Merge branch 'main' into feature/BlockchainBlockData

.github/workflows/test.yml

@@ -28,11 +28,11 @@ jobs:
           key: ${{ runner.os }}-v1-linting
           restore-keys: ${{ runner.os }}-v1-linting
 
-      - run: pip install bandit black codespell flake8 mypy==0.982 pyupgrade safety pylint==2.15.2
+      - run: pip install bandit black codespell flake8 mypy==0.982 pyupgrade safety pylint==2.15.2 packaging==22
       - run: pip install types-pytz types-requests types-termcolor types-tabulate types-PyYAML types-python-dateutil types-setuptools types-six
       - run: bandit -x ./tests -r . || true
       - run: black --diff --check .
-      - run: codespell --ignore-words-list=commun,statics,ro,zar,zlot,jewl,ba,buil,coo,ether,hist,hsi,mape,navagation,operatio,pres,ser,yeld,shold,ist,varian,datas,ake,creat,vie,hel,ket,toke,certi,buidl,ot --quiet-level=2 --skip=./tests,.git,*.css,*.csv,*.html,*.ini,*.ipynb,*.js,*.json,*.lock,*.scss,*.txt,*.yaml,./build/pyinstaller,./website/config.toml
+      - run: codespell --ignore-words-list=commun,statics,ro,zar,zlot,jewl,ba,buil,coo,ether,hist,hsi,mape,navagation,operatio,pres,ser,yeld,shold,ist,varian,datas,ake,creat,vie,hel,ket,toke,certi,buidl,ot,te --quiet-level=2 --skip=./tests,.git,*.css,*.csv,*.html,*.ini,*.ipynb,*.js,*.json,*.lock,*.scss,*.txt,*.yaml,./build/pyinstaller,./website/config.toml
       - run: flake8 . --count --ignore=E203,W503 --max-line-length=122 --show-source --statistics --exclude ./build/pyinstaller,./website/content
       - run: mypy --ignore-missing-imports openbb_terminal
       - run: shopt -s globstar && pyupgrade --py38-plus **/*.py

.pre-commit-config.yaml

@@ -25,7 +25,7 @@ repos:
         entry: codespell
         args:
           [
-            "--ignore-words-list=commun,ro,zar,vie,hel,jewl,zlot,ba,buil,coo,ether,hist,hsi,mape,navagation,operatio,pres,ser,yeld,shold,ist,varian,datas,ake,creat,statics,ket,toke,certi,buidl",
+            "--ignore-words-list=te,commun,ro,zar,vie,hel,jewl,zlot,ba,buil,coo,ether,hist,hsi,mape,navagation,operatio,pres,ser,yeld,shold,ist,varian,datas,ake,creat,statics,ket,toke,certi,buidl",
             "--quiet-level=2",
             "--skip=./tests,.git,*.css,*.csv,*.html,*.ini,*.ipynb,*.js,*.json,*.lock,*.scss,*.txt,*.yaml,build/pyinstaller/*,./website/config.toml",
           ]

CONTRIBUTING.md

@@ -629,9 +629,9 @@ With:
 
     <br>
 
-4. Consistent and clear argument naming; not `symbol` in _view and then `ticker` in `_file` -> ticker everywhere; the name should be descriptive of what information it hold (see Style Guide section below)
+4. Consistent and clear argument naming; not `symbol` in `_view` and then `ticker` in `_file` -> ticker everywhere; the name should be descriptive of what information it holds (see Style Guide section below)
 
-    - Why? You can quickly understand what the input it should be; example: tickers and stock names are fundamentally different, but they’re both strings so they should be named accordingly.
+    - Why? You can quickly understand what the input should be; example: tickers and stock names are fundamentally different, but they’re both strings so they should be named accordingly.
 
     <br>
 
@@ -796,7 +796,7 @@ With:
 
     - Why? To respect the principles laid out in Code Structure and the previous bullet point. If your code does not have this `get_` → `display_` map it’s likely that i. and/or ii. fail to hold.
 
-        i. Data is processed in _model files and displayed in `_view` files
+        i. Data is processed in `_model` files and displayed in `_view` files
 
         ii. `_view` and `_model` files will have the same arguments (except for output options)
 
@@ -1307,7 +1307,7 @@ The way to interpret this file is by following the path to a data source, e.g.
 
 ### Export Data
 
-In the `_view.py` files it is common having at the end of each function `export_data` being called. This tipycally looks like:
+In the `_view.py` files it is common having at the end of each function `export_data` being called. This typically looks like:
 
 ```python
     export_data(
@@ -1512,7 +1512,7 @@ Install the pre-commit hooks by running: `pre-commit install`.
 
 ### Coding
 
-Although the Coding Guidelines section has been already explained. It is worth mentioning that if you want to be faster
+Although the Coding Guidelines section has been already explained, it is worth mentioning that if you want to be faster
 at developing a new feature, you may implement it first on a `jupyter notebook` and then carry it across to the
 terminal. This is mostly useful when the feature relies on scraping data from a website, or implementing a Neural
 Network model.

openbb_terminal/core/config/paths.py

@@ -34,3 +34,4 @@ def get_user_data_directory():
 USER_PRESETS_DIRECTORY = USER_DATA_DIRECTORY / "presets"
 USER_REPORTS_DIRECTORY = USER_DATA_DIRECTORY / "reports"
 USER_CUSTOM_REPORTS_DIRECTORY = USER_DATA_DIRECTORY / "reports" / "custom reports"
+USER_FORECAST_MODELS_DIRECTORY = USER_DATA_DIRECTORY / "exports" / "forecast_models"

openbb_terminal/feature_flags.py

@@ -147,7 +147,7 @@
     else:
         raise Exception("Using git")
 except Exception:
-    version = "2.0.0"
+    version = "2.0.1"
 VERSION = str(os.getenv("OPENBB_VERSION", version))
 
 # Select the terminal translation language

openbb_terminal/forecast/brnn_model.py

@@ -14,6 +14,7 @@
 from darts.utils.likelihood_models import GaussianLikelihood
 from openbb_terminal.decorators import log_start_end
 from openbb_terminal.forecast import helpers
+from openbb_terminal.core.config.paths import USER_FORECAST_MODELS_DIRECTORY
 
 logger = logging.getLogger(__name__)
 
@@ -132,6 +133,8 @@ def get_brnn_data(
         force_reset=force_reset,
         save_checkpoints=save_checkpoints,
         likelihood=GaussianLikelihood(),
+        log_tensorboard=True,
+        work_dir=USER_FORECAST_MODELS_DIRECTORY,
     )
 
     # fit model on train series for historical forecasting
@@ -145,9 +148,13 @@ def get_brnn_data(
             past_covariate_val,
         )
     best_model = BlockRNNModel.load_from_checkpoint(
-        model_name=model_save_name, best=True
+        model_name=model_save_name,
+        best=True,
+        work_dir=USER_FORECAST_MODELS_DIRECTORY,
     )
 
+    helpers.print_tensorboard_logs(model_save_name, USER_FORECAST_MODELS_DIRECTORY)
+
     # Showing historical backtesting without retraining model (too slow)
     return helpers.get_prediction(
         "Block RNN",

openbb_terminal/forecast/forecast_controller.py

@@ -19,14 +19,11 @@
             "Follow instructions on creating a new conda environment with the latest "
             f"Darts version ({darts_latest}):"
         )
-        print(
-            "https://github.com/OpenBB-finance/OpenBBTerminal/blob/main/openbb_terminal/README.md"
-        )
+        print("https://docs.openbb.co/terminal/quickstart/installation")
 except ModuleNotFoundError:
     raise ModuleNotFoundError(
-        "Please install the forecast version of the terminal. Instructions "
-        "are here: https://github.com/OpenBB-finance/OpenBBTerminal/"
-        "blob/main/openbb_terminal/README.md#anaconda--python"
+        "Please install the forecast version of the terminal. Instructions can be found "
+        "under the python tab: https://docs.openbb.co/terminal/quickstart/installation"
     )
 
 import pandas as pd

openbb_terminal/forecast/helpers.py

@@ -454,7 +454,7 @@ def get_pl_kwargs(
     pl_trainer_kwargs = {
         "callbacks": [my_stopper],
         "accelerator": accelerator,
-        "logger": False,
+        # "logger": False,
         # "enable_progress_bar": False,
         "enable_model_summary": False,
     }
@@ -980,3 +980,13 @@ def check_dates(s: pd.Series) -> bool:
         except AttributeError:
             return False
     return True
+
+
+def print_tensorboard_logs(model_save_name: str, user_directory: str):
+    console.print()
+    tensorboard_logs_dir = os.path.join(user_directory, model_save_name, "logs")
+    console.print(
+        "This model supports Tensorboard logs. To view, open a new terminal windown and run:"
+    )
+    console.print("tensorboard --logdir=" + tensorboard_logs_dir)
+    console.print()

openbb_terminal/forecast/nbeats_model.py

@@ -13,6 +13,7 @@
 from openbb_terminal.decorators import log_start_end
 
 from openbb_terminal.forecast import helpers
+from openbb_terminal.core.config.paths import USER_FORECAST_MODELS_DIRECTORY
 
 logger = logging.getLogger(__name__)
 
@@ -135,6 +136,8 @@ def get_NBEATS_data(
         save_checkpoints=save_checkpoints,
         random_state=42,
         pl_trainer_kwargs=helpers.get_pl_kwargs(accelerator="cpu"),
+        log_tensorboard=True,
+        work_dir=USER_FORECAST_MODELS_DIRECTORY,
     )
 
     # fit model on train series for historical forecasting
@@ -147,7 +150,11 @@ def get_NBEATS_data(
             past_covariate_train,
             past_covariate_val,
         )
-    best_model = NBEATSModel.load_from_checkpoint(model_name=model_save_name, best=True)
+    best_model = NBEATSModel.load_from_checkpoint(
+        model_name=model_save_name, best=True, work_dir=USER_FORECAST_MODELS_DIRECTORY
+    )
+
+    helpers.print_tensorboard_logs(model_save_name, USER_FORECAST_MODELS_DIRECTORY)
 
     # Showing historical backtesting without retraining model (too slow)
     return helpers.get_prediction(

openbb_terminal/forecast/nhits_model.py

@@ -14,6 +14,7 @@
 from darts.utils.likelihood_models import GaussianLikelihood
 from openbb_terminal.decorators import log_start_end
 from openbb_terminal.forecast import helpers
+from openbb_terminal.core.config.paths import USER_FORECAST_MODELS_DIRECTORY
 
 logger = logging.getLogger(__name__)
 
@@ -164,6 +165,8 @@ def get_nhits_data(
         force_reset=force_reset,
         save_checkpoints=save_checkpoints,
         likelihood=GaussianLikelihood(),
+        log_tensorboard=True,
+        work_dir=USER_FORECAST_MODELS_DIRECTORY,
     )
 
     # fit model on train series for historical forecasting
@@ -176,7 +179,11 @@ def get_nhits_data(
             past_covariate_train,
             past_covariate_val,
         )
-    best_model = NHiTSModel.load_from_checkpoint(model_name=model_save_name, best=True)
+    best_model = NHiTSModel.load_from_checkpoint(
+        model_name=model_save_name, best=True, work_dir=USER_FORECAST_MODELS_DIRECTORY
+    )
+
+    helpers.print_tensorboard_logs(model_save_name, USER_FORECAST_MODELS_DIRECTORY)
 
     # Showing historical backtesting without retraining model (too slow)
     return helpers.get_prediction(

openbb_terminal/forecast/rnn_model.py

@@ -13,6 +13,7 @@
 from darts.utils.likelihood_models import GaussianLikelihood
 from openbb_terminal.decorators import log_start_end
 from openbb_terminal.forecast import helpers
+from openbb_terminal.core.config.paths import USER_FORECAST_MODELS_DIRECTORY
 
 logger = logging.getLogger(__name__)
 
@@ -117,13 +118,19 @@ def get_rnn_data(
         force_reset=force_reset,
         save_checkpoints=save_checkpoints,
         likelihood=GaussianLikelihood(),
+        log_tensorboard=True,
+        work_dir=USER_FORECAST_MODELS_DIRECTORY,
     )
 
     # fit model on train series for historical forecasting
     with warnings.catch_warnings():
         warnings.simplefilter("ignore")
         helpers.fit_model(rnn_model, train, val)
-    best_model = RNNModel.load_from_checkpoint(model_name=model_save_name, best=True)
+    best_model = RNNModel.load_from_checkpoint(
+        model_name=model_save_name, best=True, work_dir=USER_FORECAST_MODELS_DIRECTORY
+    )
+
+    helpers.print_tensorboard_logs(model_save_name, USER_FORECAST_MODELS_DIRECTORY)
 
     # Showing historical backtesting without retraining model (too slow)
     return helpers.get_prediction(

openbb_terminal/forecast/tcn_model.py

@@ -12,6 +12,7 @@
 from darts.models import TCNModel
 from openbb_terminal.decorators import log_start_end
 from openbb_terminal.forecast import helpers
+from openbb_terminal.core.config.paths import USER_FORECAST_MODELS_DIRECTORY
 
 logger = logging.getLogger(__name__)
 
@@ -132,6 +133,8 @@ def get_tcn_data(
         save_checkpoints=save_checkpoints,
         random_state=42,
         pl_trainer_kwargs=helpers.get_pl_kwargs(accelerator="cpu"),
+        log_tensorboard=True,
+        work_dir=USER_FORECAST_MODELS_DIRECTORY,
     )
 
     # fit model on train series for historical forecasting
@@ -144,7 +147,11 @@ def get_tcn_data(
             past_covariate_train,
             past_covariate_val,
         )
-    best_model = TCNModel.load_from_checkpoint(model_name=model_save_name, best=True)
+    best_model = TCNModel.load_from_checkpoint(
+        model_name=model_save_name, best=True, work_dir=USER_FORECAST_MODELS_DIRECTORY
+    )
+
+    helpers.print_tensorboard_logs(model_save_name, USER_FORECAST_MODELS_DIRECTORY)
 
     # Showing historical backtesting without retraining model (too slow)
     return helpers.get_prediction(

openbb_terminal/forecast/tft_model.py

@@ -14,7 +14,7 @@
 
 from openbb_terminal.decorators import log_start_end
 from openbb_terminal.forecast import helpers
-
+from openbb_terminal.core.config.paths import USER_FORECAST_MODELS_DIRECTORY
 
 warnings.simplefilter("ignore", ConvergenceWarning)
 
@@ -172,6 +172,8 @@ def get_tft_data(
             quantiles=quantiles
         ),  # QuantileRegression is set per default
         add_relative_index=True,  # TODO There is a bug with this. Must fix. Should be false
+        log_tensorboard=True,
+        work_dir=USER_FORECAST_MODELS_DIRECTORY,
     )
 
     # fit model on train series for historical forecasting
@@ -184,7 +186,11 @@ def get_tft_data(
             past_covariate_train,
             past_covariate_val,
         )
-    best_model = TFTModel.load_from_checkpoint(model_name=model_save_name, best=True)
+    best_model = TFTModel.load_from_checkpoint(
+        model_name=model_save_name, best=True, work_dir=USER_FORECAST_MODELS_DIRECTORY
+    )
+
+    helpers.print_tensorboard_logs(model_save_name, USER_FORECAST_MODELS_DIRECTORY)
 
     # Showing historical backtesting without retraining model (too slow)
     return helpers.get_prediction(

openbb_terminal/forecast/trans_model.py

@@ -12,6 +12,7 @@
 from darts.models import TransformerModel
 from openbb_terminal.decorators import log_start_end
 from openbb_terminal.forecast import helpers
+from openbb_terminal.core.config.paths import USER_FORECAST_MODELS_DIRECTORY
 
 logger = logging.getLogger(__name__)
 
@@ -142,6 +143,8 @@ def get_trans_data(
         pl_trainer_kwargs=helpers.get_pl_kwargs(accelerator="cpu"),
         force_reset=force_reset,
         save_checkpoints=save_checkpoints,
+        log_tensorboard=True,
+        work_dir=USER_FORECAST_MODELS_DIRECTORY,
     )
 
     # fit model on train series for historical forecasting
@@ -155,9 +158,11 @@ def get_trans_data(
             past_covariate_val,
         )
     best_model = TransformerModel.load_from_checkpoint(
-        model_name=model_save_name, best=True
+        model_name=model_save_name, best=True, work_dir=USER_FORECAST_MODELS_DIRECTORY
     )
 
+    helpers.print_tensorboard_logs(model_save_name, USER_FORECAST_MODELS_DIRECTORY)
+
     # Showing historical backtesting without retraining model (too slow)
     return helpers.get_prediction(
         "Transformer",