3.0.1rc3

DogsTailFarmer · Mar 21, 2024 · 10aceac · 10aceac
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,3 +1,10 @@
+## 3.0.1rc3 - 2024-03-21
+### Added for new features
+:rocket: `Backtesting`: handling of partially filling events
+
+### Update
+* Up requirements for exchanges-wrapper==2.1.3
+
 ## 3.0.1rc1 - 2024-03-19
 ### Fix
 * Cyclic Backtesting workflow

diff --git a/martin_binance/__init__.py b/martin_binance/__init__.py
@@ -6,7 +6,7 @@
 __author__ = "Jerry Fedorenko"
 __copyright__ = "Copyright © 2021 Jerry Fedorenko aka VM"
 __license__ = "MIT"
-__version__ = "3.0.1rc1"
+__version__ = "3.0.1rc3"
 __maintainer__ = "Jerry Fedorenko"
 __contact__ = "https://github.com/DogsTailFarmer"
 

diff --git a/martin_binance/backtest/OoTSP.py b/martin_binance/backtest/OoTSP.py
@@ -6,7 +6,7 @@
 __author__ = "Jerry Fedorenko"
 __copyright__ = "Copyright © 2021 Jerry Fedorenko aka VM"
 __license__ = "MIT"
-__version__ = "3.0.1rc1"
+__version__ = "3.0.1rc3"
 __maintainer__ = "Jerry Fedorenko"
 __contact__ = "https://github.com/DogsTailFarmer"
 
@@ -24,56 +24,56 @@
 
 
 def main():
-    questions = [
-        inquirer.List(
-            "path",
-            message="Select from saved: exchange_PAIR with the strategy you want to optimize",
-            choices=[f.name for f in BACKTEST_PATH.iterdir() if f.is_dir() and f.name.count('_') == 1],
-        ),
-        inquirer.List(
-            "mode",
-            message="New study session or analise from saved one",
-            choices=["New", "Analise saved study session"],
-        ),
-        inquirer.Text(
-            "n_trials",
-            message="Enter number of cycles, from 10 to 1000",
-            ignore=lambda x: x["mode"] == "Analise saved study session",
-            default='150',
-            validate=lambda _, c: 10 <= int(c) <= 1000,
-        ),
-    ]
-
-    answers = inquirer.prompt(questions, theme=GreenPassion())
-
-    study_name = answers.get('path')  # Unique identifier of the study
-    storage_name = f"sqlite:///{Path(BACKTEST_PATH, study_name, 'study.db')}"
-
-    if answers.get('mode') == 'New':
-        Path(BACKTEST_PATH, study_name, 'study.db').unlink(missing_ok=True)
-        try:
-            strategy = next(Path(BACKTEST_PATH, study_name).glob("cli_*.py"))
-        except StopIteration:
-            raise UserWarning(f"Can't find cli_*.py in {Path(BACKTEST_PATH, study_name)}")
-
-        study = optimize(
-            study_name,
-            strategy,
-            int(answers.get('n_trials', '0')),
-            storage_name,
-            skip_log=SKIP_LOG,
-            show_progress_bar=SKIP_LOG
-        )
-        print_study_result(study)
-        print(f"Study instance saved to {storage_name} for later use")
-    elif answers.get('mode') == 'Analise saved study session':
-        # noinspection PyArgumentList
-        study = optuna.load_study(study_name=study_name, storage=storage_name)
-
-        print(f"Best value: {study.best_value}")
-        print(f"Original value: {study.get_trials()[0].value}")
-
-        while 1:
+    while 1:
+        questions = [
+                inquirer.List(
+                    "path",
+                    message="Select from saved: exchange_PAIR with the strategy you want to optimize",
+                    choices=[f.name for f in BACKTEST_PATH.iterdir() if f.is_dir() and f.name.count('_') == 1],
+                ),
+                inquirer.List(
+                    "mode",
+                    message="New study session or analise from saved one",
+                    choices=["New", "Analise saved study session", "Exit"],
+                ),
+                inquirer.Text(
+                    "n_trials",
+                    message="Enter number of cycles, from 2 to 1000",
+                    ignore=lambda x: x["mode"] in ("Analise saved study session", "Exit"),
+                    default='150',
+                    validate=lambda _, c: 15 <= int(c) <= 1000,
+                ),
+            ]
+
+        answers = inquirer.prompt(questions, theme=GreenPassion())
+
+        study_name = answers.get('path')  # Unique identifier of the study
+        storage_name = f"sqlite:///{Path(BACKTEST_PATH, study_name, 'study.db')}"
+
+        if answers.get('mode') == 'New':
+            Path(BACKTEST_PATH, study_name, 'study.db').unlink(missing_ok=True)
+            try:
+                strategy = next(Path(BACKTEST_PATH, study_name).glob("cli_*.py"))
+            except StopIteration:
+                raise UserWarning(f"Can't find cli_*.py in {Path(BACKTEST_PATH, study_name)}")
+
+            study = optimize(
+                study_name,
+                strategy,
+                int(answers.get('n_trials', '0')),
+                storage_name,
+                skip_log=SKIP_LOG,
+                show_progress_bar=SKIP_LOG
+            )
+            print_study_result(study)
+            print(f"Study instance saved to {storage_name} for later use")
+        elif answers.get('mode') == 'Analise saved study session':
+            # noinspection PyArgumentList
+            study = optuna.load_study(study_name=study_name, storage=storage_name)
+
+            print(f"Best value: {study.best_value}")
+            print(f"Original value: {study.get_trials()[0].value}")
+
             questions = [
                 inquirer.List(
                     "mode",
@@ -106,12 +106,14 @@ def main():
                     print("Can't find GUI, you can copy study instance to another environment for analyze it")
             elif answers.get('mode') == 'Get parameters for specific trial':
                 trial = study.get_trials()[int(answers.get('n_trial', '0'))]
-                print(trial.number)
+                print(f"number: {trial.number}")
                 print(trial.state)
-                print(trial.value)
-                print(trial.params)
+                print(f"value: {trial.value}")
+                print(f"params: {trial.params}")
             else:
                 break
+        else:
+            break
 
 
 def print_study_result(study):