    """
    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.

    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 string, sys
    from CSVParser import CSVParser
    from string import join, replace, split, strip
    from types import *
    from MiscUtils import NoDefault
    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,
    }

    ## 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 '<TableColumn %s with %s at %x>' % (
                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:
                raise DataTableError, 'Unknown column type "%s"' % self._type
            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='string', usePickleCache=None):
            if usePickleCache is None:
                self.usePickleCache = self.usePickleCache  # grab the class-level attr
            else:
                self.usePickleCache = usePickleCache
            if 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:
                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):
            haveReadHeadings = 0
            parse = CSVParser(fieldSep=delimiter, allowComments=allowComments, stripWhitespace=stripWhite).parse
            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)
                        self.createNameToIndexMap()
                        haveReadHeadings = 1
            if values is None:
                raise DataTableError, "Unfinished multiline record."
            return self

        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 type(headings[0]) is StringType:
                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: '',
    }

    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 type(key) is StringType:
                key = self._nameToIndexMap[key]
            return self._values[key]

        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()