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AutoML: Improve notebooks for easier usage on Google Colab #174

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Dec 4, 2023
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AutoML: Improve notebooks for easier usage on Google Colab #174

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89abd38
ML/AutoML: Reworked connection string for easier usage
ckurze Nov 30, 2023
637960d
ML/AutoML: Slight changes for requirements
ckurze Nov 30, 2023
f9658b3
ML/AutoML: Harmonize notebooks, and easier connection string handling
ckurze Nov 30, 2023
86e77a7
ML/AutoML: Increase notebook execution timeout from 240 to 300 seconds
amotl Dec 2, 2023
bb5e35a
ML/AutoML: Fix testing after streamlining the connectivity configuration
amotl Dec 4, 2023
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87 changes: 62 additions & 25 deletions topic/machine-learning/automl/automl_classification_with_pycaret.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -115,12 +115,27 @@
"source": [
"## Getting started\n",
"\n",
"First, install the required dependencies. \n",
"\n",
"```bash\n",
"pip install -r requirements.txt\n",
"```\n",
"First, install the required dependencies. "
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"#!pip install -r requirements.txt\n",
"\n",
"# In an environment like Google Colab, please use the absolute URL to the requirements.txt file.\n",
"# Note: Some inconsistencies of dependencies might get reported. They can usually be ignored.\n",
"# Restart the runtime, if asked by Colab.\n",
"#!pip install -r https://raw.githubusercontent.com/crate/cratedb-examples/main/topic/machine-learning/automl/requirements.txt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Note:** As of time of this writing, PyCaret requires Python 3.8, 3.9 or 3.10.\n",
"\n",
"Second, you will need a CrateDB instance to store and serve the data. The easiest\n",
Expand All @@ -131,31 +146,53 @@
"create an `.env` file with the following content:\n",
"\n",
"```env\n",
"CRATE_HOST=<your-crate-host> # set this to localhost if you're running crate locally\n",
"CRATE_USER=<your-crate-user> # set this to crate if you're running crate locally\n",
"CRATE_PASSWORD=<your-crate-password> # set this to \"\" if you're running crate locally\n",
"CRATE_SSL=true # set this to false if you're running crate locally\n",
"# use this string for a connection to CrateDB Cloud\n",
"CONNECTION_STRING=crate://username:password@hostname/?ssl=true \n",
"\n",
"# use this string for a local connection to CrateDB\n",
"# CONNECTION_STRING=crate://crate@localhost/?ssl=false\n",
"```\n",
"\n",
"You can find your CrateDB credentials in the [CrateDB Cloud Console].\n",
"\n",
"[CrateDB Cloud Console]: https://cratedb.com/docs/cloud/en/latest/reference/overview.html#cluster\n",
"[deploy a cluster]: https://cratedb.com/docs/cloud/en/latest/tutorials/deploy/stripe.html#deploy-cluster\n",
"\n",
"### Creating demo data\n",
"[deploy a cluster]: https://cratedb.com/docs/cloud/en/latest/tutorials/deploy/stripe.html#deploy-cluster"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"For convenience, this notebook comes with an accompanying CSV dataset which you\n",
"can quickly import into the database. Upload the CSV file to your CrateDB cloud\n",
"cluster, as described [here](https://cratedb.com/docs/cloud/en/latest/reference/overview.html#import).\n",
"To follow this notebook, choose `pycaret_churn` for your table name.\n",
"# For CrateDB Cloud, use:\n",
"CONNECTION_STRING = os.environ.get(\n",
" \"CRATEDB_CONNECTION_STRING\",\n",
" \"crate://username:password@hostname/?ssl=true\",\n",
")\n",
"\n",
"This will automatically create a new database table and import the data."
"# For an self-deployed CrateDB, e.g. via Docker, please use:\n",
"# CONNECTION_STRING = os.environ.get(\n",
"# \"CRATEDB_CONNECTION_STRING\",\n",
"# \"crate://crate@localhost/?ssl=false\",\n",
"# )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Creating demo data\n",
"\n",
"For convenience, this notebook comes with an accompanying CSV dataset which you\n",
"can quickly import into the database. Upload the CSV file to your CrateDB cloud\n",
"cluster, as described [here](https://cratedb.com/docs/cloud/en/latest/reference/overview.html#import).\n",
"To follow this notebook, choose `pycaret_churn` for your table name.\n",
"\n",
"This will automatically create a new database table and import the data.\n",
"\n",
"### Alternative data import using code\n",
"\n",
"If you prefer to use code to import your data, please execute the following lines which read the CSV\n",
Expand All @@ -175,8 +212,7 @@
"if os.path.exists(\".env\"):\n",
" dotenv.load_dotenv(\".env\", override=True)\n",
"\n",
"dburi = f\"crate://{os.environ['CRATE_USER']}:{os.environ['CRATE_PASSWORD']}@{os.environ['CRATE_HOST']}:4200?ssl={os.environ['CRATE_SSL']}\"\n",
"engine = sa.create_engine(dburi, echo=os.environ.get('DEBUG'))\n",
"engine = sa.create_engine(CONNECTION_STRING, echo=os.environ.get('DEBUG'))\n",
"df = pd.read_csv(\"https://github.com/crate/cratedb-datasets/raw/main/machine-learning/automl/churn-dataset.csv\")\n",
"\n",
"with engine.connect() as conn:\n",
Expand Down Expand Up @@ -214,8 +250,7 @@
"if os.path.exists(\".env\"):\n",
" dotenv.load_dotenv(\".env\", override=True)\n",
"\n",
"dburi = f\"crate://{os.environ['CRATE_USER']}:{os.environ['CRATE_PASSWORD']}@{os.environ['CRATE_HOST']}:4200?ssl={os.environ['CRATE_SSL']}\"\n",
"engine = sa.create_engine(dburi, echo=os.environ.get('DEBUG'))\n",
"engine = sa.create_engine(CONNECTION_STRING, echo=os.environ.get('DEBUG'))\n",
"\n",
"with engine.connect() as conn:\n",
" with conn.execute(sa.text(\"SELECT * FROM pycaret_churn\")) as cursor:\n",
Expand All @@ -224,7 +259,7 @@
"# We set the MLFLOW_TRACKING_URI to our CrateDB instance. We'll see later why\n",
"os.environ[\n",
" \"MLFLOW_TRACKING_URI\"\n",
"] = f\"{dburi}&schema=mlflow\""
"] = f\"{CONNECTION_STRING}&schema=mlflow\""
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The same would apply here, but on the other notebook, the error doesn't happen?

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Oh well, it does.

============= short test summary info =============
FAILED test.py::test_notebook[automl_timeseries_forecasting_with_pycaret.ipynb] - nbclient.exceptions.CellTimeoutError: A cell timed out while it was being executed, after 300 seconds.
FAILED test.py::test_notebook[automl_classification_with_pycaret.ipynb] - nbclient.exceptions.CellTimeoutError: A cell timed out while it was being executed, after 300 seconds.
============= 2 failed, 2 passed, 62 warnings in 880.39s (0:14:40) =============

]
},
{
Expand Down Expand Up @@ -966,8 +1001,10 @@
"# - \"n_select\" defines how many models are selected.\n",
"# - \"exclude\" defines which models are excluded from the comparison.\n",
"\n",
"# Note: This is only relevant if we are executing automated tests\n",
"if \"PYTEST_CURRENT_TEST\" in os.environ:\n",
" best_models = compare_models(sort=\"AUC\", include=[\"lr\", \"knn\"], n_select=3)\n",
"# If we are not in an automated test, compare the available models\n",
"else:\n",
" # For production scenarios, it might be worth to include \"lightgbm\" again.\n",
" best_models = compare_models(sort=\"AUC\", exclude=[\"lightgbm\"], n_select=3)"
Expand Down Expand Up @@ -3406,7 +3443,7 @@
"source": [
"os.environ[\n",
" \"MLFLOW_TRACKING_URI\"\n",
"] = f\"crate://{os.environ['CRATE_USER']}:{os.environ['CRATE_PASSWORD']}@{os.environ['CRATE_HOST']}:4200?ssl={os.environ['CRATE_SSL']}&schema=mlflow\""
"] = f\"{CONNECTION_STRING}&schema=mlflow\""
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Dito.

]
},
{
Expand Down Expand Up @@ -3484,7 +3521,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "crate",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
Expand All @@ -3498,7 +3535,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.0"
"version": "3.11.4"
}
},
"nbformat": 4,
Expand Down
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