Merge branch 'develop' into no-ticker-2

config.json.example

@@ -23,7 +23,7 @@
     "ask_strategy":{
         "use_order_book": false,
         "order_book_min": 1,
-        "order_book_max": 9,
+        "order_book_max": 1,
         "use_sell_signal": true,
         "sell_profit_only": false,
         "ignore_roi_if_buy_signal": false

config_binance.json.example

@@ -23,7 +23,7 @@
     "ask_strategy":{
         "use_order_book": false,
         "order_book_min": 1,
-        "order_book_max": 9,
+        "order_book_max": 1,
         "use_sell_signal": true,
         "sell_profit_only": false,
         "ignore_roi_if_buy_signal": false

config_full.json.example

@@ -38,7 +38,7 @@
         "price_side": "ask",
         "use_order_book": false,
         "order_book_min": 1,
-        "order_book_max": 9,
+        "order_book_max": 1,
         "use_sell_signal": true,
         "sell_profit_only": false,
         "ignore_roi_if_buy_signal": false

config_kraken.json.example

@@ -23,7 +23,7 @@
     "ask_strategy":{
         "use_order_book": false,
         "order_book_min": 1,
-        "order_book_max": 9,
+        "order_book_max": 1,
         "use_sell_signal": true,
         "sell_profit_only": false,
         "ignore_roi_if_buy_signal": false

docs/configuration.md

@@ -536,8 +536,14 @@ The idea here is to place the sell order early, to be ahead in the queue.
 
 A fixed slot (mirroring `bid_strategy.order_book_top`) can be defined by setting `ask_strategy.order_book_min` and `ask_strategy.order_book_max` to the same number.
 
-!!! Warning "Orderbook and stoploss_on_exchange"
-    Using `ask_strategy.order_book_max` higher than 1 may increase the risk, since an eventual [stoploss on exchange](#understand-order_types) will be needed to be cancelled as soon as the order is placed.
+!!! Warning "Order_book_max > 1 - increased risks for stoplosses!"
+    Using `ask_strategy.order_book_max` higher than 1 will increase the risk the stoploss on exchange is cancelled too early, since an eventual [stoploss on exchange](#understand-order_types) will be cancelled as soon as the order is placed.
+    Also, the sell order will remain on the exchange for `unfilledtimeout.sell` (or until it's filled) - which can lead to missed stoplosses (with or without using stoploss on exchange).
+
+!!! Warning "Order_book_max > 1 in dry-run"
+    Using `ask_strategy.order_book_max` higher than 1 will result in improper dry-run results (significantly better than real orders executed on exchange), since dry-run assumes orders to be filled almost instantly.
+    It is therefore advised to not use this setting for dry-runs.
+
 
 #### Sell price without Orderbook enabled
 

docs/hyperopt.md

@@ -160,6 +160,9 @@ So let's write the buy strategy using these values:
                         dataframe['macd'], dataframe['macdsignal']
                     ))
 
+            # Check that volume is not 0
+            conditions.append(dataframe['volume'] > 0)
+
             if conditions:
                 dataframe.loc[
                     reduce(lambda x, y: x & y, conditions),

docs/utils.md

@@ -429,6 +429,7 @@ usage: freqtrade hyperopt-list [-h] [-v] [--logfile FILE] [-V] [-c PATH]
                                [--min-total-profit FLOAT]
                                [--max-total-profit FLOAT] [--no-color]
                                [--print-json] [--no-details]
+                               [--export-csv FILE]
 
 optional arguments:
   -h, --help            show this help message and exit
@@ -450,6 +451,8 @@ optional arguments:
                         useful if you are redirecting output to a file.
   --print-json          Print best result detailization in JSON format.
   --no-details          Do not print best epoch details.
+  --export-csv FILE     Export to CSV-File. This will disable table print.
+                        Example: --export-csv hyperopt.csv
 
 Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
@@ -458,9 +461,10 @@ Common arguments:
                         details.
   -V, --version         show program's version number and exit
   -c PATH, --config PATH
-                        Specify configuration file (default: `config.json`).
-                        Multiple --config options may be used. Can be set to
-                        `-` to read config from stdin.
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
   -d PATH, --datadir PATH
                         Path to directory with historical backtesting data.
   --userdir PATH, --user-data-dir PATH

freqtrade/commands/arguments.py

@@ -69,7 +69,8 @@ ARGS_HYPEROPT_LIST = ["hyperopt_list_best", "hyperopt_list_profitable",
                       "hyperopt_list_min_avg_time", "hyperopt_list_max_avg_time",
                       "hyperopt_list_min_avg_profit", "hyperopt_list_max_avg_profit",
                       "hyperopt_list_min_total_profit", "hyperopt_list_max_total_profit",
-                      "print_colorized", "print_json", "hyperopt_list_no_details"]
+                      "print_colorized", "print_json", "hyperopt_list_no_details",
+                      "export_csv"]
 
 ARGS_HYPEROPT_SHOW = ["hyperopt_list_best", "hyperopt_list_profitable", "hyperopt_show_index",
                       "print_json", "hyperopt_show_no_header"]

freqtrade/commands/cli_options.py

@@ -221,6 +221,13 @@ AVAILABLE_CLI_OPTIONS = {
         action='store_true',
         default=False,
     ),
+    "export_csv": Arg(
+        '--export-csv',
+        help='Export to CSV-File.'
+        ' This will disable table print.'
+        ' Example: --export-csv hyperopt.csv',
+        metavar='FILE',
+    ),
     "hyperopt_jobs": Arg(
         '-j', '--job-workers',
         help='The number of concurrently running jobs for hyperoptimization '

freqtrade/commands/hyperopt_commands.py

@@ -21,6 +21,7 @@ def start_hyperopt_list(args: Dict[str, Any]) -> None:
 
     print_colorized = config.get('print_colorized', False)
     print_json = config.get('print_json', False)
+    export_csv = config.get('export_csv', None)
     no_details = config.get('hyperopt_list_no_details', False)
     no_header = False
 
@@ -49,6 +50,7 @@ def start_hyperopt_list(args: Dict[str, Any]) -> None:
     if print_colorized:
         colorama_init(autoreset=True)
 
+    if not export_csv:
         try:
             Hyperopt.print_result_table(config, trials, total_epochs,
                                         not filteroptions['only_best'], print_colorized, 0)
@@ -60,6 +62,11 @@ def start_hyperopt_list(args: Dict[str, Any]) -> None:
         results = sorted_trials[0]
         Hyperopt.print_epoch_details(results, total_epochs, print_json, no_header)
 
+    if trials and export_csv:
+        Hyperopt.export_csv_file(
+            config, trials, total_epochs, not filteroptions['only_best'], export_csv
+        )
+
 
 def start_hyperopt_show(args: Dict[str, Any]) -> None:
     """

freqtrade/commands/optimize_commands.py

@@ -17,10 +17,15 @@ def setup_optimize_configuration(args: Dict[str, Any], method: RunMode) -> Dict[
     """
     config = setup_utils_configuration(args, method)
 
-    if method == RunMode.BACKTEST:
-        if config['stake_amount'] == constants.UNLIMITED_STAKE_AMOUNT:
-            raise DependencyException('stake amount could not be "%s" for backtesting' %
-                                      constants.UNLIMITED_STAKE_AMOUNT)
+    no_unlimited_runmodes = {
+        RunMode.BACKTEST: 'backtesting',
+        RunMode.HYPEROPT: 'hyperoptimization',
+    }
+    if (method in no_unlimited_runmodes.keys() and
+            config['stake_amount'] == constants.UNLIMITED_STAKE_AMOUNT):
+        raise DependencyException(
+            f'The value of `stake_amount` cannot be set as "{constants.UNLIMITED_STAKE_AMOUNT}" '
+            f'for {no_unlimited_runmodes[method]}')
 
     return config
 

freqtrade/configuration/configuration.py

@@ -282,6 +282,9 @@ class Configuration:
         self._args_to_config(config, argname='print_json',
                              logstring='Parameter --print-json detected ...')
 
+        self._args_to_config(config, argname='export_csv',
+                             logstring='Parameter --export-csv detected: {}')
+
         self._args_to_config(config, argname='hyperopt_jobs',
                              logstring='Parameter -j/--job-workers detected: {}')
 

freqtrade/data/history/idatahandler.py

@@ -145,27 +145,40 @@ class IDataHandler(ABC):
         if startup_candles > 0 and timerange_startup:
             timerange_startup.subtract_start(timeframe_to_seconds(timeframe) * startup_candles)
 
-        df = self._ohlcv_load(pair, timeframe, timerange=timerange_startup)
-        if df.empty:
+        pairdf = self._ohlcv_load(pair, timeframe,
+                                  timerange=timerange_startup)
+        if self._check_empty_df(pairdf, pair, timeframe, warn_no_data):
+            return pairdf
+        else:
+            enddate = df.iloc[-1]['date']
+
+            if timerange_startup:
+                self._validate_pairdata(pair, pairdf, timerange_startup)
+                pairdf = trim_dataframe(pairdf, timerange_startup)
+                if self._check_empty_df(pairdf, pair, timeframe, warn_no_data):
+                    return pairdf
+
+            # incomplete candles should only be dropped if we didn't trim the end beforehand.
+            pairdf = clean_ohlcv_dataframe(pairdf, timeframe,
+                                           pair=pair,
+                                           fill_missing=fill_missing,
+                                           drop_incomplete=(drop_incomplete and
+                                                            enddate == pairdf.iloc[-1]['date']))
+            self._check_empty_df(pairdf, pair, timeframe, warn_no_data)
+            return pairdf
+
+    def _check_empty_df(self, pairdf: DataFrame, pair: str, timeframe: str, warn_no_data: bool):
+        """
+        Warn on empty dataframe
+        """
+        if pairdf.empty:
             if warn_no_data:
                 logger.warning(
                     f'No history data for pair: "{pair}", timeframe: {timeframe}. '
                     'Use `freqtrade download-data` to download the data'
                 )
-            return df
-        else:
-            enddate = df.iloc[-1]['date']
-
-            if timerange_startup:
-                self._validate_pairdata(pair, df, timerange_startup)
-                df = trim_dataframe(df, timerange_startup)
-
-            # incomplete candles should only be dropped if we didn't trim the end beforehand.
-            return clean_ohlcv_dataframe(df, timeframe,
-                                         pair=pair,
-                                         fill_missing=fill_missing,
-                                         drop_incomplete=(drop_incomplete and
-                                                          enddate == df.iloc[-1]['date']))
+            return True
+        return False
 
     def _validate_pairdata(self, pair, pairdata: DataFrame, timerange: TimeRange):
         """

freqtrade/optimize/hyperopt.py

@@ -23,6 +23,8 @@ from joblib import (Parallel, cpu_count, delayed, dump, load,
                     wrap_non_picklable_objects)
 from pandas import DataFrame, json_normalize, isna
 import tabulate
+from os import path
+import io
 
 from freqtrade.data.converter import trim_dataframe
 from freqtrade.data.history import get_timerange
@@ -330,10 +332,10 @@ class Hyperopt:
             lambda x: '{}/{}'.format(str(x).rjust(len(str(total_epochs)), ' '), total_epochs)
         )
         trials['Avg profit'] = trials['Avg profit'].apply(
-            lambda x: ('{:,.2f}%'.format(x)).rjust(7, ' ') if not isna(x) else "--".rjust(7, ' ')
+            lambda x: '{:,.2f}%'.format(x).rjust(7, ' ') if not isna(x) else "--".rjust(7, ' ')
         )
         trials['Avg duration'] = trials['Avg duration'].apply(
-            lambda x: ('{:,.1f} m'.format(x)).rjust(7, ' ') if not isna(x) else "--".rjust(7, ' ')
+            lambda x: '{:,.1f} m'.format(x).rjust(7, ' ') if not isna(x) else "--".rjust(7, ' ')
         )
         trials['Objective'] = trials['Objective'].apply(
             lambda x: '{:,.5f}'.format(x).rjust(8, ' ') if x != 100000 else "N/A".rjust(8, ' ')
@@ -381,6 +383,62 @@ class Hyperopt:
             )
         print(table)
 
+    @staticmethod
+    def export_csv_file(config: dict, results: list, total_epochs: int, highlight_best: bool,
+                        csv_file: str) -> None:
+        """
+        Log result to csv-file
+        """
+        if not results:
+            return
+
+        # Verification for overwrite
+        if path.isfile(csv_file):
+            logger.error("CSV-File already exists!")
+            return
+
+        try:
+            io.open(csv_file, 'w+').close()
+        except IOError:
+            logger.error("Filed to create CSV-File!")
+            return
+
+        trials = json_normalize(results, max_level=1)
+        trials['Best'] = ''
+        trials['Stake currency'] = config['stake_currency']
+        trials = trials[['Best', 'current_epoch', 'results_metrics.trade_count',
+                         'results_metrics.avg_profit', 'results_metrics.total_profit',
+                         'Stake currency', 'results_metrics.profit', 'results_metrics.duration',
+                         'loss', 'is_initial_point', 'is_best']]
+        trials.columns = ['Best', 'Epoch', 'Trades', 'Avg profit', 'Total profit', 'Stake currency',
+                          'Profit', 'Avg duration', 'Objective', 'is_initial_point', 'is_best']
+        trials['is_profit'] = False
+        trials.loc[trials['is_initial_point'], 'Best'] = '*'
+        trials.loc[trials['is_best'], 'Best'] = 'Best'
+        trials.loc[trials['Total profit'] > 0, 'is_profit'] = True
+        trials['Epoch'] = trials['Epoch'].astype(str)
+        trials['Trades'] = trials['Trades'].astype(str)
+
+        trials['Total profit'] = trials['Total profit'].apply(
+            lambda x: '{:,.8f}'.format(x) if x != 0.0 else ""
+        )
+        trials['Profit'] = trials['Profit'].apply(
+            lambda x: '{:,.2f}'.format(x) if not isna(x) else ""
+        )
+        trials['Avg profit'] = trials['Avg profit'].apply(
+            lambda x: '{:,.2f}%'.format(x) if not isna(x) else ""
+        )
+        trials['Avg duration'] = trials['Avg duration'].apply(
+            lambda x: '{:,.1f} m'.format(x) if not isna(x) else ""
+        )
+        trials['Objective'] = trials['Objective'].apply(
+            lambda x: '{:,.5f}'.format(x) if x != 100000 else ""
+        )
+
+        trials = trials.drop(columns=['is_initial_point', 'is_best', 'is_profit'])
+        trials.to_csv(csv_file, index=False, header=True, mode='w', encoding='UTF-8')
+        print("CSV-File created!")
+
     def has_space(self, space: str) -> bool:
         """
         Tell if the space value is contained in the configuration

freqtrade/optimize/hyperopt_loss_sharpe.py

@@ -36,7 +36,7 @@ class SharpeHyperOptLoss(IHyperOptLoss):
         expected_returns_mean = total_profit.sum() / days_period
         up_stdev = np.std(total_profit)
 
-        if (np.std(total_profit) != 0.):
+        if up_stdev != 0:
             sharp_ratio = expected_returns_mean / up_stdev * np.sqrt(365)
         else:
             # Define high (negative) sharpe ratio to be clear that this is NOT optimal.

freqtrade/optimize/hyperopt_loss_sharpe_daily.py

@@ -51,7 +51,7 @@ class SharpeHyperOptLossDaily(IHyperOptLoss):
         expected_returns_mean = total_profit.mean()
         up_stdev = total_profit.std()
 
-        if (up_stdev != 0.):
+        if up_stdev != 0:
             sharp_ratio = expected_returns_mean / up_stdev * math.sqrt(days_in_year)
         else:
             # Define high (negative) sharpe ratio to be clear that this is NOT optimal.

freqtrade/optimize/hyperopt_loss_sortino.py

@@ -39,7 +39,7 @@ class SortinoHyperOptLoss(IHyperOptLoss):
         results.loc[total_profit < 0, 'downside_returns'] = results['profit_percent']
         down_stdev = np.std(results['downside_returns'])
 
-        if np.std(total_profit) != 0.0:
+        if down_stdev != 0:
             sortino_ratio = expected_returns_mean / down_stdev * np.sqrt(365)
         else:
             # Define high (negative) sortino ratio to be clear that this is NOT optimal.

freqtrade/optimize/hyperopt_loss_sortino_daily.py

@@ -59,7 +59,7 @@ class SortinoHyperOptLossDaily(IHyperOptLoss):
         # where P = sum_daily["profit_percent_after_slippage"]
         down_stdev = math.sqrt((total_downside**2).sum() / len(total_downside))
 
-        if (down_stdev != 0.):
+        if down_stdev != 0:
             sortino_ratio = expected_returns_mean / down_stdev * math.sqrt(days_in_year)
         else:
             # Define high (negative) sortino ratio to be clear that this is NOT optimal.

freqtrade/pairlist/IPairList.py

@@ -67,21 +67,37 @@ class IPairList(ABC):
         """
 
     @staticmethod
-    def verify_blacklist(pairlist: List[str], blacklist: List[str]) -> List[str]:
+    def verify_blacklist(pairlist: List[str], blacklist: List[str],
+                         aswarning: bool) -> List[str]:
         """
         Verify and remove items from pairlist - returning a filtered pairlist.
+        Logs a warning or info depending on `aswarning`.
+        Pairlists explicitly using this method shall use `aswarning=False`!
+        :param pairlist: Pairlist to validate
+        :param blacklist: Blacklist to validate pairlist against
+        :param aswarning: Log message as Warning or info
+        :return: pairlist - blacklisted pairs
         """
         for pair in deepcopy(pairlist):
             if pair in blacklist:
+                if aswarning:
                     logger.warning(f"Pair {pair} in your blacklist. Removing it from whitelist...")
+                else:
+                    logger.info(f"Pair {pair} in your blacklist. Removing it from whitelist...")
                 pairlist.remove(pair)
         return pairlist
 
-    def _verify_blacklist(self, pairlist: List[str]) -> List[str]:
+    def _verify_blacklist(self, pairlist: List[str], aswarning: bool = True) -> List[str]:
         """
         Proxy method to verify_blacklist for easy access for child classes.
+        Logs a warning or info depending on `aswarning`.
+        Pairlists explicitly using this method shall use aswarning=False!
+        :param pairlist: Pairlist to validate
+        :param aswarning: Log message as Warning or info.
+        :return: pairlist - blacklisted pairs
         """
-        return IPairList.verify_blacklist(pairlist, self._pairlistmanager.blacklist)
+        return IPairList.verify_blacklist(pairlist, self._pairlistmanager.blacklist,
+                                          aswarning=aswarning)
 
     def _whitelist_for_active_markets(self, pairlist: List[str]) -> List[str]:
         """
@@ -113,6 +129,5 @@ class IPairList(ABC):
             if pair not in sanitized_whitelist:
                 sanitized_whitelist.append(pair)
 
-        sanitized_whitelist = self._verify_blacklist(sanitized_whitelist)
         # We need to remove pairs that are unknown
         return sanitized_whitelist

freqtrade/pairlist/VolumePairList.py

@@ -106,7 +106,7 @@ class VolumePairList(IPairList):
 
         # Validate whitelist to only have active market pairs
         pairs = self._whitelist_for_active_markets([s['symbol'] for s in sorted_tickers])
-        pairs = self._verify_blacklist(pairs)
+        pairs = self._verify_blacklist(pairs, aswarning=False)
         # Limit to X number of pairs
         pairs = pairs[:self._number_pairs]
         logger.info(f"Searching {self._number_pairs} pairs: {pairs}")

freqtrade/pairlist/pairlistmanager.py

@@ -91,6 +91,6 @@ class PairListManager():
             pairlist = pl.filter_pairlist(pairlist, tickers)
 
         # Validation against blacklist happens after the pairlists to ensure blacklist is respected.
-        pairlist = IPairList.verify_blacklist(pairlist, self.blacklist)
+        pairlist = IPairList.verify_blacklist(pairlist, self.blacklist, True)
 
         self._whitelist = pairlist

freqtrade/templates/base_config.json.j2

@@ -24,7 +24,7 @@
         "price_side": "ask",
         "use_order_book": false,
         "order_book_min": 1,
-        "order_book_max": 9,
+        "order_book_max": 1,
         "use_sell_signal": true,
         "sell_profit_only": false,
         "ignore_roi_if_buy_signal": false

freqtrade/templates/base_hyperopt.py.j2

@@ -21,7 +21,7 @@ class {{ hyperopt }}(IHyperOpt):
     """
     This is a Hyperopt template to get you started.
 
-    More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md
+    More information in the documentation: https://www.freqtrade.io/en/latest/hyperopt/
 
     You should:
     - Add any lib you need to build your hyperopt.
@@ -29,11 +29,14 @@ class {{ hyperopt }}(IHyperOpt):
     You must keep:
     - The prototypes for the methods: populate_indicators, indicator_space, buy_strategy_generator.
 
-    The roi_space, generate_roi_table, stoploss_space methods are no longer required to be
-    copied in every custom hyperopt. However, you may override them if you need the
-    'roi' and the 'stoploss' spaces that differ from the defaults offered by Freqtrade.
-    Sample implementation of these methods can be found in
-    https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt_advanced.py
+    The methods roi_space, generate_roi_table and stoploss_space are not required
+    and are provided by default.
+    However, you may override them if you need 'roi' and 'stoploss' spaces that
+    differ from the defaults offered by Freqtrade.
+    Sample implementation of these methods will be copied to `user_data/hyperopts` when
+    creating the user-data directory using `freqtrade create-userdir --userdir user_data`,
+    or is available online under the following URL:
+    https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py.
     """
 
     @staticmethod
@@ -63,6 +66,9 @@ class {{ hyperopt }}(IHyperOpt):
                         dataframe['close'], dataframe['sar']
                     ))
 
+            # Check that the candle had volume
+            conditions.append(dataframe['volume'] > 0)
+
             if conditions:
                 dataframe.loc[
                     reduce(lambda x, y: x & y, conditions),
@@ -108,6 +114,9 @@ class {{ hyperopt }}(IHyperOpt):
                         dataframe['sar'], dataframe['close']
                     ))
 
+            # Check that the candle had volume
+            conditions.append(dataframe['volume'] > 0)
+
             if conditions:
                 dataframe.loc[
                     reduce(lambda x, y: x & y, conditions),

freqtrade/templates/sample_hyperopt.py

@@ -20,23 +20,28 @@ import freqtrade.vendor.qtpylib.indicators as qtpylib
 class SampleHyperOpt(IHyperOpt):
     """
     This is a sample Hyperopt to inspire you.
-    Feel free to customize it.
 
-    More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md
+    More information in the documentation: https://www.freqtrade.io/en/latest/hyperopt/
 
     You should:
     - Rename the class name to some unique name.
     - Add any methods you want to build your hyperopt.
     - Add any lib you need to build your hyperopt.
 
+    An easier way to get a new hyperopt file is by using
+    `freqtrade new-hyperopt --hyperopt MyCoolHyperopt`.
+
     You must keep:
     - The prototypes for the methods: populate_indicators, indicator_space, buy_strategy_generator.
 
-    The roi_space, generate_roi_table, stoploss_space methods are no longer required to be
-    copied in every custom hyperopt. However, you may override them if you need the
-    'roi' and the 'stoploss' spaces that differ from the defaults offered by Freqtrade.
-    Sample implementation of these methods can be found in
-    https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt_advanced.py
+    The methods roi_space, generate_roi_table and stoploss_space are not required
+    and are provided by default.
+    However, you may override them if you need 'roi' and 'stoploss' spaces that
+    differ from the defaults offered by Freqtrade.
+    Sample implementation of these methods will be copied to `user_data/hyperopts` when
+    creating the user-data directory using `freqtrade create-userdir --userdir user_data`,
+    or is available online under the following URL:
+    https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py.
     """
 
     @staticmethod
@@ -73,6 +78,9 @@ class SampleHyperOpt(IHyperOpt):
                         dataframe['close'], dataframe['sar']
                     ))
 
+            # Check that volume is not 0
+            conditions.append(dataframe['volume'] > 0)
+
             if conditions:
                 dataframe.loc[
                     reduce(lambda x, y: x & y, conditions),
@@ -133,6 +141,9 @@ class SampleHyperOpt(IHyperOpt):
                         dataframe['sar'], dataframe['close']
                     ))
 
+            # Check that volume is not 0
+            conditions.append(dataframe['volume'] > 0)
+
             if conditions:
                 dataframe.loc[
                     reduce(lambda x, y: x & y, conditions),

freqtrade/templates/sample_hyperopt_advanced.py

@@ -22,7 +22,7 @@ class AdvancedSampleHyperOpt(IHyperOpt):
     This is a sample hyperopt to inspire you.
     Feel free to customize it.
 
-    More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md
+    More information in the documentation: https://www.freqtrade.io/en/latest/hyperopt/
 
     You should:
     - Rename the class name to some unique name.
@@ -32,8 +32,9 @@ class AdvancedSampleHyperOpt(IHyperOpt):
     You must keep:
     - The prototypes for the methods: populate_indicators, indicator_space, buy_strategy_generator.
 
-    The roi_space, generate_roi_table, stoploss_space methods are no longer required to be
-    copied in every custom hyperopt. However, you may override them if you need the
+    The methods roi_space, generate_roi_table and stoploss_space are not required
+    and are provided by default.
+    However, you may override them if you need the
     'roi' and the 'stoploss' spaces that differ from the defaults offered by Freqtrade.
 
     This sample illustrates how to override these methods.
@@ -92,6 +93,9 @@ class AdvancedSampleHyperOpt(IHyperOpt):
                         dataframe['close'], dataframe['sar']
                     ))
 
+            # Check that volume is not 0
+            conditions.append(dataframe['volume'] > 0)
+
             if conditions:
                 dataframe.loc[
                     reduce(lambda x, y: x & y, conditions),
@@ -152,6 +156,9 @@ class AdvancedSampleHyperOpt(IHyperOpt):
                         dataframe['sar'], dataframe['close']
                     ))
 
+            # Check that volume is not 0
+            conditions.append(dataframe['volume'] > 0)
+
             if conditions:
                 dataframe.loc[
                     reduce(lambda x, y: x & y, conditions),

requirements-common.txt

@@ -1,13 +1,13 @@
 # requirements without requirements installable via conda
 # mainly used for Raspberry pi installs
-ccxt==1.23.30
+ccxt==1.23.81
 SQLAlchemy==1.3.13
 python-telegram-bot==12.4.2
 arrow==0.15.5
 cachetools==4.0.0
 requests==2.23.0
 urllib3==1.25.8
-wrapt==1.12.0
+wrapt==1.12.1
 jsonschema==3.2.0
 TA-Lib==0.4.17
 tabulate==0.8.6
@@ -30,4 +30,4 @@ flask==1.1.1
 colorama==0.4.3
 # Building config files interactively
 questionary==1.5.1
-prompt-toolkit==3.0.3
+prompt-toolkit==3.0.4

requirements-hyperopt.txt

@@ -3,7 +3,7 @@
 
 # Required for hyperopt
 scipy==1.4.1
-scikit-learn==0.22.2
+scikit-learn==0.22.2.post1
 scikit-optimize==0.7.4
 filelock==3.0.12
 joblib==0.14.1

requirements-plot.txt

@@ -1,5 +1,5 @@
 # Include all requirements to run the bot.
 -r requirements.txt
 
-plotly==4.5.2
+plotly==4.5.3
 

tests/commands/test_commands.py

@@ -902,6 +902,21 @@ def test_hyperopt_list(mocker, capsys, hyperopt_results):
     assert all(x not in captured.out
                for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 7/12", " 8/12"
                          " 9/12", " 10/12", " 11/12", " 12/12"])
+    args = [
+        "hyperopt-list",
+        "--no-details",
+        "--export-csv", "test_file.csv"
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    assert all(x in captured.out
+               for x in ["CSV-File created!"])
+    f = Path("test_file.csv")
+    assert 'Best,1,2,-1.25%,-0.00125625,,-2.51,"3,930.0 m",0.43662' in f.read_text()
+    assert f.is_file()
+    f.unlink()
 
 
 def test_hyperopt_show(mocker, capsys, hyperopt_results):

tests/optimize/test_backtesting.py

@@ -241,7 +241,7 @@ def test_setup_optimize_configuration_unlimited_stake_amount(mocker, default_con
         '--strategy', 'DefaultStrategy',
     ]
 
-    with pytest.raises(DependencyException, match=r'.*stake amount.*'):
+    with pytest.raises(DependencyException, match=r'.`stake_amount`.*'):
         setup_optimize_configuration(get_args(args), RunMode.BACKTEST)
 
 

tests/optimize/test_hyperopt.py

@@ -10,10 +10,11 @@ import pytest
 from arrow import Arrow
 from filelock import Timeout
 
+from freqtrade import constants
 from freqtrade.commands.optimize_commands import (setup_optimize_configuration,
                                                   start_hyperopt)
 from freqtrade.data.history import load_data
-from freqtrade.exceptions import OperationalException
+from freqtrade.exceptions import DependencyException, OperationalException
 from freqtrade.optimize.default_hyperopt import DefaultHyperOpt
 from freqtrade.optimize.default_hyperopt_loss import DefaultHyperOptLoss
 from freqtrade.optimize.hyperopt import Hyperopt
@@ -158,6 +159,21 @@ def test_setup_hyperopt_configuration_with_arguments(mocker, default_conf, caplo
     assert log_has('Parameter --print-all detected ...', caplog)
 
 
+def test_setup_hyperopt_configuration_unlimited_stake_amount(mocker, default_conf, caplog) -> None:
+    default_conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
+
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = [
+        'hyperopt',
+        '--config', 'config.json',
+        '--hyperopt', 'DefaultHyperOpt',
+    ]
+
+    with pytest.raises(DependencyException, match=r'.`stake_amount`.*'):
+        setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
+
+
 def test_hyperoptresolver(mocker, default_conf, caplog) -> None:
     patched_configuration_load_config_file(mocker, default_conf)
 

tests/pairlist/test_pairlist.py

@@ -240,8 +240,6 @@ def test_pairlist_class(mocker, whitelist_conf, markets, pairlist):
     (['ETH/BTC', 'TKN/BTC', 'ETH/USDT'], "is not compatible with your stake currency"),
     # BCH/BTC not available
     (['ETH/BTC', 'TKN/BTC', 'BCH/BTC'], "is not compatible with exchange"),
-    # BLK/BTC in blacklist
-    (['ETH/BTC', 'TKN/BTC', 'BLK/BTC'], "in your blacklist. Removing "),
     # BTT/BTC is inactive
     (['ETH/BTC', 'TKN/BTC', 'BTT/BTC'], "Market is not active")
 ])