From 825bccd1658a919c60724af7ce0011bb7bcba408 Mon Sep 17 00:00:00 2001 From: ryanSoley Date: Mon, 17 Jun 2024 15:07:45 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20capitalo?= =?UTF-8?q?ne/rubicon-ml@70a15342ed65b41b6e8abfd5464998c86cf4be39=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .buildinfo | 2 +- .../integration-prefect-workflows.ipynb.txt | 1510 +++++++++++++---- api_reference.html | 22 +- contribute-schema.html | 6 +- contributing.html | 6 +- faqs.html | 6 +- genindex.html | 6 +- glossary.html | 6 +- index.html | 6 +- integrations/integration-git.html | 6 +- .../integration-prefect-workflows.html | 833 ++++++--- .../integration-prefect-workflows.ipynb | 1510 +++++++++++++---- integrations/integration-sklearn.html | 6 +- logging-examples/log-with-schema.html | 6 +- logging-examples/logging-concurrently.html | 6 +- .../logging-experiment-failures.html | 6 +- logging-examples/logging-feature-plots.html | 6 +- logging-examples/logging-plots.html | 6 +- .../logging-training-metadata.html | 6 +- .../manage-experiment-relationships.html | 6 +- logging-examples/multiple-backend.html | 6 +- logging-examples/register-custom-schema.html | 6 +- logging-examples/rubiconJSON-querying.html | 6 +- logging-examples/set-schema.html | 6 +- logging-examples/tagging.html | 6 +- .../visualizing-logged-dataframes.html | 6 +- objects.inv | Bin 7825 -> 7796 bytes py-modindex.html | 6 +- quick-look/logging-experiments.html | 6 +- quick-look/sharing-experiments.html | 6 +- quick-look/visualizing-experiments.html | 6 +- schema-representation.html | 6 +- search.html | 6 +- searchindex.js | 2 +- tutorials/failure-modes.html | 6 +- visualizations.html | 6 +- visualizations/dashboard.html | 6 +- visualizations/dataframe-plot.html | 6 +- visualizations/experiments-table.html | 6 +- visualizations/metric-correlation-plot.html | 6 +- visualizations/metric-lists-comparisons.html | 6 +- 41 files changed, 3008 insertions(+), 1075 deletions(-) diff --git a/.buildinfo b/.buildinfo index 3c26b837..d2a36872 100644 --- a/.buildinfo +++ b/.buildinfo @@ -1,4 +1,4 @@ # Sphinx build info version 1 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: 5b25f2df92cddedc41025700c107d7a4 +config: 16f37f496281599e7b4d3181c507bc5d tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/_sources/integrations/integration-prefect-workflows.ipynb.txt b/_sources/integrations/integration-prefect-workflows.ipynb.txt index 3140a17d..4c7d029a 100644 --- a/_sources/integrations/integration-prefect-workflows.ipynb.txt +++ b/_sources/integrations/integration-prefect-workflows.ipynb.txt @@ -158,20 +158,21 @@ "metadata": {}, "outputs": [], "source": [ - "from prefect import Flow\n", + "from prefect import flow\n", "\n", "\n", "n_components = 2\n", "n_neighbors = 5\n", "is_standardized = True\n", "\n", - "with Flow(\"Wine Classification\") as flow:\n", + "@flow\n", + "def wine_flow():\n", " wine_dataset = load_data()\n", " \n", " feature_names = get_feature_names(wine_dataset)\n", " train_test_split = split_data(wine_dataset)\n", " \n", - " accuracy = fit_pred_model(\n", + " return fit_pred_model(\n", " train_test_split,\n", " n_components,\n", " n_neighbors,\n", @@ -185,15 +186,7 @@ "source": [ "### Running a flow and viewing results\n", "\n", - "Now we'll register our **flow** with the local server. First, we'll have to\n", - "use the ``prefect`` CLI one more time to create a project.\n", - "\n", - "```bash\n", - "prefect create project 'Wine Classification'\n", - "```\n", - "\n", - "The URL printed from the call to ``flow.register`` opens the local Prefect UI.\n", - "We can use it to run and monitor our **flows**. " + "Now we'll run the flow." ] }, { @@ -202,114 +195,207 @@ "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Flow URL: http://localhost:8080/default/flow/aef9fb65-c49b-4c46-89be-e31c357a165e\n", - " └── ID: 531ffe8c-fb2b-4855-b5d8-f9bcef51ad2d\n", - " └── Project: Wine Classification\n", - " └── Labels: ['8c859084633f']\n" - ] - } - ], - "source": [ - "flow_id = flow.register(project_name=\"Wine Classification\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We'll also put together a function to run our **flows** and wait for them to finish." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ + "data": { + "text/html": [ + "
00:56:44.598 | INFO    | prefect.engine - Created flow run 'rugged-pony' for flow 'wine-flow'\n",
+       "
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00:56:45.890 | INFO    | prefect.engine - Created flow run 'laughing-newt' for flow 'rubicon-wine-flow'\n",
+       "
\n" + ], + "text/plain": [ + "00:56:45.890 | \u001b[36mINFO\u001b[0m | prefect.engine - Created flow run\u001b[35m 'laughing-newt'\u001b[0m for flow\u001b[1;35m 'rubicon-wine-flow'\u001b[0m\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "experiment 6b1c3846-5aab-4bda-8c16-15b279d8616c\n", - "features: ['alcalinity_of_ash', 'alcohol', 'ash', 'color_intensity', 'flavanoids', 'hue', 'magnesium', 'malic_acid', 'nonflavanoid_phenols', 'od280/od315_of_diluted_wines', 'proanthocyanins', 'proline', 'total_phenols']\n", - "parameters: [('is_standardized', True), ('n_components', 2), ('n_neighbors', 5)]\n", - "metrics: [('accuracy', 1.0)]\n" - ] - } - ], - "source": [ - "from rubicon_ml import Rubicon\n", - "\n", - "\n", - "rubicon = Rubicon(persistence=\"filesystem\", root_dir=root_path)\n", - "project = rubicon.get_project(\"Wine Classification with Prefect\")\n", - " \n", - "experiment = project.experiments()[0]\n", - "\n", - "features = [f.name for f in experiment.features()]\n", - "parameters = [(p.name, p.value) for p in experiment.parameters()]\n", - "metrics = [(m.name, m.value) for m in experiment.metrics()]\n", - "\n", - "print(\n", - " f\"experiment {experiment.id}\\n\"\n", - " f\"features: {features}\\nparameters: {parameters}\\n\"\n", - " f\"metrics: {metrics}\"\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Extracting data from ``rubicon_ml`` is much simpler than pulling it from the various\n", - "**tasks** as they succeed. Especially in the case where we're running thousands\n", - "of **tasks** in a **flow**.\n", - "\n", - "### Concurrent Logging with Dask\n", - "\n", - "Prefect plays nicely with Dask in order to provide parallel computing when possible.\n", - "The Prefect scheduler is smart enough to know which **tasks** do and do not depend\n", - "on each other, so it can intelligently decide when to run independent **tasks** at\n", - "the same time.\n", - "\n", - "Let's run the same **flow** as above, except this time we'll log eight different\n", - "experiments with eight different feature sets and accuracy results. First, we'll\n", - "need to use Dask to start a local cluster." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "import dask.distributed\n", - "from prefect.executors import DaskExecutor\n", - "\n", - "\n", - "dask_client = dask.distributed.Client()\n", - "dask_executor = DaskExecutor(address=dask_client.cluster.scheduler.address)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Before we look at the new **flow**, let's see how easy it is to make our own \n", - "``rubicon_ml`` Prefect **tasks**. Currently, the ``log_feature_task`` logs one \n", - "feature to one experiment. Let's say in this example, we want to log our entire\n", - "feature set in one **task**. That's slightly different than what we currently\n", - "have in the ``log_feature_task``, so let's see how we can make a new one using\n", - "the ``rubicon_ml`` logging library." - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "@task\n", - "def log_feature_set(experiment, feature_names):\n", - " \"\"\"log a set of features to a rubicon experiment\n", - " \n", - " Parameters\n", - " ----------\n", - " experiment : rubicon.Experiment\n", - " the experiment to log the feature set to\n", - " feature_names : list of str\n", - " the names of the features to log to `experiment`\n", - " \"\"\"\n", - " features = []\n", - " \n", - " for name in feature_names:\n", - " features.append(experiment.log_feature(name=name))\n", - " \n", - " return features" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Easy! Even though its so simple, this particular **task** is actually more in-depth\n", - "than the ones you'll find in the library. The Prefect **tasks** in the library are\n", - "simply wrappers around existing logging library functions, like ``experiment.log_feature``.\n", - "\n", - "Now we can make our new **flow** to log multiple experiments in parallel." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "n_components = [2, 2, 2, 2, 4, 4, 4, 4 ]\n", - "n_neighbors = [5, 5, 10, 10, 5, 5, 10, 10 ]\n", - "is_standardized = [True, False, True, False, True, False, True, False]\n", - "\n", - "experiment_names = [f\"mapped run {i}\" for i in range(len(n_components))]\n", - "\n", - "with Flow(\n", - " \"Wine Classification with Rubicon - Mapped\",\n", - " executor=dask_executor,\n", - ") as mapped_flow:\n", - " project = get_or_create_project_task(\n", - " \"filesystem\",\n", - " root_path,\n", - " \"Wine Classification with Prefect - Mapped\",\n", - " )\n", - " experiments = create_experiment_task.map(\n", - " unmapped(project),\n", - " name=experiment_names,\n", - " description=unmapped(\"concurrent example with Prefect\"),\n", - " )\n", - " \n", - " wine_dataset = load_data()\n", - " \n", - " feature_names = get_feature_names(wine_dataset)\n", - " train_test_split = split_data(wine_dataset)\n", - " \n", - " log_feature_set.map(experiments, unmapped(feature_names))\n", - " log_parameter_task.map(experiments, unmapped(\"n_components\"), n_components)\n", - " log_parameter_task.map(experiments, unmapped(\"n_neighbors\"), n_neighbors)\n", - " log_parameter_task.map(experiments, unmapped(\"is_standardized\"), is_standardized)\n", - " \n", - " accuracies = fit_pred_model.map(\n", - " unmapped(train_test_split),\n", - " n_components,\n", - " n_neighbors,\n", - " is_standardized,\n", - " )\n", - " \n", - " log_metric_task.map(experiments, unmapped(\"accuracy\"), accuracies)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let's register and run one last **flow**. If you check out the timeline for your completed\n", - "**flows** on the UI linked by `mapped_flow.register`, you'll notice tasks executing at the same\n", - "time now." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ + "data": { + "text/html": [ + "
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00:56:46.311 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-12' for task 'log_feature_task'\n",
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\n" + ], + "text/plain": [ + "00:56:46.724 | \u001b[36mINFO\u001b[0m | Task run 'log_feature_task-1' - Finished in state \u001b[32mCompleted\u001b[0m()\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
00:56:46.749 | INFO    | Task run 'log_parameter_task-2' - Finished in state Completed()\n",
+       "
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00:56:46.761 | INFO    | Flow run 'laughing-newt' - Created task run 'fit_pred_model-0' for task 'fit_pred_model'\n",
+       "
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00:56:46.761 | INFO    | Flow run 'laughing-newt' - Executing 'fit_pred_model-0' immediately...\n",
+       "
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00:56:46.771 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-2' for task 'log_feature_task'\n",
+       "
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00:56:46.772 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-2' for execution.\n",
+       "
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00:56:46.817 | INFO    | Task run 'fit_pred_model-0' - Finished in state Completed()\n",
+       "
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00:56:46.839 | INFO    | Flow run 'laughing-newt' - Created task run 'log_metric_task-0' for task 'log_metric_task'\n",
+       "
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00:56:46.840 | INFO    | Flow run 'laughing-newt' - Executing 'log_metric_task-0' immediately...\n",
+       "
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+       "
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+       "
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+       "
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00:56:46.971 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-5' for task 'log_feature_task'\n",
+       "
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00:56:46.972 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-5' for execution.\n",
+       "
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+       "
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+       "
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00:56:47.084 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-9' for execution.\n",
+       "
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+       "
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00:56:47.152 | INFO    | Flow run 'laughing-newt' - Finished in state Completed()\n",
+       "
\n" + ], + "text/plain": [ + "00:56:47.152 | \u001b[36mINFO\u001b[0m | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Finished in state \u001b[32mCompleted\u001b[0m()\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "1.0" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "flow_with_concurrent_rubicon_id = mapped_flow.register(\n", - " project_name=\"Wine Classification\",\n", - ")\n", - "flow_run_with_concurrent_rubicon_id = run_flow(\n", - " prefect_client,\n", - " flow_with_concurrent_rubicon_id,\n", - ")" + "accuracy = rubicon_wine_flow()\n", + "accuracy" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Retrieving all the results of a mapped **task** is even more cumbersome than\n", - "retrieving just the accuracy above. We'll simply use the ``rubicon_ml`` Dashboard to\n", - "check out all the data we just logged!" + "This time we can use ``rubicon_ml`` to inspect our accuracy, among other things!" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 10, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " * Running on http://127.0.0.1:8050/ (Press CTRL+C to quit)\n", - "127.0.0.1 - - [16/Apr/2021 15:29:39] \"\u001b[37mGET /_alive_71180c28-37bc-4127-a50b-e754fe3e6812 HTTP/1.1\u001b[0m\" 200 -\n" - ] - }, { "name": "stdout", "output_type": "stream", "text": [ - "Dash app running on http://127.0.0.1:8050/\n" + "experiment 35173154-a912-4ed0-9920-188d62e6f3d2\n", + "features: ['proline', 'proanthocyanins', 'flavanoids', 'alcalinity_of_ash', 'nonflavanoid_phenols', 'hue', 'alcohol', 'od280/od315_of_diluted_wines', 'malic_acid', 'ash', 'magnesium', 'total_phenols', 'color_intensity']\n", + "parameters: [('n_components', 2), ('n_neighbors', 5), ('is_standardized', True)]\n", + "metrics: [('accuracy', 1.0)]\n" ] } ], "source": [ - "from rubicon_ml.viz import Dashboard\n", + "from rubicon_ml import Rubicon\n", "\n", "\n", - "project = get_project(\n", - " \"filesystem\",\n", - " root_path,\n", - " \"Wine Classification with Prefect - Mapped\",\n", - ")\n", + "rubicon = Rubicon(persistence=\"memory\", root_dir=\".\")\n", + "project = rubicon.get_project(\"Wine Classification with Prefect\")\n", + " \n", + "experiment = project.experiments()[0]\n", + "\n", + "features = [f.name for f in experiment.features()]\n", + "parameters = [(p.name, p.value) for p in experiment.parameters()]\n", + "metrics = [(m.name, m.value) for m in experiment.metrics()]\n", "\n", - "Dashboard(project.experiments()).show()" + "print(\n", + " f\"experiment {experiment.id}\\n\"\n", + " f\"features: {features}\\nparameters: {parameters}\\n\"\n", + " f\"metrics: {metrics}\"\n", + ")" ] } ], @@ -676,7 +1466,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.4" + "version": "3.12.3" } }, "nbformat": 4, diff --git a/api_reference.html b/api_reference.html index af772c6b..1254d145 100644 --- a/api_reference.html +++ b/api_reference.html @@ -6,7 +6,7 @@ - API Reference - rubicon-ml v0.7.4 + API Reference - rubicon-ml v0.8.0 @@ -181,7 +181,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
@@ -209,7 +209,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
@@ -209,7 +209,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
 diff --git a/contributing.html b/contributing.html index caf326e3..51baeb57 100644 --- a/contributing.html +++ b/contributing.html @@ -6,7 +6,7 @@ - Contributing - rubicon-ml v0.7.4 + Contributing - rubicon-ml v0.8.0 @@ -181,7 +181,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
@@ -209,7 +209,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
 diff --git a/faqs.html b/faqs.html index 2506948f..fae0b785 100644 --- a/faqs.html +++ b/faqs.html @@ -6,7 +6,7 @@ - FAQs - rubicon-ml v0.7.4 + FAQs - rubicon-ml v0.8.0 @@ -181,7 +181,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
@@ -209,7 +209,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
 diff --git a/genindex.html b/genindex.html index aa0622de..adc21d70 100644 --- a/genindex.html +++ b/genindex.html @@ -4,7 +4,7 @@ - Index - rubicon-ml v0.7.4 + Index - rubicon-ml v0.8.0 @@ -179,7 +179,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
@@ -207,7 +207,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
 diff --git a/glossary.html b/glossary.html index 8ef78fc6..038c8721 100644 --- a/glossary.html +++ b/glossary.html @@ -6,7 +6,7 @@ - Glossary - rubicon-ml v0.7.4 + Glossary - rubicon-ml v0.8.0 @@ -181,7 +181,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
@@ -209,7 +209,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
 diff --git a/index.html b/index.html index e95c4fd3..8702ccd6 100644 --- a/index.html +++ b/index.html @@ -6,7 +6,7 @@ - rubicon-ml v0.7.4 + rubicon-ml v0.8.0 @@ -181,7 +181,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
@@ -209,7 +209,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
 diff --git a/integrations/integration-git.html b/integrations/integration-git.html index c006b347..9718d003 100644 --- a/integrations/integration-git.html +++ b/integrations/integration-git.html @@ -6,7 +6,7 @@ - Integrate with Git - rubicon-ml v0.7.4 + Integrate with Git - rubicon-ml v0.8.0 @@ -182,7 +182,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
@@ -210,7 +210,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
 diff --git a/integrations/integration-prefect-workflows.html b/integrations/integration-prefect-workflows.html index 3224990c..326c3814 100644 --- a/integrations/integration-prefect-workflows.html +++ b/integrations/integration-prefect-workflows.html @@ -6,7 +6,7 @@ - Integrate with Prefect - rubicon-ml v0.7.4 + Integrate with Prefect - rubicon-ml v0.8.0 @@ -182,7 +182,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
@@ -210,7 +210,7 @@
-
rubicon-ml v0.7.4
 +
rubicon-ml v0.8.0
 @@ -436,20 +436,21 @@

Setting up a simple flow
[6]:

-
from prefect import Flow
+
from prefect import flow
 
 
 n_components = 2
 n_neighbors = 5
 is_standardized = True
 
-with Flow("Wine Classification") as flow:
+@flow
+def wine_flow():
     wine_dataset = load_data()
 
     feature_names = get_feature_names(wine_dataset)
     train_test_split = split_data(wine_dataset)
 
-    accuracy = fit_pred_model(
+    return fit_pred_model(
         train_test_split,
         n_components,
         n_neighbors,
@@ -461,107 +462,130 @@ 
Setting up a simple flow
 
Running a flow and viewing results

-
Now we’ll register our flow with the local server. First, we’ll have to use the prefect CLI one more time to create a project.

-
prefect create project 'Wine Classification'
-

-

-
The URL printed from the call to flow.register opens the local Prefect UI. We can use it to run and monitor our flows.

+
Now we’ll run the flow.

 

 
[7]:
 

 

-
flow_id = flow.register(project_name="Wine Classification")
+
accuracy = wine_flow()
+accuracy
 

 

 

-

+

 

 

-

-
-Flow URL: http://localhost:8080/default/flow/aef9fb65-c49b-4c46-89be-e31c357a165e
- └── ID: 531ffe8c-fb2b-4855-b5d8-f9bcef51ad2d
- └── Project: Wine Classification
- └── Labels: ['8c859084633f']
-

+

+
00:56:44.598 | INFO    | prefect.engine - Created flow run 'rugged-pony' for flow 'wine-flow'
+

 

-
We’ll also put together a function to run our flows and wait for them to finish.

-

-
[8]:
+

+

+

+

+
00:56:44.646 | INFO    | Flow run 'rugged-pony' - Created task run 'load_data-0' for task 'load_data'
 

 

-
import time
-from prefect import Client
-
-
-prefect_client = Client()
-
-def run_flow(client, flow_id):
-    flow_run_id = client.create_flow_run(flow_id=flow_id)
-
-    is_finished = False
-    while not is_finished:
-        state = client.get_flow_run_info(flow_run_id).state
-        print(f"{state.message.strip('.')}. Waiting...")
-
-        time.sleep(3)
-
-        is_finished = state.is_finished()
-
-    assert state.is_successful()
-    print(f"Flow run {flow_run_id} was successful!")
-
-    return flow_run_id
-
-flow_run_id = run_flow(prefect_client, flow_id)
+

+

+

+

+
00:56:44.647 | INFO    | Flow run 'rugged-pony' - Executing 'load_data-0' immediately...
 

 

+

+

 

-

+

+
00:56:45.352 | INFO    | Task run 'load_data-0' - Finished in state Completed()
+

+

+

 

 

-

-
-Flow run scheduled. Waiting...
-Flow run scheduled. Waiting...
-All reference tasks succeeded. Waiting...
-Flow run 024457a5-aac4-449a-a5a3-7b3986f90cba was successful!
-

+

+
00:56:45.372 | INFO    | Flow run 'rugged-pony' - Created task run 'get_feature_names-0' for task 'get_feature_names'
+

 

-
We assigned a few variables in our flow, most notably the result of fit_pred_model, accuracy. This accuracy metric is how we’ll determine whether or not the model we trained is a success. However, retrieving state variables from flows is a bit cumbersome.

-

-
[9]:
+

+

+

+

+
00:56:45.373 | INFO    | Flow run 'rugged-pony' - Executing 'get_feature_names-0' immediately...
 

 

-
info = prefect_client.get_flow_run_info(flow_run_id)
-
-slugs = [t.task_slug for t in info.task_runs]
-index = slugs.index(accuracy.slug)
-
-result = info.task_runs[index].state._result.read(
-    info.task_runs[index].state._result.location,
-)
-result.value
+

+

+

+

+
00:56:45.423 | INFO    | Task run 'get_feature_names-0' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:45.440 | INFO    | Flow run 'rugged-pony' - Created task run 'split_data-0' for task 'split_data'
+

+

+

+

+

+

+
00:56:45.441 | INFO    | Flow run 'rugged-pony' - Executing 'split_data-0' immediately...
+

+

+

+

+

+

+
00:56:45.547 | INFO    | Task run 'split_data-0' - Finished in state Completed()
 

 

+

+

+

+

+
00:56:45.566 | INFO    | Flow run 'rugged-pony' - Created task run 'fit_pred_model-0' for task 'fit_pred_model'
+

+

+

+

+

+

+
00:56:45.567 | INFO    | Flow run 'rugged-pony' - Executing 'fit_pred_model-0' immediately...
+

+

+

+

+

+

+
00:56:45.693 | INFO    | Task run 'fit_pred_model-0' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:45.719 | INFO    | Flow run 'rugged-pony' - Finished in state Completed()
+

 

 

-
[9]:
+
[7]:
 

 

 

 
-0.9555555555555556
+0.9333333333333333
 

 

-
What’s going on here isn’t exactly intuitive, and all that only extracted one piece of data from one task.

 
 

 
Adding Rubicon to your flow

 
We can leverage the Prefect tasks within the rubicon_ml library to log all the info we want about our model run. Then, we can use the standard rubicon_ml logging library to retrieve and inspect our metrics and other logged data. This is much simpler than digging through the state of each executed task and extracting its results.

 
Here’s the same flow from above, this time with rubicon_ml tasks integrated.

 

-
[10]:
+
[8]:
 

 

 
import os
@@ -569,17 +593,15 @@ 
Adding Rubicon to your flowfrom prefect import unmapped
 
 
-root_dir = os.environ.get("RUBICON_ROOT", "rubicon-root")
-root_path = f"{os.path.dirname(os.getcwd())}/{root_dir}"
-
 n_components = 2
 n_neighbors = 5
 is_standardized = True
 
-with Flow("Wine Classification with Rubicon") as flow:
+@flow
+def rubicon_wine_flow():
     project = get_or_create_project_task(
-        "filesystem",
-        root_path,
+        "memory",
+        ".",
         "Wine Classification with Prefect",
     )
     experiment = create_experiment_task(
@@ -604,229 +626,561 @@ 
Adding Rubicon to your flow)
 
     log_metric_task(experiment, "accuracy", accuracy)
+
+    return accuracy
 

 

 

 
Again, we’ll register and run the flow.

 

-
[11]:
+
[9]:
 

 

-
flow_with_rubicon_id = flow.register(project_name="Wine Classification")
-flow_run_with_rubicon_id = run_flow(prefect_client, flow_with_rubicon_id)
+
accuracy = rubicon_wine_flow()
+accuracy
 

 

 

-

+

 

 

-

-
-Flow URL: http://localhost:8080/default/flow/9b91bafc-7e8b-4361-b1d0-bc57dac4cebc
- └── ID: 081b9522-5db8-4ce6-ae64-ea8afd5b323e
- └── Project: Wine Classification
- └── Labels: ['8c859084633f']
-Flow run scheduled. Waiting...
-Submitted for execution. Waiting...
-Running flow. Waiting...
-All reference tasks succeeded. Waiting...
-Flow run 29cef175-c115-4da2-a9f7-40f79bdb6104 was successful!
-

+

+
00:56:45.890 | INFO    | prefect.engine - Created flow run 'laughing-newt' for flow 'rubicon-wine-flow'
+

 

-
This time we can use rubicon_ml to inspect our accuracy, among other things!

-

-
[12]:
+

+

+

+

+
00:56:45.942 | INFO    | Flow run 'laughing-newt' - Created task run 'get_or_create_project_task-0' for task 'get_or_create_project_task'
 

 

-
from rubicon_ml import Rubicon
-
-
-rubicon = Rubicon(persistence="filesystem", root_dir=root_path)
-project = rubicon.get_project("Wine Classification with Prefect")
-
-experiment = project.experiments()[0]
-
-features = [f.name for f in experiment.features()]
-parameters = [(p.name, p.value) for p in experiment.parameters()]
-metrics = [(m.name, m.value) for m in experiment.metrics()]
-
-print(
-    f"experiment {experiment.id}\n"
-    f"features: {features}\nparameters: {parameters}\n"
-    f"metrics: {metrics}"
-)
+

+

+

+

+
00:56:45.943 | INFO    | Flow run 'laughing-newt' - Executing 'get_or_create_project_task-0' immediately...
 

 

+

+

 

-

+

+
00:56:45.995 | INFO    | Task run 'get_or_create_project_task-0' - Finished in state Completed()
+

+

+

 

 

-

-
-experiment 6b1c3846-5aab-4bda-8c16-15b279d8616c
-features: ['alcalinity_of_ash', 'alcohol', 'ash', 'color_intensity', 'flavanoids', 'hue', 'magnesium', 'malic_acid', 'nonflavanoid_phenols', 'od280/od315_of_diluted_wines', 'proanthocyanins', 'proline', 'total_phenols']
-parameters: [('is_standardized', True), ('n_components', 2), ('n_neighbors', 5)]
-metrics: [('accuracy', 1.0)]
-

+

+
00:56:46.011 | INFO    | Flow run 'laughing-newt' - Created task run 'create_experiment_task-0' for task 'create_experiment_task'
+

 

-
Extracting data from rubicon_ml is much simpler than pulling it from the various tasks as they succeed. Especially in the case where we’re running thousands of tasks in a flow.

-

-

-
Concurrent Logging with Dask

-
Prefect plays nicely with Dask in order to provide parallel computing when possible. The Prefect scheduler is smart enough to know which tasks do and do not depend on each other, so it can intelligently decide when to run independent tasks at the same time.

-
Let’s run the same flow as above, except this time we’ll log eight different experiments with eight different feature sets and accuracy results. First, we’ll need to use Dask to start a local cluster.

-

-
[13]:
+

+

+

+

+
00:56:46.012 | INFO    | Flow run 'laughing-newt' - Executing 'create_experiment_task-0' immediately...
 

 

-
import dask.distributed
-from prefect.executors import DaskExecutor
-
-
-dask_client = dask.distributed.Client()
-dask_executor = DaskExecutor(address=dask_client.cluster.scheduler.address)
+

+

+

+

+
00:56:46.052 | INFO    | Task run 'create_experiment_task-0' - Finished in state Completed()
 

 

+

+

 

-
Before we look at the new flow, let’s see how easy it is to make our own rubicon_ml Prefect tasks. Currently, the log_feature_task logs one feature to one experiment. Let’s say in this example, we want to log our entire feature set in one task. That’s slightly different than what we currently have in the log_feature_task, so let’s see how we can make a new one using the rubicon_ml logging library.

-

-
[14]:
+

+
00:56:46.068 | INFO    | Flow run 'laughing-newt' - Created task run 'load_data-0' for task 'load_data'
 

 

-
@task
-def log_feature_set(experiment, feature_names):
-    """log a set of features to a rubicon experiment
-
-    Parameters
-    ----------
-    experiment : rubicon.Experiment
-        the experiment to log the feature set to
-    feature_names : list of str
-        the names of the features to log to `experiment`
-    """
-    features = []
-
-    for name in feature_names:
-        features.append(experiment.log_feature(name=name))
-
-    return features
+

+

+

+

+
00:56:46.069 | INFO    | Flow run 'laughing-newt' - Executing 'load_data-0' immediately...
 

 

+

+

 

-
Easy! Even though its so simple, this particular task is actually more in-depth than the ones you’ll find in the library. The Prefect tasks in the library are simply wrappers around existing logging library functions, like experiment.log_feature.

-
Now we can make our new flow to log multiple experiments in parallel.

-

-
[15]:
+

+
00:56:46.112 | INFO    | Task run 'load_data-0' - Finished in state Completed()
 

 

-
n_components =    [2,    2,     2,    2,     4,    4,     4,    4    ]
-n_neighbors =     [5,    5,     10,   10,    5,    5,     10,   10   ]
-is_standardized = [True, False, True, False, True, False, True, False]
-
-experiment_names = [f"mapped run {i}" for i in range(len(n_components))]
-
-with Flow(
-    "Wine Classification with Rubicon - Mapped",
-    executor=dask_executor,
-) as mapped_flow:
-    project = get_or_create_project_task(
-        "filesystem",
-        root_path,
-        "Wine Classification with Prefect - Mapped",
-    )
-    experiments = create_experiment_task.map(
-        unmapped(project),
-        name=experiment_names,
-        description=unmapped("concurrent example with Prefect"),
-    )
-
-    wine_dataset = load_data()
-
-    feature_names = get_feature_names(wine_dataset)
-    train_test_split = split_data(wine_dataset)
-
-    log_feature_set.map(experiments, unmapped(feature_names))
-    log_parameter_task.map(experiments, unmapped("n_components"), n_components)
-    log_parameter_task.map(experiments, unmapped("n_neighbors"), n_neighbors)
-    log_parameter_task.map(experiments, unmapped("is_standardized"), is_standardized)
-
-    accuracies = fit_pred_model.map(
-        unmapped(train_test_split),
-        n_components,
-        n_neighbors,
-        is_standardized,
-    )
-
-    log_metric_task.map(experiments, unmapped("accuracy"), accuracies)
+

+

+

+

+
00:56:46.129 | INFO    | Flow run 'laughing-newt' - Created task run 'get_feature_names-0' for task 'get_feature_names'
 

 

+

+

 

-
Let’s register and run one last flow. If you check out the timeline for your completed flows on the UI linked by mapped_flow.register, you’ll notice tasks executing at the same time now.

-

-
[16]:
+

+
00:56:46.129 | INFO    | Flow run 'laughing-newt' - Executing 'get_feature_names-0' immediately...
 

 

-
flow_with_concurrent_rubicon_id = mapped_flow.register(
-    project_name="Wine Classification",
-)
-flow_run_with_concurrent_rubicon_id = run_flow(
-    prefect_client,
-    flow_with_concurrent_rubicon_id,
-)
+

+

+

+

+
00:56:46.168 | INFO    | Task run 'get_feature_names-0' - Finished in state Completed()
 

 

+

+

 

-

+

+
00:56:46.184 | INFO    | Flow run 'laughing-newt' - Created task run 'split_data-0' for task 'split_data'
+

+

+

+

+

+

+
00:56:46.185 | INFO    | Flow run 'laughing-newt' - Executing 'split_data-0' immediately...
+

+

+

+

+

+

+
00:56:46.232 | INFO    | Task run 'split_data-0' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.311 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-12' for task 'log_feature_task'
+

+

+

+

+

+

+
00:56:46.312 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-12' for execution.
+

+

+

+

+

+

+
00:56:46.322 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-7' for task 'log_feature_task'
+

+

+

+

+

+

+
00:56:46.323 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-7' for execution.
+

+

+

+

+

+

+
00:56:46.334 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-8' for task 'log_feature_task'
+

+

+

+

+

+

+
00:56:46.335 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-8' for execution.
+

+

+

+

+

+

+
00:56:46.356 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-6' for task 'log_feature_task'
+

+

+

+

+

+

+
00:56:46.357 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-6' for execution.
+

+

+

+

+

+

+
00:56:46.399 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-3' for task 'log_feature_task'
+

+

+

+

+

+

+
00:56:46.400 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-3' for execution.
+

+

+

+

+

+

+
00:56:46.417 | INFO    | Task run 'log_feature_task-12' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.425 | INFO    | Task run 'log_feature_task-8' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.444 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-10' for task 'log_feature_task'
+

+

+

+

+

+

+
00:56:46.445 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-10' for execution.
+

+

+

+

+

+

+
00:56:46.459 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-4' for task 'log_feature_task'
+

+

+

+

+

+

+
00:56:46.461 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-4' for execution.
+

+

+

+

+

+

+
00:56:46.499 | INFO    | Task run 'log_feature_task-6' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.508 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-0' for task 'log_feature_task'
+

+

+

+

+

+

+
00:56:46.509 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-0' for execution.
+

+

+

+

+

+

+
00:56:46.524 | INFO    | Task run 'log_feature_task-7' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.543 | INFO    | Task run 'log_feature_task-10' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.556 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-11' for task 'log_feature_task'
+

+

+

+

+

+

+
00:56:46.557 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-11' for execution.
+

+

+

+

+

+

+
00:56:46.567 | INFO    | Flow run 'laughing-newt' - Created task run 'log_parameter_task-0' for task 'log_parameter_task'
+

+

+

+

+

+

+
00:56:46.568 | INFO    | Flow run 'laughing-newt' - Executing 'log_parameter_task-0' immediately...
+

+

+

+

+

+

+
00:56:46.612 | INFO    | Task run 'log_feature_task-11' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.620 | INFO    | Task run 'log_feature_task-3' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.627 | INFO    | Task run 'log_parameter_task-0' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.640 | INFO    | Flow run 'laughing-newt' - Created task run 'log_parameter_task-1' for task 'log_parameter_task'
+

+

+

+

+

+

+
00:56:46.641 | INFO    | Flow run 'laughing-newt' - Executing 'log_parameter_task-1' immediately...
+

+

+

+

+

+

+
00:56:46.651 | INFO    | Task run 'log_feature_task-0' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.668 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-1' for task 'log_feature_task'
+

+

+

+

+

+

+
00:56:46.669 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-1' for execution.
+

+

+

+

+

+

+
00:56:46.696 | INFO    | Task run 'log_parameter_task-1' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.713 | INFO    | Flow run 'laughing-newt' - Created task run 'log_parameter_task-2' for task 'log_parameter_task'
+

+

+

 

 

+

+
00:56:46.714 | INFO    | Flow run 'laughing-newt' - Executing 'log_parameter_task-2' immediately...
+

+

+

+

+

+

+
00:56:46.724 | INFO    | Task run 'log_feature_task-1' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.749 | INFO    | Task run 'log_parameter_task-2' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.761 | INFO    | Flow run 'laughing-newt' - Created task run 'fit_pred_model-0' for task 'fit_pred_model'
+

+

+

+

+

+

+
00:56:46.761 | INFO    | Flow run 'laughing-newt' - Executing 'fit_pred_model-0' immediately...
+

+

+

+

+

+

+
00:56:46.771 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-2' for task 'log_feature_task'
+

+

+

+

+

+

+
00:56:46.772 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-2' for execution.
+

+

+

+

+

+

+
00:56:46.817 | INFO    | Task run 'fit_pred_model-0' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.839 | INFO    | Flow run 'laughing-newt' - Created task run 'log_metric_task-0' for task 'log_metric_task'
+

+

+

+

+

+

+
00:56:46.840 | INFO    | Flow run 'laughing-newt' - Executing 'log_metric_task-0' immediately...
+

+

+

+

+

+

+
00:56:46.854 | INFO    | Task run 'log_feature_task-2' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.871 | INFO    | Task run 'log_feature_task-4' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.885 | INFO    | Task run 'log_metric_task-0' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:46.971 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-5' for task 'log_feature_task'
+

+

+

+

+

+

+
00:56:46.972 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-5' for execution.
+

+

+

+

+

+

+
00:56:47.004 | INFO    | Task run 'log_feature_task-5' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:47.083 | INFO    | Flow run 'laughing-newt' - Created task run 'log_feature_task-9' for task 'log_feature_task'
+

+

+

+

+

+

+
00:56:47.084 | INFO    | Flow run 'laughing-newt' - Submitted task run 'log_feature_task-9' for execution.
+

+

+

+

+

+

+
00:56:47.132 | INFO    | Task run 'log_feature_task-9' - Finished in state Completed()
+

+

+

+

+

+

+
00:56:47.152 | INFO    | Flow run 'laughing-newt' - Finished in state Completed()
+

+

+

+
[9]:
+

+

 

 
-Flow URL: http://localhost:8080/default/flow/1ff30ad8-530c-4502-a9ad-cfed39b145fd
- └── ID: 5f925f68-877c-4922-952c-927da5cf5a34
- └── Project: Wine Classification
- └── Labels: ['8c859084633f']
-Flow run scheduled. Waiting...
-Flow run scheduled. Waiting...
-Running flow. Waiting...
-Running flow. Waiting...
-Running flow. Waiting...
-All reference tasks succeeded. Waiting...
-Flow run 418550e0-01eb-4d48-b78b-fbe101da0622 was successful!
+1.0
 

 

-
Retrieving all the results of a mapped task is even more cumbersome than retrieving just the accuracy above. We’ll simply use the rubicon_ml Dashboard to check out all the data we just logged!

+
This time we can use rubicon_ml to inspect our accuracy, among other things!

 

-
[17]:
+
[10]:
 

 

-
from rubicon_ml.viz import Dashboard
+
from rubicon_ml import Rubicon
 
 
-project = get_project(
-    "filesystem",
-    root_path,
-    "Wine Classification with Prefect - Mapped",
-)
+rubicon = Rubicon(persistence="memory", root_dir=".")
+project = rubicon.get_project("Wine Classification with Prefect")
+
+experiment = project.experiments()[0]
 
-Dashboard(project.experiments()).show()
+features = [f.name for f in experiment.features()]
+parameters = [(p.name, p.value) for p in experiment.parameters()]
+metrics = [(m.name, m.value) for m in experiment.metrics()]
+
+print(
+    f"experiment {experiment.id}\n"
+    f"features: {features}\nparameters: {parameters}\n"
+    f"metrics: {metrics}"
+)
 

 

 

-

-

-

-

-
- * Running on http://127.0.0.1:8050/ (Press CTRL+C to quit)
-127.0.0.1 - - [16/Apr/2021 15:29:39] "GET /_alive_71180c28-37bc-4127-a50b-e754fe3e6812 HTTP/1.1" 200 -
-

-

 

 

 

 

 
-Dash app running on http://127.0.0.1:8050/
+experiment 35173154-a912-4ed0-9920-188d62e6f3d2
+features: ['proline', 'proanthocyanins', 'flavanoids', 'alcalinity_of_ash', 'nonflavanoid_phenols', 'hue', 'alcohol', 'od280/od315_of_diluted_wines', 'malic_acid', 'ash', 'magnesium', 'total_phenols', 'color_intensity']
+parameters: [('n_components', 2), ('n_neighbors', 5), ('is_standardized', True)]
+metrics: [('accuracy', 1.0)]
 

 

 

@@ -891,7 +1245,6 @@ 
Concurrent Logging with DaskSetting up a simple flow
 
  • Running a flow and viewing results
    • 
 
  • Adding Rubicon to your flow
    • 
-
  • Concurrent Logging with Dask
    • 
 
 
 
diff --git a/integrations/integration-prefect-workflows.ipynb b/integrations/integration-prefect-workflows.ipynb
index 3140a17d..4c7d029a 100644
--- a/integrations/integration-prefect-workflows.ipynb
+++ b/integrations/integration-prefect-workflows.ipynb
@@ -158,20 +158,21 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from prefect import Flow\n",
+    "from prefect import flow\n",
     "\n",
     "\n",
     "n_components = 2\n",
     "n_neighbors = 5\n",
     "is_standardized = True\n",
     "\n",
-    "with Flow(\"Wine Classification\") as flow:\n",
+    "@flow\n",
+    "def wine_flow():\n",
     "    wine_dataset = load_data()\n",
     "    \n",
     "    feature_names = get_feature_names(wine_dataset)\n",
     "    train_test_split = split_data(wine_dataset)\n",
     "    \n",
-    "    accuracy = fit_pred_model(\n",
+    "    return fit_pred_model(\n",
     "        train_test_split,\n",
     "        n_components,\n",
     "        n_neighbors,\n",
@@ -185,15 +186,7 @@
    "source": [
     "### Running a flow and viewing results\n",
     "\n",
-    "Now we'll register our **flow** with the local server. First, we'll have to\n",
-    "use the ``prefect`` CLI one more time to create a project.\n",
-    "\n",
-    "```bash\n",
-    "prefect create project 'Wine Classification'\n",
-    "```\n",
-    "\n",
-    "The URL printed from the call to ``flow.register`` opens the local Prefect UI.\n",
-    "We can use it to run and monitor our **flows**. "
+    "Now we'll run the flow."
    ]
   },
   {
@@ -202,114 +195,207 @@
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Flow URL: http://localhost:8080/default/flow/aef9fb65-c49b-4c46-89be-e31c357a165e\n",
-      " └── ID: 531ffe8c-fb2b-4855-b5d8-f9bcef51ad2d\n",
-      " └── Project: Wine Classification\n",
-      " └── Labels: ['8c859084633f']\n"
-     ]
-    }
-   ],
-   "source": [
-    "flow_id = flow.register(project_name=\"Wine Classification\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We'll also put together a function to run our **flows** and wait for them to finish."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
+     "data": {
+      "text/html": [
+       "
    00:56:44.598 | INFO    | prefect.engine - Created flow run 'rugged-pony' for flow 'wine-flow'\n",
+       "
    \n"
+      ],
+      "text/plain": [
+       "00:56:44.598 | \u001b[36mINFO\u001b[0m    | prefect.engine - Created flow run\u001b[35m 'rugged-pony'\u001b[0m for flow\u001b[1;35m 'wine-flow'\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Flow run scheduled. Waiting...\n",
-      "Flow run scheduled. Waiting...\n",
-      "All reference tasks succeeded. Waiting...\n",
-      "Flow run 024457a5-aac4-449a-a5a3-7b3986f90cba was successful!\n"
-     ]
-    }
-   ],
-   "source": [
-    "import time\n",
-    "from prefect import Client\n",
-    "\n",
-    "\n",
-    "prefect_client = Client()\n",
-    "\n",
-    "def run_flow(client, flow_id):\n",
-    "    flow_run_id = client.create_flow_run(flow_id=flow_id)\n",
-    "    \n",
-    "    is_finished = False\n",
-    "    while not is_finished:\n",
-    "        state = client.get_flow_run_info(flow_run_id).state\n",
-    "        print(f\"{state.message.strip('.')}. Waiting...\")\n",
-    "        \n",
-    "        time.sleep(3)\n",
-    "        \n",
-    "        is_finished = state.is_finished()\n",
-    "\n",
-    "    assert state.is_successful()\n",
-    "    print(f\"Flow run {flow_run_id} was successful!\")\n",
-    "    \n",
-    "    return flow_run_id\n",
-    "    \n",
-    "flow_run_id = run_flow(prefect_client, flow_id)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We assigned a few variables in our **flow**, most notably the result of ``fit_pred_model``, ``accuracy``.\n",
-    "This accuracy metric is how we'll determine whether or not the model we trained is a success. However,\n",
-    "retrieving state variables from **flows** is a bit cumbersome."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:44.646 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'rugged-pony'\u001b[0m - Created task run 'load_data-0' for task 'load_data'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
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+      "text/html": [
+       "
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+       "
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+      ],
       "text/plain": [
-       "0.9555555555555556"
+       "00:56:44.647 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'rugged-pony'\u001b[0m - Executing 'load_data-0' immediately...\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:45.352 | \u001b[36mINFO\u001b[0m    | Task run 'load_data-0' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
    00:56:45.372 | INFO    | Flow run 'rugged-pony' - Created task run 'get_feature_names-0' for task 'get_feature_names'\n",
+       "
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+      ],
+      "text/plain": [
+       "00:56:45.372 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'rugged-pony'\u001b[0m - Created task run 'get_feature_names-0' for task 'get_feature_names'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:45.373 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'rugged-pony'\u001b[0m - Executing 'get_feature_names-0' immediately...\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:45.423 | \u001b[36mINFO\u001b[0m    | Task run 'get_feature_names-0' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:45.440 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'rugged-pony'\u001b[0m - Created task run 'split_data-0' for task 'split_data'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:45.441 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'rugged-pony'\u001b[0m - Executing 'split_data-0' immediately...\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:45.547 | \u001b[36mINFO\u001b[0m    | Task run 'split_data-0' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
    00:56:45.566 | INFO    | Flow run 'rugged-pony' - Created task run 'fit_pred_model-0' for task 'fit_pred_model'\n",
+       "
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+      ],
+      "text/plain": [
+       "00:56:45.566 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'rugged-pony'\u001b[0m - Created task run 'fit_pred_model-0' for task 'fit_pred_model'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:45.567 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'rugged-pony'\u001b[0m - Executing 'fit_pred_model-0' immediately...\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:45.693 | \u001b[36mINFO\u001b[0m    | Task run 'fit_pred_model-0' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
    \n"
+      ],
+      "text/plain": [
+       "00:56:45.719 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'rugged-pony'\u001b[0m - Finished in state \u001b[32mCompleted\u001b[0m()\n"
       ]
      },
-     "execution_count": 9,
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "0.9333333333333333"
+      ]
+     },
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "info = prefect_client.get_flow_run_info(flow_run_id)\n",
-    "\n",
-    "slugs = [t.task_slug for t in info.task_runs]\n",
-    "index = slugs.index(accuracy.slug)\n",
-    "\n",
-    "result = info.task_runs[index].state._result.read(\n",
-    "    info.task_runs[index].state._result.location,\n",
-    ")\n",
-    "result.value"
+    "accuracy = wine_flow()\n",
+    "accuracy"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "What's going on here isn't exactly intuitive, and all that only extracted one\n",
-    "piece of data from one task.\n",
-    " \n",
     "### Adding Rubicon to your flow\n",
     "\n",
     "We can leverage the Prefect tasks within the ``rubicon_ml`` library to log all the\n",
@@ -323,7 +409,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -332,17 +418,15 @@
     "from prefect import unmapped\n",
     "\n",
     "\n",
-    "root_dir = os.environ.get(\"RUBICON_ROOT\", \"rubicon-root\")\n",
-    "root_path = f\"{os.path.dirname(os.getcwd())}/{root_dir}\"\n",
-    "\n",
     "n_components = 2\n",
     "n_neighbors = 5\n",
     "is_standardized = True\n",
     "\n",
-    "with Flow(\"Wine Classification with Rubicon\") as flow:    \n",
+    "@flow\n",
+    "def rubicon_wine_flow():    \n",
     "    project = get_or_create_project_task(\n",
-    "        \"filesystem\",\n",
-    "        root_path,\n",
+    "        \"memory\",\n",
+    "        \".\",\n",
     "        \"Wine Classification with Prefect\",\n",
     "    )\n",
     "    experiment = create_experiment_task(\n",
@@ -366,7 +450,9 @@
     "        is_standardized,\n",
     "    )\n",
     "    \n",
-    "    log_metric_task(experiment, \"accuracy\", accuracy)"
+    "    log_metric_task(experiment, \"accuracy\", accuracy)\n",
+    "\n",
+    "    return accuracy"
    ]
   },
   {
@@ -378,285 +464,989 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Flow URL: http://localhost:8080/default/flow/9b91bafc-7e8b-4361-b1d0-bc57dac4cebc\n",
-      " └── ID: 081b9522-5db8-4ce6-ae64-ea8afd5b323e\n",
-      " └── Project: Wine Classification\n",
-      " └── Labels: ['8c859084633f']\n",
-      "Flow run scheduled. Waiting...\n",
-      "Submitted for execution. Waiting...\n",
-      "Running flow. Waiting...\n",
-      "All reference tasks succeeded. Waiting...\n",
-      "Flow run 29cef175-c115-4da2-a9f7-40f79bdb6104 was successful!\n"
-     ]
-    }
-   ],
-   "source": [
-    "flow_with_rubicon_id = flow.register(project_name=\"Wine Classification\")\n",
-    "flow_run_with_rubicon_id = run_flow(prefect_client, flow_with_rubicon_id)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "This time we can use ``rubicon_ml`` to inspect our accuracy, among other things!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [
+     "data": {
+      "text/html": [
+       "
    00:56:45.890 | INFO    | prefect.engine - Created flow run 'laughing-newt' for flow 'rubicon-wine-flow'\n",
+       "
    \n"
+      ],
+      "text/plain": [
+       "00:56:45.890 | \u001b[36mINFO\u001b[0m    | prefect.engine - Created flow run\u001b[35m 'laughing-newt'\u001b[0m for flow\u001b[1;35m 'rubicon-wine-flow'\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "experiment 6b1c3846-5aab-4bda-8c16-15b279d8616c\n",
-      "features: ['alcalinity_of_ash', 'alcohol', 'ash', 'color_intensity', 'flavanoids', 'hue', 'magnesium', 'malic_acid', 'nonflavanoid_phenols', 'od280/od315_of_diluted_wines', 'proanthocyanins', 'proline', 'total_phenols']\n",
-      "parameters: [('is_standardized', True), ('n_components', 2), ('n_neighbors', 5)]\n",
-      "metrics: [('accuracy', 1.0)]\n"
-     ]
-    }
-   ],
-   "source": [
-    "from rubicon_ml import Rubicon\n",
-    "\n",
-    "\n",
-    "rubicon = Rubicon(persistence=\"filesystem\", root_dir=root_path)\n",
-    "project = rubicon.get_project(\"Wine Classification with Prefect\")\n",
-    "    \n",
-    "experiment = project.experiments()[0]\n",
-    "\n",
-    "features = [f.name for f in experiment.features()]\n",
-    "parameters = [(p.name, p.value) for p in experiment.parameters()]\n",
-    "metrics = [(m.name, m.value) for m in experiment.metrics()]\n",
-    "\n",
-    "print(\n",
-    "    f\"experiment {experiment.id}\\n\"\n",
-    "    f\"features: {features}\\nparameters: {parameters}\\n\"\n",
-    "    f\"metrics: {metrics}\"\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Extracting data from ``rubicon_ml`` is much simpler than pulling it from the various\n",
-    "**tasks** as they succeed. Especially in the case where we're running thousands\n",
-    "of **tasks** in a **flow**.\n",
-    "\n",
-    "### Concurrent Logging with Dask\n",
-    "\n",
-    "Prefect plays nicely with Dask in order to provide parallel computing when possible.\n",
-    "The Prefect scheduler is smart enough to know which **tasks** do and do not depend\n",
-    "on each other, so it can intelligently decide when to run independent **tasks** at\n",
-    "the same time.\n",
-    "\n",
-    "Let's run the same **flow** as above, except this time we'll log eight different\n",
-    "experiments with eight different feature sets and accuracy results. First, we'll\n",
-    "need to use Dask to start a local cluster."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import dask.distributed\n",
-    "from prefect.executors import DaskExecutor\n",
-    "\n",
-    "\n",
-    "dask_client = dask.distributed.Client()\n",
-    "dask_executor = DaskExecutor(address=dask_client.cluster.scheduler.address)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Before we look at the new **flow**, let's see how easy it is to make our own \n",
-    "``rubicon_ml`` Prefect **tasks**. Currently, the ``log_feature_task`` logs one \n",
-    "feature to one experiment. Let's say in this example, we want to log our entire\n",
-    "feature set in one **task**. That's slightly different than what we currently\n",
-    "have in the ``log_feature_task``, so let's see how we can make a new one using\n",
-    "the ``rubicon_ml`` logging library."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "@task\n",
-    "def log_feature_set(experiment, feature_names):\n",
-    "    \"\"\"log a set of features to a rubicon experiment\n",
-    "    \n",
-    "    Parameters\n",
-    "    ----------\n",
-    "    experiment : rubicon.Experiment\n",
-    "        the experiment to log the feature set to\n",
-    "    feature_names : list of str\n",
-    "        the names of the features to log to `experiment`\n",
-    "    \"\"\"\n",
-    "    features = []\n",
-    "    \n",
-    "    for name in feature_names:\n",
-    "        features.append(experiment.log_feature(name=name))\n",
-    "        \n",
-    "    return features"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Easy! Even though its so simple, this particular **task** is actually more in-depth\n",
-    "than the ones you'll find in the library. The Prefect **tasks** in the library are\n",
-    "simply wrappers around existing logging library functions, like ``experiment.log_feature``.\n",
-    "\n",
-    "Now we can make our new **flow** to log multiple experiments in parallel."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "n_components =    [2,    2,     2,    2,     4,    4,     4,    4    ]\n",
-    "n_neighbors =     [5,    5,     10,   10,    5,    5,     10,   10   ]\n",
-    "is_standardized = [True, False, True, False, True, False, True, False]\n",
-    "\n",
-    "experiment_names = [f\"mapped run {i}\" for i in range(len(n_components))]\n",
-    "\n",
-    "with Flow(\n",
-    "    \"Wine Classification with Rubicon - Mapped\",\n",
-    "    executor=dask_executor,\n",
-    ") as mapped_flow:\n",
-    "    project = get_or_create_project_task(\n",
-    "        \"filesystem\",\n",
-    "        root_path,\n",
-    "        \"Wine Classification with Prefect - Mapped\",\n",
-    "    )\n",
-    "    experiments = create_experiment_task.map(\n",
-    "        unmapped(project),\n",
-    "        name=experiment_names,\n",
-    "        description=unmapped(\"concurrent example with Prefect\"),\n",
-    "    )\n",
-    "    \n",
-    "    wine_dataset = load_data()\n",
-    "    \n",
-    "    feature_names = get_feature_names(wine_dataset)\n",
-    "    train_test_split = split_data(wine_dataset)\n",
-    "    \n",
-    "    log_feature_set.map(experiments, unmapped(feature_names))\n",
-    "    log_parameter_task.map(experiments, unmapped(\"n_components\"), n_components)\n",
-    "    log_parameter_task.map(experiments, unmapped(\"n_neighbors\"), n_neighbors)\n",
-    "    log_parameter_task.map(experiments, unmapped(\"is_standardized\"), is_standardized)\n",
-    "    \n",
-    "    accuracies = fit_pred_model.map(\n",
-    "        unmapped(train_test_split),\n",
-    "        n_components,\n",
-    "        n_neighbors,\n",
-    "        is_standardized,\n",
-    "    )\n",
-    " \n",
-    "    log_metric_task.map(experiments, unmapped(\"accuracy\"), accuracies)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Let's register and run one last **flow**. If you check out the timeline for your completed\n",
-    "**flows** on the UI linked by `mapped_flow.register`, you'll notice tasks executing at the same\n",
-    "time now."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
+     "data": {
+      "text/html": [
+       "
    00:56:45.942 | INFO    | Flow run 'laughing-newt' - Created task run 'get_or_create_project_task-0' for task 'get_or_create_project_task'\n",
+       "
    \n"
+      ],
+      "text/plain": [
+       "00:56:45.942 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'get_or_create_project_task-0' for task 'get_or_create_project_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:45.943 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Executing 'get_or_create_project_task-0' immediately...\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:45.995 | \u001b[36mINFO\u001b[0m    | Task run 'get_or_create_project_task-0' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
    00:56:46.011 | INFO    | Flow run 'laughing-newt' - Created task run 'create_experiment_task-0' for task 'create_experiment_task'\n",
+       "
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+      ],
+      "text/plain": [
+       "00:56:46.011 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'create_experiment_task-0' for task 'create_experiment_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.012 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Executing 'create_experiment_task-0' immediately...\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
    00:56:46.052 | INFO    | Task run 'create_experiment_task-0' - Finished in state Completed()\n",
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+      "text/plain": [
+       "00:56:46.052 | \u001b[36mINFO\u001b[0m    | Task run 'create_experiment_task-0' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      "text/plain": [
+       "00:56:46.112 | \u001b[36mINFO\u001b[0m    | Task run 'load_data-0' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
    00:56:46.129 | INFO    | Flow run 'laughing-newt' - Created task run 'get_feature_names-0' for task 'get_feature_names'\n",
+       "
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+      ],
+      "text/plain": [
+       "00:56:46.129 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'get_feature_names-0' for task 'get_feature_names'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      "text/plain": [
+       "00:56:46.129 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Executing 'get_feature_names-0' immediately...\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.168 | \u001b[36mINFO\u001b[0m    | Task run 'get_feature_names-0' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.184 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'split_data-0' for task 'split_data'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+      "text/plain": [
+       "00:56:46.185 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Executing 'split_data-0' immediately...\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.232 | \u001b[36mINFO\u001b[0m    | Task run 'split_data-0' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+      ],
+      "text/plain": [
+       "00:56:46.311 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_feature_task-12' for task 'log_feature_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "00:56:46.312 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Submitted task run 'log_feature_task-12' for execution.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+      ],
+      "text/plain": [
+       "00:56:46.322 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_feature_task-7' for task 'log_feature_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.323 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Submitted task run 'log_feature_task-7' for execution.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.334 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_feature_task-8' for task 'log_feature_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+      "text/plain": [
+       "00:56:46.335 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Submitted task run 'log_feature_task-8' for execution.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.356 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_feature_task-6' for task 'log_feature_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+      ],
+      "text/plain": [
+       "00:56:46.357 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Submitted task run 'log_feature_task-6' for execution.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.399 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_feature_task-3' for task 'log_feature_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      "text/plain": [
+       "00:56:46.400 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Submitted task run 'log_feature_task-3' for execution.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.425 | \u001b[36mINFO\u001b[0m    | Task run 'log_feature_task-8' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.444 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_feature_task-10' for task 'log_feature_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      "text/plain": [
+       "00:56:46.445 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Submitted task run 'log_feature_task-10' for execution.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.459 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_feature_task-4' for task 'log_feature_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      "text/plain": [
+       "00:56:46.461 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Submitted task run 'log_feature_task-4' for execution.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+      ],
+      "text/plain": [
+       "00:56:46.508 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_feature_task-0' for task 'log_feature_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+       "00:56:46.524 | \u001b[36mINFO\u001b[0m    | Task run 'log_feature_task-7' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+      ],
+      "text/plain": [
+       "00:56:46.556 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_feature_task-11' for task 'log_feature_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      "text/plain": [
+       "00:56:46.557 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Submitted task run 'log_feature_task-11' for execution.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.567 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_parameter_task-0' for task 'log_parameter_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Flow URL: http://localhost:8080/default/flow/1ff30ad8-530c-4502-a9ad-cfed39b145fd\n",
-      " └── ID: 5f925f68-877c-4922-952c-927da5cf5a34\n",
-      " └── Project: Wine Classification\n",
-      " └── Labels: ['8c859084633f']\n",
-      "Flow run scheduled. Waiting...\n",
-      "Flow run scheduled. Waiting...\n",
-      "Running flow. Waiting...\n",
-      "Running flow. Waiting...\n",
-      "Running flow. Waiting...\n",
-      "All reference tasks succeeded. Waiting...\n",
-      "Flow run 418550e0-01eb-4d48-b78b-fbe101da0622 was successful!\n"
-     ]
+     "data": {
+      "text/html": [
+       "
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+       "
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+       "00:56:46.568 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Executing 'log_parameter_task-0' immediately...\n"
+      ]
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+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "00:56:46.612 | \u001b[36mINFO\u001b[0m    | Task run 'log_feature_task-11' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
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+     "output_type": "display_data"
+    },
+    {
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+      "text/html": [
+       "
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+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+      ]
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+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+      ],
+      "text/plain": [
+       "00:56:46.640 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_parameter_task-1' for task 'log_parameter_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.641 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Executing 'log_parameter_task-1' immediately...\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.651 | \u001b[36mINFO\u001b[0m    | Task run 'log_feature_task-0' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.668 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_feature_task-1' for task 'log_feature_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.669 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Submitted task run 'log_feature_task-1' for execution.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.696 | \u001b[36mINFO\u001b[0m    | Task run 'log_parameter_task-1' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.713 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_parameter_task-2' for task 'log_parameter_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.714 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Executing 'log_parameter_task-2' immediately...\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.724 | \u001b[36mINFO\u001b[0m    | Task run 'log_feature_task-1' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.749 | \u001b[36mINFO\u001b[0m    | Task run 'log_parameter_task-2' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.761 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'fit_pred_model-0' for task 'fit_pred_model'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.761 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Executing 'fit_pred_model-0' immediately...\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.771 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_feature_task-2' for task 'log_feature_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.772 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Submitted task run 'log_feature_task-2' for execution.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.817 | \u001b[36mINFO\u001b[0m    | Task run 'fit_pred_model-0' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.839 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_metric_task-0' for task 'log_metric_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.840 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Executing 'log_metric_task-0' immediately...\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.854 | \u001b[36mINFO\u001b[0m    | Task run 'log_feature_task-2' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.871 | \u001b[36mINFO\u001b[0m    | Task run 'log_feature_task-4' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.885 | \u001b[36mINFO\u001b[0m    | Task run 'log_metric_task-0' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.971 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_feature_task-5' for task 'log_feature_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:46.972 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Submitted task run 'log_feature_task-5' for execution.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:47.004 | \u001b[36mINFO\u001b[0m    | Task run 'log_feature_task-5' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:47.083 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Created task run 'log_feature_task-9' for task 'log_feature_task'\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:47.084 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Submitted task run 'log_feature_task-9' for execution.\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
+      "text/plain": [
+       "00:56:47.132 | \u001b[36mINFO\u001b[0m    | Task run 'log_feature_task-9' - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
    00:56:47.152 | INFO    | Flow run 'laughing-newt' - Finished in state Completed()\n",
+       "
    \n"
+      ],
+      "text/plain": [
+       "00:56:47.152 | \u001b[36mINFO\u001b[0m    | Flow run\u001b[35m 'laughing-newt'\u001b[0m - Finished in state \u001b[32mCompleted\u001b[0m()\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "1.0"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "flow_with_concurrent_rubicon_id = mapped_flow.register(\n",
-    "    project_name=\"Wine Classification\",\n",
-    ")\n",
-    "flow_run_with_concurrent_rubicon_id = run_flow(\n",
-    "    prefect_client,\n",
-    "    flow_with_concurrent_rubicon_id,\n",
-    ")"
+    "accuracy = rubicon_wine_flow()\n",
+    "accuracy"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Retrieving all the results of a mapped **task** is even more cumbersome than\n",
-    "retrieving just the accuracy above. We'll simply use the ``rubicon_ml`` Dashboard to\n",
-    "check out all the data we just logged!"
+    "This time we can use ``rubicon_ml`` to inspect our accuracy, among other things!"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      " * Running on http://127.0.0.1:8050/ (Press CTRL+C to quit)\n",
-      "127.0.0.1 - - [16/Apr/2021 15:29:39] \"\u001b[37mGET /_alive_71180c28-37bc-4127-a50b-e754fe3e6812 HTTP/1.1\u001b[0m\" 200 -\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Dash app running on http://127.0.0.1:8050/\n"
+      "experiment 35173154-a912-4ed0-9920-188d62e6f3d2\n",
+      "features: ['proline', 'proanthocyanins', 'flavanoids', 'alcalinity_of_ash', 'nonflavanoid_phenols', 'hue', 'alcohol', 'od280/od315_of_diluted_wines', 'malic_acid', 'ash', 'magnesium', 'total_phenols', 'color_intensity']\n",
+      "parameters: [('n_components', 2), ('n_neighbors', 5), ('is_standardized', True)]\n",
+      "metrics: [('accuracy', 1.0)]\n"
      ]
     }
    ],
    "source": [
-    "from rubicon_ml.viz import Dashboard\n",
+    "from rubicon_ml import Rubicon\n",
     "\n",
     "\n",
-    "project = get_project(\n",
-    "    \"filesystem\",\n",
-    "    root_path,\n",
-    "    \"Wine Classification with Prefect - Mapped\",\n",
-    ")\n",
+    "rubicon = Rubicon(persistence=\"memory\", root_dir=\".\")\n",
+    "project = rubicon.get_project(\"Wine Classification with Prefect\")\n",
+    "    \n",
+    "experiment = project.experiments()[0]\n",
+    "\n",
+    "features = [f.name for f in experiment.features()]\n",
+    "parameters = [(p.name, p.value) for p in experiment.parameters()]\n",
+    "metrics = [(m.name, m.value) for m in experiment.metrics()]\n",
     "\n",
-    "Dashboard(project.experiments()).show()"
+    "print(\n",
+    "    f\"experiment {experiment.id}\\n\"\n",
+    "    f\"features: {features}\\nparameters: {parameters}\\n\"\n",
+    "    f\"metrics: {metrics}\"\n",
+    ")"
    ]
   }
  ],
@@ -676,7 +1466,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.4"
+   "version": "3.12.3"
   }
  },
  "nbformat": 4,
diff --git a/integrations/integration-sklearn.html b/integrations/integration-sklearn.html
index 2ce0aa80..a95c69fe 100644
--- a/integrations/integration-sklearn.html
+++ b/integrations/integration-sklearn.html
@@ -6,7 +6,7 @@
 
 
     
-        Integrate with Scikit-learn - rubicon-ml v0.7.4
+        Integrate with Scikit-learn - rubicon-ml v0.8.0
       
     
     
@@ -182,7 +182,7 @@
       
     
    
     
    
-      
    rubicon-ml v0.7.4
    
+      
    rubicon-ml v0.8.0
    
     
    
     
    
       
    
@@ -210,7 +210,7 @@
     
   
    
   
-  
    rubicon-ml v0.7.4
    
+  
    rubicon-ml v0.8.0
    
   
 
   
diff --git a/logging-examples/log-with-schema.html b/logging-examples/log-with-schema.html
index 75d76d35..62e223cb 100644
--- a/logging-examples/log-with-schema.html
+++ b/logging-examples/log-with-schema.html
@@ -6,7 +6,7 @@
 
 
     
-        Logging with a schema - rubicon-ml v0.7.4
+        Logging with a schema - rubicon-ml v0.8.0
       
     
     
@@ -182,7 +182,7 @@
       
     
    
     
    
-      
    rubicon-ml v0.7.4
    
+      
    rubicon-ml v0.8.0
    
     
    
     
    
       
    
@@ -210,7 +210,7 @@
     
   
    
   
-  
    rubicon-ml v0.7.4
    
+  
    rubicon-ml v0.8.0
    
   
 
   
diff --git a/logging-examples/logging-concurrently.html b/logging-examples/logging-concurrently.html
index c920ed5a..f67952b1 100644
--- a/logging-examples/logging-concurrently.html
+++ b/logging-examples/logging-concurrently.html
@@ -6,7 +6,7 @@
 
 
     
-        Logging Concurrently - rubicon-ml v0.7.4
+        Logging Concurrently - rubicon-ml v0.8.0
       
     
     
@@ -182,7 +182,7 @@
       
     
    
     
    
-      
    rubicon-ml v0.7.4
    
+      
    rubicon-ml v0.8.0
    
     
    
     
    
       
    
@@ -210,7 +210,7 @@
     
   
    
   
-  
    rubicon-ml v0.7.4
    
+  
    rubicon-ml v0.8.0
    
   
 
   
diff --git a/logging-examples/logging-experiment-failures.html b/logging-examples/logging-experiment-failures.html
index e67ce30c..a1bb6344 100644
--- a/logging-examples/logging-experiment-failures.html
+++ b/logging-examples/logging-experiment-failures.html
@@ -6,7 +6,7 @@
 
 
     
-        Distinguish Failed Experiments - rubicon-ml v0.7.4
+        Distinguish Failed Experiments - rubicon-ml v0.8.0
       
     
     
@@ -182,7 +182,7 @@
       
     
    
     
    
-      
    rubicon-ml v0.7.4
    
+      
    rubicon-ml v0.8.0
    
     
    
     
    
       
    
@@ -210,7 +210,7 @@
     
   
    
   
-  
    rubicon-ml v0.7.4
    
+  
    rubicon-ml v0.8.0
    
   
 
   
diff --git a/logging-examples/logging-feature-plots.html b/logging-examples/logging-feature-plots.html
index 6acffc82..f78fc126 100644
--- a/logging-examples/logging-feature-plots.html
+++ b/logging-examples/logging-feature-plots.html
@@ -6,7 +6,7 @@
 
 
     
-        Link Plots to Features - rubicon-ml v0.7.4
+        Link Plots to Features - rubicon-ml v0.8.0
       
     
     
@@ -182,7 +182,7 @@
       
     
    
     
    
-      
    rubicon-ml v0.7.4
    
+      
    rubicon-ml v0.8.0
    
     
    
     
    
       
    
@@ -210,7 +210,7 @@
     
   
    
   
-  
    rubicon-ml v0.7.4
    
+  
    rubicon-ml v0.8.0
    
   
 
   
diff --git a/logging-examples/logging-plots.html b/logging-examples/logging-plots.html
index 89c2c83c..4e48c23b 100644
--- a/logging-examples/logging-plots.html
+++ b/logging-examples/logging-plots.html
@@ -6,7 +6,7 @@
 
 
     
-        Logging Plots as PNGs - rubicon-ml v0.7.4
+        Logging Plots as PNGs - rubicon-ml v0.8.0
       
     
     
@@ -182,7 +182,7 @@
       
     
    
     
    
-      
    rubicon-ml v0.7.4
    
+      
    rubicon-ml v0.8.0
    
     
    
     
    
       
    
@@ -210,7 +210,7 @@
     
   
    
   
-  
    rubicon-ml v0.7.4
    
+  
    rubicon-ml v0.8.0
    
   
 
   
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index 749e45a5..dc9ea211 100644
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@@ -179,7 +179,7 @@
       
     
    
     
    
-      
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+      
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@@ -207,7 +207,7 @@
     
   
    
   
-  
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+  
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diff --git a/quick-look/logging-experiments.html b/quick-look/logging-experiments.html
index 95aadf61..944adc96 100644
--- a/quick-look/logging-experiments.html
+++ b/quick-look/logging-experiments.html
@@ -6,7 +6,7 @@
 
 
     
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@@ -182,7 +182,7 @@
       
     
    
     
    
-      
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@@ -210,7 +210,7 @@
     
   
    
   
-  
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diff --git a/quick-look/sharing-experiments.html b/quick-look/sharing-experiments.html
index fff00f07..3e776c18 100644
--- a/quick-look/sharing-experiments.html
+++ b/quick-look/sharing-experiments.html
@@ -6,7 +6,7 @@
 
 
     
-        Sharing Experiments - rubicon-ml v0.7.4
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@@ -182,7 +182,7 @@
       
     
    
     
    
-      
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+      
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@@ -210,7 +210,7 @@
     
   
    
   
-  
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+  
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diff --git a/quick-look/visualizing-experiments.html b/quick-look/visualizing-experiments.html
index c56fe894..b4d9e68e 100644
--- a/quick-look/visualizing-experiments.html
+++ b/quick-look/visualizing-experiments.html
@@ -6,7 +6,7 @@
 
 
     
-        Visualizing Experiments - rubicon-ml v0.7.4
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@@ -182,7 +182,7 @@
       
     
    
     
    
-      
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+      
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@@ -210,7 +210,7 @@
     
   
    
   
-  
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diff --git a/schema-representation.html b/schema-representation.html
index 91b2efa1..e124f062 100644
--- a/schema-representation.html
+++ b/schema-representation.html
@@ -6,7 +6,7 @@
 
 
     
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@@ -181,7 +181,7 @@
       
     
    
     
    
-      
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@@ -209,7 +209,7 @@
     
   
    
   
-  
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+  
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diff --git a/search.html b/search.html
index 58dc8406..dc8f1391 100644
--- a/search.html
+++ b/search.html
@@ -7,7 +7,7 @@
 
     
 
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@@ -181,7 +181,7 @@
       
     
    
     
    
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@@ -209,7 +209,7 @@
     
   
    
   
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diff --git a/searchindex.js b/searchindex.js
index 46d286fa..3aa7269a 100644
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diff --git a/tutorials/failure-modes.html b/tutorials/failure-modes.html
index 4c844e6b..747a7b06 100644
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@@ -6,7 +6,7 @@
 
 
     
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--- a/visualizations.html
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index 918939a7..4eda0f79 100644
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index 84d42319..58ed916f 100644
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