The strategy implemented in the provided code performs backtesting of trading strategies. Here's a brief description of what the strategy does:
The strategy is implemented as a class called "TheMessenger" that inherits from the "IStrategy" class. It consists of three main methods: "populate_indicators," "populate_buy_trend," and "populate_sell_trend."
"populate_indicators":
This method takes a DataFrame and metadata as input and returns a modified DataFrame.
It calculates and adds various indicators to the DataFrame, including informative indicators based on 1-hour data and normal time frame indicators.
After modifying the DataFrame, it sends the latest data to a specified URL using a POST request.
"populate_buy_trend": This method takes a DataFrame and metadata as input and returns a modified DataFrame. It defines various conditions for identifying buy opportunities based on different indicators. It assigns a "buy_tag" to the rows that meet specific buy conditions. If any of the conditions are met, it sets the "buy" column value to 1 for those rows. "populate_sell_trend": This method takes a DataFrame and metadata as input and returns a modified DataFrame. It identifies sell opportunities based on conditions such as the difference in BTC values, close price compared to the 200-day exponential moving average (EMA), Chaikin Money Flow (CMF), relative strength index (RSI), and volume. If the conditions for a sell opportunity are met, it marks those rows accordingly. Overall, this strategy involves calculating indicators, identifying buy and sell opportunities based on specific conditions, and updating the DataFrame accordingly. The modified DataFrame can then be used for further analysis or visualization.
It calculates and adds various indicators to the DataFrame, including informative indicators based on 1-hour data and normal time frame indicators.
After modifying the DataFrame, it sends the latest data to a specified URL using a POST request.
"populate_buy_trend": This method takes a DataFrame and metadata as input and returns a modified DataFrame. It defines various conditions for identifying buy opportunities based on different indicators. It assigns a "buy_tag" to the rows that meet specific buy conditions. If any of the conditions are met, it sets the "buy" column value to 1 for those rows. "populate_sell_trend": This method takes a DataFrame and metadata as input and returns a modified DataFrame. It identifies sell opportunities based on conditions such as the difference in BTC values, close price compared to the 200-day exponential moving average (EMA), Chaikin Money Flow (CMF), relative strength index (RSI), and volume. If the conditions for a sell opportunity are met, it marks those rows accordingly. Overall, this strategy involves calculating indicators, identifying buy and sell opportunities based on specific conditions, and updating the DataFrame accordingly. The modified DataFrame can then be used for further analysis or visualization.
Traceback (most recent call last): File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connection.py", line 198, in _new_conn sock = connection.create_connection( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/util/connection.py", line 85, in create_connection raise err File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/util/connection.py", line 73, in create_connection sock.connect(sa) TimeoutError: [Errno 110] Connection timed out The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connectionpool.py", line 793, in urlopen response = self._make_request( ^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connectionpool.py", line 496, in _make_request conn.request( File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connection.py", line 400, in request self.endheaders() File "/usr/local/lib/python3.11/http/client.py", line 1293, in endheaders self._send_output(message_body, encode_chunked=encode_chunked) File "/usr/local/lib/python3.11/http/client.py", line 1052, in _send_output self.send(msg) File "/usr/local/lib/python3.11/http/client.py", line 990, in send self.connect() File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connection.py", line 238, in connect self.sock = self._new_conn() ^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connection.py", line 207, in _new_conn raise ConnectTimeoutError( urllib3.exceptions.ConnectTimeoutError: (, 'Connection to 10.25.96.7 timed out. (connect timeout=None)') The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/ftuser/.local/lib/python3.11/site-packages/requests/adapters.py", line 486, in send resp = conn.urlopen( ^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connectionpool.py", line 847, in urlopen retries = retries.increment( ^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/util/retry.py", line 515, in increment raise MaxRetryError(_pool, url, reason) from reason # type: ignore[arg-type] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ urllib3.exceptions.MaxRetryError: HTTPConnectionPool(host='10.25.96.7', port=8999): Max retries exceeded with url: /data-gateway/submit-data (Caused by ConnectTimeoutError( , 'Connection to 10.25.96.7 timed out. (connect timeout=None)')) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/freqtrade/freqtrade/main.py", line 42, in main return_code = args['func'](args) ^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/commands/optimize_commands.py", line 58, in start_backtesting backtesting.start() File "/freqtrade/freqtrade/optimize/backtesting.py", line 1401, in start min_date, max_date = self.backtest_one_strategy(strat, data, timerange) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/optimize/backtesting.py", line 1318, in backtest_one_strategy preprocessed = self.strategy.advise_all_indicators(data) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1378, in advise_all_indicators return {pair: self.advise_indicators(pair_data.copy(), {'pair': pair}).copy() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1378, in return {pair: self.advise_indicators(pair_data.copy(), {'pair': pair}).copy() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1410, in advise_indicators return self.populate_indicators(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/TheMessenger.py", line 340, in populate_indicators requests.post('http://10.25.96.7:8999/data-gateway/submit-data', json=postData) File "/home/ftuser/.local/lib/python3.11/site-packages/requests/api.py", line 115, in post return request("post", url, data=data, json=json, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/requests/api.py", line 59, in request return session.request(method=method, url=url, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/requests/sessions.py", line 589, in request resp = self.send(prep, **send_kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/requests/sessions.py", line 703, in send r = adapter.send(request, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/requests/adapters.py", line 507, in send raise ConnectTimeout(e, request=request) requests.exceptions.ConnectTimeout: HTTPConnectionPool(host='10.25.96.7', port=8999): Max retries exceeded with url: /data-gateway/submit-data (Caused by ConnectTimeoutError( , 'Connection to 10.25.96.7 timed out.
(connect timeout=None)'))
stoploss: -0.99 timeframe: 5m hash(sha256): c0f88dca86a675d326d4d1ba49c86cfc1640b16c9aec012a9d4679f904dc9217 indicators: upper bb_middleband3 bb_upperband3 btc_1d EWO ema_200 btc_5m leading_senkou_span_b_1h ema_13 close senkou_a cloud_top_1h cci_length_val tenkan_sen fastk rsi_fast srsi_fk r_14 bb_middleband2 volume srsi_fd cci_long tenkan_sen_1h leading_senkou_span_a senkou_a senkou_b closedelta bb_bottom_cross leading_senkou_span_b open bb_delta chikou_span_greater btc_threshold fastd btc_diff sma_15 bb_upperband2 high kijun_sen volume_mean_4 mid kijun_sen_1h chikou_span_greater_1h senkou_span_a bb_width ema_8 e
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last change: 2024-04-28 15:07:17