[Zope3-checkins] CVS: Zope3/src/pythonlib/compat22 - _csv.c:1.2.2.1 csv.py:1.1.2.1
Grégoire Weber
zope@i-con.ch
Sun, 22 Jun 2003 10:22:24 -0400
Update of /cvs-repository/Zope3/src/pythonlib/compat22
In directory cvs.zope.org:/tmp/cvs-serv24874/src/pythonlib/compat22
Added Files:
Tag: cw-mail-branch
_csv.c csv.py
Log Message:
Synced up with HEAD
=== Added File Zope3/src/pythonlib/compat22/_csv.c === (1150/1550 lines abridged)
/* csv module */
/*
This module provides the low-level underpinnings of a CSV reading/writing
module. Users should not use this module directly, but import the csv.py
module instead.
**** For people modifying this code, please note that as of this writing
**** (2003-03-23), it is intended that this code should work with Python
**** 2.2.
*/
#define MODULE_VERSION "1.0"
#include "Python.h"
#include "structmember.h"
/* begin 2.2 compatibility macros */
#ifndef PyDoc_STRVAR
/* Define macros for inline documentation. */
#define PyDoc_VAR(name) static char name[]
#define PyDoc_STRVAR(name,str) PyDoc_VAR(name) = PyDoc_STR(str)
#ifdef WITH_DOC_STRINGS
#define PyDoc_STR(str) str
#else
#define PyDoc_STR(str) ""
#endif
#endif /* ifndef PyDoc_STRVAR */
#ifndef PyMODINIT_FUNC
# if defined(__cplusplus)
# define PyMODINIT_FUNC extern "C" void
# else /* __cplusplus */
# define PyMODINIT_FUNC void
# endif /* __cplusplus */
#endif
/* end 2.2 compatibility macros */
static PyObject *error_obj; /* CSV exception */
static PyObject *dialects; /* Dialect registry */
typedef enum {
START_RECORD, START_FIELD, ESCAPED_CHAR, IN_FIELD,
IN_QUOTED_FIELD, ESCAPE_IN_QUOTED_FIELD, QUOTE_IN_QUOTED_FIELD
} ParserState;
typedef enum {
QUOTE_MINIMAL, QUOTE_ALL, QUOTE_NONNUMERIC, QUOTE_NONE
} QuoteStyle;
typedef struct {
QuoteStyle style;
char *name;
} StyleDesc;
static StyleDesc quote_styles[] = {
{ QUOTE_MINIMAL, "QUOTE_MINIMAL" },
{ QUOTE_ALL, "QUOTE_ALL" },
{ QUOTE_NONNUMERIC, "QUOTE_NONNUMERIC" },
{ QUOTE_NONE, "QUOTE_NONE" },
{ 0 }
};
typedef struct {
PyObject_HEAD
int doublequote; /* is " represented by ""? */
char delimiter; /* field separator */
char quotechar; /* quote character */
char escapechar; /* escape character */
int skipinitialspace; /* ignore spaces following delimiter? */
PyObject *lineterminator; /* string to write between records */
QuoteStyle quoting; /* style of quoting to write */
int strict; /* raise exception on bad CSV */
} DialectObj;
staticforward PyTypeObject Dialect_Type;
typedef struct {
PyObject_HEAD
PyObject *input_iter; /* iterate over this for input lines */
DialectObj *dialect; /* parsing dialect */
PyObject *fields; /* field list for current record */
ParserState state; /* current CSV parse state */
char *field; /* build current field in here */
int field_size; /* size of allocated buffer */
int field_len; /* length of current field */
int had_parse_error; /* did we have a parse error? */
} ReaderObj;
staticforward PyTypeObject Reader_Type;
#define ReaderObject_Check(v) ((v)->ob_type == &Reader_Type)
typedef struct {
PyObject_HEAD
PyObject *writeline; /* write output lines to this file */
DialectObj *dialect; /* parsing dialect */
char *rec; /* buffer for parser.join */
int rec_size; /* size of allocated record */
int rec_len; /* length of record */
int num_fields; /* number of fields in record */
} WriterObj;
staticforward PyTypeObject Writer_Type;
/*
* DIALECT class
*/
static PyObject *
get_dialect_from_registry(PyObject * name_obj)
{
PyObject *dialect_obj;
dialect_obj = PyDict_GetItem(dialects, name_obj);
if (dialect_obj == NULL)
return PyErr_Format(error_obj, "unknown dialect");
Py_INCREF(dialect_obj);
return dialect_obj;
}
static int
check_delattr(PyObject *v)
{
if (v == NULL) {
PyErr_SetString(PyExc_TypeError,
"Cannot delete attribute");
return -1;
}
return 0;
}
static PyObject *
get_string(PyObject *str)
{
Py_XINCREF(str);
return str;
}
static int
set_string(PyObject **str, PyObject *v)
{
if (check_delattr(v) < 0)
return -1;
if (!PyString_Check(v)
#ifdef Py_USING_UNICODE
&& !PyUnicode_Check(v)
#endif
) {
PyErr_BadArgument();
return -1;
}
Py_XDECREF(*str);
Py_INCREF(v);
*str = v;
return 0;
}
static PyObject *
get_nullchar_as_None(char c)
{
if (c == '\0') {
Py_INCREF(Py_None);
return Py_None;
}
else
return PyString_FromStringAndSize((char*)&c, 1);
}
static int
set_None_as_nullchar(char * addr, PyObject *v)
{
if (check_delattr(v) < 0)
return -1;
if (v == Py_None)
*addr = '\0';
else if (!PyString_Check(v) || PyString_Size(v) != 1) {
PyErr_BadArgument();
return -1;
}
else {
char *s = PyString_AsString(v);
if (s == NULL)
return -1;
*addr = s[0];
}
return 0;
}
[-=- -=- -=- 1150 lines omitted -=- -=- -=-]
return NULL;
}
if (PyDict_SetItem(dialects, name_obj, dialect_obj) < 0) {
Py_DECREF(dialect_obj);
return NULL;
}
Py_DECREF(dialect_obj);
Py_INCREF(Py_None);
return Py_None;
}
static PyObject *
csv_unregister_dialect(PyObject *module, PyObject *name_obj)
{
if (PyDict_DelItem(dialects, name_obj) < 0)
return PyErr_Format(error_obj, "unknown dialect");
Py_INCREF(Py_None);
return Py_None;
}
static PyObject *
csv_get_dialect(PyObject *module, PyObject *name_obj)
{
return get_dialect_from_registry(name_obj);
}
/*
* MODULE
*/
PyDoc_STRVAR(csv_module_doc,
"CSV parsing and writing.\n"
"\n"
"This module provides classes that assist in the reading and writing\n"
"of Comma Separated Value (CSV) files, and implements the interface\n"
"described by PEP 305. Although many CSV files are simple to parse,\n"
"the format is not formally defined by a stable specification and\n"
"is subtle enough that parsing lines of a CSV file with something\n"
"like line.split(\",\") is bound to fail. The module supports three\n"
"basic APIs: reading, writing, and registration of dialects.\n"
"\n"
"\n"
"DIALECT REGISTRATION:\n"
"\n"
"Readers and writers support a dialect argument, which is a convenient\n"
"handle on a group of settings. When the dialect argument is a string,\n"
"it identifies one of the dialects previously registered with the module.\n"
"If it is a class or instance, the attributes of the argument are used as\n"
"the settings for the reader or writer:\n"
"\n"
" class excel:\n"
" delimiter = ','\n"
" quotechar = '\"'\n"
" escapechar = None\n"
" doublequote = True\n"
" skipinitialspace = False\n"
" lineterminator = '\r\n'\n"
" quoting = QUOTE_MINIMAL\n"
"\n"
"SETTINGS:\n"
"\n"
" * quotechar - specifies a one-character string to use as the \n"
" quoting character. It defaults to '\"'.\n"
" * delimiter - specifies a one-character string to use as the \n"
" field separator. It defaults to ','.\n"
" * skipinitialspace - specifies how to interpret whitespace which\n"
" immediately follows a delimiter. It defaults to False, which\n"
" means that whitespace immediately following a delimiter is part\n"
" of the following field.\n"
" * lineterminator - specifies the character sequence which should \n"
" terminate rows.\n"
" * quoting - controls when quotes should be generated by the writer.\n"
" It can take on any of the following module constants:\n"
"\n"
" csv.QUOTE_MINIMAL means only when required, for example, when a\n"
" field contains either the quotechar or the delimiter\n"
" csv.QUOTE_ALL means that quotes are always placed around fields.\n"
" csv.QUOTE_NONNUMERIC means that quotes are always placed around\n"
" fields which contain characters other than [+-0-9.].\n"
" csv.QUOTE_NONE means that quotes are never placed around fields.\n"
" * escapechar - specifies a one-character string used to escape \n"
" the delimiter when quoting is set to QUOTE_NONE.\n"
" * doublequote - controls the handling of quotes inside fields. When\n"
" True, two consecutive quotes are interpreted as one during read,\n"
" and when writing, each quote character embedded in the data is\n"
" written as two quotes\n");
PyDoc_STRVAR(csv_reader_doc,
" csv_reader = reader(iterable [, dialect='excel']\n"
" [optional keyword args])\n"
" for row in csv_reader:\n"
" process(row)\n"
"\n"
"The \"iterable\" argument can be any object that returns a line\n"
"of input for each iteration, such as a file object or a list. The\n"
"optional \"dialect\" parameter is discussed below. The function\n"
"also accepts optional keyword arguments which override settings\n"
"provided by the dialect.\n"
"\n"
"The returned object is an iterator. Each iteration returns a row\n"
"of the CSV file (which can span multiple input lines):\n");
PyDoc_STRVAR(csv_writer_doc,
" csv_writer = csv.writer(fileobj [, dialect='excel']\n"
" [optional keyword args])\n"
" for row in csv_writer:\n"
" csv_writer.writerow(row)\n"
"\n"
" [or]\n"
"\n"
" csv_writer = csv.writer(fileobj [, dialect='excel']\n"
" [optional keyword args])\n"
" csv_writer.writerows(rows)\n"
"\n"
"The \"fileobj\" argument can be any object that supports the file API.\n");
PyDoc_STRVAR(csv_list_dialects_doc,
"Return a list of all know dialect names.\n"
" names = csv.list_dialects()");
PyDoc_STRVAR(csv_get_dialect_doc,
"Return the dialect instance associated with name.\n"
" dialect = csv.get_dialect(name)");
PyDoc_STRVAR(csv_register_dialect_doc,
"Create a mapping from a string name to a dialect class.\n"
" dialect = csv.register_dialect(name, dialect)");
PyDoc_STRVAR(csv_unregister_dialect_doc,
"Delete the name/dialect mapping associated with a string name.\n"
" csv.unregister_dialect(name)");
static struct PyMethodDef csv_methods[] = {
{ "reader", (PyCFunction)csv_reader,
METH_VARARGS | METH_KEYWORDS, csv_reader_doc},
{ "writer", (PyCFunction)csv_writer,
METH_VARARGS | METH_KEYWORDS, csv_writer_doc},
{ "list_dialects", (PyCFunction)csv_list_dialects,
METH_NOARGS, csv_list_dialects_doc},
{ "register_dialect", (PyCFunction)csv_register_dialect,
METH_VARARGS, csv_register_dialect_doc},
{ "unregister_dialect", (PyCFunction)csv_unregister_dialect,
METH_O, csv_unregister_dialect_doc},
{ "get_dialect", (PyCFunction)csv_get_dialect,
METH_O, csv_get_dialect_doc},
{ NULL, NULL }
};
PyMODINIT_FUNC
init_csv(void)
{
PyObject *module;
StyleDesc *style;
if (PyType_Ready(&Dialect_Type) < 0)
return;
Dialect_Type.tp_alloc = PyType_GenericAlloc;
if (PyType_Ready(&Reader_Type) < 0)
return;
if (PyType_Ready(&Writer_Type) < 0)
return;
/* Create the module and add the functions */
module = Py_InitModule3("_csv", csv_methods, csv_module_doc);
if (module == NULL)
return;
/* Add version to the module. */
if (PyModule_AddStringConstant(module, "__version__",
MODULE_VERSION) == -1)
return;
/* Add _dialects dictionary */
dialects = PyDict_New();
if (dialects == NULL)
return;
if (PyModule_AddObject(module, "_dialects", dialects))
return;
/* Add quote styles into dictionary */
for (style = quote_styles; style->name; style++) {
if (PyModule_AddIntConstant(module, style->name,
style->style) == -1)
return;
}
/* Add the Dialect type */
if (PyModule_AddObject(module, "Dialect", (PyObject *)&Dialect_Type))
return;
/* Add the CSV exception object to the module. */
error_obj = PyErr_NewException("_csv.Error", NULL, NULL);
if (error_obj == NULL)
return;
PyModule_AddObject(module, "Error", error_obj);
}
=== Added File Zope3/src/pythonlib/compat22/csv.py ===
"""
csv.py - read/write/investigate CSV files
"""
import re
from _csv import Error, __version__, writer, reader, register_dialect, \
unregister_dialect, get_dialect, list_dialects, \
QUOTE_MINIMAL, QUOTE_ALL, QUOTE_NONNUMERIC, QUOTE_NONE, \
__doc__
try:
from cStringIO import StringIO
except ImportError:
from StringIO import StringIO
__all__ = [ "QUOTE_MINIMAL", "QUOTE_ALL", "QUOTE_NONNUMERIC", "QUOTE_NONE",
"Error", "Dialect", "excel", "excel_tab", "reader", "writer",
"register_dialect", "get_dialect", "list_dialects", "Sniffer",
"unregister_dialect", "__version__", "DictReader", "DictWriter" ]
class Dialect:
_name = ""
_valid = False
# placeholders
delimiter = None
quotechar = None
escapechar = None
doublequote = None
skipinitialspace = None
lineterminator = None
quoting = None
def __init__(self):
if self.__class__ != Dialect:
self._valid = True
errors = self._validate()
if errors != []:
raise Error, "Dialect did not validate: %s" % ", ".join(errors)
def _validate(self):
errors = []
if not self._valid:
errors.append("can't directly instantiate Dialect class")
if self.delimiter is None:
errors.append("delimiter character not set")
elif (not isinstance(self.delimiter, str) or
len(self.delimiter) > 1):
errors.append("delimiter must be one-character string")
if self.quotechar is None:
if self.quoting != QUOTE_NONE:
errors.append("quotechar not set")
elif (not isinstance(self.quotechar, str) or
len(self.quotechar) > 1):
errors.append("quotechar must be one-character string")
if self.lineterminator is None:
errors.append("lineterminator not set")
elif not isinstance(self.lineterminator, str):
errors.append("lineterminator must be a string")
if self.doublequote not in (True, False):
errors.append("doublequote parameter must be True or False")
if self.skipinitialspace not in (True, False):
errors.append("skipinitialspace parameter must be True or False")
if self.quoting is None:
errors.append("quoting parameter not set")
if self.quoting is QUOTE_NONE:
if (not isinstance(self.escapechar, (unicode, str)) or
len(self.escapechar) > 1):
errors.append("escapechar must be a one-character string or unicode object")
return errors
class excel(Dialect):
delimiter = ','
quotechar = '"'
doublequote = True
skipinitialspace = False
lineterminator = '\r\n'
quoting = QUOTE_MINIMAL
register_dialect("excel", excel)
class excel_tab(excel):
delimiter = '\t'
register_dialect("excel-tab", excel_tab)
class DictReader:
def __init__(self, f, fieldnames, restkey=None, restval=None,
dialect="excel", *args):
self.fieldnames = fieldnames # list of keys for the dict
self.restkey = restkey # key to catch long rows
self.restval = restval # default value for short rows
self.reader = reader(f, dialect, *args)
def __iter__(self):
return self
def next(self):
row = self.reader.next()
# unlike the basic reader, we prefer not to return blanks,
# because we will typically wind up with a dict full of None
# values
while row == []:
row = self.reader.next()
d = dict(zip(self.fieldnames, row))
lf = len(self.fieldnames)
lr = len(row)
if lf < lr:
d[self.restkey] = row[lf:]
elif lf > lr:
for key in self.fieldnames[lr:]:
d[key] = self.restval
return d
class DictWriter:
def __init__(self, f, fieldnames, restval="", extrasaction="raise",
dialect="excel", *args):
self.fieldnames = fieldnames # list of keys for the dict
self.restval = restval # for writing short dicts
if extrasaction.lower() not in ("raise", "ignore"):
raise ValueError, \
("extrasaction (%s) must be 'raise' or 'ignore'" %
extrasaction)
self.extrasaction = extrasaction
self.writer = writer(f, dialect, *args)
def _dict_to_list(self, rowdict):
if self.extrasaction == "raise":
for k in rowdict.keys():
if k not in self.fieldnames:
raise ValueError, "dict contains fields not in fieldnames"
return [rowdict.get(key, self.restval) for key in self.fieldnames]
def writerow(self, rowdict):
return self.writer.writerow(self._dict_to_list(rowdict))
def writerows(self, rowdicts):
rows = []
for rowdict in rowdicts:
rows.append(self._dict_to_list(rowdict))
return self.writer.writerows(rows)
class Sniffer:
'''
"Sniffs" the format of a CSV file (i.e. delimiter, quotechar)
Returns a Dialect object.
'''
def __init__(self):
# in case there is more than one possible delimiter
self.preferred = [',', '\t', ';', ' ', ':']
def sniff(self, sample, delimiters=None):
"""
Returns a dialect (or None) corresponding to the sample
"""
quotechar, delimiter, skipinitialspace = \
self._guess_quote_and_delimiter(sample, delimiters)
if delimiter is None:
delimiter, skipinitialspace = self._guess_delimiter(sample,
delimiters)
class dialect(Dialect):
_name = "sniffed"
lineterminator = '\r\n'
quoting = QUOTE_MINIMAL
# escapechar = ''
doublequote = False
dialect.delimiter = delimiter
# _csv.reader won't accept a quotechar of ''
dialect.quotechar = quotechar or '"'
dialect.skipinitialspace = skipinitialspace
return dialect
def _guess_quote_and_delimiter(self, data, delimiters):
"""
Looks for text enclosed between two identical quotes
(the probable quotechar) which are preceded and followed
by the same character (the probable delimiter).
For example:
,'some text',
The quote with the most wins, same with the delimiter.
If there is no quotechar the delimiter can't be determined
this way.
"""
matches = []
for restr in ('(?P<delim>[^\w\n"\'])(?P<space> ?)(?P<quote>["\']).*?(?P=quote)(?P=delim)', # ,".*?",
'(?:^|\n)(?P<quote>["\']).*?(?P=quote)(?P<delim>[^\w\n"\'])(?P<space> ?)', # ".*?",
'(?P<delim>>[^\w\n"\'])(?P<space> ?)(?P<quote>["\']).*?(?P=quote)(?:$|\n)', # ,".*?"
'(?:^|\n)(?P<quote>["\']).*?(?P=quote)(?:$|\n)'): # ".*?" (no delim, no space)
regexp = re.compile(restr, re.S | re.M)
matches = regexp.findall(data)
if matches:
break
if not matches:
return ('', None, 0) # (quotechar, delimiter, skipinitialspace)
quotes = {}
delims = {}
spaces = 0
for m in matches:
n = regexp.groupindex['quote'] - 1
key = m[n]
if key:
quotes[key] = quotes.get(key, 0) + 1
try:
n = regexp.groupindex['delim'] - 1
key = m[n]
except KeyError:
continue
if key and (delimiters is None or key in delimiters):
delims[key] = delims.get(key, 0) + 1
try:
n = regexp.groupindex['space'] - 1
except KeyError:
continue
if m[n]:
spaces += 1
quotechar = reduce(lambda a, b, quotes = quotes:
(quotes[a] > quotes[b]) and a or b, quotes.keys())
if delims:
delim = reduce(lambda a, b, delims = delims:
(delims[a] > delims[b]) and a or b, delims.keys())
skipinitialspace = delims[delim] == spaces
if delim == '\n': # most likely a file with a single column
delim = ''
else:
# there is *no* delimiter, it's a single column of quoted data
delim = ''
skipinitialspace = 0
return (quotechar, delim, skipinitialspace)
def _guess_delimiter(self, data, delimiters):
"""
The delimiter /should/ occur the same number of times on
each row. However, due to malformed data, it may not. We don't want
an all or nothing approach, so we allow for small variations in this
number.
1) build a table of the frequency of each character on every line.
2) build a table of freqencies of this frequency (meta-frequency?),
e.g. 'x occurred 5 times in 10 rows, 6 times in 1000 rows,
7 times in 2 rows'
3) use the mode of the meta-frequency to determine the /expected/
frequency for that character
4) find out how often the character actually meets that goal
5) the character that best meets its goal is the delimiter
For performance reasons, the data is evaluated in chunks, so it can
try and evaluate the smallest portion of the data possible, evaluating
additional chunks as necessary.
"""
data = filter(None, data.split('\n'))
ascii = [chr(c) for c in range(127)] # 7-bit ASCII
# build frequency tables
chunkLength = min(10, len(data))
iteration = 0
charFrequency = {}
modes = {}
delims = {}
start, end = 0, min(chunkLength, len(data))
while start < len(data):
iteration += 1
for line in data[start:end]:
for char in ascii:
metaFrequency = charFrequency.get(char, {})
# must count even if frequency is 0
freq = line.strip().count(char)
# value is the mode
metaFrequency[freq] = metaFrequency.get(freq, 0) + 1
charFrequency[char] = metaFrequency
for char in charFrequency.keys():
items = charFrequency[char].items()
if len(items) == 1 and items[0][0] == 0:
continue
# get the mode of the frequencies
if len(items) > 1:
modes[char] = reduce(lambda a, b: a[1] > b[1] and a or b,
items)
# adjust the mode - subtract the sum of all
# other frequencies
items.remove(modes[char])
modes[char] = (modes[char][0], modes[char][1]
- reduce(lambda a, b: (0, a[1] + b[1]),
items)[1])
else:
modes[char] = items[0]
# build a list of possible delimiters
modeList = modes.items()
total = float(chunkLength * iteration)
# (rows of consistent data) / (number of rows) = 100%
consistency = 1.0
# minimum consistency threshold
threshold = 0.9
while len(delims) == 0 and consistency >= threshold:
for k, v in modeList:
if v[0] > 0 and v[1] > 0:
if ((v[1]/total) >= consistency and
(delimiters is None or k in delimiters)):
delims[k] = v
consistency -= 0.01
if len(delims) == 1:
delim = delims.keys()[0]
skipinitialspace = (data[0].count(delim) ==
data[0].count("%c " % delim))
return (delim, skipinitialspace)
# analyze another chunkLength lines
start = end
end += chunkLength
if not delims:
return ('', 0)
# if there's more than one, fall back to a 'preferred' list
if len(delims) > 1:
for d in self.preferred:
if d in delims.keys():
skipinitialspace = (data[0].count(d) ==
data[0].count("%c " % d))
return (d, skipinitialspace)
# finally, just return the first damn character in the list
delim = delims.keys()[0]
skipinitialspace = (data[0].count(delim) ==
data[0].count("%c " % delim))
return (delim, skipinitialspace)
def has_header(self, sample):
# Creates a dictionary of types of data in each column. If any
# column is of a single type (say, integers), *except* for the first
# row, then the first row is presumed to be labels. If the type
# can't be determined, it is assumed to be a string in which case
# the length of the string is the determining factor: if all of the
# rows except for the first are the same length, it's a header.
# Finally, a 'vote' is taken at the end for each column, adding or
# subtracting from the likelihood of the first row being a header.
def seval(item):
"""
Strips parens from item prior to calling eval in an
attempt to make it safer
"""
return eval(item.replace('(', '').replace(')', ''))
rdr = reader(StringIO(sample), self.sniff(sample))
header = rdr.next() # assume first row is header
columns = len(header)
columnTypes = {}
for i in range(columns): columnTypes[i] = None
checked = 0
for row in rdr:
# arbitrary number of rows to check, to keep it sane
if checked > 20:
break
checked += 1
if len(row) != columns:
continue # skip rows that have irregular number of columns
for col in columnTypes.keys():
try:
try:
# is it a built-in type (besides string)?
thisType = type(seval(row[col]))
except OverflowError:
# a long int?
thisType = type(seval(row[col] + 'L'))
thisType = type(0) # treat long ints as int
except:
# fallback to length of string
thisType = len(row[col])
if thisType != columnTypes[col]:
if columnTypes[col] is None: # add new column type
columnTypes[col] = thisType
else:
# type is inconsistent, remove column from
# consideration
del columnTypes[col]
# finally, compare results against first row and "vote"
# on whether it's a header
hasHeader = 0
for col, colType in columnTypes.items():
if type(colType) == type(0): # it's a length
if len(header[col]) != colType:
hasHeader += 1
else:
hasHeader -= 1
else: # attempt typecast
try:
eval("%s(%s)" % (colType.__name__, header[col]))
except:
hasHeader += 1
else:
hasHeader -= 1
return hasHeader > 0