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Diffstat (limited to 'paste/webkit/FakeWebware/MiscUtils/DataTable.py')
| -rw-r--r-- | paste/webkit/FakeWebware/MiscUtils/DataTable.py | 804 |
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diff --git a/paste/webkit/FakeWebware/MiscUtils/DataTable.py b/paste/webkit/FakeWebware/MiscUtils/DataTable.py deleted file mode 100644 index 1c92522..0000000 --- a/paste/webkit/FakeWebware/MiscUtils/DataTable.py +++ /dev/null @@ -1,804 +0,0 @@ -""" -DataTable.py - - -INTRODUCTION - -This class is useful for representing a table of data arranged by named -columns, where each row in the table can be thought of as a record: - - name phoneNumber - ------ ----------- - Chuck 893-3498 - Bill 893-0439 - John 893-5901 - -This data often comes from delimited text files which typically -have well defined columns or fields with several rows each of which can -be thought of as a record. - -Using a DataTable can be as easy as using lists and dictionaries: - - table = DataTable('users.csv') - for row in table: - print row['name'], row['phoneNumber'] - -Or even: - - table = DataTable('users.csv') - for row in table: - print '%(name)s %(phoneNumber)s' % row - -The above print statement relies on the fact that rows can be treated -like dictionaries, using the column headings as keys. - -You can also treat a row like an array: - - table = DataTable('something.tabbed', delimiter='\t') - for row in table: - for item in row: - print item, - print - - -COLUMNS - -Column headings can have a type specification like so: - name, age:int, zip:int - -Possible types include string, int, float and datetime. However, -datetime is not well supported right now. - -String is assumed if no type is specified but you can set that -assumption when you create the table: - - table = DataTable(headings, defaultType='float') - -Using types like int and float will cause DataTable to actually -convert the string values (perhaps read from a file) to these types -so that you can use them in natural operations. For example: - - if row['age']>120: - self.flagData(row, 'age looks high') - -As you can see, each row can be accessed as a dictionary with keys -according the column headings. Names are case sensitive. - - -ADDING ROWS - -Like Python lists, data tables have an append() method. You can append -TableRecords, or you pass a dictionary, list or object, in which case a -TableRecord is created based on given values. See the method docs below -for more details. - - -FILES - -By default, the files that DataTable reads from are expected to be -comma-separated value files. - -Limited comments are supported: A comment is any line whose very first -character is a #. This allows you to easily comment out lines in your -data files without having to remove them. - -Whitespace around field values is stripped. - -You can control all this behavior through the arguments found in the -initializer and the various readFoo() methods: - - ...delimiter=',', allowComments=1, stripWhite=1 - -For example: - - table = DataTable('foo.tabbed', delimiter='\t', allowComments=0, stripWhite=0) - -You should access these parameters by their name since additional ones -could appear in the future, thereby changing the order. - -If you are creating these text files, we recommend the -comma-separated-value format, or CSV. This format is better defined -than the tab delimited format, and can easily be edited and manipulated -by popular spreadsheets and databases. - - -MICROSOFT EXCEL - -On Microsoft Windows systems with Excel and the win32all package -(http://starship.python.net/crew/mhammond/), DataTable will use Excel -(via COM) to read ".xls" files. - -from MiscUtils import DataTable -assert DataTable.canReadExcel() -table = DataTable.DataTable('foo.xls') - -With consistency to its CSV processing, DataTable will ignore any row -whose first cell is '#' and strip surrounding whitespace around strings. - - -TABLES FROM SCRATCH - -Here's an example that constructs a table from scratch: - - table = DataTable(['name', 'age:int']) - table.append(['John', 80]) - table.append({'name': 'John', 'age': 80}) - print table - - -QUERIES - -A simple query mechanism is supported for equality of fields: - - matches = table.recordsEqualTo({'uid': 5}) - if matches: - for match in matches: - print match - else: - print 'No matches.' - - -COMMON USES - -* Programs can keep configuration and other data in simple comma- -separated text files and use DataTable to access them. For example, a -web site could read it's sidebar links from such a file, thereby -allowing people who don't know Python (or even HTML) to edit these -links without having to understand other implementation parts of the -site. - -* Servers can use DataTable to read and write log files. - - -FROM THE COMMAND LINE - -The only purpose in invoking DataTable from the command line is to see -if it will read a file: - -> python DataTable.py foo.csv - -The data table is printed to stdout. - - -CACHING - -DataTable uses "pickle caching" so that it can read .csv files faster -on subsequent loads. You can disable this across the board with: - from MiscUtils.DataTable import DataTable - DataTable.usePickleCache = 0 - -Or per instance by passing "usePickleCache=0" to the constructor. - -See the docstring of PickleCache.py for more information. - - -MORE DOCS - -Some of the methods in this module have worthwhile doc strings to look -at. See below. - - -TO DO - -* Allow callback parameter or setting for parsing CSV records. -* Perhaps TableRecord should inherit UserList and UserDict and override methods as appropriate...? -* Better support for datetime. -* _types and BlankValues aren't really packaged, advertised or - documented for customization by the user of this module. -* DataTable: - * Parameterize the TextColumn class. - * Parameterize the TableRecord class. - * More list-like methods such as insert() - * writeFileNamed() is flawed: it doesn't write the table column - type - * Should it inherit from UserList? -* Add error checking that a column name is not a number (which could - cause problems). -* Look for various @@ tags through out the code. - -""" - - -import os, string, sys -from CSVParser import CSVParser -from string import join, replace, split, strip -from types import * - -try: - StringTypes -except NameError: - StringTypes = StringType - -try: - from MiscUtils import NoDefault -except ImportError: - class NoDefault: - pass - -try: - from mx.DateTime import DateTimeType, DateTimeFrom -except ImportError: - pass - - -## Types ## - -DateTimeType = "<custom-type 'datetime'>" -ObjectType = "<type 'Object'>" - -_types = { - 'string': StringType, - 'int': IntType, - 'long': LongType, - 'float': FloatType, - 'datetime': DateTimeType, - 'object': ObjectType, -} - - -## Functions ## - -def canReadExcel(): - try: - from win32com.client import Dispatch - Dispatch("Excel.Application") - except: - return False - else: - return True - - -## Classes ## - - -class DataTableError(Exception): - pass - - -class TableColumn: - """ - A table column represents a column of the table including name and - type. - - It does not contain the actual values of the column. These are - stored individually in the rows. - """ - - def __init__(self, spec): - - # spec is a string such as 'name' or 'name:type' - fields = split(spec, ':') - if len(fields)>2: - raise DataTableError, 'Invalid column spec %s' % repr(spec) - self._name = fields[0] - - if len(fields)==1: - self._type = None - else: - self.setType(fields[1]) - - def name(self): - return self._name - - def type(self): - return self._type - - def setType(self, type): - """ Sets the type (by a string containing the name) of the heading. Usually invoked by DataTable to set the default type for columns whose types were not specified. """ - if type==None: - self._type = None - else: - try: - self._type = _types[type] - except: - raise DataTableError, 'Unknown type %s' % repr(type) - - def __repr__(self): - return '<%s %s with %s at %x>' % ( - self.__class__.__name__, repr(self._name), repr(self._type), id(self)) - - def __str__(self): - return self._name - - - ## Utilities ## - - def valueForRawValue(self, rawValue): - """ The rawValue is typically a string or value already of the appropriate type. TableRecord invokes this method to ensure that values (especially strings that come from files) are the correct types (e.g., ints are ints and floats are floats). """ - # @@ 2000-07-23 ce: an if-else ladder? perhaps these should be dispatched messages or a class hier - if self._type is StringType: - value = str(rawValue) - elif self._type is IntType: - if rawValue=='': - value = 0 - else: - value = int(rawValue) - elif self._type is LongType: - if rawValue=='': - value = 0 - else: - value = long(rawValue) - elif self._type is FloatType: - if rawValue=='': - value = 0.0 - else: - value = float(rawValue) - elif self._type is DateTimeType: - value = DateTimeFrom(rawValue) - elif self._type is ObjectType: - value = rawValue - else: - # no type set, leave values as they are - value = rawValue - return value - - -class DataTable: - """ - See the doc string for this module. - """ - - usePickleCache = 1 - - - ## Init ## - - def __init__(self, filenameOrHeadings=None, delimiter=',', allowComments=1, stripWhite=1, defaultType=None, usePickleCache=None): - if usePickleCache is None: - self.usePickleCache = self.usePickleCache # grab the class-level attr - else: - self.usePickleCache = usePickleCache - if defaultType and not _types.has_key(defaultType): - raise DataTableError, 'Unknown type for default type: %s' % repr(defaultType) - self._defaultType = defaultType - self._filename = None - self._headings = [] - self._rows = [] - if filenameOrHeadings: - if type(filenameOrHeadings) is StringType: - self.readFileNamed(filenameOrHeadings, delimiter, allowComments, stripWhite) - else: - self.setHeadings(filenameOrHeadings) - - - ## File I/O ## - - def readFileNamed(self, filename, delimiter=',', allowComments=1, stripWhite=1): - self._filename = filename - data = None - if self.usePickleCache: - from PickleCache import readPickleCache, writePickleCache - data = readPickleCache(filename, pickleVersion=1, source='MiscUtils.DataTable') - if data is None: - if self._filename.endswith('.xls'): - self.readExcel() - else: - file = open(self._filename, 'r') - self.readFile(file, delimiter, allowComments, stripWhite) - file.close() - if self.usePickleCache: - writePickleCache(self, filename, pickleVersion=1, source='MiscUtils.DataTable') - else: - self.__dict__ = data.__dict__ - return self - - def readFile(self, file, delimiter=',', allowComments=1, stripWhite=1): - return self.readLines(file.readlines(), delimiter, allowComments, stripWhite) - - def readString(self, string, delimiter=',', allowComments=1, stripWhite=1): - return self.readLines(split(string, '\n'), delimiter, allowComments, stripWhite) - - def readLines(self, lines, delimiter=',', allowComments=1, stripWhite=1): - if self._defaultType is None: - self._defaultType = 'string' - haveReadHeadings = 0 - parse = CSVParser(fieldSep=delimiter, allowComments=allowComments, stripWhitespace=stripWhite).parse - values = '' - for line in lines: - # process a row, either headings or data - values = parse(line) - if values: - if haveReadHeadings: - row = TableRecord(self, values) - self._rows.append(row) - else: - self.setHeadings(values) - haveReadHeadings = 1 - if values is None: - raise DataTableError, "Unfinished multiline record." - return self - - def canReadExcel(self): - return canReadExcel() - - def readExcel(self): - maxBlankRows = 10 - numRowsToReadPerCall = 20 - - from win32com.client import Dispatch - xl = Dispatch("Excel.Application") - wb = xl.Workbooks.Open(os.path.abspath(self._filename)) - try: - sh = wb.Worksheets(1) - sh.Cells(1, 1) - - # determine max column - numCols = 1 - while 1: - if sh.Cells(1, numCols).Value in [None, '']: - numCols -= 1 - break - numCols += 1 - if numCols<=0: - return - - def strip(x): - try: - return x.strip() - except: - return x - - # read rows of data - maxCol = chr(ord('A') + numCols - 1) - haveReadHeadings = 0 - rowNum = 1 - numBlankRows = 0 - valuesBuffer = {} # keyed by row number - while 1: - try: - # grab a single row - values = valuesBuffer[rowNum] - except KeyError: - # woops. read buffer is out of fresh rows - valuesRows = sh.Range('A%i:%s%i' % (rowNum, maxCol, rowNum+numRowsToReadPerCall-1)).Value - valuesBuffer.clear() - j = rowNum - for valuesRow in valuesRows: - valuesBuffer[j] = valuesRow - j += 1 - values = valuesBuffer[rowNum] - - # non-"buffered" version, one row at a time: - # values = sh.Range('A%i:%s%i' % (rowNum, maxCol, rowNum)).Value[0] - - values = [strip(v) for v in values] - nonEmpty = [v for v in values if v] - if nonEmpty: - if values[0] not in ('#', u'#'): - if haveReadHeadings: - row = TableRecord(self, values) - self._rows.append(row) - else: - self.setHeadings(values) - haveReadHeadings = 1 - numBlankRows = 0 - else: - numBlankRows += 1 - if numBlankRows>maxBlankRows: - # consider end of spreadsheet - break - rowNum += 1 - finally: - wb.Close() - - def save(self): - self.writeFileNamed(self._filename) - - def writeFileNamed(self, filename): - file = open(filename, 'w') - self.writeFile(file) - file.close() - - def writeFile(self, file): - """ - @@ 2000-07-20 ce: This doesn't write the column types (like :int) back out. - @@ 2000-07-21 ce: It's notable that a blank numeric value gets read as zero and written out that way. Also, values None are written as blanks. - """ - - # write headings - file.write(join(map(lambda h: str(h), self._headings), ',')) - file.write('\n') - - def ValueWritingMapper(item): - # So that None gets written as a blank and everything else as a string - if item is None: - return '' - else: - return str(item) - - # write rows - for row in self._rows: - file.write(join(map(ValueWritingMapper, row), ',')) - file.write('\n') - - def commit(self): - if self._changed: - self.save() - self._changed = 0 - - - ## Headings ## - - def heading(self, index): - if type(key) is StringType: - key = self._nameToIndexMap[key] - return self._headings[index] - - def hasHeading(self, name): - return self._nameToIndexMap.has_key(name) - - def numHeadings(self): - return len(self._headings) - - def headings(self): - return self._headings - - def setHeadings(self, headings): - """ Headings can be a list of strings (like ['name', 'age:int']) or a list of TableColumns or None. """ - if not headings: - self._headings = [] - elif isinstance(headings[0], StringTypes): - self._headings = map(lambda h: TableColumn(h), headings) - elif isinstance(headings[0], TableColumn): - self._headings = list(headings) - for heading in self._headings: - if heading.type() is None: - heading.setType(self._defaultType) - self.createNameToIndexMap() - - - ## Row access (list like) ## - - def __len__(self): - return len(self._rows) - - def __getitem__(self, index): - return self._rows[index] - - def append(self, object): - """ If object is not a TableRecord, then one is created, passing the object to initialize the TableRecord. Therefore, object can be a TableRecord, list, dictionary or object. See TableRecord for details. """ - - if not isinstance(object, TableRecord): - object = TableRecord(self, object) - self._rows.append(object) - self._changed = 1 - - - ## Queries ## - - def recordsEqualTo(self, dict): - records = [] - keys = dict.keys() - for record in self._rows: - matches = 1 - for key in keys: - if record[key]!=dict[key]: - matches = 0 - break - if matches: - records.append(record) - return records - - - ## As a string ## - - def __repr__(self): - # Initial info - s = ['DataTable: %s\n%d rows\n' % (self._filename, len(self._rows))] - - # Headings - s.append(' ') - s.append(join(map(lambda h: str(h), self._headings), ', ')) - s.append('\n') - - # Records - i = 0 - for row in self._rows: - s.append('%3d. ' % i) - s.append(join(map(lambda r: str(r), row), ', ')) - s.append('\n') - i = i + 1 - return join(s, '') - - - ## As a dictionary ## - - def dictKeyedBy(self, key): - """ Returns a dictionary containing the contents of the table indexed by the particular key. This is useful for tables that have a column which represents a unique key (such as a name, serial number, etc.). """ - dict = {} - for row in self: - dict[row[key]] = row - return dict - - - ## Misc access ## - - def filename(self): - return self._filename - - def nameToIndexMap(self): - """ Table rows keep a reference to this map in order to speed up index-by-names (as in row['name']). """ - return self._nameToIndexMap - - - ## Self utilities ## - - def createNameToIndexMap(self): - """ - Invoked by self to create the nameToIndexMap after the table's - headings have been read/initialized. - """ - map = {} - for i in range(len(self._headings)): - map[self._headings[i].name()] = i - self._nameToIndexMap = map - - -# @@ 2000-07-20 ce: perhaps for each type we could specify a function to convert from string values to the values of the type - -BlankValues = { - StringType: '', - IntType: 0, - FloatType: 0.0, - DateTimeType: '', - None: None, -} - - -class TableRecord: - - ## Init ## - - def __init__(self, table, values=None): - """ - Dispatches control to one of the other init methods based on the type of values. Values can be one of three things: - 1. A TableRecord - 2. A list - 3. A dictionary - 4. Any object responding to hasValueForKey() and valueForKey(). - """ - self._headings = table.headings() - self._nameToIndexMap = table.nameToIndexMap() - # @@ 2000-07-20 ce: Take out the headings arg to the init method since we have an attribute for that - - if values is not None: - valuesType = type(values) - if valuesType is ListType or valuesType is TupleType: - # @@ 2000-07-20 ce: check for required attributes instead - self.initFromSequence(values) - elif valuesType is DictType: - self.initFromDict(values) - elif valuesType is InstanceType: - self.initFromObject(value) - else: - raise DataTableError, 'Unknown type for values %s.' % valuesType - - def initFromSequence(self, values): - if len(self._headings)<len(values): - raise DataTableError, ('There are more values than headings.\nheadings(%d, %s)\nvalues(%d, %s)' % (len(self._headings), self._headings, len(values), values)) - self._values = [] - numHeadings = len(self._headings) - numValues = len(values) - assert numValues<=numHeadings - for i in range(numHeadings): - heading = self._headings[i] - if i>=numValues: - self._values.append(BlankValues[heading.type()]) - else: - self._values.append(heading.valueForRawValue(values[i])) - - def initFromDict(self, dict): - self._values = [] - for heading in self._headings: - name = heading.name() - if dict.has_key(name): - self._values.append(heading.valueForRawValue(dict[name])) - else: - self._values.append(BlankValues[heading.type()]) - - def initFromObject(self, object): - """ - The object is expected to response to hasValueForKey(name) and - valueForKey(name) for each of the headings in the table. It's - alright if the object returns 0 for hasValueForKey(). In that - case, a "blank" value is assumed (such as zero or an empty - string). If hasValueForKey() returns 1, then valueForKey() must - return a value. - """ - self._values = [] - for heading in self._headings: - name = heading.name() - if object.hasValueForKey(name): - self._values.append(heading.valueForRawValue(object.valueForKey(name))) - else: - self._values.append(BlankValues[heading.type()]) - - - ## Accessing like a sequence or dictionary ## - - def __len__(self): - return len(self._values) - - def __getitem__(self, key): - if isinstance(key, StringTypes): - key = self._nameToIndexMap[key] - try: - return self._values[key] - except TypeError: - raise TypeError, 'key=%r, key type=%r, self._values=%r' % (key, type(key), self._values) - - def __setitem__(self, key, value): - if type(key) is StringType: - key = self._nameToIndexMap[key] - self._values[key] = value - - def __repr__(self): - return '%s' % self._values - - def get(self, key, default=None): - index = self._nameToIndexMap.get(key, None) - if index is None: - return default - else: - return self._values[index] - - def has_key(self, key): - return self._nameToIndexMap.has_key(key) - - def keys(self): - return self._nameToIndexMap.keys() - - def values(self): - return self._values - - def items(self): - items = [] - for key in self.keys(): - items.append((key, self[key])) - return items - - - ## Additional access ## - - def asList(self): - """ - Returns a sequence whose values are the same at the record's - and in the order defined by the table. - """ - # It just so happens that our implementation already has this - return self._values[:] - - def asDict(self): - """ Returns a dictionary whose key-values match the table record. """ - dict = {} - nameToIndexMap = self._nameToIndexMap - for key in nameToIndexMap.keys(): - dict[key] = self._values[nameToIndexMap[key]] - return dict - - - ## valueForFoo() family ## - - def valueForKey(self, key, default=NoDefault): - if default is NoDefault: - return self[key] - else: - return self.get(key, default) - - def valueForAttr(self, attr, default=NoDefault): - return self.valueForKey(attr['Name'], default) - - - -def main(args=None): - if args is None: - args = sys.argv - for arg in args[1:]: - dt = DataTable(arg) - print '*** %s ***' % arg - print dt - print - - -if __name__=='__main__': - main() |