Python string.translate函数代码示例

def index_img_kw(img, title, description):
    """
    Parses the the title and description and creates a frequency table,
    then stores the frequencies into the Keywords table for the given
    image_id
    """

    frequencies = {}
    title_kws = title.split()
    des_kws = description.split()


    for word in title_kws:
        word = word.lower()
        word = string.translate(word, None, string.punctuation)
        if word not in STOP_WORDS:
            frequencies[word] = frequencies[word] + 2 if word in frequencies else 2
    
    for word in des_kws:
        if word not in STOP_WORDS:
            word = word.lower()
            word = string.translate(word, None, string.punctuation)
            frequencies[word] = frequencies[word] + 1 if word in frequencies else 1
    
    # Save in database now for this image
    try:
        for entry, val in frequencies.items():
        
            kw = Keywords()
            kw.keyword = entry.lower()
            kw.frequency = val
            kw.image = img
            kw.save()
    except:
        print sys.exc_info()

def make_langs(country_name):
    """Generates all four answers for the primary language quiz question, 
    including the right answer. Returns as a set."""
    langs = set()

    #Make country objects for wrong answers from same continent
    country_obj = Country.query.filter(Country.country_name == country_name).first()
    right_langs = country_obj.languages
    right_langs = str(right_langs)
    right_langs = translate(right_langs, None, '{"}')
    langs.add(right_langs)
    if country_obj.continent_name == "Caribbean":
        langs.add("English, Spanish")

    continent = country_obj.continent_name
    nearby_countries = Country.query.filter(Country.continent_name == continent, Country.country_name != country_name).all()
    top_index = len(nearby_countries) - 1
    print top_index

    while len(langs) < 4:
        index = randint(0, top_index)
        wrong_lang = (nearby_countries[index]).languages
        wrong_lang = str(wrong_lang)
        wrong_lang = translate(wrong_lang, None, '{"}')
        langs.add(wrong_lang)
        print langs
        print len(langs)


    return langs

def encrypt_all(password, method, op, data):
    if method is not None and method.lower() == 'table':
        method = None
    if not method:
        [encrypt_table, decrypt_table] = init_table(password)
        if op:
            return string.translate(data, encrypt_table)
        else:
            return string.translate(data, decrypt_table)
    else:
        import M2Crypto.EVP
        result = []
        method = method.lower()
        (key_len, iv_len) = method_supported[method]
        (key, _) = EVP_BytesToKey(password, key_len, iv_len)
        if op:
            iv = random_string(iv_len)
            result.append(iv)
        else:
            iv = data[:iv_len]
            data = data[iv_len:]
        if method == 'salsa20-ctr':
            cipher = encrypt_salsa20.Salsa20Cipher(method, key, iv, op)
        elif method == 'rc4-md5':
            cipher = encrypt_rc4_md5.create_cipher(method, key, iv, op)
        else:
            cipher = M2Crypto.EVP.Cipher(method.replace('-', '_'), key, iv,
                                         op, key_as_bytes=0, d='md5',
                                         salt=None, i=1, padding=1)
        result.append(cipher.update(data))
        return ''.join(result)

def hashword(plaintext):
	"""
	Munge a plaintext word into something else. Hopefully, the result
	will have some mnemonic value.
	"""
	# get a list of random bytes. A byte will be randomly picked from
	# this list when needed.
	rb = getrandomlist()
	# 0.25 chance of case being swapped
	if rb[rb[0]] < 64:
		plaintext = string.swapcase(plaintext)
	# 0.50 chance of vowels being translated one of two ways.
	if rb[rb[2]] > 127:
		plaintext = string.translate(plaintext, 
			string.maketrans('aeiou AEIOU', '@3!0& 4#10%'))
	else:
		plaintext = string.translate(plaintext, 
			string.maketrans('aeiou AEIOU', '^#1$~ $3!0&'))
	# 0.4 chance of some additional consonant translation
	if rb[rb[4]] < 102:
		plaintext = string.translate(plaintext, 
			string.maketrans('cglt CGLT', '(<1+ (<1+'))
	# if word is short, add some digits
	if len(plaintext) < 5:
		plaintext = plaintext + `rb[5]`
	# 0.2 chance of some more digits appended
	if rb[rb[3]] < 51:
		plaintext = plaintext + `rb[205]`
	return plaintext

def main():
    f=string.ascii_lowercase
    t=f[2:]+f[:2]
    trans_tables=string.maketrans(f,t)
    encs="g fmnc wms bgblr rpylqjyrc gr zw fylb. rfyrq ufyr amknsrcpq ypc dmp. bmgle gr gl zw fylb gq glcddgagclr ylb rfyr'q ufw rfgq rcvr gq qm jmle. sqgle qrpgle.kyicrpylq() gq pcamkkclbcb. lmu ynnjw ml rfc spj."
    print(string.translate(encs,trans_tables))
    print(string.translate('map',trans_tables))

def word_histogram(source):
    """Create histogram of normalized words (no punct or digits)
	scale that in terms of percentage"""
    hist = {}
    trans = maketrans('','')
    if type(source) in (StringType,UnicodeType):  # String-like src
        for word in split(source):
            word = translate(word, trans, punctuation+digits)
	    word=word.lower()
            if len(word) > 0:
                hist[word] = hist.get(word,0) + 1
    elif hasattr(source,'read'):                  # File-like src
        try:
            from xreadlines import xreadlines     # Check for module
            for line in xreadlines(source):
                for word in split(line):
                    word = translate(word, trans, punctuation+digits)
                    word=word.lower()
                    if len(word) > 0:
                        hist[word] = hist.get(word,0) + 1
        except ImportError:                       # Older Python ver
            line = source.readline()          # Slow but mem-friendly
            while line:
                for word in split(line):
                    word = translate(word, trans, punctuation+digits)
                    word=word.lower()
                    if len(word) > 0:
                        hist[word] = hist.get(word,0) + 1
                line = source.readline()
    else:
        raise TypeError, \
              "source must be a string-like or file-like object"
    return hist

def seq2(ch,start,end):
    trans = string.maketrans('ATCGatcg','TAGCtagc')
    if ch[0:2] == 'ch':
        inFile = open('/netshare1/home1/people/hansun/Data/GenomeSeq/Human/ucsc.hg19.fasta.fa')
        while True:
            line1 = inFile.readline().strip()
            line2 = inFile.readline().strip()
            if line1:
                if line1 == '>'+ch:
                    if start <= end:
                        seq = line2[start-1:end].upper()
                    else:
                        seq = string.translate(line2[end-1:start][::-1],trans).upper()
                    return seq
            else:
                break
        inFile.close()
    elif ch[0:2] == 'NC':
        inFile = open('/netshare1/home1/people/hansun/Data/VirusesGenome/VirusesGenome.fasta.fa')
        while True:
            line1 = inFile.readline().strip()
            line2 = inFile.readline().strip()
            if line1:
                if line1.find('>'+ch) == 0:
                    if start <= end:
                        seq = line2[start-1:end].upper()
                    else:
                        seq = string.translate(line2[end-1:start][::-1],trans).upper()
                    return seq
            else:
                break
        inFile.close()

def encrypt_all(password, method, op, data):
    if method is not None and method.lower() == "table":
        method = None
    if not method:
        [encrypt_table, decrypt_table] = init_table(password)
        if op:
            return string.translate(data, encrypt_table)
        else:
            return string.translate(data, decrypt_table)
    else:
        import M2Crypto.EVP

        result = []
        method = method.lower()
        (key_len, iv_len) = method_supported[method]
        (key, _) = EVP_BytesToKey(password, key_len, iv_len)
        if op:
            iv = random_string(iv_len)
            result.append(iv)
        else:
            iv = data[:iv_len]
            data = data[iv_len:]
        cipher = M2Crypto.EVP.Cipher(
            method.replace("-", "_"), key, iv, op, key_as_bytes=0, d="md5", salt=None, i=1, padding=1
        )
        result.append(cipher.update(data))
        f = cipher.final()
        if f:
            result.append(f)
        return "".join(result)

def alleleCount(baseList,refNuc):
    table = string.maketrans('ATCG', 'TAGC')
    pos = defaultdict(int)
    neg = defaultdict(int)
    if refNuc in ['A', 'T']:
        for (base, isReverse) in baseList:
            if isReverse:    # negative strand
                neg[string.translate(base, table)] += 1
            else:    # positive strand
                pos[base] += 1
    elif refNuc == 'C': # only negative strand
        for (base, isReverse) in baseList:
            if isReverse:
                neg[string.translate(base, table)] += 1
    elif refNuc == 'G': # only positive strand
        for (base, isReverse) in baseList:
            if not isReverse:
                pos[base] += 1
    aCount = pos['A'] + neg['A']
    tCount = pos['T'] + neg['T']
    cCount = pos['C'] + neg['C']
    gCount = pos['G'] + neg['G']
    total = aCount + tCount + cCount + gCount
    posCov = sum([pos[base] for base in ['A', 'T', 'C', 'G']])
    negCov = sum([neg[base] for base in ['A', 'T', 'C', 'G']])
    return aCount, tCount, cCount, gCount, total, posCov, negCov

def decoder3():
    table = string.maketrans(
        'abcdefghijklmnopqrstuvwxyz',
        'cdefghijklmnopqrstuvwxyzab'
    )
    print string.translate(codedmessage, table)
    print string.translate('map', table)

 def encripta_maketrans(self, texto):
     # Conjunto dos caracteres do alfabeto sob a lógica do Rot13
     alfabeto = string.maketrans("ABCDEFGHIJKLMabcdefghijklmNOPQRSTUVWXYZnopqrstuvwxyz", 
         "NOPQRSTUVWXYZnopqrstuvwxyzABCDEFGHIJKLMabcdefghijklm")
     # A função translate que faz a conversão 
     # recebe o que deve ser convertido também o nome da técnica a ser usado que neste caso é o rot_13
     print string.translate(texto, alfabeto)      

 def __find(self):
     self.status(1, "searching")
     self.__nfound = 0
     for i, filename in enumerate(self.get_files()):
         if i % 16 == 0:
             self.status(self.__nfound)
         try:
             f = open(filename, 'r')
         except IOError:
             continue
         for linenumber, line in enumerate(f):
             if not self.__running:
                 self.__finished()
             if BINARY_RE.match(line):
                 break
             line = string.translate(line, all_chars, hi_bit_chars)
             line = string.translate(line, hi_lo_table)
             matches = self.__pattern.findall(line)
             if len(matches):
                 self.__nfound = self.__nfound + len(matches)
                 if self.__nfound >= self.__options.maxresults:
                     self.__finished()
                 result = GrepResult(linenumber, filename, line, matches)
                 gtk.threads_enter()
                 self.emit('found', result)
                 gtk.threads_leave()
         f.close()
     self.__finished()

def scrape_links_and_wordlistify(links, lower=False, verbose=1):
    import nltk
    import requests
    import string
    raw = ''
    wordlist = {}
    for site in links:
        try:
            if verbose == 1:
                print '[+] fetching data from: ', site
            if site.find('http://pastebin.com/') == 0:
                raw = requests.get(site.replace('http://pastebin.com/', 'http://pastebin.com/raw.php?i=')).content
            else:
                raw = requests.get(site).content
            if lower == False:
                l = string.translate(nltk.clean_html(raw), string.maketrans(string.punctuation, ' ' * 32)).split()
                freq_an(l, wordlist)
            else:
                l = string.lower(nltk.clean_html(raw))
                l = string.translate(l, string.maketrans(string.punctuation, ' ' * 32)).split()
                freq_an(l, wordlist)
        except:
            if verbose == 1:
                print '[-] Skipping url: ', site
    return wordlist

 def make_code(self):
     symbols = (string.ascii_uppercase + string.digits)
     string.translate(symbols, None, 'OI')
     random.seed()
     code = ''
     for i in range(10):
         code += random.choice(symbols)
     self.code = code

def decoder4():
    table = string.maketrans(
        string.ascii_lowercase,
        string.ascii_lowercase[2:] + string.ascii_lowercase[:2]
    )
    print string.translate(codedmessage, table)
    print codedmessage.translate(table)
    print string.translate('map', table)