def main(url, checkRange=30):
header.processBegin(url=url)
header.clearFolder() #[2019.02.11]
try:
soup = request2soup(url)
df_1 = parsingTitle(soup, checkRange)
if len(df_1) != 0:
#outputCsv(df_1, "第一層結果", FinalPath)
header.outputCsv(df_1, "第一層結果")
df_2 = parsingDetail(df_1)
#outputCsv(df_2, "第二層結果", FinalPath)
header.outputCsv(df_2, "第二層結果")
header.RESULT_COUNT = len(df_2)
header.zipFile()
header.createInfoFile()
header.createOKFile()
header.outputLastResult(df_1, header.lastResult,
checkRange) #[2019.02.11]新增產出lastResult方法
except:
logging.error("執行爬網作業失敗")
traceback.print_exc()
header.createInfoFile()
header.processEnd()
def main(url, tabNumber, checkRange=15):
header.processBegin()
header.clearFolder()
DownloadTool = SeleniumUtil.ChromeDownload()
DownloadTool.setDownLoadTempPath(header.TEMP_PATH)
DownloadTool.setDownLoadFinalPath(FinalPath)
chrome_options = DownloadTool.getChromeOptions()
driver = webdriver.Chrome(
chrome_options=chrome_options) # open chrome browser with Options
try:
if tabNumber >= 19 and tabNumber <= 22 and isinstance(tabNumber, int):
url = url + str(tabNumber)
else:
raise ValueError("tabNumber 必須為 19 到 22 的整數")
driver.get(url)
df_1 = parsingTitle(url, driver, checkRange)
if len(df_1) != 0:
header.outputCsv(df_1, "第一層結果", FinalPath)
df_2 = parsingDetail(df_1, tabNumber, FinalPath)
header.outputCsv(df_2, "第二層結果", FinalPath)
header.RESULT_COUNT = len(df_1)
header.zipFile()
header.createInfoFile()
header.createOKFile()
header.outputLastResult(df_1, header.lastResult,
checkRange) # 2019-02-01新增產出lastResult方法
except:
logging.error("執行爬網作業失敗")
header.EXIT_CODE = -1
traceback.print_exc()
header.processEnd()
def main(url, checkRange = 30):
header.processBegin(url = url)
header.clearFolder()
try:
soup = request2soup(url, 1)
df_1 = parsingTitle(soup, checkRange)
if len(df_1) != 0:
header.outputCsv(df_1, "第一層結果")
df_2 = parsingDetail(df_1)
header.outputCsv(df_2, "Result")
header.RESULT_COUNT= len(df_2)
header.zipFile()
header.createInfoFile()
header.createOKFile()
except:
print("執行爬網作業失敗")
logging.error("執行爬網作業失敗")
header.EXIT_CODE = -1
traceback.print_exc()
header.createInfoFile()
header.processEnd()
def main(url, checkRange = 30):
header.processBegin()
header.clearFolder()
try:
df_1 = parsingTitle(url, checkRange)
if len(df_1) == 0:
return
header.outputCsv(df_1, "第一層結果", FinalPath)
df_2 = parsingDetail(df_1, FinalPath)
header.outputCsv(df_2, "第二層結果", FinalPath)
header.RESULT_COUNT = len(df_1)
header.zipFile()
header.createInfoFile()
header.createOKFile()
header.outputLastResult(df_1, header.lastResult, checkRange) # 2019-02-01新增產出lastResult方法
except:
logging.error("執行爬網作業失敗")
header.EXIT_CODE = -1
traceback.print_exc()
header.processEnd()
def main():
header.processBegin(url=WEB_URL)
header.clearFolder()
try:
reqMap = {
# [20190402] 新增查詢的縣市
"REGION_IDs": {
"1": "台北市",
"2": "基隆市",
"3": "新北市",
"4": "新竹市",
"5": "新竹縣",
"6": "桃園市",
"7": "苗栗縣",
"8": "台中市",
"10": "彰化縣",
"11": "南投縣",
"12": "嘉義市",
"13": "嘉義縣",
"14": "雲林縣",
"15": "台南市",
"17": "高雄市",
"19": "屏東縣",
"21": "宜蘭縣",
"22": "台東縣",
"23": "花蓮縣",
"24": "澎湖縣",
"25": "金門縣",
"26": "連江縣"
},
"QUERY_TYPEs": {
'1': "住宅用地",
'2': "商業用地",
'3': "工業用地"
},
"CONDITIONS": {
"is_new_list": '1',
"type": '2',
"searchtype": '1',
"firstRow": '0',
"kind": "11", # 廠房土地出售
"area": "300," # 最小 300 坪
}
}
standbyDataFrame, historyDataFrame = parsingTitle(reqMap)
if len(standbyDataFrame) < 1:
# 無資料更新
logMsg = "無資料更新，爬網日期：" + TODAY
print(logMsg)
logging.critical(logMsg)
else:
finishDataFrame, detailDataFrame = parsingDetail(standbyDataFrame)
header.outputCsv(detailDataFrame, header.PROJECT)
header.RESULT_COUNT = len(detailDataFrame)
# 更新 crawlHistory 檔案
updateHistoryDataFrame = pd.concat(
[historyDataFrame, finishDataFrame], ignore_index=True)
header.outputCsv(updateHistoryDataFrame, "crawlHistory",
header.LAST_RESULT_PATH)
header.zipFile()
header.createInfoFile()
header.createOKFile()
except:
setErrorMessage("執行爬網作業失敗")
header.createInfoFile()
header.zipFile(zipFolder=header.LOG_PATH, zipResultWithLog=False)
header.processEnd()
