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How to use str_ignore method in autotest

Best Python code snippet using autotest_python

regression.py

Source:regression.py

...278    param prefix1: output prefix in Avg/SD lines279    param prefix2: output prefix in Diff Avg/P-value lines280    param prefix3: output prefix in total Sign line281    """282    def str_ignore(str, split=False):283        str = str.split("|")284        for i in range(ignore_col):285            str[i] = " "286        if split:287            return "|".join(str[ignore_col:])288        return "|".join(str)289    def tee_line(content, file, n=None):290        fd = open(file, "a")291        print content292        str = ""293        str += "<TR ALIGN=CENTER>"294        content = content.split("|")295        for i in range(len(content)):296            if n and i >= 2 and i < ignore_col + 2:297                str += "<TD ROWSPAN=%d WIDTH=1%% >%s</TD>" % (n, content[i])298            else:299                str += "<TD WIDTH=1%% >%s</TD>" % content[i]300        str += "</TR>"301        fd.write(str + "\n")302        fd.close()303    for l in range(len(lists[0])):304        if not re.findall("[a-zA-Z]", lists[0][l]):305            break306    tee("<TABLE BORDER=1 CELLSPACING=1 CELLPADDING=1 width=10%><TBODY>",307        f)308    tee("<h3>== %s " % sum + "==</h3>", f)309    category = 0310    for i in range(len(lists[0])):311        for n in range(len(lists)):312            is_diff = False313            for j in range(len(lists)):314                if lists[0][i] != lists[j][i]:315                    is_diff = True316                if len(lists) == 1 and not re.findall("[a-zA-Z]", lists[j][i]):317                    is_diff = True318            pfix = prefix1[0]319            if len(prefix1) != 1:320                pfix = prefix1[n]321            if is_diff:322                if n == 0:323                    tee_line(pfix + lists[n][i], f, n=len(lists) + len(rates))324                else:325                    tee_line(pfix + str_ignore(lists[n][i], True), f)326            if not is_diff and n == 0:327                if '|' in lists[n][i]:328                    tee_line(prefix0 + lists[n][i], f)329                elif "Category:" in lists[n][i]:330                    if category != 0 and prefix3:331                        if len(allpvalues[category - 1]) > 0:332                            tee_line(prefix3 + str_ignore(333                                     allpvalues[category - 1][0]), f)334                        tee("</TBODY></TABLE>", f)335                        tee("<br>", f)336                        tee("<TABLE BORDER=1 CELLSPACING=1 CELLPADDING=1 "337                            "width=10%><TBODY>", f)338                    category += 1339                    tee("<TH colspan=3 >%s</TH>" % lists[n][i], f)340                else:341                    tee("<TH colspan=3 >%s</TH>" % lists[n][i], f)342        for n in range(len(rates)):343            if lists[0][i] != rates[n][i] and not re.findall("[a-zA-Z]",344                                                             rates[n][i]):345                tee_line(prefix2[n] + str_ignore(rates[n][i], True), f)346    if prefix3 and len(allpvalues[-1]) > 0:347        tee_line(prefix3 + str_ignore(allpvalues[category - 1][0]), f)348    tee("</TBODY></TABLE>", f)349def analyze(test, type, arg1, arg2, configfile):350    """ Compute averages/p-vales of two samples, print results nicely """351    config = ConfigParser.ConfigParser()352    config.read(configfile)353    ignore_col = int(config.get(test, "ignore_col"))354    avg_update = config.get(test, "avg_update")355    desc = config.get(test, "desc")356    def get_list(dir):357        result_file_pattern = config.get(test, "result_file_pattern")358        cmd = 'find %s|grep "%s.*/%s"' % (dir, test, result_file_pattern)359        print cmd360        return commands.getoutput(cmd)361    if type == 'file':...

palavras.py

Source:palavras.py

1import csv2def gerarSet(string):3    temp_set = set()4    for x in string:5        temp_set.add(x)6    return temp_set7def retirarIgnores(frase, set_ignore):8    for letra in frase:9        if letra in set_ignore:10            frase = frase.replace(letra, '')11    return frase12def palavrasNoDicionario(dicionario, palavrasFrase):13    temp_list_erratas = []14    for palavra in palavrasFrase:15        if palavra not in dicionario:16            temp_list_erratas.append(palavra)17    return temp_list_erratas18def notasIntencoes(dicionarioIntencoes, frase):19    temp_dict_notas = {}20    contador = 121    for palavra in frase:22        for intencao in dicionarioIntencoes.keys():23            if palavra in dicionarioIntencoes[intencao]:24                if intencao not in temp_dict_notas:25                    temp_dict_notas[intencao] = 026                temp_dict_notas[intencao] += 1 * contador27        contador += 128    return temp_dict_notas29def analiseIntecoes(dicionario_notas_intencoes):30    if len(dicionario_notas_intencoes.keys()) == 0:31        return ""32    lista_keys = []33    for i in dicionario_notas_intencoes.keys():34        lista_keys.append(i)35    intencao_atual = lista_keys[0]36    intencao_atual_nota = dicionario_notas_intencoes[lista_keys[0]]37    for intencao in dicionario_notas_intencoes.keys():38        if dicionario_notas_intencoes[intencao] > intencao_atual_nota:39            intencao_atual_nota = dicionario_notas_intencoes[intencao]40            intencao_atual = intencao41    return intencao_atual42str_letras = "abcdefghijklmnopqrstuvwxyz"43str_ignore = "1234567890()*&%$#@!',./?"44set_letras = gerarSet(str_letras)45set_ignore = gerarSet(str_ignore)46with open('pt_br.txt', 'r', encoding='ISO-8859-1') as f:47    palavras = f.read().split('\n')48with open('intencoes.csv', 'r', encoding='utf8') as csv_f:49    csv_reader = csv.reader(csv_f, delimiter=';')50    dict_intencoes = {}51    linha_counter = 052    for linha in csv_reader:53        if linha_counter == 0:54            linha_counter += 155            continue56        if linha[0] not in dict_intencoes:57            dict_intencoes[linha[0]] = []58        dict_intencoes[linha[0]].append(linha[1])59sair = False60context = []61def conversa(input):62    input = retirarIgnores(input.lower(), set_ignore)63    dict_retorno = {}64    frase_separada = input.split()65    erratas = palavrasNoDicionario(palavras, frase_separada)66    notas_intencoes = notasIntencoes(dict_intencoes, frase_separada)67    intencao = analiseIntecoes(notas_intencoes)68    if len(erratas) > 0:69        dict_retorno['speelCheck'] = 'error'70        dict_retorno['erratas'] = erratas71    else:72        context.append(intencao)73        dict_retorno['spellChack'] = 'ok'74        dict_retorno['response'] = {}75        dict_retorno['response']['intencao'] = intencao76        dict_retorno['response']['notas'] = notas_intencoes77    return dict_retorno78while sair != True:79    frase = retirarIgnores(input("Input: "), set_ignore).lower()80    response = conversa(frase)81    if 'response' in response:82        if response['response']['intencao'] == 'sair':83            break84        elif response['response']['intencao'] == 'reset':85            context.clear()...

bowling.py

Source:bowling.py

1import re2import numpy as np3import pandas as pd4from .scrapers import get_innings_by_innings_stats5default_renames = {"mdns": "maidens",6                   "wkts": "wickets",7                   "econ": "economy",8                   "pos": "position",9                   "inns": "innings"}10default_deletes = ['nan', 'DNB', 'TDNB']11def total_balls(overs_str, str_ignore=['DNB', 'TDNB'], ignore_value=0):12    """13    Calculate total balls bowled from overs formatting14    Parameters15    ----------16    overs_str: string17        Overs bowled in traditional format overs.balls18    str_ignore: list19        Strings to ignore and return 0 - indicators that the player didn't bowl20    ignore_value: int21        Value to input for strings matched into str_ignore22    Returns23    -------24    int:25        The number of balls bowled as an int26    """27    if overs_str in str_ignore:28        return ignore_value29    grouping_re = re.compile(r'^([0-9]*)\.([0-5]*)$').search(overs_str)30    if grouping_re is None:31        return int(overs_str) * 632    else:33        overs = int(grouping_re.group(1)) * 634        balls = int(grouping_re.group(2))35        return overs + balls36def test_innings_by_innings(player_id, column_rename=default_renames, score_deletes=default_deletes, home_or_away=-1):37    """38    Return the test innings by innings for a given player39    Parameters40    ----------41    player_id: int42        Player ID for cricketer from ESPNcricinfo43    column_rename: dict44        Rename columns old: new45    score_deletes: list46        Values to represent null47    home_or_away: int48        Value to limit to either home or away matches49    Returns50    -------51    pandas.DataFrame52        Test innings DataFrame scraped from site53    """54    raw_table = get_innings_by_innings_stats(player_id, 'Bowling', 'Test', home_or_away)55    if raw_table is None:56        return None57    raw_table.replace('-', np.nan, inplace=True)58    raw_table.columns = raw_table.columns.str.lower().str.replace(' ', '_')59    #  Rename columns60    raw_table.rename(column_rename, axis=1, inplace=True)61    raw_table.runs = raw_table.runs.apply(62        lambda x: np.nan if x in score_deletes else x)63    raw_table['total_balls'] = raw_table.overs.astype(str).apply(total_balls)64    #  Remove blank columns65    raw_table.drop('', axis=1, inplace=True)66    return raw_table67def test_home_or_away(player_id):68    """69    Get the test bowling innings for a given player with column indicating home/away/neutral70    Parameters71    ----------72    player_id: int73        Player ID for cricketer from ESPNcricinfo74    Returns75    -------76    pandas.DataFrame77        Test innings DataFrame scraped from site with additional home/away/neutral column78    """79    home = test_innings_by_innings(player_id, home_or_away=1)80    away = test_innings_by_innings(player_id, home_or_away=2)81    neutral = test_innings_by_innings(player_id, home_or_away=3)...

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