Fix typos discovered by codespell

build_helpers/pre_commit_update.py

@@ -1,4 +1,4 @@
-# File used in CI to ensure pre-commit dependencies are kept uptodate.
+# File used in CI to ensure pre-commit dependencies are kept up-to-date.
 
 import sys
 from pathlib import Path

docs/advanced-backtesting.md

@@ -36,7 +36,7 @@ freqtrade backtesting-analysis -c <config.json> --analysis-groups 0 1 2 3 4 5
 ```
 
 This command will read from the last backtesting results. The `--analysis-groups` option is
-used to specify the various tabular outputs showing the profit fo each group or trade,
+used to specify the various tabular outputs showing the profit of each group or trade,
 ranging from the simplest (0) to the most detailed per pair, per buy and per sell tag (4):
 
 * 0: overall winrate and profit summary by enter_tag

docs/backtesting.md

@@ -587,7 +587,7 @@ These precision values are based on current exchange limits (as described in the
 
 ## Improved backtest accuracy
 
-One big limitation of backtesting is it's inability to know how prices moved intra-candle (was high before close, or viceversa?).
+One big limitation of backtesting is it's inability to know how prices moved intra-candle (was high before close, or vice-versa?).
 So assuming you run backtesting with a 1h timeframe, there will be 4 prices for that candle (Open, High, Low, Close).
 
 While backtesting does take some assumptions (read above) about this - this can never be perfect, and will always be biased in one way or the other.

docs/faq.md

@@ -2,7 +2,7 @@
 
 ## Supported Markets
 
-Freqtrade supports spot trading, as well as (isolated) futures trading for some selected exchanges. Please refer to the [documentation start page](index.md#supported-futures-exchanges-experimental) for an uptodate list of supported exchanges.
+Freqtrade supports spot trading, as well as (isolated) futures trading for some selected exchanges. Please refer to the [documentation start page](index.md#supported-futures-exchanges-experimental) for an up-to-date list of supported exchanges.
 
 ### Can my bot open short positions?
 
@@ -14,7 +14,7 @@ In spot markets, you can in some cases use leveraged spot tokens, which reflect
 
 ### Can my bot trade options or futures?
 
-Futures trading is supported for selected exchanges. Please refer to the [documentation start page](index.md#supported-futures-exchanges-experimental) for an uptodate list of supported exchanges.
+Futures trading is supported for selected exchanges. Please refer to the [documentation start page](index.md#supported-futures-exchanges-experimental) for an up-to-date list of supported exchanges.
 
 ## Beginner Tips & Tricks
 

docs/freqai-parameter-table.md

@@ -55,7 +55,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
 |  |  **Data split parameters within the `freqai.data_split_parameters` sub dictionary**
 | `data_split_parameters` | Include any additional parameters available from scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website). <br> **Datatype:** Dictionary.
 | `test_size` | The fraction of data that should be used for testing instead of training. <br> **Datatype:** Positive float < 1.
-| `shuffle` | Shuffle the training data points during training. Typically, to not remove the chronological order of data in time-series forecasting, this is set to `False`. <br> **Datatype:** Boolean. <br> Defaut: `False`.
+| `shuffle` | Shuffle the training data points during training. Typically, to not remove the chronological order of data in time-series forecasting, this is set to `False`. <br> **Datatype:** Boolean. <br> Default: `False`.
 
 ### Model training parameters
 

docs/rest-api.md

@@ -454,7 +454,7 @@ To properly configure your reverse proxy (securely), please consult it's documen
 - **Caddy**: Caddy v2 supports websockets out of the box, see the [documentation](https://caddyserver.com/docs/v2-upgrade#proxy)
 
 !!! Tip "SSL certificates"
-    You can use tools like certbot to setup ssl certificates to access your bot's UI through encrypted connection by using any fo the above reverse proxies.
+    You can use tools like certbot to setup ssl certificates to access your bot's UI through encrypted connection by using any of the above reverse proxies.
     While this will protect your data in transit, we do not recommend to run the freqtrade API outside of your private network (VPN, SSH tunnel).
 
 ### OpenAPI interface

docs/stoploss.md

@@ -240,7 +240,7 @@ When using leverage, the same principle is applied - with stoploss defining the
 
 Therefore, a stoploss of 10% on a 10x trade would trigger on a 1% price move.
 If your stake amount (own capital) was 100$ - this trade would be 1000$ at 10x (after leverage).
-If price moves 1% - you've lost 10$ of your own capital - therfore stoploss will trigger in this case.
+If price moves 1% - you've lost 10$ of your own capital - therefore stoploss will trigger in this case.
 
 Make sure to be aware of this, and avoid using too tight stoploss (at 10x leverage, 10% risk may be too little to allow the trade to "breath" a little).
 

docs/strategy-advanced.md

@@ -326,4 +326,4 @@ for val in self.buy_ema_short.range:
 dataframe = pd.concat(frames, axis=1)
 ```
 
-Freqtrade does however also counter this by running `dataframe.copy()` on the dataframe right after the `populate_indicators()` method - so performance implications of this should be low to non-existant.
+Freqtrade does however also counter this by running `dataframe.copy()` on the dataframe right after the `populate_indicators()` method - so performance implications of this should be low to non-existent.

docs/strategy-customization.md

@@ -776,7 +776,7 @@ The orderbook structure is aligned with the order structure from [ccxt](https://
 Therefore, using `ob['bids'][0][0]` as demonstrated above will result in using the best bid price. `ob['bids'][0][1]` would look at the amount at this orderbook position.
 
 !!! Warning "Warning about backtesting"
-    The order book is not part of the historic data which means backtesting and hyperopt will not work correctly if this method is used, as the method will return uptodate values.
+    The order book is not part of the historic data which means backtesting and hyperopt will not work correctly if this method is used, as the method will return up-to-date values.
 
 ### *ticker(pair)*
 

docs/trade-object.md

@@ -126,7 +126,7 @@ An `Order` object will always be tied to it's corresponding [`Trade`](#trade-obj
 ### Order - Available attributes
 
 an Order object is typically attached to a trade.
-Most properties here can be None as they are dependant on the exchange response.
+Most properties here can be None as they are dependent on the exchange response.
 
 |  Attribute | DataType | Description |
 |------------|-------------|-------------|
@@ -141,7 +141,7 @@ Most properties here can be None as they are dependant on the exchange response.
 `amount` | float | Amount in base currency
 `filled` | float | Filled amount (in base currency)
 `remaining` | float | Remaining amount
-`cost` | float | Cost of the order - usually average * filled (*Exchange dependant on futures, may contain the cost with or without leverage and may be in contracts.*)
+`cost` | float | Cost of the order - usually average * filled (*Exchange dependent on futures, may contain the cost with or without leverage and may be in contracts.*)
 `stake_amount` | float | Stake amount used for this order. *Added in 2023.7.*
 `order_date` | datetime | Order creation date **use `order_date_utc` instead**
 `order_date_utc` | datetime | Order creation date (in UTC)

freqtrade/configuration/configuration.py

@@ -202,7 +202,7 @@ class Configuration:
 
         if self.args.get('show_sensitive'):
             logger.warning(
-                "Sensitive information will be shown in the upcomming output. "
+                "Sensitive information will be shown in the upcoming output. "
                 "Please make sure to never share this output without redacting "
                 "the information yourself.")
 

freqtrade/data/dataprovider.py

@@ -523,7 +523,7 @@ class DataProvider:
         Send custom RPC Notifications from your bot.
         Will not send any bot in modes other than Dry-run or Live.
         :param message: Message to be sent. Must be below 4096.
-        :param always_send: If False, will send the message only once per candle, and surpress
+        :param always_send: If False, will send the message only once per candle, and suppress
                             identical messages.
                             Careful as this can end up spaming your chat.
                             Defaults to False

freqtrade/exchange/exchange.py

@@ -758,7 +758,7 @@ class Exchange:
 
     def price_get_one_pip(self, pair: str, price: float) -> float:
         """
-        Get's the "1 pip" value for this pair.
+        Gets the "1 pip" value for this pair.
         Used in PriceFilter to calculate the 1pip movements.
         """
         precision = self.markets[pair]['precision']['price']
@@ -2007,7 +2007,7 @@ class Exchange:
             range(since_ms, until_ms or dt_ts(), one_call)]
 
         data: List = []
-        # Chunk requests into batches of 100 to avoid overwelming ccxt Throttling
+        # Chunk requests into batches of 100 to avoid overwhelming ccxt Throttling
         for input_coro in chunks(input_coroutines, 100):
 
             results = await asyncio.gather(*input_coro, return_exceptions=True)
@@ -2124,7 +2124,7 @@ class Exchange:
         Only used in the dataprovider.refresh() method.
         :param pair_list: List of 2 element tuples containing pair, interval to refresh
         :param since_ms: time since when to download, in milliseconds
-        :param cache: Assign result to _klines. Usefull for one-off downloads like for pairlists
+        :param cache: Assign result to _klines. Useful for one-off downloads like for pairlists
         :param drop_incomplete: Control candle dropping.
             Specifying None defaults to _ohlcv_partial_candle
         :return: Dict of [{(pair, timeframe): Dataframe}]
@@ -2135,7 +2135,7 @@ class Exchange:
         input_coroutines, cached_pairs = self._build_ohlcv_dl_jobs(pair_list, since_ms, cache)
 
         results_df = {}
-        # Chunk requests into batches of 100 to avoid overwelming ccxt Throttling
+        # Chunk requests into batches of 100 to avoid overwhelming ccxt Throttling
         for input_coro in chunks(input_coroutines, 100):
             async def gather_stuff():
                 return await asyncio.gather(*input_coro, return_exceptions=True)
@@ -2295,7 +2295,7 @@ class Exchange:
                                   since: Optional[int] = None,
                                   params: Optional[dict] = None) -> Tuple[List[List], Any]:
         """
-        Asyncronously gets trade history using fetch_trades.
+        Asynchronously gets trade history using fetch_trades.
         Handles exchange errors, does one call to the exchange.
         :param pair: Pair to fetch trade data for
         :param since: Since as integer timestamp in milliseconds
@@ -2352,7 +2352,7 @@ class Exchange:
                                           since: Optional[int] = None,
                                           from_id: Optional[str] = None) -> Tuple[str, List[List]]:
         """
-        Asyncronously gets trade history using fetch_trades
+        Asynchronously gets trade history using fetch_trades
         use this when exchange uses id-based iteration (check `self._trades_pagination`)
         :param pair: Pair to fetch trade data for
         :param since: Since as integer timestamp in milliseconds
@@ -2403,7 +2403,7 @@ class Exchange:
     async def _async_get_trade_history_time(self, pair: str, until: int,
                                             since: Optional[int] = None) -> Tuple[str, List[List]]:
         """
-        Asyncronously gets trade history using fetch_trades,
+        Asynchronously gets trade history using fetch_trades,
         when the exchange uses time-based iteration (check `self._trades_pagination`)
         :param pair: Pair to fetch trade data for
         :param since: Since as integer timestamp in milliseconds

freqtrade/exchange/gate.py

@@ -79,7 +79,7 @@ class Gate(Exchange):
             # As such, futures orders on gate will not contain a fee, which causes
             # a repeated "update fee" cycle and wrong calculations.
             # Therefore we patch the response with fees if it's not available.
-            # An alternative also contianing fees would be
+            # An alternative also containing fees would be
             # privateFuturesGetSettleAccountBook({"settle": "usdt"})
             pair_fees = self._trading_fees.get(pair, {})
             if pair_fees:

freqtrade/exchange/okx.py

@@ -56,7 +56,7 @@ class Okx(Exchange):
         """
         Exchange ohlcv candle limit
         OKX has the following behaviour:
-        * 300 candles for uptodate data
+        * 300 candles for up-to-date data
         * 100 candles for historic data
         * 100 candles for additional candles (not futures or spot).
         :param timeframe: Timeframe to check

freqtrade/freqai/RL/BaseEnvironment.py

@@ -222,7 +222,7 @@ class BaseEnvironment(gym.Env):
     @abstractmethod
     def step(self, action: int):
         """
-        Step depeneds on action types, this must be inherited.
+        Step depends on action types, this must be inherited.
         """
         return
 
@@ -326,7 +326,7 @@ class BaseEnvironment(gym.Env):
 
     def _update_unrealized_total_profit(self):
         """
-        Update the unrealized total profit incase of episode end.
+        Update the unrealized total profit in case of episode end.
         """
         if self._position in (Positions.Long, Positions.Short):
             pnl = self.get_unrealized_profit()
@@ -357,7 +357,7 @@ class BaseEnvironment(gym.Env):
         """
         return self.actions
 
-    # Keeping around incase we want to start building more complex environment
+    # Keeping around in case we want to start building more complex environment
     # templates in the future.
     # def most_recent_return(self):
     #     """

freqtrade/freqai/RL/BaseReinforcementLearningModel.py

@@ -311,7 +311,7 @@ class BaseReinforcementLearningModel(IFreqaiModel):
             if not prices_train_old.empty:
                 prices_train = prices_train_old
                 rename_dict = rename_dict_old
-            logger.warning('Reinforcement learning module didnt find the correct raw prices '
+            logger.warning('Reinforcement learning module didn't find the correct raw prices '
                            'assigned in feature_engineering_standard(). '
                            'Please assign them with:\n'
                            'dataframe["%-raw_close"] = dataframe["close"]\n'
@@ -458,7 +458,7 @@ def make_env(MyRLEnv: Type[BaseEnvironment], env_id: str, rank: int,
 
     :param env_id: (str) the environment ID
     :param num_env: (int) the number of environment you wish to have in subprocesses
-    :param seed: (int) the inital seed for RNG
+    :param seed: (int) the initial seed for RNG
     :param rank: (int) index of the subprocess
     :param env_info: (dict) all required arguments to instantiate the environment.
     :return: (Callable)

freqtrade/freqai/data_drawer.py

@@ -280,7 +280,7 @@ class FreqaiDataDrawer:
 
         new_pred = pred_df.copy()
         # set new_pred values to nans (we want to signal to user that there was nothing
-        # historically made during downtime. The newest pred will get appeneded later in
+        # historically made during downtime. The newest pred will get appended later in
         # append_model_predictions)
 
         new_pred["date_pred"] = dataframe["date"]

freqtrade/freqai/data_kitchen.py

@@ -612,7 +612,7 @@ class FreqaiDataKitchen:
         pairs = self.freqai_config["feature_parameters"].get("include_corr_pairlist", [])
 
         for pair in pairs:
-            pair = pair.replace(':', '')  # lightgbm doesnt like colons
+            pair = pair.replace(':', '')  # lightgbm does not like colons
             pair_cols = [col for col in dataframe.columns if col.startswith("%")
                          and f"{pair}_" in col]
 
@@ -638,7 +638,7 @@ class FreqaiDataKitchen:
         pairs = self.freqai_config["feature_parameters"].get("include_corr_pairlist", [])
         current_pair = current_pair.replace(':', '')
         for pair in pairs:
-            pair = pair.replace(':', '')  # lightgbm doesnt work with colons
+            pair = pair.replace(':', '')  # lightgbm does not work with colons
             if current_pair != pair:
                 dataframe = dataframe.merge(corr_dataframes[pair], how='left', on='date')
 
@@ -841,7 +841,7 @@ class FreqaiDataKitchen:
             f = spy.stats.norm.fit(self.data_dictionary["train_labels"][label])
             self.data["labels_mean"][label], self.data["labels_std"][label] = f[0], f[1]
 
-        # incase targets are classifications
+        # in case targets are classifications
         for label in self.unique_class_list:
             self.data["labels_mean"][label], self.data["labels_std"][label] = 0, 0
 

freqtrade/freqai/freqai_interface.py

@@ -222,7 +222,7 @@ class IFreqaiModel(ABC):
             time.sleep(1)
             pair = self.train_queue[0]
 
-            # ensure pair is avaialble in dp
+            # ensure pair is available in dp
             if pair not in strategy.dp.current_whitelist():
                 self.train_queue.popleft()
                 logger.warning(f'{pair} not in current whitelist, removing from train queue.')

freqtrade/freqai/prediction_models/PyTorchMLPClassifier.py

@@ -74,7 +74,7 @@ class PyTorchMLPClassifier(BasePyTorchClassifier):
         model.to(self.device)
         optimizer = torch.optim.AdamW(model.parameters(), lr=self.learning_rate)
         criterion = torch.nn.CrossEntropyLoss()
-        # check if continual_learning is activated, and retreive the model to continue training
+        # check if continual_learning is activated, and retrieve the model to continue training
         trainer = self.get_init_model(dk.pair)
         if trainer is None:
             trainer = PyTorchModelTrainer(

freqtrade/freqai/prediction_models/PyTorchMLPRegressor.py

@@ -69,7 +69,7 @@ class PyTorchMLPRegressor(BasePyTorchRegressor):
         model.to(self.device)
         optimizer = torch.optim.AdamW(model.parameters(), lr=self.learning_rate)
         criterion = torch.nn.MSELoss()
-        # check if continual_learning is activated, and retreive the model to continue training
+        # check if continual_learning is activated, and retrieve the model to continue training
         trainer = self.get_init_model(dk.pair)
         if trainer is None:
             trainer = PyTorchModelTrainer(

freqtrade/freqai/prediction_models/PyTorchTransformerRegressor.py

@@ -80,7 +80,7 @@ class PyTorchTransformerRegressor(BasePyTorchRegressor):
         model.to(self.device)
         optimizer = torch.optim.AdamW(model.parameters(), lr=self.learning_rate)
         criterion = torch.nn.MSELoss()
-        # check if continual_learning is activated, and retreive the model to continue training
+        # check if continual_learning is activated, and retrieve the model to continue training
         trainer = self.get_init_model(dk.pair)
         if trainer is None:
             trainer = PyTorchTransformerTrainer(

freqtrade/freqai/prediction_models/ReinforcementLearner_multiproc.py

@@ -63,6 +63,6 @@ class ReinforcementLearner_multiproc(ReinforcementLearner):
                                                                is_masking_supported(self.eval_env)))
 
         # TENSORBOARD CALLBACK DOES NOT RECOMMENDED TO USE WITH MULTIPLE ENVS,
-        # IT WILL RETURN FALSE INFORMATIONS, NEVERTHLESS NOT THREAD SAFE WITH SB3!!!
+        # IT WILL RETURN FALSE INFORMATION, NEVERTHELESS NOT THREAD SAFE WITH SB3!!!
         actions = self.train_env.env_method("get_actions")[0]
         self.tensorboard_callback = TensorboardCallback(verbose=1, actions=actions)

freqtrade/freqai/torch/PyTorchModelTrainer.py

@@ -38,7 +38,7 @@ class PyTorchModelTrainer(PyTorchTrainerInterface):
         :param init_model: A dictionary containing the initial model/optimizer
             state_dict and model_meta_data saved by self.save() method.
         :param model_meta_data: Additional metadata about the model (optional).
-        :param data_convertor: convertor from pd.DataFrame to torch.tensor.
+        :param data_convertor: converter from pd.DataFrame to torch.tensor.
         :param n_steps: used to calculate n_epochs. The number of training iterations to run.
             iteration here refers to the number of times optimizer.step() is called.
             ignored if n_epochs is set.

freqtrade/freqai/utils.py

@@ -178,7 +178,7 @@ def record_params(config: Dict[str, Any], full_path: Path) -> None:
 
 def get_timerange_backtest_live_models(config: Config) -> str:
     """
-    Returns a formated timerange for backtest live/ready models
+    Returns a formatted timerange for backtest live/ready models
     :param config: Configuration dictionary
 
     :return: a string timerange (format example: '20220801-20220822')

freqtrade/freqtradebot.py

@@ -64,7 +64,7 @@ class FreqtradeBot(LoggingMixin):
         # Init objects
         self.config = config
         exchange_config: ExchangeConfig = deepcopy(config['exchange'])
-        # Remove credentials from original exchange config to avoid accidental credentail exposure
+        # Remove credentials from original exchange config to avoid accidental credential exposure
         remove_exchange_credentials(config['exchange'], True)
 
         self.strategy: IStrategy = StrategyResolver.load_strategy(self.config)
@@ -176,7 +176,7 @@ class FreqtradeBot(LoggingMixin):
         try:
             Trade.commit()
         except Exception:
-            # Exeptions here will be happening if the db disappeared.
+            # Exceptions here will be happening if the db disappeared.
             # At which point we can no longer commit anyway.
             pass
 
@@ -227,7 +227,7 @@ class FreqtradeBot(LoggingMixin):
         self.strategy.analyze(self.active_pair_whitelist)
 
         with self._exit_lock:
-            # Check for exchange cancelations, timeouts and user requested replace
+            # Check for exchange cancellations, timeouts and user requested replace
             self.manage_open_orders()
 
         # Protect from collisions with force_exit.
@@ -1291,12 +1291,12 @@ class FreqtradeBot(LoggingMixin):
 
     def manage_trade_stoploss_orders(self, trade: Trade, stoploss_orders: List[Dict]):
         """
-        Perform required actions acording to existing stoploss orders of trade
+        Perform required actions according to existing stoploss orders of trade
         :param trade: Corresponding Trade
         :param stoploss_orders: Current on exchange stoploss orders
         :return: None
         """
-        # If all stoploss orderd are canceled for some reason we add it again
+        # If all stoploss ordered are canceled for some reason we add it again
         canceled_sl_orders = [o for o in stoploss_orders
                               if o['status'] in ('canceled', 'cancelled')]
         if (

freqtrade/optimize/backtesting.py

@@ -297,7 +297,7 @@ class Backtesting:
                 candle_type=CandleType.FUNDING_RATE
             )
 
-            # For simplicity, assign to CandleType.Mark (might contian index candles!)
+            # For simplicity, assign to CandleType.Mark (might contain index candles!)
             mark_rates_dict = history.load_data(
                 datadir=self.config['datadir'],
                 pairs=self.pairlists.whitelist,
@@ -1217,7 +1217,7 @@ class Backtesting:
         :return: DataFrame with trades (results of backtesting)
         """
         self.prepare_backtest(self.enable_protections)
-        # Ensure wallets are uptodate (important for --strategy-list)
+        # Ensure wallets are up-to-date (important for --strategy-list)
         self.wallets.update()
         # Use dict of lists with data for performance
         # (looping lists is a lot faster than pandas DataFrames)

freqtrade/persistence/custom_data.py

@@ -18,7 +18,7 @@ class _CustomData(ModelBase):
     """
     CustomData database model
     Keeps records of metadata as key/value store
-    for trades or global persistant values
+    for trades or global persistent values
     One to many relationship with Trades:
       - One trade can have many metadata entries
       - One metadata entry can only be associated with one Trade

freqtrade/persistence/trade_model.py

@@ -847,7 +847,7 @@ class LocalTrade:
                 isclose(order.safe_amount_after_fee, amount_tr, abs_tol=MATH_CLOSE_PREC)
                 or (not recalculating and order.safe_amount_after_fee > amount_tr)
             ):
-                # When recalculating a trade, only comming out to 0 can force a close
+                # When recalculating a trade, only coming out to 0 can force a close
                 self.close(order.safe_price)
             else:
                 self.recalc_trade_from_orders()
@@ -1125,7 +1125,7 @@ class LocalTrade:
                 prof = self.calculate_profit(exit_rate, exit_amount, float(avg_price))
                 close_profit_abs += prof.profit_abs
                 if total_stake > 0:
-                    # This needs to be calculated based on the last occuring exit to be aligned
+                    # This needs to be calculated based on the last occurring exit to be aligned
                     # with realized_profit.
                     close_profit = (close_profit_abs / total_stake) * self.leverage
             else:
@@ -1502,7 +1502,7 @@ class Trade(ModelBase, LocalTrade):
     id: Mapped[int] = mapped_column(Integer, primary_key=True)  # type: ignore
 
     orders: Mapped[List[Order]] = relationship(
-        "Order", order_by="Order.id", cascade="all, delete-orphan", lazy="selectin",
+        "Order", order_by="Order.id", cascade="all, delete-orphan", lazy="selection",
         innerjoin=True)  # type: ignore
     custom_data: Mapped[List[_CustomData]] = relationship(
         "_CustomData", cascade="all, delete-orphan",

freqtrade/plot/plotting.py

@@ -445,7 +445,7 @@ def generate_candlestick_graph(
         ) -> go.Figure:
     """
     Generate the graph from the data generated by Backtesting or from DB
-    Volume will always be ploted in row2, so Row 1 and 3 are to our disposal for custom indicators
+    Volume will always be plotted in row2, so Row 1 and 3 are to our disposal for custom indicators
     :param pair: Pair to Display on the graph
     :param data: OHLCV DataFrame containing indicators and entry/exit signals
     :param trades: All trades created
@@ -673,7 +673,7 @@ def plot_profit(config: Config) -> None:
     """
     Plots the total profit for all pairs.
     Note, the profit calculation isn't realistic.
-    But should be somewhat proportional, and therefor useful
+    But should be somewhat proportional, and therefore useful
     in helping out to find a good algorithm.
     """
     if 'timeframe' not in config:

freqtrade/plugins/pairlist/RemotePairList.py

@@ -116,7 +116,7 @@ class RemotePairList(IPairList):
                 "default": "filter",
                 "options": ["filter", "append"],
                 "description": "Processing mode",
-                "help": "Append pairs to incomming pairlist or filter them?",
+                "help": "Append pairs to incoming pairlist or filter them?",
             },
             **IPairList.refresh_period_parameter(),
             "keep_pairlist_on_failure": {

freqtrade/plugins/pairlist/VolumePairList.py

@@ -65,7 +65,7 @@ class VolumePairList(IPairList):
         self._tf_in_min = timeframe_to_minutes(self._lookback_timeframe)
         _tf_in_sec = self._tf_in_min * 60
 
-        # wether to use range lookback or not
+        # whether to use range lookback or not
         self._use_range = (self._tf_in_min > 0) & (self._lookback_period > 0)
 
         if self._use_range & (self._refresh_period < _tf_in_sec):

freqtrade/plugins/protections/iprotection.py

@@ -110,7 +110,7 @@ class IProtection(LoggingMixin, ABC):
         Get lock end time
         """
         max_date: datetime = max([trade.close_date for trade in trades if trade.close_date])
-        # comming from Database, tzinfo is not set.
+        # coming from Database, tzinfo is not set.
         if max_date.tzinfo is None:
             max_date = max_date.replace(tzinfo=timezone.utc)
 

freqtrade/resolvers/iresolver.py

@@ -163,7 +163,7 @@ class IResolver:
     def load_object(cls, object_name: str, config: Config, *, kwargs: dict,
                     extra_dir: Optional[str] = None) -> Any:
         """
-        Search and loads the specified object as configured in hte child class.
+        Search and loads the specified object as configured in the child class.
         :param object_name: name of the module to import
         :param config: configuration dictionary
         :param extra_dir: additional directory to search for the given pairlist

freqtrade/rpc/external_message_consumer.py

@@ -237,7 +237,7 @@ class ExternalMessageConsumer:
                 continue
 
             except Exception as e:
-                # An unforseen error has occurred, log and continue
+                # An unforeseen error has occurred, log and continue
                 logger.error("Unexpected error has occurred:")
                 logger.exception(e)
                 await asyncio.sleep(self.sleep_time)
@@ -387,7 +387,7 @@ class ExternalMessageConsumer:
             )
 
         if not did_append:
-            # We want an overlap in candles incase some data has changed
+            # We want an overlap in candles in case some data has changed
             n_missing += 1
             # Set to None for all candles if we missed a full df's worth of candles
             n_missing = n_missing if n_missing < FULL_DATAFRAME_THRESHOLD else 1500

freqtrade/rpc/rpc.py

@@ -301,7 +301,7 @@ class RPC:
                     for oo in trade.open_orders
                 ]
 
-                # exemple: '*.**.**' trying to enter, exit and exit with 3 different orders
+                # example: '*.**.**' trying to enter, exit and exit with 3 different orders
                 active_attempt_side_symbols_str = '.'.join(active_attempt_side_symbols)
 
                 detail_trade = [

freqtrade/rpc/telegram.py

@@ -488,7 +488,7 @@ class Telegram(RPCHandler):
         elif msg['type'] == RPCMessageType.WARNING:
             message = f"\N{WARNING SIGN} *Warning:* `{msg['status']}`"
         elif msg['type'] == RPCMessageType.EXCEPTION:
-            # Errors will contain exceptions, which are wrapped in tripple ticks.
+            # Errors will contain exceptions, which are wrapped in triple ticks.
             message = f"\N{WARNING SIGN} *ERROR:* \n {msg['status']}"
 
         elif msg['type'] == RPCMessageType.STARTUP:

freqtrade/strategy/strategy_helper.py

@@ -78,7 +78,7 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
     # all indicators on the informative sample MUST be calculated before this point
     if ffill:
         # https://pandas.pydata.org/docs/user_guide/merging.html#timeseries-friendly-merging
-        # merge_ordered - ffill method is 2.5x faster than seperate ffill()
+        # merge_ordered - ffill method is 2.5x faster than separate ffill()
         dataframe = pd.merge_ordered(dataframe, informative, fill_method="ffill", left_on='date',
                                      right_on=date_merge, how='left')
     else:

freqtrade/templates/strategy_subtemplates/strategy_methods_advanced.j2

@@ -3,7 +3,7 @@ def bot_loop_start(self, current_time: datetime, **kwargs) -> None:
     """
     Called at the start of the bot iteration (one loop).
     Might be used to perform pair-independent tasks
-    (e.g. gather some remote ressource for comparison)
+    (e.g. gather some remote resource for comparison)
 
     For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
 

freqtrade/wallets.py

@@ -306,7 +306,7 @@ class Wallets:
         :raise: DependencyException if the available stake amount is too low
         """
         stake_amount: float
-        # Ensure wallets are uptodate.
+        # Ensure wallets are up-to-date.
         if update:
             self.update()
         val_tied_up = Trade.total_open_trades_stakes()

freqtrade/worker.py

@@ -137,7 +137,7 @@ class Worker:
         Throttles the given callable that it
         takes at least `min_secs` to finish execution.
         :param func: Any callable
-        :param throttle_secs: throttling interation execution time limit in seconds
+        :param throttle_secs: throttling iteration execution time limit in seconds
         :param timeframe: ensure iteration is executed at the beginning of the next candle.
         :param timeframe_offset: offset in seconds to apply to the next candle time.
         :return: Any (result of execution of func)

scripts/ws_client.py

@@ -191,7 +191,7 @@ class ClientProtocol:
             self.logger.info("Empty DataFrame")
 
     async def _handle_default(self, name, type, data):
-        self.logger.info("Unkown message of type {type} received...")
+        self.logger.info("Unknown message of type {type} received...")
         self.logger.info(data)
 
 
@@ -277,7 +277,7 @@ async def create_client(
             continue
 
         except Exception as e:
-            # An unforseen error has occurred, log and try reconnecting again
+            # An unforeseen error has occurred, log and try reconnecting again
             logger.error("Unexpected error has occurred:")
             logger.exception(e)
 

tests/commands/test_commands.py

@@ -1609,4 +1609,4 @@ def test_start_show_config(capsys, caplog):
     assert "Your combined configuration is:" in captured.out
     assert '"max_open_trades":' in captured.out
     assert '"secret": "REDACTED"' not in captured.out
-    assert log_has_re(r'Sensitive information will be shown in the upcomming output.*', caplog)
+    assert log_has_re(r'Sensitive information will be shown in the upcoming output.*', caplog)

tests/conftest.py

@@ -49,7 +49,7 @@ def pytest_addoption(parser):
 
 def pytest_configure(config):
     config.addinivalue_line(
-        "markers", "longrun: mark test that is running slowly and should not be run regularily"
+        "markers", "longrun: mark test that is running slowly and should not be run regularly"
     )
     if not config.option.longrun:
         setattr(config.option, 'markexpr', 'not longrun')

tests/data/test_datahandler.py

@@ -251,7 +251,7 @@ def test_datahandler__check_empty_df(testdatadir, caplog):
 # @pytest.mark.parametrize('datahandler', [])
 @pytest.mark.skip("All datahandlers currently support trades data.")
 def test_datahandler_trades_not_supported(datahandler, testdatadir, ):
-    # Currently disabled. Reenable should a new provider not support trades data.
+    # Currently disabled. Re-enable should a new provider not support trades data.
     dh = get_datahandler(testdatadir, datahandler)
     with pytest.raises(NotImplementedError):
         dh.trades_load('UNITTEST/ETH')

tests/exchange/test_exchange.py

@@ -3830,7 +3830,7 @@ def test_ohlcv_candle_limit(default_conf, mocker, exchange_name):
     [
         ("BTC/USDT", 'BTC', 'USDT', "binance", True, False, False, 'spot', {}, True),
         ("USDT/BTC", 'USDT', 'BTC', "binance", True, False, False, 'spot', {}, True),
-        # No seperating /
+        # No separating /
         ("BTCUSDT", 'BTC', 'USDT', "binance", True, False, False, 'spot', {}, True),
         ("BTCUSDT", None, "USDT", "binance", True, False, False, 'spot', {}, False),
         ("USDT/BTC", "BTC", None, "binance", True, False, False, 'spot', {}, False),
@@ -4346,7 +4346,7 @@ def test_combine_funding_and_mark(
     ('binance', 0, 2, "2021-09-01 00:00:01", "2021-09-01 08:00:00",  30.0, -0.00091409999),
     ('binance', 0, 2, "2021-08-31 23:58:00", "2021-09-01 08:00:00",  30.0, -0.00091409999),
     ('binance', 0, 2, "2021-09-01 00:10:01", "2021-09-01 08:00:00",  30.0, -0.0002493),
-    # TODO: Uncoment once _calculate_funding_fees can pas time_in_ratio to exchange._get_funding_fee
+    # TODO: Uncomment once _calculate_funding_fees can pas time_in_ratio to exchange._get_funding_fee
     # ('kraken', "2021-09-01 00:00:00", "2021-09-01 08:00:00",  30.0, -0.0014937),
     # ('kraken', "2021-09-01 00:00:15", "2021-09-01 08:00:00",  30.0, -0.0008289),
     # ('kraken', "2021-09-01 01:00:14", "2021-09-01 08:00:00",  30.0, -0.0008289),
@@ -4358,7 +4358,7 @@ def test_combine_funding_and_mark(
     ('gate', 0, 2, "2021-09-01 00:00:00", "2021-09-01 12:00:00",  30.0, -0.0009140999),
     ('gate', 1, 2, "2021-09-01 00:00:01", "2021-09-01 08:00:00",  30.0, -0.0002493),
     ('binance', 0,  2, "2021-09-01 00:00:00", "2021-09-01 08:00:00",  50.0, -0.0015235),
-    # TODO: Uncoment once _calculate_funding_fees can pas time_in_ratio to exchange._get_funding_fee
+    # TODO: Uncomment once _calculate_funding_fees can pas time_in_ratio to exchange._get_funding_fee
     # ('kraken', "2021-09-01 00:00:00", "2021-09-01 08:00:00",  50.0, -0.0024895),
 ])
 def test__fetch_and_calculate_funding_fees(

tests/freqai/test_freqai_datadrawer.py

@@ -143,7 +143,7 @@ def test_get_timerange_from_backtesting_live_df_pred_not_found(mocker, freqai_co
 def test_set_initial_return_values(mocker, freqai_conf):
     """
     Simple test of the set initial return values that ensures
-    we are concatening and ffilling values properly.
+    we are concatenating and ffilling values properly.
     """
 
     strategy = get_patched_freqai_strategy(mocker, freqai_conf)

tests/freqtradebot/test_freqtradebot.py

@@ -285,7 +285,7 @@ def test_edge_overrides_stoploss(limit_order, fee, caplog, mocker,
             'last': enter_price * buy_price_mult,
     })
 
-    # stoploss shoud be hit
+    # stoploss should be hit
     assert freqtrade.handle_trade(trade) is not ignore_strat_sl
     if not ignore_strat_sl:
         assert log_has_re('Exit for NEO/BTC detected. Reason: stop_loss.*', caplog)
@@ -1398,7 +1398,7 @@ def test_update_trade_state_sell(
     assert order.status == 'open'
     freqtrade.update_trade_state(trade, trade.open_orders_ids[-1], l_order)
     assert trade.amount == l_order['amount']
-    # Wallet needs to be updated after closing a limit-sell order to reenable buying
+    # Wallet needs to be updated after closing a limit-sell order to re-enable buying
     assert wallet_mock.call_count == 1
     assert not trade.is_open
     # Order is updated by update_trade_state
@@ -3240,7 +3240,7 @@ def test_locked_pairs(default_conf_usdt, ticker_usdt, fee,
     )
     trade.close(ticker_usdt_sell_down()['bid'])
     assert freqtrade.strategy.is_pair_locked(trade.pair, side='*')
-    # Boths sides are locked
+    # Both sides are locked
     assert freqtrade.strategy.is_pair_locked(trade.pair, side='long')
     assert freqtrade.strategy.is_pair_locked(trade.pair, side='short')
 
@@ -4829,7 +4829,7 @@ def test_update_funding_fees(
     freqtrade.execute_entry('ETH/USDT', 123, is_short=is_short)
     freqtrade.execute_entry('LTC/USDT', 2.0, is_short=is_short)
     freqtrade.execute_entry('XRP/USDT', 123, is_short=is_short)
-    multipl = 1 if is_short else -1
+    multiple = 1 if is_short else -1
     trades = Trade.get_open_trades()
     assert len(trades) == 3
     for trade in trades:
@@ -4847,7 +4847,7 @@ def test_update_funding_fees(
             assert trade.funding_fees == pytest.approx(sum(
                 trade.amount *
                 mark_prices[trade.pair].iloc[1:2]['open'] *
-                funding_rates[trade.pair].iloc[1:2]['open'] * multipl
+                funding_rates[trade.pair].iloc[1:2]['open'] * multiple
             ))
 
     else:
@@ -4859,7 +4859,7 @@ def test_update_funding_fees(
             trade.amount *
             mark_prices[trade.pair].iloc[1:2]['open'] *
             funding_rates[trade.pair].iloc[1:2]['open'] *
-            multipl
+            multiple
         ))
 
 

tests/optimize/test_backtest_detail.py

@@ -107,7 +107,7 @@ tc5 = BTContainer(data=[
     trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=3)]
 )
 
-# Test 6: Drops 3% / Recovers 6% Positive / Closes 1% positve, Stop-Loss triggers 2% Loss
+# Test 6: Drops 3% / Recovers 6% Positive / Closes 1% positive, Stop-Loss triggers 2% Loss
 # stop-loss: 2% ROI: 5%
 tc6 = BTContainer(data=[
     # D   O     H     L     C    V    EL XL ES Xs  BT
@@ -121,7 +121,7 @@ tc6 = BTContainer(data=[
     trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=2)]
 )
 
-# Test 7: 6% Positive / 1% Negative / Close 1% Positve, ROI Triggers 3% Gain
+# Test 7: 6% Positive / 1% Negative / Close 1% Positive, ROI Triggers 3% Gain
 # stop-loss: 2% ROI: 3%
 tc7 = BTContainer(data=[
     # D   O     H     L     C    V    EL XL ES Xs  BT

tests/optimize/test_backtesting_adjust_position.py

@@ -87,9 +87,9 @@ def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) ->
 
     for _, t in results.iterrows():
         ln = data_pair.loc[data_pair["date"] == t["open_date"]]
-        # Check open trade rate alignes to open rate
+        # Check open trade rate aligns to open rate
         assert ln is not None
-        # check close trade rate alignes to close rate or is between high and low
+        # check close trade rate aligns to close rate or is between high and low
         ln = data_pair.loc[data_pair["date"] == t["close_date"]]
         assert (round(ln.iloc[0]["open"], 6) == round(t["close_rate"], 6) or
                 round(ln.iloc[0]["low"], 6) < round(

tests/optimize/test_lookahead_analysis.py

@@ -152,7 +152,7 @@ def test_lookahead_helper_text_table_lookahead_analysis_instances(lookahead_conf
     assert data[0][2].__contains__('too few trades')
     assert len(data[0]) == 3
 
-    # now check for an error which occured after enough trades
+    # now check for an error which occurred after enough trades
     analysis.total_signals = 12
     analysis.false_entry_signals = 11
     analysis.false_exit_signals = 10

tests/optimize/test_optimize_reports.py

@@ -129,7 +129,7 @@ def test_generate_backtest_stats(default_conf, testdatadir, tmp_path):
     assert strat_stats['backtest_start'] == min_date.strftime(DATETIME_PRINT_FORMAT)
     assert strat_stats['backtest_end'] == max_date.strftime(DATETIME_PRINT_FORMAT)
     assert strat_stats['total_trades'] == len(results['DefStrat']['results'])
-    # Above sample had no loosing trade
+    # Above sample had no losing trade
     assert strat_stats['max_drawdown_account'] == 0.0
 
     # Retry with losing trade

tests/persistence/test_persistence.py

@@ -1871,7 +1871,7 @@ def test_get_trades__query(fee, is_short):
     # without orders there should be no join issued.
     query1 = Trade.get_trades_query([], include_orders=False)
 
-    # Empty "with-options -> default - selectin"
+    # Empty "with-options -> default - selection"
     assert query._with_options == ()
     assert query1._with_options != ()
 

tests/plugins/test_pairlist.py

@@ -605,7 +605,7 @@ def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, t
     ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
        "lookback_days": 1}],
      "BTC", "binance", "default_refresh_too_short"),  # OperationalException expected
-    # ambigous configuration with lookback days and period
+    # ambiguous configuration with lookback days and period
     ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
        "lookback_days": 1, "lookback_period": 1}],
      "BTC", "binance", "lookback_days_and_period"),  # OperationalException expected
@@ -617,7 +617,7 @@ def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, t
     ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
        "lookback_timeframe": "1m", "lookback_period": 2000, "refresh_period": 3600}],
      "BTC", "binance", "lookback_exceeds_exchange_request_size"),  # OperationalException expected
-    # expecing pairs as given
+    # expecting pairs as given
     ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
        "lookback_timeframe": "1d", "lookback_period": 1, "refresh_period": 86400}],
      "BTC", "binance", ['LTC/BTC', 'ETH/BTC', 'TKN/BTC', 'XRP/BTC', 'HOT/BTC']),

tests/rpc/test_rpc_apiserver.py

@@ -1619,7 +1619,7 @@ def test_api_pair_history(botclient, mocker):
     assert 'data' in result
     data = result['data']
     assert len(data) == 289
-    # analyed DF has 30 columns
+    # analyzed DF has 30 columns
     assert len(result['columns']) == 30
     assert len(data[0]) == 30
     date_col_idx = [idx for idx, c in enumerate(result['columns']) if c == 'date'][0]

tests/strategy/test_interface.py

@@ -81,7 +81,7 @@ def test_returns_latest_signal(ohlcv_history):
     assert _STRATEGY.get_entry_signal('ETH/BTC', '5m', mocked_history) == (None, None)
 
     _STRATEGY.config['trading_mode'] = 'futures'
-    # Short signal get's ignored as can_short is not set.
+    # Short signal gets ignored as can_short is not set.
     assert _STRATEGY.get_entry_signal('ETH/BTC', '5m', mocked_history) == (None, None)
 
     _STRATEGY.can_short = True

tests/strategy/test_strategy_helpers.py

@@ -253,7 +253,7 @@ def test_stoploss_from_open(side, profitrange):
 
                     assert stoploss >= 0
                     # Technically the formula can yield values greater than 1 for shorts
-                    # eventhough it doesn't make sense because the position would be liquidated
+                    # even though it doesn't make sense because the position would be liquidated
                     if side == 'long':
                         assert stoploss <= 1
 

tests/test_plotting.py

@@ -125,7 +125,7 @@ def test_add_areas(default_conf, testdatadir, caplog):
     assert fig == fig2
     assert log_has_re(r'Indicator "no_indicator" ignored\..*', caplog)
 
-    # everythin given in plot config, row 3
+    # everything given in plot config, row 3
     fig3 = add_areas(fig, 3, data, indicators)
     figure = fig3.layout.figure
     fill_macd = find_trace_in_fig_data(figure.data, "MACD Fill")
@@ -495,7 +495,7 @@ def test_plot_profit(default_conf, mocker, testdatadir):
     # no main_plot, adds empty main_plot
     ([], [], {'subplots': {'RSI': {'rsi': {'color': 'red'}}}},
      {'main_plot': {}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}}),
-    # indicator 1 / 2 should have prevelance
+    # indicator 1 / 2 should have prevalence
     (['sma', 'ema3'], ['macd'],
      {'main_plot': {'sma': {}}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}},
      {'main_plot': {'sma': {}, 'ema3': {}}, 'subplots': {'Other': {'macd': {}}}}