def get_data_portal(exchange_names):
        open_calendar = get_calendar('OPEN')
        asset_finder = ExchangeAssetFinder()

        data_portal = DataPortalExchangeBacktest(
            exchange_names=exchange_names,
            asset_finder=asset_finder,
            trading_calendar=open_calendar,
            first_trading_day=None  # will set dynamically based on assets
        )
        return data_portal
예제 #2
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    def setup(self):
        log.info('creating bitfinex exchange')
        exchanges = get_exchanges(['bitfinex', 'bittrex', 'poloniex'])
        open_calendar = get_calendar('OPEN')
        asset_finder = ExchangeAssetFinder()

        self.data_portal_live = DataPortalExchangeLive(
            exchanges=exchanges,
            asset_finder=asset_finder,
            trading_calendar=open_calendar,
            first_trading_day=pd.to_datetime('today', utc=True))

        self.data_portal_backtest = DataPortalExchangeBacktest(
            exchanges=exchanges,
            asset_finder=asset_finder,
            trading_calendar=open_calendar,
            first_trading_day=None  # will set dynamically based on assets
        )
예제 #3
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def _run(handle_data,
         initialize,
         before_trading_start,
         analyze,
         algofile,
         algotext,
         defines,
         data_frequency,
         capital_base,
         data,
         bundle,
         bundle_timestamp,
         start,
         end,
         output,
         print_algo,
         local_namespace,
         environ,
         live,
         exchange,
         algo_namespace,
         quote_currency,
         live_graph,
         analyze_live,
         simulate_orders,
         auth_aliases,
         stats_output):
    """Run a backtest for the given algorithm.

    This is shared between the cli and :func:`catalyst.run_algo`.
    """
    # TODO: refactor for more granularity
    if algotext is not None:
        if local_namespace:
            ip = get_ipython()  # noqa
            namespace = ip.user_ns
        else:
            namespace = {}

        for assign in defines:
            try:
                name, value = assign.split('=', 2)
            except ValueError:
                raise ValueError(
                    'invalid define %r, should be of the form name=value' %
                    assign,
                )
            try:
                # evaluate in the same namespace so names may refer to
                # eachother
                namespace[name] = eval(value, namespace)
            except Exception as e:
                raise ValueError(
                    'failed to execute definition for name %r: %s' % (name, e),
                )
    elif defines:
        raise _RunAlgoError(
            'cannot pass define without `algotext`',
            "cannot pass '-D' / '--define' without '-t' / '--algotext'",
        )
    else:
        namespace = {}
        if algofile is not None:
            algotext = algofile.read()

    if print_algo:
        if PYGMENTS:
            highlight(
                algotext,
                PythonLexer(),
                TerminalFormatter(),
                outfile=sys.stdout,
            )
        else:
            click.echo(algotext)

    log.info('Catalyst version {}'.format(catalyst.__version__))
    if not DISABLE_ALPHA_WARNING:
        log.warn(ALPHA_WARNING_MESSAGE)
        # sleep(3)

    if live:
        if simulate_orders:
            mode = 'paper-trading'
        else:
            mode = 'live-trading'
    else:
        mode = 'backtest'

    log.info('running algo in {mode} mode'.format(mode=mode))

    exchange_name = exchange
    if exchange_name is None:
        raise ValueError('Please specify at least one exchange.')

    if isinstance(auth_aliases, string_types):
        aliases = auth_aliases.split(',')
        if len(aliases) < 2 or len(aliases) % 2 != 0:
            raise ValueError(
                'the `auth_aliases` parameter must contain an even list '
                'of comma-delimited values. For example, '
                '"binance,auth2" or "binance,auth2,bittrex,auth2".'
            )

        auth_aliases = dict(zip(aliases[::2], aliases[1::2]))

    exchange_list = [x.strip().lower() for x in exchange.split(',')]
    exchanges = dict()
    for name in exchange_list:
        if auth_aliases is not None and name in auth_aliases:
            auth_alias = auth_aliases[name]
        else:
            auth_alias = None

        exchanges[name] = get_exchange(
            exchange_name=name,
            quote_currency=quote_currency,
            must_authenticate=(live and not simulate_orders),
            skip_init=True,
            auth_alias=auth_alias,
        )

    open_calendar = get_calendar('OPEN')

    env = TradingEnvironment(
        load=partial(
            load_crypto_market_data,
            environ=environ,
            start_dt=start,
            end_dt=end
        ),
        environ=environ,
        exchange_tz='UTC',
        asset_db_path=None  # We don't need an asset db, we have exchanges
    )
    env.asset_finder = ExchangeAssetFinder(exchanges=exchanges)

    def choose_loader(column):
        bound_cols = TradingPairPricing.columns
        if column in bound_cols:
            return ExchangePricingLoader(data_frequency)
        raise ValueError(
            "No PipelineLoader registered for column %s." % column
        )

    if live:
        # TODO: fix the start data.
        # is_start checks if a start date was specified by user
        # needed for live clock
        is_start = True

        if start is None:
            start = pd.Timestamp.utcnow()
            is_start = False
        elif start:
            assert pd.Timestamp.utcnow() <= start, \
                "specified start date is in the past."
        elif start and end:
            assert start < end, "start date is later than end date."

        # TODO: fix the end data.
        # is_end checks if an end date was specified by user
        # needed for live clock
        is_end = True

        if end is None:
            end = start + timedelta(hours=8760)
            is_end = False

        data = DataPortalExchangeLive(
            exchanges=exchanges,
            asset_finder=env.asset_finder,
            trading_calendar=open_calendar,
            first_trading_day=pd.to_datetime('today', utc=True)
        )

        sim_params = create_simulation_parameters(
            start=start,
            end=end,
            capital_base=capital_base,
            emission_rate='minute',
            data_frequency='minute'
        )

        # TODO: use the constructor instead
        sim_params._arena = 'live'

        algorithm_class = partial(
            ExchangeTradingAlgorithmLive,
            exchanges=exchanges,
            algo_namespace=algo_namespace,
            live_graph=live_graph,
            simulate_orders=simulate_orders,
            stats_output=stats_output,
            analyze_live=analyze_live,
            start=start,
            is_start=is_start,
            end=end,
            is_end=is_end,
        )
    elif exchanges:
        # Removed the existing Poloniex fork to keep things simple
        # We can add back the complexity if required.

        # I don't think that we should have arbitrary price data bundles
        # Instead, we should center this data around exchanges.
        # We still need to support bundles for other misc data, but we
        # can handle this later.

        if (start and start != pd.tslib.normalize_date(start)) or \
                (end and end != pd.tslib.normalize_date(end)):
            # todo: add to Sim_Params the option to
            # start & end at specific times
            log.warn(
                "Catalyst currently starts and ends on the start and "
                "end of the dates specified, respectively. We hope to "
                "Modify this and support specific times in a future release."
            )

        data = DataPortalExchangeBacktest(
            exchange_names=[ex_name for ex_name in exchanges],
            asset_finder=None,
            trading_calendar=open_calendar,
            first_trading_day=start,
            last_available_session=end
        )

        sim_params = create_simulation_parameters(
            start=start,
            end=end,
            capital_base=capital_base,
            data_frequency=data_frequency,
            emission_rate=data_frequency,
        )

        algorithm_class = partial(
            ExchangeTradingAlgorithmBacktest,
            exchanges=exchanges
        )

    elif bundle is not None:
        bundle_data = load(
            bundle,
            environ,
            bundle_timestamp,
        )

        prefix, connstr = re.split(
            r'sqlite:///',
            str(bundle_data.asset_finder.engine.url),
            maxsplit=1,
        )
        if prefix:
            raise ValueError(
                "invalid url %r, must begin with 'sqlite:///'" %
                str(bundle_data.asset_finder.engine.url),
            )

        env = TradingEnvironment(asset_db_path=connstr, environ=environ)
        first_trading_day = \
            bundle_data.equity_minute_bar_reader.first_trading_day

        data = DataPortal(
            env.asset_finder, open_calendar,
            first_trading_day=first_trading_day,
            equity_minute_reader=bundle_data.equity_minute_bar_reader,
            equity_daily_reader=bundle_data.equity_daily_bar_reader,
            adjustment_reader=bundle_data.adjustment_reader,
        )

    perf = algorithm_class(
        namespace=namespace,
        env=env,
        get_pipeline_loader=choose_loader,
        sim_params=sim_params,
        **{
            'initialize': initialize,
            'handle_data': handle_data,
            'before_trading_start': before_trading_start,
            'analyze': analyze,
        } if algotext is None else {
            'algo_filename': getattr(algofile, 'name', '<algorithm>'),
            'script': algotext,
        }
    ).run(
        data,
        overwrite_sim_params=False,
    )

    if output == '-':
        click.echo(str(perf))
    elif output != os.devnull:  # make the catalyst magic not write any data
        perf.to_pickle(output)

    return perf
예제 #4
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def _build_algo_and_data(handle_data, initialize, before_trading_start,
                         analyze, algofile, algotext, defines, data_frequency,
                         capital_base, data, bundle, bundle_timestamp, start,
                         end, output, print_algo, local_namespace, environ,
                         live, exchange, algo_namespace, base_currency,
                         live_graph, analyze_live, simulate_orders,
                         stats_output):
    namespace = _build_namespace(algotext, local_namespace, defines)
    if algotext is not None:
        algotext = algofile.read()

    if print_algo:
        _pretty_print_code(algotext)

    mode = _mode(simulate_orders, live)
    log.info('running algo in {mode} mode'.format(mode=mode))

    exchanges = _build_exchanges_dict(exchange, live, simulate_orders,
                                      base_currency)

    open_calendar = get_calendar('OPEN')

    env = TradingEnvironment(
        load=partial(load_crypto_market_data,
                     environ=environ,
                     start_dt=start,
                     end_dt=end),
        environ=environ,
        exchange_tz='UTC',
        asset_db_path=None)  # We don't need an asset db, we have exchanges

    env.asset_finder = ExchangeAssetFinder(exchanges=exchanges)

    choose_loader = partial(_choose_loader, data_frequency)

    if live:
        start, end = _get_live_time_range()
        data_frequency = 'minute'  # TODO double check if this is the desired behavior

    sim_params = create_simulation_parameters(start=start,
                                              end=end,
                                              capital_base=capital_base,
                                              emission_rate=data_frequency,
                                              data_frequency=data_frequency)

    if algotext is None:
        algorithm_class_kwargs = {
            'initialize': initialize,
            'handle_data': handle_data,
            'before_trading_start': before_trading_start,
            'analyze': analyze
        }
    else:
        algorithm_class_kwargs = {
            'algo_filename': getattr(algofile, 'name', '<algorithm>'),
            'script': algotext
        }

    if live:
        return _build_live_algo_and_data(
            sim_params, exchanges, env, open_calendar, simulate_orders,
            algo_namespace, capital_base, live_graph, stats_output,
            analyze_live, base_currency, namespace, choose_loader,
            algorithm_class_kwargs)
    else:
        return _build_backtest_algo_and_data(exchanges, bundle, env, environ,
                                             bundle_timestamp, open_calendar,
                                             start, end, namespace,
                                             choose_loader, sim_params,
                                             algorithm_class_kwargs)
예제 #5
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def _run(handle_data, initialize, before_trading_start, analyze, algofile,
         algotext, defines, data_frequency, capital_base, data, bundle,
         bundle_timestamp, start, end, output, print_algo, local_namespace,
         environ, live, exchange, algo_namespace, base_currency, live_graph,
         analyze_live, simulate_orders, stats_output):
    """Run a backtest for the given algorithm.

    This is shared between the cli and :func:`catalyst.run_algo`.
    """
    if algotext is not None:
        if local_namespace:
            ip = get_ipython()  # noqa
            namespace = ip.user_ns
        else:
            namespace = {}

        for assign in defines:
            try:
                name, value = assign.split('=', 2)
            except ValueError:
                raise ValueError(
                    'invalid define %r, should be of the form name=value' %
                    assign, )
            try:
                # evaluate in the same namespace so names may refer to
                # eachother
                namespace[name] = eval(value, namespace)
            except Exception as e:
                raise ValueError(
                    'failed to execute definition for name %r: %s' %
                    (name, e), )
    elif defines:
        raise _RunAlgoError(
            'cannot pass define without `algotext`',
            "cannot pass '-D' / '--define' without '-t' / '--algotext'",
        )
    else:
        namespace = {}
        if algofile is not None:
            algotext = algofile.read()

    if print_algo:
        if PYGMENTS:
            highlight(
                algotext,
                PythonLexer(),
                TerminalFormatter(),
                outfile=sys.stdout,
            )
        else:
            click.echo(algotext)

    mode = 'paper-trading' if simulate_orders else 'live-trading' \
        if live else 'backtest'
    log.info('running algo in {mode} mode'.format(mode=mode))

    exchange_name = exchange
    if exchange_name is None:
        raise ValueError('Please specify at least one exchange.')

    exchange_list = [x.strip().lower() for x in exchange.split(',')]

    exchanges = dict()
    for exchange_name in exchange_list:
        exchanges[exchange_name] = get_exchange(
            exchange_name=exchange_name,
            base_currency=base_currency,
            must_authenticate=(live and not simulate_orders),
            skip_init=True,
        )

    open_calendar = get_calendar('OPEN')

    env = TradingEnvironment(
        load=partial(load_crypto_market_data,
                     environ=environ,
                     start_dt=start,
                     end_dt=end),
        environ=environ,
        exchange_tz='UTC',
        asset_db_path=None  # We don't need an asset db, we have exchanges
    )
    env.asset_finder = ExchangeAssetFinder(exchanges=exchanges)

    def choose_loader(column):
        bound_cols = TradingPairPricing.columns
        if column in bound_cols:
            return ExchangePricingLoader(data_frequency)
        raise ValueError("No PipelineLoader registered for column %s." %
                         column)

    if live:
        start = pd.Timestamp.utcnow()

        # TODO: fix the end data.
        end = start + timedelta(hours=8760)

        data = DataPortalExchangeLive(exchanges=exchanges,
                                      asset_finder=env.asset_finder,
                                      trading_calendar=open_calendar,
                                      first_trading_day=pd.to_datetime(
                                          'today', utc=True))

        def fetch_capital_base(exchange, attempt_index=0):
            """
            Fetch the base currency amount required to bootstrap
            the algorithm against the exchange.

            The algorithm cannot continue without this value.

            :param exchange: the targeted exchange
            :param attempt_index:
            :return capital_base: the amount of base currency available for
            trading
            """
            try:
                log.debug('retrieving capital base in {} to bootstrap '
                          'exchange {}'.format(base_currency, exchange_name))
                balances = exchange.get_balances()
            except ExchangeRequestError as e:
                if attempt_index < 20:
                    log.warn('could not retrieve balances on {}: {}'.format(
                        exchange.name, e))
                    sleep(5)
                    return fetch_capital_base(exchange, attempt_index + 1)

                else:
                    raise ExchangeRequestErrorTooManyAttempts(
                        attempts=attempt_index, error=e)

            if base_currency in balances:
                base_currency_available = balances[base_currency]['free']
                log.info(
                    'base currency available in the account: {} {}'.format(
                        base_currency_available, base_currency))

                return base_currency_available
            else:
                raise BaseCurrencyNotFoundError(base_currency=base_currency,
                                                exchange=exchange_name)

        if not simulate_orders:
            for exchange_name in exchanges:
                exchange = exchanges[exchange_name]
                balance = fetch_capital_base(exchange)

                if balance < capital_base:
                    raise NotEnoughCapitalError(
                        exchange=exchange_name,
                        base_currency=base_currency,
                        balance=balance,
                        capital_base=capital_base,
                    )

        sim_params = create_simulation_parameters(start=start,
                                                  end=end,
                                                  capital_base=capital_base,
                                                  emission_rate='minute',
                                                  data_frequency='minute')

        # TODO: use the constructor instead
        sim_params._arena = 'live'

        algorithm_class = partial(
            ExchangeTradingAlgorithmLive,
            exchanges=exchanges,
            algo_namespace=algo_namespace,
            live_graph=live_graph,
            simulate_orders=simulate_orders,
            stats_output=stats_output,
            analyze_live=analyze_live,
        )
    elif exchanges:
        # Removed the existing Poloniex fork to keep things simple
        # We can add back the complexity if required.

        # I don't think that we should have arbitrary price data bundles
        # Instead, we should center this data around exchanges.
        # We still need to support bundles for other misc data, but we
        # can handle this later.

        data = DataPortalExchangeBacktest(
            exchange_names=[exchange_name for exchange_name in exchanges],
            asset_finder=None,
            trading_calendar=open_calendar,
            first_trading_day=start,
            last_available_session=end)

        sim_params = create_simulation_parameters(
            start=start,
            end=end,
            capital_base=capital_base,
            data_frequency=data_frequency,
            emission_rate=data_frequency,
        )

        algorithm_class = partial(ExchangeTradingAlgorithmBacktest,
                                  exchanges=exchanges)

    elif bundle is not None:
        bundle_data = load(
            bundle,
            environ,
            bundle_timestamp,
        )

        prefix, connstr = re.split(
            r'sqlite:///',
            str(bundle_data.asset_finder.engine.url),
            maxsplit=1,
        )
        if prefix:
            raise ValueError(
                "invalid url %r, must begin with 'sqlite:///'" %
                str(bundle_data.asset_finder.engine.url), )

        env = TradingEnvironment(asset_db_path=connstr, environ=environ)
        first_trading_day = \
            bundle_data.equity_minute_bar_reader.first_trading_day

        data = DataPortal(
            env.asset_finder,
            open_calendar,
            first_trading_day=first_trading_day,
            equity_minute_reader=bundle_data.equity_minute_bar_reader,
            equity_daily_reader=bundle_data.equity_daily_bar_reader,
            adjustment_reader=bundle_data.adjustment_reader,
        )

    perf = algorithm_class(
        namespace=namespace,
        env=env,
        get_pipeline_loader=choose_loader,
        sim_params=sim_params,
        **{
            'initialize': initialize,
            'handle_data': handle_data,
            'before_trading_start': before_trading_start,
            'analyze': analyze,
        } if algotext is None else {
            'algo_filename': getattr(algofile, 'name', '<algorithm>'),
            'script': algotext,
        }).run(
            data,
            overwrite_sim_params=False,
        )

    if output == '-':
        click.echo(str(perf))
    elif output != os.devnull:  # make the catalyst magic not write any data
        perf.to_pickle(output)

    return perf