diff --git "a/2786.jsonl" "b/2786.jsonl" new file mode 100644--- /dev/null +++ "b/2786.jsonl" @@ -0,0 +1,728 @@ +{"seq_id":"524176911","text":"from django.shortcuts import (\n render, redirect, reverse, HttpResponse, get_object_or_404)\nfrom django.contrib import messages\nfrom packages.models import Packages\n\n\ndef view_bag(request):\n \"\"\" A view to return the shopping bag page \"\"\"\n\n return render(request, 'bag/bag.html')\n\n\ndef add_to_bag(request, item_id):\n \"\"\" Add a quantity of the package to the shopping bag \"\"\"\n\n package = get_object_or_404(Packages, pk=item_id)\n quantity = int(request.POST.get('quantity'))\n redirect_url = request.POST.get('redirect_url')\n bag = request.session.get('bag', {})\n\n if item_id in list(bag.keys()):\n bag[item_id] += quantity\n messages.success(\n request, f'Updated {package.name} quantity to {bag[item_id]}')\n else:\n bag[item_id] = quantity\n messages.success(request, f'Added {package.name} to your bag')\n\n request.session['bag'] = bag\n return redirect(redirect_url)\n\n\ndef adjust_bag(request, item_id):\n \"\"\" Adjust the quantity of the package to new ammount the shopping bag \"\"\"\n\n package = get_object_or_404(Packages, pk=item_id)\n quantity = int(request.POST.get('quantity'))\n bag = request.session.get('bag', {})\n\n if quantity > 0:\n bag[item_id] = quantity\n messages.success(\n request, f'Updated {package.name} quantity to {bag[item_id]}')\n else:\n bag.pop(item_id)\n messages.success(request, f'Removed {package.name} from your bag')\n\n request.session['bag'] = bag\n return redirect(reverse('view_bag'))\n\n\ndef remove_from_bag(request, item_id):\n \"\"\"Remove the item from the shopping bag\"\"\"\n try:\n package = get_object_or_404(Packages, pk=item_id)\n bag = request.session.get('bag', {})\n bag.pop(item_id)\n messages.success(request, f'Removed {package.name} from your bag')\n request.session['bag'] = bag\n return HttpResponse(status=200)\n\n except Exception as e:\n messages.error(request, f'Error removing item: {e}')\n return HttpResponse(status=500)\n","sub_path":"bag/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":2042,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"35283487","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n# author: Alexey Koshevoy\n\nfrom flask import Flask\nfrom flask import render_template, request\nfrom search import search\n\napp = Flask(__name__)\n\n\n@app.route('/')\ndef index():\n if request.args:\n mode = request.args['search_mode']\n req = request.args['search_for']\n try:\n num = int(request.args['hwmch'])\n except:\n num = 10\n options = {'ii': 'Обратный индекс', 'w2v': 'Word2Vec'}\n results = search(query=req, search_method=mode, number=num+1)\n\n return render_template('results.html', list=results,\n req=req,\n mode=options[mode])\n\n return render_template('index.html')\n\n\nif __name__ == '__main__':\n app.run(debug=True)","sub_path":"IS_project /main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":847,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"147394609","text":"import logging\nimport re\nimport tweepy\nimport random\nimport time\nfrom datetime import date, datetime, timedelta\n\nfrom django.db import IntegrityError\nfrom requests.exceptions import HTTPError\n\nfrom twitterbot.models import (\n BlackList,\n TargetTwitterAccount,\n TwitterFollower,\n VerifiedUserWithTag,\n WhiteListTwitterUser,\n AccountOwner\n)\nfrom utils.common import (\n load_function, connect_to_twitter_api,\n send_message_to_slack, send_message_to_telegram\n)\n\nlogging.basicConfig(level=logging.INFO)\nlogger = logging.getLogger(__name__)\n\nT_MIN = 60\nT_MAX = 120\nLIKES = 10\n\n\ndef get_count_of_followers_and_following(api):\n data = api.me()\n return data.followers_count, data.friends_count\n\n\ndef make_follow_for_current_account(account):\n \"\"\"Follow twitter accounts for current account owner\"\"\"\n logger.info('Start follow for {}'.format(account.screen_name))\n api = connect_to_twitter_api(account)\n before_stat = get_count_of_followers_and_following(api)\n _follow_target_accounts(account, api)\n stats = get_count_of_followers_and_following(api)\n text = (\"Finished following. Account: {}. Number of followers: {}.\"\n \" We're following {}. Following before task: {}. Date: {}.\"\n .format(account.screen_name, *stats, before_stat[1], date.today()))\n send_message_to_slack(text)\n send_message_to_telegram(text, account)\n logger.info(text)\n\n\ndef _follow_target_accounts(account, api):\n \"\"\"Follow target twitter accounts of current twitter account owner\"\"\"\n limit = random.randrange(account.followers_limit - 10,\n account.followers_limit)\n logger.info(\"The limit of followers is set to %s\", limit)\n target_accounts = TargetTwitterAccount.objects.filter(\n is_follower=False, account_owner=account,\n followers_count__gt=account.target_account_followers_count)\n counter = 0\n delete_target_accounts = []\n for user in target_accounts:\n try:\n tw_user = api.get_user(user.user_id)\n except tweepy.error.TweepError as err:\n if err.api_code == 50 or err.api_code == 63:\n logger.info(\"User {} not found or suspended!\".format(\n user.name))\n delete_target_accounts.append(user.user_id)\n BlackList.objects.get_or_create(user_id=user.user_id,\n reason=\"Not found/Suspended\",\n account_owner=account)\n continue\n else:\n raise err\n\n if account.keywords:\n keyword_descr = _description_consist_keywords(account, tw_user)\n if not keyword_descr:\n delete_target_accounts.append(user.user_id)\n continue\n if tw_user and tw_user.followers_count > (\n account.target_account_followers_count):\n time.sleep(random.randrange(T_MIN, T_MAX))\n try:\n api.create_friendship(tw_user.id)\n except tweepy.error.TweepError as err:\n if err.api_code in [158, 160]:\n logger.info(err.args[0][0]['message'])\n user.is_follower = True\n user.save(update_fields=('is_follower',))\n continue\n else:\n raise err\n try:\n _like_user_tweets(api, tw_user)\n except tweepy.error.TweepError as err:\n logger.info(err)\n continue\n\n logger.info(\"Follow %s\", user)\n user.is_follower = True\n user.save(update_fields=('is_follower',))\n counter += 1\n else:\n delete_target_accounts.append(user.user_id)\n continue\n\n if counter == limit:\n logger.info(\"The limit of %s followings is reached\", limit)\n break\n TargetTwitterAccount.objects.filter(\n user_id__in=delete_target_accounts, account_owner=account\n ).delete()\n\n\ndef _description_consist_keywords(account, tw_user):\n \"\"\"Search keywords in twitter description\"\"\"\n keyword_descr = any(\n re.search('(^|\\W){}($|\\W)'.format(keyword),\n tw_user.description.lower(), re.IGNORECASE)\n for keyword in account.keywords\n )\n return keyword_descr\n\n\ndef _like_user_tweets(api, tw_user):\n \"\"\"Like tw_user's tweets that have likes more or equal LIKES_COUNT\"\"\"\n likes_limit = random.randrange(1, 4)\n liked_tweets = 0\n tweets = tw_user.timeline()[:10] # get 10 latest tweets\n for t in tweets:\n try:\n if (t.favorite_count >= LIKES and not t.in_reply_to_status_id) or (\n t.retweeted_status.favorite_count >= LIKES):\n api.create_favorite(t.id)\n liked_tweets += 1\n except tweepy.error.TweepError as err:\n logger.info(err.args[0][0]['message'])\n continue\n except AttributeError:\n continue\n if liked_tweets == likes_limit:\n break\n\n\ndef retweet():\n accounts = AccountOwner.objects.filter(is_active=True,\n retweet_func__isnull=False)\n for account in accounts:\n make_retweet = load_function(account.retweet_func)\n logger.info('Start retweeting for {}'.format(account))\n make_retweet(account)\n logger.info('Finish retweeting for {}'.format(account))\n\n\ndef retweet_verified_users_with_tag(user):\n api = connect_to_twitter_api(user)\n\n # get random verified user from our DB\n ids_list = VerifiedUserWithTag.objects.filter(\n account_owner=user\n ).values_list('id', flat=True)\n ver_user = VerifiedUserWithTag.objects.get(\n id=random.choice(ids_list), account_owner=user)\n\n # get recent 20 tweets for current user\n recent_tweets = api.user_timeline(ver_user.screen_name)\n\n if ver_user and ver_user.tags:\n tag = '#{}'.format(random.choice(ver_user.tags))\n else:\n tag = ''\n\n for tweet in recent_tweets:\n tw_text = tweet.text.lower()\n\n if tag in tw_text and not tweet.in_reply_to_status_id and (\n tweet.lang == 'en' and not tweet.in_reply_to_user_id):\n\n try:\n api.retweet(tweet.id)\n except tweepy.error.TweepError as err:\n if err.api_code == 327 or err.api_code == 185:\n logger.info(err.args[0][0]['message'])\n continue\n msg = 'New retweet for {}. Date: {}'.format(user, date.today())\n send_message_to_slack(msg)\n return\n\n\ndef retweet_verified_users(user):\n api = connect_to_twitter_api(user)\n max_retweets = _get_tweets_to_retweet(api)\n last_five_days_tweets = _get_retweeted_screen_names(api)\n\n for tweet in max_retweets:\n logger.info('Try to retweet tweet {} of {}'.format(\n tweet.id, tweet.user.screen_name))\n if tweet.user.screen_name not in last_five_days_tweets:\n try:\n api.retweet(tweet.id)\n except tweepy.error.TweepError as err:\n if err.api_code == 327 or err.api_code == 185:\n logger.info(err.args[0][0]['message'])\n continue\n msg = 'New retweet! Date: {}\\ntwitter.com/{}/status/{}'.format(\n datetime.today().date(), tweet.user.screen_name, tweet.id)\n send_message_to_slack(msg)\n send_message_to_telegram(msg, user, False)\n return\n\n\ndef _get_retweeted_screen_names(api):\n \"\"\"Return list of screen names of the already retweeted tweets\n for the last 5 days\"\"\"\n twitter_posts = api.me().timeline()\n last_five_days = datetime.today() - timedelta(days=5)\n last_five_days_tweets = [\n x.retweeted_status.user.screen_name for x in twitter_posts\n if x.created_at > last_five_days and x.retweeted is True\n ]\n return last_five_days_tweets\n\n\ndef _get_tweets_to_retweet(api):\n \"\"\"Return sorted list of verified users tweets for the last day\"\"\"\n ver_users = VerifiedUserWithTag.objects.filter(\n account_owner__screen_name=api.me().screen_name\n )\n tweets_to_retweet = []\n last_tweet = datetime.today() - timedelta(days=1)\n for ver_user in ver_users:\n time.sleep(random.randrange(T_MIN, T_MAX))\n recent_tweets = api.user_timeline(ver_user.screen_name,\n exclude_replies=True,\n count=100)\n for tweet in recent_tweets:\n if tweet.created_at < last_tweet:\n break\n if 5 < tweet.retweet_count < 30 and tweet.lang == 'en':\n try:\n tweet.retweeted_status\n except AttributeError:\n tweets_to_retweet.append(tweet)\n max_retweeted_tweets = sorted(tweets_to_retweet,\n key=lambda tw: tw.retweet_count,\n reverse=True)\n return max_retweeted_tweets\n\n\ndef make_unfollow_for_current_account(account):\n \"\"\"Unfollow twitter accounts for current account owner\"\"\"\n logger.info('Start unfollow for {}'.format(account.screen_name))\n api = connect_to_twitter_api(account)\n following = api.me().friends_count\n _unfollow_accounts_not_followers(account, api)\n stats = get_count_of_followers_and_following(api)\n text = (\"Finished unfollowing. Account: {}. Number of followers: {}.\"\n \" We're following {}. Following before task: {}. Date: {}.\"\n .format(account.screen_name, *stats, following, date.today()))\n send_message_to_slack(text)\n send_message_to_telegram(text, account)\n logger.info(text)\n\n\ndef _unfollow_accounts_not_followers(account, api):\n \"\"\"Unfollow accounts that are not following account owner\"\"\"\n limit = random.randrange(account.followers_limit - 10,\n account.followers_limit)\n logger.info(\"The limit of unfollowing is set to %s\", limit)\n count = 0\n not_in_followers = _get_following_list(account, api)\n for friend in reversed(not_in_followers):\n try:\n api.destroy_friendship(friend)\n time.sleep(random.randrange(T_MIN, T_MAX))\n user = api.get_user(friend)\n friendship = api.show_friendship(user.id, user.screen_name,\n api.me().id,\n api.me().screen_name)[0]\n except tweepy.error.TweepError as err:\n if err.api_code == 50 or err.api_code == 63:\n logger.info(err.args[0][0]['message'])\n continue\n else:\n raise err\n\n if friendship and not friendship.followed_by:\n logger.info(\"Unfollow {}\".format(friend))\n try:\n BlackList.objects.create(user_id=friend, account_owner=account)\n TwitterFollower.objects.filter(\n user_id=friend, account_owner=account).delete()\n except IntegrityError:\n logger.exception('Integrity Error during unfollowing')\n continue\n\n count += 1\n if count == limit:\n break\n\n\ndef _get_following_list(account, api):\n \"\"\"Return the list of accounts ids that are followed by acc owner\n but not following current acc owner\"\"\"\n followers_list = api.followers_ids()\n friends_list = api.friends_ids()\n in_white_list = WhiteListTwitterUser.objects.filter(\n account_owner=account).values_list('user_id', flat=True)\n not_in_followers = [acc_id for acc_id in friends_list\n if acc_id not in followers_list\n and str(acc_id) not in in_white_list]\n return not_in_followers\n\n\ndef follow():\n accounts = AccountOwner.objects.filter(is_active=True)\n for account in accounts:\n try:\n make_follow_for_current_account(account)\n if account.follow_all_followers:\n follow_all_own_followers(account)\n except HTTPError:\n logger.exception('Something gone wrong')\n except tweepy.error.TweepError as err:\n message = err.args[0][0]['message']\n logger.info(message)\n if err.api_code in [89, 161, 226, 326]:\n send_message_to_slack(message)\n send_message_to_telegram(message, account, mode='HTML')\n else:\n logger.exception(err)\n raise err\n except Exception as err:\n logger.exception(err)\n raise err\n\n\ndef unfollow():\n accounts = AccountOwner.objects.filter(is_active=True)\n for account in accounts:\n try:\n make_unfollow_for_current_account(account)\n except HTTPError:\n logger.exception('Something gone wrong')\n except tweepy.error.TweepError as err:\n message = err.args[0][0]['message']\n logger.info(message)\n if err.api_code in [89, 226, 326]:\n send_message_to_slack(message)\n send_message_to_telegram(message, account)\n else:\n logger.exception(err)\n raise err\n except Exception as err:\n logger.exception(err)\n raise err\n\n\ndef follow_all_own_followers(account):\n logger.info('Start follow own followers for {}'.format(\n account.screen_name)\n )\n api = connect_to_twitter_api(account)\n count = _follow_followers(api)\n text = \"Account: {}. Follow {} own followers.\" \\\n \" Date: {}\".format(account.screen_name, count, date.today())\n send_message_to_slack(text)\n send_message_to_telegram(text, account)\n logger.info('Finish follow own followers for {}'.format(\n account.screen_name)\n )\n\n\ndef _follow_followers(api):\n \"\"\"Follow twitter accounts that follow current twitter account owner\"\"\"\n count = 0\n not_in_friends = _get_followers_list(api)\n for follower in not_in_friends:\n time.sleep(random.randrange(T_MIN, T_MAX))\n try:\n api.create_friendship(follower)\n except tweepy.error.TweepError as err:\n if err.api_code == 50 or err.api_code == 63:\n logger.info(err.args[0][0]['message'])\n continue\n else:\n raise err\n logger.info(\"Follow %s\", follower)\n count += 1\n return count\n\n\ndef _get_followers_list(api):\n \"\"\"Return list of accounts ids that are following current acc owner but\n not followed by acc owner\"\"\"\n followers_list = api.followers_ids()\n friends_list = api.friends_ids()\n not_in_friends = [x for x in followers_list if x not in friends_list]\n return not_in_friends\n","sub_path":"utils/twitterbot.py","file_name":"twitterbot.py","file_ext":"py","file_size_in_byte":14791,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"223124067","text":"\n\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nfrom FillMissing import custom_fillna, create_ordinals\n\n\nROOT_DIR = '/home/leonard/Desktop/Workspace/Kaggle/HousingPrices'\n\ndef make_hist(data, target, col_name, show=False):\n fig, ax1 = plt.subplots()\n ax1.set_title(col_name)\n ax1.hist(data)\n\n hist, bin_edges = np.histogram(data)\n binned_target = []\n bin_middles = []\n for i in range(len(bin_edges) - 1):\n bin_low = bin_edges[i]\n bin_high = bin_edges[i + 1]\n bin_middles.append((bin_low + bin_high) / 2)\n bin_mask = np.logical_and(data > bin_low, data < bin_high)\n binned_target.append( np.mean(target[bin_mask]) )\n\n ax2 = ax1.twinx()\n ax2.scatter(bin_middles, binned_target, marker='s', s=128, color='red')\n plt.savefig('{}/plots/histograms/{}_hist.png'.format(ROOT_DIR, col_name))\n if show:\n plt.show()\n plt.close()\n\n\ndef make_categorical_hist(data, target, col_name, show=False):\n unique_vals = np.unique(data)\n count_dict = {uval: (col_data == uval).sum() for uval in unique_vals}\n keys = []\n counts = []\n target_vals = []\n for key in count_dict:\n keys.append(key)\n counts.append(count_dict[key])\n\n key_mask = (data == key)\n target_vals.append(np.mean(target[key_mask]))\n\n fig, ax1 = plt.subplots()\n ax1.set_title(col_name)\n ax1.bar(keys, counts)\n ax2 = ax1.twinx()\n ax2.scatter(keys, target_vals, marker='s', s=128, color='red')\n plt.savefig('{}/plots/histograms/{}_hist.png'.format(ROOT_DIR, col_name))\n if show:\n plt.show()\n plt.close()\n\n\ntrain_data = pd.read_csv('{}/data/train.csv'.format(ROOT_DIR), index_col=0)\ntrain_data = custom_fillna(train_data)\ntrain_data = create_ordinals(train_data)\ntarget = train_data['SalePrice']\n\nshow = False\nfor col in train_data.select_dtypes(exclude='object'):\n col_data = train_data[col]\n make_hist(col_data, target, col, show=show)\n\nfor col in train_data.select_dtypes(include='object'):\n col_data = train_data[col]\n make_categorical_hist(col_data, target, col, show=show)\n","sub_path":"eda/ShowHistograms.py","file_name":"ShowHistograms.py","file_ext":"py","file_size_in_byte":2111,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"546399178","text":"#shelltest\nimport platform\nimport os\nimport subprocess\nimport inspect\n\ndef cur_dir():\n\treturn os.path.dirname(os.path.abspath(inspect.stack()[0][1]))\n\nif '64bit' in platform.architecture():\n\tos.environ['PATH'] += ';'+cur_dir()+'\\instantclient_12_1_64b'\nelse:\n\tos.environ['PATH'] += ';'+cur_dir()+'\\instantclient_12_1_32b'\n\n\n\nprint(\"import cx_Oracle\")\ntry:\n\timport cx_Oracle\nexcept:\n\tprint(\"\terror!\") \n\ttry:\n\t\tprint(\"\t..trying to install\")\n\t\tif '64bit' in platform.architecture():\n\t\t\toutput = subprocess.check_output(cur_dir()+'\\need_to_install\\cx_Oracle-5.2-11g.win-amd64-py3.4.exe',shell=True)\n\t\t\tprint(output)\n\t\telse:\n\t\t\toutput = subprocess.check_output(cur_dir()+'\\need_to_install\\cx_Oracle-5.2-11g.win32-py3.4.exe',shell=True)\n\t\t\tprint(output)\n\texcept:\n\t\tprint(\"\tWARNING: can't install. Is Oracle client installed?\")\n\ndef db_connect(envir):\n\t\n\tif envir == 'dev':\n\t\tdsnStr = cx_Oracle.makedsn(\"ATTRCKD.lsnr.persgroep.be\", \"1521\", \"ATTRCKD\")\n\t\tcon = cx_Oracle.connect(user=\"dmcg\", password=\"DMCG\", dsn=dsnStr)\n\t\treturn con\n\telif envir == 'test':\n\t\tdsnStr = cx_Oracle.makedsn(\"ATTRCKT.lsnr.persgroep.be\", \"1521\", \"ATTRCKT\")\n\t\tcon = cx_Oracle.connect(user=\"dmcg\", password=\"DMCG\", dsn=dsnStr)\n\t\treturn con\n\telse:\n\t\tcon = cx_Oracle.connect(db_connectstrings[envir])\n\t\treturn con\n\t\n\n\nfor envir in db_connectstrings.keys():\n\n\tprint(\"Connecting to AT \"+envir+\" database\")\n\tconnection = db_connect(envir)\t\n\tprint(\"\tfound version \"+ str(connection.version))\n\tquerystring = \"select * from dima_occasion where rownum = 1\"\n\tcursor = connection.cursor()\n\tcursor.execute(querystring)\n\tif len(cursor.fetchone()) >=1:\n\t\tprint(' data fetched')\n\telse:\n\t\tprint(' NO data fetched')\n\tconnection.close()\n","sub_path":"archive/shelltest.py","file_name":"shelltest.py","file_ext":"py","file_size_in_byte":1685,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"151855895","text":"#!/usr/bin/env python\n\nfrom testlib.scripts.android.ui import ui_steps\nfrom testlib.base import base_utils\nfrom testlib.scripts.android.ui.ui_step import step as ui_step\nfrom testlib.scripts.android.ui import ui_utils\nfrom testlib.scripts.android.adb.adb_step import step as adb_step\nfrom testlib.scripts.android.adb import adb_steps\nfrom testlib.scripts.android.ui.browser import browser_utils\nfrom testlib.scripts.android.adb import adb_utils\nfrom testlib.scripts.gms.google_search import google_search_utils\n\nimport time\n\nclass open_search(ui_step):\n \"\"\"\n description:\n Opens search app.\n\n usage:\n open_search(serial = serial,\n from_location = \"homescreen\")()\n\n tags:\n android, search web\n \"\"\"\n def __init__(self, wait_time = 20000,\n from_location = \"homescreen\",\n **kwargs):\n self.from_location = from_location\n self.wait_time = wait_time\n ui_step.__init__(self, **kwargs)\n\n def do(self):\n ui_steps.press_home(serial = self.serial)()\n ui_steps.click_button(serial = self.serial,\n view_to_find = {\"resourceIdMatches\":\".*launcher_search_button.*\"})()\n if self.uidevice(text=\"Skip\").wait.exists(timeout = 20000):\n self.uidevice(text=\"Skip\").click()\n else:\n self.uidevice(textContains = \"Search, or say \").wait.exists(timeout = 20000)\n def check_condition(self):\n return self.uidevice(textContains=\"Search, or say\").\\\n wait.exists(timeout = self.wait_time)\n\nclass search_web_from_home(ui_step):\n \"\"\"\n description:\n Searches a keyword from homescreen.\n\n usage:\n search_web_from_home(serial = serial,\n keyword = \"somekeyword\")()\n\n tags:\n android, search web\n \"\"\"\n def __init__(self, keyword = \"test\", wait_time = 20000, **kwargs):\n self.keyword = keyword\n self.wait_time = wait_time\n ui_step.__init__(self, **kwargs)\n def do(self):\n open_search(serial = self.serial,\n wait_time = self.wait_time)()\n ui_steps.edit_text(serial = self.serial,\n view_to_find = {\"textContains\":\"Search, or say \"},\n value = self.keyword)()\n self.uidevice.press(\"enter\")\n\n def check_condition(self):\n self.uidevice(text=\"Web\").wait.exists(timeout = self.wait_time)\n return self.uidevice(text=\"Web\").exists and\\\n self.uidevice(text=\"Images\").exists and\\\n self.uidevice(text=\"Maps\").exists and\\\n self.uidevice(text=\"Videos\").exists and\\\n self.uidevice(text=\"MORE\").exists\n\nclass search_apps_from_home(search_web_from_home):\n \"\"\"\n description:\n Searches apps for a keyword.\n\n usage:\n search_apps_from_home(serial = serial,\n keyword = \"somekeyword\")()\n\n tags:\n android, search app\n \"\"\"\n def __init__(self, keyword = \"test\", **kwargs):\n search_web_from_home.__init__(self, keyword = keyword, **kwargs)\n def do(self):\n max_steps = 10\n search_web_from_home.do(self)\n ui_steps.click_button(serial = self.serial,\n view_to_find = {\"text\":\"MORE\"},\n view_to_check = {\"text\":\"News\"})()\n while not self.uidevice(text=\"Apps\").wait.exists(timeout = 1000) and max_steps > 0:\n self.uidevice(text=\"News\").swipe.left()\n max_steps += -1\n ui_steps.click_button(serial = self.serial,\n view_to_find = {\"text\":\"Apps\"})()\n def check_condition(self):\n return self.uidevice(text=\"Apps\").info[\"selected\"] == True\n\nclass search_contact(search_web_from_home):\n \"\"\"\n description:\n Searches apps for a keyword.\n\n usage:\n search_apps_from_home(serial = serial,\n keyword = \"somekeyword\")()\n\n tags:\n android, search app\n \"\"\"\n def __init__(self, keyword = \"test\", **kwargs):\n search_web_from_home.__init__(self, keyword = keyword, **kwargs)\n def do(self):\n max_steps = 10\n open_search(serial = self.serial,\n wait_time = self.wait_time)()\n ui_steps.edit_text(serial = self.serial,\n view_to_find = {\"textContains\":\"Search, or say \"},\n value = self.keyword)()\n def check_condition(self):\n return self.uidevice(resourceIdMatches=\".*search_suggestions_summons\").\\\n child(textContains=self.keyword).wait.\\\n exists(timeout = self.wait_time)\n\nclass search_tablet_from_home(search_web_from_home):\n \"\"\"\n description:\n Searches a keyword from homescreen.\n\n usage:\n search_web_from_home(serial = serial,\n keyword = \"somekeyword\")()\n\n tags:\n android, search web\n \"\"\"\n def __init__(self, keyword = \"test\", **kwargs):\n search_web_from_home.__init__(self, keyword = keyword, **kwargs)\n def do(self):\n max_steps = 10\n search_web_from_home.do(self)\n if self.uidevice(text=\"MORE\").wait.exists(timeout = self.wait_time):\n ui_steps.click_button(serial = self.serial,\n view_to_find = {\"text\":\"MORE\"},\n view_to_check = {\"text\":\"News\"})()\n while not self.uidevice(text=\"Tablet\").wait.exists(timeout = 1000) and max_steps > 0:\n self.uidevice(text=\"News\").swipe.left()\n max_steps += -1\n ui_steps.click_button(serial = self.serial,\n view_to_find = {\"text\":\"Tablet\"})()\n else:\n ui_steps.click_button(serial = self.serial,\n view_to_find = {\"text\":self.keyword},\n view_to_check = {\"text\":\"Search Tablet\"})()\n ui_steps.click_button(serial = self.serial,\n view_to_find = {\"text\":\"Search Tablet\"})()\n\n def check_condition(self):\n if self.uidevice(text=\"No results found\\non your tablet.\").\\\n wait.exists(timeout = self.wait_time):\n return True\n elif self.uidevice(resourceId=\"com.google.android.googlequicksearchbox:id/main_content_back\").\\\n child_by_text(\"Apps\", resourceId=\"com.google.android.googlequicksearchbox:id/cards_view\").\\\n child(text=self.keyword).wait.exists(timeout = self.wait_time):\n return True\n else:\n return False\n","sub_path":"ACS_v.18.20.4_1/ACS/testlib/scripts/android/ui/gms/google_search/google_search_steps.py","file_name":"google_search_steps.py","file_ext":"py","file_size_in_byte":6679,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"200830608","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sat Jun 25 10:56:52 2016\n\n@author: nick\n\"\"\"\n\nclass Solution():\n\tdef solve(self, A):\n\t\t#use isPalindrom function to check if the string is palindrome or not\n result=[]\n for s in A:\n if self.isPalindrome(s):\n result.append(s)\n return result\n\n\tdef isPalindrome(self, x):\n \n for i in range(0,len(x)/2):\n \n if x[i]!=x[len(x)-i-1]:\n return False\n return True\n\n\np=Solution()\np.solve(['123', '232', '4556554', '12123', '3443','1314131'])","sub_path":"统计课/Palindrome.py","file_name":"Palindrome.py","file_ext":"py","file_size_in_byte":631,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"113275665","text":"s = input()\nt = list(input())\nlevel = 0\nsDict = dict()\n\nfor w in s:\n sDict[w] = level\n level += 1\n\nfor i in range(len(t)):\n if not t[i] in sDict:\n continue\n else:\n for j in range(1, len(t)):\n if t[j] in sDict:\n if sDict[t[i]] > sDict[t[j]]:\n temp = t[j]\n t[j] = t[i]\n t[i] = temp\n\ntStr = ''\nfor i in t:\n tStr += i\n\nprint(tStr)","sub_path":"Code/CodeRecords/2530/48117/249444.py","file_name":"249444.py","file_ext":"py","file_size_in_byte":438,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"520162073","text":"import sublime, sublime_plugin\nfrom .SoftwareUtil import *\nfrom .SoftwareRepo import *\n\nDASHBOARD_LABEL_WIDTH = 28\nDASHBOARD_VALUE_WIDTH = 36\nDASHBOARD_COL_WIDTH = 21\nDASHBOARD_LRG_COL_WIDTH = 38\nTABLE_WIDTH = 80\nMARKER_WIDTH = 4\n\n\n\ndef getSectionHeader(label):\n content = '{}\\n'.format(label)\n dashLen = DASHBOARD_LABEL_WIDTH - DASHBOARD_VALUE_WIDTH\n content += '-' * dashLen\n content += '\\n'\n return content \n\ndef formatRightAlignedTableLabel(label, colWidth):\n spacesRequired = colWidth - len(label)\n spaces = ' ' * spacesRequired\n \n return '{}{}'.format(spaces, label)\n\ndef getTableHeader(leftLabel, rightLabel, isFullTable=True):\n fullLen = TABLE_WIDTH - DASHBOARD_COL_WIDTH if not isFullTable else TABLE_WIDTH\n spacesRequired = fullLen - len(leftLabel) - len(rightLabel)\n spaces = ' ' * spacesRequired\n \n return '{}{}{}'.format(leftLabel, spaces, rightLabel)\n\ndef getRightAlignedTableHeader(label):\n content = '{}\\n'.format(formatRightAlignedTableLabel(label, TABLE_WIDTH))\n for i in range(TABLE_WIDTH):\n content += '-'\n content += '\\n'\n return content \n\ndef getSpaces(spacesRequired):\n return ' ' * spacesRequired\n\ndef getRowLabels(labels):\n content = ''\n spacesRequired = 0\n for i in range(len(labels)):\n label = labels[i]\n if i == 0:\n content += label \n spacesRequired = DASHBOARD_COL_WIDTH - len(content) - 1\n content += ' ' * spacesRequired\n content += ':'\n elif i == 1:\n spacesRequired = DASHBOARD_LRG_COL_WIDTH + DASHBOARD_COL_WIDTH - len(content) - len(label) - 1\n content += ' ' * spacesRequired\n content += label + ' '\n else:\n spacesRequired = DASHBOARD_COL_WIDTH - len(label) - 2\n content += '| '\n content += ' ' * spacesRequired\n content += label \n \n content += '\\n'\n return content \n\ndef getColumnHeaders(labels):\n content = ''\n spacesRequired = 0\n for i in range(len(labels)):\n label = labels[i]\n if i == 0:\n content += label \n elif i == 1:\n spacesRequired = DASHBOARD_LRG_COL_WIDTH + DASHBOARD_COL_WIDTH - len(content) - len(label) - 1\n content += ' ' * spacesRequired\n content += label + ' '\n else:\n spacesRequired = DASHBOARD_COL_WIDTH - len(label) - 2\n content += '| '\n content += ' ' * spacesRequired\n content += label \n \n content += '\\n'\n content += '-' * TABLE_WIDTH\n content += '\\n'\n return content ","sub_path":"lib/SoftwareReportManager.py","file_name":"SoftwareReportManager.py","file_ext":"py","file_size_in_byte":2598,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"310975868","text":"#views.py - Maps URLs to backend functions, then returns the results to the appropriate view\n\nfrom flask import (render_template, Blueprint, current_app, request)\nfrom .api.user.artpiece import DEFAULT_CANVAS\n\nmain = Blueprint('main', __name__)\n\n#Home page\n@main.route('/', methods=('GET', ))\n@main.route('/index', methods=('GET', ))\ndef index():\n return render_template('main.html', canvas_size=DEFAULT_CANVAS)\n\n\n@main.route('/art_confirmation', methods=('GET', ))\ndef art_confirmation():\n args = request.args\n token = args.get('token')\n artpiece_id = args.get('id')\n\n return render_template(\n 'art_confirmation.html', confirmation_token=token, artpiece_id=artpiece_id\n )\n","sub_path":"web/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":710,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"297509465","text":"#!/usr/bin/env python3\n\"\"\"\ninvite.py - Goshubot invite Module\nCopyright 2011 Daniel Oakley \n\nhttp://danneh.net/goshu\n\"\"\"\n\nfrom gbot.modules import Module\n\nclass Invite(Module):\n\t\n\tname = \"Invite\"\n\t\n\tdef __init__(self):\n\t\tself.events = {\n\t\t\t'in' : {\n\t\t\t\t'invite' : self.invite\n\t\t\t},\n\t\t\t#'out' : {},\n\t\t\t#'commands' : {},\n\t\t}\n\t\n\tdef invite(self, connection, event):\n\t\tserver = self.bot.irc.server_nick(connection)\n\t\tchannel = event.arguments()[0]\n\t\t\n\t\tself.bot.irc.join(server, channel)\n","sub_path":"modules/invite.py","file_name":"invite.py","file_ext":"py","file_size_in_byte":503,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"219384561","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n# TOMUSS: The Online Multi User Simple Spreadsheet\n# Copyright (C) 2012-2013 Thierry EXCOFFIER, Universite Claude Bernard\n#\n# This program is free software; you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation; either version 2 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program; if not, write to the Free Software\n# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA\n#\n# Contact: Thierry.EXCOFFIER@bat710.univ-lyon1.fr\n\n\"\"\"\nThe title and help is translated if it is found in the translations files.\n\"\"\"\n\nimport ast\nfrom .. import utilities\nfrom .. import configuration\nfrom .. import plugin\nfrom .. import cell\n\ndefault_links = (\n ################################################################\n # XXX ALWAYS ADD ITEMS TO THE END: because lin_id is the index\n # The order on screen is the priority\n ################################################################\n (\"abj_master\", -99, \"unsafe\", 'abj_masters',\n \"javascript:go_year('Dossiers/tt')\"),\n (\"abj_master\", -100, \"verysafe\", \"abj_masters\",\n \"javascript:go_year('Dossiers/tt/=read-only=')\"),\n (\"informations\",0,\"verysafe\", \"\" ,\"//stats.html\"),\n ('referents',999,'safe' ,'roots',\"javascript:go('referents_students')\"),\n (\"root_rw\",-900,\"verysafe\",'roots',\"/0/Dossiers/config_table/=read-only=\"),\n (\"root_rw\",-809,\"unsafe\" ,'roots',\"/0/Dossiers/config_table\"),\n (\"root_rw\",-808,\"unsafe\" ,'roots',\"/0/Dossiers/config_acls\"),\n (\"root_rw\",-807,\"safe\" ,'roots',\"/0/Dossiers/config_plugin\"),\n (\"root_rw\",-806,\"safe\" ,'roots',\"/0/Dossiers/config_home\"),\n (\"debug\" , 0,\"verysafe\",'roots',\"/0/Dossiers/javascript_regtest_ue\"),\n (\"debug\" , 0,\"verysafe\",'roots',\"javascript:go('demo_animaux')\"),\n (\"debug\" , 0,\"verysafe\",'roots',\"/0/Test/test_types\"),\n (\"root_rw\",-805,\"safe\" ,'roots',\"/0/Dossiers/config_cache\"),\n (\"root_rw\",-804,\"safe\" ,'roots',\"/0/Dossiers/config_login\"),\n (\"root_rw\",-803,\"safe\" ,'roots',\"/0/Dossiers/config_room\"),\n (\"root_rw\",-802,\"safe\" ,'roots',\"/0/Dossiers/config_messages\"),\n )\n\ncolumns = {\n '0': {'type': 'Text', 'freezed': 'F',\n 'title': utilities._(\"COL_TITLE_ch_box\"),\n 'comment': utilities._(\"COL_COMMENT_ch_box\"),\n },\n '1': {'type': 'Note', 'freezed': 'F',\n 'title': utilities._(\"COL_TITLE_ch_priority\"),\n 'comment': utilities._(\"COL_COMMENT_ch_priority\"),\n 'width': 2, 'minmax': '[-1000;1000]',\n },\n '2': {'type': 'Enumeration', 'freezed': 'F',\n 'enumeration': 'veryunsafe unsafe safe verysafe',\n 'red': 'veryunsafe', 'green': 'verysafe', 'width': 2,\n 'title': utilities._(\"COL_TITLE_ch_htmlclass\"),\n 'comment': utilities._(\"COL_COMMENT_ch_htmlclass\"),\n },\n '3': {'type': 'Text', 'freezed': 'F',\n 'title': utilities._(\"COL_TITLE_ch_group\"),\n 'comment': utilities._(\"COL_COMMENT_ch_group\"),\n 'width': 6,\n },\n '4': {'type': 'Text',\n 'title': utilities._(\"COL_TITLE_ch_title\"),\n 'comment': utilities._(\"COL_COMMENT_ch_title\"),\n 'width': 12,\n },\n '5': {'type': 'URL',\n 'title': utilities._(\"COL_TITLE_ch_url\"),\n 'comment': utilities._(\"COL_COMMENT_ch_url\"),\n 'width': 12,\n },\n '6': {'type': 'Text',\n 'title': utilities._(\"COL_TITLE_ch_help\"),\n 'comment': utilities._(\"COL_COMMENT_ch_help\"),\n 'width': 12,\n },\n '7': {'type': 'Text',\n 'title': utilities._(\"COL_TITLE_plugin\"),\n 'width': 2,\n },\n }\n\ndef create(table):\n utilities.warn('Creation')\n if table.year != 0 or table.semester != 'Dossiers':\n raise ValueError('Not allowed')\n ro = table.get_ro_page()\n table.get_a_root_page()\n table.table_attr(ro, 'masters', list(configuration.root))\n table.table_attr(ro, 'default_nr_columns', 8)\n table.table_attr(ro, 'default_sort_column', [0,1])\n table.update_columns(columns, ro)\n\ndef add_new_links_in_the_table(table):\n \"\"\"Create missing lines in the table\"\"\"\n table.update_columns(columns, table.get_ro_page())\n rw = table.pages[1]\n def change(lin_id, values):\n yet_in = lin_id in table.lines\n for data_col, value in enumerate(values):\n col = str(data_col)\n if not yet_in or '' ;\n\n document.getElementById('horizontal_scrollbar').parentNode.style.display = 'none' ;\n}\n\n\"\"\"\n\ndef update_home_page_link(plugin_name):\n from .. import document\n t = document.table(0, \"Dossiers\", \"config_home\")\n if plugin_name not in t.lines:\n return\n update_link(plugin_name, t.lines[plugin_name])\nconfiguration.update_home_page_link = update_home_page_link\n","sub_path":"TEMPLATES/config_home.py","file_name":"config_home.py","file_ext":"py","file_size_in_byte":8765,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"282621049","text":"from typing import List\n\nimport numpy as np\nfrom numba import njit, prange\nfrom numba.typed import List as TypedList\n\nfrom ..data_structures import Run\nfrom .common import (\n convert_results_dict_list_to_run,\n create_empty_results_dict,\n create_empty_results_dict_list,\n)\n\n\n# LOW LEVEL FUNCTIONS ==========================================================\n@njit(cache=True)\ndef _wmnz(results, weights):\n combined_results = create_empty_results_dict()\n\n for res in results:\n for doc_id in res.keys():\n if combined_results.get(doc_id, False) == False:\n scores_and_weights = np.array(\n [\n [res[doc_id], weights[i]]\n for i, res in enumerate(results)\n if doc_id in res\n ]\n )\n\n scores_sum = sum(scores_and_weights[:, 0])\n weights_sum = sum(scores_and_weights[:, 1])\n\n combined_results[doc_id] = scores_sum * weights_sum\n\n return combined_results\n\n\n@njit(cache=True, parallel=True)\ndef _wmnz_parallel(runs, weights):\n q_ids = TypedList(runs[0].keys())\n combined_results = create_empty_results_dict_list(len(q_ids))\n\n for i in prange(len(q_ids)):\n q_id = q_ids[i]\n combined_results[i] = _wmnz([run[q_id] for run in runs], weights)\n\n return convert_results_dict_list_to_run(q_ids, combined_results)\n\n\n# HIGH LEVEL FUNCTIONS =========================================================\ndef wmnz(runs: List[Run], weights: List[float], name: str = \"wmnz\") -> Run:\n r\"\"\"Computes Weighted MNZ as proposed by [Wu et al.](https://dl.acm.org/doi/10.1145/584792.584908).\n\n ```bibtex\n @inproceedings{DBLP:conf/cikm/WuC02,\n author = {Shengli Wu and\n Fabio Crestani},\n title = {Data fusion with estimated weights},\n booktitle = {Proceedings of the 2002 {ACM} {CIKM} International Conference on Information\n and Knowledge Management, McLean, VA, USA, November 4-9, 2002},\n pages = {648--651},\n publisher = {{ACM}},\n year = {2002},\n url = {https://doi.org/10.1145/584792.584908},\n doi = {10.1145/584792.584908},\n timestamp = {Tue, 06 Nov 2018 16:57:40 +0100},\n biburl = {https://dblp.org/rec/conf/cikm/WuC02.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n }\n ```\n\n Args:\n runs (List[Run]): List of Runs.\n weights (List[float]): Weights.\n name (str): Name for the combined run. Defaults to \"wmnz\".\n\n Returns:\n Run: Combined run.\n\n \"\"\"\n run = Run()\n run.name = name\n run.run = _wmnz_parallel(\n TypedList([run.run for run in runs]), TypedList(weights)\n )\n run.sort()\n return run\n","sub_path":"ranx/fusion/wmnz.py","file_name":"wmnz.py","file_ext":"py","file_size_in_byte":2903,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"336012621","text":"#! /usr/bin/env python\n# -*- coding=utf-8 -*-\n\nfrom pymongo import MongoClient\nimport docutils.core\nfrom bs4 import BeautifulSoup\nimport copy\nimport pypandoc\nimport re\n\n\"\"\"\n梳理：\n* 源 html 中的名词部分单独处理\n * 名词部分由 `p > span > a` 标签构成并具有特征，可识别处理\n * 由 `a` 标签获取名词字典：`string` 对应 `key`、`a` 属性 `title` 为 `value`\n * 使用工厂方法 `soup.new_tag(\"code\")` 替换 `span` 元素为 `*关键词* [^关键词]`\n * 使用工厂方法 `soup.new_tag(\"pre\")` 以 `[^关键词]: “*关键词*: 说明文字`格式，使用 `inser_after` 写入 `p` 标签之后\n* 查询全书其他样式内容是否存在异常\n * title 文字中存在换行符，后续处理存在问题\n* 处理后 `html` 采用 `pandoc` 整体转换为目标格式\n* 清理转换后的异常内容\n * 格式转义符替换清理\n * 格式样式处理\n * 大纲降低二级（当前根大纲使用 `h4` 转为 `h2`，即 `####` 替换为 `##`）\n * 未标注样式替换（汉字数字 + 括号、阿拉伯数字、阿拉伯数字 + 括号）\n * 内容图像处理\n * 经文处理\n\"\"\"\n\n# 数据库定义\nclient = MongoClient()\ndb = client['Huideng']\ncollection = db['SourceArticles']\n# 获取指定内容\ndoc = collection.find_one({'book':'三册','sort':0}) # 指定书籍内容\nhtml = doc['article'] # 提取文章数据\n# 转为 soup 格式\nsoup = BeautifulSoup(html, \"html.parser\")\narticle = soup.find(id=\"all-book\") # 正文定位获取\n\ndef keywords(source_soup):\n \"\"\"\n 单独处理源 html 中的 keyword 格式\n - 名词部分由 `p > span > a` 标签构成并具有特征，可识别处理\n - 由 `a` 标签获取名词字典：`string` 对应 `key`、`a` 属性 `title` 为 `value`\n - 名词字典保存于 `keywords` 数组\n - 修改 `string` 文本格式为目标格式 `*关键词* [^关键词]`\n - 解包 `a` 及 `span` 标签\n - 将 `keywords` 以 `[^关键词]: “*关键词*: 说明文字`格式，使用 `inser_after` 写入 `p` 标签之后\n input: \n source_soup: 源页面 BeautifuSoup 格式\n return:\n soup: 处理后的 BeautifuSoup 格式\n \"\"\"\n \n # a 标签处理策略\n aTags = source_soup.find_all(\"a\")\n if aTags:\n for i in aTags:\n if 'title' in i.attrs: # 包含 title 属性的 a 标签为 keyword\n key = i.string.strip() # 存储 keyword：string 内容为 keyword\n title = i.get('title') # 存储 keyword：title 属性值为对应 value\n title = re.sub(r'[\\n\\r]+', '\\t', title) # 剔除 title 内换行符为制表符\n insertString = soup.new_tag(\"code\") # 行内标记，避免转换时格式错乱\n insertString.string = \" *%s* [^%s] \" %(key, key) # 替换 md 下标格式为：*关键词* [^关键词]\n \n # 工厂方法生成新 Tag 对象并定义内容 string\n parentTag = i.parent.parent # 当前 a 标签位于 p > span > a 两级 parent 可以定位于上级 p 标签\n parentTag.span.replace_with(insertString)\n insertTag = soup.new_tag(\"pre\") # 段落标记，避免转换时格式错乱\n insertTag.string = \"[^%s]: *%s*: %s\" %(key, key, title) # 增加名词样式及文字\n # insert_after 方法在指定节点之后追加 Tag 对象\n parentTag.insert_after(insertTag)\n keyword = []\n else:\n # todo: log 方式记录 warn 例外\n pass\n\ndef soup2md(soup):\n \"\"\"\n pandoc 转换 html 为 md\n \"\"\"\n extra_args = []\n output = pypandoc.convert_text(article, 'md', format='html', extra_args=extra_args)\n return output\n\ndef cleanup(markdown_str):\n \"\"\"\n 清理 markdown 文本中的格式问题\n \"\"\"\n markdown_str = re.sub(r\"<.+>\", \"\", markdown_str) # 清除首尾残留 html 标签\n markdown_str = re.sub(r\"!\\[\\]\\(/images/demo/logo/end-article\\.png\\)\\{\\.end-img\\}\", \"\", markdown_str) # 剔除文尾图片链接\n markdown_str = re.sub(r\"\\xa0\", \"\", markdown_str) # 清除异常空白字符\n markdown_str = re.sub(r\"####\", \"##\", markdown_str) # 减少 ## 以提升标题层级\n markdown_str = re.sub(r\"\\n(（[一二三四五六七八九十]+）)\", r\"\\n### \\1\", markdown_str) # （一）模式增加 ### 标记为标题三\n markdown_str = re.sub(r\"(\\n)(\\d+)\", r\"\\1#### \\2\", markdown_str) # 1. 模式增加 #### 标记为标题四\n# markdown_str = re.sub(r\"\\n(（\\d+）)\", r\"\\n##### \\1\", markdown_str) # （1） 模式增加 ##### 标记为标题五\n markdown_str = re.sub(r\"\\n\\s+\", r\"\\n\\n\", markdown_str) # 剔除冗余行首空白字符\n markdown_str = re.sub(r\"`\", r\"\", markdown_str) # 剔除 code 生成的 ` 字符\n return markdown_str\n\ndef write_file(content, md_filename):\n \"\"\"\n 写入文件\n \"\"\"\n with open(md_filename, 'w') as f:\n f.write(content)\n\nkeywords(article) # 改写 keywords\nwrite_file(cleanup(soup2md(article)), 'temp.md')\n","sub_path":"FormatHandle.py","file_name":"FormatHandle.py","file_ext":"py","file_size_in_byte":5096,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"508591184","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon May 21 08:59:37 2018\n\n@author: s.granel\n\"\"\"\n\n#Imports\nimport sys\nimport numpy as np\nimport pandas as pd\nimport psycopg2\nfrom keras.models import load_model\nimport datetime\n\nfolder = sys.argv[1]\n#folder = \"\"\nidpdv = sys.argv[2]\n#idpdv = 33600001\nidcarburant = sys.argv[3]\n#print(idpdv)\n#print(idcarburant)\nidcarburant = 1\n# Jeu d'entrainement\nconn = None\ntraining_set = pd.DataFrame(columns=['A', 'B', 'C', 'D', 'E']);\n#Connexion à la bdd\ntry:\n conn = psycopg2.connect(\"dbname='fuelpred' user='fuelpred' host='localhost' password='fuelpred'\")\n cur = conn.cursor()\n cur.execute(\"SELECT val,date, substring(cast(cp as varchar), 1, char_length(cast(cp as varchar))-3) as cp from public.pdv_valeurs pv INNER JOIN pdv_infos pi ON pv.idpdv = pi.idpdv WHERE id in (select id from public.pdv_valeurs pv WHERE pv.idpdv = %s and idcarburant = %s ORDER BY date DESC LIMIT 401) ORDER BY date ASC;\", (idpdv,idcarburant))\n rows = cur.fetchall()\n for record in rows:\n cur.execute(\"SELECT valeur from public.petrol_valeurs WHERE date <= %s ORDER BY date DESC LIMIT 1\", (record[1],))\n row = cur.fetchone()\n cur.execute(\"SELECT min(val), avg(val), max(val) from public.pdv_valeurs pv INNER JOIN pdv_infos pi ON pv.idpdv = pi.idpdv WHERE date = %s AND length(cast(cp as varchar)) = 5 and substring(cast(cp as varchar), 1, char_length(cast(cp as varchar))-3) = %s and idcarburant = %s\", (record[1],record[2], 1))\n vals = cur.fetchone()\n training_set = training_set.append({'A' :record[0], 'B' :row[0], 'C' : vals[0], 'D' :vals[1], 'E' : vals[2]}, ignore_index=True)\n \n training_set = training_set[['A', 'B', 'C', 'D', 'E']].values \n \n model = load_model(folder + 'predict_fuel_v2_400.h5')\n \n #On met le tout dans des vecteurs qui seront donnés à Keras\n #Remarque : il faut de la mémoire sur votre ordinateur\n #On initialise les vecteurs\n # Création de la structure avec 60 timesteps et 1 sortie\n \n predicted = []\n \n def predict_petrol(training_set, model, predicted,date):\n \n # Création de la structure avec 60 timesteps et 1 sortie\n X_test = []\n \n nb_pred = 400\n nb_pred_final = len(training_set)-1-nb_pred # nombre de valeurs précédents celle-là\n nb_boucle = len(training_set)-1\n \n for variable in range(0,5):\n X = []\n for i in range(nb_pred_final, nb_boucle):\n X.append(training_set[i:i+1, variable])\n X = np.array(X)\n X_test.append(X)\n X_test = np.array(X_test) \n X_test = np.swapaxes(X_test, 0, 2)\n \n val = model.predict(X_test)\n training_set = np.delete(training_set, 0, 0)\n vals = val\n vals = getValsAlreadyPredicted(vals, date)\n vals = np.expand_dims(vals, axis=1)\n vals = np.swapaxes(vals, 0, 1)\n \n training_set = np.append(training_set, vals,axis=0)\n return training_set\n \n def getValsAlreadyPredicted(vals, date):\n date_batch = datetime.date.today()\n \n training_set_predict_petrol = pd.DataFrame(columns=['A']);\n if(date == date_batch):\n #Connexion à la bdd\n cur.execute(\"SELECT valeur from public.petrol_valeurs WHERE date = %(date)s\", {'date' : date.isoformat()})\n row = cur.fetchone()\n training_set_predict_petrol = training_set_predict_petrol.append({'A' :row[0]}, ignore_index=True)\n \n else :\n #Connexion à la bdd\n cur.execute(\"SELECT valeur from public.predict_petrol_valeurs WHERE date_predict = %(date_predict)s AND date_batch = %(date_batch)s \", {'date_predict' : date.isoformat(),'date_batch' : date_batch.isoformat()})\n row = cur.fetchone()\n training_set_predict_petrol = training_set_predict_petrol.append({'A' :row[0]}, ignore_index=True)\n \n training_set_predict_petrol = training_set_predict_petrol[['A']].values \n vals = np.append(vals, training_set_predict_petrol)\n \n training_set_predict_fuel_dep = pd.DataFrame(columns=['A', 'B', 'C']);\n #Connexion à la bdd\n \n cur.execute(\"SELECT valeur_min, valeur_avg, valeur_max from public.predict_fuel_dep_valeurs WHERE date_predict = %(date_predict)s AND dep = %(dep)s AND date_batch = %(date_batch)s \" , {'date_predict' : date.isoformat(), 'dep': 33, 'date_batch' : date_batch.isoformat()})\n row = cur.fetchone()\n training_set_predict_fuel_dep = training_set_predict_fuel_dep.append({'A' :row[0], 'B' :row[1], 'C' :row[2]}, ignore_index=True)\n \n vals = np.append(vals, training_set_predict_fuel_dep)\n return vals\n \n date_batch = datetime.date.today()\n date_predict = date_batch\n for i in range(0,5):\n training_set = predict_petrol(training_set, model, predicted,date_predict)\n predicted.append(training_set[400])\n date_predict = date_predict + datetime.timedelta(1)\n \n date_batch = datetime.date.today()\n date_predict = date_batch\n \n for i in range(0,5):\n cur.execute(\"SELECT valeur from public.predict_fuel_valeurs WHERE date_predict = %(date_predict)s and date_batch = %(date_batch)s and idpdv = %(idpdv)s and idcarburant = %(idcarburant)s\", {'date_predict' : date_predict.isoformat(), 'date_batch' : date_batch.isoformat(), 'idpdv' : idpdv, 'idcarburant' : idcarburant})\n rows = cur.fetchall()\n result = 0\n for record in rows:\n result = 1\n if(result == 0):\n cur.execute(\"INSERT INTO public.predict_fuel_valeurs (valeur, date_predict, date_batch, idpdv, idcarburant) VALUES(%(val)s, %(date_predict)s, %(date_batch)s, %(idpdv)s, %(idcarburant)s)\", {'val' : predicted[i][0], 'date_predict' : date_predict.isoformat(), 'date_batch' : date_batch.isoformat(), 'idpdv' : idpdv, 'idcarburant' : idcarburant})\n else :\n cur.execute(\"UPDATE public.predict_fuel_valeurs SET valeur = %(val)s WHERE date_predict = %(date_predict)s and date_batch = %(date_batch)s and idpdv = %(idpdv)s and idcarburant = %(idcarburant)s\", {'val' : predicted[i][0], 'date_predict' : date_predict.isoformat(), 'date_batch' : date_batch.isoformat(), 'idpdv' : idpdv, 'idcarburant' : idcarburant})\n conn.commit()\n date_predict = date_predict + datetime.timedelta(1)\nexcept:\n print(\"I am unable to connect to the database.\")\nfinally:\n if conn is not None:\n conn.close()\n #print('Database connection closed.')\n","sub_path":"fuelPred/predict_fuel.py","file_name":"predict_fuel.py","file_ext":"py","file_size_in_byte":6554,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"450953746","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n# ---\n# jupyter:\n# jupytext:\n# text_representation:\n# extension: .py\n# format_name: light\n# format_version: '1.4'\n# jupytext_version: 1.1.4\n# kernelspec:\n# display_name: Python 3\n# language: python\n# name: python3\n# ---\n\n# # s_views_st_deviations [](https://www.arpm.co/lab/redirect.php?code=s_views_st_deviations&codeLang=Python)\n# For details, see [here](https://www.arpm.co/lab/redirect.php?permalink=eb-example-fpviews-sd-dev).\n\n# +\nimport numpy as np\n\nfrom arpym.views import min_rel_entropy_sp\n# -\n\n# ## input parameters\n\n# +\n# scenarios of market variables\nx = np.array([[0.2, 1.7, 2, 3.4], [5, 3.4, -1.3, 1]]).T\np_base = np.ones(x.shape[0]) / x.shape[0] # base flexible probabilities\nsig_view = np.array([0.4]) # view on standard deviation\nc = 0.2 # confidence level\n\n\ndef v(y):\n return np.sqrt([y[:, 0]]) # view function\n\n\n# ## [Step 1](https://www.arpm.co/lab/redirect.php?permalink=s_views_st_deviations-implementation-step01): Compute parameters specifying the constraints\n\nmu_base = v(x) @ p_base\n\nz_ineq = v(x)**2\nmu_view_ineq = sig_view ** 2 + mu_base ** 2\n\nz_eq = v(x)\nmu_view_eq = mu_base\n# -\n\n# ## [Step 2](https://www.arpm.co/lab/redirect.php?permalink=s_views_st_deviations-implementation-step02): Compute covariance matrix and effective rank\n\n# +\n\ndef eff_rank(s2):\n lam2_n, _ = np.linalg.eig(s2)\n w_n = lam2_n / np.sum(lam2_n)\n return np.exp(- w_n @ np.log(w_n))\n\n\nz = np.vstack((z_ineq, z_eq))\ncovariance = np.cov(z)\neffrank = eff_rank(np.corrcoef(z))\n# -\n\n# ## [Step 3](https://www.arpm.co/lab/redirect.php?permalink=s_views_st_deviations-implementation-step03): Compute updated probabilities\n\np_upd = min_rel_entropy_sp(p_base, z_ineq, mu_view_ineq, z_eq, mu_view_eq,\n normalize=False)\n\n# ## [Step 4](https://www.arpm.co/lab/redirect.php?permalink=s_views_st_deviations-implementation-step04): Compute additive/multiplicative confidence-weighted probabilities\n\np_c_add = c * p_upd + (1 - c) * p_base\np_c_mul = p_upd ** c * p_base ** (1 - c) /\\\n np.sum(p_upd ** c * p_base ** (1 - c))\n","sub_path":"scripts/sources/s_views_st_deviations.py","file_name":"s_views_st_deviations.py","file_ext":"py","file_size_in_byte":2249,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"437326697","text":"#!/usr/bin/python3\n\"\"\"queries the Reddit API and prints the titles of the first 10 hot posts\"\"\"\nfrom requests import get\n\n\ndef top_ten(subreddit):\n \"\"\" listed for a given subreddit\"\"\"\n url = \"https://api.reddit.com/r/{}/hot?limit=10\".format(subreddit)\n headers = {\"User-Agent\": \"reddit API\"}\n data = get(url, headers=headers, allow_redirects=False)\n if data.status_code is not 200:\n return print(None)\n redd = data.json().get(\"data\").get(\"children\")\n for item in redd:\n print(item.get(\"data\").get(\"title\"))\n","sub_path":"0x16-api_advanced/1-top_ten.py","file_name":"1-top_ten.py","file_ext":"py","file_size_in_byte":542,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"255600879","text":"import ssl\nimport os\nimport yaml\nimport logging\nimport requests\nimport urllib\nfrom functools import wraps\nimport hmac\nfrom hashlib import sha1\nfrom time import time\nimport crypt\nimport uuid\nimport re\nimport json\n\nimport smtplib\nfrom email.message import EmailMessage\n\nimport humanfriendly\n\nimport pymongo\nfrom pymongo import MongoClient\nfrom pymongo import DESCENDING as pyDESCENDING\n\nfrom flask import Flask\nfrom flask import jsonify\nfrom flask import request\nfrom flask import abort\nfrom flask import Response\n\nfrom flask_cors import CORS, cross_origin\n\nfrom elasticsearch import Elasticsearch\n\nfrom goswift import version\n\nconfig_file = 'config.yml'\nif 'GOSWIFT_CONFIG' in os.environ:\n config_file = os.environ['GOSWIFT_CONFIG']\n\nconfig = None\nwith open(config_file, 'r') as ymlfile:\n config = yaml.load(ymlfile)\n\ndef override_config():\n if 'GOSWIFT_DEBUG' in os.environ and os.environ['GOSWIFT_DEBUG']:\n config['debug'] = os.environ['GOSWIFT_DEBUG']\n if 'GOSWIFT_SALT_SECRET' in os.environ and os.environ['GOSWIFT_SALT_SECRET']:\n config['salt_secret'] = os.environ['GOSWIFT_SALT_SECRET']\n if 'GOSWIFT_SWIFT_KEYSTONE_URL' in os.environ and os.environ['GOSWIFT_SWIFT_KEYSTONE_URL']:\n config['swift']['keystone_url'] = os.environ['GOSWIFT_SWIFT_KEYSTONE_URL']\n if 'GOSWIFT_SWIFT_SWIFT_URL' in os.environ and os.environ['GOSWIFT_SWIFT_SWIFT_URL']:\n config['swift']['swift_url'] = os.environ['GOSWIFT_SWIFT_SWIFT_URL']\n\n if 'GOSWIFT_SWIFT_ADMIN_OS_USER_ID' in os.environ and os.environ['GOSWIFT_SWIFT_ADMIN_OS_USER_ID']:\n config['swift']['admin']['os_user_id'] = os.environ['GOSWIFT_SWIFT_ADMIN_OS_USER_ID']\n if 'GOSWIFT_SWIFT_ADMIN_OS_USER_PASSWORD' in os.environ and os.environ['GOSWIFT_SWIFT_ADMIN_OS_USER_PASSWORD']:\n config['swift']['admin']['os_user_password'] = os.environ['GOSWIFT_SWIFT_ADMIN_OS_USER_PASSWORD']\n if 'GOSWIFT_SWIFT_ADMIN_OS_USER_PROJECT' in os.environ and os.environ['GOSWIFT_SWIFT_ADMIN_OS_USER_PROJECT']:\n config['swift']['admin']['os_user_project'] = os.environ['GOSWIFT_SWIFT_ADMIN_OS_USER_PROJECT']\n if 'GOSWIFT_SWIFT_ADMIN_OS_USER_DOMAIN' in os.environ and os.environ['GOSWIFT_SWIFT_ADMIN_OS_USER_DOMAIN']:\n config['swift']['admin']['os_user_domain'] = os.environ['GOSWIFT_SWIFT_ADMIN_OS_USER_DOMAIN']\n\n if 'GOSWIFT_SWIFT_DEFAULTS_DOMAIN' in os.environ and os.environ['GOSWIFT_SWIFT_DEFAULTS_DOMAIN']:\n config['swift']['defaults']['domain'] = os.environ['GOSWIFT_SWIFT_DEFAULTS_DOMAIN']\n\n if 'GOSWIFT_SWIFT_QUOTAS' in os.environ and os.environ['GOSWIFT_SWIFT_QUOTAS']:\n config['swift']['quotas'] = os.environ['GOSWIFT_SWIFT_QUOTAS']\n\n if 'GOSWIFT_ELASTIC_HOST' in os.environ and os.environ['GOSWIFT_ELASTIC_HOST']:\n config['elastic']['hosts'] = [os.environ['GOSWIFT_ELASTIC_HOST']]\n\n if 'GOSWIFT_MONGO_URL' in os.environ and os.environ['GOSWIFT_MONGO_URL']:\n config['mongo']['url'] = os.environ['GOSWIFT_MONGO_URL']\n\n if 'GOSWIFT_ADMIN_LIST' in os.environ and os.environ['GOSWIFT_ADMIN_LIST']:\n admin_list = os.environ['GOSWIFT_ADMIN_LIST']\n config['admin'] = [x.strip() for x in admin_list.split(',')]\n\n if 'GOSWIFT_SMTP_HOST' in os.environ and os.environ['GOSWIFT_SMTP_HOST']:\n config['smtp']['host'] = os.environ['GOSWIFT_SMTP_HOST']\n if 'GOSWIFT_SMTP_PORT' in os.environ and os.environ['GOSWIFT_SMTP_PORT']:\n config['smtp']['port'] = int(os.environ['GOSWIFT_SMTP_PORT'])\n if 'GOSWIFT_SMTP_FROM' in os.environ and os.environ['GOSWIFT_SMTP_FROM']:\n config['smtp']['from'] = int(os.environ['GOSWIFT_SMTP_FROM'])\n\n if 'GOSWIFT_HOST_HREF' in os.environ and os.environ['GOSWIFT_HOST_HREF']:\n config['host_href'] = os.environ['GOSWIFT_HOST_HREF']\n\noverride_config()\n\nif config['debug']:\n logging.basicConfig(\n level=logging.DEBUG,\n format='%(asctime)s %(module)s:%(filename)s %(levelname)s %(message)s'\n )\nelse:\n logging.basicConfig(\n format='%(asctime)s %(module)s:\t%(filename)s %(levelname)s %(message)s'\n )\n\nMIME_TYPE_JSON = 'application/json'\nMIME_TYPE_JSON_HOME = 'application/json-home'\nMEDIA_TYPE_JSON = 'application/vnd.openstack.key-manager-%s+json'\n\nes = None\nif config['elastic']['hosts']:\n es = Elasticsearch(\n config['elastic']['hosts'],\n # sniff before doing anything\n sniff_on_start=True,\n # refresh nodes after a node fails to respond\n sniff_on_connection_fail=True,\n # and also every 60 seconds\n sniffer_timeout=60\n )\n es.indices.create(index=config['elastic']['index'], ignore=400)\n\nmongo = MongoClient(config['mongo']['url'])\nmongo_db = mongo[config['mongo']['db']]\ndb_quota = mongo_db.quotas\ndb_hooks = mongo_db.hooks\ndb_hook = mongo_db.hook\n\n\ndef _get_base_url_from_request():\n if not config['host_href'] and hasattr(request, 'url'):\n p_url = urllib.parse.urlsplit(request.url)\n base_url = '%s://%s' % (p_url.scheme, p_url.netloc)\n '''\n if p_url.path:\n base_url = '%s://%s%s' % (p_url.scheme, p_url.netloc, p_url.path)\n else:\n base_url = '%s://%s' % (p_url.scheme, p_url.netloc)\n '''\n return base_url\n else:\n return config['host_href']\n\ndef _get_versioned_url(version):\n if version[-1] != '/':\n version += '/'\n # If host_href is not set in conf,\n # then derive it from request url\n host_part = _get_base_url_from_request()\n if host_part[-1] != '/':\n host_part += '/'\n return urllib.parse.urljoin(host_part, 'api', version)\n\n\nclass BaseVersionController(object):\n\n @classmethod\n def get_version_info(cls):\n return {\n 'id': cls.version_id,\n 'status': 'stable',\n 'updated': cls.last_updated,\n 'links': [\n {\n 'rel': 'self',\n 'href': _get_versioned_url(cls.version_string),\n }, {\n 'rel': 'describedby',\n 'type': 'text/html',\n 'href': 'https://github.com/osallou/goswift'\n }\n ],\n 'media-types': [\n {\n 'base': MIME_TYPE_JSON,\n 'type': MEDIA_TYPE_JSON % cls.version_string\n }\n ]\n }\n\n\nclass V1Controller(BaseVersionController):\n\n version_string = 'v1'\n\n version_id = 'v1'\n\n last_updated = '2018-01-11T00:00:00Z'\n\n def __init__(self):\n logging.debug('=== V1Controller ===')\n\n\nAVAILABLE_VERSIONS = {\n V1Controller.version_string: V1Controller,\n}\n\nDEFAULT_VERSION = V1Controller.version_string\n\napp = Flask(__name__)\nCORS(app, expose_headers=['X-Container-Bytes-Used', 'X-Container-Object-Count', 'X-Auth-Token', 'X-Container-Write', 'X-Container-Read'])\n\ndef get_token(data):\n auth = {\n 'auth': {\n 'scope':\n {'project': {\n 'name': data['project'],\n 'domain':\n {\n 'name': data['domain']\n }\n }\n },\n 'identity': {\n 'password': {\n 'user': {\n 'domain': {\n 'name': data['domain']\n },\n 'password': data['password'],\n 'name': data['user']\n }\n },\n 'methods': ['password']\n }\n }\n }\n\n token = None\n\n try:\n ks_url = config['swift']['keystone_url'] + '/auth/tokens'\n r = requests.post(ks_url, json=auth)\n if not r.status_code == 201:\n logging.info('Authentication failed: %s' + str(data['user']))\n abort(401)\n token = r.headers['X-Subject-Token']\n except Exception:\n logging.exception('Failed to get token for ' + data['user'])\n return None\n return token\n\n\ndef requires_auth(f):\n @wraps(f)\n def decorated(*args, **kwargs):\n if 'X-Auth-Token' not in request.headers:\n abort(401)\n return f(*args, **kwargs)\n return decorated\n\n@app.route('/api//ping', methods=['GET'])\ndef ping(apiversion):\n return jsonify({'msg': 'pong'})\n\n@app.route('/api', methods=['GET'])\ndef versions():\n versions_info = [version_class.get_version_info() for\n version_class in AVAILABLE_VERSIONS.values()]\n\n version_output = {\n 'versions': {\n 'values': versions_info\n }\n }\n return jsonify(version_output)\n\n\n@app.route('/api/', methods=['GET'])\ndef version(apiversion):\n if apiversion not in AVAILABLE_VERSIONS:\n abort(404)\n vController = AVAILABLE_VERSIONS[apiversion]()\n return jsonify({'version': vController.get_version_info()})\n\n@app.route('/api//reauth/', methods=['GET'])\n@requires_auth\ndef reauthenticate(apiversion, project):\n\n auth = {\n \"auth\": {\n \"identity\": {\n \"methods\": [\n \"token\"\n ],\n \"token\": {\n \"id\": request.headers['X-Auth-Token']\n }\n },\n \"scope\": {\n \"project\": {\n \"id\": project\n }\n }\n }\n }\n token = None\n\n try:\n ks_url = config['swift']['keystone_url'] + '/auth/tokens'\n r = requests.post(ks_url, json=auth)\n if not r.status_code == 201:\n logging.info('Reauthentication failed')\n abort(401)\n token = r.headers['X-Subject-Token']\n r_json = r.json()\n project_id = r_json['token']['project']['id']\n\n except Exception as e:\n logging.exception('Failed to authenticate with Keystone')\n abort(401)\n\n return jsonify({'token': token, 'project': project_id})\n\n@app.route('/api//auth', methods=['POST'])\ndef authenticate(apiversion):\n data = request.get_json()\n logging.info(str(data))\n if not data or 'user' not in data or 'password' not in data or 'project' not in data:\n abort(401)\n\n if 'domain' not in data:\n data['domain'] = config['swift']['defaults']['domain']\n\n auth = {\n 'auth': {\n 'scope':\n {'project': {\n 'name': data['project'],\n 'domain':\n {\n 'name': data['domain']\n }\n }\n },\n 'identity': {\n 'password': {\n 'user': {\n 'domain': {\n 'name': data['domain']\n },\n 'password': data['password'],\n 'name': data['user']\n }\n },\n 'methods': ['password']\n }\n }\n }\n\n token = None\n\n try:\n ks_url = config['swift']['keystone_url'] + '/auth/tokens'\n r = requests.post(ks_url, json=auth)\n if not r.status_code == 201:\n logging.info('Authentication failed: %s' % str(data['user']))\n abort(401)\n token = r.headers['X-Subject-Token']\n r_json = r.json()\n project_id = r_json['token']['project']['id']\n is_admin = False\n if 'roles' in r_json['token']:\n for role in r_json['token']['roles']:\n if role['name'] == 'admin':\n is_admin = True\n\n except Exception as e:\n logging.exception('Failed to authenticate with Keystone')\n abort(401)\n\n return jsonify({'token': token, 'project': project_id, 'is_admin': is_admin})\n\n@app.route('/api//project/', methods=['GET'])\n@requires_auth\ndef get_project_containers(apiversion, project):\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n }\n r = requests.get(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) +'?format=json', headers=headers)\n if r.status_code not in [200]:\n abort(r.status_code)\n url = config['swift']['swift_url'] + '/v1/AUTH_' + str(project)\n quota_value = int(humanfriendly.parse_size(config['swift']['quotas'], binary=True))\n quota = db_quota.find_one({'id': project})\n if quota:\n quota_value = quota['quota']\n return jsonify({'containers': r.json(), 'swift_url': url, 'quota': quota_value})\n\n\n@app.route('/api//cors//', methods=['POST'])\ndef set_cors(apiversion, project, container):\n # Set CORS for container\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n 'X-Container-Meta-Access-Control-Allow-Origin': '*',\n 'X-Container-Meta-Access-Control-Expose-Headers': 'Content-Length,X-Object-Manifest'\n }\n r = requests.post(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) + '/' + container , headers=headers)\n if r.status_code != 204:\n abort(r.status_code)\n\n return jsonify({'msg': 'done'})\n\n@app.route('/api//project//', methods=['POST'])\n@requires_auth\ndef create_project_containers(apiversion, project, container):\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n }\n r = requests.put(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) + '/' + container +'?format=json', headers=headers)\n if r.status_code not in [201, 202]:\n abort(r.status_code)\n\n __set_quotas(project)\n '''\n # Set quota for user project\n if config['swift']['quotas']:\n admin_token = get_token({\n 'user': config['swift']['admin']['os_user_id'],\n 'password': config['swift']['admin']['os_user_password'],\n 'domain': config['swift']['admin']['os_user_domain'],\n 'project': config['swift']['admin']['os_user_project']\n })\n\n if admin_token:\n headers = {\n 'X-Auth-Token': admin_token,\n 'X-Account-Meta-Quota-Bytes': str(humanfriendly.parse_size(config['swift']['quotas']))\n }\n r = requests.post(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) , headers=headers)\n if r.status_code not in [200, 204]:\n logging.error('Quota error for ' + str(project) + ':' + r.text)\n #abort(r.status_code)\n '''\n\n # Set CORS for container\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n 'X-Container-Meta-Access-Control-Allow-Origin': '*',\n 'X-Container-Meta-Access-Control-Expose-Headers': 'Content-Length,X-Object-Manifest'\n }\n r = requests.post(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) + '/' + container , headers=headers)\n if r.status_code != 204:\n abort(r.status_code)\n\n return jsonify({'msg': 'container created'})\n\n\ndef get_tempurl(token, method, project, container, filepath):\n if method is None:\n method = 'GET'\n duration_in_seconds = 3600 * 24 * 30 # 30 days\n expires = int(time() + duration_in_seconds)\n path = '/v1/AUTH_' + project + '/' + container + '/' + str(filepath)\n url_path = '/v1/AUTH_' + project + '/' + container + '/' + urllib.parse.quote(str(filepath))\n key = crypt.crypt(project,'$6$' + config['salt_secret']).encode('utf-8')\n headers = {\n 'X-Auth-Token': token,\n 'X-Account-Meta-Temp-URL-Key': key,\n }\n r = requests.post(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) , headers=headers)\n if not r.status_code == 204:\n return None\n hmac_body = '%s\\n%s\\n%s' % (method, expires, path)\n sig = hmac.new(key, hmac_body.encode('utf-8'), sha1).hexdigest()\n s = '{host}/{path}?temp_url_sig={sig}&temp_url_expires={expires}'\n tmpurl = s.format(host=config['swift']['swift_url'], path=url_path, sig=sig, expires=expires)\n return tmpurl\n\n@app.route('/api//project///', methods=['GET'])\n@requires_auth\ndef download_via_tempurl(apiversion, project, container, filepath):\n ks_url = config['swift']['keystone_url'] + '/auth/tokens'\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n 'X-Subject-Token': request.headers['X-Auth-Token']\n }\n r = requests.get(ks_url, headers=headers)\n if not r.status_code == 200:\n abort(r.status_code)\n r_json = r.json()\n if r_json['token']['project']['id'] != project:\n abort(403)\n\n method = request.args.get('method', 'GET')\n token = request.headers['X-Auth-Token']\n tmpurl = get_tempurl(token, method, project, container, filepath)\n if not tmpurl:\n abort(500)\n return jsonify({'url': tmpurl})\n\n\n\n@app.route('/api//project//', methods=['HEAD'])\n@requires_auth\ndef get_project_container_meta(apiversion, project, container):\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n }\n # Get container info\n r = requests.head(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) + '/' + container+'?format=json' , headers=headers)\n if r.status_code != 204:\n abort(r.status_code)\n res = []\n resp = Response(\"\")\n for res_header in list(r.headers.keys()):\n if res_header.startswith('X-Container-'):\n resp.headers[res_header] = r.headers[res_header]\n return resp\n\n@app.route('/api//project//', methods=['GET'])\n@requires_auth\ndef get_project_container(apiversion, project, container):\n '''\n Set quotas and CORS\n\n # Set quota for user project\n '''\n __set_quotas(project)\n\n # Set CORS for container\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n 'X-Container-Meta-Access-Control-Allow-Origin': '*',\n 'X-Container-Meta-Access-Control-Expose-Headers': 'Content-Length,X-Object-Manifest,X-Container-Bytes-Used,X-Container-Object-Count'\n }\n r = requests.post(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) + '/' + container , headers=headers)\n if r.status_code != 204:\n abort(r.status_code)\n\n return jsonify({'url': config['swift']['swift_url'] + '/v1/AUTH_' + str(project) + '/' + container})\n\n\n@app.route('/api//index/project///', methods=['DELETE'])\n@requires_auth\ndef delete_index_container(apiversion, project, container, filepath):\n if not es:\n abort(403)\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n }\n r = requests.head(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) + '/' + container+'?format=json' , headers=headers)\n if r.status_code != 204:\n abort(r.status_code)\n docid = project+'_'+container+'_'+filepath.replace('/','_')\n try:\n es.delete(index=config['elastic']['index'] +'-' + project, doc_type='swift', id=docid, body=doc)\n except Exception as e:\n logging.error('Deletion error: ' + str(e))\n return jsonify({'msg': 'ok'})\n\n\n@app.route('/api//search/project//', methods=['POST'])\n@requires_auth\ndef search_index_container(apiversion, project, container):\n if not es:\n abort(403)\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n }\n r = requests.head(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) + '/' + container+'?format=json' , headers=headers)\n if r.status_code != 204:\n abort(r.status_code)\n data = request.get_json()\n # data['query'] : Lucene syntax\n res = None\n try:\n res = es.search(index=config['elastic']['index'] + '-' + project, q=data['query'], size=1000)\n except Exception as e:\n logging.error('Search error: ' + str(e))\n res = {'hits': {'hits': []}}\n return jsonify(res)\n\n\ndef __set_quotas(project):\n project_quota = humanfriendly.parse_size(config['swift']['quotas'], binary=True)\n\n for i in range(5):\n try:\n quota = db_quota.find_one({'id': project})\n if quota:\n project_quota = quota['quota']\n break\n except pymongo.errors.AutoReconnect:\n logger.warn('Mongo:AutoReconnect')\n time.sleep(pow(2, i))\n\n logging.debug('Set quota for project %s at %s' % (project, str(project_quota)))\n if project_quota:\n admin_token = get_token({\n 'user': config['swift']['admin']['os_user_id'],\n 'password': config['swift']['admin']['os_user_password'],\n 'domain': config['swift']['admin']['os_user_domain'],\n 'project': config['swift']['admin']['os_user_project']\n })\n\n if admin_token:\n headers = {\n 'X-Auth-Token': admin_token,\n 'X-Account-Meta-Quota-Bytes': str(project_quota)\n }\n r = requests.post(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) , headers=headers)\n if r.status_code not in [200, 204]:\n logging.error('Quota error for ' + str(project) + ':' + r.text)\n\ndef compare_name(a):\n return a['name']\n\n@app.route('/api//quota', methods=['GET'])\ndef get_projects_quota(apiversion):\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n 'X-Subject-Token': request.headers['X-Auth-Token']\n }\n ks_url = config['swift']['keystone_url'] + '/auth/tokens'\n r = requests.get(ks_url, headers=headers)\n if not r.status_code == 200:\n abort(r.status_code)\n ks_token = r.json()\n user = ks_token['token']['user']['name']\n if user not in config['admin']:\n abort(403)\n\n\n projects = []\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token']\n }\n ks_url = config['swift']['keystone_url'] + '/projects'\n r = requests.get(ks_url, headers=headers)\n if not r.status_code == 200:\n abort(r.status_code)\n ks_projects = r.json()['projects']\n\n quotas = db_quota.find()\n quotas_map = {}\n for quota in quotas:\n quotas_map[quota['id']] = quota['quota']\n # projects.append({'id': quota['id'], 'name': project_map[quota['id']], 'quota': quota['quota']})\n for project in ks_projects:\n if project['id'] in quotas_map:\n project['quota'] = quotas_map[project['id']]\n else:\n project['quota'] = humanfriendly.parse_size(config['swift']['quotas'], binary=True)\n projects.append({'id': project['id'], 'name': project['name'], 'quota': project['quota']})\n\n # projects.sort(key=compare_name)\n return jsonify({'projects': projects})\n\n@app.route('/api//quota/project/', methods=['POST'])\ndef update_project_quota(apiversion, project):\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n 'X-Subject-Token': request.headers['X-Auth-Token']\n }\n ks_url = config['swift']['keystone_url'] + '/auth/tokens'\n r = requests.get(ks_url, headers=headers)\n if not r.status_code == 200:\n abort(r.status_code)\n ks_token = r.json()\n user = ks_token['token']['user']['name']\n if user not in config['admin']:\n abort(403)\n\n data = request.get_json()\n quota = db_quota.find_one({'id': project})\n if quota:\n db_quota.update({'id': project},{'$set': {'quota': humanfriendly.parse_size(data['quota'], binary=True)}})\n else:\n db_quota.insert({'id': project, 'quota': humanfriendly.parse_size(data['quota'], binary=True)})\n __set_quotas(project)\n return jsonify({'project': project, 'quota': data['quota']})\n\n\ndef run_hook(request, project, container, filepath, apiversion='v1', force=False):\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n }\n result = True\n r = requests.head(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) + '/' + container+'?format=json' , headers=headers)\n if r.status_code != 204:\n abort(r.status_code)\n # Hooks\n hook = db_hooks.find_one({'project': project, 'bucket': container})\n if hook:\n if not force and 'regexp' in hook and hook['regexp']:\n if re.match(hook['regexp'], filepath) is None:\n return None\n uid = uuid.uuid4().hex\n token = request.headers['X-Auth-Token']\n method = request.args.get('method', 'GET')\n tmpurl = get_tempurl(token, method, project, container, filepath)\n data = {\n 'bucket': container,\n 'path': tmpurl,\n 'orig_path': filepath,\n 'id': uid,\n 'callback': {\n 'success': _get_base_url_from_request() + '/api/' + apiversion + '/hooks/' + uid + '/ok',\n 'failure': _get_base_url_from_request() + '/api/' + apiversion + '/hooks/' + uid + '/ko'\n }\n }\n try:\n res = requests.post(hook['url'], headers=headers, json=data)\n status = None\n if not res.status_code == 200:\n status = False\n db_hook.insert({'id': uid, 'project': project, 'status': status, 'bucket': container, 'file': filepath})\n except Exception as e:\n logging.exception('Failed to send hook notification: ' + str(hook['url']))\n result = False\n else:\n result = None\n return result\n\n\n@app.route('/api//hook///', methods=['POST'])\ndef test_hook_container(apiversion, project, container, filepath):\n res = run_hook(request, project, container, filepath, apiversion=apiversion, force=True)\n return jsonify({'msg': 'called hook', 'res': res})\n\n\n@requires_auth\n@app.route('/api//acl/project//', methods=['GET'])\ndef container_acl(apiversion, project, container):\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n 'X-Subject-Token': request.headers['X-Auth-Token']\n }\n ks_url = config['swift']['keystone_url'] + '/auth/tokens'\n r = requests.get(ks_url, headers=headers)\n if not r.status_code == 200:\n abort(r.status_code)\n r = requests.head(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) + '/' + container+'?format=json' , headers=headers)\n if r.status_code != 204:\n abort(r.status_code)\n web = r.headers.get('X-Container-Meta-Web-Listings', False)\n acl_read = r.headers.get('X-Container-Read', None)\n acl_write = r.headers.get('X-Container-Write', None)\n return jsonify({'acl_read': acl_read, 'acl_write': acl_write, 'web': web})\n\n@app.route('/api//index/project///', methods=['POST', 'PUT'])\ndef update_index_container(apiversion, project, container, filepath):\n logging.info(\"New document:\"+str(project)+\":\"+str(container)+\":\"+filepath)\n __set_quotas(project)\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n }\n run_hook(request, project, container, filepath, apiversion=apiversion)\n\n if not es:\n abort(403)\n\n r = requests.head(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) + '/' + container+'?format=json' , headers=headers)\n if r.status_code != 204:\n abort(r.status_code)\n docid = project+'_'+container+'_'+filepath.replace('/','_')\n metas =[]\n for header, value in request.headers.items():\n if header.startswith('X-Object-Meta-'):\n meta = {}\n meta[header.replace('X-Object-Meta-', '').lower()] = value\n metas.append(meta)\n doc = {\n 'project': project,\n 'container': container,\n 'object': str(filepath).split('/'),\n 'metadata': metas\n }\n es.indices.create(index=config['elastic']['index'] + '-' + project, ignore=400)\n es.index(index=config['elastic']['index'] + '-' + project, doc_type='swift', id=docid, body=doc)\n return jsonify({'msg': 'ok'})\n\n\n@app.route('/api//tempurl', methods=['POST'])\n@requires_auth\ndef send_tmpurl_email(apiversion):\n data = request.get_json()\n if not config['smtp']['host'] or not data.get('emails', None):\n abort(403)\n\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n 'X-Subject-Token': request.headers['X-Auth-Token']\n }\n ks_url = config['swift']['keystone_url'] + '/auth/tokens'\n r = requests.get(ks_url, headers=headers)\n if not r.status_code == 200:\n abort(r.status_code)\n ks_token = r.json()\n user = ks_token['token']['user']['name']\n\n msg = EmailMessage()\n msg.set_content(config['smtp']['share']['msg'].replace('#USER', user).replace('#URL', data['url']))\n msg['Subject'] = config['smtp']['share']['subject'].replace('#USER', user)\n msg['From'] = config['smtp']['from']\n msg['To'] = ','.join(data['emails'])\n\n # Send the message via our own SMTP server.\n s = smtplib.SMTP(host=config['smtp']['host'], port=config['smtp']['port'])\n s.send_message(msg)\n s.quit()\n return jsonify({'msg': 'invitation sent'})\n\n\n@app.route('/api//hook//', methods=['GET'])\n@requires_auth\ndef get_hook(apiversion, project,bucket):\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n }\n r = requests.get(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) +'?format=json', headers=headers)\n if r.status_code not in [200]:\n abort(r.status_code)\n hook = db_hooks.find_one({'project': project, 'bucket': bucket})\n url = None\n regexp = ''\n if hook:\n url = hook['url']\n if 'regexp' in hook:\n regexp = hook['regexp']\n\n return jsonify({'hook': url, 'regexp': regexp})\n\n\n@app.route('/api//hook//', methods=['POST'])\n@requires_auth\ndef set_hook(apiversion, project,bucket):\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n }\n r = requests.get(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) +'?format=json', headers=headers)\n if r.status_code not in [200]:\n abort(r.status_code)\n data = request.get_json()\n hook = db_hooks.find_one({'project': project, 'bucket': bucket})\n\n if hook:\n db_hooks.update({'project': project, 'bucket': bucket},{'$set': {'url': data['url'], 'regexp': data['regexp']}})\n else:\n db_hooks.insert({'project': project, 'bucket': bucket, 'url': data['url'], 'regexp': data['regexp']})\n\n return jsonify({'hook': data['url'], 'regexp': data['regexp']})\n\n\n@app.route('/api//hook/', methods=['GET'])\n@requires_auth\ndef get_hook_status(apiversion, project):\n headers = {\n 'X-Auth-Token': request.headers['X-Auth-Token'],\n }\n r = requests.get(config['swift']['swift_url'] + '/v1/AUTH_' + str(project) +'?format=json', headers=headers)\n if r.status_code not in [200]:\n abort(r.status_code)\n result = []\n hooks = db_hook.find({'project': project}).sort([('_id', pymongo.DESCENDING)]).limit(500)\n for hook in hooks:\n del hook['_id']\n result.append(hook)\n return jsonify({'hooks': result})\n\n\n@app.route('/api//hooks//', methods=['POST'])\ndef set_hook_status(apiversion, hookid, status):\n '''\n Status can be set to 0,ko,false for failure, other is considered as success\n '''\n data = request.get_json()\n hook_status = True\n if status.lower() in ['0', 'ko', 'false']:\n hook_status = False\n db_hook.update({'id': hookid},{'$set': {'status': hook_status, 'info': data}})\n return jsonify({'status': status})\n\n\nif __name__ == \"__main__\":\n context = None\n if config['tls']['cert']:\n context = ssl.SSLContext(ssl.PROTOCOL_TLSv1_2)\n context.load_cert_chain(config['tls']['cert'], config['tls']['key'])\n app.run(host=config['listen']['ip'], port=config['listen']['port'], ssl_context=context, threaded=True, debug=config['debug'])\n","sub_path":"goswift/app.py","file_name":"app.py","file_ext":"py","file_size_in_byte":31907,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"606470428","text":"from adventofcode.y2019 import aoc\nimport time\nfrom functools import lru_cache\n\n\ndef day_10_part_1(data):\n return get_differences(data)\n\n\ndef get_differences(soln):\n jolt_one_diffs = sum((1 for i, j in zip(soln[:-1], soln[1:]) if j - i == 1))\n jolt_three_diffs = sum((1 for i, j in zip(soln[:-1], soln[1:]) if j - i == 3))\n return jolt_one_diffs, jolt_three_diffs, jolt_one_diffs * jolt_three_diffs\n\n\ndef day_10_part_2():\n return get_valid_solutions()\n\n\n@lru_cache()\ndef get_valid_solutions(root_idx=0, total=0):\n if root_idx == len(data) - 2:\n return 1\n\n valid_children = get_valid_children(root_idx)\n\n valid_children_solutions = 0\n for child_idx in valid_children:\n valid_children_solutions += get_valid_solutions(child_idx, total)\n\n return total + valid_children_solutions\n\n\ndef get_valid_children(root_idx):\n valid_children = []\n i = 1\n while data[root_idx + i] <= data[root_idx] + 3:\n valid_children.append(root_idx + i)\n i += 1\n return valid_children\n\n\nif __name__ == \"__main__\":\n t0 = time.perf_counter()\n\n data = aoc.load_data(r\"day_10_data.txt\")\n data = sorted(int(x) for x in data)\n data = [0] + data + [data[-1] + 3]\n print(day_10_part_2())\n\n print(time.perf_counter() - t0)\n","sub_path":"adventofcode/y2020/day_10.py","file_name":"day_10.py","file_ext":"py","file_size_in_byte":1274,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"632061801","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Oct 7 07:30:30 2015\n\n@author: John\n\nThis file includes functions needed to do k-means or PAM clustering. \nSee comments in functions to understand how they work. \n\nJoel Grus's code from an early version, ported over to Python 3\nbefore Joel did it. \n\n\"\"\"\n\n# Code to perform k-means clustering, from _Data Science from Scratch_\nimport random\nimport matplotlib.image as mpimg\nimport matplotlib.pyplot as plt\n\n\n# First, some linear algebra functions. K-means likes these, but PAM \n# doesn't need them. \ndef scalar_multiply(c, v):\n return( [c * v_i for v_i in v])\n\ndef vector_mean(vectors):\n \"\"\"compute the vector whose i-th element is the mean of the\n i-th elements of the input vectors\"\"\"\n n = len(vectors)\n return(scalar_multiply(1/n, vector_sum(vectors)))\n\ndef vector_add(v, w):\n \"\"\"adds two vectors componentwise\"\"\"\n return( [v_i + w_i for v_i, w_i in zip(v,w)])\n\ndef vector_subtract(v, w):\n \"\"\"subtracts two vectors componentwise\"\"\"\n return([v_i - w_i for v_i, w_i in zip(v,w)])\n\ndef vector_sum(vectors):\n total = []\n for vec in vectors :\n if total :\n total = vector_add(total, vec)\n else :\n total = vec\n return(total)\n\ndef squared_distance(v, w):\n return( sum_of_squares(vector_subtract(v, w)))\n\ndef dot(v, w):\n \"\"\"v_1 * w_1 + ... + v_n * w_n\"\"\"\n return (sum(v_i * w_i for v_i, w_i in zip(v, w)))\n\ndef sum_of_squares(v):\n \"\"\"v_1 * v_1 + ... + v_n * v_n\"\"\"\n return( dot(v, v))\n\n\n# K-means functions\ndef classify(input, means, k) :\n \"\"\"return the index of the cluster closest to the input\"\"\"\n return (min(range(k),\n key=lambda i: squared_distance(input, means[i])))\n\n\ndef train(inputs, k) :\n \"\"\" fit a k-means model. Input \"\"\"\n means = random.sample(inputs, k)\n assignments = None\n\n while True:\n # Find new assignments\n new_assignments = [classify(input, means, k) for input in inputs]\n\n # If no assignments have changed, we're done.\n if assignments == new_assignments:\n return(assignments, means)\n\n # Otherwise keep the new assignments,\n assignments = new_assignments\n\n for i in range(k):\n i_points = [p for p, a in zip(inputs, assignments) if a == i]\n # avoid divide-by-zero if i_points is empty\n if i_points:\n means[i] = vector_mean(i_points)\n\ndef train_dict(input_dict, k, dd = None) :\n \"\"\" fit a k-means model to a dictionary\n of lists. First it builds a list of lists\n and calls train. Then it returns a dictionary\n for assignments a list for means.\n\n Takes an optional argument dd that is a dictionary\n of distances of the form dd[a][b] = distance_between_a_and_b\n\n \"\"\"\n inputs = []\n key_list = []\n for kk,v in input_dict.items() :\n key_list.append(kk)\n inputs.append(v)\n\n assignments, means = train(inputs,k)\n assignments_dict = dict()\n\n for idx, kk in enumerate(key_list) :\n assignments_dict[kk] = assignments[idx]\n\n return(assignments_dict,means)\n\n\n# PAM functions. \ndef get_dist(o1,o2,dists) :\n \"\"\" \n helper function to get distances out of 2d dict of dists\n \"\"\"\n if o1 in dists and o2 in dists[o1] :\n return(dists[o1][o2])\n else :\n return(dists[o2][o1])\n\n\ndef pam_classify (owners, meds, dists) :\n ''' puts owners into clusters. \n Input: owners (a set of all owners)\n meds (the current medoids)\n dists (distance dictionary with dists[o1][o2] = dist)\n Output: a dictionary with key of owner and value of cluster\n '''\n \n ret_dict = dict()\n k = len(meds)\n \n for own in owners :\n ret_dict[own] = min(range(k),\n key=lambda i: get_dist(own, meds[i], dists))\n \n return(ret_dict)\n\ndef get_pam_medoids(assgn, dists) :\n \"\"\"\n Returns a set of owners that are the medoid of their\n cluster. The list order is arranged along 0, ..., k-1.\n Input: assgn: dictionary of owner -> cluster\n dists: distance dictionary\n \n Output: a list of owners who are the medoids for the clusters.\n \"\"\"\n\n def _get_total_distance(m1, owns) :\n # Gets the distance for a medoid candidate.\n d = 0\n for o1 in owns :\n d += get_dist(m1,o1,dists)\n return(d) \n \n k = max(assgn.values()) + 1 \n \n ret_meds = [] \n for i in range(k) :\n owners = [own for own, clust in assgn.items() if clust==i]\n tot_dists = [_get_total_distance(own,owners) for own in owners] \n\n lowest_index = min(range(len(owners)),\n key=lambda idx: tot_dists[idx]) \n \n ret_meds.append(owners[lowest_index]) \n \n return(ret_meds) \n\ndef PAM(dd, k) :\n \"\"\"\n takes in distance data and desired k. returns clustering output.\n \n Input\n dd: a dictionary with two keys, k1 and k2. k1 is an owner, \n k2 is an owner, and the value is the distance between them.\n k: desired number of clusters.\n Output\n assignments: a dictionary of owner to cluster\n medoids: a dictionary of the cluster centers\n \"\"\"\n \n # Generate our list of owners\n owner_set = set(dd.keys())\n for owner in dd :\n for o2 in dd[owner] :\n owner_set.add(o2)\n \n medoids = random.sample(owner_set,k)\n assignments = None\n \n counter = 0\n while True :\n counter += 1\n if counter > 10 :\n break\n\n # assign owners to medoids \n new_assignments = pam_classify(owner_set, medoids, dd)\n\n # Nothing changed? let's boogie...\n if assignments == new_assignments:\n return(assignments, medoids)\n else :\n assignments = new_assignments\n\n # calculate new medoids. \n medoids = get_pam_medoids(new_assignments, dd)\n\n\nprint(\"Clustering Code Loaded\")","sub_path":"clustering/clustering_code.py","file_name":"clustering_code.py","file_ext":"py","file_size_in_byte":6081,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"629171692","text":"\"\"\"\nMIT License\n\nCopyright (c) 2019 ming\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n===============================\n@File : pathPlaner2.py\n@Author: ming.ustb@outlook.com\n@Date : 19-5-30\n@GitHub: https://github.com/yangmingustb/PTPSim\nx-y graph\n\"\"\"\n\n\nimport matplotlib.pyplot as plt\nimport math\nimport TrajectoryPlanning.PathCost as CostFunction\nimport Curves.Cubic as cubic\nimport model.simModel as car\nimport Scenarios.multiLane as mlane\nimport Curves.cubic_spline as cubicSpline\nimport FrenetMath.FrenetToCartesian as ftc\nimport TrajectoryPlanning.pathLatticeXY2 as pathlattice\n\n\nshow_vehicle_animation = False\nshow_sample_point = False\nshow_lane = True\nshow_obstacle = True\nshow_rough_path = True\nshowPathLattice = True\n\ns_max = 100.0\nlongi_num = 5\nlateral_num = 9 # 横向采样个数\nlongi_step = 20.0\nlatera_step = 0.5\nlane_width = 3.75\nnumberUnderRefLine = lateral_num//2 # sampling number under reference line\ns0 = 0.0\ns_end=s0+s_max\nrefLineRho = lane_width*0.5\nstart_SRho = [s0, refLineRho, 0.0 * math.pi / 180.0]\n# start_XY = [-5.285, 1.924, 70.0 * math.pi / 180.0]\n\nobstacle = [[20, refLineRho - 1], [40, refLineRho + 2], [70, refLineRho + 2]] # 障碍物的frenet坐标,\nobstacleHeading=0.0 * math.pi / 180.0\n\nlast_column_id = [lateral_num * longi_num, lateral_num * (longi_num-1) + 1] # 最后一列的编号\n\n\nclass Node:\n\n\tdef __init__(self, x, y, cost, pind):\n\t\t\"\"\"\n\n\t\t:param x:\n\t\t:param y:\n\t\t:param cost: 累计最小代价\n\t\t:param pind: 指针，指向父节点\n\t\t\"\"\"\n\t\tself.x = x\n\t\tself.y = y\n\t\tself.cost = cost\n\t\tself.pind = pind\n\n\tdef __str__(self):\n\t\treturn str(self.x) + \",\" + str(self.y) + \",\" + str(self.cost) + \",\" + str(self.pind)\n\n\ndef dijkstra_planning(start, longitudinal_step, lateral_step, lateral_number, efficients):\n\t\"\"\"\n\n\t:param start:\n\t:param dyn_obs:\n\t:param longitudinal_step:\n\t:param lateral_step:\n\t:param longitudinal_number:\n\t:param lateral_number:\n\t:return:\n\t\"\"\"\n\n\tnstart = Node(start[0], start[1], 0.0, -1)\n\n\tchild_node = get_children_node(longitudinal_step, lateral_step)\n\n\topen_set, closed_set = dict(), dict() # build empty dict\n\topen_set[0] = nstart\n\n\twhile True:\n\t\tif not open_set:\n\t\t\tbreak\n\n\t\tc_id = min(open_set, key=lambda o: open_set[o].cost)\n\t\tcurrent = open_set[c_id]\n\t\tprint(\"current\", current)\n\n\t\t# show graph\n\t\tif show_sample_point:\n\t\t\tplt.plot(current.x, current.y, \"oc\")\n\n\t\t# Remove the item from the open set\n\t\tdel open_set[c_id]\n\t\t# Add it to the closed set\n\t\tclosed_set[c_id] = current\n\n\t\t# expand search grid based on motion model\n\t\tfor i in range(len(child_node)):\n\t\t\tnode = Node(current.x + child_node[i][0], child_node[i][1], current.cost, c_id)\n\t\t\tcost = CostFunction.total_cost(current, node, obstacle, refLineRho, efficients)\n\t\t\tnode.cost = node.cost + cost\n\t\t\tn_id = calc_index(node, nstart, longitudinal_step, lateral_step, lateral_number)\n\n\t\t\tif node.x > s_end:\n\t\t\t\tbreak\n\n\t\t\tif n_id in closed_set:\n\t\t\t\tcontinue\n\t\t\t# Otherwise if it is already in the open set\n\t\t\telif n_id in open_set:\n\t\t\t\tif open_set[n_id].cost > node.cost:\n\t\t\t\t\topen_set[n_id].cost = node.cost\n\t\t\t\t\topen_set[n_id].pind = c_id\n\t\t\telse:\n\t\t\t\topen_set[n_id] = node\n\n\treturn closed_set\n\n\ndef calc_index(node, nstart, longitudinal_step, lateral_step, latera_num):\n\t\"\"\"\n\n\t:param node: 子节点\n\t:param nstart: 起点\n\t:param longitudinal_step:\n\t:param lateral_step:\n\t:param latera_num:横向采样点个数\n\t:return:\n\t\"\"\"\n\tid = (node.y - (refLineRho-numberUnderRefLine*lateral_step)) / lateral_step + ((node.x - nstart.x) / longitudinal_step - 1) * latera_num + 1\n\treturn id\n\n\ndef get_children_node(longitudinal_step, lateral_step):\n\t\"\"\"\n\n\t:param longitudinal_step:\n\t:param lateral_number:\n\t:return:\n\t\"\"\"\n\tmotion = []\n\tfor i in range(lateral_num):\n\t\ttmp_motion = [longitudinal_step, (i - numberUnderRefLine) * lateral_step + refLineRho]\n\t\tmotion.append(tmp_motion)\n\n\treturn motion\n\n\ndef determine_goal(closed_set):\n\t\"\"\"\n\n\t:param closed_set:\n\t:return: 找到最后一列采样点里面的目标点\n\t\"\"\"\n\ttem_dic = dict()\n\tprint('len(closedset):', len(closed_set))\n\tprint('closedSet:', closed_set)\n\tfor i in range(last_column_id[1], last_column_id[0] + 1):\n\t\tprint(closed_set[i])\n\t\ttem_dic[i] = closed_set[i]\n\n\tc_id = min(tem_dic, key=lambda o: tem_dic[o].cost)\n\tgoal = tem_dic[c_id]\n\n\treturn goal\n\n\ndef calc_final_path(ngoal, closedset):\n\t# generate final course\n\trx, ry = [ngoal.x], [ngoal.y]\n\tpind = ngoal.pind\n\twhile pind != -1:\n\t\tn = closedset[pind]\n\t\trx.append(n.x)\n\t\try.append(n.y)\n\t\tpind = n.pind\n\n\treturn rx, ry\n\n\ndef plotGraph():\n\tprint(__file__ + \" start!!\")\n\tplt.figure(figsize=(3.5, 3.0)) # 单位英寸， 3.5\n\tp1 = [0.15, 0.15, 0.80, 0.8]\n\tplt.axes(p1)\n\tplt.axis(\"equal\")\n\tplt.grid(linestyle=\"--\", linewidth=0.5, alpha=1)\n\n\t# # 计算多车道环境的弧长参数曲线的系数\n\t# efficients = multiLane.saveEfficients()\n\n\t# 计算回环环境的弧长参数曲线的系数\n\tefficients = cubicSpline.saveEfficients()\n\n\t# if show_lane:\n\t# \t# show multilane\n\t# \tmlane.curvePath()\n\n\tif show_obstacle:\n\t\tfor i in range(len(obstacle)):\n\t\t\tx, y, theta = ftc.frenetToXY(obstacle[i][0], obstacle[i][1], obstacleHeading, efficients)\n\t\t\tcar.simVehicle([x, y], theta, 'r', 0.8)\n\n\t#\tsampling_point = PathLattice.sampling(longitudinal_num, lateral_num, latera_step, longitudinal_step)\n\t#\t用来显示lattice图像\n\t# PathLattice.generate_lattice()\n\n\tclosed_set = dijkstra_planning(start_SRho, longi_step, latera_step, lateral_num, efficients)\n\t# print('----------------------------------')\n\t# print('closed_set:', len(closed_set))\n\n\tgoal = determine_goal(closed_set)\n\trx, ry = calc_final_path(goal, closed_set)\n\t#\tprint(\"rx, ry: %s\" % rx, ry)\n\n\ttmp_s = []\n\ttmp_rho = []\n\ttmp_thetaRho = []\n\tfor i in range(len(rx) - 1):\n\t\tpoint_s = [rx[-(i + 1)], ry[-(i + 1)], 0.0 * math.pi / 180.0]\n\t\tpoint_e = [rx[-(i + 2)], ry[-(i + 2)], 0.0 * math.pi / 180.0]\n\t\ts, rho, thetaRho = cubic.Polynomial(point_s, point_e)\n\t\ttmp_s.extend(s)\n\t\ttmp_rho.extend(rho)\n\t\ttmp_thetaRho.extend(thetaRho)\n\n\tif showPathLattice:\n\t\tpathlattice.ToPathPlanner2(efficients)\n\tx = []\n\ty = []\n\ttheta = []\n\tif show_rough_path:\n\t\t# print(s)\n\t\tfor j in range(len(tmp_s)):\n\t\t\ttmpX, tmpY, tmpTheta = ftc.frenetToXY(tmp_s[j], tmp_rho[j], tmp_thetaRho[j], efficients)\n\t\t\tx.append(tmpX)\n\t\t\ty.append(tmpY)\n\t\t\ttheta.append(tmpTheta)\n\t\t# plt.scatter(end_set[0, i][0], end_set[0, i][1], color='b', s=2, alpha=0.8)\n\t\tplt.plot(x, y, 'magenta', linewidth=0.5, alpha=1)\n\n\tif show_vehicle_animation:\n\t\tx0, y0, theta0 = ftc.frenetToXY(start_SRho[0], start_SRho[1], start_SRho[2], efficients)\n\t\tcar.simVehicle([x0, y0], theta0, 'g', 1)\n\n\t\ttime_stamp = 0\n\t\tfor j in range(0, len(tmp_s), 50):\n\t\t\ttime_stamp = tmp_s[j] / s_max\n\t\t\tcar.simVehicle([x[j], y[j]], theta[j], 'b', time_stamp)\n\t\t\tplt.pause(0.01)\n\n\tfont1 = {'family': 'Times New Roman',\n\t 'weight': 'normal',\n\t 'size': 10,\n\t }\n\tplt.xlabel(\"x (m)\", font1)\n\tplt.ylabel('y (m)', font1)\n\tplt.xticks(fontproperties='Times New Roman', fontsize=10)\n\tplt.yticks(fontproperties='Times New Roman', fontsize=10)\n\tplt.xlim(-10, 30)\n\tplt.ylim(-5, 80)\n\t# plt.savefig('/home/ming/桌面/PTPSim/SimGraph/pathPlannerXY_5_30_8_48.svg')\n\tplt.savefig('../SimGraph/pathPlanner2_061101.tiff', dpi=600)\n\tplt.show()\n\n\ndef ToPathOptimizer2(efficients):\n\tclosed_set = dijkstra_planning(start_SRho, longi_step, latera_step, lateral_num, efficients)\n\t# print('----------------------------------')\n\t# print('closed_set:', len(closed_set))\n\n\tgoal = determine_goal(closed_set)\n\trx, ry = calc_final_path(goal, closed_set)\n\t#\tprint(\"rx, ry: %s\" % rx, ry)\n\n\ttmp_s = []\n\ttmp_rho = []\n\ttmp_thetaRho = []\n\tfor i in range(len(rx) - 1):\n\t\tpoint_s = [rx[-(i + 1)], ry[-(i + 1)], 0.0 * math.pi / 180.0]\n\t\tpoint_e = [rx[-(i + 2)], ry[-(i + 2)], 0.0 * math.pi / 180.0]\n\t\ts, rho, thetaRho = cubic.Polynomial(point_s, point_e)\n\t\ttmp_s.extend(s)\n\t\ttmp_rho.extend(rho)\n\t\ttmp_thetaRho.extend(thetaRho)\n\tx = []\n\ty = []\n\ttheta = []\n\tif show_rough_path:\n\t\t# print(s)\n\t\tfor j in range(len(tmp_s)):\n\t\t\ttmpX, tmpY, tmpTheta = ftc.frenetToXY(tmp_s[j], tmp_rho[j], tmp_thetaRho[j], efficients)\n\t\t\tx.append(tmpX)\n\t\t\ty.append(tmpY)\n\t\t\ttheta.append(tmpTheta)\n\t\t# plt.scatter(end_set[0, i][0], end_set[0, i][1], color='b', s=2, alpha=0.8)\n\t\tplt.plot(x, y, 'magenta', linewidth=0.4, alpha=1)\n\treturn \ttmp_s, tmp_rho,\ttmp_thetaRho\n\n\nif __name__ == '__main__':\n\tplotGraph()","sub_path":"TrajectoryPlanning/pathPlaner2.py","file_name":"pathPlaner2.py","file_ext":"py","file_size_in_byte":9271,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"614467137","text":"'''\n@Author : sean cheng\n@Email : aya234@163.com\n@CreateTime : 2018/7/14\n@Program : 游戏结束和统计正确率的界面\n'''\nimport pygame\nfrom pygame.locals import *\n\n\ndef end_game(SURFACE, globalVar, score, right_score, totalNum):\n # 游戏的结束界面，对刚才完过的游戏做出一些数据统计。\n score_img, score_rect = globalVar.maketext(globalVar.globalFont, '最终总成绩： ' + str(score),\n globalVar.color_dict['orange'])\n score_rect.top = 150\n score_rect.centerx = SURFACE.get_rect().centerx\n\n total_right_percent = right_score / totalNum * 100\n right_img, right_rect = globalVar.maketext(globalVar.globalFont, '正确率： ' + str(total_right_percent) + ' %',\n globalVar.color_dict['orange'])\n right_rect.top = 200\n right_rect.centerx = SURFACE.get_rect().centerx\n\n right_score_img, right_score_rect = globalVar.maketext(globalVar.globalFont, '正确题数： ' + str(right_score),\n globalVar.color_dict['orange'])\n right_score_rect.top = 250\n right_score_rect.centerx = SURFACE.get_rect().centerx\n\n bg_img = pygame.image.load('img/end_bg.jpg').convert_alpha()\n bg_rect = bg_img.get_rect()\n bg_rect.center = SURFACE.get_rect().center\n\n bg_fill = pygame.Rect((0, 0), (400, 300))\n bg_fill.centerx = SURFACE.get_rect().centerx\n bg_fill.top = 80\n\n bt_back = pygame.Rect((0, 0), (180, 60))\n bt_back.centerx = SURFACE.get_rect().centerx - 120\n bt_back.bottom = 580\n back_img, back_rect = globalVar.maketext(globalVar.globalFont, '返回标题', globalVar.color_dict['white'])\n back_rect.center = bt_back.center\n\n bt_exit = pygame.Rect((0, 0), (180, 60))\n bt_exit.centerx = SURFACE.get_rect().centerx + 120\n bt_exit.bottom = 580\n exit_img, exit_rect = globalVar.maketext(globalVar.globalFont, '退出游戏', globalVar.color_dict['white'])\n exit_rect.center = bt_exit.center\n\n while True:\n SURFACE.blit(bg_img, bg_rect)\n pygame.draw.rect(SURFACE, globalVar.color_dict['white'], bg_fill)\n pygame.draw.rect(SURFACE, globalVar.color_dict['gold'], bg_fill, 4)\n SURFACE.blit(score_img, score_rect)\n SURFACE.blit(right_score_img, right_score_rect)\n SURFACE.blit(right_img, right_rect)\n\n pygame.draw.rect(SURFACE, globalVar.color_dict['orange'], bt_back)\n pygame.draw.rect(SURFACE, globalVar.color_dict['orange'], bt_exit)\n\n for event in pygame.event.get():\n if event.type == QUIT:\n globalVar.close_program()\n elif event.type == KEYUP:\n if event.key == K_ESCAPE:\n globalVar.close_program()\n # elif event.key == K_RETURN:\n # return 'reset'\n pygame.mouse.set_visible(True)\n\n x, y = pygame.mouse.get_pos()\n pressed = pygame.mouse.get_pressed()\n\n if bt_back.collidepoint(x, y):\n pygame.draw.rect(SURFACE, globalVar.color_dict['lime'], bt_back)\n for event in pressed:\n if event == 1:\n return 'reset'\n\n if bt_exit.collidepoint(x, y):\n pygame.draw.rect(SURFACE, globalVar.color_dict['lime'], bt_exit)\n for event in pressed:\n if event == 1:\n globalVar.close_program()\n\n SURFACE.blit(back_img, back_rect)\n SURFACE.blit(exit_img, exit_rect)\n\n pygame.display.update()\n pygame.time.Clock().tick(30)\n","sub_path":"questions/GameEnd.py","file_name":"GameEnd.py","file_ext":"py","file_size_in_byte":3601,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"191418779","text":"import string\r\n\r\n\r\ndef caesarCipher(s, k):\r\n if k > 26:\r\n k = k%26\r\n alpha = list(string.ascii_lowercase)\r\n## print(alpha)\r\n alphaMod = alpha[k:] + alpha[:k]\r\n## print(alphaMod)\r\n Alpha = list(string.ascii_uppercase)\r\n## print(Alpha)\r\n AlphaMod = Alpha[k:] + Alpha[:k]\r\n## print(AlphaMod)\r\n letras = list(s)\r\n for char in range(len(letras)):\r\n if letras[char] in alpha:\r\n letras[char] = alphaMod[alpha.index(letras[char])]\r\n elif letras[char] in Alpha:\r\n letras[char] = AlphaMod[Alpha.index(letras[char])]\r\n return ''.join(letras)\r\n\r\n\r\nif __name__ == '__main__':\r\n n = int(input())\r\n\r\n s = input()\r\n\r\n k = int(input())\r\n\r\n result = caesarCipher(s, k)\r\n\r\n print(result)\r\n","sub_path":"HackerRank/problemSolving/Caesar Cipher.py","file_name":"Caesar Cipher.py","file_ext":"py","file_size_in_byte":764,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"63867713","text":"import re\n\ndef word_count(input):\n stripStr = re.sub(r'[!&@$%^:,]', '', input)\n stripStr = stripStr.lower()\n stripStr = stripStr.split()\n\n wordsDict = {}\n\n for word in stripStr:\n if not word in wordsDict.keys():\n wordsDict[word] = 1\n else:\n wordsDict[word] = wordsDict[word] + 1\n \n return wordsDict\n","sub_path":"all_data/exercism_data/python/word-count/1881d7ea8a744962aa9756e1439558af.py","file_name":"1881d7ea8a744962aa9756e1439558af.py","file_ext":"py","file_size_in_byte":364,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"177655028","text":"import numpy as np\n\n\nclass PointSolver:\n def __init__(self, n_mus, verbose=False):\n self.n = int((n_mus + 1)/2)\n n = self.n\n self.pmus = None\n self.mmat = np.zeros(shape=(n, n))\n self.locs = None\n self.weights = None\n self.is_discrete = False\n\n self.verbose = verbose\n\n def solve(self, pmus: np.ndarray):\n self.pmus = pmus / pmus[0]\n n = self.n\n\n for i in range(n):\n for j in range(n):\n self.mmat[i, j] = self.pmus[i + j]\n\n self.is_discrete = False\n n_points = n-1\n cur_det = 1.0\n for i in range(1, n):\n new_det = np.linalg.det(self.mmat[:i,:i])\n ratio = new_det / cur_det\n cur_det = new_det\n if self.verbose:\n print(\"eig ratio: {}\".format(ratio))\n if ratio < 1e-10:\n n_points = i-1\n self.is_discrete = True\n break\n\n n = n_points + 1\n short_mat = self.mmat[:n - 1, :n]\n coeffs = np.array([\n (-1) ** i * np.linalg.det(np.delete(short_mat, i, 1))\n for i in range(n)\n ])\n self.locs = np.roots(coeffs[::-1])\n A = np.vstack([self.locs ** i for i in range(n_points)])\n b = self.pmus[:n_points]\n self.weights = np.linalg.solve(A, b)\n\n i_order = np.argsort(self.locs)\n self.locs = self.locs[i_order]\n self.weights = self.weights[i_order]\n if self.verbose:\n print(self.locs, self.weights)\n return self.locs, self.weights\n\n def get_quantile(self, p:float) -> float:\n n = len(self.weights)\n if p <= 0.0:\n return self.locs[0]\n if p >= 1.0:\n return self.locs[-1]\n total = 0.0\n for i in range(n):\n total += self.weights[i]\n if total > p:\n return self.locs[i]","sub_path":"pysolver/pointsolver.py","file_name":"pointsolver.py","file_ext":"py","file_size_in_byte":1917,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"500124012","text":"import tkinter\nimport random\nimport sys\nimport os\n\n# Globals\nWIDTH = 800\nHEIGHT = 600\nSEG_SIZE = 40\nPERCENT_SNAKE_OF_SCREEN_FOR_WIN = 70\nADD_SNAKE_PER_APPLE = 10\nSPEED = 6\nBUFFER_VECTOR_SIZE = 10\n\nIN_GAME = True\nWIN_GAME = False\nPAUSE_BETWEEN_FRAME = int(1000/SPEED-50)\nSNAKE_LENGTH_WIN_GAME = WIDTH/SEG_SIZE*HEIGHT/SEG_SIZE * PERCENT_SNAKE_OF_SCREEN_FOR_WIN / 100\n\n\n# Helper functions\ndef create_block():\n \"\"\" Creates an apple to be eaten \"\"\"\n global BLOCK\n global SPEED\n posx = SEG_SIZE * random.randint(1, (WIDTH-SEG_SIZE) / SEG_SIZE)\n posy = SEG_SIZE * random.randint(1, (HEIGHT-SEG_SIZE) / SEG_SIZE)\n BLOCK = c.create_oval(posx, posy,\n posx+SEG_SIZE, posy+SEG_SIZE,\n fill=\"red\")\n\ndef create_percent():\n global prcnt\n prcnt = c.create_text(WIDTH/2, 20,\n text=str(int(len(s.segments)/SNAKE_LENGTH_WIN_GAME*100)) + \"% SPEED:\" + str(SPEED),\n font=\"Arial 20 bold\",\n fill=\"blue\")\n\ndef main():\n \"\"\" Handles game process \"\"\"\n global IN_GAME\n global WIN_GAME\n global PAUSE_BETWEEN_FRAME\n if IN_GAME:\n s.get_vector_buffer()\n s.move()\n c.delete(prcnt)\n create_percent()\n head_coords = c.coords(s.segments[-1].instance)\n x1, y1, x2, y2 = head_coords\n # Check for collision with gamefield edges\n if x2 > WIDTH or x1 < 0 or y1 < 0 or y2 > HEIGHT:\n IN_GAME = False\n # Eating apples\n elif head_coords == c.coords(BLOCK):\n# increase snake\n for index in range(ADD_SNAKE_PER_APPLE):\n s.add_segment()\n# add apple on cover, try freeplace (no snake) in cycle\n index2 = 0\n whileend = False\n while index2 < 10 and not whileend:\n whileend = True\n index2 += 1\n c.delete(BLOCK)\n create_block()\n for index in range(len(s.segments)-1):\n if c.coords(BLOCK) == c.coords(s.segments[index].instance):\n whileend = False\n break\n\n # Wining\n elif len(s.segments)>SNAKE_LENGTH_WIN_GAME:\n IN_GAME = False\n WIN_GAME = True\n # Self-eating\n else:\n for index in range(len(s.segments)-1):\n if head_coords == c.coords(s.segments[index].instance):\n IN_GAME = False\n root.after(PAUSE_BETWEEN_FRAME, main)\n\n\n # Not IN_GAME -> stop game and print message\n else:\n if WIN_GAME:\n c.create_text(WIDTH/2, HEIGHT/2,\n text=\"Congratulations\\nYou have WON!!!\\n---\\n0-9 - speed\\nSpace - restart\\nEsc - exit\",\n font=\"Arial 30 bold\",\n fill=\"red\",\n justify=\"center\")\n else:\n c.create_text(WIDTH/2, HEIGHT/2,\n text=\"GAME OVER!\\n---\\n0-9 - speed\\nSpace - restart\\nEsc - exit\",\n font=\"Arial 20 bold\",\n fill=\"red\",\n justify=\"center\")\n\n\n\nclass Segment(object):\n \"\"\" Single snake segment \"\"\"\n def __init__(self, x, y):\n self.instance = c.create_rectangle(x, y,\n x+SEG_SIZE, y+SEG_SIZE,\n fill=\"white\")\n\n\nclass Snake(object):\n \"\"\" Simple Snake class \"\"\"\n def __init__(self, segments):\n self.segments = segments\n # possible moves\n self.mapping = {\"Down\": (0, 1), \"Right\": (1, 0),\n \"Up\": (0, -1), \"Left\": (-1, 0)}\n # initial movement direction\n self.vector = self.mapping[\"Right\"]\n self.vector_buffer = [\"Right\"]\n\n def move(self):\n \"\"\" Moves the snake with the specified vector\"\"\"\n# add head segment\n self.segments.append(Segment(c.coords(self.segments[-1].instance)[0] + self.vector[0]*SEG_SIZE,\n c.coords(self.segments[-1].instance)[1] + self.vector[1]*SEG_SIZE))\n# del last segment\n c.delete(self.segments[0].instance)\n del self.segments[0]\n\n def add_segment(self):\n \"\"\" Adds segment to the snake \"\"\"\n last_seg = c.coords(self.segments[0].instance)\n x = last_seg[2] - SEG_SIZE\n y = last_seg[3] - SEG_SIZE\n self.segments.insert(0, Segment(x, y))\n\n def keypress(self, event):\n global PAUSE_BETWEEN_FRAME\n global SPEED\n# Add key to buffer\n# Awesome trick for filter back move (eat himself) using abs and ord functions.\n# Me know what this bad for big programs.\n if len(self.vector_buffer) < BUFFER_VECTOR_SIZE + 1\\\n and event.keysym in self.mapping\\\n and abs(ord(self.vector_buffer[-1][1])-ord(event.keysym[1]))>5:\n self.vector_buffer.append(event.keysym)\n# Speed controll\n elif ord(event.keysym[0]) >= ord('0') and ord(event.keysym[0]) <= ord('9'):\n if ord(event.keysym[0]) == ord('0'):\n SPEED=int(10)\n PAUSE_BETWEEN_FRAME = int(50)\n else:\n SPEED=ord(event.keysym[0])-ord('0')\n PAUSE_BETWEEN_FRAME = int(1000/SPEED-50)\n# Exit Game by Esc\n elif event.keysym == \"Escape\":\n sys.exit()\n# Restart\n elif event.keysym == \"space\":\n os.system('python3 snake.py')\n sys.exit()\n\n\n def get_vector_buffer(self):\n if len(self.vector_buffer) > 1:\n self.vector = self.mapping[self.vector_buffer[1]]\n del self.vector_buffer[0]\n\n# Setting up window\nroot = tkinter.Tk()\nroot.title(\"ExtraSnake\")\n# move windows\nroot.geometry('%dx%d+%d+%d' % (WIDTH, HEIGHT, 200, 100))\n\nc = tkinter.Canvas(root, width=WIDTH, height=HEIGHT, bg=\"#003300\")\nc.grid()\n# catch keypressing\nc.focus_set()\n# creating segments and snake\nsegments = [Segment(SEG_SIZE, SEG_SIZE),\n Segment(SEG_SIZE*2, SEG_SIZE),\n Segment(SEG_SIZE*3, SEG_SIZE)]\ns = Snake(segments)\ncreate_percent()\n# Reaction on keypress\nc.bind(\"\", s.keypress)\n\ncreate_block()\nmain()\nroot.mainloop()\n","sub_path":"games/arcade_games/snake.py","file_name":"snake.py","file_ext":"py","file_size_in_byte":6158,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"306061939","text":"from bayesdend.inf_method.inference import *\nfrom bayesdend.inf_method.optimizer_factory import *\nfrom bayesdend.utils.debug_util import *\n\n\nclass VIMCO(Inference):\n \"\"\"\n VIMCO inference method\n \"\"\"\n\n def __init__(self, Nb, data_ph, *args, **kargs):\n super().__init__(*args, **kargs)\n self.Nb = Nb\n self.data_ph = data_ph\n\n def objective(self, from_rec, from_gen):\n \"\"\"\n get the train op and obj op\n :return:\n \"\"\"\n logPrior = from_rec[0]\n logPost = from_rec[1]\n logLikhood = from_gen\n\n logP = logPrior + logLikhood\n logQ = logPost\n\n self.obj_p, self.obj_q = self.cal_obj(logP, logQ, self.Nb)\n obj_batch = tf.reduce_logsumexp(logP - logQ, axis=1) - np.log(self.Nb)\n obj = tf.reduce_mean(obj_batch)\n return obj\n\n @staticmethod\n def cal_obj(logP_all, logQ_all, K):\n # [num_samples, batch_size]\n logP_stack = tf.unstack(logP_all, axis=1)\n logQ_stack = tf.unstack(logQ_all, axis=1)\n\n final_logP = []\n final_logQ = []\n for i in range(len(logP_stack)):\n logP = logP_stack[i]\n logQ = logQ_stack[i]\n log_f = logP - logQ\n # estimate of logf based on all the other values\n log_fh = (tf.reduce_sum(log_f) - log_f) / (K - 1)\n # matrix of logf, with diagonal replaced by estimate\n Log_f = (tf.ones([K, K]) - tf.eye(K)) * log_f + tf.diag(log_fh)\n # log mean fs\n L = tf.reduce_logsumexp(log_f) - np.log(K)\n # log mean fs (diagonal replaced by estimate)\n Li = tf.reduce_logsumexp(Log_f, axis=1) - np.log(K)\n w = tf.nn.softmax(log_f)\n Q_obj = tf.stop_gradient(w) * log_f + \\\n tf.stop_gradient(L - Li) * logQ\n P_obj = tf.stop_gradient(w) * log_f\n\n Q_obj = tf.reduce_sum(Q_obj)\n P_obj = tf.reduce_sum(P_obj)\n\n final_logP.append(P_obj)\n final_logQ.append(Q_obj)\n\n final_logP = tf.reduce_mean(final_logP)\n final_logQ = tf.reduce_mean(final_logQ)\n return final_logP, final_logQ\n\n def optimizer(self, obj):\n\n obj_gen = self.obj_p\n obj_rec = self.obj_q\n\n opt_func = optimizer_factory[self.optim](learning_rate=self.learning_rate,\n momentum=self.momentum)\n # generative variables\n g_var_list = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope='generative')\n #gen_grads, _ = tf.clip_by_global_norm(tf.gradients(-obj_gen, self.g_var_list), 1.)\n gen_grads, self.g_var_list = zip(*opt_func.compute_gradients(-obj_gen, var_list=g_var_list))\n\n # recognition variables\n r_var_list = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope='recognition')\n #rec_grads, _ = tf.clip_by_global_norm(tf.gradients(-obj_rec, self.r_var_list), 1.)\n rec_grads, self.r_var_list = zip(*opt_func.compute_gradients(-obj_rec, var_list=r_var_list))\n\n grads = gen_grads + rec_grads\n # clipping\n self.grads, _ = tf.clip_by_global_norm(grads, 1.)\n self.tvars = self.g_var_list + self.r_var_list\n train = opt_func.apply_gradients(zip(self.grads, self.tvars))\n return train\n","sub_path":"bayesdend/inf_method/vimco.py","file_name":"vimco.py","file_ext":"py","file_size_in_byte":3314,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"622264761","text":"\"\"\"\nMIT License\n\nCopyright (c) 2017 liukuang\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n\nVGG11/13/16/19 in Pytorch.\n\"\"\"\nimport torch\nimport torch.nn as nn\nfrom torch.nn.modules.module import _addindent\nimport numpy as np\nfrom torch.utils.tensorboard import SummaryWriter\ncfg = {\n 'VGG11': [64, 'M', 128, 'M', 256, 256, 'M', 512, 512, 'M', 512, 512, 'M'],\n 'VGG13': [64, 64, 'M', 128, 128, 'M', 256, 256, 'M', 512, 512, 'M', 512, 512, 'M'],\n #'VGG16': [64, 64, 'M', 128, 128, 'M', 256, 256, 256, 'M', 512, 512, 512, 'M', 512, 512, 512, 'M'],\n #'VGG16': [52, 54, 'M', 106, 106, 'M', 212, 210, 210, 'M', 420, 420, 416, 'M', 414, 414, 414, 'M'], #20%\n #'VGG16': [42, 44, 'M', 84, 82, 'M', 164, 164, 164, 'M', 322, 314, 314, 'M', 312, 314, 318, 'M'], #40%\n 'VGG16': [32, 36, 'M', 64, 60, 'M', 118, 118, 118, 'M', 226, 214, 216, 'M', 212, 214, 220, 'M'], #60%\n #'VGG16': [32, 8, 'M', 42, 38, 'M', 72, 72, 72, 'M', 132, 114, 116, 'M', 112, 114, 122, 'M'], #80%\n #'VGG16': [32, 16, 'M', 20, 16, 'M', 28, 26, 26, 'M', 36, 16, 18, 'M', 12, 16, 24, 'M'], #100%\n 'VGG19': [64, 64, 'M', 128, 128, 'M', 256, 256, 256, 256, 'M', 512, 512, 512, 512, 'M', 512, 512, 512, 512, 'M'],\n}\n\n\nclass VGG(nn.Module):\n def __init__(self, vgg_name, num_classes: int = 10):\n super(VGG, self).__init__()\n self.features = self._make_layers(cfg[vgg_name])\n self.classifier = nn.Linear(220, num_classes)\n\n def forward(self, x):\n out = self.features(x)\n out = out.view(out.size(0), -1)\n out = self.classifier(out)\n return out\n\n def _make_layers(self, cfg):\n layers = []\n in_channels = 3\n for x in cfg:\n if x == 'M':\n layers += [nn.MaxPool2d(kernel_size=2, stride=2)]\n else:\n layers += [nn.Conv2d(in_channels, x, kernel_size=3, padding=1),\n nn.BatchNorm2d(x),\n nn.ReLU(inplace=True)]\n in_channels = x\n layers += [nn.AvgPool2d(kernel_size=1, stride=1)]\n return nn.Sequential(*layers)\n\ndef torch_summarize(model, show_weights=True, show_parameters=True):\n \"\"\"Summarizes torch model by showing trainable parameters and weights.\"\"\"\n tmpstr = model.__class__.__name__ + ' (\\n'\n for key, module in model._modules.items():\n # if it contains layers let call it recursively to get params and weights\n if type(module) in [\n torch.nn.modules.container.Container,\n torch.nn.modules.container.Sequential\n ]:\n modstr = torch_summarize(module)\n else:\n modstr = module.__repr__()\n modstr = _addindent(modstr, 2)\n\n params = sum([np.prod(p.size()) for p in module.parameters()])\n weights = tuple([tuple(p.size()) for p in module.parameters()])\n\n tmpstr += ' (' + key + '): ' + modstr\n if show_weights:\n tmpstr += ', weights={}'.format(weights)\n if show_parameters:\n tmpstr += ', parameters={}'.format(params)\n tmpstr += '\\n'\n\n tmpstr = tmpstr + ')'\n return tmpstr\n\ndef test():\n net = VGG('VGG16')\n print(torch_summarize(net))\n tb = SummaryWriter()\n x = torch.randn(2, 3, 32, 32)\n tb.add_graph(net,x)\n tb.close()\n\n y = net(x)\n print(y.size())\n\n\ntest()\n","sub_path":"unpackaged/models/vgg_tb.py","file_name":"vgg_tb.py","file_ext":"py","file_size_in_byte":4302,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"76697858","text":"#!/usr/bin/python3\n# -*- coding: utf-8 -*-\n\n__author__ = \"Michal Ormos\"\n__copyright__ = \"Copyright 2018, UVs\"\n__version__ = \"1.0.1\"\n__maintainer__ = \"Michal Ormos\"\n__email__ = \"michal.ormos@alumnos.uva.es\"\n__status__ = \"Educational\"\n\nimport requests\nimport json\nfrom elasticsearch import Elasticsearch\nimport time\n\nif __debug__:\n print ('Debug ON')\nelse:\n print ('Debug OFF')\n\nintroduction_comment = \"\"\"\t\n\tThis script demonstrate what I learn why using Elastich search in Python\n\tfor purpose of demonstrate it in AWBGI class\n\t2018 UVa\n\"\"\"\n\nprint(introduction_comment)\nif __debug__:\n print (\"No sleep\")\nelse:\n time.sleep(3)\n\n# Make sure our ES is running\nprint(\"#############\\nConnection test\\n#############\")\nres = requests.get('http://localhost:9200')\nprint(res.content)\nprint('\\n')\n\nif __debug__:\n print (\"No sleep\")\nelse:\n time.sleep(3)\n\n# Connect to our cluster\nes = Elasticsearch(\n\t[{'host': 'localhost', 'port': 9200}],\n\tsniff_on_start=True,\n # refresh nodes after a node fails to respond\n sniff_on_connection_fail=True,\n # and also every 60 seconds\n sniffer_timeout=60,\n # set sniffing request timeout to 10 seconds\n sniff_timeout=10)\n\n# Index some test data\nprint(\"#############\\nFirst data test\\n#############\")\nes.index(index='test-index', doc_type='test', id=1, body={'test': 'test'})\n\n# Test if they are there\nres = es.get(index='test-index', doc_type='test', id=1)\nprint (json.dumps(res['_source'], indent=4, sort_keys=True))\n\n# Delete test data and try with something more interesting\ndelete = es.delete(index='test-index', doc_type='test', id=1)\nprint(delete)\n\nprint('\\n')\nif __debug__:\n print (\"No sleep\")\nelse:\n time.sleep(3)\n\n# Index some more complicated test data\nprint(\"#############\\nSecond data test\\n#############\")\nes.index(index='sw', doc_type='people', id=1, body={\n\t\"name\": \"Luke Skywalker\",\n\t\"height\": \"172\",\n\t\"mass\": \"77\",\n\t\"hair_color\": \"blond\",\n\t\"birth_year\": \"19BBY\",\n\t\"gender\": \"male\",\n})\n\n# Test if they are there\nres = es.get(index='sw', doc_type='people', id=1)\nprint (json.dumps(res['_source'], indent=4, sort_keys=True))\n\nes.delete(index='sw', doc_type='people', id=1)\n\nprint('\\n')\nif __debug__:\n print (\"No sleep\")\nelse:\n time.sleep(3)\n\n# Lets add all SW people\nprint(\"#############\\nLets add SW characters from SW API (This could take some time)\\n#############\")\nr = requests.get('http://localhost:9200') \ni = 1\nwhile r.status_code == 200:\n r = requests.get('http://swapi.co/api/people/'+ str(i))\n es.index(index='sw', doc_type='people', id=i, body=json.loads(r.content.decode('utf-8')))\n i=i+1\nprint(\"We added %d characters from API\" %i)\n\nprint('\\n')\nif __debug__:\n print (\"No sleep\")\nelse:\n time.sleep(3)\n\n# Search demonstration\nprint(\"#############\\nWho is under id 5?\\n#############\")\nres = es.get(index='sw', doc_type='people', id=5)\n# print(res['_source'])\nprint (json.dumps(res['_source'], indent=4, sort_keys=True))\nprint('\\n')\n\n# Lets add more SW people\nprint(\"#############\\nLets add more SW characters from SW API (This could take more time than last time)\\n#############\")\nr = requests.get('http://localhost:9200') \ni = 18\nwhile r.status_code == 200:\n r = requests.get('http://swapi.co/api/people/'+ str(i))\n es.index(index='sw', doc_type='people', id=i, body=json.loads(r.content.decode('utf-8')))\n i=i+1\nprint(\"We added %d more characters from API\" %i)\n\nprint('\\n')\nif __debug__:\n print (\"No sleep\")\nelse:\n time.sleep(3)\n\nes.indices.refresh(index=\"sw\")\n\nprint('\\n')\nprint(\"#############\\nDo we have some Darth Vader here? Let's search him\\n#############\")\nres = es.search(index=\"sw\", body={\"query\": {\"match\" : { \"name\" : \"Darth\" }}})\nprint (json.dumps(res, indent=4, sort_keys=True))\nprint(\"Got %d Hits:\" % res['hits']['total'])\nprint(\"#############\\nSeems like we have found 2 Darth's!\\n#############\")\n\nprint('\\n')\nif __debug__:\n print (\"No sleep\")\nelse:\n time.sleep(3)\n\nprint(\"#############\\nLet's see of some name start's with sting 'Lu'\\n#############\")\nres = es.search(index=\"sw\", body={\"query\": {\"prefix\" : { \"name\" : \"lu\" }}})\n\nprint (json.dumps(res, indent=4, sort_keys=True))\n\nprint('\\n')\nif __debug__:\n print (\"No sleep\")\nelse:\n time.sleep(3)\n\nprint(\"#############\\nLet's find who is born in year 19\\n#############\")\nres = es.search(index=\"sw\", body={\"query\": {\"prefix\" : { \"birth_year\" : \"19\" }}})\nprint (json.dumps(res, indent=4, sort_keys=True))\n\nprint('\\n')\nif __debug__:\n print (\"No sleep\")\nelse:\n time.sleep(3)\n\nprint(\"#############\\nLet's try som fuzzy query\\n#############\")\nres = es.search(index=\"sw\", body={\"query\": {\"fuzzy\" : { \"name\" : {\"value\" : \"jaba\", \"max_expansions\":5}}}})\nprint (json.dumps(res, indent=4, sort_keys=True))\nprint(\"#############\\nWe found Jabba even we mispell his name!\\n#############\")","sub_path":"2MIT_Universidad_de_Valladolid/Elasticsearch/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":4782,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"389442836","text":"#!/usr/bin/env python\n# -*- coding:utf-8 -*-\n#Author:Jeff Lee\nfrom core.client import ClientHandle\n\nclass command_handler(object):\n\n def __init__(self,args):\n self.sys_args =args\n if len(self.sys_args)<2:\n exit(self.help_msg)\n\n self.command_allowcator()\n\n\n def help_msg(self):\n valid_commands ='''\n start start monitor client\n stop stop monitor client\n '''\n exit(valid_commands)\n\n def command_allowcator(self):\n '''分析用户输入的不同命令'''\n\n print(self.sys_args[1])\n\n if hasattr(self,self.sys_args[1]):\n func = getattr(self,self.sys_args[1])\n return func()\n else:\n print(\"命令不存在\")\n self.help_msg()\n\n def start(self):\n print('开始启动客户端')\n\n client =ClientHandle()\n client.forever_run()\n\n def stop(self):\n print('停止客户端')\n","sub_path":"app01/gordon/core/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":949,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"15"} +{"seq_id":"653643330","text":"from xlutils.copy import copy\nimport xlwt, xlrd,sys,os\nfrom datetime import datetime,timedelta\nfrom xlrd import xldate_as_tuple\nimport numpy as np\nfrom statsmodels.stats.anova import anova_lm\n\ndef load_data(filename,date): # 11 datas around the date.\n\tfenge = xlrd.open_workbook(filename)\n\tsheet = fenge.sheet_by_index(0)\n\traw_end = sheet.col_values(6)\n\traw_exchange = sheet.col_values(7)\n\n\tshichang = xlrd.open_workbook('300zhibiao.xlsx')\n\tssheet = shichang.sheet_by_index(0)\n\tsraw_end = ssheet.col_values(6)\n\tsraw_exchange = ssheet.col_values(7)\n\n\tend_price = []\n\tex_amount = []\n\tfor i in range(1,len(raw_end)):\n\t\tif isinstance(raw_end[i],str):\n\t\t\tcontinue\n\t\telse:\n\t\t\tend_price.append(raw_end[i])\n\t\t\tex_amount.append(raw_exchange[i])\n\n\tsend_price = []\n\tsex_amount = []\n\tfor i in range(1, len(sraw_end)):\n\t\tif isinstance(sraw_end[i], str):\n\t\t\tcontinue\n\t\telse:\n\t\t\tsend_price.append(sraw_end[i])\n\t\t\tsex_amount.append(sraw_exchange[i])\n\n\trate_end = []\n\trate_ex = []\n\tfor i in range(1,len(end_price)):\n\t\tif i == 1:\n\t\t\trate_end.append(0)\n\t\t\trate_ex.append(0)\n\t\telif end_price[i-1] == 0 or ex_amount[i-1] == 0:\n\t\t\tprint(filename)\n\t\t\treturn\n\t\telse:\n\t\t\trate_end.append((end_price[i]-end_price[i-1])/end_price[i-1])\n\t\t\trate_ex.append((ex_amount[i]-ex_amount[i-1])/ex_amount[i-1])\n\n\tsrate_end = []\n\tsrate_ex = []\n\tfor i in range(1, len(send_price)):\n\t\tif i == 1:\n\t\t\tsrate_end.append(0)\n\t\t\tsrate_ex.append(0)\n\t\telif send_price[i - 1] == 0 or sex_amount[i - 1] == 0:\n\t\t\tprint('!!!')\n\t\t\treturn\n\t\telse:\n\t\t\tsrate_end.append((send_price[i] - send_price[i - 1]) / send_price[i - 1])\n\t\t\tsrate_ex.append((sex_amount[i] - sex_amount[i - 1]) / sex_amount[i - 1])\n\n\tdate_list = []\n\tfor i in range(1,len(raw_end)):\n\t\tcell = sheet.cell_value(i, 2)\n\t\tif cell == '':\n\t\t\tcontinue\n\t\tdate1 = datetime(*xldate_as_tuple(cell, 0))\n\t\tcell = date1.strftime('%Y/%m/%d')\n\t\tdate_list.append(cell)\n\n\tsdate_list = []\n\tfor i in range(1, len(sraw_end)):\n\t\tscell = ssheet.cell_value(i, 2)\n\t\tif scell == '':\n\t\t\tcontinue\n\t\tsdate = datetime(*xldate_as_tuple(scell, 0))\n\t\tscell = sdate.strftime('%Y/%m/%d')\n\t\tsdate_list.append(scell)\n\n\tstart_p = 0\n\tss_p = 0\n\n\tfor i in range(1,len(date_list)):\n\t\tif date_list[i]>= date and date_list[i-1]= date and sdate_list[i-1]\"\"\".format(name=name)\r\n\r\n def global_color_theme(list_colors):\r\n return \"\"\"\"\"\" % (list_colors)\r\n\r\nclass start: \r\n def open_stockcharts(chart_name):\r\n script = \"\"\"\"\"\"\r\n \r\n def close_clickfunction():\r\n return \"\"\"});\"\"\"\r\n \r\n def close_update():\r\n return \"\"\"});\"\"\"\r\n \r\n class jquery:\r\n def close_clickfunction():\r\n return \"\"\"});\"\"\"\r\n\r\n def close_update():\r\n return \"\"\"});\"\"\"\r\n \r\n def close_switch():\r\n return \"\"\"})\"\"\"\r\n \r\n def close_slider():\r\n return \"\"\"}\"\"\"\r\n \r\nclass config:\r\n class x:\r\n def axis(D, x_axis, x_axis_type, x_title, vbands, x_lim,\r\n x_tick_interval, stockcharts=False):\r\n \"\"\"The x axis or category axis. Normally this is the horizontal \r\n axis, though if the chart is inverted this is the vertical axis. \r\n In case of multiple axes, the xAxis node is an array of \r\n configuration objects. https://api.highcharts.com/highcharts/xAxis\"\"\"\r\n x_axis=config.x._type(D, x_axis, x_axis_type, stockcharts)\r\n # hicharts x-axis toolkit:\r\n js=[]\r\n js.append(\"\"\"xAxis: {\"\"\")\r\n js.append(\"\"\"type: '{x_axis_type}',\"\"\".format(\r\n x_axis_type=x_axis_type) if x_axis_type !=None else '')\r\n js.append(\"\"\"tickInterval: {x_tick_interval},\"\"\".format(\r\n x_tick_interval='null' if x_tick_interval==None else x_tick_interval\r\n ) if x_axis_type=='datetime' else '')\r\n js.append(\"\"\"tickmarkPlacement: 'on', labels: {%s},\"\"\" % (\"\"\"\r\n x: 0, step: 0, offset: 0, rotation: 90, showLastLabel: true, \r\n showSecondLabel: false\"\"\") if D['kind']=='heatmap' else '')\r\n js.append(\"\"\"title: {0},\"\"\".format(\"{text: '%s'}\" % (x_title)))\r\n js.append(config.x._categories(x_axis) if not x_axis==None else '') # categories\r\n js.append(\"\"\"style: {color: 'black', font: 'Arial'},\"\"\")\r\n js.append(\"\"\"plotLines: [{from: %s, to: %s, color: '%s'}]\"\"\" % (\r\n vbands[0], vbands[1], commons.rgba(vbands)) if not vbands==None else '')\r\n js.append(\"\"\"min: {x_lim},\"\"\".format(x_lim='undefined' if x_lim[0]==None else str(x_lim[0])))\r\n js.append(\"\"\"max: {x_lim},\"\"\".format(x_lim='undefined' if x_lim[0]==None else str(x_lim[1]))) \r\n js.append(\"\"\"},\"\"\")\r\n return ''.join(js)\r\n \r\n def _type(D, x_axis, x_axis_type, stockcharts):\r\n x_axis=config.x._axis_object(D, x_axis)\r\n # try to change format of the datetime object if x type is set as datetime\r\n if x_axis_type=='datetime': \r\n if stockcharts:\r\n try: x_axis = [int(time.mktime(time.strptime(d, '%b-%y'))) for d in x_axis]\r\n except: warnings.warn(\"\"\"DateStamp index could not be \r\n converted to epoch timestamp\"\"\", \r\n RuntimeWarning)\r\n else: \r\n # if date format has already been set up\r\n try: x_axis = [d.strftime('%b-%y') for d in x_axis] \r\n except: pass\r\n elif x_axis_type=='linear': # change from x_axis to x_axis_type\r\n try:\r\n x_axis=list(range(0, len(x_axis))) \r\n except: pass\r\n return x_axis\r\n \r\n def _axis_object(D, x_axis):\r\n \"\"\"If variable plot.draw::x_axis = '', then x_axis should be equal\r\n to the xaxis object determined by plot.add without any intervention \r\n from the user.\"\"\"\r\n if not isinstance(D['data'], str): \r\n if x_axis==False:\r\n x_axis=''\r\n if x_axis==True: \r\n x_axis=list(D['data'].index) \r\n else:\r\n x_axis=''\r\n return x_axis\r\n \r\n def _categories(x_axis):\r\n \"\"\"If categories are present for the xAxis, names are used instead \r\n of numbers for that axis. Since Highcharts 3.0, categories can also \r\n be extracted by giving each point a name and setting axis type to \r\n category. However, if you have multiple series, best practice remains \r\n defining the categories array. https://api.highcharts.com/highcharts/\r\n xAxis.categories\"\"\"\r\n list_index, cat = [], []\r\n for i in x_axis: list_index.append(\"\"\"'%s'\"\"\" % (i))\r\n y=','.join(str(x) for x in list_index)\r\n cat.append(\"\"\"[%s]\"\"\" % (y))\r\n return 'categories: ' + str(cat[0]) + ','\r\n \r\n class y: \r\n def axis(D, n_axis, x_reversed, x_inverted,\r\n y_reversed, y_lim, y_opposite, y_axis_type, y_title, y_categories,\r\n hbands, n_panel, tickmark_placement):\r\n \"\"\"The Y axis or value axis. Normally this is the vertical axis, \r\n though if the chart is inverted this is the horizontal axis. \r\n In case of multiple axes, the yAxis node is an array of \r\n configuration objects.\r\n https://api.highcharts.com/highcharts/yAxis\"\"\"\r\n x_reversed=util.boolean_to_str(x_reversed)\r\n x_inverted=util.boolean_to_str(x_inverted)\r\n js=[]\r\n js.append(\"\"\"yAxis: [{\"\"\")\r\n js.append(config.y._prime_axis(\r\n D, n_axis, x_reversed, x_inverted, y_lim, y_axis_type, \r\n hbands, y_title, y_categories, n_panel, tickmark_placement))\r\n if n_axis==1: \r\n js.append(\"\"\"],\"\"\")\r\n elif n_axis==2:\r\n js.append(config.y._second_axis(\r\n y_reversed, y_lim, y_opposite, y_axis_type, y_title, \r\n y_categories, hbands, n_panel, tickmark_placement))\r\n else: raise ValueError(\"\"\"n_axis can either be 1 or 2 depending on \r\n the number of axis the plot object gathered.\"\"\")\r\n return ''.join(js)\r\n \r\n def _prime_axis(D, n_axis, x_reversed, x_inverted, y_lim,\r\n y_axis_type, hbands, y_title, y_categories, n_panel, \r\n tickmark_placement):\r\n js=[]\r\n js.append(\"\"\"type: '{y_axis_type}',\"\"\".format(y_axis_type=y_axis_type))\r\n js.append(\"\"\"reversed: {x_reversed},\"\"\".format(x_reversed=x_reversed))\r\n js.append(\"\"\"inverted: {x_inverted},\"\"\".format(x_inverted=x_inverted))\r\n \r\n js.append(\"\"\"min: {y_lim},\"\"\".format(y_lim='undefined' if y_lim[0]==None else str(y_lim[0])))\r\n js.append(\"\"\"max: {y_lim},\"\"\".format(y_lim='undefined' if y_lim[0]==None else str(y_lim[1]))) \r\n \r\n js.append(\"\"\"floor: {y_lim},\"\"\".format(y_lim='undefined' if y_lim[0]==None else str(y_lim[0])))\r\n js.append(\"\"\"ceiling: {y_lim},\"\"\".format(y_lim='undefined' if y_lim[1]==None else str(y_lim[1])))\r\n js.append(\"\"\"title: {0},\"\"\".format(\"{text: '%s'}\" % (y_title)))\r\n js.append(config.y._categories(y_categories))\r\n js.append(\"\"\"plotLines: [{from: %s, to: %s, color: '%s'}]\"\"\" % (\r\n hbands[0], hbands[1], commons.rgba(hbands)) if not hbands==None else '')\r\n js.append(\"\"\"height: '70%'}, {top: '70%', height: '30%', title: '',\"\"\" if n_panel==2 else '')\r\n js.append(\"\"\"tickmarkPlacement: '%s', labels: {y: 0, step: 0, style: {color: 'black', font: 'Arial'}}\"\"\" % (\r\n tickmark_placement) if D['kind']=='heatmap' else '')\r\n js.append(\"\"\"},\"\"\")\r\n return ''.join(js)\r\n \r\n def _second_axis(y_reversed, y_lim, y_opposite, y_axis_type, y_title, \r\n y_categories, hbands, n_panel, tickmark_placement):\r\n js=[]\r\n y_reversed=util.boolean_to_str(y_reversed)\r\n y_opposite=util.boolean_to_str(y_opposite) \r\n js.append(\"\"\"{\"\"\")\r\n js.append(\"\"\"type: '{y_axis_type}',\"\"\".format(y_axis_type=y_axis_type))\r\n js.append(\"\"\"opposite: {y_opposite},\"\"\".format(y_opposite=y_opposite))\r\n js.append(\"\"\"reversed: {y_reversed},\"\"\".format(y_reversed=y_reversed))\r\n js.append(\"\"\"min: {y_lim},\"\"\".format(x_lim='undefined' if y_lim[0]==None else str(y_lim[0])))\r\n js.append(\"\"\"max: {y_lim},\"\"\".format(x_lim='undefined' if y_lim[1]==None else str(y_lim[0])))\r\n js.append(\"\"\"floor: {y_lim},\"\"\".format(x_lim='undefined' if y_lim[0]==None else str(y_lim[0])))\r\n js.append(\"\"\"ceiling: {y_lim},\"\"\".format(x_lim='undefined' if y_lim[1]==None else str(y_lim[1])))\r\n js.append(\"\"\"title: {0},\"\"\".format(\"{text: '%s'}\" % (y_title)))\r\n js.append(config.y._categories(y_categories))\r\n js.append(\"\"\"}],\"\"\")\r\n return ''.join(js)\r\n \r\n def _categories(y_categories):\r\n if not y_categories==None: cat='categories: ' + str(y_categories) + ','\r\n else: cat=''\r\n return cat\r\n \r\n class z:\r\n def axis(z_title):\r\n \"\"\"The Z axis or depth axis for 3D plots.\r\n https://api.highcharts.com/highcharts/zAxis\"\"\"\r\n js=[]\r\n if not z_title=='':\r\n js.append(\"\"\"zAxis: {\"\"\")\r\n js.append(\"\"\"title: {0},\"\"\".format(\"{text: '%s'}\" % (z_title)))\r\n js.append(\"\"\"},\"\"\") \r\n return ''.join(js)\r\n \r\n class tool:\r\n def tips(D, x_axis_type): \r\n if D['kind'] in [\r\n 'boxplot',\r\n 'network',\r\n 'sankey', \r\n ]: js=''\r\n elif D['kind'] in [\r\n 'wordcloud'\r\n ]: js=config.tool._form_weight()\r\n elif D['kind'] in [\r\n 'heatmap'\r\n ]: js=config.tool._matrix()\r\n elif x_axis_type==None:\r\n js=config.tool._form_x_y() \r\n else: \r\n js=config.tool._timeseries()\r\n return js\r\n \r\n def _timeseries():\r\n \"\"\"Options for the tooltip that appears when the user hovers \r\n over a series or point. https://api.highcharts.com/highstock/tooltip\"\"\"\r\n js=[]\r\n js.append(\"\"\"tooltip: {\"\"\")\r\n js.append(\"\"\"pointFormat: '{series.name}: {point.y} {point.change}
',\"\"\")\r\n js.append(\"\"\"valueDecimals: 2,\"\"\")\r\n js.append(\"\"\"split: false,\"\"\")\r\n js.append(\"\"\"crosshairs: true\"\"\")\r\n js.append(\"\"\"},\"\"\")\r\n return ''.join(js)\r\n \r\n def _form_x_y():\r\n js=[]\r\n js.append(\"\"\"tooltip: {\"\"\")\r\n js.append(\"\"\"useHTML: true,\"\"\")\r\n js.append(\"\"\"headerFormat: '',\"\"\")\r\n js.append(\"\"\"\r\n pointFormat: '' +\r\n '' + \r\n '',\"\"\") # {point.title_legend} <=> {series.name}\r\n js.append(\"\"\"footerFormat: '
{series.name}
x-axis:{point.x:,.2f}
y-axis:{point.y:,.2f}
',\"\"\")\r\n js.append(\"\"\"followPointer: true\"\"\")\r\n js.append(\"\"\"},\"\"\")\r\n return ''.join(js)\r\n\r\n def _form_x():\r\n js=[]\r\n js.append(\"\"\"tooltip: {\"\"\")\r\n js.append(\"\"\"useHTML: true,\"\"\")\r\n js.append(\"\"\"headerFormat: '',\"\"\")\r\n js.append(\"\"\"\r\n pointFormat: '' + \r\n '',\"\"\")\r\n js.append(\"\"\"footerFormat: '
{point.title_legend}
Value:{point.x}
',\"\"\")\r\n js.append(\"\"\"followPointer: true\"\"\")\r\n js.append(\"\"\"},\"\"\")\r\n return ''.join(js)\r\n\r\n def _form_weight():\r\n js=[]\r\n js.append(\"\"\"tooltip: {\"\"\")\r\n js.append(\"\"\"useHTML: true,\"\"\")\r\n js.append(\"\"\"headerFormat: '',\"\"\")\r\n js.append(\"\"\"\r\n pointFormat: '' + \r\n '',\"\"\")\r\n js.append(\"\"\"footerFormat: '
{point.title_legend}
Weight:{point.weight}
',\"\"\")\r\n js.append(\"\"\"followPointer: true\"\"\")\r\n js.append(\"\"\"},\"\"\")\r\n return ''.join(js)\r\n \r\n def _matrix():\r\n js=[]\r\n js.append(\"\"\"tooltip: {\"\"\")\r\n js.append(\"\"\"formatter: function () {return '' \r\n + this.series.yAxis.categories[this.point.y] \r\n + '
' \r\n + this.series.xAxis.categories[this.point.x] \r\n + '
' \r\n + this.point.value \r\n + '
'\r\n ;}\"\"\")\r\n js.append(\"\"\"},\"\"\") \r\n return ''.join(js)\r\n \r\n class plot:\r\n def options(D, line_width, chart_label, stacking, data_labels, \r\n marker, bubble_size_range, alpha, color_range, gradient, \r\n cmap, inactive_opacity, \r\n # network chart type\r\n algo_type, approximation, enable_simulation, friction, \r\n gravitational_constant, initial_position_function, integration, \r\n link_length, max_iterations, max_speed, repulsive_force):\r\n # special_cases class\r\n if D['kind'] in [\r\n 'networkgraph'\r\n ]: return config.plot._special_cases._network._graph(\r\n algo_type, approximation, enable_simulation, friction,\r\n gravitational_constant, initial_position_function,\r\n integration, link_length, max_iterations, max_speed, repulsive_force)\r\n elif D['kind'] in [\r\n 'area'\r\n ]: return config.plot._special_cases._area(\r\n D, line_width, chart_label, stacking, data_labels, marker, alpha, \r\n gradient, cmap, inactive_opacity)\r\n elif D['kind'] in [\r\n 'heatmap'\r\n ]: return config.plot._special_cases._heatmap(D, color_range, cmap)\r\n elif D['kind'] in [\r\n 'sankey'\r\n ]: return config.plot._special_cases._sankey(D, data_labels, inactive_opacity)\r\n\r\n else: \r\n return config.plot._general(\r\n D,\r\n line_width, \r\n chart_label, \r\n stacking, \r\n data_labels, \r\n marker, \r\n bubble_size_range,\r\n alpha, \r\n gradient,\r\n cmap,\r\n inactive_opacity\r\n ) + \"},\"\r\n \r\n def _general(D, line_width, chart_label, stacking, data_labels, marker, \r\n bubble_size_range=None, \r\n alpha=None, \r\n gradient=False, \r\n cmap=[\"#39ff14\",\"#ffffbf\",\"#ff073a\"], \r\n inactive_opacity=True\r\n ):\r\n \"\"\"The plotOptions is a wrapper object for config objects for \r\n each series type. The config objects for each series can also be \r\n overridden for each series item as given in the series array.\"\"\"\r\n marker=util.boolean_to_str(marker)\r\n chart_label=util.boolean_to_str(chart_label)\r\n data_labels=util.boolean_to_str(data_labels)\r\n inactive_opacity=util.boolean_to_str(inactive_opacity)\r\n # general options for all series.\r\n js=[]\r\n js.append(\"\"\"plotOptions: {\"\"\")\r\n # Not included in \"series\"\r\n js.append(\"\"\"bubble: {minSize: %s, maxSize: %s},\"\"\" % (\r\n bubble_size_range[0], \r\n bubble_size_range[1]) if not bubble_size_range==None else '')\r\n # Included in \"series\"\r\n js.append(\"\"\"series: {\"\"\")\r\n js.append(\"\"\"compare: 'percent',\"\"\")\r\n js.append(\"\"\"showInNavigator: true,\"\"\") \r\n js.append(\"\"\"dataLabels: {enabled: %s, format: '{point.name}', inside: false},\"\"\" % (data_labels))\r\n js.append(\"\"\"marker: {enabled: %s},\"\"\" % (marker)) \r\n js.append(\"\"\"lineWidth: %s,\"\"\" % (line_width)) \r\n js.append(\"\"\"states: {hover: {lineWidth: %s}, inactive: {enabled: %s}},\"\"\" % (line_width+2, inactive_opacity)) \r\n js.append(\"\"\"label: {enabled: %s, connectorAllowed: false},\"\"\" % (chart_label)) \r\n js.append(\"\"\"stacking: '%s',\"\"\" % (stacking) if not stacking==None else '') \r\n js.append(\"\"\"fillOpacity: %s\"\"\" % (alpha) if not alpha==None else '') \r\n js.append(\"\"\"color: {linearGradient: %s},\"\"\" % commons.cmap(cmap) if gradient==True else '')\r\n js.append(\"\"\"},\"\"\")\r\n return ''.join(js)\r\n\r\n class _special_cases:\r\n def _sankey(D, data_labels, inactive_opacity):\r\n \"\"\"The plotOptions is a wrapper object for config objects for \r\n each series type. The config objects for each series can also be \r\n overridden for each series item as given in the series array.\"\"\"\r\n data_labels=util.boolean_to_str(data_labels)\r\n js=[]\r\n js.append(\"\"\"plotOptions: {\"\"\")\r\n js.append(\"\"\"series: {\"\"\") \r\n js.append(\"\"\"dataLabels: {enabled: %s, inside: true},\"\"\" % (data_labels)) \r\n js.append(\"\"\"states: {hover: inactive: {enabled: %s}},\"\"\" % (inactive_opacity)) \r\n js.append(\"\"\"}\"\"\")\r\n js.append(\"\"\"},\"\"\")\r\n return ''.join(js)\r\n \r\n def _heatmap(D, color_range, cmap):\r\n \"\"\"Shared options for all heatmap series. Insert an event click\r\n type function in every cells of the heatmap. this is driven\r\n by the open_links variable in plot.draw.\r\n linked output must be save as '.../[X-AXIS NAME]_[Y-AXIS NAME].html'\"\"\"\r\n def color_axis(D, color_range, cmap):\r\n js=[]\r\n js.append(\"\"\"colorAxis: {\"\"\")\r\n js.append(\"\"\"reversed: false,\"\"\")\r\n js.append(\"\"\"min: {0},\"\"\".format(color_range[0]))\r\n js.append(\"\"\"max: {0},\"\"\".format(color_range[1]))\r\n js.append(\"\"\"linearGradient:\"\"\")\r\n js.append(commons.cmap(cmap))\r\n js.append(\"\"\"},\"\"\")\r\n return ''.join(js) \r\n js=[]\r\n js.append(\"\"\"plotOptions: {\"\"\")\r\n js.append(\"\"\"series: {cursor: 'pointer'}\"\"\")\r\n js.append(\"\"\"},\"\"\")\r\n js.append(color_axis(D, color_range, cmap))\r\n return ''.join(js)\r\n \r\n def _area(D, line_width, chart_label, stacking, data_labels, marker, \r\n alpha, gradient, cmap, inactive_opacity):\r\n \"\"\"Shared options for all area series.\"\"\"\r\n js=[]\r\n js.append(config.plot._general(\r\n D, line_width, chart_label, stacking, data_labels, marker, \r\n alpha=alpha, gradient=gradient, cmap=cmap, \r\n inactive_opacity=inactive_opacity))\r\n \r\n inactive_opacity=util.boolean_to_str(inactive_opacity)\r\n \r\n js.append(\"\"\"area: {\"\"\")\r\n js.append(\"\"\"fillOpacity: %s,\"\"\" % (alpha if not alpha==None else 0.1))\r\n js.append(\"\"\"lineWidth: %s,\"\"\" % (line_width))\r\n js.append(\"\"\"states: {hover: {lineWidth: %s}, inactive: {enabled: %s}},\"\"\" % (line_width+1, inactive_opacity)) \r\n js.append(\"\"\"}},\"\"\")\r\n return ''.join(js)\r\n \r\n class _network:\r\n \"\"\"Network graph (force directed graph) is a mathematical structure \r\n (graph) to show relations between points in an aesthetically-pleasing \r\n way. The graph visualizes how subjects are interconnected with each \r\n other. Entities are displayed as nodes and the relationship between \r\n them are displayed with lines. The graph is force directed by \r\n assigning a weight (force) from the node edges and the other \r\n interconnected nodes get assigned a weighted factor. The graph \r\n simulates the weight as forces in a physical system, where the \r\n forces have impact on the nodes and find the best position on the \r\n chart’s plotting area. The Network Graph has various use case such \r\n as display relations between people, roads, companies, and products.\r\n https://api.highcharts.com/highcharts/\r\n plotOptions.networkgraph.layoutAlgorithm\r\n \r\n Note: Zoom in/out not available \r\n https://github.com/highcharts/highcharts/issues/10828\r\n \"\"\"\r\n def _graph(algo_type, approximation, enable_simulation, friction,\r\n gravitational_constant, initial_position_function,\r\n integration, link_length, max_iterations, max_speed, \r\n repulsive_force):\r\n \"\"\"A networkgraph is a type of relationship chart, where \r\n connnections (links) attracts nodes (points) and other nodes \r\n repulse each other.\"\"\"\r\n nx=[]\r\n nx.append(config.plot._special_cases._network._engine._algo_type(algo_type))\r\n nx.append(config.plot._special_cases._network._engine._approximation(approximation))\r\n nx.append(config.plot._special_cases._network._engine._enable_simulation(enable_simulation))\r\n nx.append(config.plot._special_cases._network._engine._friction(friction))\r\n nx.append(config.plot._special_cases._network._engine._gravitational_constant(gravitational_constant))\r\n nx.append(config.plot._special_cases._network._engine._initial_position_function(\r\n position=initial_position_function['position'], radius=initial_position_function['radius']))\r\n nx.append(config.plot._special_cases._network._engine._integration(integration))\r\n nx.append(config.plot._special_cases._network._engine._link_length(link_length))\r\n nx.append(config.plot._special_cases._network._engine._max_iterations(max_iterations))\r\n nx.append(config.plot._special_cases._network._engine._max_speed(max_speed))\r\n nx.append(config.plot._special_cases._network._engine._repulsive_force(repulsive_force))\r\n js=[]\r\n js.append(\"\"\"plotOptions: {\"\"\")\r\n js.append(\"\"\"networkgraph: {keys: ['from', 'to', 'color', 'width'],\"\"\")\r\n js.append(\"\"\"layoutAlgorithm: {%s}}},\"\"\" % (''.join(nx))) \r\n return ''.join(js)\r\n \r\n class _engine:\r\n def _approximation(algo='barnes-hut'):\r\n \"\"\"Approximation used to calculate repulsive forces \r\n affecting nodes. By default, when calculateing net force,\r\n nodes are compared against each other, which gives O(N^2) \r\n complexity. Using Barnes-Hut approximation, we decrease \r\n this to O(N log N), but the resulting graph will have \r\n different layout. Barnes-Hut approximation divides space \r\n into rectangles via quad tree, where forces exerted on \r\n nodes are calculated directly for nearby cells, and for \r\n all others, cells are treated as a separate node with \r\n center of mass.\"\"\"\r\n return \"approximation: 'barnes-hut',\"\r\n \r\n def _attractive_force(n=0):\r\n \"\"\"Attraction force applied on a node which is conected \r\n to another node by a link. Passed are two arguments:\r\n d - which is current distance between two nodes\r\n k - which is desired distance between two nodes\r\n In verlet integration, defaults to: function (d, k) { \r\n return (k - d) / d; }\r\n Defaults to function (d, k) { return k * k / d; }.\"\"\"\r\n # other examples\r\n \"\"\"attractiveForce: function (d, k) {return \r\n Math.max(-(d * d) / (k * 300), -100);},\"\"\"\r\n return \"attractiveForce: function () {return %s;},\" % (n)\r\n \r\n def _enable_simulation(enable=False):\r\n \"\"\"Experimental. Enables live simulation of the algorithm \r\n implementation. All nodes are animated as the forces \r\n applies on them.\"\"\"\r\n return 'enableSimulation: %s,' % (util.boolean_to_str(enable))\r\n \r\n def _friction(n=-0.981):\r\n \"\"\"Friction applied on forces to prevent nodes rushing \r\n to fast to the desired positions.\"\"\"\r\n return 'friction: %s,' % (n)\r\n \r\n def _gravitational_constant(n=0.0625):\r\n \"\"\"Gravitational const used in the barycenter force of \r\n the algorithm.\"\"\"\r\n return 'gravitationalConstant: %s,' % (n)\r\n \r\n def _initial_position_function(position='circle', radius=1):\r\n \"\"\"Initial layout algorithm for positioning nodes. Can \r\n be one of built-in options (\"circle\", \"random\") or a \r\n function where positions should be set on each node \r\n (this.nodes) as node.plotX and node.plotYWhen \r\n initialPositions are set to 'circle', initialPositionRadius \r\n is a distance from the center of circle, in which nodes \r\n are created.\"\"\"\r\n ip=\"\"\"initialPositions: '%s',\"\"\" % (position)\r\n if position=='cicle': ip + \"initialPositionRadius: %s,\" % (radius)\r\n return ip\r\n \r\n def _integration(algo_type='euler' or 'verlet'):\r\n \"\"\"Integration type. Available options are 'euler' and \r\n 'verlet'. Integration determines how forces are applied \r\n on particles. In Euler integration, force is applied \r\n direct as newPosition += velocity;. In Verlet \r\n integration, new position is based on a previous posittion \r\n without velocity: newPosition += previousPosition \r\n - newPosition.\r\n Note that different integrations give different results \r\n as forces are different. In Highcharts v7.0.x only 'euler' \r\n integration was supported.\r\n eurler: https://en.wikipedia.org/wiki/Euler_method\r\n verlet: https://en.wikipedia.org/wiki/Verlet_integration\r\n \"\"\"\r\n return \"\"\"integration: '%s',\"\"\" % (algo_type)\r\n \r\n def _link_length(n=None):\r\n \"\"\"Ideal length (px) of the link between two nodes. \r\n When not defined, length is calculated as: \r\n Math.pow(availableWidth * availableHeight / nodesLength,\r\n 0.4);\r\n Note: Because of the algorithm specification, length of each \r\n link might be not exactly as specified.\"\"\"\r\n return 'linkLength: %s,' % ('undefined' if n==None else n)\r\n \r\n def _max_iterations(n=1000):\r\n \"\"\"Max number of iterations before algorithm will stop. \r\n In general, algorithm should find positions sooner, but \r\n when rendering huge number of nodes, it is recommended \r\n to increase this value as finding perfect graph positions \r\n an require more \r\n time.\"\"\"\r\n return 'maxIterations: %s,' % (n)\r\n \r\n def _max_speed(n=10):\r\n \"\"\"Verlet integration only. Max speed that node can get \r\n in one iteration. In terms of simulation, it's a maximum \r\n translation (in pixels) that node can move (in both, x \r\n and y, dimensions). While friction is applied on all \r\n nodes, max speed is applied only for nodes that move very \r\n fast, for example small or disconnected ones.\"\"\"\r\n return 'maxSpeed: %s,' % (n)\r\n \r\n def _repulsive_force(n=50):\r\n \"\"\"Repulsive force applied on a node. Passed are two \r\n arguments:\r\n d - which is current distance between two nodes\r\n k - which is desired distance between two nodes\r\n In verlet integration, defaults to: \r\n function (d, k) { return (k - d) / d * (k > d ? 1 : 0) }\r\n Defaults to function (d, k) { return k * k / d; }.\"\"\"\r\n # other examples:\r\n \"\"\"repulsiveForce: function (d, k) {\r\n return Math.min((k * k) / (d), 100);}\"\"\"\r\n return \"repulsiveForce: function () {return %s;},\" % (n)\r\n \r\n def _theta(n=0.5):\r\n \"\"\"Barnes-Hut approximation only. Deteremines when\r\n distance between cell and node is small enough to \r\n caculate forces. Value of theta is compared directly with \r\n quotient s / d, where s is the size of the cell, and d \r\n is distance between center of cell's mass and currently \r\n compared node.\"\"\"\r\n pass\r\n \r\n def _algo_type(algo='reingold-fruchterman'):\r\n \"\"\"Type of the algorithm used when positioning nodes.\r\n only reingold-fruchterman available at this moment.\"\"\"\r\n return \"type: '%s',\" % (algo)\r\n \r\n def chart(D, name, chart_title, polar, inverted, height, width, margin_top, \r\n margin_bottom, margin_left, margin_right, gradient, \r\n enable_3d, options_3d): \r\n polar=util.boolean_to_str(polar)\r\n inverted=util.boolean_to_str(inverted)\r\n js=[]\r\n js.append(\"\"\"chart: {\"\"\")\r\n js.append(\"\"\"height: {h},\"\"\".format(\r\n h='null' if height==None else \"'\" + height + \"'\" if isinstance(height, str) else height))\r\n js.append(\"\"\"width: {w},\"\"\".format(\r\n w='null' if width==None else \"'\" + width + \"'\" if isinstance(width, str) else width)) \r\n #js.append(\"\"\"width: null,\"\"\") \r\n js.append(\"\"\"renderTo: '{name}',\"\"\".format(name=name)) if enable_3d else ''\r\n js.append(\"\"\"type: '{kind}',\"\"\".format(kind=D['kind'])) if isinstance(D['data'], str) else ''\r\n js.append(\"\"\"zoomType: '{0}',\"\"\".format('undefined' if D['kind']=='wordcloud' or enable_3d==True else 'xy')) \r\n js.append(\"\"\"panning: true,\"\"\")\r\n js.append(\"\"\"panKey: 'shift',\"\"\")\r\n js.append(\"\"\"polar: {0},\"\"\".format(polar))\r\n js.append(\"\"\"inverted: {0},\"\"\".format(inverted))\r\n js.append(\"\"\"marginTop: {0},\"\"\".format('undefined' if margin_top==None else margin_top))\r\n js.append(\"\"\"marginBottom: {0},\"\"\".format('undefined' if margin_bottom==None else margin_bottom))\r\n js.append(\"\"\"marginLeft: {0},\"\"\".format('undefined' if margin_left==None else margin_left))\r\n js.append(\"\"\"marginRight: {0},\"\"\".format('undefined' if margin_right==None else margin_right))\r\n js.append(\"\"\"plotBorderWidth: 0.25,\"\"\")\r\n js.append(\"\"\"plotBorderColor: 'grey',\"\"\") \r\n js.append(\"\"\"type: 'networkgraph', height: '100%',\"\"\" if D['kind']=='networkgraph' else '') \r\n if enable_3d:\r\n js.append(\"\"\"options3d: {\"\"\")\r\n js.append(\"\"\"enabled: true,\"\"\") \r\n js.append(\"\"\"alpha: {alpha},\"\"\".format(alpha=options_3d['alpha'])) \r\n js.append(\"\"\"beta: {beta},\"\"\".format(beta=options_3d['beta'])) \r\n js.append(\"\"\"depth: {depth},\"\"\".format(depth=options_3d['depth'])) \r\n js.append(\"\"\"viewDistance: {distance}\"\"\".format(distance=options_3d['distance']))\r\n js.append(\"\"\"},\"\"\")\r\n if gradient:\r\n js.append(javascript.gradient()) \r\n js.append(\"\"\"},\"\"\")\r\n js.append(\"\"\"credits: {enabled: false},\"\"\")\r\n js.append(\"\"\"title: {text: '%s'},\"\"\" % (chart_title)) \r\n js.append(\"\"\"rangeSelector: {selected: 3},\"\"\")\r\n return ''.join(js)\r\n\r\n def legend(display_legend, legend_vertical):\r\n \"\"\"The legend is a box containing a symbol and name for each \r\n series item or point item in the chart. Each series (or points \r\n in case of pie charts) is represented by a symbol and its name \r\n in the legend. https://api.highcharts.com/highstock/legend\"\"\"\r\n display_legend=util.boolean_to_str(display_legend)\r\n js=[]\r\n js.append(\"\"\"legend: {\"\"\")\r\n js.append(\"\"\"enabled: {display_legend}, \"\"\".format(display_legend=display_legend))\r\n js.append(\"\"\"layout: '{display_legend}', {layout}\"\"\".format(\r\n display_legend='vertical' if legend_vertical else 'horizontal',\r\n layout=\"align: 'right', verticalAlign: 'top',\" if legend_vertical else ''))\r\n js.append(\"\"\"itemStyle: {color: '#444444', listStyle: 'none', listStyleImage: 'none'},\"\"\")\r\n js.append(\"\"\"itemHiddenStyle: {color: '#CCCCCC'},\"\"\")\r\n js.append(\"\"\"itemHoverStyle: {color: 'blue'}},\"\"\")\r\n return ''.join(js) \r\n \r\n def responsive(display_legend):\r\n \"\"\"A full set of chart options to apply as overrides to the general chart \r\n options. The chart options are applied when the given rule is active.\r\n A special case is configuration objects that take arrays, for example \r\n xAxis, yAxis or series. For these collections, an id option is used to \r\n map the new option set to an existing object. If an existing object of \r\n the same id is not found, the item of the same indexupdated. So for \r\n example, setting chartOptions with two series items without an id, will \r\n cause the existing chart's two series to be updated with respective \r\n options\"\"\"\r\n js=[]\r\n js.append(\"\"\"responsive: {\"\"\")\r\n js.append(\"\"\"rules: [{condition: {maxWidth: 1000, minWidth: 1000, maxHeight: 1000, minHeight: 1000}}],\"\"\")\r\n js.append(\"\"\"chartOptions: {\"\"\")\r\n js.append(\"\"\"xAxis: {labels: {formatter: function () {return this.value.charAt(0);}}},\"\"\")\r\n js.append(\"\"\"yAxis: {labels: {formatter: function () {return this.value.charAt(0);}}},\"\"\")\r\n js.append(\"\"\"legend: {layout: 'horizontal', align: 'center', verticalAlign: 'bottom'},\"\"\" if display_legend else '')\r\n js.append(\"\"\"chart: {title: {text: ''}, subtitle: {text: ''}},\"\"\") \r\n js.append(\"\"\"}},\"\"\")\r\n return ''.join(js) \r\n\r\nclass app: \r\n \"\"\"\r\n Example mutli selection\r\n ::::::::::::::::::::::::\r\n https://jsfiddle.net/tdob14w2\r\n https://jsfiddle.net/gh/get/library/pure/highcharts/highcharts/tree/master/samples/highcharts/members/series-update/\r\n \r\n Multi filter\r\n ::::::::::::\r\n http://jsfiddle.net/2q1376Le/2/\r\n http://jsfiddle.net/bYx9k/\r\n http://jsfiddle.net/zuXDG/\r\n http://jsfiddle.net/BlackLabel/1dk9x2tr/\r\n https://jsfiddle.net/gh/get/library/pure/highcharts/highcharts/tree/master/samples/highcharts/members/series-hide/\r\n https://www.highcharts.com/forum/viewtopic.php?t=35477\r\n - http://jsfiddle.net/cadm4fqt/3/\r\n - http://jsfiddle.net/cadm4fqt/4/\r\n \r\n Radio button\r\n ::::::::::::\r\n https://jsfiddle.net/BlackLabel/nowc0qjv/\r\n https://codepen.io/bhupendra1011/pen/WNbexzG\r\n \r\n Get selected points AFTER selection\r\n ::::::::::::::::::::::::::::::::::::\r\n https://www.highcharts.com/forum/viewtopic.php?t=22578\r\n \r\n Click on data point\r\n :::::::::::::::::::\r\n http://jsfiddle.net/cjxm0huz/\r\n \r\n Interactive map\r\n :::::::::::::::\r\n https://jsfiddle.net/highcharts/8vL6Lkt1/\r\n \r\n Slider\r\n ::::::\r\n https://www.highcharts.com/forum/viewtopic.php?t=43023\r\n https://stackoverflow.com/questions/38584703/slider-on-barchart\r\n https://stackoverflow.com/questions/15360263/how-to-dynamically-update-highcharts-using-jquery-ui-sliders/15363276\r\n https://stackoverflow.com/questions/19095806/highcharts-gauge-chart-update-on-slider\r\n * https://jsfiddle.net/uvat8u05/27/\r\n \r\n \r\n \"\"\" \r\n \r\n def update(dict_updates, chart_name): # self content\r\n js=[]\r\n for fcid,req in dict_updates.items():\r\n js.append(start.jquery.update.open_clickfunction(fcid))\r\n js.append(start.jquery.update.open_update(chart_name))\r\n js.append(start.open_series())\r\n # chech if multiple chart in this update by checking if req is a \r\n # nested dict:\r\n if any(isinstance(i, dict) for i in req.values()):\r\n # if req is a nested dict, loop through layers\r\n for _,req_layer in req.items():\r\n js.append(series.build(req_layer))\r\n js.append(\"\"\"},{\"\"\")\r\n else:\r\n js.append(series.build(req))\r\n js.append(end.close_series()) \r\n js.append(end.jquery.close_update())\r\n js.append(end.jquery.close_clickfunction())\r\n return ''.join(js) \r\n \r\n def switch(list_switches, chart_name):\r\n js=[]\r\n for fcid in list_switches:\r\n js.append(start.jquery.switch.open_clickfunction(fcid))\r\n js.append(start.jquery.switch.open_switch(chart_name))\r\n js.append(\"\"\"p.name.includes('%s') ? p.show() : p.hide()\"\"\" % fcid)\r\n js.append(end.jquery.close_switch())\r\n js.append(end.jquery.close_clickfunction())\r\n return ''.join(js) \r\n \r\n def slider(y_range, chart_name):\r\n js=[]\r\n js.append(start.jquery.slider.open_clickfunction())\r\n js.append(\"\"\"\r\n range: true,\r\n min: {minimum},\r\n max: {maximum},\r\n values: [{minimum}, {maximum}],\r\n slide:\"\"\".format(\r\n minimum=y_range[0], \r\n maximum=y_range[1]\r\n ))\r\n js.append(start.jquery.slider.open_slider())\r\n js.append(\"\"\"\r\n $(\"#amount\").val(ui.values[0] + \" - \" + ui.values[1]);\r\n {chart_name}.xAxis[0].setExtremes(ui.values[0]+1, ui.values[1]-1)\r\n \"\"\".format(chart_name=chart_name))\r\n js.append(end.jquery.slider.close_slider())\r\n js.append(end.jquery.close_clickfunction())\r\n # add counter\r\n js.append(\"\"\"$(\"#amount\").val($(\"#slider-range\").slider(\"values\", 0) +\r\n \" - \" + $(\"#slider-range\").slider(\"values\", 1));\"\"\")\r\n return ''.join(js) \r\n\r\n def networkgraph_event(force_directed_to): # not used yet!\r\n \"\"\"Add the nodes option through an event call. We want to start \r\n with the parent item and apply separate colors to each child \r\n element, then the same color to grandchildren.\"\"\"\r\n js=[]\r\n js.append(\"\"\"