def Run(self):
parser = argparse.ArgumentParser(
description='GitHub Repository Uploader.',
)
#parser.add_argument('path_dir_pj')
parser.add_argument('-n', '--username', action='append')
parser.add_argument('-d', '--path_dir_db')
parser.add_argument('-id', '--path_dir_input_db')
parser.add_argument('-od', '--path_dir_output_db')
parser.add_argument('-u', '--url', '--upload_url', action='append')
parser.add_argument('-y', '--yaml')
self.__args = parser.parse_args()
print(self.__args)
# 起動引数チェック
usernames = self.__GetUsernames()
Log().debug(f'対象ユーザ: {usernames}')
path_out = self.__GetDirOutputDb()
Log().debug(f'出力パス: {path_out}')
path_out.mkdir(parents=True, exist_ok=True)
self.__GetYaml()
self.__GetUrl()
# 草DB作成
# 草データ取得
data = None
try:
data = FromApi()
except RateLimitError as e:
data = FromSvg()
finally:
if data is None: raise NotGetError()
Insert(data)
def Insert(db, table_name, **kv):
columns = ','.join([k for k in kv.keys()])
values = ','.join(GetInsertValues(kv.values()))
#db.query(f'insert into {table_name} ({columns}) values ({values});')
sql = f'insert into {table_name} ({columns}) values ({values});'
Log().debug(sql)
db.query(sql)
def find_all_process_most_frequent(varas_group):
macro_trace_processes = {}
for vara in varas_group:
df_vara = df_log[df_log['case: orgao'] == vara]
p = PreProcess(df=df_vara)
p.select_desired_columns()
p.filter_outlier_timestamp()
p.filter_outlier_movements(lower=0.05, upper=0.95)
p.filter_outlier_trace_time(lower=0.05, upper=0.95)
l = Log(df_log=p.df_log.sort_values('time:timestamp'))
all_macro_trace = find_all_macro_trace(l.log, macrosteps)
for tran in all_macro_trace:
if tran not in macro_trace_processes:
macro_trace_processes[tran] = 0
macro_trace_processes[tran] += 1
macro_trace_processes = {k: v for k, v in \
sorted(macro_trace_processes.items(),
key=lambda item: item[1])}
macro_trace_processes
def __init__(self, uuid):
self.TAG = "BrowserProfileLauncher"
self.APPINDICATOR_ID = "io_serdarsen_github_budgie_browser_profile_launcher"
self.dir_path = os.path.dirname(os.path.realpath(__file__))
self.manager = None
self.popover = None
self.popoverHeightOffset = 20
self.popoverMinHeight = 150
self.popoverMaxHeight = 480
self.popoverMinWidth = 256
self.popoverHeight = 0
self.popoverWidth = 230
self.launcherButtonHeight = 36
self.lenProfiles = 0
self.launcherButtons = []
self.availableBrowsers = []
self.currentProfile = None
self.currentBrowser = None
self.chromiumBrowser = None
self.chromeBrowser = None
Budgie.Applet.__init__(self)
self.log = Log("budgie-browser-profile-launcher")
self.localStateHelper = LocalStateHelper()
self.popenHelper = PopenHelper()
self.sortHelper = SortHelper()
self.buildIndicator()
self.buildPopover()
self.buildStack()
self.update(True)
def CreateTable(db, table_name, **name_types):
columns = ', '.join(k + ' ' + v for k, v in name_types.items())
#for k, v in name_types.items():
# k + ' ' + v
#db.query('create table {table_name} (Id integer, Name text);')
sql = f'create table {table_name} ({columns});'
Log().debug(sql)
db.query(sql)
def Run(self):
parser = argparse.ArgumentParser(
description='GitHub Repository Uploader.',
)
#parser.add_argument('path_dir_pj')
parser.add_argument('-n', '--username', action='append')
parser.add_argument('-i', '--path_dir_input')
parser.add_argument('-o', '--path_dir_output')
parser.add_argument('-u', '--url', '--upload_url', action='append')
parser.add_argument('-y', '--yaml')
self.__args = parser.parse_args()
print(self.__args)
# 起動引数チェック
usernames = self.__GetUsernames()
Log().debug(f'対象ユーザ: {usernames}')
path_out = self.__GetDirOutputDb()
Log().debug(f'出力パス: {path_out}')
path_out.mkdir(parents=True, exist_ok=True)
self.__Getyaml()
self.__GetUrl()
def __init__(self, driver, timeout=10):
self.byDic = {
'id': By.ID,
'name': By.NAME,
'class_name': By.CLASS_NAME,
'xpath': By.XPATH,
'link_text': By.LINK_TEXT,
'css': By.CSS_SELECTOR
}
self.driver = driver
self.outTime = timeout
log = Log()
self.loger = log.get_log()
def log(url, method):
log = Log()
log.time = datetime.now()
log.url = url
log.method = method
log_file = open(constants.LOG_FILE, "a")
log_file.write(
str(log.url) + "\t" + log.method + "\t" +
log.time.strftime('%Y-%m-%d %H:%M:%S') + "\n")
log_file.close()
def login(driver):
log = Log()
loger = log.get_log()
loger.info("登录系统")
login = LoginPage(driver)
driver.get(url)
driver.maximize_window()
login.login_system(userName, passWord)
sleep(1)
user_page = UserPage(driver)
user_page.go_to_system()
user_page.switch_tab(2)
title = user_page.get_title()
assert "一企一档" in title, "进入一企一档失败，所以case失败"
def __init__(self):
self.TAG = "LocalStateHelper"
self.log = Log("budgie-browser-profile-launcher")
self.jsonHelper = JsonHelper()
self.localStateFileName = "Local State"
self.lastProfileNum = 0
self.lastPersonNum = 0
self.home_dir = expanduser("~")
self.chromiumConfigPath = self.home_dir + "/.config/chromium/"
self.chromeConfigPath = self.home_dir + "/.config/google-chrome/"
self.chromiumCachePath = self.home_dir + "/.cache/chromium/"
self.chromeCachePath = self.home_dir + "/.cache/google-chrome/"
self.availbleBrowsers = []
def __init__(self):
self.TAG = "PopenHelper"
self.log = Log("budgie-browser-profile-launcher")
self.procs = []
# _*_ coding:utf-8 _*_ # @Author: emily # @Date : 2018/3/20 13:52 # @Contact : [email protected] # @Desc: 安踏测试环境做忠诚度计算相关的性能测试时候，无法判断订单是否全部被处理完成。 # 为了解决这个问题，需要从日志里找出订单开始处理和处理完成的两断信息，如果关键信息出现了两次，那么认为已经处理完成。 # 如果没有出现关键信息或者不只出现两次，那么记录下来。 from log.Log import Log import os import time log = Log() #获取需要分析的全部关键字 def getKeyWord(): for i in range(0, 3): orderId = "record:key:orderEventHandler/152885895197" + str(i) searchKeyWord(orderId) i += 1 #查询关键字是否存在两个 def searchKeyWord(keywords): filename = "C:/test/loyalty2-calc.log" word = keywords count = 0 try: fobj = open(filename, 'r', encoding='UTF-8') except IOError as e:
from log.Log import INTENSE_FILTERING
from discovery.DFG import DFG
import visualization.Visualizer as Visualizer
from log.PreProcess import PreProcess
file_path = '/home/vercosa/Documentos/bases_desafio_cnj/'+\
'log_vara_2.csv'
p = PreProcess(file_location=file_path)
p.select_desired_columns()
p.filter_outlier_timestamp()
p.filter_outlier_movements(lower=0.01, upper=0.99)
p.filter_outlier_trace_time(lower=0.01, upper=0.99)
l = Log(df_log=p.df_log.sort_values('time:timestamp'))
# l.filter_variants(1.1)
dfg = DFG(l.log,
parameters={parameters.Parameters.AGGREGATION_MEASURE:'mean'},
variant=dfg_discovery.Variants.FREQUENCY)
dfg.filter_activities(number_act=10)
dfg.filter_edges(percentage=0.3)
print(dfg.dfg)
Visualizer.\
dfg_visualizer(dfg.dfg,
l.log,
variant=dfg_visualization.Variants.FREQUENCY)
def __init__(self, driver):
self.driver = driver
self.timeout = 10
self.t = 0.5
user = Log()
self.log = user.get_log()
'Baixa/Arquivamento',
]
pp = PreProcess(file_location=file_path)
pp.select_desired_columns()
pp.filter_outlier_timestamp()
pp.map_movements(movement_path)
df_log = pp.df_log
df_vara = df_log[df_log['case: orgao'] == vara]
pp_vara = PreProcess(df=df_vara)
pp_vara.filter_outlier_movements(lower=0.05, upper=0.95)
pp_vara.filter_outlier_trace_time(lower=0.05, upper=0.95)
log = Log(df_log=pp_vara.df_log.sort_values('time:timestamp'))
median_case_duration = case_statistics.\
get_median_caseduration(log.log, parameters={
case_statistics.Parameters.TIMESTAMP_KEY: "time:timestamp"
})
print('median case duration: ', str(median_case_duration/ (24*60*60)))
ms = MacroSteps(log.log, macrosteps)
res = ms.calc_macrosteps()
print(res)
df_time = df_time[(df_time['duration'] < lower_bound) |
(df_time['duration'] > upper_bound)]
df_time.count()
df_time.reset_index(level=0, inplace=True)
df['case:concept:name'].nunique()
key = ['case:concept:name']
i1 = df.set_index(key).index
i2 = df_time.set_index(key).index
df = df[~i1.isin(i2)]
df['case:concept:name'].nunique()
# log = log_converter.apply(df_log)
l = Log(df_log=df)
l.filter_variants(1)
dfg = DFG(l.log,
parameters={parameters.Parameters.AGGREGATION_MEASURE: 'mean'},
variant=dfg_discovery.Variants.PERFORMANCE)
print(dfg.dfg)
Visualizer.dfg_visualizer(dfg.dfg,
l.log,
variant=dfg_visualization.Variants.PERFORMANCE)
print('teste')
def __init__(self):
self.TAG = "JsonHelper"
self.log = Log("budgie-browser-profile-launcher")
from log.Log import Log
from pm4py.statistics.traces.log import case_statistics
from pm4py.algo.discovery.dfg import algorithm as dfg_discovery
from discovery.DFG import DFG
import visualization.Visualizer as Visualizer
# file_path = 'log/examples/running-example.xes'
file_path = 'log/examples/Receipt phase of an environmental permit' + \
' application process (_WABO_) CoSeLoG project.xes'
l = Log(file_path)
# variants_count = case_statistics.get_variant_statistics(l.log)
# variants_count = \
# sorted(variants_count,
# key=lambda x: x['count'],
# reverse=True)
# print('')
# print(variants_count)
# print('')
l.filter_variants(Log.INTENSE_FILTERING)
# dfg_discovery.apply(l.log)
dfg = DFG(l.log)