Esempio n. 1
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def handle_initial_reporting(name,                          \
                             fragment,                      \
                             frag_num, tabbed = tabbed,     \
                             report_basics = report_basics, \
                             report_input = report_input,    ):
    if (report_basics):
        report_initial_info(name, fragment, frag_num)
    elif (report_input):
        if tabbed:
            sys.stdout.write('\t')
        handle_output("Input" + name)
    return
Esempio n. 2
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def remove_periods(string, tabbed=tabbed):
    street_name = []
    street_name.append(string)

    period_problem_re = re.compile(r'[\.]')
    periods = 0

    if (period_problem_re.search(string)):
        handle_output('Found periods in string: ' + string)

    while (period_problem_re.search(string)):
        partial = string.split('.')

        if (partial != street_name):
            string = ''.join(partial)
            periods += 1

        handle_output('Cleaned value: ' + string)

    if (periods > 0):
        #if tabbed:
        #    sys.stdout.write('\t')
        handle_output('Periods: ' + str(periods) + ' (removed)')
        handle_output('\n', newline=False)

    return string
Esempio n. 3
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def split_and_fix(string, char, index, basic=False, deep=False, zipcode=False):
    fragment = string.split(char)

    if (basic):
        cleaned_name = update_name(fragment[index])
        # for uniformity in reporting
        handle_output('\n', newline=False)
    if (deep):
        cleaned_name = deep_scan(fragment[index], full_string=string)
    if (zipcode):
        # hot fix
        cleaned_zip = fragment[index]
        return cleaned_zip

    return cleaned_name
Esempio n. 4
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def update_name(name,
                prefix=prefix,
                suffix=suffix,
                reporting=True,
                report_result=report_result,
                newline=True):
    # for list-type comparison later
    street_name = convert_to_list(name)

    # fragment: list of street name parts. frag_num: number of
    # fragments. last: list index number of the last fragment
    fragment, frag_num, last = fragment_and_count(name)

    # print the given street name and its fragment list and quantity
    if (reporting):
        handle_initial_reporting(name, fragment, frag_num)

    # learn the medial name parts; the lateral (first and last)
    # fragments will be handled later in the rest of the process
    learn_medial_name_parts(fragment)

    # last == (len(name) - 1). If length == 1, then there is no
    # chance for a prefix/suffix.
    if (last > 0):
        # inspect and fix prefix
        name, fragment, actual_names = audit_prefix(name,
                                                    fragment,
                                                    street_name,
                                                    last,
                                                    reporting=reporting)
        # inspect and fix suffix
        name, actual_names = audit_suffix(name,
                                          fragment,
                                          street_name,
                                          last,
                                          reporting=reporting)

    # print the cleaned up, or unchanged, street name
    if (reporting):
        if (report_result):
            report_result(name)
        if (newline):
            handle_output("\n", True, True, 0)

    return name
Esempio n. 5
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def audit_prefix(name,
                 fragment,
                 street_name,
                 last,
                 learned_name_parts=learned_names,
                 reporting=True,
                 report_lateral=report_lateral_parts,
                 tabbed=tabbed):
    if (fragment[0] not in expected_prefix):
        if (reporting):
            if (report_lateral):
                if tabbed:
                    sys.stdout.write('\t')
                handle_output("Prefix: " + fragment[0])

        if (fragment[0] not in expected_suffix) and (fragment[0]
                                                     not in suffix):
            name = reformat_value(name, fragment, street_name, prefix, 0)
        elif (fragment[0] in expected_suffix) or (fragment[0] in suffix):
            name, fragment, street_name = fix_misplacement(fragment, last)
            name = reformat_value(name, fragment, street_name, prefix, 0)

        if (name.split()[0] == fragment[0]):
            if (fragment[0] not in learned_name_parts):
                learned_name_parts.add(fragment[0])
                if (report_lateral):
                    if tabbed:
                        sys.stdout.write('\t')
                    handle_output(
                        "....Warning: prefix dictionary may not have "
                        "been sufficient to support: " + fragment[0])

        elif (fragment[0] in learned_name_parts):
            if (report_lateral):
                if tabbed:
                    sys.stdout.write('\t')
                handle_output("....Note: found this fragment in the learned "
                              "names list: " + fragment[0])

    else:
        if (report_lateral):
            if tabbed:
                sys.stdout.write('\t')
            handle_output("Prefix: " + fragment[0] + " (expected)")

    return name, fragment, learned_name_parts
Esempio n. 6
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def fix_misplacement(fragment,
                     last,
                     report_lateral=report_lateral_parts,
                     tabbed=tabbed):
    # temporary copy of fragment; for a quick comparison at the end
    copy = fragment

    if (fragment[last] in expected_prefix):
        temp = fragment[0]  # T = a
        fragment[0] = fragment[last]  # a = z
        fragment[last] = temp  # z = T

        # log and print
        if (report_lateral):
            if tabbed:
                sys.stdout.write('\t')
            handle_output("Prefix: " + fragment[0] + " (switched)")

    elif (fragment[last] not in expected_prefix):
        temp = fragment[0]  # T = a
        for index in xrange(last):  # a = b, b = c, ...
            fragment[index] = fragment[index + 1]  # ... , x = y, y = z
        fragment[last] = temp  # z = T

        # log and print event message
        if (report_lateral):
            if tabbed:
                sys.stdout.write('\t')
            handle_output("Prefix: " + fragment[0] + " (switched)")

    # provide a new name and street_name (list-type of name),
    # since the fragment list has been changed
    name = ' '.join(fragment)
    street_name = []
    street_name.append(name)
    return name, fragment, street_name
Esempio n. 7
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def audit_suffix(name,
                 fragment,
                 street_name,
                 last,
                 learned_name_parts=learned_names,
                 reporting=True,
                 report_lateral=report_lateral_parts,
                 tabbed=tabbed):
    if (fragment[last]) not in expected_suffix:
        if (reporting):
            if (report_lateral):
                if tabbed:
                    sys.stdout.write('\t')
                handle_output("Suffix: " + fragment[last])

        name = reformat_value(name, fragment, street_name, suffix, last)
        street_name = name.split()

        if (street_name[len(street_name) - 1] == fragment[last]):
            if fragment[last] not in learned_name_parts:
                learned_name_parts.add(fragment[last])
                if (report_lateral):
                    if tabbed:
                        sys.stdout.write('\t')
                    handle_output("....Warning: suffix dictionary may not "
                                  "have been sufficient to support: " +
                                  fragment[last])

        elif (fragment[last] in learned_name_parts):
            if (report_lateral):
                if tabbed:
                    sys.stdout.write('\t')
                handle_output("....Note: found this fragment in the learned "
                              "names list: " + fragment[last])
    else:
        if (report_lateral):
            if tabbed:
                sys.stdout.write('\t')
            handle_output("Suffix: " + fragment[last] + " (expected)")

    return name, learned_name_parts
Esempio n. 8
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def report_initial_info(name,           \
                        fragment,       \
                        frag_num,       \
                        tabbed = tabbed  ):
    if tabbed:
        sys.stdout.write('\t')
    handle_output("Input: " + name)

    if tabbed:
        sys.stdout.write('\t')
    handle_output(fragment)

    if tabbed:
        sys.stdout.write('\t')
    handle_output("Frag_num: " + str(frag_num))
    return
Esempio n. 9
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def deep_scan(name,                         \
              return_useables = False,      \
              full_string = None,           \
              report_result = report_result  ):
    # report state
    handle_output("Beginning deep scan...")

    # variables (lists are for the anticipation that multiple parts
    # of the same type might exist here; such as two zipcodes)
    words = re.split('\W', name)
    wc = len(words)  # word count

    # scanner status
    w2w_scan = False  # word-by-word scan record

    # string value variables
    useables = {}  # know what it is; can't use it
    unknown = []  # don't know what it is
    fs = []  # fake_string - rebuilt name
    housenumber = []
    suite = []
    city = []
    state = []
    zipcode = []

    # condition variables

    # prefix_stat -- 0 for 'does not exist yet'; 1 for 'it has been set'
    ps = 0
    # suffix stat -- 0 for 'does not exist yet'; 1 for 'it has been set'
    ss = 0
    # actual name parts stat -- 0 for none; 1 to infinite for quantity
    ns = 0
    # for keeping track of the words in the fragment during for loops
    index = 0

    # new suffix (for switching out with the old one)
    s = ''
    # description of the name part based on findings -- for reporting
    # findings to the analyst
    descr = ''
    # final result variable
    result = ''

    # out-of-scope signals
    highway = False  # highway marking
    suite_designation = False  # suite marking

    # basic info about the fragment going through analysis
    handle_output("Fragment: " + name)
    handle_output("Word Count: " + str(wc))
    ''' Quick Highway Address Scan '''

    handle_output("Starting the Quick Highway scan...")

    potential_zipcode = False

    for part in name.split(' '):
        if (US_zipcode_re.search(part)):
            potential_zipcode = True

    if not (potential_zipcode):
        if (highway_general_re.search(name)):
            descr = "highway name"
            handle_output("This string is a potential " + descr)
            highway = True
            result = "*highway_code"
        if (interstate_re.search(name)):
            descr = "interstate name"
            handle_output("This string is a potential " + descr)
            highway = True
            result = "*highway_code"

        if result == "*highway_code":
            handle_output(
                "This address value has been deemed as a highway address"
                " and will be inserted back into the data without"
                " manipulation.")
    # report state
    handle_output("End of Quick Highway scan.")

    if descr == '':
        handle_output("Nothing has been found by the Quick Highway scan.")
    ''' Quick Suite Designation Scan '''

    # some strings that have a comma followed by a suite designation can
    # waste time and resources, especially in my OSM file, so let's take
    # care of it at the beginning and set the right signals
    # (suite_designation = True) to bypass the rigorous scans
    if not highway:
        handle_output("Attempting the Quick Suite Designation scan...")
        first_letter = ''
        # hard-coded based off of my own dataset's errors; otherwise,
        # this has to become a loop or a smart regex pattern test; or
        # something better
        try:
            # example, words == [ 'first', 'second', 'third' ]
            #                       [0]      [1]       [2]
            #          words[0][0] == 'f'
            #          words[1][0] == 's'
            if (words[0][0] != ''):
                first_letter = words[0][0]
            else:
                first_letter = words[1][0]
        except:
            # perhaps the first "letter" of the first "part" of the list
            # is an '' (empty string), for instance:
            #
            # words == [ '', 'Suite', '1370' ]
            #
            # -then it could have failed because of indexing issues.
            # So, let's try the next list index item's first byte:
            try:
                first_letter = words[1][0]
            except:
                # in case of failure, make sure we didn't catch anything
                # funky before going to the next procedure
                first_letter = ''
                handle_output(
                    "The Quick Suite Designation scan could not identify "
                    "suite address information in this fragment.")
        if (first_letter != ''):
            # there's a much easier way to do this. This is just for
            # the readability and ease
            if (first_letter == ' ' or first_letter == 's'
                    or first_letter == 'S' or first_letter == '#'):
                # -then the letter might possibly be a suite
                for word in words:
                    if (suite_re.search(word)):
                        # -then the fragment most likely contains only suite designations
                        print word
                        insert_known_parts(name)
                        suite_designation = True
                        result = '*suite_code'
                        handle_output(
                            "This fragment has been deemed as a suite designation and "
                            "will be stored, but not inserted back into the data."
                        )
            handle_output("The quick Suite Designation scan is now complete.")
    # reset the description string for re-use
    descr = ''
    ''' Word-by-Word Scan and Build '''

    if not highway and not suite_designation:
        # indicate that the word-by-word scan has occurred
        wbw_scan = True

        # report state
        handle_output("Running Word-by-Word scan and build...")

        # search every word
        for word in words:
            if (word != ''):
                handle_output("Searching for '" + word + "'")
                if (word in expected_prefix):
                    descr = "prefix"
                    w = up(word)
                    fs.append(w)
                    ps = 1
                    ds_report_findings(descr)
                if (word in expected_suffix):
                    descr = "suffix"
                    s = up(word)
                    ss = 1
                    ds_report_findings(descr)
                if (word in prefix and ps == 0):
                    descr = "unconventional prefix"
                    w = up(word)
                    fs.append(w)
                    ps = 1
                    ds_report_findings(descr)
                if (word in suffix and ss == 0):
                    descr = "unconventional suffix"
                    s = up(word)
                    ss = 1
                    ds_report_findings(descr)
                if (word in learned_names):
                    descr = "part of a known street name"
                    w = up(word)
                    ds_report_findings(descr)
                if (word not in learned_names):
                    if (word[0] != word[0].upper()):
                        w = up(word)
                        if (w in learned_names):
                            descr = "part of a known street name"
                            ds_report_findings(descr)
                if (ss == 0):
                    if (street_type_re.search(word)):
                        descr = "mistyped suffix"
                        s = up(word)
                        ds_report_findings(descr)
                if (index == 0):
                    if (house_number_re.search(word)):
                        descr = "housenumber"
                        housenumber.append(word)
                        ds_report_findings(descr)
                if (index != 0) and (len(word) < 5):
                    if (suite_re.search(word)):
                        descr = "suite designation"
                        suite.append(word)
                        ds_report_findings(descr)
                if (city_sweep_re.search(word)):
                    descr = "city"
                    city.append(up(word))
                    ds_report_findings(descr)
                if (state_sweep_re.search(word)):
                    descr = "state"
                    state.append(up(word, all_chars=True))
                    ds_report_findings(descr)
                if (zipcode_re.search(word)):
                    descr = "zipcode"
                    zipcode.append(word)
                    ds_report_findings(descr)
                if (unk_digits_re.search(word)):
                    descr = "string of undesignated digits"
                    unknown.append(word)
                    ds_report_findings(descr)
                if (descr == ''):
                    unknown.append(word)
                    # it might be part of the street name
                    if (not digits_re.search(word))     and    \
                                    (word not in suite) and    \
                                    (word not in city)  and    \
                                    (word not in state):
                        uw = up(word)
                        fs.append(uw)

                # add a medial part of the street name
                #if ((w in learned_names) or (word in learned_names)) and    \
                if ((word in learned_names) or (up(word) in learned_names)) and     \
                                    ((not digits_re.search(word))           and    \
                                     (up(word) != s)                        and    \
                                     (word not in fs)                       and    \
                                     (up(word) not in fs)                   and    \
                                     (word not in suite)                    and    \
                                     (up(word) not in city)                 and    \
                                     (word.upper() not in state)):
                    fs.append(up(word))
                    ns += 1

                descr = ''
                index += 1
                continue

        # recall: fs stands for fake string
        #         fs is used to rebuild a healthy version of the string

        # add the suffix
        fs.append(s)
        result = ' '.join(fs)
        pass
    ''' Collect Identified and Unknown Processed Parts '''

    # put the identified parts in a packet and store them for review,
    # as they are not useable here
    if (housenumber != []):
        # if there's only one item in the list, then store the item
        # as a string
        if (len(housenumber) == 1):
            useables['housenumber'] = housenumber[0]
        # if there are more than one item in the list,
        # then just store the whole list
        else:
            useables['housenumber'] = housenumber
    if (suite != []):
        if (len(suite) == 1):
            useables['suite'] = suite[0]
        else:
            useables['suite'] = suite
    if (city != []):
        if (len(city) == 1):
            useables['city'] = city[0]
        else:
            useables['city'] = city
    if (state != []):
        if (len(state) == 1):
            useables['state'] = state[0]
        else:
            useables['state'] = state
    if (zipcode != []):
        if (len(zipcode) == 1):
            useables['zipcode'] = zipcode[0]
        else:
            useables['zipcode'] = zipcode

    # store the unknown processed parts for human review
    if (unknown != []):
        store_processed_parts(unknown, known=False)

    # store the known processed parts for human review
    if (useables != {}):
        store_processed_parts(useables,
                              name=full_string,
                              passing_useables=True)
    ''' Produce Deep Scan Final Report '''

    # if Word-by-Word scan has been conducted, yet no known parts
    # have been found
    if (w2w_scan == True) and \
               (fs == []            and     \
                housenumber == []   and     \
                suite == []         and     \
                city == []          and     \
                state == []         and     \
                zipcode == []  ):
        handle_output('Nothing has been found by the Word-by-Word scan.')

    # notify analyst that the scan process is complete
    handle_output("Deep scan is complete.")

    # show/log final result
    if (report_result):
        handle_output("Result: " + result)

    #
    if (return_useables == True):
        # if a fake string was produced, then a potentially good street
        # value is now in possession, so return it for use
        if (fs != []):
            if (useables == []):
                handle_output("Note: no useable parts were found.")
            return result, useables
    elif (return_useables == False):
        # if a fake string was produced, then a potentially good street
        # value was produced, so return it
        if (fs != []):
            return result
        if (fs == []) and (highway == False) and (suite_designation == False):
            handle_output("Failed to find any street name results with "
                          "the deep scan.")

    return result
Esempio n. 10
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def split_and_scan(string, char, street=True, zipcode=False):
    # report state
    handle_output('Running split-and-scan...')

    # if string == "Noel Road, Suite 1370"
    # then line_list == [ 'Noel Road', 'Suite 1370' ]
    line_list = string.split(char)
    handle_output(line_list)

    # in the previous list example, last item == 'Suite 1370'
    # therefore, last index == 1
    last = (len(line_list) - 1)  # last index in word_list
    index = 0  # word index

    # should be sets, due to the usage in this function; however,
    # some external functions require lists to be returned and other
    # functions smartly handle the lists
    index_of_good_frags = []  # track expected fragments
    index_of_bad_frags = []  # track unexpected fragments

    # operate on a list with more than one value;
    # for example, [ "Noel Road", "Suite 1370" ]
    #           or [ 'TX', '75240' ]
    if ((type(line_list) == type([])) and (len(line_list) > 1)):
        # report state
        handle_output('Operating on a list with more than one value...')

        # search each fragment of the given string
        for line in line_list:
            ''' Street Name Values '''

            # if street name value, then expect fragments that have
            # multiple words/parts with spaces in between them
            #
            # Loop 1:
            #   line == line_list[0], which is 'Noel Road',  index: 0
            # Loop 2:
            #   line == line_list[1], which is 'Suite 1370', index: 1
            if (street):
                # Loop 1:
                #   'Noel Road' will pass as a street value
                if (verify_street_value(line, ignore_case=True)):
                    # Loop 1:
                    #   index 0 will be appended in list of good frags
                    index_of_good_frags.append(index)
                # Loop 2:
                #   'Suite 1370' will pass as not a street value
                if (not verify_street_value(line, ignore_case = True)) and \
                                          (index not in index_of_good_frags):
                    # Loop 2:
                    #   index 1 will be appended in list of bad frags
                    index_of_bad_frags.append(index)

                # Further Dissection of the String for Analysis
                #
                # This is because the verification method might have
                # failed and provided a false negative, so deeper
                # analysis of the fragment will provide a second chance
                # at seeing the good, useful parts and fixing them for
                # use later. This is still a fragment-flagging method.
                #
                # Loop 1:
                #   words == [ 'Noel', 'Road' ]
                #   fragment index == 0
                #
                # Loop 2:
                #   words == [ 'Suite', '1370' ]
                #   fragment index == 1
                words = line.split(' ')

                # Line Loop 1:
                #
                #   Word Loop 1:
                #       word == 'Noel'
                #       fragment index == 0
                #   Word Loop 2:
                #       word == 'Road'
                #       fragment index == 0
                #
                # Line Loop 2:
                #
                #   Word Loop 1:
                #       word == 'Suite'
                #       fragment index == 1
                #   Word Loop 2:
                #       word == '1370'
                #       fragment index == 1
                for word in words:
                    if (word in prefix):
                        index_of_good_frags.append(index)
                    if (word in suffix):
                        index_of_good_frags.append(index)
            ''' Zipcode Values '''

            # if zipcode value, then expect fragments that have one
            # word/part each; therefore, no spaces, as they have been
            # removed by the split at the beginning of the procedure.
            if (zipcode):
                # Recall: this is within a loop: line in line_list
                # Where:
                #   if,
                #       string == 'TX 75240'
                #   then,
                #       line_list == [ 'TX', '75240' ]
                #
                # Loop 1:
                #   line == 'TX', index == 0
                # Loop 2:
                #   line == '75240', index == 1

                # Loop 2:
                #   '75240' will pass as a zipcode
                if (verify_zipcode_value(line)):
                    # Loop 2:
                    #   index 1 will be appended in good frags list
                    index_of_good_frags.append(index)
                if (not verify_zipcode_value(line)) and \
                       (index not in index_of_good_frags):
                    # Loop 1:
                    #   index 0 will be appended in bad frags list
                    index_of_bad_frags.append(index)

            # index tracking in the fragment loop; begins at 0
            index += 1

    # report state
    handle_output('Split-and-scan is complete.')
    return index_of_good_frags, index_of_bad_frags
Esempio n. 11
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def clean_string(string, char=',', value_type="street"):
    if (report_input) or (report_basics):
        handle_output('Input: ' + string)

    handle_output("Cleaning problematic '" + value_type + "' string value...")

    # create a list object of the string for comparison
    # to a split object
    string_list = []
    string_list.append(string)

    split_string = string.split(char)

    cleaned_string = ''
    processed_names = ''
    processed_names_list = []

    # Handling given character (arg: char) issues
    if (split_string != string_list):
        handle_output("Found a '" + char + "' issue...")

        if (value_type == "street"):
            good_frag_index, bad_frag_index = split_and_scan(string, char)
        if (value_type == 'zipcode'):
            good_frag_index, bad_frag_index = split_and_scan(string,
                                                             char,
                                                             street=False,
                                                             zipcode=True)
        handle_output('Output: ' + split_string[good_frag_index[0]] +
                      ' (piping)')

        # Try just one good fragment, since only one good value can be
        # taken for now,
        #
        # However, I propose that future plans should include to fuse
        # multiple good parts together in the correct way, as needed,
        # which will require wider analytic capabilities (*1), and to
        # decide between two or more completely good fragment values
        # to keep as the best value (*2).
        #
        # Current Analytic Capacity Limitations
        #
        # 1. Multiple Valid Parts Improperly Separated by a Character.
        #
        #   if,
        #       string == 'W, Arapaho, Road, TX, 75080'
        #   then,
        #       only 'W' will be used, while the rest will be stored as
        #       identified, useful, and in need of further analysis
        #
        # A much wider analytic capacity is required for this function
        # to properly clean multiple comma (or other char) issues.
        #
        # 2. Multiple Valid Values Improperly Included Together and
        #    Separated by a Character.
        #
        #   if,
        #       string == 'W Arapaho Road, N Coit Road, TX, 75080'
        #   then,
        #       only 'W Arapaho Road' will be used, while the rest will
        #       be stored away for future analysis.
        #
        # At this time, such problems have not been found in the Dallas
        # County OSM dataset that I have retrieved, so there is no need
        # to create the wider analytic procedures.
        #
        if good_frag_index != []:
            index = good_frag_index[0]
            if (value_type == 'street'):
                cleaned_string = split_and_fix(string, char, index, basic=True)
            if (value_type == 'zipcode'):
                cleaned_string = split_and_fix(string,
                                               char,
                                               index,
                                               zipcode=True)
        else:
            handle_output("No good fragments were found in this string.")

        if bad_frag_index != []:
            handle_output("Attempting to identify the bad fragment and store "
                          "for manual inspection...")
            for index in bad_frag_index:
                processed_names = split_and_fix(string, char, index, deep=True)
            # if the processed string is not empty or a code,
            # then append it to the processed_names list
            if (processed_names != '') and (processed_names[0] != '*'):
                processed_names_list.append(processed_names)

            # if one or more bad frags were processed,
            # then store them in the processed_parts log
            if (processed_names_list != []):
                store_processed_parts(processed_names_list, known=True)
                handle_output(
                    "Bad fragment has been salvaged and stored in the "
                    "'useables' section of the log (some words could "
                    "be listed as 'unknown').")
        else:
            handle_output("No bad fragments were found in this string.")
    # Handling non-given-char issues
    else:
        handle_output("No '" + char + "' issues found.")
        if (value_type == 'street'):
            cleaned_string = deep_scan(string, full_string=string)
            if (cleaned_string != string) and (cleaned_string not in codes):
                handle_output("\n", newline=False)
                cleaned_string = update_name(cleaned_string, newline=False)
        if (value_type == 'zipcode'):
            good_frags, bad_frags = split_and_scan(string,
                                                   char,
                                                   street=False,
                                                   zipcode=True)
            if (good_frags != []):
                cleaned_zipcode = split_and_fix(string,
                                                char,
                                                good_frags,
                                                zipcode=True)
            if (cleaned_string != string)         and   \
                    (cleaned_string not in codes) and   \
                    (cleaned_string != ''):
                handle_output("\n", newline=False)
                cleaned_string = update_name(cleaned_string, newline=False)

    return cleaned_string
Esempio n. 12
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def report_learned_names(actual_parts=learned_names):
    handle_output("Learned: ")
    handle_output(actual_parts)
    # this separation will make the log analysis easier later
    handle_output("\n", False, False, 0)
    return
Esempio n. 13
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def report_result(name, tabbed=True):
    if tabbed:
        sys.stdout.write('\t')
    handle_output("Result: " + name)
Esempio n. 14
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def ds_report_findings(description):
    handle_output("....It's a potential " + description + ".")
    return