_iv = aes.encrypt(AES_data['iv']) conn.send(aes_iv) time.sleep(1) elif data == "OFB": mode = "OFB" aes = AES.new(AES_data["K3"], AES.MODE_ECB) aes_key = aes.encrypt(pad(KM["OFB_key"], AES.block_size)) conn.send(aes_key) time.sleep(1) print(AES_data['iv']) aes = AES.new(AES_data["K3"], AES.MODE_ECB) aes_iv = aes.encrypt(AES_data['iv']) conn.send(aes_iv) print(aes_iv) time.sleep(1) elif data == 'key_refresh': aes = AES.new(AES_data["K3"], AES.MODE_ECB) AES_data['iv'] = Crypto.Random.get_random_bytes(AES.block_size) aes_key = None if mode == "CBC": KM["CBC_key"] = Crypto.Random.get_random_bytes(AES.block_size) aes_key = aes.encrypt(pad(KM["CBC_key"], 16)) elif mode == "OFB": KM["OFB_key"] = Crypto.Random.get_random_bytes(AES.block_size) aes_key = aes.encrypt(pad(KM["OFB_key"], 16)) conn.send(aes_key) aes = AES.new(AES_data["K3"], AES.MODE_ECB) aes_iv = aes.encrypt(AES_data['iv']) conn.send(aes_iv) time.sleep(1) conn.send(get_encryption_type().encode()) else: conn.send("does not exist".encode()) conn.close()

[ "tuguimadalinaa@gmail.com" ]

tuguimadalinaa@gmail.com

ada482c584c8db533f2adf5cd8b8c477eff5ea8d

0109433801b0116f3e575324fee9b27d4f6e1506

/registrasi/migrations/0001_initial.py

1f7119cc0a2b92fe606fc167d5f85b400717b15b

[]

no_license

yaumil94/sahara-project

116255a544b044364ba3d86b8dcbd0a8656f2551

1c345d5e5f9b2ba39154c54abda243fa0bee3d79

refs/heads/master

2020-07-03T14:54:05.850495

2015-10-21T13:43:06

null

0

null

UTF-8

Python

false

1,824

py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import migrations, models from django.conf import settings import django.contrib.auth.models class Migration(migrations.Migration): dependencies = [ ('auth', '0006_require_contenttypes_0002'), ] operations = [ migrations.CreateModel( name='Member', fields=[ ('user_ptr', models.OneToOneField(to=settings.AUTH_USER_MODEL, auto_created=True, primary_key=True, serialize=False, parent_link=True)), ], options={ 'abstract': False, 'verbose_name': 'user', 'verbose_name_plural': 'users', }, bases=('auth.user',), managers=[ ('objects', django.contrib.auth.models.UserManager()), ], ), migrations.CreateModel( name='Paket', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('nama', models.CharField(max_length=30)), ('harga', models.IntegerField()), ], ), migrations.CreateModel( name='Pembayaran', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('jenis', models.CharField(max_length=30)), ], ), migrations.AddField( model_name='member', name='paket', field=models.ForeignKey(to='registrasi.Paket'), ), migrations.AddField( model_name='member', name='pembayaran', field=models.ForeignKey(to='registrasi.Pembayaran'), ), ]

[ "yanwarsolahudinn@gmail.com" ]

yanwarsolahudinn@gmail.com

b654b39431cf208a9c81a1924cb0e9b756bf502f

ea0296b94a4b319f0ea1f99045a03cf5230ceb20

/blog/views.py

dc2aeaed69e0f812db471d943a11021242fe7df7

[]

no_license

nejilabs/CS-PythonDjangoTutorial-BlogSocialMediaWebApp-20190218

d7a682ca63da7c4889e514e92b59a2f96a95fc90

5e2172fbc5a86a24efe60140919f4a75ff83a6ec

refs/heads/master

2023-05-08T23:28:50.650198

2021-05-04T07:13:46

278,018,076

0

1

null

UTF-8

Python

false

1,877

py

from django.shortcuts import render, get_object_or_404 from django.contrib.auth.mixins import LoginRequiredMixin, UserPassesTestMixin from django.contrib.auth.models import User from django.views.generic import ( CreateView, DetailView, ListView, UpdateView, DeleteView ) from .models import Post def about(request): return render(request,'blog/about.html', {'title': 'About'}) class PostListView(ListView): model = Post template_name = 'blog/home.html' context_object_name = 'posts' ordering = ['-date_posted'] paginate_by = 5 class UserPostListView(ListView): model = Post template_name = 'blog/user_posts.html' context_object_name = 'posts' ordering = ['-date_posted'] paginate_by = 5 def get_queryset(self): user = get_object_or_404(User, username=self.kwargs.get('username')) return Post.objects.filter(author=user).order_by('-date_posted') class PostDetailView(DetailView): model = Post class PostCreateView(LoginRequiredMixin,CreateView): model = Post fields = ['title','content'] def form_valid(self,form): form.instance.author = self.request.user return super().form_valid(form) class PostUpdateView(LoginRequiredMixin,UserPassesTestMixin,UpdateView): model = Post fields = ['title','content'] def form_valid(self,form): form.instance.author = self.request.user return super().form_valid(form) def test_func(self): post = self.get_object() if self.request.user == post.author: return True return False class PostDeleteView(LoginRequiredMixin,UserPassesTestMixin,DeleteView): model = Post success_url = "/" def test_func(self): post = self.get_object() if self.request.user == post.author: return True return False

[ "nelsonalbajr@yahoo.com" ]

nelsonalbajr@yahoo.com

f455c273b1a7d058a7b6728157bc044a61a2736a

31b787404e5a9a304d312a2f7b52b64062a5391c

/Twitter -SA - GUI/scrapper.py

a9d58503bcab10cc209f674bfab45bae1735b98c

[ "MIT" ]

permissive

jeev20/Twitter-Sentiment-Analyzer-GUI

7039504640425f809b91237a4a3b7abbcd34e803

9d09c53ccde3c38fd94a3fe0834087532dbff127

refs/heads/master

2021-01-12T02:08:40.287749

2017-01-09T23:17:50

78,477,945

0

null

UTF-8

Python

false

1,322

py

# This program scraps twitter pages for tweets. Is written by jeev20. https://github.com/jeev20 from bs4 import BeautifulSoup from urllib import * import urllib from textblob import TextBlob import sys import time import webbrowser # open a public URL, in this case, the webbrowser url1 = "https://twitter.com/twitter" webbrowser.open_new_tab(url1) time.sleep(3) # user can input twitter account url = raw_input("Please paste link to twitter account : ") #input webaddress of the twitter account webadd = urllib.urlopen(url).read() soup = BeautifulSoup(webadd, "html.parser") #tweet title extraction def title(): return(soup.title.text) # function to return latest tweet def getText(): for tweets in soup.find_all('div',{"class": "content"}): twe = (tweets.find('p').text) return twe def time(): for tweets in soup.find_all('a',class_="tweet-timestamp js-permalink js-nav js-tooltip"): time = (tweets.get_text()) return time # function returning sentiment analysis value for the tweet def getTextsa(): twe = getText() test = TextBlob(twe) sa = (test.sentiment.polarity) return sa #used for debugging #prints the tweet and the sentiment analysis value print title() print "" print getText() print "" print time() print "" print "Sentiment Value is: ",float ("%.4f" %(getTextsa()))

[ "noreply@github.com" ]

jeev20.noreply@github.com

efb1bf096c32547eaf7c902ddf61205cf9be740d

6c10c6e229014dc3bf14efaec2ea8bf07c406752

/AILearning/MordernCNN/ConvolutionNetWork.py

83f2f779f1bcb1de50e984c7b9e062ded4e76acc

[]

no_license

GuyRobot/AIPythonExamples

e59c6edb355d9cadee2b3f19a087b1b656956262

4acdd0d4966e31a616910554bc075b641aa152df

refs/heads/master

2021-05-21T13:05:49.615593

2021-02-28T06:41:04

252,662,467

0

null

UTF-8

Python

false

1,120

py

from mxnet import gluon, nd, autograd from mxnet.gluon import nn def corr2D(X, K): h, w = K.shape Y = nd.zeros(shape=(X.shape[0] - h + 1, X.shape[1] - w + 1)) for i in range(Y.shape[0]): for j in range(Y.shape[1]): Y[i, j] = (X[i: i + h, j: j + w] * K).sum() return Y class Conv2D(nn.Block): def __init__(self, kernel_size, **kwargs): super(Conv2D, self).__init__(**kwargs) self.weights = self.params.get('weight', shape=kernel_size) self.bias = self.params.get('bias', shpae=(1, )) def forward(self, x): return corr2D(x, self.weights.data()) + self.bias.data() X = nd.ones((6, 8)) X[:, 2:6] = 0 K = nd.array([[-1, 1]]) Y = corr2D(X, K) conv2D = nn.Conv2D(1, (1, 2)) conv2D.initialize() X = X.reshape(1, 1, 6, 8) Y = Y.reshape(1, 1, 6, 7) for i in range(10): with autograd.record(): Y_hat = conv2D(X) l = (Y_hat - Y) ** 2 l.backward() conv2D.weight.data()[:] -= 3e-2 * conv2D.weight.grad() if (i + 1) % 2: print('batch %d, loss %f' % (i + 1, l.sum().asscalar())) print(conv2D.weight.data())

[ "bluexker@gmail.com" ]

bluexker@gmail.com

be4ba18a225607317de5d0b373b6c5e85b83b162

2599d93919a1cfd9a030e862d10e40e52d287655

/project_management_portal/views/create_project/tests/snapshots/snap_test_case_01.py

c2c7bf3322f211dea9c961f7b81ee250cf430987

[]

no_license

chandramoulidupam/my_projects

a6730c44ed2ba7a055d13415067b28ca74f0134b

111d7753e2cf867d51681ed41a7ea917deb9aecd

refs/heads/master

2023-09-02T03:38:59.753682

2020-06-01T06:20:48

267,607,764

0

null

2021-11-15T17:51:30

2020-05-28T14:11:11

Python

UTF-8

Python

false

836

py

# -*- coding: utf-8 -*- # snapshottest: v1 - https://goo.gl/zC4yUc from __future__ import unicode_literals from snapshottest import Snapshot snapshots = Snapshot() snapshots['TestCase01CreateProjectAPITestCase::test_case status'] = 400 snapshots['TestCase01CreateProjectAPITestCase::test_case body'] = { 'workflow_type': [ 'This field is required.' ] } snapshots['TestCase01CreateProjectAPITestCase::test_case header_params'] = { 'content-language': [ 'Content-Language', 'en' ], 'content-length': [ '45', 'Content-Length' ], 'content-type': [ 'Content-Type', 'application/json' ], 'vary': [ 'Accept-Language, Origin, Cookie', 'Vary' ], 'x-frame-options': [ 'SAMEORIGIN', 'X-Frame-Options' ] }

[ "chandramoulidupam@gmail.com" ]

chandramoulidupam@gmail.com

9965a2e865fabcba1dbc84d7eaf8219df5ed28ea

09fd2a42a931e3e094af9fc5ec6eb57dc9d42660

/addismap/manage.py

eca96ee0af49c88befcfe25f7689118434a9746b

[]

no_license

yohannes15/AddisMap

78df24404b1934f5327297efe13f220485f76de5

3bcafccd985e92cd1d894b9535c747bf4c42fd4c

refs/heads/master

2022-11-24T18:01:53.027070

2020-08-03T22:46:10

271,413,519

4

0

null

UTF-8

Python

false

628

py

#!/usr/bin/env python """Django's command-line utility for administrative tasks.""" import os import sys def main(): os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'addismap.settings') try: from django.core.management import execute_from_command_line except ImportError as exc: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) from exc execute_from_command_line(sys.argv) if __name__ == '__main__': main()

[ "y.berhane56@gmail.com" ]

y.berhane56@gmail.com

5d185b070693868eb2bcc94da19a530272dec5d9

d60ee49abaee6c74c5b777f8f112a7f75f71f029

/genome/cnvnator/stats/plot_both.py

b76affd22a535a2c3ce4b07527c8af45c714b6a6

[]

no_license

ak352/melanomics

41530f623b4bfdbd5c7b952debcb47622d1a8e88

fc5e6fdb1499616fb25a8dc05259add8a65aeca0

refs/heads/master

2020-12-24T16:14:42.271416

2015-08-06T12:48:52

18,439,919

0

null

UTF-8

Python

false

3,716

py

from pylab import * from matplotlib.backends.backend_pdf import PdfPages samples = [2,4,5,6,7,8] cnv_files = ["/work/projects/melanomics/analysis/genome/cnvnator/binSize100/patient_%d.cnv.list.NS.PM.tested" % k for k in samples] def get_cn(filename): bins_n = {} coverage_n = {} coverage_t = {} k = 0 for line in open(filename): k += 1 line = line[:-1].split("\t") loci = line[0:3] start,end = [int(x) for x in line[1:3]] if loci[0] not in bins_n: bins_n[loci[0]] = [] if loci[0] not in coverage_n: coverage_n[loci[0]] = [] coverage_t[loci[0]] = [] #Append x and y #bins_n[loci[0]].append(start-1) #coverage_n[loci[0]].append(2) bins_n[loci[0]].append(start) bins_n[loci[0]].append(end-1) rds = [float(x) for x in line[3:5]] for i,rd in enumerate(rds): if rds[i] > 5: rds[i] = 5 coverage_n[loci[0]].append(rd*2) coverage_n[loci[0]].append(rd*2) coverage_t[loci[0]].append(rd*2) coverage_t[loci[0]].append(rd*2) #bins_n[loci[0]].append(end) #coverage_n[loci[0]].append(2) return bins_n, coverage_n, coverage_t def get_lengths(): infile = "/work/projects/melanomics/data/NCBI/Homo_sapiens/NCBI/build37.2/Sequence/WholeGenomeFasta/genome.fa.fai" lengths = {} for line in open(infile): line = line[:-1].split("\t") lengths["chr"+line[0]] = int(line[1]) return lengths if __name__ == "__main__": colors = ["r", "g", "b", "magenta", "cyan", "orange"] for j,cnv_file in enumerate(cnv_files): figure(figsize=(22,20)) bins_n, coverage_n, coverage_t = get_cn(cnv_file) chroms = [] for x in range(1,23): chroms.append("chr"+str(x)) chroms.extend(["chrX", "chrY", "chrMT"]) length = get_lengths() k = 1 for chrom in chroms: subplot(5,5,k) # print len(bins_n[chrom]), len(coverage_n[chrom]), len(coverage_t[chrom]) ratio = [float(x[1])/float(x[0]+0.000001) for x in zip(coverage_n[chrom], coverage_t[chrom])] # bins = [] # nratio = [] # for i,x in enumerate(ratio): # if x < 0.5 or x > 1.5: # bins.append(bins_n[chrom][i]) # nratio.append(x) # for m in range(0,len(bins),2): # plot(bins[m:m+2], nratio[m:m+2], color=colors[j], label="patient_%d" % samples[j]) # scatter(bins_n[chrom], ratio, color='r', s=2, label="tumor/normal ratio") plot(bins_n[chrom], ratio, color='r', lw=3, label="tumor/normal ratio") #scatter(bins_n[chrom], coverage_t[chrom], color='r', s=2, label="tumor") if k==25: legend() #plot(bins_n[chrom], coverage_n[chrom], color='b') #plot(bins_t[chrom], coverage_t[chrom], color='r') ylim([0,5]) xlim([0,length[chrom]]) title(chrom + "(patient_%d)" % samples[j]) print chrom #print chrom, bins_n[chrom] #print chrom, coverage_n[chrom] k+=1 outfile = "/work/projects/melanomics/analysis/genome/cnvnator/binSize100/graphs/patient_%d.cnv.pdf" % samples[j] savefig(outfile, \ bbox_inches = "tight") sys.stderr.write("Plots save at %s\n" % outfile) #plot(bins_n[chrom], coverage_n[chrom]) #scatter(bins_n["chr1"], coverage_n["chr1"]) #fig=gcf() #fig.set_size_inches(18.5,10.5) #fig.savefig('foo1.png',dpi=100) #show()

[ "ak@uni.fake" ]

ak@uni.fake

9a2c49f544049615b1e0f7cf64ee36d80f8a921a

7e16835a0a47c36bc12e9b0ca8990ab57304914e

/flask_security_bundle/views/security_controller.py

a250c08932fd067cb114cee5abfb2b45759c4b52

[ "MIT" ]

permissive

briancappello/flask-security-bundle

b3436152277d4e7886933cf026d8c2e843998c1c

d9b97a4408c2001a0d29f5c55a4540a4917abd24

refs/heads/master

2021-04-15T11:37:20.085204

2018-08-24T22:12:01

126,606,284

0

null

UTF-8

Python

false

11,647

py

from flask import current_app as app, request from flask_unchained import Controller, route, lazy_gettext as _ from flask_unchained import injectable from flask_unchained.bundles.sqlalchemy import SessionManager from http import HTTPStatus from werkzeug.datastructures import MultiDict from ..decorators import anonymous_user_required, auth_required from ..extensions import Security from ..services import SecurityService, SecurityUtilsService from ..utils import current_user class SecurityController(Controller): def __init__(self, security: Security = injectable, security_service: SecurityService = injectable, security_utils_service: SecurityUtilsService = injectable, session_manager: SessionManager = injectable): self.security = security self.security_service = security_service self.security_utils_service = security_utils_service self.session_manager = session_manager @route(only_if=False) @auth_required() def check_auth_token(self): """ View function to check a token, and if it's valid, log the user in. Disabled by default; must be explicitly enabled in your ``routes.py``. """ # the auth_required decorator verifies the token and sets current_user, # just need to return a success response return self.jsonify({'user': current_user}) @route(methods=['GET', 'POST']) @anonymous_user_required(msg='You are already logged in', category='success') def login(self): """ View function to log a user in. Supports html and json requests. """ form = self._get_form('SECURITY_LOGIN_FORM') if (form.validate_on_submit() and self.security_service.login_user(form.user, form.remember.data)): self.after_this_request(self._commit) if request.is_json: return self.jsonify({'token': form.user.get_auth_token(), 'user': form.user}) self.flash(_('flask_security_bundle.flash.login'), category='success') return self.redirect('SECURITY_POST_LOGIN_REDIRECT_ENDPOINT') elif form.errors: form = self.security_service.process_login_errors(form) if request.is_json: return self.jsonify({'error': form.errors.get('_error')[0]}, code=HTTPStatus.UNAUTHORIZED) return self.render('login', login_user_form=form, **self.security.run_ctx_processor('login')) @route() def logout(self): """ View function to log a user out. Supports html and json requests. """ if current_user.is_authenticated: self.security_service.logout_user() if request.is_json: return '', HTTPStatus.NO_CONTENT self.flash(_('flask_security_bundle.flash.logout'), category='success') return self.redirect('SECURITY_POST_LOGOUT_REDIRECT_ENDPOINT') @route(methods=['GET', 'POST'], only_if=lambda app: app.config.get('SECURITY_REGISTERABLE')) @anonymous_user_required def register(self): """ View function to register user. Supports html and json requests. """ form = self._get_form('SECURITY_REGISTER_FORM') if form.validate_on_submit(): user = self.security_service.user_manager.create(**form.to_dict()) self.security_service.register_user(user) return self.redirect('SECURITY_POST_REGISTER_REDIRECT_ENDPOINT') return self.render('register', register_user_form=form, **self.security.run_ctx_processor('register')) @route(methods=['GET', 'POST'], only_if=lambda app: app.config.get('SECURITY_CONFIRMABLE')) def send_confirmation_email(self): """ View function which sends confirmation token and instructions to a user. """ form = self._get_form('SECURITY_SEND_CONFIRMATION_FORM') if form.validate_on_submit(): self.security_service.send_email_confirmation_instructions(form.user) self.flash(_('flask_security_bundle.flash.confirmation_request', email=form.user.email), category='info') if request.is_json: return '', HTTPStatus.NO_CONTENT elif form.errors and request.is_json: return self.errors(form.errors) return self.render('send_confirmation_email', send_confirmation_form=form, **self.security.run_ctx_processor('send_confirmation_email')) @route('/confirm/<token>', only_if=lambda app: app.config.get('SECURITY_CONFIRMABLE')) def confirm_email(self, token): """ View function to confirm a user's token from the confirmation email send to them. Supports html and json requests. """ expired, invalid, user = \ self.security_utils_service.confirm_email_token_status(token) if not user or invalid: invalid = True self.flash(_('flask_security_bundle.flash.invalid_confirmation_token'), category='error') already_confirmed = user is not None and user.confirmed_at is not None if expired and not already_confirmed: self.security_service.send_email_confirmation_instructions(user) self.flash(_('flask_security_bundle.flash.confirmation_expired', email=user.email, within=app.config.get('SECURITY_CONFIRM_EMAIL_WITHIN')), category='error') if invalid or (expired and not already_confirmed): return self.redirect('SECURITY_CONFIRM_ERROR_REDIRECT_ENDPOINT', 'security_controller.send_confirmation_email') if self.security_service.confirm_user(user): self.after_this_request(self._commit) self.flash(_('flask_security_bundle.flash.email_confirmed'), category='success') else: self.flash(_('flask_security_bundle.flash.already_confirmed'), category='info') if user != current_user: self.security_service.logout_user() self.security_service.login_user(user) return self.redirect('SECURITY_POST_CONFIRM_REDIRECT_ENDPOINT', 'SECURITY_POST_LOGIN_REDIRECT_ENDPOINT') @route(methods=['GET', 'POST'], only_if=lambda app: app.config.get('SECURITY_RECOVERABLE')) @anonymous_user_required(msg='You are already logged in', category='success') def forgot_password(self): """ View function to request a password recovery email with a reset token. Supports html and json requests. """ form = self._get_form('SECURITY_FORGOT_PASSWORD_FORM') if form.validate_on_submit(): self.security_service.send_reset_password_instructions(form.user) self.flash(_('flask_security_bundle.flash.password_reset_request', email=form.user.email), category='info') if request.is_json: return '', HTTPStatus.NO_CONTENT elif form.errors and request.is_json: return self.errors(form.errors) return self.render('forgot_password', forgot_password_form=form, **self.security.run_ctx_processor('forgot_password')) @route('/reset-password/<string:token>', methods=['GET', 'POST'], only_if=lambda app: app.config.get('SECURITY_RECOVERABLE')) @anonymous_user_required def reset_password(self, token): """ View function verify a users reset password token from the email we sent to them. It also handles the form for them to set a new password. Supports html and json requests. """ expired, invalid, user = \ self.security_utils_service.reset_password_token_status(token) if invalid: self.flash(_('flask_security_bundle.flash.invalid_reset_password_token'), category='error') return self.redirect('SECURITY_INVALID_RESET_TOKEN_REDIRECT') elif expired: self.security_service.send_reset_password_instructions(user) self.flash(_('flask_security_bundle.flash.password_reset_expired', email=user.email, within=app.config.get('SECURITY_RESET_PASSWORD_WITHIN')), category='error') return self.redirect('SECURITY_EXPIRED_RESET_TOKEN_REDIRECT') spa_redirect = app.config.get('SECURITY_API_RESET_PASSWORD_HTTP_GET_REDIRECT') if request.method == 'GET' and spa_redirect: return self.redirect(spa_redirect, token=token, _external=True) form = self._get_form('SECURITY_RESET_PASSWORD_FORM') if form.validate_on_submit(): self.security_service.reset_password(user, form.password.data) self.security_service.login_user(user) self.after_this_request(self._commit) self.flash(_('flask_security_bundle.flash.password_reset'), category='success') if request.is_json: return self.jsonify({'token': user.get_auth_token(), 'user': user}) return self.redirect('SECURITY_POST_RESET_REDIRECT_ENDPOINT', 'SECURITY_POST_LOGIN_REDIRECT_ENDPOINT') elif form.errors and request.is_json: return self.errors(form.errors) return self.render('reset_password', reset_password_form=form, reset_password_token=token, **self.security.run_ctx_processor('reset_password')) @route(methods=['GET', 'POST'], only_if=lambda app: app.config.get('SECURITY_CHANGEABLE')) @auth_required def change_password(self): """ View function for a user to change their password. Supports html and json requests. """ form = self._get_form('SECURITY_CHANGE_PASSWORD_FORM') if form.validate_on_submit(): self.security_service.change_password( current_user._get_current_object(), form.new_password.data) self.after_this_request(self._commit) self.flash(_('flask_security_bundle.flash.password_change'), category='success') if request.is_json: return self.jsonify({'token': current_user.get_auth_token()}) return self.redirect('SECURITY_POST_CHANGE_REDIRECT_ENDPOINT', 'SECURITY_POST_LOGIN_REDIRECT_ENDPOINT') elif form.errors and request.is_json: return self.errors(form.errors) return self.render('change_password', change_password_form=form, **self.security.run_ctx_processor('change_password')) def _get_form(self, name): form_cls = app.config.get(name) if request.is_json: return form_cls(MultiDict(request.get_json())) return form_cls(request.form) def _commit(self, response=None): self.session_manager.commit() return response

[ "briancappello@gmail.com" ]

briancappello@gmail.com

e7ea88b1c6c9c2d142b0f97f9ca2d143d8f0be8a

f90d6eb8c815b26be1c839ed5bbe0c65f7079e65

/69.py

43e28bbb26cf587ba0d74e36a5923745b207c84c

[]

no_license

zhangxu0307/leetcode_solutions

0c2b76e838f60e48f392605166bd2b6725686740

c5779489b3e71a12008023d8776ca0f1c10321e0

refs/heads/master

2021-01-24T16:52:58.555076

2018-02-28T02:40:32

123,217,403

0

null

UTF-8

Python

false

468

py

class Solution(object): def mySqrt(self, x): """ :type x: int :rtype: int """ start = 1 end = x mid = 0 while start <= end: mid = (end + start)/2 if x/mid == mid: return mid elif x/mid > mid: start = mid+1 elif x/mid < mid: end = mid-1 return end x = 2 s = Solution() ans = s.mySqrt(x) print ans

[ "zhangxu0307@163.com" ]

zhangxu0307@163.com

d683a95ff6e6491370e8718e4a90b876a96cd363

b241363657adce376209818d6b0c158c23c73164

/crm/migrations/0002_airconditioning_environment_lamp.py

2166bd6c4a3626a5b8aa9f2ec938a2c9e3aef4d8

[]

no_license

hesllerhuller/django-sass

c93cf37bf49e5109668c79e4e4fa95c3870b4fe7

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refs/heads/main

2023-02-27T22:41:53.809489

2021-02-01T19:13:19

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# Generated by Django 3.1.5 on 2021-01-23 21:13 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('crm', '0001_initial'), ] operations = [ migrations.CreateModel( name='Environment', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=255)), ('local', models.CharField(max_length=255)), ('t_a', models.FloatField(blank=True)), ('t_t', models.FloatField(blank=True)), ('umd', models.FloatField(blank=True)), ('n_g', models.FloatField(blank=True)), ], ), migrations.CreateModel( name='Lamp', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('power', models.FloatField(default=0)), ('on_off', models.BooleanField(default=0)), ('environment', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='crm.environment')), ], ), migrations.CreateModel( name='AirConditioning', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('power', models.FloatField(default=0)), ('brand', models.CharField(max_length=255)), ('model', models.CharField(max_length=255)), ('on_off', models.BooleanField(default=0)), ('environment', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='crm.environment')), ], ), ]

[ "hesllerh@gmail.com" ]

hesllerh@gmail.com

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/core/jobs/transforms/validation/subtopic_validation_test.py

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oppia/oppia

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d16fdf23d790eafd63812bd7239532256e30a21d

refs/heads/develop

2023-09-04T07:50:13.661276

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2023-09-14T18:25:11

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# coding: utf-8 # # Copyright 2021 The Oppia Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS-IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Unit tests for jobs.transforms.subtopic_validation.""" from __future__ import annotations from core.jobs import job_test_utils from core.jobs.transforms.validation import subtopic_validation from core.jobs.types import base_validation_errors from core.platform import models import apache_beam as beam MYPY = False if MYPY: # pragma: no cover from mypy_imports import base_models from mypy_imports import subtopic_models (base_models, subtopic_models) = models.Registry.import_models( [models.Names.BASE_MODEL, models.Names.SUBTOPIC]) class ValidateSubtopicCommitCmdsSchemaTests(job_test_utils.PipelinedTestBase): def test_validate_change_domain_implemented(self) -> None: valid_commit_cmd_model = ( subtopic_models.SubtopicPageSnapshotMetadataModel( id='123', created_on=self.YEAR_AGO, last_updated=self.NOW, committer_id='committer_id', commit_type='delete', commit_cmds=[{ 'cmd': base_models.VersionedModel.CMD_DELETE_COMMIT}]) ) output = ( self.pipeline | beam.Create([valid_commit_cmd_model]) | beam.ParDo( subtopic_validation.ValidateSubtopicPageSnapshotMetadataModel()) ) self.assert_pcoll_equal(output, []) def test_subtopic_page_change_object_with_missing_cmd(self) -> None: invalid_commit_cmd_model = ( subtopic_models.SubtopicPageSnapshotMetadataModel( id='123', created_on=self.YEAR_AGO, last_updated=self.NOW, committer_id='committer_id', commit_type='delete', commit_cmds=[{'invalid': 'data'}]) ) output = ( self.pipeline | beam.Create([invalid_commit_cmd_model]) | beam.ParDo( subtopic_validation.ValidateSubtopicPageSnapshotMetadataModel()) ) self.assert_pcoll_equal( output, [ base_validation_errors.CommitCmdsValidateError( invalid_commit_cmd_model, {'invalid': 'data'}, 'Missing cmd key in change dict') ]) def test_subtopic_page_change_object_with_invalid_cmd(self) -> None: invalid_commit_cmd_model = ( subtopic_models.SubtopicPageSnapshotMetadataModel( id='123', created_on=self.YEAR_AGO, last_updated=self.NOW, committer_id='committer_id', commit_type='delete', commit_cmds=[{'cmd': 'invalid'}]) ) output = ( self.pipeline | beam.Create([invalid_commit_cmd_model]) | beam.ParDo( subtopic_validation.ValidateSubtopicPageSnapshotMetadataModel()) ) self.assert_pcoll_equal( output, [ base_validation_errors.CommitCmdsValidateError( invalid_commit_cmd_model, {'cmd': 'invalid'}, 'Command invalid is not allowed') ]) def test_subtopic_page_change_object_with_missing_attribute_in_cmd( self ) -> None: invalid_commit_cmd_model = ( subtopic_models.SubtopicPageSnapshotMetadataModel( id='123', created_on=self.YEAR_AGO, last_updated=self.NOW, committer_id='committer_id', commit_type='edit', commit_cmds=[{ 'cmd': 'update_subtopic_page_property', 'property_name': '<p>page_contents_html</p>', 'subtopic_id': 'subtopic_id' }]) ) output = ( self.pipeline | beam.Create([invalid_commit_cmd_model]) | beam.ParDo( subtopic_validation.ValidateSubtopicPageSnapshotMetadataModel()) ) self.assert_pcoll_equal( output, [ base_validation_errors.CommitCmdsValidateError( invalid_commit_cmd_model, { 'cmd': 'update_subtopic_page_property', 'property_name': '<p>page_contents_html</p>', 'subtopic_id': 'subtopic_id' }, 'The following required attributes are missing: ' 'new_value, old_value') ]) def test_subtopic_page_change_object_with_extra_attribute_in_cmd( self ) -> None: invalid_commit_cmd_model = ( subtopic_models.SubtopicPageSnapshotMetadataModel( id='123', created_on=self.YEAR_AGO, last_updated=self.NOW, committer_id='committer_id', commit_type='create', commit_cmds=[{ 'cmd': 'create_new', 'topic_id': 'topic_id', 'subtopic_id': 'subtopic_id', 'invalid': 'invalid' }]) ) output = ( self.pipeline | beam.Create([invalid_commit_cmd_model]) | beam.ParDo( subtopic_validation.ValidateSubtopicPageSnapshotMetadataModel()) ) self.assert_pcoll_equal( output, [ base_validation_errors.CommitCmdsValidateError( invalid_commit_cmd_model, { 'cmd': 'create_new', 'topic_id': 'topic_id', 'subtopic_id': 'subtopic_id', 'invalid': 'invalid' }, 'The following extra attributes are present: invalid') ]) def test_subtopic_page_change_object_with_invalid_subtopic_page_property( self ) -> None: invalid_commit_cmd_model = ( subtopic_models.SubtopicPageSnapshotMetadataModel( id='123', created_on=self.YEAR_AGO, last_updated=self.NOW, committer_id='committer_id', commit_type='edit', commit_cmds=[{ 'cmd': 'update_subtopic_page_property', 'subtopic_id': 'subtopic_id', 'property_name': 'invalid', 'old_value': 'old_value', 'new_value': 'new_value', }]) ) output = ( self.pipeline | beam.Create([invalid_commit_cmd_model]) | beam.ParDo( subtopic_validation.ValidateSubtopicPageSnapshotMetadataModel()) ) self.assert_pcoll_equal( output, [ base_validation_errors.CommitCmdsValidateError( invalid_commit_cmd_model, { 'cmd': 'update_subtopic_page_property', 'subtopic_id': 'subtopic_id', 'property_name': 'invalid', 'old_value': 'old_value', 'new_value': 'new_value', }, 'Value for property_name in cmd ' 'update_subtopic_page_property: invalid is not allowed') ]) class ValidateSubtopicPageCommitLogEntryModelTests( job_test_utils.PipelinedTestBase): def test_validate_subtopic_page_model(self) -> None: valid_commit_cmd_model = ( subtopic_models.SubtopicPageCommitLogEntryModel( id='subtopicpage_id123', created_on=self.YEAR_AGO, last_updated=self.NOW, commit_type='test-type', user_id='', subtopic_page_id='123', post_commit_status='private', commit_cmds=[{ 'cmd': base_models.VersionedModel.CMD_DELETE_COMMIT}]) ) output = ( self.pipeline | beam.Create([valid_commit_cmd_model]) | beam.ParDo( subtopic_validation.ValidateSubtopicPageCommitLogEntryModel()) ) self.assert_pcoll_equal(output, []) def test_raises_commit_cmd_none_error(self) -> None: invalid_commit_cmd_model = ( subtopic_models.SubtopicPageCommitLogEntryModel( id='model_id123', created_on=self.YEAR_AGO, last_updated=self.NOW, commit_type='test-type', user_id='', subtopic_page_id='123', post_commit_status='private', commit_cmds=[{ 'cmd': base_models.VersionedModel.CMD_DELETE_COMMIT}]) ) output = ( self.pipeline | beam.Create([invalid_commit_cmd_model]) | beam.ParDo( subtopic_validation.ValidateSubtopicPageCommitLogEntryModel( )) ) self.assert_pcoll_equal( output, [ base_validation_errors.CommitCmdsNoneError( invalid_commit_cmd_model) ])

[ "noreply@github.com" ]

oppia.noreply@github.com