Esempio n. 1
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 def parse_expect(self, input, expected_result, **kw):
     parser = csv.parser()
     for kw_arg, kw_value in kw.items():
         setattr(parser, kw_arg, kw_value)
     result = []
     for line in string.split(input, '\n'):
         fields = parser.parse(line)
         if not fields:
             continue
         result.append(fields)
     self.assertEqual(expected_result, result)
Esempio n. 2
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def iif_to_list(fd):
    parser = csv.parser(field_sep='\t')
    rows = []
    while 1:
        line = ifile.readline()
        if not line:
            break
        fields = parser.parse(line)
        if not fields:
            continue
        rows.append(fields)
    fd.close()
    return rows
Esempio n. 3
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def iif_to_list(fd):
    parser = csv.parser(field_sep='\t')
    rows = []
    while 1:
        line = ifile.readline()
        if not line:
            break
        fields = parser.parse(line)
        if not fields:
            continue
        rows.append(fields)
    fd.close()
    return rows
Esempio n. 4
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    def __init__(self, master):
        self.master = master
        self.f1 = Frame(self.master)
        self.canvas = Canvas(self.f1,
                             width=width,
                             height=height,
                             background="#ffffff")
        self.img = Image.open(map_file)
        self.pimg = ImageTk.PhotoImage(self.img)
        self.img = self.canvas.create_image(0, 0, anchor=NW, image=self.pimg)

        self.canvas.bind("<Button-1>", self.mousedown)

        self.nodes = {}
        p = csv.parser()
        n_file = open(nodes_file)
        headers = n_file.readline()
        while 1:
            line = n_file.readline()
            if not line:
                break
            (idx, x, y) = p.parse(line)
            x = int(x)
            y = int(y)
            self.nodes[idx] = (x, y)
            node = self.canvas.create_oval(x - node_radius,
                                           y - node_radius,
                                           x + node_radius,
                                           y + node_radius,
                                           fill=node_color,
                                           outline=node_outline_color)

        self.segments = []
        s_file = open(segments_file)
        headers = s_file.readline()
        while 1:
            line = s_file.readline()
            if not line:
                break
            (start, end) = p.parse(line)
            start = int(start)
            end = int(end)
            self.segments.append((start, end))

        self.canvas.pack()

        self.l = Label(self.f1, text="foo")
        self.l.pack()

        self.f1.pack()
Esempio n. 5
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    def __init__(self,master):
        self.master = master
        self.f1 = Frame(self.master)
        self.canvas = Canvas(self.f1,width=width,height=height,background="#ffffff")
        self.img = Image.open(map_file)
        self.pimg = ImageTk.PhotoImage(self.img)
        self.img = self.canvas.create_image(0,0,anchor=NW,image=self.pimg)

        self.canvas.bind("<Button-1>",self.mousedown)

        self.nodes = {}
        p = csv.parser()
        n_file = open(nodes_file)
        headers = n_file.readline()
        while 1:
            line = n_file.readline()
            if not line:
                break
            (idx,x,y) = p.parse(line)
            x = int(x)
            y = int(y)
            self.nodes[idx] = (x,y)
            node = self.canvas.create_oval(x - node_radius,y-node_radius,x+node_radius,y+node_radius,fill=node_color,outline=node_outline_color)

        self.segments = []
        s_file = open(segments_file)
        headers = s_file.readline()
        while 1:
            line = s_file.readline()
            if not line:
                break
            (start,end) = p.parse(line)
            start = int(start)
            end = int(end)
            self.segments.append((start,end))
            

        self.canvas.pack()

        self.l = Label(self.f1,text="foo")
        self.l.pack()
        
        self.f1.pack()
Esempio n. 6
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 def convert(self):
 #
 # *Convert the input file rows into XML,
 # * and  outputting.
 # *
 # *
 # **
     output =open(self.outputFile, 'w')
     output.write(self.header1+self.header2+self.header3)
     if self.debug:
         print "convert: writing to ", self.outputFile
         print "convert: reading fm: ", self.inputFile
     output.write(self.OPEN_START+self.rootname+self.CLOSE)  #ROOT tag
 
 #
     p = csv.parser()
     f = open(self.inputFile,'r')
     nrows = int(self.nfields) # number of fields
     #Read and parse input file till full record in hand as list
     
     while 1:
         line = f.readline()
         if not line:
             break
         rec = p.parse(line)
         if rec is not None:
             output.write(self.OPEN_START+self.rowname+self.CLOSE+self.NEWLINE) #<entry>
             idx = 0
             for fld in rec:
                 #idx = rec.index(fld)  #index of this item
                 nfld1 = string.replace(fld,"&","&amp;") # subst for &
                 nfld  = string.replace(nfld1,"£","&#x00A3;") # subst for £
                 tag = self.fieldnames['field'+str(idx)]
                 output.write(self.INDENT+self.OPEN_START+tag+self.CLOSE)
                 output.write(nfld)
                 output.write(self.OPEN_END+tag+self.CLOSE+self.NEWLINE)
                 idx += 1
             output.write(self.OPEN_END+self.rowname+self.CLOSE+self.NEWLINE)# </entry>
             
     output.write(self.OPEN_END+self.rootname+self.CLOSE)  #ROOT tag
     output.close()
    ''' Takes the file object called "fd" and returns
    a list of title events, e.g. [(35, "Alchemy"), (2003, "Banana")]'''
    ret = []

    # ASSUME that no revision is more than 64MiB long :-)
    SLURPSIZE = 65536 * 1024
    chunk = fd.read(SLURPSIZE) # a "character array", not decoded Unicode
    offset = 0
    # now we get to use multiline regexes

    while chunk:
        title_pos = title_position(chunk)
        if title_pos > -1:
            title = title_string(chunk) # FIXME: call can be optimized to include title_pos
            start = title_pos
            length = 0 # who cares?, so long as we don't match it next time
            ret.append((offset + title_pos, title))
            chunk = chunk[title_pos:]
            offset += title_pos
            chunk += fd.read(SLURPSIZE - len(chunk))
        else:
            return ret # we're done

if __name__ == '__main__':
    import sys
    import csv
    p = csv.parser()
    values = fd2lists(sys.stdin)
    for vals in values:
        print p.join(vals)
#!/usr/bin/python
# Hacking at XML with regular expressions is great fun.

if __name__ == '__main__':
    import sys
    import csv
    titleparser = csv.parser()
    revparser = csv.parser()
    try:
        titles = open(sys.argv[1])
        revs = open(sys.argv[2])
    except:
        print "Usage: %s title-file.csv revision-file.csv" % sys.argv[0]
        raise AssertionError()

    titledata = []
    for line in titles.xreadlines():
        offset, title = titleparser.parse(line)
        titledata.append((int(offset), title))

    for line in revs.xreadlines():
        offset, length, eyedee = revparser.parse(line)
        offset, length = int(offset), int(length)
        # if the offset is less than the first titledata, then we're doomed
        if offset < titledata[0][0]:
            raise AssertionError("OMG")
        # Now we know it's >= titledata[0][0]
        # if it's > titledata[1][0], then we should pop titledata
        elif len(titledata) > 1 and  offset > titledata[1][0]:
            title = titledata.pop(0)[1]
        else:
Esempio n. 9
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    def csv2numeric(self, filename, types):
        """ opens a csv file and reads it in to named
        Numeric arrays. the file must have the names of the
        columns on the first line

        types is an array of types to treat the columns as. eg, for a file like

        a,b
        1,2.3
        2,5.6
        3,7.84

        you would do

        data = self.csv2numeric("file.csv",[int,float])

        and data would look like:

        {'a': array([1 2 3]), 'b': array([2.3 5.6 7.84])}

        it can really only handle numerical datatypes. ie, you can't
        have strings or even alphabetical characters in the file other
        than the first header row. 

        """
        if not re.match("(http:|\/|file:)", filename):
            filename = urlparse.urljoin(self.uri_base, filename)
        file = urllib.urlopen(filename)
        arrays = []
        headers = []
        try:
            p = csv.parser()
            header_line = file.readline()
            fields = p.parse(header_line)
            for f in fields:
                arrays.append([])
                headers.append(f)
            while 1:
                line = file.readline()
                if not line:
                    break
                fields = p.parse(line)
                for i in range(len(fields)):
                    typecode = types[i]
                    try:
                        arrays[i].append(typecode(fields[i]))
                    except:
                        arrays[i].append(fields[i])
        except AttributeError:
            # must be using python 2.3
            reader = csv.reader(file)
            fields = reader.next()
            for f in fields:
                arrays.append([])
                headers.append(f)
            for row in reader:
                fields = row
                for i in range(len(fields)):
                    typecode = types[i]
                    try:
                        arrays[i].append(typecode(fields[i]))
                    except:
                        try:
                            arrays[i].append(fields[i])
                        except:
                            pass
        results = {}
        for i in range(len(headers)):
            results[headers[i]] = array(arrays[i])
        return results
Esempio n. 10
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 def parse_exception(self, input, exception, **kw):
     parser = csv.parser()
     for kw_arg, kw_value in kw.items():
         setattr(parser, kw_arg, kw_value)
     self.assertRaises(exception, parser.parse, input)
Esempio n. 11
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 def join_expect(self, input, expected_result, **kw):
     parser = csv.parser()
     for kw_arg, kw_value in kw.items():
         setattr(parser, kw_arg, kw_value)
     result = parser.join(input)
     self.assertEqual(expected_result, result)
Esempio n. 12
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    def csv2numeric(self,filename,types):
        """ opens a csv file and reads it in to named
        Numeric arrays. the file must have the names of the
        columns on the first line

        types is an array of types to treat the columns as. eg, for a file like

        a,b
        1,2.3
        2,5.6
        3,7.84

        you would do

        data = self.csv2numeric("file.csv",[int,float])

        and data would look like:

        {'a': array([1 2 3]), 'b': array([2.3 5.6 7.84])}

        it can really only handle numerical datatypes. ie, you can't
        have strings or even alphabetical characters in the file other
        than the first header row. 

        """
        if not re.match("(http:|\/|file:)",filename):
            filename = urlparse.urljoin(self.uri_base,filename)
        file = urllib.urlopen(filename)
        arrays = []
        headers = []
        try:
            p = csv.parser()
            header_line = file.readline()
            fields = p.parse(header_line)
            for f in fields:
                arrays.append([])
                headers.append(f)
            while 1:
                line = file.readline()
                if not line:
                    break
                fields = p.parse(line)
                for i in range(len(fields)):
                    typecode = types[i]
                    try:
                        arrays[i].append(typecode(fields[i]))
                    except:
                        arrays[i].append(fields[i])
        except AttributeError:
            # must be using python 2.3
            reader = csv.reader(file)
            fields = reader.next()
            for f in fields:
                arrays.append([])
                headers.append(f)
            for row in reader:
                fields = row
                for i in range(len(fields)):
                    typecode = types[i]
                    try:
                        arrays[i].append(typecode(fields[i]))
                    except:
                        try:
                            arrays[i].append(fields[i])
                        except:
                            pass
        results = {}
        for i in range(len(headers)):
            results[headers[i]] = array(arrays[i])
        return results