Mercurial > cpython-lru_cache-weakref
annotate Lib/csv.py @ 80661:94de77bd0b4b 2.7
Issue #16194: document imp.load_dynamic problems
when read several extension modules from the same binary object file.
| author | Andrew Svetlov <andrew.svetlov@gmail.com> |
|---|---|
| date | Thu, 29 Nov 2012 19:51:28 +0200 |
| parents | cd8d3c2d3bce |
| children | 0e1d538d36dc |
| rev | line source |
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1 |
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2 """ |
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3 csv.py - read/write/investigate CSV files |
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4 """ |
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5 |
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6 import re |
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7 from functools import reduce |
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8 from _csv import Error, __version__, writer, reader, register_dialect, \ |
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9 unregister_dialect, get_dialect, list_dialects, \ |
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10 field_size_limit, \ |
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11 QUOTE_MINIMAL, QUOTE_ALL, QUOTE_NONNUMERIC, QUOTE_NONE, \ |
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12 __doc__ |
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13 from _csv import Dialect as _Dialect |
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14 |
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15 try: |
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16 from cStringIO import StringIO |
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17 except ImportError: |
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18 from StringIO import StringIO |
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19 |
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20 __all__ = [ "QUOTE_MINIMAL", "QUOTE_ALL", "QUOTE_NONNUMERIC", "QUOTE_NONE", |
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21 "Error", "Dialect", "__doc__", "excel", "excel_tab", |
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22 "field_size_limit", "reader", "writer", |
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23 "register_dialect", "get_dialect", "list_dialects", "Sniffer", |
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24 "unregister_dialect", "__version__", "DictReader", "DictWriter" ] |
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25 |
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26 class Dialect: |
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27 """Describe an Excel dialect. |
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28 |
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29 This must be subclassed (see csv.excel). Valid attributes are: |
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30 delimiter, quotechar, escapechar, doublequote, skipinitialspace, |
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31 lineterminator, quoting. |
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32 |
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33 """ |
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34 _name = "" |
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35 _valid = False |
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36 # placeholders |
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37 delimiter = None |
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38 quotechar = None |
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39 escapechar = None |
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40 doublequote = None |
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41 skipinitialspace = None |
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42 lineterminator = None |
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43 quoting = None |
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44 |
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45 def __init__(self): |
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46 if self.__class__ != Dialect: |
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47 self._valid = True |
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48 self._validate() |
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49 |
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50 def _validate(self): |
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51 try: |
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52 _Dialect(self) |
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53 except TypeError, e: |
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54 # We do this for compatibility with py2.3 |
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55 raise Error(str(e)) |
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56 |
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57 class excel(Dialect): |
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58 """Describe the usual properties of Excel-generated CSV files.""" |
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59 delimiter = ',' |
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60 quotechar = '"' |
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61 doublequote = True |
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62 skipinitialspace = False |
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63 lineterminator = '\r\n' |
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64 quoting = QUOTE_MINIMAL |
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65 register_dialect("excel", excel) |
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66 |
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67 class excel_tab(excel): |
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68 """Describe the usual properties of Excel-generated TAB-delimited files.""" |
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69 delimiter = '\t' |
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70 register_dialect("excel-tab", excel_tab) |
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71 |
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72 |
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73 class DictReader: |
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74 def __init__(self, f, fieldnames=None, restkey=None, restval=None, |
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75 dialect="excel", *args, **kwds): |
| 48198 | 76 self._fieldnames = fieldnames # list of keys for the dict |
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77 self.restkey = restkey # key to catch long rows |
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78 self.restval = restval # default value for short rows |
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79 self.reader = reader(f, dialect, *args, **kwds) |
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80 self.dialect = dialect |
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81 self.line_num = 0 |
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82 |
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83 def __iter__(self): |
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84 return self |
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85 |
| 48198 | 86 @property |
| 87 def fieldnames(self): | |
| 88 if self._fieldnames is None: | |
| 89 try: | |
| 90 self._fieldnames = self.reader.next() | |
| 91 except StopIteration: | |
| 92 pass | |
| 93 self.line_num = self.reader.line_num | |
| 94 return self._fieldnames | |
| 95 | |
| 96 @fieldnames.setter | |
| 97 def fieldnames(self, value): | |
| 98 self._fieldnames = value | |
| 99 | |
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100 def next(self): |
| 48198 | 101 if self.line_num == 0: |
| 102 # Used only for its side effect. | |
| 103 self.fieldnames | |
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104 row = self.reader.next() |
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105 self.line_num = self.reader.line_num |
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106 |
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107 # unlike the basic reader, we prefer not to return blanks, |
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108 # because we will typically wind up with a dict full of None |
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109 # values |
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110 while row == []: |
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111 row = self.reader.next() |
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112 d = dict(zip(self.fieldnames, row)) |
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113 lf = len(self.fieldnames) |
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114 lr = len(row) |
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115 if lf < lr: |
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116 d[self.restkey] = row[lf:] |
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117 elif lf > lr: |
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118 for key in self.fieldnames[lr:]: |
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119 d[key] = self.restval |
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120 return d |
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121 |
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122 |
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123 class DictWriter: |
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124 def __init__(self, f, fieldnames, restval="", extrasaction="raise", |
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125 dialect="excel", *args, **kwds): |
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126 self.fieldnames = fieldnames # list of keys for the dict |
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127 self.restval = restval # for writing short dicts |
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128 if extrasaction.lower() not in ("raise", "ignore"): |
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129 raise ValueError, \ |
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130 ("extrasaction (%s) must be 'raise' or 'ignore'" % |
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131 extrasaction) |
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132 self.extrasaction = extrasaction |
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133 self.writer = writer(f, dialect, *args, **kwds) |
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134 |
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135 def writeheader(self): |
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136 header = dict(zip(self.fieldnames, self.fieldnames)) |
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137 self.writerow(header) |
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138 |
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139 def _dict_to_list(self, rowdict): |
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140 if self.extrasaction == "raise": |
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141 wrong_fields = [k for k in rowdict if k not in self.fieldnames] |
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142 if wrong_fields: |
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143 raise ValueError("dict contains fields not in fieldnames: " + |
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144 ", ".join(wrong_fields)) |
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145 return [rowdict.get(key, self.restval) for key in self.fieldnames] |
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146 |
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147 def writerow(self, rowdict): |
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148 return self.writer.writerow(self._dict_to_list(rowdict)) |
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149 |
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150 def writerows(self, rowdicts): |
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151 rows = [] |
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152 for rowdict in rowdicts: |
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153 rows.append(self._dict_to_list(rowdict)) |
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154 return self.writer.writerows(rows) |
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155 |
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156 # Guard Sniffer's type checking against builds that exclude complex() |
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157 try: |
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158 complex |
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159 except NameError: |
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160 complex = float |
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161 |
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162 class Sniffer: |
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163 ''' |
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164 "Sniffs" the format of a CSV file (i.e. delimiter, quotechar) |
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165 Returns a Dialect object. |
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166 ''' |
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167 def __init__(self): |
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168 # in case there is more than one possible delimiter |
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169 self.preferred = [',', '\t', ';', ' ', ':'] |
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170 |
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171 |
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172 def sniff(self, sample, delimiters=None): |
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173 """ |
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174 Returns a dialect (or None) corresponding to the sample |
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175 """ |
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176 |
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177 quotechar, doublequote, delimiter, skipinitialspace = \ |
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178 self._guess_quote_and_delimiter(sample, delimiters) |
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179 if not delimiter: |
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180 delimiter, skipinitialspace = self._guess_delimiter(sample, |
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181 delimiters) |
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182 |
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183 if not delimiter: |
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184 raise Error, "Could not determine delimiter" |
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185 |
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186 class dialect(Dialect): |
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187 _name = "sniffed" |
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188 lineterminator = '\r\n' |
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189 quoting = QUOTE_MINIMAL |
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190 # escapechar = '' |
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191 |
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192 dialect.doublequote = doublequote |
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193 dialect.delimiter = delimiter |
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194 # _csv.reader won't accept a quotechar of '' |
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195 dialect.quotechar = quotechar or '"' |
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196 dialect.skipinitialspace = skipinitialspace |
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197 |
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198 return dialect |
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199 |
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200 |
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201 def _guess_quote_and_delimiter(self, data, delimiters): |
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202 """ |
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203 Looks for text enclosed between two identical quotes |
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204 (the probable quotechar) which are preceded and followed |
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205 by the same character (the probable delimiter). |
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206 For example: |
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207 ,'some text', |
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208 The quote with the most wins, same with the delimiter. |
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209 If there is no quotechar the delimiter can't be determined |
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210 this way. |
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211 """ |
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212 |
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213 matches = [] |
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214 for restr in ('(?P<delim>[^\w\n"\'])(?P<space> ?)(?P<quote>["\']).*?(?P=quote)(?P=delim)', # ,".*?", |
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215 '(?:^|\n)(?P<quote>["\']).*?(?P=quote)(?P<delim>[^\w\n"\'])(?P<space> ?)', # ".*?", |
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216 '(?P<delim>>[^\w\n"\'])(?P<space> ?)(?P<quote>["\']).*?(?P=quote)(?:$|\n)', # ,".*?" |
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217 '(?:^|\n)(?P<quote>["\']).*?(?P=quote)(?:$|\n)'): # ".*?" (no delim, no space) |
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218 regexp = re.compile(restr, re.DOTALL | re.MULTILINE) |
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219 matches = regexp.findall(data) |
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220 if matches: |
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221 break |
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222 |
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223 if not matches: |
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224 # (quotechar, doublequote, delimiter, skipinitialspace) |
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225 return ('', False, None, 0) |
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226 quotes = {} |
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227 delims = {} |
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228 spaces = 0 |
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229 for m in matches: |
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230 n = regexp.groupindex['quote'] - 1 |
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231 key = m[n] |
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232 if key: |
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233 quotes[key] = quotes.get(key, 0) + 1 |
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234 try: |
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235 n = regexp.groupindex['delim'] - 1 |
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236 key = m[n] |
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237 except KeyError: |
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238 continue |
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239 if key and (delimiters is None or key in delimiters): |
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240 delims[key] = delims.get(key, 0) + 1 |
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241 try: |
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242 n = regexp.groupindex['space'] - 1 |
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243 except KeyError: |
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244 continue |
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245 if m[n]: |
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246 spaces += 1 |
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247 |
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248 quotechar = reduce(lambda a, b, quotes = quotes: |
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249 (quotes[a] > quotes[b]) and a or b, quotes.keys()) |
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250 |
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251 if delims: |
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252 delim = reduce(lambda a, b, delims = delims: |
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253 (delims[a] > delims[b]) and a or b, delims.keys()) |
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254 skipinitialspace = delims[delim] == spaces |
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255 if delim == '\n': # most likely a file with a single column |
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256 delim = '' |
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257 else: |
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258 # there is *no* delimiter, it's a single column of quoted data |
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259 delim = '' |
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260 skipinitialspace = 0 |
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261 |
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262 # if we see an extra quote between delimiters, we've got a |
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263 # double quoted format |
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264 dq_regexp = re.compile(r"((%(delim)s)|^)\W*%(quote)s[^%(delim)s\n]*%(quote)s[^%(delim)s\n]*%(quote)s\W*((%(delim)s)|$)" % \ |
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265 {'delim':delim, 'quote':quotechar}, re.MULTILINE) |
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266 |
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267 |
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268 |
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269 if dq_regexp.search(data): |
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270 doublequote = True |
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271 else: |
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272 doublequote = False |
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273 |
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274 return (quotechar, doublequote, delim, skipinitialspace) |
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275 |
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276 |
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277 def _guess_delimiter(self, data, delimiters): |
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278 """ |
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279 The delimiter /should/ occur the same number of times on |
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280 each row. However, due to malformed data, it may not. We don't want |
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281 an all or nothing approach, so we allow for small variations in this |
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282 number. |
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283 1) build a table of the frequency of each character on every line. |
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284 2) build a table of frequencies of this frequency (meta-frequency?), |
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285 e.g. 'x occurred 5 times in 10 rows, 6 times in 1000 rows, |
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286 7 times in 2 rows' |
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287 3) use the mode of the meta-frequency to determine the /expected/ |
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288 frequency for that character |
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289 4) find out how often the character actually meets that goal |
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290 5) the character that best meets its goal is the delimiter |
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291 For performance reasons, the data is evaluated in chunks, so it can |
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292 try and evaluate the smallest portion of the data possible, evaluating |
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293 additional chunks as necessary. |
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294 """ |
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295 |
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296 data = filter(None, data.split('\n')) |
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297 |
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298 ascii = [chr(c) for c in range(127)] # 7-bit ASCII |
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299 |
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300 # build frequency tables |
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301 chunkLength = min(10, len(data)) |
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302 iteration = 0 |
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303 charFrequency = {} |
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304 modes = {} |
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305 delims = {} |
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306 start, end = 0, min(chunkLength, len(data)) |
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307 while start < len(data): |
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308 iteration += 1 |
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309 for line in data[start:end]: |
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310 for char in ascii: |
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311 metaFrequency = charFrequency.get(char, {}) |
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312 # must count even if frequency is 0 |
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313 freq = line.count(char) |
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314 # value is the mode |
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315 metaFrequency[freq] = metaFrequency.get(freq, 0) + 1 |
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316 charFrequency[char] = metaFrequency |
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317 |
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318 for char in charFrequency.keys(): |
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319 items = charFrequency[char].items() |
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320 if len(items) == 1 and items[0][0] == 0: |
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321 continue |
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322 # get the mode of the frequencies |
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323 if len(items) > 1: |
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324 modes[char] = reduce(lambda a, b: a[1] > b[1] and a or b, |
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325 items) |
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326 # adjust the mode - subtract the sum of all |
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327 # other frequencies |
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328 items.remove(modes[char]) |
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329 modes[char] = (modes[char][0], modes[char][1] |
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330 - reduce(lambda a, b: (0, a[1] + b[1]), |
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331 items)[1]) |
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332 else: |
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333 modes[char] = items[0] |
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334 |
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335 # build a list of possible delimiters |
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336 modeList = modes.items() |
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337 total = float(chunkLength * iteration) |
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338 # (rows of consistent data) / (number of rows) = 100% |
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339 consistency = 1.0 |
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340 # minimum consistency threshold |
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341 threshold = 0.9 |
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342 while len(delims) == 0 and consistency >= threshold: |
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343 for k, v in modeList: |
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344 if v[0] > 0 and v[1] > 0: |
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345 if ((v[1]/total) >= consistency and |
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346 (delimiters is None or k in delimiters)): |
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347 delims[k] = v |
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348 consistency -= 0.01 |
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349 |
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350 if len(delims) == 1: |
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351 delim = delims.keys()[0] |
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352 skipinitialspace = (data[0].count(delim) == |
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353 data[0].count("%c " % delim)) |
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354 return (delim, skipinitialspace) |
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355 |
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356 # analyze another chunkLength lines |
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357 start = end |
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358 end += chunkLength |
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359 |
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360 if not delims: |
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361 return ('', 0) |
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362 |
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363 # if there's more than one, fall back to a 'preferred' list |
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364 if len(delims) > 1: |
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365 for d in self.preferred: |
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366 if d in delims.keys(): |
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367 skipinitialspace = (data[0].count(d) == |
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368 data[0].count("%c " % d)) |
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369 return (d, skipinitialspace) |
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370 |
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371 # nothing else indicates a preference, pick the character that |
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372 # dominates(?) |
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373 items = [(v,k) for (k,v) in delims.items()] |
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374 items.sort() |
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375 delim = items[-1][1] |
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376 |
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377 skipinitialspace = (data[0].count(delim) == |
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378 data[0].count("%c " % delim)) |
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379 return (delim, skipinitialspace) |
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380 |
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381 |
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382 def has_header(self, sample): |
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383 # Creates a dictionary of types of data in each column. If any |
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384 # column is of a single type (say, integers), *except* for the first |
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385 # row, then the first row is presumed to be labels. If the type |
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386 # can't be determined, it is assumed to be a string in which case |
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387 # the length of the string is the determining factor: if all of the |
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388 # rows except for the first are the same length, it's a header. |
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389 # Finally, a 'vote' is taken at the end for each column, adding or |
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390 # subtracting from the likelihood of the first row being a header. |
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391 |
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392 rdr = reader(StringIO(sample), self.sniff(sample)) |
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393 |
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394 header = rdr.next() # assume first row is header |
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395 |
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396 columns = len(header) |
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397 columnTypes = {} |
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398 for i in range(columns): columnTypes[i] = None |
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399 |
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400 checked = 0 |
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401 for row in rdr: |
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402 # arbitrary number of rows to check, to keep it sane |
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403 if checked > 20: |
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404 break |
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405 checked += 1 |
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406 |
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407 if len(row) != columns: |
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408 continue # skip rows that have irregular number of columns |
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409 |
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410 for col in columnTypes.keys(): |
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411 |
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412 for thisType in [int, long, float, complex]: |
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413 try: |
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414 thisType(row[col]) |
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415 break |
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416 except (ValueError, OverflowError): |
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417 pass |
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418 else: |
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419 # fallback to length of string |
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420 thisType = len(row[col]) |
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421 |
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422 # treat longs as ints |
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423 if thisType == long: |
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424 thisType = int |
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425 |
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426 if thisType != columnTypes[col]: |
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427 if columnTypes[col] is None: # add new column type |
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428 columnTypes[col] = thisType |
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429 else: |
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430 # type is inconsistent, remove column from |
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431 # consideration |
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432 del columnTypes[col] |
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433 |
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434 # finally, compare results against first row and "vote" |
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435 # on whether it's a header |
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436 hasHeader = 0 |
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437 for col, colType in columnTypes.items(): |
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438 if type(colType) == type(0): # it's a length |
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439 if len(header[col]) != colType: |
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440 hasHeader += 1 |
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441 else: |
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442 hasHeader -= 1 |
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443 else: # attempt typecast |
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444 try: |
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445 colType(header[col]) |
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446 except (ValueError, TypeError): |
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447 hasHeader += 1 |
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448 else: |
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449 hasHeader -= 1 |
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450 |
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451 return hasHeader > 0 |
