From a5c7bcf667e04c1f72ef993f9b67c6e62d7ef70d Mon Sep 17 00:00:00 2001
From: Svyatoslav <pchelintsev.sv@phystech.edu>
Date: Thu, 30 Nov 2023 19:02:45 +0300
Subject: [PATCH] Added logging with mlflow

---
 .gitignore                          |   1 +
 README.md                           |   3 +
 configs/cb_config.yaml              |   9 +-
 configs/rf_config.yaml              |  10 +-
 mlopscourse/models/base.py          |   4 +
 mlopscourse/models/catboost.py      |  24 ++
 mlopscourse/models/random_forest.py |  37 ++
 mlopscourse/train.py                |  17 +-
 mlopscourse/utils.py                |   6 +
 poetry.lock                         | 628 +++++++++++++++++++++++++++-
 pyproject.toml                      |   1 +
 11 files changed, 736 insertions(+), 4 deletions(-)
 create mode 100644 mlopscourse/utils.py

diff --git a/.gitignore b/.gitignore
index fccf941..1c68fce 100644
--- a/.gitignore
+++ b/.gitignore
@@ -161,3 +161,4 @@ cython_debug/
 checkpoints
 predictions
 catboost_info
+mlruns
diff --git a/README.md b/README.md
index e726468..825d84a 100644
--- a/README.md
+++ b/README.md
@@ -79,6 +79,9 @@ The available models are `rf` (Random Forest from the `scikit-learn` library) an
 poetry run python3 commands.py train --config_name cb_config
 ```
 
+_N.B. Do not forget to set `logging.mlflow.tracking_uri` before the launch. The logs are
+saved in the default directory: `mlruns`._
+
 ### Evaluation
 
 If you want to infer a previously trained model, make sure you've placed the checkpoint in
diff --git a/configs/cb_config.yaml b/configs/cb_config.yaml
index 9f37ea4..a3f887c 100644
--- a/configs/cb_config.yaml
+++ b/configs/cb_config.yaml
@@ -9,10 +9,17 @@ model:
     learning_rate: 0.3
     l2_leaf_reg: 3
     loss_function: RMSE
-    metric_period: 100
+    metric_period: 10
+    logging_level: Verbose
 
 training:
   checkpoint_name: cb_model.p
 
 inference:
   checkpoint_name: cb_model.p
+
+logging:
+  commit_id: None # Adding new fields from a script is prohibited by default
+  mlflow:
+    exp_name: MLOps hw2
+    tracking_uri: http://127.0.0.1:5000
diff --git a/configs/rf_config.yaml b/configs/rf_config.yaml
index 82e4efd..30881ac 100644
--- a/configs/rf_config.yaml
+++ b/configs/rf_config.yaml
@@ -1,11 +1,19 @@
 model:
   name: rf
   hyperparams:
-    n_estimators: 500
+    n_estimators: 100
     random_state: 0
+    verbose: 0
+    n_jobs: -1
 
 training:
   checkpoint_name: rf_model.p
 
 inference:
   checkpoint_name: rf_model.p
+
+logging:
+  commit_id: None # Adding new fields from a script is prohibited by default
+  mlflow:
+    exp_name: MLOps hw2
+    tracking_uri: http://127.0.0.1:5000
diff --git a/mlopscourse/models/base.py b/mlopscourse/models/base.py
index 07b0f4a..3685547 100644
--- a/mlopscourse/models/base.py
+++ b/mlopscourse/models/base.py
@@ -35,3 +35,7 @@ def __call__(self, X_sample: pd.DataFrame) -> pd.Series:
     def save_checkpoint(self, path: str) -> None:
         with open(path + self.cfg.training.checkpoint_name, "wb") as f:
             pickle.dump(self, f)
+
+    @abstractmethod
+    def log_fis_and_metrics(self, exp_id: str) -> None:
+        raise NotImplementedError()
diff --git a/mlopscourse/models/catboost.py b/mlopscourse/models/catboost.py
index d8de95c..1a07d59 100644
--- a/mlopscourse/models/catboost.py
+++ b/mlopscourse/models/catboost.py
@@ -1,5 +1,6 @@
 from typing import List, Optional
 
+import mlflow
 import numpy as np
 import pandas as pd
 from catboost import CatBoostRegressor, Pool
@@ -68,3 +69,26 @@ def __call__(self, X_sample: pd.DataFrame) -> np.ndarray:
             feature_names=list(X_sample.columns),
         )
         return self.model.predict(sample_data)
+
+    def log_fis_and_metrics(self, exp_id: str, col_names: List[str]) -> None:
+        with mlflow.start_run(
+            experiment_id=exp_id, run_name=f"training-{self.cfg.model.name}"
+        ):
+            # Log the model's hyperparameters and the code version
+            mlflow.log_params(self.cfg.model.hyperparams)
+            mlflow.log_param("commit_id", self.cfg.logging.commit_id)
+            # Log feature importances
+            mlflow.log_metrics(
+                {
+                    f"fi_of_{col_name}": self.model.feature_importances_[i]
+                    for i, col_name in enumerate(col_names)
+                }
+            )
+            r2_scores = self.model.evals_result_["learn"]["R2"]
+            rmse_scores = self.model.evals_result_["learn"]["RMSE"]
+            assert len(r2_scores) == len(rmse_scores), "Something wrong with metrics!"
+            for i in range(len(r2_scores)):
+                mlflow.log_metrics(
+                    {"R2_metric": r2_scores[i], "RMSE_loss": rmse_scores[i]},
+                    step=i * self.cfg.model.hyperparams.metric_period,
+                )
diff --git a/mlopscourse/models/random_forest.py b/mlopscourse/models/random_forest.py
index 97c16c0..4f25001 100644
--- a/mlopscourse/models/random_forest.py
+++ b/mlopscourse/models/random_forest.py
@@ -1,12 +1,15 @@
 from typing import List, Optional
 
+import mlflow
 import numpy as np
 import pandas as pd
 from omegaconf import DictConfig
 from sklearn.compose import ColumnTransformer
 from sklearn.ensemble import RandomForestRegressor
+from sklearn.metrics import mean_squared_error, r2_score
 from sklearn.pipeline import make_pipeline
 from sklearn.preprocessing import OrdinalEncoder
+from tqdm import tqdm
 
 from .base import BaseModel
 
@@ -52,3 +55,37 @@ def eval(self, X_test: pd.DataFrame, y_test: pd.Series) -> pd.Series:
 
     def __call__(self, X_sample: pd.DataFrame) -> np.ndarray:
         return self.model.predict(X_sample)
+
+    def log_fis_and_metrics(
+        self, exp_id: str, X_train: pd.DataFrame, y_train: pd.Series
+    ) -> None:
+        with mlflow.start_run(
+            experiment_id=exp_id, run_name=f"training-{self.cfg.model.name}"
+        ):
+            # Log the model's hyperparameters and the code version
+            mlflow.log_params(self.cfg.model.hyperparams)
+            mlflow.log_param("commit_id", self.cfg.logging.commit_id)
+            # Log feature importances
+            mlflow.log_metrics(
+                {
+                    f"fi_of_{col_name}": self.model.named_steps[
+                        "randomforestregressor"
+                    ].feature_importances_[i]
+                    for i, col_name in enumerate(X_train.columns)
+                }
+            )
+            # Log R2 and RMSE metrics
+            for i in tqdm(range(0, self.cfg.model.hyperparams.n_estimators)):
+                model_i = make_pipeline(
+                    self.preprocessor, RandomForestRegressor(**self.cfg.model.hyperparams)
+                )
+                model_i.named_steps["randomforestregressor"].n_estimators = i + 1
+                model_i.fit(X_train, y_train)
+                y_pred = model_i.predict(X_train)
+                mlflow.log_metrics(
+                    {
+                        "R2_metric": r2_score(y_train, y_pred),
+                        "RMSE_metric": mean_squared_error(y_train, y_pred, squared=False),
+                    },
+                    step=i,
+                )
diff --git a/mlopscourse/train.py b/mlopscourse/train.py
index b83d4b7..9c7294c 100644
--- a/mlopscourse/train.py
+++ b/mlopscourse/train.py
@@ -1,11 +1,13 @@
 import os
 
 import fire
+import mlflow
 from hydra import compose
 from omegaconf import DictConfig, OmegaConf
 
 from .data.prepare_dataset import load_dataset
 from .models.models_zoo import prepare_model
+from .utils import get_git_revision_hash
 
 
 class Trainer:
@@ -23,6 +25,7 @@ def __init__(self, config_name: str, **kwargs: dict) -> None:
         self.cfg: DictConfig = compose(
             config_name=config_name, overrides=[f"{k}={v}" for k, v in kwargs.items()]
         )
+        self.cfg.logging.commit_id = get_git_revision_hash()
         print(OmegaConf.to_yaml(self.cfg))
 
     def train(self) -> None:
@@ -40,7 +43,19 @@ def train(self) -> None:
 
         os.makedirs("checkpoints", exist_ok=True)
         model.save_checkpoint("checkpoints/")
-        print("The training was finished successfully!")
+        print("The training was finished successfully!\nCollecting logs...")
+
+        # Since there is no easy way to log metrics as functions of time during
+        # the training, they should be collected after it.
+        mlflow_cfg = self.cfg.logging.mlflow
+        mlflow.set_tracking_uri(mlflow_cfg.tracking_uri)
+        exp_id = mlflow.set_experiment(mlflow_cfg.exp_name).experiment_id
+        # Unfortunately, logging is model dependent, at least because
+        # RandomForestRegressor doesn't provide the target metric progress.
+        if self.cfg.model.name == "cb":
+            model.log_fis_and_metrics(exp_id, X_train.columns)
+        else:
+            model.log_fis_and_metrics(exp_id, X_train, y_train)
 
 
 if __name__ == "__main__":
diff --git a/mlopscourse/utils.py b/mlopscourse/utils.py
new file mode 100644
index 0000000..ea38f52
--- /dev/null
+++ b/mlopscourse/utils.py
@@ -0,0 +1,6 @@
+import subprocess
+
+
+# Credits to https://stackoverflow.com/a/21901260/12187881
+def get_git_revision_hash() -> str:
+    return subprocess.check_output(["git", "rev-parse", "HEAD"]).decode("ascii").strip()
diff --git a/poetry.lock b/poetry.lock
index d7eacb3..310d8c4 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -136,6 +136,25 @@ files = [
 [package.dependencies]
 frozenlist = ">=1.1.0"
 
+[[package]]
+name = "alembic"
+version = "1.12.1"
+description = "A database migration tool for SQLAlchemy."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "alembic-1.12.1-py3-none-any.whl", hash = "sha256:47d52e3dfb03666ed945becb723d6482e52190917fdb47071440cfdba05d92cb"},
+    {file = "alembic-1.12.1.tar.gz", hash = "sha256:bca5877e9678b454706347bc10b97cb7d67f300320fa5c3a94423e8266e2823f"},
+]
+
+[package.dependencies]
+Mako = "*"
+SQLAlchemy = ">=1.3.0"
+typing-extensions = ">=4"
+
+[package.extras]
+tz = ["python-dateutil"]
+
 [[package]]
 name = "amqp"
 version = "5.1.1"
@@ -257,6 +276,17 @@ files = [
     {file = "billiard-4.1.0.tar.gz", hash = "sha256:1ad2eeae8e28053d729ba3373d34d9d6e210f6e4d8bf0a9c64f92bd053f1edf5"},
 ]
 
+[[package]]
+name = "blinker"
+version = "1.7.0"
+description = "Fast, simple object-to-object and broadcast signaling"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "blinker-1.7.0-py3-none-any.whl", hash = "sha256:c3f865d4d54db7abc53758a01601cf343fe55b84c1de4e3fa910e420b438d5b9"},
+    {file = "blinker-1.7.0.tar.gz", hash = "sha256:e6820ff6fa4e4d1d8e2747c2283749c3f547e4fee112b98555cdcdae32996182"},
+]
+
 [[package]]
 name = "cachetools"
 version = "5.3.2"
@@ -613,6 +643,17 @@ prompt-toolkit = ">=3.0.36"
 [package.extras]
 testing = ["pytest (>=7.2.1)", "pytest-cov (>=4.0.0)", "tox (>=4.4.3)"]
 
+[[package]]
+name = "cloudpickle"
+version = "2.2.1"
+description = "Extended pickling support for Python objects"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "cloudpickle-2.2.1-py3-none-any.whl", hash = "sha256:61f594d1f4c295fa5cd9014ceb3a1fc4a70b0de1164b94fbc2d854ccba056f9f"},
+    {file = "cloudpickle-2.2.1.tar.gz", hash = "sha256:d89684b8de9e34a2a43b3460fbca07d09d6e25ce858df4d5a44240403b6178f5"},
+]
+
 [[package]]
 name = "colorama"
 version = "0.4.6"
@@ -768,6 +809,26 @@ files = [
     {file = "cycler-0.11.0.tar.gz", hash = "sha256:9c87405839a19696e837b3b818fed3f5f69f16f1eec1a1ad77e043dcea9c772f"},
 ]
 
+[[package]]
+name = "databricks-cli"
+version = "0.18.0"
+description = "A command line interface for Databricks"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "databricks-cli-0.18.0.tar.gz", hash = "sha256:87569709eda9af3e9db8047b691e420b5e980c62ef01675575c0d2b9b4211eb7"},
+    {file = "databricks_cli-0.18.0-py2.py3-none-any.whl", hash = "sha256:1176a5f42d3e8af4abfc915446fb23abc44513e325c436725f5898cbb9e3384b"},
+]
+
+[package.dependencies]
+click = ">=7.0"
+oauthlib = ">=3.1.0"
+pyjwt = ">=1.7.0"
+requests = ">=2.17.3"
+six = ">=1.10.0"
+tabulate = ">=0.7.7"
+urllib3 = ">=1.26.7,<3"
+
 [[package]]
 name = "dictdiffer"
 version = "0.9.0"
@@ -818,6 +879,27 @@ files = [
     {file = "distro-1.8.0.tar.gz", hash = "sha256:02e111d1dc6a50abb8eed6bf31c3e48ed8b0830d1ea2a1b78c61765c2513fdd8"},
 ]
 
+[[package]]
+name = "docker"
+version = "6.1.3"
+description = "A Python library for the Docker Engine API."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "docker-6.1.3-py3-none-any.whl", hash = "sha256:aecd2277b8bf8e506e484f6ab7aec39abe0038e29fa4a6d3ba86c3fe01844ed9"},
+    {file = "docker-6.1.3.tar.gz", hash = "sha256:aa6d17830045ba5ef0168d5eaa34d37beeb113948c413affe1d5991fc11f9a20"},
+]
+
+[package.dependencies]
+packaging = ">=14.0"
+pywin32 = {version = ">=304", markers = "sys_platform == \"win32\""}
+requests = ">=2.26.0"
+urllib3 = ">=1.26.0"
+websocket-client = ">=0.32.0"
+
+[package.extras]
+ssh = ["paramiko (>=2.4.3)"]
+
 [[package]]
 name = "dpath"
 version = "2.1.6"
@@ -1159,6 +1241,29 @@ files = [
 six = "*"
 termcolor = "*"
 
+[[package]]
+name = "flask"
+version = "3.0.0"
+description = "A simple framework for building complex web applications."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "flask-3.0.0-py3-none-any.whl", hash = "sha256:21128f47e4e3b9d597a3e8521a329bf56909b690fcc3fa3e477725aa81367638"},
+    {file = "flask-3.0.0.tar.gz", hash = "sha256:cfadcdb638b609361d29ec22360d6070a77d7463dcb3ab08d2c2f2f168845f58"},
+]
+
+[package.dependencies]
+blinker = ">=1.6.2"
+click = ">=8.1.3"
+importlib-metadata = {version = ">=3.6.0", markers = "python_version < \"3.10\""}
+itsdangerous = ">=2.1.2"
+Jinja2 = ">=3.1.2"
+Werkzeug = ">=3.0.0"
+
+[package.extras]
+async = ["asgiref (>=3.2)"]
+dotenv = ["python-dotenv"]
+
 [[package]]
 name = "flatten-dict"
 version = "0.4.2"
@@ -1524,6 +1629,76 @@ dev = ["flake8", "pep8-naming", "tox (>=3)", "twine", "wheel"]
 docs = ["sphinx (>=5)", "sphinx-autodoc-typehints", "sphinx-rtd-theme"]
 test = ["coverage", "mock (>=4)", "pytest (>=7)", "pytest-cov", "pytest-mock (>=3)"]
 
+[[package]]
+name = "greenlet"
+version = "3.0.1"
+description = "Lightweight in-process concurrent programming"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "greenlet-3.0.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:f89e21afe925fcfa655965ca8ea10f24773a1791400989ff32f467badfe4a064"},
+    {file = "greenlet-3.0.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:28e89e232c7593d33cac35425b58950789962011cc274aa43ef8865f2e11f46d"},
+    {file = "greenlet-3.0.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b8ba29306c5de7717b5761b9ea74f9c72b9e2b834e24aa984da99cbfc70157fd"},
+    {file = "greenlet-3.0.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:19bbdf1cce0346ef7341705d71e2ecf6f41a35c311137f29b8a2dc2341374565"},
+    {file = "greenlet-3.0.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:599daf06ea59bfedbec564b1692b0166a0045f32b6f0933b0dd4df59a854caf2"},
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+docs = ["Sphinx"]
+test = ["objgraph", "psutil"]
+
 [[package]]
 name = "gto"
 version = "1.5.0"
@@ -1549,6 +1724,26 @@ typer = ">=0.4.1"
 [package.extras]
 tests = ["freezegun", "pylint (==3.0.2)", "pylint-plugin-utils", "pytest", "pytest-cov", "pytest-lazy-fixture (==0.6.3)", "pytest-mock", "pytest-test-utils", "types-freezegun"]
 
+[[package]]
+name = "gunicorn"
+version = "21.2.0"
+description = "WSGI HTTP Server for UNIX"
+optional = false
+python-versions = ">=3.5"
+files = [
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+]
+
+[package.dependencies]
+packaging = "*"
+
+[package.extras]
+eventlet = ["eventlet (>=0.24.1)"]
+gevent = ["gevent (>=1.4.0)"]
+setproctitle = ["setproctitle"]
+tornado = ["tornado (>=0.2)"]
+
 [[package]]
 name = "httplib2"
 version = "0.22.0"
@@ -1662,6 +1857,34 @@ requests = "*"
 dev = ["mypy (==0.971)", "pylint (==2.15.0)", "pytest (==7.2.0)", "pytest-cov (==3.0.0)", "pytest-mock (==3.8.2)", "pytest-sugar (==0.9.5)", "types-requests"]
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+version = "2.1.2"
+description = "Safely pass data to untrusted environments and back."
+optional = false
+python-versions = ">=3.7"
+files = [
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+optional = false
+python-versions = ">=3.7"
+files = [
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+
+[package.extras]
+i18n = ["Babel (>=2.7)"]
+
 [[package]]
 name = "joblib"
 version = "1.3.2"
@@ -1819,6 +2042,43 @@ sqs = ["boto3 (>=1.26.143)", "pycurl (>=7.43.0.5)", "urllib3 (>=1.26.16)"]
 yaml = ["PyYAML (>=3.10)"]
 zookeeper = ["kazoo (>=2.8.0)"]
 
+[[package]]
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+version = "1.3.0"
+description = "A super-fast templating language that borrows the best ideas from the existing templating languages."
+optional = false
+python-versions = ">=3.8"
+files = [
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+
+[package.extras]
+babel = ["Babel"]
+lingua = ["lingua"]
+testing = ["pytest"]
+
+[[package]]
+name = "markdown"
+version = "3.5.1"
+description = "Python implementation of John Gruber's Markdown."
+optional = false
+python-versions = ">=3.8"
+files = [
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+
+[package.extras]
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+testing = ["coverage", "pyyaml"]
+
 [[package]]
 name = "markdown-it-py"
 version = "3.0.0"
@@ -1843,6 +2103,75 @@ profiling = ["gprof2dot"]
 rtd = ["jupyter_sphinx", "mdit-py-plugins", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx_book_theme"]
 testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
 
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+version = "2.1.3"
+description = "Safely add untrusted strings to HTML/XML markup."
+optional = false
+python-versions = ">=3.7"
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 [[package]]
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 version = "3.8.0"
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+[[package]]
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+version = "2.8.1"
+description = "MLflow: A Platform for ML Development and Productionization"
+optional = false
+python-versions = ">=3.8"
+files = [
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+Jinja2 = [
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+
+[package.extras]
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+sqlserver = ["mlflow-dbstore"]
+xethub = ["mlflow-xethub"]
+
 [[package]]
 name = "multidict"
 version = "6.0.4"
@@ -2078,6 +2458,22 @@ pyasn1-modules = ">=0.0.5"
 rsa = ">=3.1.4"
 six = ">=1.6.1"
 
+[[package]]
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+version = "3.2.2"
+description = "A generic, spec-compliant, thorough implementation of the OAuth request-signing logic"
+optional = false
+python-versions = ">=3.6"
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+signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
+
 [[package]]
 name = "omegaconf"
 version = "2.3.0"
@@ -2421,6 +2817,54 @@ files = [
 [package.extras]
 test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
 
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+]
+
+[package.dependencies]
+numpy = ">=1.16.6"
+
 [[package]]
 name = "pyasn1"
 version = "0.5.0"
@@ -2692,6 +3136,23 @@ files = [
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 ]
 
+[[package]]
+name = "pyjwt"
+version = "2.8.0"
+description = "JSON Web Token implementation in Python"
+optional = false
+python-versions = ">=3.7"
+files = [
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+]
+
+[package.extras]
+crypto = ["cryptography (>=3.4.0)"]
+dev = ["coverage[toml] (==5.0.4)", "cryptography (>=3.4.0)", "pre-commit", "pytest (>=6.0.0,<7.0.0)", "sphinx (>=4.5.0,<5.0.0)", "sphinx-rtd-theme", "zope.interface"]
+docs = ["sphinx (>=4.5.0,<5.0.0)", "sphinx-rtd-theme", "zope.interface"]
+tests = ["coverage[toml] (==5.0.4)", "pytest (>=6.0.0,<7.0.0)"]
+
 [[package]]
 name = "pyopenssl"
 version = "23.3.0"
@@ -2831,6 +3292,20 @@ files = [
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 ]
 
+[[package]]
+name = "querystring-parser"
+version = "1.2.4"
+description = "QueryString parser for Python/Django that correctly handles nested dictionaries"
+optional = false
+python-versions = "*"
+files = [
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+]
+
+[package.dependencies]
+six = "*"
+
 [[package]]
 name = "requests"
 version = "2.31.0"
@@ -3168,6 +3643,109 @@ files = [
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 ]
 
+[[package]]
+name = "sqlalchemy"
+version = "2.0.23"
+description = "Database Abstraction Library"
+optional = false
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+]
+
+[package.dependencies]
+greenlet = {version = "!=0.4.17", markers = "platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\""}
+typing-extensions = ">=4.2.0"
+
+[package.extras]
+aiomysql = ["aiomysql (>=0.2.0)", "greenlet (!=0.4.17)"]
+aioodbc = ["aioodbc", "greenlet (!=0.4.17)"]
+aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing-extensions (!=3.10.0.1)"]
+asyncio = ["greenlet (!=0.4.17)"]
+asyncmy = ["asyncmy (>=0.2.3,!=0.2.4,!=0.2.6)", "greenlet (!=0.4.17)"]
+mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2,!=1.1.5)"]
+mssql = ["pyodbc"]
+mssql-pymssql = ["pymssql"]
+mssql-pyodbc = ["pyodbc"]
+mypy = ["mypy (>=0.910)"]
+mysql = ["mysqlclient (>=1.4.0)"]
+mysql-connector = ["mysql-connector-python"]
+oracle = ["cx-oracle (>=8)"]
+oracle-oracledb = ["oracledb (>=1.0.1)"]
+postgresql = ["psycopg2 (>=2.7)"]
+postgresql-asyncpg = ["asyncpg", "greenlet (!=0.4.17)"]
+postgresql-pg8000 = ["pg8000 (>=1.29.1)"]
+postgresql-psycopg = ["psycopg (>=3.0.7)"]
+postgresql-psycopg2binary = ["psycopg2-binary"]
+postgresql-psycopg2cffi = ["psycopg2cffi"]
+postgresql-psycopgbinary = ["psycopg[binary] (>=3.0.7)"]
+pymysql = ["pymysql"]
+sqlcipher = ["sqlcipher3-binary"]
+
+[[package]]
+name = "sqlparse"
+version = "0.4.4"
+description = "A non-validating SQL parser."
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "sqlparse-0.4.4-py3-none-any.whl", hash = "sha256:5430a4fe2ac7d0f93e66f1efc6e1338a41884b7ddf2a350cedd20ccc4d9d28f3"},
+    {file = "sqlparse-0.4.4.tar.gz", hash = "sha256:d446183e84b8349fa3061f0fe7f06ca94ba65b426946ffebe6e3e8295332420c"},
+]
+
+[package.extras]
+dev = ["build", "flake8"]
+doc = ["sphinx"]
+test = ["pytest", "pytest-cov"]
+
 [[package]]
 name = "sqltrie"
 version = "0.8.0"
@@ -3396,6 +3974,21 @@ files = [
     {file = "voluptuous-0.13.1.tar.gz", hash = "sha256:e8d31c20601d6773cb14d4c0f42aee29c6821bbd1018039aac7ac5605b489723"},
 ]
 
+[[package]]
+name = "waitress"
+version = "2.1.2"
+description = "Waitress WSGI server"
+optional = false
+python-versions = ">=3.7.0"
+files = [
+    {file = "waitress-2.1.2-py3-none-any.whl", hash = "sha256:7500c9625927c8ec60f54377d590f67b30c8e70ef4b8894214ac6e4cad233d2a"},
+    {file = "waitress-2.1.2.tar.gz", hash = "sha256:780a4082c5fbc0fde6a2fcfe5e26e6efc1e8f425730863c04085769781f51eba"},
+]
+
+[package.extras]
+docs = ["Sphinx (>=1.8.1)", "docutils", "pylons-sphinx-themes (>=1.0.9)"]
+testing = ["coverage (>=5.0)", "pytest", "pytest-cover"]
+
 [[package]]
 name = "wcwidth"
 version = "0.2.8"
@@ -3407,6 +4000,39 @@ files = [
     {file = "wcwidth-0.2.8.tar.gz", hash = "sha256:8705c569999ffbb4f6a87c6d1b80f324bd6db952f5eb0b95bc07517f4c1813d4"},
 ]
 
+[[package]]
+name = "websocket-client"
+version = "1.6.4"
+description = "WebSocket client for Python with low level API options"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "websocket-client-1.6.4.tar.gz", hash = "sha256:b3324019b3c28572086c4a319f91d1dcd44e6e11cd340232978c684a7650d0df"},
+    {file = "websocket_client-1.6.4-py3-none-any.whl", hash = "sha256:084072e0a7f5f347ef2ac3d8698a5e0b4ffbfcab607628cadabc650fc9a83a24"},
+]
+
+[package.extras]
+docs = ["Sphinx (>=6.0)", "sphinx-rtd-theme (>=1.1.0)"]
+optional = ["python-socks", "wsaccel"]
+test = ["websockets"]
+
+[[package]]
+name = "werkzeug"
+version = "3.0.1"
+description = "The comprehensive WSGI web application library."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "werkzeug-3.0.1-py3-none-any.whl", hash = "sha256:90a285dc0e42ad56b34e696398b8122ee4c681833fb35b8334a095d82c56da10"},
+    {file = "werkzeug-3.0.1.tar.gz", hash = "sha256:507e811ecea72b18a404947aded4b3390e1db8f826b494d76550ef45bb3b1dcc"},
+]
+
+[package.dependencies]
+MarkupSafe = ">=2.1.1"
+
+[package.extras]
+watchdog = ["watchdog (>=2.3)"]
+
 [[package]]
 name = "yarl"
 version = "1.9.2"
@@ -3529,4 +4155,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 [metadata]
 lock-version = "2.0"
 python-versions = ">= 3.9, < 3.13"
-content-hash = "0342bc00755934e3708f20a4477a4ca42fc3a8f0834da73ea92d401b38a6e251"
+content-hash = "66409ad23983c1749fe99b550fc67c77e14ec77798dc3e922a35981a418c96ca"
diff --git a/pyproject.toml b/pyproject.toml
index f46551e..c78e4d3 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -14,6 +14,7 @@ scikit-learn = "^1.3.1"
 catboost = "^1.2.2"
 fire = "^0.5.0"
 hydra-core = "^1.3.2"
+mlflow = "^2.8.1"
 
 [tool.poetry.group.dev.dependencies]
 pre-commit = "^3.4.0"