Module backtrader.feeds.csvgeneric

Classes

class GenericCSV

Expand source code

class GenericCSV(feed.CSVFeedBase):
    DataCls = GenericCSVData

Ancestors

• CSVFeedBase
• FeedBase

Class variables

var DataCls

Parses a CSV file according to the order and field presence defined by the parameters

Specific parameters (or specific meaning):

• dataname: The filename to parse or a file-like object

• The lines parameters (datetime, open, high …) take numeric values

  A value of -1 indicates absence of that field in the CSV source

• If time is present (parameter time >=0) the source contains separated fields for date and time, which will be combined

• nullvalue

  Value that will be used if a value which should be there is missing (the CSV field is empty)

• dtformat: Format used to parse the datetime CSV field. See the python strptime/strftime documentation for the format.

  If a numeric value is specified, it will be interpreted as follows

  • 1: The value is a Unix timestamp of type int representing the number of seconds since Jan 1st, 1970

  • 2: The value is a Unix timestamp of type float

  If a callable is passed

  • it will accept a string and return a datetime.datetime python instance

• tmformat: Format used to parse the time CSV field if "present" (the default for the "time" CSV field is not to be present)

var frompackages

var packages

var params

class GenericCSVData (*args, **kwargs)

Parses a CSV file according to the order and field presence defined by the parameters

Specific parameters (or specific meaning):

• dataname: The filename to parse or a file-like object

• The lines parameters (datetime, open, high …) take numeric values

  A value of -1 indicates absence of that field in the CSV source

• If time is present (parameter time >=0) the source contains separated fields for date and time, which will be combined

• nullvalue

  Value that will be used if a value which should be there is missing (the CSV field is empty)

• dtformat: Format used to parse the datetime CSV field. See the python strptime/strftime documentation for the format.

  If a numeric value is specified, it will be interpreted as follows

  • 1: The value is a Unix timestamp of type int representing the number of seconds since Jan 1st, 1970

  • 2: The value is a Unix timestamp of type float

  If a callable is passed

  • it will accept a string and return a datetime.datetime python instance

• tmformat: Format used to parse the time CSV field if "present" (the default for the "time" CSV field is not to be present)

Expand source code

class GenericCSVData(feed.CSVDataBase):
    '''Parses a CSV file according to the order and field presence defined by the
    parameters

    Specific parameters (or specific meaning):

      - ``dataname``: The filename to parse or a file-like object

      - The lines parameters (datetime, open, high ...) take numeric values

        A value of -1 indicates absence of that field in the CSV source

      - If ``time`` is present (parameter time >=0) the source contains
        separated fields for date and time, which will be combined

      - ``nullvalue``

        Value that will be used if a value which should be there is missing
        (the CSV field is empty)

      - ``dtformat``: Format used to parse the datetime CSV field. See the
        python strptime/strftime documentation for the format.

        If a numeric value is specified, it will be interpreted as follows

          - ``1``: The value is a Unix timestamp of type ``int`` representing
            the number of seconds since Jan 1st, 1970

          - ``2``: The value is a Unix timestamp of type ``float``

        If a **callable** is passed

          - it will accept a string and return a `datetime.datetime` python
            instance

      - ``tmformat``: Format used to parse the time CSV field if "present"
        (the default for the "time" CSV field is not to be present)

    '''

    params = (
        ('nullvalue', float('NaN')),
        ('dtformat', '%Y-%m-%d %H:%M:%S'),
        ('tmformat', '%H:%M:%S'),

        ('datetime', 0),
        ('time', -1),
        ('open', 1),
        ('high', 2),
        ('low', 3),
        ('close', 4),
        ('volume', 5),
        ('openinterest', 6),
    )

    def start(self):
        super(GenericCSVData, self).start()

        self._dtstr = False
        if isinstance(self.p.dtformat, string_types):
            self._dtstr = True
        elif isinstance(self.p.dtformat, integer_types):
            idt = int(self.p.dtformat)
            if idt == 1:
                self._dtconvert = lambda x: datetime.utcfromtimestamp(int(x))
            elif idt == 2:
                self._dtconvert = lambda x: datetime.utcfromtimestamp(float(x))

        else:  # assume callable
            self._dtconvert = self.p.dtformat

    def _loadline(self, linetokens):
        # Datetime needs special treatment
        dtfield = linetokens[self.p.datetime]
        if self._dtstr:
            dtformat = self.p.dtformat

            if self.p.time >= 0:
                # add time value and format if it's in a separate field
                dtfield += 'T' + linetokens[self.p.time]
                dtformat += 'T' + self.p.tmformat

            dt = datetime.strptime(dtfield, dtformat)
        else:
            dt = self._dtconvert(dtfield)

        if self.p.timeframe >= TimeFrame.Days:
            # check if the expected end of session is larger than parsed
            if self._tzinput:
                dtin = self._tzinput.localize(dt)  # pytz compatible-ized
            else:
                dtin = dt

            dtnum = date2num(dtin)  # utc'ize

            dteos = datetime.combine(dt.date(), self.p.sessionend)
            dteosnum = self.date2num(dteos)  # utc'ize

            if dteosnum > dtnum:
                self.lines.datetime[0] = dteosnum
            else:
                # Avoid reconversion if already converted dtin == dt
                self.l.datetime[0] = date2num(dt) if self._tzinput else dtnum
        else:
            self.lines.datetime[0] = date2num(dt)

        # The rest of the fields can be done with the same procedure
        for linefield in (x for x in self.getlinealiases() if x != 'datetime'):
            # Get the index created from the passed params
            csvidx = getattr(self.params, linefield)

            if csvidx is None or csvidx < 0:
                # the field will not be present, assignt the "nullvalue"
                csvfield = self.p.nullvalue
            else:
                # get it from the token
                csvfield = linetokens[csvidx]

            if csvfield == '':
                # if empty ... assign the "nullvalue"
                csvfield = self.p.nullvalue

            # get the corresponding line reference and set the value
            line = getattr(self.lines, linefield)
            line[0] = float(float(csvfield))

        return True

Ancestors

• CSVDataBase
• DataBase
• AbstractDataBase
• OHLCDateTime
• OHLC
• DataSeries
• LineSeries
• LineMultiple
• LineRoot

Subclasses

• MT4CSVData
• SierraChartCSVData

Class variables

var alias

var aliased

var frompackages

var linealias

var packages

var params

var plotinfo

var plotlines

Methods

def start(self)

Expand source code

def start(self):
    super(GenericCSVData, self).start()

    self._dtstr = False
    if isinstance(self.p.dtformat, string_types):
        self._dtstr = True
    elif isinstance(self.p.dtformat, integer_types):
        idt = int(self.p.dtformat)
        if idt == 1:
            self._dtconvert = lambda x: datetime.utcfromtimestamp(int(x))
        elif idt == 2:
            self._dtconvert = lambda x: datetime.utcfromtimestamp(float(x))

    else:  # assume callable
        self._dtconvert = self.p.dtformat

Inherited members

• CSVDataBase:
  • addminperiod
  • compensate
  • get_notifications
  • incminperiod
  • islive
  • lines
  • minbuffer
  • next
  • nextstart
  • once
  • oncestart
  • prenext
  • preonce
  • put_notification
  • qbuffer
  • setenvironment
  • setminperiod
  • updateminperiod