OS:
import sys,os # print(os.getcwd()) # print(os.chdir('..')) # # os.removedirs('dir1/dir2')#blank will be del,or can't # print(os.listdir()) #print(os.stat('ss.py')) #****the time of create and modify # print(os.stat('path/filename')) #os.sep windows:\ linus:/ # os.linesep windows: linus: # print(os.system('dir')) # print(os.environ) #get the system's environment variables # os.path.dirname(path=) # os.path.basedirname(path=) #the file name # os.path.abspath(path=) #absolute path # os.path.split(path=) #split with dirname and filename # os.path.exists(path=) #judge # os.path.isabs(path=) # os.path.isfile(path=) # os.path.isdir(path=) #**************os.path.join(path1[,path2[,...]]) # os.path.getatime() #the last save time # os.path.getmtime() #the last modify time
SYS:
# **************sys****************** # sys.argv #the same as input :order line list:the first character is the path of the current program # sys.exit() # sys.version # sys.maxint # sys.path # sys.platform # print(sys.argv) # command = sys.argv[1] # path = sys.argv[2] # if command == 'post': # pass # if command == 'get': # pass #********the prosessing line is based on the method # import time # for i in range(10): # sys.stdout.write('#') #the same as print # time.sleep(0.1) # sys.stdout.flush()
JSON & PICKLE & SHELVE:
JSON:Can be transformed in defferent language,expecially in JS;
Pickle: can only be used in Python，and will be incompatible in defferent python version,so usually use pickle to save datas that is not important .
#dumps:Serialization loads:Deserialization # dir='{"name":"alex"}' # f=open("hello","w") # f.write(dir) # f_read=open("hello","r") # data=f_read.read() # print(data) # data=eval(data) # print(data["name"]) import json # dir='{"name":"alex"}' # data=json.dumps(dir) # i=8 # l=[11,22] # data1=json.dumps(i) # print(data1) # print(type(data1)) # data2=json.dumps(l) # print(data2) # print(type(data2)) # print(data) # print(type(data)) # f=open("new_hello","w") # f.write(data) #the former two sentense is equal to json.dump(data,f) # f_read=open("new_hello","r") # data=json.loads(f_read.read()) #the former two sentense is equal to json.load(f) # print(data) # print(type(data)) # import json # with open("json_test","r") as f: # data = f.read() # data = json.loads(data) # print(data["name"]) # import pickle # # j = pickle.dumps(dir) # # print((type(j))) #<class 'bytes'> # # f = open("pickle_test","wb") # # f.write(j) # #=======>data=pickle.dump(f,dir) # f = open("pickle_test","rb") # data=pickle.loads(f.read()) # print(data) #=======>data=pickle.load(f) #shelve:the same as pickle # import shelve # f = shelve.open(r'shelve') # # f['stu1_info']={'name':'alex',"age":'29'} # # f.close() # #generate 3 files # print(f.get('stu1_info')["age"])
XML:the same as json but json is more esier, XML can be recognized in every program language;
The file:
<?xml version="1.0"?> <data> <country name="Liechtenstein"> <rank updated="yes">2</rank> <year>2008</year> <gdppc>141100</gdppc> <neighbor name="Austria" direction="E"/> <neighbor name="Switzerland" direction="W"/> </country> <country name="Singapore"> <rank updated="yes">5</rank> <year>2011</year> <gdppc>59900</gdppc> <neighbor name="Malaysia" direction="N"/> </country> <country name="Panama"> <rank updated="yes">69</rank> <year>2011</year> <gdppc>13600</gdppc> <neighbor name="Costa Rica" direction="W"/> <neighbor name="Colombia" direction="E"/> </country> </data>
xml operations:add,del,modify and check:
# import xml.etree.ElementTree as ET # tree = ET.parse('xml_lesson') # root = tree.getroot() # print(root.tag) #traversing xml file # for i in root: # # print(i) # # print(i.tag) # for j in i: # # print(j.tag) # # print(j.attrib) # print(j.text) # print(i.attrib) #trversing year nodes: # for node in root.iter('year'): # print(node.tag,node.text) ####modify: # for node in root.iter('year'): # new_year = int(node.text) + 1 # node.text = str(new_year) # node.set("updated","yes") # tree.write("abc.xml") ######delete: # for country in root.findall('country'): # rank=int(country.find('rank').text) # if rank > 50: # root.remove(country) # tree.write('output.xml') ########create a new xml file: # new_xml =ET.Element("namelist") # name = ET.SubElement(new_xml,"name",attrib={"enrolled":"yes"}) # age = ET.SubElement(name,"age",attrib={"checked":"no"}) # sex = ET.SubElement(name,"sex") # sex.text = "fale" # name2 = ET.SubElement(new_xml,"name",attrib={"enrolled":"yes"}) # age = ET.SubElement(name2,"age") # age.text = "19" # # et = ET.ElementTree(new_xml) # et.write("test_xml",encoding="utf-8",xml_declaration=True)
RE:
import re ret = re.findall('a..in', 'helloalvin') print(ret) # ['alvin'] ret = re.findall('^a...n', 'alvinhelloawwwn') print(ret) # ['alvin'] ret = re.findall('a...n$', 'alvinhelloawwwn') print(ret) # ['awwwn'] ret = re.findall('a...n$', 'alvinhelloawwwn') print(ret) # ['awwwn'] ret = re.findall('abc*', 'abcccc') # 贪婪匹配[0,+oo] print(ret) # ['abcccc'] ret = re.findall('abc+', 'abccc') # [1,+oo] print(ret) # ['abccc'] ret = re.findall('abc?', 'abccc') # [0,1] print(ret) # ['abc'] ret = re.findall('abc{1,4}', 'abccc') print(ret) # ['abccc'] 贪婪匹配 #注意：前面的 *, +,?等都是贪婪匹配，也就是尽可能匹配，后面加?号使其变成惰性匹配 ret = re.findall('abc*?', 'abcccccc') print(ret) # ['ab'] #元字符之字符集［］： # --------------------------------------------字符集[] ret = re.findall('a[bc]d', 'acd') print(ret) # ['acd'] ret = re.findall('[a-z]', 'acd') print(ret) # ['a', 'c', 'd'] ret = re.findall('[.*+]', 'a.cd+') print(ret) # ['.', '+'] # 在字符集里有功能的符号: - ^ ret = re.findall('[1-9]', '45dha3') print(ret) # ['4', '5', '3'] ret = re.findall('[^ab]', '45bdha3') print(ret) # ['4', '5', 'd', 'h', '3'] ret = re.findall('[d]', '45bdha3') print(ret) # ['4', '5', '3'] # 元字符之转义符 # 反斜杠后边跟元字符去除特殊功能,比如. # 反斜杠后边跟普通字符实现特殊功能,比如d,d+ # # d 匹配任何十进制数；它相当于类 [0-9]。 # D 匹配任何非数字字符；它相当于类 [^0-9]。 # s 匹配任何空白字符；它相当于类 [ fv]。 # S 匹配任何非空白字符；它相当于类 [^ fv]。 # w 匹配任何字母数字字符；它相当于类 [a-zA-Z0-9_]。 # W 匹配任何非字母数字字符；它相当于类 [^a-zA-Z0-9_] # 匹配一个特殊字符边界，比如空格 ，&，＃等