Python re.split() Examples

def gist_fetch(query, page_idx, total_items=1000):
    gist_url = "https://gist.github.com/search?utf8=%E2%9C%93&q={}&p={}"
    query = urllib.parse.quote(query)
    gists = []

    try:
        resp = requests.get(gist_url.format(query, page_idx))
        soup = bs4.BeautifulSoup(resp.text, 'html.parser')
        total_items = min(total_items, int(
            [x.text.split()[0] for x in soup.find_all('h3')
                if "gist results" in x.text][0].replace(',', '')))
        gists = [x.get("href") for x in soup.findAll(
                            "a", class_="link-overlay")]
    except IndexError:
        return {"data": None, "total_items": 0}

    return {"data": gists, "total_items": total_items} 

def write_version_py():
    content = """# GENERATED VERSION FILE
# TIME: {}

__version__ = '{}'
short_version = '{}'
version_info = ({})
"""
    sha = get_hash()
    with open('mmdet/VERSION', 'r') as f:
        SHORT_VERSION = f.read().strip()
    VERSION_INFO = ', '.join(SHORT_VERSION.split('.'))
    VERSION = SHORT_VERSION + '+' + sha

    version_file_str = content.format(time.asctime(), VERSION, SHORT_VERSION,
                                      VERSION_INFO)
    with open(version_file, 'w') as f:
        f.write(version_file_str) 

def make_cuda_ext(name, module, sources, sources_cuda=[]):

    define_macros = []
    extra_compile_args = {'cxx': []}

    if torch.cuda.is_available() or os.getenv('FORCE_CUDA', '0') == '1':
        define_macros += [('WITH_CUDA', None)]
        extension = CUDAExtension
        extra_compile_args['nvcc'] = [
            '-D__CUDA_NO_HALF_OPERATORS__',
            '-D__CUDA_NO_HALF_CONVERSIONS__',
            '-D__CUDA_NO_HALF2_OPERATORS__',
        ]
        sources += sources_cuda
    else:
        print(f'Compiling {name} without CUDA')
        extension = CppExtension
        # raise EnvironmentError('CUDA is required to compile MMDetection!')

    return extension(
        name=f'{module}.{name}',
        sources=[os.path.join(*module.split('.'), p) for p in sources],
        define_macros=define_macros,
        extra_compile_args=extra_compile_args) 

def find_test_path(test_file):
    """Searches for the test file and returns the path if found
    As a default, the currend working directory is the top of the search.
    If a directory was provided as part of the argument, the directory will be
    joined with cwd unless it was an absolute path, in which case, the
    absolute path will be used instead. 
    """
    test_file += ".py"
    test_path = os.path.split(test_file)
    top = os.path.join(os.getcwd(), test_path[0])

    for (path, dirs, files) in os.walk(top):
        if test_path[1] in files:
            return  os.path.join(path, test_path[1])
    raise FileNotFoundError("Could not find " + test_path[1] + 
                            "in directory: " + top) 

def basic_tokenizer(sentence):
  """Very basic tokenizer: split the sentence into a list of tokens."""
  words = []
  if old_style:
    for space_separated_fragment in sentence.strip().split():
      words.extend(re.split(_OLD_WORD_SPLIT, space_separated_fragment))
    return [w for w in words if w]
  for space_separated_fragment in sentence.strip().split():
    tokens = [t for t in re.split(_WORD_SPLIT, space_separated_fragment) if t]
    first_is_char = False
    for i, t in enumerate(tokens):
      if len(t) == 1 and t in _PUNCTUATION:
        tokens[i] = _CHAR_MARKER + t
        if i == 0:
          first_is_char = True
    if words and words[-1] != _SPACE and (first_is_char or is_char(words[-1])):
      tokens = [_SPACE] + tokens
    spaced_tokens = []
    for i, tok in enumerate(tokens):
      spaced_tokens.append(tokens[i])
      if i < len(tokens) - 1:
        if tok != _SPACE and not (is_char(tok) or is_char(tokens[i+1])):
          spaced_tokens.append(_SPACE)
    words.extend(spaced_tokens)
  return words 

def extract_fields_db2(obj, line, field_name_regex):
    line = '#'.join(re.split('\s*#', line))

    last_key = ''
    field_names = re.findall(field_name_regex, line)
    for field in reversed(field_names):
        split_at = line.find(field) + len(field)
        field_name = re.split('\s*:', field)[0]
        # don't overwrite existing fields
        if field_name in obj:
            continue
        else:
            obj[field_name] = ' '.join(line[split_at:].split())
            if not last_key:
                last_key = field_name
        line = line[:split_at - len(field)]
    return last_key 

def _parse_docstring(self, docstring=''):
        """
        :param docstring:
        :return: (summary, description, schema)
        """
        summary, description, schema = None, None, dict()
        docstring = docstring.strip()

        if '---' in docstring:
            head, yml = re.split(r'\s*---+\s*\n', docstring)
            if yml:
                schema = self.yaml_load(yml) or dict()
        else:
            head = docstring

        if '\n' in head.strip():
            summary, description = map(lambda s: s.strip(), head.split('\n', 1))
        elif head:
            summary = head.strip()

        return summary, description, schema 

def get_cipher_list(encryption_mode):
    """
    Get list of ciphers from encryption mode.

    Example:
    get_cipher_list("psk2+tkip+aes") -> ["TKIP", "CCMP"]
    """
    parts = encryption_mode.lower().split('+')
    ciphers = []

    if "tkip" in parts:
        ciphers.append("TKIP")
    if "ccmp" in parts or "aes" in parts:
        ciphers.append("CCMP")

    if len(ciphers) == 0:
        # We need to enable at least one cipher. Most modes default to CCMP
        # except for wpa.
        if parts[0] == "wpa":
            ciphers.append("TKIP")
        else:
            ciphers.append("CCMP")

    return ciphers 

def __init__(self, name, uiType, size, persistence, familyPrefix, uiParams, tableSize, prefixSymbol, line):
		self.name = name
		self.familyPrefix = familyPrefix or ""
		self.uiType = uiType
		self.prefixSymbol = prefixSymbol
		if self.uiType == "ui_text_edit":
			self.prefixSymbol = "@"
		self.uiParams = uiParams or ""
		self.numElements = size
		self.dimensionsString = size
		self.underscore = ""
		if "," in size:
			self.underscore = "_"
			self.numElements = "*".join(["(%s)" % dim for dim in size.split(",")])
		self.numElements = tryStringEval(self.numElements, line, "UI array size")
		self.persistence = persistence or ""
		self.tableSize = tableSize 

def prefix_with_ns(name, namespaces, function_parameter_names=None, force_prefixing=False):
    if not namespaces:
        return name
    function_parameter_names = function_parameter_names or []
    ##name = name.replace('.', '__') # replace . by __

    if name[0] in variable_prefixes:
        prefix, unprefixed_name = name[0], name[1:]
    else:
        prefix, unprefixed_name = '', name

    # if the name consists of multiple parts (eg. myfamily.myvariable extract the first part - myfamily in this example)
    first_name_part = name.split('.')[0]

    # if built-in name or function parameter
    if (unprefixed_name in ksp_builtins.variables_unprefixed or
          name in ksp_builtins.functions or
          name in ksp_builtins.keywords or
          first_name_part in function_parameter_names) and not force_prefixing:
        return name # don't add prefix

    # add namespace to name
    return prefix + '.'.join(namespaces + [unprefixed_name]) 

def multiRunPostProcessing(self, PPoutpath, folders):
        outtext = list()
        for folder in folders:
            lines = list()
            with open(os.path.join(folder,'NEIDinfo.txt'), 'r') as g: #Write to file
                lines = g.read().split('\n')[0:-1]
            lines2 = [line.split(',') for line in lines]
            try:
                lines2 = lines2.remove([''])
            except:
                pass
            lines3 = [','.join(line) for line in lines2 if float(line[1]) < 24764.0/6371.0]
            outtext.append('\n'.join(lines3))#OUTTEXT contains a complete list of all sub-neptune detections
        with open(os.path.join(PPoutpath,'NEIDallSubNeptunes.txt'), 'w') as g: #Write to file
            g.write('\n'.join(outtext))
        
        #### Count number of surveys analyzed
        NumAnalyzed = 0
        for folder in folders:
            pklfiles = glob.glob(os.path.join(folder,'*.pkl'))
            NumAnalyzed += len(pklfiles)
        with open(os.path.join(PPoutpath,'NEIDcountFilesAnalyzed.txt'), 'w') as g: #Write to file
            g.write(str(NumAnalyzed)) 

def get_max_word_length(
    string, formatter=None
):  # type: (str, Optional[Formatter]) -> int
    if formatter is not None:
        string = formatter.remove_format(string)

    max_length = 0
    words = re.split("\s+", string)

    for word in words:
        max_length = max(max_length, get_string_length(word))

    return max_length 

def get_max_line_length(
    string, formatter=None
):  # type: (str, Optional[Formatter]) -> int
    if formatter is not None:
        string = formatter.remove_format(string)

    max_length = 0
    words = re.split("\n", string)

    for word in words:
        max_length = max(max_length, get_string_length(word))

    return max_length 

def validate_hostname(hostname):
    if len(hostname) > 255:
        raise Exception("Hostname {} is longer than 255 characters".format(hostname))
    if hostname[-1] == ".":
        hostname = hostname[:-1]
    allowed = re.compile(r"(?!-)[A-Z\d-]{1,63}(?<!-)$", re.IGNORECASE)
    if not all(allowed.match(x) for x in hostname.split(".")):
        raise Exception("Hostname {} is not RFC 1123 compliant".format(hostname)) 

def natural_sort(i):
    return sorted(i, key=lambda s: [int(t) if t.isdigit() else t.lower() for t in re.split(r"(\d+)", s)]) 

def decode_block_string(self, block_string):
        """Gets a block through a string notation of arguments."""
        assert isinstance(block_string, str)
        ops = block_string.split('_')
        options = {}
        for op in ops:
            splits = re.split(r'(\d.*)', op)
            if len(splits) >= 2:
                key, value = splits[:2]
                options[key] = value

        if 's' not in options or len(options['s']) != 2:
            raise ValueError('Strides options should be a pair of integers.')

        self.input_filters = int(options['i'])
        self.output_filters = int(options['o'])
        self.dw_kernel_size = self._parse_ksize(options['k'])
        self.expand_kernel_size = self._parse_ksize(options['a'])
        self.project_kernel_size = self._parse_ksize(options['p'])
        self.num_repeat = int(options['r'])
        self.identity_skip = ('noskip' not in block_string)
        self.se_ratio = float(options['se']) if 'se' in options else None
        self.expand_ratio = int(options['e'])
        self.strides = [int(options['s'][0]), int(options['s'][1])]
        self.swish = 'sw' in block_string
        self.dilated = 'dilated' in block_string

        return self 

def _parse_ksize(self, ss):
        return [int(k) for k in ss.split('.')] 

def read_aliases(alfile):
        '''Read aliases map from given file'''
        if alfile is None:
            return {}
        almap = {}
        with open(alfile, 'r') as fd:
            for line in fd:
                alias, token = line.strip().split()[0:2]
                almap[alias] = token
        return almap 

def __norm_cat(self, label, hashes):
        if not label:
            return []

        # Initialize list of tokens to return
        ret = []

        # Split label into tokens and process each token
        for token in re.split("[^0-9a-zA-Z]", label):
            # Remove leading and trailing backspace from token
            # and convert to lowercase
            token = token.lower()

            # Remove digits at the end
            # FIXME: What if it is a hash, and removes digits at the end???
            end_len = len(re.findall("\d*$", token)[0])
            if end_len:
                token = token[:-end_len]

            # Ignore short token
            if len(token) < 4:
                continue

            # Ignore token if prefix of a hash of the sample 
            # Most AVs use MD5 prefixes in labels, 
            # but we check SHA1 and SHA256 as well
            hash_token = False
            for hash_str in hashes:
                if hash_str[0:len(token)] == token:
                    hash_token = True
                    break
            if hash_token:
                continue
            for keys, values in self.cat.iteritems():
                if token in values:
                    token = keys
                    ret.append(token)
                    break
                    # Add token
        return ret 

def forward(self, x, sequence_mask):
        x = self.c_attn(x)
        query, key, value = x.split(self.split_size, dim=2)
        query = self.split_heads(query)
        key = self.split_heads(key, k=True)
        value = self.split_heads(value)
        a = self._attn(query, key, value, sequence_mask)
        a = self.merge_heads(a)
        a = self.c_proj(a)
        a = self.resid_dropout(a)
        return a 

def get_hash():
    if os.path.exists('.git'):
        sha = get_git_hash()[:7]
    elif os.path.exists(version_file):
        try:
            from mmdet.version import __version__
            sha = __version__.split('+')[-1]
        except ImportError:
            raise ImportError('Unable to get git version')
    else:
        sha = 'unknown'

    return sha 

def prepare_dir(self, relative):
        d = os.path.dirname(relative)
        if d and not os.path.exists(self.to_abs(d)):
            import re
            folders = re.split(r"\\|/", d)
            p = self.root
            for f in folders:
                p += os.path.sep + f
                if not os.path.exists(p):
                    os.makedirs(p) 

def dispatchTPFQuery(raw_tpf_query, loader, acceptHeader, content):
    """Executes the specified TPF query."""
    endpoint, auth = gquery.guess_endpoint_uri(raw_tpf_query, loader)
    glogger.debug("=====================================================")
    glogger.debug("Sending query to TPF endpoint: {}".format(endpoint))
    glogger.debug("=====================================================")

    # TODO: pagination for TPF

    # Preapre HTTP request
    reqHeaders = {'Accept': acceptHeader, 'Authorization': 'token {}'.format(static.ACCESS_TOKEN)}
    if content:
        reqHeaders = {'Accept': static.mimetypes[content], 'Authorization': 'token {}'.format(static.ACCESS_TOKEN)}
    tpf_list = re.split('\n|=', raw_tpf_query)
    subject = tpf_list[tpf_list.index('subject') + 1]
    predicate = tpf_list[tpf_list.index('predicate') + 1]
    object = tpf_list[tpf_list.index('object') + 1]
    data = {'subject': subject, 'predicate': predicate, 'object': object}

    response = requests.get(endpoint, params=data, headers=reqHeaders, auth=auth)
    glogger.debug('Response header from endpoint: ' + response.headers['Content-Type'])

    # Response headers
    resp = response.text
    headers = {}
    headers['Content-Type'] = response.headers['Content-Type']
    headers['Server'] = 'grlc/' + grlc_version
    return resp, 200, headers 

def read_reference(reference_path):
    prefixes = []
    refseq = {}
    with open(reference_path, 'r') as ref:
        for line in ref:
            if not line.startswith('>'): # seq name
                refseq[prefix] += line.strip() # dont count newlines
            else:
                prefix = line[1:].strip().split()[0]
                if prefix not in prefixes:
                    prefixes.append(prefix)
                    refseq[prefix] = ""
    return refseq, prefixes 

def write_sam(read_file, id_to_cigar_map, reference_path, orig_prefix):
    references, prefixes = read_reference(reference_path) # orig_prefix is prefix without _ in name
    write_sam = os.path.join(read_file.rsplit("/",1)[0], orig_prefix) + ".sam"
    write_header(write_sam, references, prefixes)
    with open(read_file, 'r') as reads:
        for line in reads:
            if line.startswith('>'):
                name, start, align_status, index, strand, soffset, align_length, eoffset = line.strip().split('_')
                ref_name = name[1:] # first sign of name is ">"
                QNAME = ref_name + "-" + index 
                query = ref_name + "-" + index 
                if strand == 'R':
                    FLAG = str(16)
                else:
                    FLAG = str(0)
                if align_status == "unaligned": #special cigar/no pos for non-mapping reads
                    POS = str(0)
                    CIGAR = "*"
                    RNAME = "*" # treated as unmapped
                else:
                    POS = start
                    RNAME = ref_name
                    try:
                        CIGAR, pos = id_to_cigar_map[query]
                    except KeyError: #sequence did not have any errors
                        CIGAR, pos = "%sM" % align_length, align_length
                MAPQ = str(255)
                RNEXT = '*'
                PNEXT = '0'
                QUAL = '*'  # no quality for nanosim
            else:
                SEQ = line.strip()
                TLEN = str(len(SEQ)) 
                if CIGAR != '*': # unmapped bases counted as insertions in read
                    CIGAR = soffset + "I" + CIGAR + str(int(align_length) - int(pos)) + "M" + eoffset + "I"
                sam_line = [QNAME, FLAG, RNAME, POS, MAPQ, CIGAR, RNEXT, PNEXT, TLEN, SEQ, QUAL]
                clen = get_cigar_length(CIGAR)
                with open(write_sam, 'a+') as samfile:
                    samfile.write("\t".join(sam_line) + "\n")
    return prefixes 

def get_cigars_nanosim(error_profile):
    errors = {}
    slen = {}
    with open(error_profile, 'r') as ep:
        for line in ep:
            if line.startswith("Seq"):
                continue # header
            name, pos, error_type, length, refseq, qseq = re.split(r'\t|\s{2,}',line) # split at tab and multiple whitespace
            if error_type == "mis":
                continue # this version ignores mismatches
            seqname = name.split("_")
            seqname = seqname[0] + "-" + seqname[-1] # later on used as sequence name
            if seqname in errors:
                errors[seqname].append((int(pos),error_type,int(length)))
            else:
                errors[seqname] = [(int(pos),error_type,int(length))]
    cigars = {}
    # if ins at pos x with length y, then that ins started at x-y! (see test_error_profile)
    for sequence in errors:
        sorted_errors = sorted(errors[sequence],key=lambda x: x[0])
        ref_len = 0
        CIGAR = ""
        for pos, etype, length in sorted_errors:
            if etype == 'ins':
                if (int(pos) - ref_len > 0):
                    CIGAR += str(int(pos) - ref_len) + "M"
                CIGAR += str(length) + "I"
                ref_len = int(pos)
                length = 0 # only relevant if insertion at the end
            elif etype == 'del':
                if (int(pos) - ref_len > 0):
                    CIGAR += str(int(pos) - ref_len) + "M"
                CIGAR += str(length) + "D"
                ref_len = int(pos) + int(length)
        # if deletion at the end, the number of matches has to be reduces
        cigars[sequence] = (CIGAR, int(pos) + int(length))
    return cigars 

def convert_fasta(fasta_reads):
    out_name = fasta_reads.rsplit("_",1)[0] + ".fq" # /path/to/genomeid_reads.fasta
    with open(fasta_reads,'r') as reads:
        with open(out_name, 'w') as out:
            for line in reads:
                if line.startswith(">"):
                    spl = line.strip().split("_")
                    name = spl[0][1:] # without >
                    index = spl[3]
                    out.write("@" + name + "-" + index + '\n')
                else:
                    out.write(line)
                    out.write("+\n")
                    out.write("I" * (len(line) - 1) + '\n') # no quality information is available 

def calc_cortices(subject, atlas_subject, worklog, hemis=None):
    '''
    calc_cortices extracts the hemisphere objects (of the subject) to which the atlas is being
    applied. By default these are 'lh' and 'rh', but for HCP subjects other hemispheres may be
    desired.

    Afferent parameters:
      @ hemis 
        The hemispheres onto which to put the atlas; this may take a number of forms: 'lh' or 'rh' 
        (or --hemis=lh / --hemis=rh) applies the atlas to the given hemisphere only; otherwise a
        list of hemispheres may be specified as a python object (e.g.
        --hemis='("lh_LR32k","rh_LR32k")') or as a comma or whitespace separated string (such as
        'lh_LR32k,lh_LR59k' or 'rh rh_LR164k'). 'lr', 'both', and 'all' are equivalent to 'lh rh';
        this is the default behavior if hemis is not provided explicitly.
      @ subject 
        The neuropythy subject object onto which the atlas is being projected.
      @ atlas_subject 
        Theneuropythy subject object from which the atlas is being projected.
    '''
    if hemis is None or hemis is Ellipsis: hemis = 'lr'
    if pimms.is_str(hemis):
        if hemis.lower() in ['lr', 'both', 'all']: hemis = ('lh','rh')
        else: hemis = re.split(r'([,;:]|\s)+', hemis)[::2]
    if atlas_subject.name == 'fsaverage_sym':
        hemis = ['rhx' if h == 'rh' else h for h in hemis]
    sctcs = {}
    actcs = {}
    worklog('Preparing Hemispheres...')
    for h in hemis:
        if h not in subject.hemis:
            raise ValueError('Subject %s does not have requested hemi %s' % (subject.name, h))
        sctcs[h] = curry(lambda sub,h: sub.hemis[h], subject,       h)
        h = 'lh' if h == 'rhx' else h
        if h not in atlas_subject.hemis:
            raise ValueError('Atlas subject %s does not have requested hemi %s' % (
                atlas_subject.name, h))
        actcs[h] = curry(lambda sub,h: sub.hemis[h], atlas_subject, h)
    return {'subject_cortices': pimms.lazy_map(sctcs),
            'atlas_cortices':   pimms.lazy_map(actcs)} 

def _format_afferent_doc(docstr, abbrevs=None, cols=80):
    try:
        (ln1, docs) = docstr.split('\n\n')
    except Exception: return ''
    anm0 = ln1.split(' (')[0]
    anm = anm0.replace('_', '-')
    header = '  --' + anm
    if abbrevs and anm0 in abbrevs: header = header + ' | -' + abbrevs[anm0]
    docs = [
        '\n     '.join(
            textwrap.wrap(
                ' '.join([s.strip() for s in ss.split('\n')[1:]]),
                cols-6))
        for ss in docs.split('\n)')]
    return header + '\n' + ''.join(['   * ' + d for d in docs]) 

def parse_contexts(args):
    # parse context into Context objects
    contexts = re.split(r'\W+', args.config.get('common', 'context'))
    for i, ctx in enumerate(contexts):
        if ctx[:3] == 'gpu':
            contexts[i] = mx.context.gpu(int(ctx[3:]))
        else:
            contexts[i] = mx.context.cpu(int(ctx[3:]))
    return contexts