def onExport(self, evt):
dialog = wx.FileDialog(self, u"选择要导出的文件位置", os.getcwd(), style=wx.FD_SAVE | wx.FD_OVERWRITE_PROMPT,
wildcard="*.csv")
if dialog.ShowModal() == wx.ID_OK:
filePath = dialog.GetPath()
if filePath:
try:
personalWorkDayDict = self.exportData[0]
dailyAttendenceList = self.exportData[1]
personalWorkDayLengthList = self.exportData[2]
startDate = self.exportData[3]
firstLine = u'员工名,班组名'
totalWeekNum = int(len(dailyAttendenceList) / 7)
for totalWeekNum in range(1, totalWeekNum + 1):
dateStr = u',"第 ' + str(totalWeekNum) + u' 周\n'
endDate = TimeUtil.getFormatedDate(startDate, 6)
dateStr += (startDate + ' -- ' + endDate + '"')
firstLine += dateStr
startDate = TimeUtil.getFormatedDate(endDate, 1)
lines = [firstLine]
for item in personalWorkDayDict:
wokerName = item[0]
groupName = item[1]
workDayList = item[2]
lines.append(wokerName + ',' + groupName + u',' + u','.join(
list(map(lambda week: ' '.join(list(map(str, week))), workDayList))))
lines.append('\n')
lines.append(u'员工名,班组名,总天数,总工时（小时）')
# 工时
for i in range(len(personalWorkDayLengthList)):
lines.append(','.join(personalWorkDayLengthList[i]))
lines.append('\n')
lines.append(u'日期,出勤员工')
groupInfo = ',' + ''.join(list(map(lambda x: x[1].groupName + ',' * int(x[1].workLoad), dailyAttendenceList[0][1])))
innerLines = list()
for dailyAttendence in dailyAttendenceList:
date = dailyAttendence[0]
groupAttendenceList = dailyAttendence[1]
attendenceStr = date
for groupAttendence in groupAttendenceList:
attendence = groupAttendence[0]
attendenceStr += ',' + attendence
innerLines.append(attendenceStr)
lines.append(groupInfo)
lines.extend(innerLines)
FileUtil.writeAll(filePath, lines)
wx.MessageBox(u'成功导出到文件', filePath)
except Exception as e:
wx.MessageBox(u'导出失败，原因为: ' + str(e))
dialog.Destroy()
def onFileRead(self, filePath):
if filePath:
try:
workerList = FileUtil.readAll(filePath)
wx.MessageBox(u"导入数据成功", u"导入数据", style=wx.OK | wx.ICON_EXCLAMATION)
return workerList
except Exception as e:
wx.MessageBox(u"导入数据失败，请检测数据格式，并保证文件为UTF-8格式", u"导入数据", style=wx.OK | wx.ICON_EXCLAMATION)
wx.MessageBox(str(e))
return list()
import jieba as jb
from wordcloud import WordCloud
import matplotlib.pyplot as plt
from src.Util.FileUtil import FileUtil
import json
txt = FileUtil.readFileToTex("E:\\flaskProject\\static\\file\wordText.txt",'["岗位职责""工作描述""工作职责""工作职责1""要求"]')
print(txt)
jb.add_word("机器学习",4)
words = jb.cut(txt) # 使用精确模式对文本进行分词
counts = {} # 通过键值对的形式存储词语及其出现的次数
# 统计词频
for word in words:
if len(word) == 1: # 单个词语不计算在内
continue
else:
counts[word] = counts.get(word, 0) + 1 # 遍历所有词语，每出现一次其对应的值加 1
# 注解：dict.get(word,0)当能查询到相匹配的字典时，就会显示相应key对应的value，如果不能的话，就会显示后面的这个参数
# 有些不重要的词语但出现次数较多，可以通过构建排除词库excludes来删除
items = list(counts.items())
items.sort(key=lambda x: x[1], reverse=True) # 根据词语出现的次数进行从大到小排序
jsonData = json.dumps(items,ensure_ascii=False)
print(jsonData)
# 输出统计结果
for i in range(10):
word, count = items[i]
def onFileRead(self, filePath):
if filePath:
# try:
lines = FileUtil.readAll(filePath)
self.updateGrid(lines)
wx.MessageBox("导入数据成功" + ' '.join(lines), "导入数据", style=wx.OK | wx.ICON_EXCLAMATION)
