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本帖最后由 冫京冫京 于 2020-9-7 07:18 编辑
新人小白刚刚开始学习python，正在做一个小型的project，做了姑且算是一半吧，然后卡住了，冥思苦想几天实在毫无头绪，希望地里的大神们帮助一下。
Project的大致意思是：1.读取文件夹中的PDF文件SampleCh7.pdf，并从pdf文件中提取所有文本。 需要用PyPDF2这一部分已经做完了。下面会加上已做好的代码。
2. 构建一个WordAnalysis类来进行分析工作。该类应该包括以下方法（请自行定义属性）。
class WordAnalysis:
def __init__(self):
def __str__(self):
def AddRemovedWords(self, word):
def DelRemovedWords(self, word):
def ExtractWords(self, text):
def Show(self, freq):
For ExtractWords(self, text):
It should:
1). Strip off all punctuations, numbers, and symbols, only words are kept, and try to remove non-words as much as you can, for example, single letter words.
剥去所有标点符号、数字、符号，只保留单词，尽量去掉非单词，比如单字母单词。
2). Convert the plurals to singular words, and convert the capitalized words to lowercase words. You can use the pattern module to convert the plurals to singular words. Again, you need to install the pattern module as follows:
将复数词转换为单数词，将大写词转换为小写词。您可以使用模式模块将复数词转换为单数词。同样，你需要安装模式模块，如下。
3). Count the frequency of the words, and save them in a dictionary (internal attribute).
计算单词的频率，并将其保存在字典中（内部属性）。
For AddRemovedWords(self, word),
it will add a word to be filtered out, so that the dictionary will not save the frequency of the world, for example, ‘the’.
它会增加一个词被过滤掉，这样字典就不会保存世界的频率，比如'the'。
For DelRemovedWords(self, word):
It can remove a word from the filter list, and add the word back to the dictionary for frequency count.
它可以从过滤列表中删除一个单词，并将该单词添加回字典中进行频率计数。
For Show(self, freq):
It will show the words with frequency higher than specified frequency, freq, and show them in descending order.
它将显示频率高于指定频率freq的词，并按降序显示。
in __str__(self):
It prints out all the words in the dictionary. It should print out the words and frequency 4 pairs in a row.
它可以打印出字典中的所有单词。它应该连续打印出单词和频率4对。
In __init__(self)
It should construct all the internal attributes of the class.
它应该构造该类的所有内部属性。
以上这些关于class里面的function完全搞不懂，没有头绪。希望大神们能帮忙指导一下。
下面是目前为止的代码：
import PyPDF2
newfile = open('C:/CSTU/2020-7 Python for AI/Project submission/result.txt','w')
pdfFileObj = open('C:/CSTU/2020-7 Python for AI/Project submission/Copy of SampleCh7.pdf','rb')
pdfReader = PyPDF2.PdfFileReader(pdfFileObj)
pages = pdfReader.numPages
for i in range(pages):
pageObj = pdfReader.getPage(i)
print(pageObj.extractText())
newfile.write(pageObj.extractText())
pdfFileObj.close()
newfile.close()
最后要求输出到txt文档，结果格式是：
word -- number -- frequency: 31
word -- is -- frequency: 25
word -- to -- frequency: 24
word -- phone -- frequency: 24
word -- you -- frequency: 22
word -- in -- frequency: 22
word -- regular -- frequency: 19
word -- expression -- frequency: 19
word -- text -- frequency: 19
word -- of -- frequency: 19
word -- for -- frequency: 18
word -- pattern -- frequency: 17
word -- isphonenumber -- frequency: 15
word -- if -- frequency: 14
word -- string -- frequency: 13
word -- that -- frequency: 12
word -- chunk -- frequency: 12
word -- with -- frequency: 11
word -- return -- frequency: 11
pattern 17 matching 3 with 11 regular 19
expression 19 you 22 may 2 be 6
familiar 1 searching 1 for 18 text 19
by 4 pressing 1 ctrl 1 entering 1
word 4 re 4 looking 1 go 2
one 2 step 3 further 1 they 1
allow 1 to 24 specify 1 of 19
search 2 not 8 know 5 busines 1
exact 1 phone 24 number 31 but 9
if 14 live 1 in 22 united 1
state 1 or 4 canada 1 it 10
will 5 three 9 digit 5 followed 1
hyphen 8 then 6 fmy 5 more 9
optionally 1 area 3 code 10 at 9
start 2 thi 9 is 25 how 3
as 4 human 1 when 4 see 4
we 4 also 4 recognize 1 all 4
sort 1 other 4 every 1 day 2
email 2 address 2 have 6 symbol 1
middle 1 social 2 security 1 nine 1
two 1 website 1 url 1 often 1
period 1 forward 1 slash 1 news 1
headline 1 use 4 title 1 case 1
medium 1 hashtag 1 begin 1 contain 1
no 1 space 1 chapter 4 are 3
helpful 1 few 1 non 1 programmer 2
about 2 them 2 even 3 though 1
most 1 modern 1 editor 2 processor 1
such 2 microsoft 1 openof 1 ce 1
nd 9 replace 2 feature 2 that 12
can 6 based 1 on 8 huge 1
time 2 saver 1 just 1 software 1
user 1 fact 1 tech 1 writer 1
cory 2 doctorow 2 argue 1 should 2
teaching 1 before 1 programming 1 knowing 1
mean 1 difference 1 between 1 solving 2
problem 2 nerd 1 forget 1 solve 1
cou 1 ple 1 keystroke 1 take 2
person 1 tediou 1 error 1 prone 1
work 2 slog 1 through 4 ll 4
writing 1 program 9 out 1 using 2
make 2 much 2 les 3 bloated 1
show 1 basic 1 move 1 some 1
powerful 1 string 13 substitution 1 creating 1
ymy 1 own 1 character 10 class 1
finally 1 end 1 write 2 automatically 1
extract 1 from 3 block 1 finding 2
without 1 say 1 want 1 an 4
american 2 here 1 example 5 let 1
function 8 named 1 isphonenumber 15 check 7
whether 3 match 5 returning 1 either 1
true 3 false 9 open 1 new 2
le 2 tab 1 enter 1 following 3
save 1 py 2 def 1 len 2
return 11 range 4 isdecimal 3 ?here 1
what 3 ict 2 really 1 teach 2
kid 2 do 3 guardian 1 december 1
http 1 www 1 theguardian 1 com 1
technology 1 dec 1 trueprint 1 print 8
moshi 10 run 4 output 2 look 2
like 5 truei 1 falsethe 1 ha 1
several 1 valid 1 any 4 these 3
fail 3 first 1 exactly 1 rst 4
consist 1 only 2 numeric 2 rest 1
follow 1 must 1 after 2 another 2
nally 1 execution 1 manage 1 get 1
past 1 calling 2 argument 1 test 1
because 1 long 2 wanted 1 within 1
larger 1 would 5 add 2 last 1
call 4 message 9 me 7 tomorrow 1
my 1 office 1 chunk 12 found 3
done 4 each 3 iteration 3 loop 4
assigned 3 variable 1 itera 1 tion 1
next 1 value 1 so 3 pas 1
continue 1 eventually 1 entire 1 testing 1
piece 1 printing 1 sati 1 es 1
once 1 going 1 while 1 short 2
could 2 million 1 still 1 than 2
second 2 similar 1 quicker 1 previou 2
number? 1 nding 1 lot 1 something 1
limited 1 line 1 formatted 1 num 1
ber 1 had 1 extension 1 validate 1
yet 1 addi 1 tional 1 there 1
easier 1 way 1 called 1 regex 5
description 1 pat 1 tern 1 stand 1
character歵hat 1 single 1 numeral 1 used 1
python 1 same 1 did 1 sophisticated 1
adding 1 brace 1 saying 1 ?match 1
slightly 1 shorter 1 correct 1 format 1
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