New Artifact version section.

colabs/artifact_basics/Artifact_Basics.ipynb

@@ -193,7 +193,7 @@
       "outputs": [],
       "source": [
         "run = wandb.init(project=\"artifact-basics\")\n",
-        "artifact = run.use_artifact(artifact_or_name=\"my_first_artifact:latest\") # selects the artifact you're adding the file to\n",
+        "artifact = run.use_artifact(\"my_first_artifact:latest\") # selects the artifact you're adding the file to\n",
         "artifact.add_file(local_path=\"/content/sample_data/california_housing_test.csv\", name=\"new_file\")\n",
         "run.log_artifact(artifact)\n",
         "run.finish()"
@@ -205,7 +205,7 @@
       "source": [
         "This adds a new .csv file called `new_file` to the `my_first_artifact` Artifact. \n",
         "\n",
-        "Optionally, you can choose to add an entire directory to an Artifact:"
+        "If you edit a file, you'll need to go through a similar process:"
       ]
     },
     {
@@ -214,20 +214,28 @@
       "metadata": {},
       "outputs": [],
       "source": [
+        "# sorts the .csv file\n",
+        "import pandas\n",
+        "csvData = pandas.read_csv(\"/content/sample_data/california_housing_test.csv\") \n",
+        "csvData.sort_values(csvData.columns[6],  \n",
+        "                    axis=0, \n",
+        "                    inplace=True)\n",
+        "csvData.to_csv(\"/content/sample_data/california_housing_test.csv\") # overwrites file with the sorted data\n",
+        "# adds the new file to the artifact\n",
         "run = wandb.init(project=\"artifact-basics\")\n",
-        "artifact = run.use_artifact(\"my_first_artifact:latest\") # selects the artifact you're adding the file to, and makes a new artifact version\n",
-        "artifact.add_dir(local_path=\"/content/sample_data\", name=\"new_directory\")\n",
-        "run.log_artifact(artifact, aliases= [\"sorted\",\"cleaned\"])\n",
-        "run.finish()"
+        "artifact = run.use_artifact(\"my_first_artifact:latest\")\n",
+        "artifact.add_file(local_path=\"/content/sample_data/california_housing_test.csv\", name=\"sorted_file\")\n",
+        "run.log_artifact(artifact, aliases= [\"sorted\"]) # logs the new artifact version, overwriting the old one.\n",
+        "run.finish()\n"
       ]
     },
     {
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "This adds a new version of `my_first_artifact` with an entire folder with several .csv files. To save your changes, you'll need to [`log`](https://docs.wandb.ai/ref/python/log) or [`save`](https://docs.wandb.ai/ref/python/artifact#save) them. The new version will overwrite the contents of the previous version of the Artifact.\n",
+        "Now the sorted file will be logged in `my_first_artifact`. Any changes you log to an artifact will overwrite any older version. \n",
         "\n",
-        "The Artifact has also been given a custom `aliases`, a label for this Artifact version. While the `alias` is currently `staging`, the default aliases is `vN`, where `N` is the number of versions the Artifact has. This increments automatically."
+        "The Artifact has also been given a custom `alias`, a label for this Artifact version. While the `alias` is currently `sorted`, the default aliases is `vN`, where `N` is the number of versions the Artifact has. This increments automatically."
       ]
     },
     {
@@ -343,7 +351,7 @@
         "2. [Lineage](https://docs.wandb.ai/guides/artifacts/explore-and-traverse-an-artifact-graph): View lineage graphs, which are automatically built when using W&B artifact system, providing an auditable visual overview of the relationships between specific artifact versions, datasets models and runs.\n",
         "3. [Model Registry](https://docs.wandb.ai/guides/model_registry): Learn how to centralize your best artifact versions in a shared registry.\n",
         "4. [Artifact Automations](https://docs.wandb.ai/guides/artifacts/project-scoped-automations): Automatically run specific Weights & Biases jobs based on changes to your artifacts, such as automatically training a new model each time a new version of the training data is logged.\n",
-        "5. [Artifacts FAQ](https://docs.wandb.ai/guides/artifacts/artifacts-faqs): Frequently asked questions on Artifact security, workflows, and retention policy."
+        "5. [Reference Artifacts](https://docs.wandb.ai/guides/artifacts/track-external-files#download-a-reference-artifact): Track files saved outside the W&B server, like Amazon S3 buckets, GCS buckets, Azure blobs, and more. "
       ]
     }
   ],