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-->\n","\u003Ch2\u003EOverview\u003C/h2\u003E\n","\u003Cp\u003EIn this guide, we will use the Posit Team Native App to build an interactive Python dashboard over Home Mortgage Disclosure Act (HMDA) data. In Posit Workbench you will open the Positron Pro IDE, connect to Snowflake with Ibis, and use Posit Assistant with a Snowflake Cortex AI model to explore the data. Then you will build a Shiny for Python dashboard and publish it to Posit Connect with one-click deployment, so your whole team can use it.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/overview_architecture.png?v=cfc33e69\" alt=\"Architecture diagram: Positron Pro in Posit Workbench queries Snowflake with the user's own credentials and publishes to Posit Connect, which queries Snowflake on behalf of each dashboard viewer. Both Workbench and Connect run inside the Snowflake account as part of the Posit Team Native App.\"\u003E\u003C/p\u003E\n","\u003Cp\u003EThe deployed dashboard respects Snowflake's own security and authorization settings. Because you attach Connect's Snowflake integration to the content before publishing, each viewer's queries run under their own Snowflake identity, so they see only the data they have been granted.\u003C/p\u003E\n","\u003Cp\u003EBy the end you will have a working dashboard where users filter mortgage applications by loan type, state, and loan amount, and see the resulting distribution of loan amounts, three headline metrics, and a year-over-year trend.\u003C/p\u003E\n","\u003Cp\u003EThis guide is the Python counterpart to \u003Ca href=\"https://www.snowflake.com/en/developers/guides/build-and-deploy-interactive-dashboard-with-posit-team-and-cortex/\"\u003EBuild and Deploy an Interactive Shiny Dashboard with the Posit Team Native App and Snowflake Cortex AI\u003C/a\u003E, which covers the same process within R.\u003C/p\u003E\n","\u003Ch3\u003EPrerequisites\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EFamiliarity with SQL and Python\u003C/li\u003E\u003Cli\u003ESome exposure to reactive dashboards is helpful but not required\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You'll Learn\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EHow to connect to Snowflake from Positron Pro in Workbench using Workbench-managed credentials, with no secrets in your code\u003C/li\u003E\u003Cli\u003EHow to query Snowflake from Python with Ibis, keeping the work in the database\u003C/li\u003E\u003Cli\u003EHow to use Posit Assistant with a Snowflake Cortex AI model for exploratory data analysis and for refining app code\u003C/li\u003E\u003Cli\u003EHow to build an interactive Shiny for Python dashboard over a Snowflake table\u003C/li\u003E\u003Cli\u003EHow to publish that dashboard to Connect and have it query Snowflake under each viewer's own credentials\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You'll Need\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EA \u003Ca href=\"https://signup.snowflake.com/?utm_source=snowflake-devrel&utm_medium=developer-guides&utm_cta=developer-guides\"\u003ESnowflake account\u003C/a\u003E with Cortex AI enabled\u003C/li\u003E\u003Cli\u003EThe \u003Ca href=\"https://app.snowflake.com/marketplace/listing/GZTSZMCB9S/posit-pbc-posit-team\"\u003EPosit Team Native App\u003C/a\u003E, already installed and configured by an administrator with the \u003Ccode\u003Eaccountadmin\u003C/code\u003E role, and access granted to you\u003C/li\u003E\u003Cli\u003EAccess to the \u003Ca href=\"https://app.snowflake.com/marketplace/listing/GZTSZ290BV255/snowflake-public-data-products-snowflake-public-data-free\"\u003E\u003Ccode\u003ESNOWFLAKE_PUBLIC_DATA_FREE\u003C/code\u003E database\u003C/a\u003E\u003C/li\u003E\u003Cli\u003EA running warehouse you can use for compute. This guide uses \u003Ccode\u003EDEFAULT_WH\u003C/code\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You'll Build\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EAn interactive Shiny for Python dashboard for exploring HMDA mortgage data, published on Connect in the Posit Team Native App and querying Snowflake as each viewer\u003C/li\u003E\u003C/ul\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ECheck Your Access to the Data\u003C/h2\u003E\n","\u003Cp\u003EIn this guide we will use the HMDA dataset from Snowflake's free public database. It holds mortgage application and origination records: loan types, applicant demographics, property characteristics, loan amounts, and outcomes, across U.S. geographic areas.\u003C/p\u003E\n","\u003Cp\u003EThe table is at:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EDatabase:\u003C/strong\u003E \u003Ccode\u003ESNOWFLAKE_PUBLIC_DATA_FREE\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ESchema:\u003C/strong\u003E \u003Ccode\u003EPUBLIC_DATA_FREE\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ETable:\u003C/strong\u003E \u003Ccode\u003EHOME_MORTGAGE_DISCLOSURE_ATTRIBUTES\u003C/code\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EIn Snowsight, click \u003Cstrong\u003E+\u003C/strong\u003E > \u003Cstrong\u003ESQL File\u003C/strong\u003E and run:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESELECT *\nFROM SNOWFLAKE_PUBLIC_DATA_FREE.PUBLIC_DATA_FREE.HOME_MORTGAGE_DISCLOSURE_ATTRIBUTES\nLIMIT 10;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ETen rows should come back. If they do not, ask your account administrator to grant you access to the database.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ELaunch Posit Workbench from the Posit Team Native App\u003C/h2\u003E\n","\u003Ch3\u003EOpen the Native App\u003C/h3\u003E\n","\u003Cp\u003EIn Snowsight, click \u003Cstrong\u003EApps\u003C/strong\u003E in the left sidebar, select the \u003Cstrong\u003EPosit Team Native App\u003C/strong\u003E, then click \u003Cstrong\u003ELaunch app\u003C/strong\u003E.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/snowflake_launch_app.png?v=cfc33e69\" alt=\"The Snowsight Apps listing with Posit Team selected and a Launch app button in the upper right.\"\u003E\u003C/p\u003E\n","\u003Cp\u003EIf you do not see the app, ask your Snowflake account administrator to install the \u003Ca href=\"https://app.snowflake.com/marketplace/listing/GZTSZMCB9S/posit-pbc-posit-team\"\u003EPosit Team Native App\u003C/a\u003E from the Marketplace, \u003Ca href=\"https://docs.posit.co/partnerships/snowflake/posit-team/\"\u003Econfigure\u003C/a\u003E it, and grant you access.\u003C/p\u003E\n","\u003Cp\u003EFrom the Posit Team landing page, click \u003Cstrong\u003EPosit Workbench\u003C/strong\u003E.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/snowflake_launch_workbench.png?v=cfc33e69\" alt=\"The Posit Team Native App landing page with tiles for Posit Workbench and Posit Connect.\"\u003E\u003C/p\u003E\n","\u003Cp\u003EYou may be prompted to sign in to Snowflake with your usual credentials.\u003C/p\u003E\n","\u003Ch3\u003EStart a Positron Pro Session\u003C/h3\u003E\n","\u003Cp\u003EWorkbench offers several IDEs, including Positron Pro, VS Code, RStudio Pro Jupyter Notebook, and JupyterLab. This guide uses Positron Pro, Posit's data science IDE for Python and R.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EClick \u003Cstrong\u003E+ New Session\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/workbench_start_new_session.png?v=cfc33e69\" alt=\"The Posit Workbench home page with a New Session button.\"\u003E\u003C/p\u003E\n\u003Col start=\"2\"\u003E\u003Cli\u003ESelect the \u003Cstrong\u003EPositron Pro\u003C/strong\u003E IDE. You can give the session a name.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/workbench_create_new_session.png?v=cfc33e69\" alt=\"The new session dialog in Workbench with Positron Pro selected as the IDE.\"\u003E\u003C/p\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003ECheck the Snowflake credential under \u003Cstrong\u003ESession Credentials\u003C/strong\u003E. It is listed by account and role, and it is selected when it shows a check mark. If a lock is displayed instead, click it and complete the sign-in prompts. To use a different role, open the drop-down arrow on the right of the credential and choose one that is signed in. Pick a role that can read \u003Ccode\u003ESNOWFLAKE_PUBLIC_DATA_FREE\u003C/code\u003E and use the \u003Ccode\u003EDEFAULT_WH\u003C/code\u003E warehouse. Your session then inherits that role, so your queries use your own identity and grants. See \u003Ca href=\"https://docs.posit.co/ide/server-pro/user/posit-workbench/managed-credentials/managed-credentials.html#starting-a-session-with-workbench-managed-credentials\"\u003EWorkbench-managed credentials\u003C/a\u003E and \u003Ca href=\"https://docs.posit.co/ide/server-pro/user/posit-workbench/managed-credentials/snowflake.html\"\u003EWorkbench-managed Snowflake credentials\u003C/a\u003E for how this works.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/workbench_snowflake_login_success.png?v=cfc33e69\" alt=\"The Session Credentials section of the new session dialog, showing a signed-in Snowflake credential.\"\u003E\u003C/p\u003E\n\u003Col start=\"4\"\u003E\u003Cli\u003EClick \u003Cstrong\u003ELaunch\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003EConfirm You Have the Right Extensions\u003C/h3\u003E\n","\u003Cp\u003EThis guide uses three extensions, all shipped with Positron as \u003Ca href=\"https://positron.posit.co/extensions.html#bootstrapped-extensions\"\u003Ebootstrapped extensions\u003C/a\u003E, so they should already be present:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EThe \u003Ca href=\"https://open-vsx.org/extension/posit/shiny\"\u003EShiny extension\u003C/a\u003E, for running Shiny apps from the editor\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.posit.co/connect/user/publishing-positron-vscode/\"\u003EPosit Publisher\u003C/a\u003E, for one-click deployment to Connect\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://positron.posit.co/assistant.html\"\u003EPosit Assistant\u003C/a\u003E, used in the next section\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EOpen the Extensions view from the activity bar and search for each by name. An installed and enabled extension shows a gear icon; otherwise click \u003Cstrong\u003EInstall\u003C/strong\u003E. If they are disabled and you cannot enable them, ask your administrator.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/positron_extensions.png?v=cfc33e69\" alt=\"The Positron Extensions view with the Shiny extension shown as installed.\"\u003E\u003C/p\u003E\n","\u003Cp\u003EYou can also confirm that the extensions loaded from the activity bar. Posit Assistant and Posit Publisher each add an icon there, highlighted below.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/positron_sidebar_icons.png?v=cfc33e69\" alt=\"The Positron activity bar with the Posit Assistant and Posit Publisher icons highlighted.\"\u003E\u003C/p\u003E\n","\u003Ch3\u003ESet Up Posit Assistant\u003C/h3\u003E\n","\u003Cp\u003E\u003Ca href=\"https://positron.posit.co/assistant.html\"\u003EPosit Assistant\u003C/a\u003E is Positron's AI assistant for data science. Beyond being able to read your active files, selected code, and project structure, it uses context from your interactive work: loaded data, plots, and console history. That is what makes it useful for exploratory analysis rather than only for writing code. The agent works in the same session as you, in much the same way as you would.\u003C/p\u003E\n","\u003Cp\u003EPositron's AI features use a bring-your-own-key model, and \u003Cstrong\u003ESnowflake Cortex\u003C/strong\u003E is one of the available providers. We don't need to manage any credentials because we opened our Workbench session through the Posit Team Native App. Positron will read those credentials, derive your Cortex endpoint from your account, and authenticate the provider for you. Your prompts and your data go to Cortex inside your own Snowflake account, under the same identity your queries use.\u003C/p\u003E\n","\u003Cp\u003EOpen Posit Assistant, which appears in the sidebar or as an editor panel depending on your configuration. Then open the model selector in the chat input area and choose a \u003Cstrong\u003ESnowflake Cortex\u003C/strong\u003E model. Models from other providers appear in the same list and display names repeat across providers, so pick deliberately rather than relying on whichever model is selected by default. When the chat form is narrow the selector collapses into an overflow (\u003Ccode\u003E...\u003C/code\u003E) menu, where the models are grouped under each provider's name.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/positron_assistant_model_picker.png?v=cfc33e69\" alt=\"The Posit Assistant model selector open in the chat input area, with a Snowflake Cortex model listed among the available providers.\"\u003E\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote:\u003C/strong\u003E If Snowflake Cortex is missing from the list, the provider may have been turned off. Provider configuration lives in \u003Ccode\u003E~/.posit/ai/providers.json\u003C/code\u003E — see the \u003Ca href=\"https://positron.posit.co/assistant-getting-started.html\"\u003EPosit Assistant Get Started guide\u003C/a\u003E — and changes require restarting Positron. On a managed Workbench installation this may be your administrator's call.\u003C/p\u003E\n\u003C/blockquote\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EGet the Guide's Materials\u003C/h2\u003E\n","\u003Cp\u003EThe code in this guide lives at \u003Ca href=\"https://github.com/posit-dev/snowflake-posit-python-dashboard-cortex\"\u003Ehttps://github.com/posit-dev/snowflake-posit-python-dashboard-cortex\u003C/a\u003E.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EOpen a terminal in Positron. If one is not already open, use the Command Palette (\u003Ccode\u003ECtrl/Cmd+Shift+P\u003C/code\u003E) and select \u003Cstrong\u003ETerminal: Create New Terminal\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EClone the repository:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Egit clone https://github.com/posit-dev/snowflake-posit-python-dashboard-cortex/\n\u003C/code\u003E\u003C/pre\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote:\u003C/strong\u003E This uses HTTPS for git authentication, so your standard git credentials apply.\u003C/p\u003E\n\u003C/blockquote\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EOpen the folder: Command Palette > \u003Cstrong\u003EFile: Open Folder\u003C/strong\u003E > \u003Ccode\u003Esnowflake-posit-python-dashboard-cortex\u003C/code\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003EInstall the Python Packages\u003C/h3\u003E\n","\u003Cp\u003EThe analysis uses \u003Ca href=\"https://ibis-project.org/\"\u003EIbis\u003C/a\u003E for querying Snowflake, \u003Ca href=\"https://plotnine.org/\"\u003Eplotnine\u003C/a\u003E for plots, \u003Ca href=\"https://shiny.posit.co/py/\"\u003EShiny for Python\u003C/a\u003E for the dashboard, and \u003Ca href=\"https://github.com/posit-dev/posit-sdk-py\"\u003Eposit-sdk\u003C/a\u003E for the Connect credential exchange. They are listed in \u003Ccode\u003Erequirements.txt\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003ERun the following commands in the Positron terminal (not in a Quarto chunk). Create a virtual environment and install the packages:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Epython -m venv .venv\nsource .venv/bin/activate\npython -m pip install -r requirements.txt\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThen select that interpreter in Positron: Command Palette > \u003Cstrong\u003EPython: Select Interpreter\u003C/strong\u003E > the \u003Ccode\u003E.venv\u003C/code\u003E entry.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote:\u003C/strong\u003E If installation fails to resolve a package, your Workbench session may point at a package mirror that predates it. Ask your administrator, or add \u003Ccode\u003E--extra-index-url https://pypi.org/simple\u003C/code\u003E to \u003Ccode\u003Erequirements.txt\u003C/code\u003E if your organization's policy allows it.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EA Word on Quarto\u003C/h3\u003E\n","\u003Cp\u003EThe narrative version of this analysis is a Quarto document, \u003Ca href=\"https://github.com/posit-dev/snowflake-posit-python-dashboard-cortex/blob/main/quarto.qmd\"\u003Equarto.qmd\u003C/a\u003E. Think of it as a Markdown document that can also run code. Click \u003Cstrong\u003ERun Cell\u003C/strong\u003E above any chunk to execute it, or click \u003Cstrong\u003EPreview\u003C/strong\u003E to render the whole document to HTML. Learn more at \u003Ca href=\"https://quarto.org/\"\u003Ehttps://quarto.org/\u003C/a\u003E.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/quarto_run_chunk.png?v=cfc33e69\" alt=\"The Run Cell button above a Python code chunk in quarto.qmd, open in Positron.\"\u003E\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EConnect to Snowflake from Python\u003C/h2\u003E\n","\u003Cp\u003EOpen \u003Ccode\u003Equarto.qmd\u003C/code\u003E and run the first code chunk.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003Eimport ibis\n\ncon = ibis.snowflake.connect(\n    warehouse="DEFAULT_WH",\n    database="SNOWFLAKE_PUBLIC_DATA_FREE",\n    schema="PUBLIC_DATA_FREE",\n    connection_name="workbench",\n)\n\nmortgage_data = con.table("HOME_MORTGAGE_DISCLOSURE_ATTRIBUTES")\nmortgage_data.schema()\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EIbis is a dataframe library that compiles Python expressions into SQL and runs them on a backend, in this case Snowflake. \u003Ccode\u003Econnection_name="workbench"\u003C/code\u003E is the important part. When you signed in to the Snowflake credential, Workbench wrote a \u003Ccode\u003Econnections.toml\u003C/code\u003E file containing a profile named \u003Ccode\u003Eworkbench\u003C/code\u003E with your account and a short-lived OAuth token, and pointed \u003Ccode\u003ESNOWFLAKE_HOME\u003C/code\u003E at it. Naming that profile is all it takes, so no account identifier, user, or password appears anywhere in your code.\u003C/p\u003E\n","\u003Cp\u003E\u003Ccode\u003Emortgage_data\u003C/code\u003E is a lazy table expression, not data. Filters and aggregations build up a query, and rows come back only when you ask for them:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003Eibis.options.interactive = True\n\nmortgage_data.select("YEAR", "STATE_NAME", "LOAN_TYPE", "LOAN_AMOUNT").head(10)\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThis matters for a dashboard over a table this size. Aggregate first, collect second. To see what Ibis sends to Snowflake, use \u003Ccode\u003Eibis.to_sql()\u003C/code\u003E:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003Eibis.to_sql(\n    mortgage_data.group_by("YEAR").aggregate(count=lambda t: t.count()).order_by("YEAR")\n)\n\u003C/code\u003E\u003C/pre\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote:\u003C/strong\u003E You may see a warning about \u003Ccode\u003EUnable to create Ibis UDFs\u003C/code\u003E when connecting. It means your role cannot create those helper functions, and it is safe to ignore for this guide.\u003C/p\u003E\n\u003C/blockquote\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EExplore the Data with Posit Assistant\u003C/h2\u003E\n","\u003Cp\u003EPosit Assistant already has \u003Ccode\u003Econ\u003C/code\u003E and \u003Ccode\u003Emortgage_data\u003C/code\u003E in its context, so we can have it help us with some of the analysis. Since it can read the variables in your live Python session, so you can refer to them by name.\u003C/p\u003E\n","\u003Cp\u003EOpen Posit Assistant and try.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003ESummarize the structure of the mortgage_data table\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EIt will write and run code to show columns, types, and basic statistics.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EExplore the relationship between loan amounts and property types\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/positron_assistant_eda.png?v=cfc33e69\" alt=\"Posit Assistant answering an exploratory data analysis prompt, with the generated Python code and a resulting plot visible in the session.\"\u003E\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EHow do loan approval rates vary across states? Push the work down to Snowflake.\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EYou might need to ask it to do some of the work in the database explicitly. This way it will stop reaching for \u003Ccode\u003Eto_pandas()\u003C/code\u003E which would pull the whole table into memory.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003ECheck mortgage_data for missing values and data quality issues\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EPosit Assistant has many of the affordances other AI agents have, such as plan mode and memory. It additionally have built-in skills to work specifically with Posit Products and their open source packages. Hence why it is able to work on the shiny for Python app so easily.\u003C/p\u003E\n","\u003Cp\u003EWhen you are done exploring you can use the \u003Ccode\u003E/report\u003C/code\u003E skill to create a Quarto document from the conversation. This is especially useful as it is a document we can work with in the future if we need to.\u003C/p\u003E\n","\u003Cp\u003EFor the full feature set, see the \u003Ca href=\"https://assistant.posit.co/docs/getting-started/\"\u003EPosit Assistant documentation\u003C/a\u003E.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EBuild the Dashboard\u003C/h2\u003E\n","\u003Cp\u003ENow build the dashboard. The complete app is \u003Ccode\u003Eapp.py\u003C/code\u003E in the repository you cloned. Open it and read through it. The remainder of this section will explain some of the specifics.\u003C/p\u003E\n","\u003Ch3\u003ECredentials Are Resolved Per Session\u003C/h3\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003Edef credentials(session):\n    # POSIT_PRODUCT since Connect 2025.02.0; RSTUDIO_PRODUCT is the deprecated\n    # spelling, kept as a fallback for older Connect versions.\n    on_connect = "CONNECT" in (\n        os.getenv("POSIT_PRODUCT"),\n        os.getenv("RSTUDIO_PRODUCT"),\n    )\n    if on_connect:\n        token = session.http_conn.headers.get("Posit-Connect-User-Session-Token")\n        if token is None:\n            raise RuntimeError(\n                "No Posit-Connect-User-Session-Token header. Attach the "\n                "Snowflake integration to this content in Connect."\n            )\n        auth = PositAuthenticator(\n            local_authenticator="EXTERNALBROWSER",\n            user_session_token=token,\n        )\n        return {\n            # Connect sets SNOWFLAKE_ACCOUNT from the attached integration.\n            "account": os.getenv("SNOWFLAKE_ACCOUNT"),\n            "authenticator": auth.authenticator,\n            "token": auth.token,\n        }\n\n    if os.getenv("SNOWFLAKE_HOME") is not None:\n        return {"connection_name": "workbench"}\n\n    raise RuntimeError("No Snowflake credentials found.")\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThe same file has to work in two places. In Workbench it uses the managed credentials, exactly as the Quarto document did. On Connect, the viewer's identity arrives as the \u003Ccode\u003EPosit-Connect-User-Session-Token\u003C/code\u003E header on their Shiny session, and \u003Ccode\u003EPositAuthenticator\u003C/code\u003E exchanges it for a Snowflake OAuth token.\u003C/p\u003E\n","\u003Cp\u003EBecause that token is per viewer and arrives on the session, \u003Ccode\u003Ecredentials(session)\u003C/code\u003E is called from inside \u003Ccode\u003Eserver()\u003C/code\u003E, not at the top of the file. Every connection in the app is built from its result, so every query the dashboard runs is attributed to the person looking at it. This is all done to make sure the people looking at the dashboard have the right permissions.\u003C/p\u003E\n","\u003Ch3\u003EThe Filters Stay Lazy\u003C/h3\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003E@reactive.calc\ndef filtered():\n    low, high = input.loan_amount()\n    data = mortgage_data.filter(\n        mortgage_data.LOAN_AMOUNT >= low,\n        mortgage_data.LOAN_AMOUNT <= high,\n    )\n    if input.loan_type() != "All":\n        data = data.filter(mortgage_data.LOAN_TYPE == input.loan_type())\n    if input.state() != "All":\n        data = data.filter(mortgage_data.STATE_NAME == input.state())\n    return data\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Ccode\u003Efiltered()\u003C/code\u003E returns an Ibis expression, not a dataframe. No rows have moved. Each output then narrows it further and materializes only what it needs, so we don't have to move the data in and out of the database, instead only fetching what we need.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003E@reactive.calc\ndef metrics():\n    return (\n        filtered()\n        .aggregate(\n            n=lambda t: t.count(),\n            avg=lambda t: t.LOAN_AMOUNT.mean(),\n            total=lambda t: t.LOAN_AMOUNT.sum(),\n        )\n        .to_pandas()\n        .iloc[0]\n    )\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThat query returns one row regardless of how many applications matched.\u003C/p\u003E\n","\u003Ch3\u003EAnything Row-Level Is Bounded\u003C/h3\u003E\n","\u003Cp\u003EThe histogram is the one output that needs individual rows rather than an aggregate, so it is capped explicitly.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003E@reactive.calc\ndef amount_sample():\n    return filtered().select("LOAN_AMOUNT").limit(50_000).to_pandas()\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EIf we didn't do this, the dashboard would try to fetch the entire table into the app process. This would not only be very time consuming with larger datasets, leading to significant hangs, but could also try to pull in more data than the session has room for.\u003C/p\u003E\n","\u003Cp\u003ENote that for this dashboard we have decided to return the first 50,000 rows Snowflake happens to produce. This may or may not be what you want in your application.\u003C/p\u003E\n","\u003Ch3\u003ERun It\u003C/h3\u003E\n","\u003Cp\u003EFrom the terminal:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Eshiny run --reload app.py\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EOr open \u003Ccode\u003Eapp.py\u003C/code\u003E and click the \u003Cstrong\u003ERun App\u003C/strong\u003E button in the editor toolbar. The dashboard opens in the Viewer pane. The \u003Ccode\u003E--reload\u003C/code\u003E flag enables auto-reload, meaning that it will watch for changes in \u003Ccode\u003Eapp.py\u003C/code\u003E and restart the app accordingly.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/shiny_run_app.png?v=cfc33e69\" alt=\"The dashboard running in the Positron Viewer pane, with filters, three value boxes, and both plots populated.\"\u003E\u003C/p\u003E\n","\u003Ch3\u003ERefine It with Posit Assistant\u003C/h3\u003E\n","\u003Cp\u003EThe dashboard is deliberately plain. Use Posit Assistant to take it further. It can see \u003Ccode\u003Eapp.py\u003C/code\u003E, and the built-in \u003Ccode\u003Eshiny-bslib\u003C/code\u003E skill in Posit Assistant loads automatically when it is relevant to your request. Try:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EAdd a tab that shows approval rates by state\n\u003C/code\u003E\u003C/pre\u003E\n\u003Cpre\u003E\u003Ccode\u003EPopulate the state dropdown from the distinct STATE_NAME values in the table rather than hardcoding five states\n\u003C/code\u003E\u003C/pre\u003E\n\u003Cpre\u003E\u003Ccode\u003EImprove the layout and color palette of this dashboard\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EKeep iterating until you are happy with it.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EPublish to Posit Connect\u003C/h2\u003E\n","\u003Cp\u003EBecause Workbench and Connect run inside the Posit Team Native App, publishing does not involve any network or authentication setup.\u003C/p\u003E\n","\u003Ch3\u003ECreate an API Key\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003EOpen Posit Connect from the Posit Team Native App.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/snowflake_launch_connect.png?v=cfc33e69\" alt=\"The Posit Team Native App landing page with the Posit Connect tile.\"\u003E\u003C/p\u003E\n\u003Col start=\"2\"\u003E\u003Cli\u003EClick your account in the upper right, then \u003Cstrong\u003EManage Your API Keys\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/connect_manage_api_keys.png?v=cfc33e69\" alt=\"The Connect account menu expanded, showing the Manage Your API Keys item.\"\u003E\u003C/p\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003EClick \u003Cstrong\u003EAdd API key\u003C/strong\u003E. In the drawer that opens, name the key, select the \u003Cstrong\u003EPublisher\u003C/strong\u003E role, and choose when it expires. Then create it.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/connect_new_api_key.png?v=cfc33e69\" alt=\"The Add API key drawer in Connect with a name filled in and the Publisher role selected.\"\u003E\u003C/p\u003E\n\u003Col start=\"4\"\u003E\u003Cli\u003ECopy the key somewhere safe. Once you close, it is not shown again.\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003EDeploy in One Click\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003EIn Positron, click the Posit Publisher icon in the tool menu.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/posit_publisher.png?v=cfc33e69\" alt=\"The Positron activity bar with the Posit Publisher icon highlighted.\"\u003E\u003C/p\u003E\n\u003Col start=\"2\"\u003E\u003Cli\u003E\n","\u003Cp\u003EUnder \u003Cstrong\u003EDeployment\u003C/strong\u003E, click \u003Cstrong\u003ESelect...\u003C/strong\u003E and create a new deployment. Choose \u003Ccode\u003Eapp.py\u003C/code\u003E as the entrypoint.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect the Connect server, or add a new one with the URL \u003Ccode\u003Ehttps://connect/\u003C/code\u003E, and paste in your API key.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/deploy_connect.png?v=cfc33e69\" alt=\"The Posit Publisher credential dialog with a Connect server URL and API key field.\"\u003E\u003C/p\u003E\n\u003Col start=\"4\"\u003E\u003Cli\u003EInclude these files:\u003C/li\u003E\u003C/ol\u003E\n\u003Cul\u003E\u003Cli\u003E[x] \u003Ccode\u003Eapp.py\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E[x] \u003Ccode\u003Erequirements.txt\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E[x] \u003Ccode\u003E.python-version\u003C/code\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/publisher_deployment_config.png?v=cfc33e69\" alt=\"The Posit Publisher deployment configuration panel listing the files included in the bundle.\"\u003E\u003C/p\u003E\n","\u003Cp\u003EThe \u003Ccode\u003E.python-version\u003C/code\u003E file that selected your session interpreter also travels into the deployment, so confirm it sits alongside \u003Ccode\u003Eapp.py\u003C/code\u003E and reads \u003Ccode\u003E3.12\u003C/code\u003E. Publisher reads it when generating the deployment manifest, which records \u003Ccode\u003E>=3.12\u003C/code\u003E as an explicit version constraint rather than just noting whichever interpreter you happened to author with. Connect then picks a matching Python installation. It ships in the repository; if you are adapting this pattern in a project of your own, create it with:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Eecho "3.12" > .python-version\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col start=\"5\"\u003E\u003Cli\u003EClick \u003Cstrong\u003EIntegration requests\u003C/strong\u003E > \u003Cstrong\u003E+\u003C/strong\u003E > the available Snowflake integration.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/publisher_snowflake_integration.png?v=cfc33e69\" alt=\"The Integration Requests section of the Posit Publisher panel with a Snowflake OAuth integration listed.\"\u003E\u003C/p\u003E\n\u003Col start=\"6\"\u003E\u003Cli\u003EClick \u003Cstrong\u003EDeploy your project\u003C/strong\u003E and watch the log.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/deploy_log_success.png?v=cfc33e69\" alt=\"A Connect deployment log ending in a success message.\"\u003E\u003C/p\u003E\n","\u003Cp\u003ESee \u003Ca href=\"https://docs.posit.co/connect/user/publishing-positron-vscode/\"\u003EPublishing from VS Code or Positron\u003C/a\u003E for more on this step.\u003C/p\u003E\n","\u003Ch3\u003EFinish the Setup in Connect\u003C/h3\u003E\n","\u003Cp\u003EWhen the deployment succeeds, click the link to your content at the end of the deployment log. This opens the app in Connect, where the remaining settings live.\u003C/p\u003E\n","\u003Cp\u003EOne step does not travel in the bundle. Open \u003Cstrong\u003EContent Settings\u003C/strong\u003E, go to the \u003Cstrong\u003ERuntime\u003C/strong\u003E tab, and in the \u003Cstrong\u003EIntegrations\u003C/strong\u003E section click \u003Cstrong\u003EAdd Integrations\u003C/strong\u003E and select the Snowflake integration. Clicking \u003Cstrong\u003EIntegration requests\u003C/strong\u003E in Publisher records a \u003Cem\u003Erequest\u003C/em\u003E in the bundle; associating the integration is a separate action in Connect.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/connect_runtime_integration.png?v=cfc33e69\" alt=\"The Runtime tab of Connect content settings with a Snowflake OAuth integration associated in the Integrations section.\"\u003E\u003C/p\u003E\n","\u003Cp\u003EIf the dashboard errors on first load, this is almost always why: without the association Connect reports \u003Ccode\u003ENo OAuth integrations have been associated with this content item\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003EAttaching the integration also sets \u003Ccode\u003ESNOWFLAKE_ACCOUNT\u003C/code\u003E on the content, which is where the app's connection gets its account identifier. You do not have to add it yourself.\u003C/p\u003E\n","\u003Cp\u003EFinally, decide who can open the dashboard. Connect defaults a new deployment to specific users or groups, so only you (and anyone you add) can see it. Still in \u003Cstrong\u003EContent Settings\u003C/strong\u003E, open the \u003Cstrong\u003EAccess\u003C/strong\u003E tab and change the setting to \u003Cstrong\u003EAll users - login required\u003C/strong\u003E. Anyone with an account on this Connect server can then open the dashboard, and each viewer's queries still run under their own Snowflake identity.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EUse and Share the Dashboard\u003C/h2\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EIn Connect, open the \u003Cstrong\u003EContent\u003C/strong\u003E tab and click your dashboard.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EExercise the filters and confirm the metrics and plots update.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/dashboard_published.png?v=cfc33e69\" alt=\"The published Shiny for Python dashboard running on Connect, with filters, value boxes, and plots showing HMDA mortgage data.\"\u003E\u003C/p\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003ETo share it, open the \u003Cstrong\u003EContent Settings\u003C/strong\u003E pane in the upper right, and on the \u003Cstrong\u003EGeneral\u003C/strong\u003E tab copy the URL from the \u003Cstrong\u003EContent URL\u003C/strong\u003E section. Send that to your team.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EBecause you attached the Snowflake integration, the dashboard uses viewer-level authentication: each person who opens it connects to Snowflake as themselves. Two colleagues with different grants on \u003Ccode\u003ESNOWFLAKE_PUBLIC_DATA_FREE\u003C/code\u003E will see different results from the same dashboard, with no filtering logic in your code. Your Snowflake RBAC policy decides what data each person sees.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote:\u003C/strong\u003E Viewers still need an account on Posit Connect to open the dashboard, because the access setting above requires a login. Snowflake RBAC controls which data they see, not whether they can reach the dashboard. Ask your Connect administrator to add the people you want to share with.\u003C/p\u003E\n\u003C/blockquote\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EConclusion And Resources\u003C/h2\u003E\n","\u003Cp\u003EYou connected to Snowflake from Positron Pro in Workbench using managed credentials, queried the data from Python with Ibis without moving it out of the database, explored it with Posit Assistant backed by a Cortex model, built an interactive Shiny for Python dashboard, and published it to Connect where it runs under each viewer's own Snowflake identity.\u003C/p\u003E\n","\u003Ch3\u003EWhat You Learned\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EHow to connect Positron Pro to Snowflake with Workbench-managed credentials, keeping secrets out of your code\u003C/li\u003E\u003Cli\u003EHow to use Ibis to keep filtering and aggregation in Snowflake instead of in Python\u003C/li\u003E\u003Cli\u003EHow to use Posit Assistant with Snowflake Cortex AI for exploratory analysis and app refinement\u003C/li\u003E\u003Cli\u003EHow to build an interactive Shiny for Python dashboard over a Snowflake table without collecting it\u003C/li\u003E\u003Cli\u003EHow to write one app file that authenticates correctly in both Workbench and Connect\u003C/li\u003E\u003Cli\u003EHow to publish to Connect with viewer-level Snowflake authentication, so RBAC is enforced per viewer\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003ERelated Resources\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EMaterials for this guide: \u003Ca href=\"https://github.com/posit-dev/snowflake-posit-python-dashboard-cortex\"\u003Esnowflake-posit-python-dashboard-cortex\u003C/a\u003E\u003C/li\u003E\u003Cli\u003EThe R version of this guide: \u003Ca href=\"https://www.snowflake.com/en/developers/guides/build-and-deploy-interactive-dashboard-with-posit-team-and-cortex/\"\u003EBuild and Deploy an Interactive Shiny Dashboard with the Posit Team Native App and Snowflake Cortex AI\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/developers/guides/analyze-data-with-python-using-posit-team/\"\u003EAnalyze Data with Python using the Posit Team Native App and Snowflake\u003C/a\u003E\u003C/li\u003E\u003Cli\u003ESnowflake Cortex AI: \u003Ca href=\"https://docs.snowflake.com/en/user-guide/snowflake-cortex/llm-functions\"\u003ELLM Functions\u003C/a\u003E\u003C/li\u003E\u003Cli\u003EPosit Assistant: \u003Ca href=\"https://assistant.posit.co/docs/getting-started/\"\u003Edocumentation\u003C/a\u003E and \u003Ca href=\"https://positron.posit.co/assistant.html\"\u003EPositron overview\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://ibis-project.org/\"\u003EIbis\u003C/a\u003E and its \u003Ca href=\"https://ibis-project.org/backends/snowflake\"\u003ESnowflake backend\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://shiny.posit.co/py/\"\u003EShiny for Python\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.posit.co/ide/server-pro/user/\"\u003EPosit Workbench user guide\u003C/a\u003E and \u003Ca href=\"https://docs.posit.co/connect/user/\"\u003EPosit Connect user guide\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.posit.co/partnerships/snowflake/posit-team/\"\u003EPosit Team Native App documentation\u003C/a\u003E\u003C/li\u003E\u003C/ul\u003E"],"description":"","title":"Build and Deploy an Interactive Python Dashboard with the Posit Team Native App and Snowflake Cortex AI","isDeveloperGuidesPage":false,":type":"snowflake-site/components/contentfragment",":items":{},":itemsOrder":[],"elements":{"quickstartArticleBody":{"dataType":"string","title":"Quickstart Article Body","value":"\u003C!-- ------------------------ --\u003E\n## Overview\n\nIn this guide, we will use the Posit Team Native App to build an interactive Python dashboard over Home Mortgage Disclosure Act (HMDA) data. In Posit Workbench you will open the Positron Pro IDE, connect to Snowflake with Ibis, and use Posit Assistant with a Snowflake Cortex AI model to explore the data. Then you will build a Shiny for Python dashboard and publish it to Posit Connect with one-click deployment, so your whole team can use it.\n\n![Architecture diagram: Positron Pro in Posit Workbench queries Snowflake with the user's own credentials and publishes to Posit Connect, which queries Snowflake on behalf of each dashboard viewer. Both Workbench and Connect run inside the Snowflake account as part of the Posit Team Native App.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/overview_architecture.png?v=cfc33e69)\n\nThe deployed dashboard respects Snowflake's own security and authorization settings. Because you attach Connect's Snowflake integration to the content before publishing, each viewer's queries run under their own Snowflake identity, so they see only the data they have been granted.\n\nBy the end you will have a working dashboard where users filter mortgage applications by loan type, state, and loan amount, and see the resulting distribution of loan amounts, three headline metrics, and a year-over-year trend.\n\nThis guide is the Python counterpart to [Build and Deploy an Interactive Shiny Dashboard with the Posit Team Native App and Snowflake Cortex AI](https://www.snowflake.com/en/developers/guides/build-and-deploy-interactive-dashboard-with-posit-team-and-cortex/), which covers the same process within R.\n\n### Prerequisites\n\n- Familiarity with SQL and Python\n- Some exposure to reactive dashboards is helpful but not required\n\n### What You'll Learn\n\n- How to connect to Snowflake from Positron Pro in Workbench using Workbench-managed credentials, with no secrets in your code\n- How to query Snowflake from Python with Ibis, keeping the work in the database\n- How to use Posit Assistant with a Snowflake Cortex AI model for exploratory data analysis and for refining app code\n- How to build an interactive Shiny for Python dashboard over a Snowflake table\n- How to publish that dashboard to Connect and have it query Snowflake under each viewer's own credentials\n\n### What You'll Need\n\n- A [Snowflake account](https://signup.snowflake.com/?utm_source=snowflake-devrel&utm_medium=developer-guides&utm_cta=developer-guides) with Cortex AI enabled\n- The [Posit Team Native App](https://app.snowflake.com/marketplace/listing/GZTSZMCB9S/posit-pbc-posit-team), already installed and configured by an administrator with the `accountadmin` role, and access granted to you\n- Access to the [`SNOWFLAKE_PUBLIC_DATA_FREE` database](https://app.snowflake.com/marketplace/listing/GZTSZ290BV255/snowflake-public-data-products-snowflake-public-data-free)\n- A running warehouse you can use for compute. This guide uses `DEFAULT_WH`\n\n### What You'll Build\n\n- An interactive Shiny for Python dashboard for exploring HMDA mortgage data, published on Connect in the Posit Team Native App and querying Snowflake as each viewer\n\n\u003C!-- ------------------------ --\u003E\n## Check Your Access to the Data\n\nIn this guide we will use the HMDA dataset from Snowflake's free public database. It holds mortgage application and origination records: loan types, applicant demographics, property characteristics, loan amounts, and outcomes, across U.S. geographic areas.\n\nThe table is at:\n\n- **Database:** `SNOWFLAKE_PUBLIC_DATA_FREE`\n- **Schema:** `PUBLIC_DATA_FREE`\n- **Table:** `HOME_MORTGAGE_DISCLOSURE_ATTRIBUTES`\n\nIn Snowsight, click **+** \u003E **SQL File** and run:\n\n```sql\nSELECT *\nFROM SNOWFLAKE_PUBLIC_DATA_FREE.PUBLIC_DATA_FREE.HOME_MORTGAGE_DISCLOSURE_ATTRIBUTES\nLIMIT 10;\n```\n\nTen rows should come back. If they do not, ask your account administrator to grant you access to the database.\n\n\u003C!-- ------------------------ --\u003E\n## Launch Posit Workbench from the Posit Team Native App\n\n### Open the Native App\n\nIn Snowsight, click **Apps** in the left sidebar, select the **Posit Team Native App**, then click **Launch app**.\n\n![The Snowsight Apps listing with Posit Team selected and a Launch app button in the upper right.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/snowflake_launch_app.png?v=cfc33e69)\n\nIf you do not see the app, ask your Snowflake account administrator to install the [Posit Team Native App](https://app.snowflake.com/marketplace/listing/GZTSZMCB9S/posit-pbc-posit-team) from the Marketplace, [configure](https://docs.posit.co/partnerships/snowflake/posit-team/) it, and grant you access.\n\nFrom the Posit Team landing page, click **Posit Workbench**.\n\n![The Posit Team Native App landing page with tiles for Posit Workbench and Posit Connect.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/snowflake_launch_workbench.png?v=cfc33e69)\n\nYou may be prompted to sign in to Snowflake with your usual credentials.\n\n### Start a Positron Pro Session\n\nWorkbench offers several IDEs, including Positron Pro, VS Code, RStudio Pro Jupyter Notebook, and JupyterLab. This guide uses Positron Pro, Posit's data science IDE for Python and R.\n\n1. Click **+ New Session**.\n\n![The Posit Workbench home page with a New Session button.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/workbench_start_new_session.png?v=cfc33e69)\n\n2. Select the **Positron Pro** IDE. You can give the session a name.\n\n![The new session dialog in Workbench with Positron Pro selected as the IDE.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/workbench_create_new_session.png?v=cfc33e69)\n\n3. Check the Snowflake credential under **Session Credentials**. It is listed by account and role, and it is selected when it shows a check mark. If a lock is displayed instead, click it and complete the sign-in prompts. To use a different role, open the drop-down arrow on the right of the credential and choose one that is signed in. Pick a role that can read `SNOWFLAKE_PUBLIC_DATA_FREE` and use the `DEFAULT_WH` warehouse. Your session then inherits that role, so your queries use your own identity and grants. See [Workbench-managed credentials](https://docs.posit.co/ide/server-pro/user/posit-workbench/managed-credentials/managed-credentials.html#starting-a-session-with-workbench-managed-credentials) and [Workbench-managed Snowflake credentials](https://docs.posit.co/ide/server-pro/user/posit-workbench/managed-credentials/snowflake.html) for how this works.\n\n![The Session Credentials section of the new session dialog, showing a signed-in Snowflake credential.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/workbench_snowflake_login_success.png?v=cfc33e69)\n\n4. Click **Launch**.\n\n### Confirm You Have the Right Extensions\n\nThis guide uses three extensions, all shipped with Positron as [bootstrapped extensions](https://positron.posit.co/extensions.html#bootstrapped-extensions), so they should already be present:\n\n- The [Shiny extension](https://open-vsx.org/extension/posit/shiny), for running Shiny apps from the editor\n- [Posit Publisher](https://docs.posit.co/connect/user/publishing-positron-vscode/), for one-click deployment to Connect\n- [Posit Assistant](https://positron.posit.co/assistant.html), used in the next section\n\nOpen the Extensions view from the activity bar and search for each by name. An installed and enabled extension shows a gear icon; otherwise click **Install**. If they are disabled and you cannot enable them, ask your administrator.\n\n![The Positron Extensions view with the Shiny extension shown as installed.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/positron_extensions.png?v=cfc33e69)\n\nYou can also confirm that the extensions loaded from the activity bar. Posit Assistant and Posit Publisher each add an icon there, highlighted below.\n\n![The Positron activity bar with the Posit Assistant and Posit Publisher icons highlighted.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/positron_sidebar_icons.png?v=cfc33e69)\n\n### Set Up Posit Assistant\n\n[Posit Assistant](https://positron.posit.co/assistant.html) is Positron's AI assistant for data science. Beyond being able to read your active files, selected code, and project structure, it uses context from your interactive work: loaded data, plots, and console history. That is what makes it useful for exploratory analysis rather than only for writing code. The agent works in the same session as you, in much the same way as you would.\n\nPositron's AI features use a bring-your-own-key model, and **Snowflake Cortex** is one of the available providers. We don't need to manage any credentials because we opened our Workbench session through the Posit Team Native App. Positron will read those credentials, derive your Cortex endpoint from your account, and authenticate the provider for you. Your prompts and your data go to Cortex inside your own Snowflake account, under the same identity your queries use.\n\nOpen Posit Assistant, which appears in the sidebar or as an editor panel depending on your configuration. Then open the model selector in the chat input area and choose a **Snowflake Cortex** model. Models from other providers appear in the same list and display names repeat across providers, so pick deliberately rather than relying on whichever model is selected by default. When the chat form is narrow the selector collapses into an overflow (`...`) menu, where the models are grouped under each provider's name.\n\n![The Posit Assistant model selector open in the chat input area, with a Snowflake Cortex model listed among the available providers.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/positron_assistant_model_picker.png?v=cfc33e69)\n\n\u003E **Note:** If Snowflake Cortex is missing from the list, the provider may have been turned off. Provider configuration lives in `~/.posit/ai/providers.json` — see the [Posit Assistant Get Started guide](https://positron.posit.co/assistant-getting-started.html) — and changes require restarting Positron. On a managed Workbench installation this may be your administrator's call.\n\n\u003C!-- ------------------------ --\u003E\n## Get the Guide's Materials\n\nThe code in this guide lives at \u003Chttps://github.com/posit-dev/snowflake-posit-python-dashboard-cortex\u003E.\n\n1. Open a terminal in Positron. If one is not already open, use the Command Palette (`Ctrl/Cmd+Shift+P`) and select **Terminal: Create New Terminal**.\n\n2. Clone the repository:\n\n   ```bash\n   git clone https://github.com/posit-dev/snowflake-posit-python-dashboard-cortex/\n   ```\n\n   \u003E **Note:** This uses HTTPS for git authentication, so your standard git credentials apply.\n\n3. Open the folder: Command Palette \u003E **File: Open Folder** \u003E `snowflake-posit-python-dashboard-cortex`.\n\n### Install the Python Packages\n\nThe analysis uses [Ibis](https://ibis-project.org/) for querying Snowflake, [plotnine](https://plotnine.org/) for plots, [Shiny for Python](https://shiny.posit.co/py/) for the dashboard, and [posit-sdk](https://github.com/posit-dev/posit-sdk-py) for the Connect credential exchange. They are listed in `requirements.txt`.\n\nRun the following commands in the Positron terminal (not in a Quarto chunk). Create a virtual environment and install the packages:\n\n```bash\npython -m venv .venv\nsource .venv/bin/activate\npython -m pip install -r requirements.txt\n```\n\nThen select that interpreter in Positron: Command Palette \u003E **Python: Select Interpreter** \u003E the `.venv` entry.\n\n\u003E **Note:** If installation fails to resolve a package, your Workbench session may point at a package mirror that predates it. Ask your administrator, or add `--extra-index-url https://pypi.org/simple` to `requirements.txt` if your organization's policy allows it.\n\n### A Word on Quarto\n\nThe narrative version of this analysis is a Quarto document, [quarto.qmd](https://github.com/posit-dev/snowflake-posit-python-dashboard-cortex/blob/main/quarto.qmd). Think of it as a Markdown document that can also run code. Click **Run Cell** above any chunk to execute it, or click **Preview** to render the whole document to HTML. Learn more at \u003Chttps://quarto.org/\u003E.\n\n![The Run Cell button above a Python code chunk in quarto.qmd, open in Positron.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/quarto_run_chunk.png?v=cfc33e69)\n\n\u003C!-- ------------------------ --\u003E\n## Connect to Snowflake from Python\n\nOpen `quarto.qmd` and run the first code chunk.\n\n```python\nimport ibis\n\ncon = ibis.snowflake.connect(\n    warehouse=\"DEFAULT_WH\",\n    database=\"SNOWFLAKE_PUBLIC_DATA_FREE\",\n    schema=\"PUBLIC_DATA_FREE\",\n    connection_name=\"workbench\",\n)\n\nmortgage_data = con.table(\"HOME_MORTGAGE_DISCLOSURE_ATTRIBUTES\")\nmortgage_data.schema()\n```\n\nIbis is a dataframe library that compiles Python expressions into SQL and runs them on a backend, in this case Snowflake. `connection_name=\"workbench\"` is the important part. When you signed in to the Snowflake credential, Workbench wrote a `connections.toml` file containing a profile named `workbench` with your account and a short-lived OAuth token, and pointed `SNOWFLAKE_HOME` at it. Naming that profile is all it takes, so no account identifier, user, or password appears anywhere in your code.\n\n`mortgage_data` is a lazy table expression, not data. Filters and aggregations build up a query, and rows come back only when you ask for them:\n\n```python\nibis.options.interactive = True\n\nmortgage_data.select(\"YEAR\", \"STATE_NAME\", \"LOAN_TYPE\", \"LOAN_AMOUNT\").head(10)\n```\n\nThis matters for a dashboard over a table this size. Aggregate first, collect second. To see what Ibis sends to Snowflake, use `ibis.to_sql()`:\n\n```python\nibis.to_sql(\n    mortgage_data.group_by(\"YEAR\").aggregate(count=lambda t: t.count()).order_by(\"YEAR\")\n)\n```\n\n\u003E **Note:** You may see a warning about `Unable to create Ibis UDFs` when connecting. It means your role cannot create those helper functions, and it is safe to ignore for this guide.\n\n\u003C!-- ------------------------ --\u003E\n## Explore the Data with Posit Assistant\n\nPosit Assistant already has `con` and `mortgage_data` in its context, so we can have it help us with some of the analysis. Since it can read the variables in your live Python session, so you can refer to them by name.\n\nOpen Posit Assistant and try.\n\n```\nSummarize the structure of the mortgage_data table\n```\n\nIt will write and run code to show columns, types, and basic statistics.\n\n```\nExplore the relationship between loan amounts and property types\n```\n\n![Posit Assistant answering an exploratory data analysis prompt, with the generated Python code and a resulting plot visible in the session.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/positron_assistant_eda.png?v=cfc33e69)\n\n```\nHow do loan approval rates vary across states? Push the work down to Snowflake.\n```\n\nYou might need to ask it to do some of the work in the database explicitly. This way it will stop reaching for `to_pandas()` which would pull the whole table into memory.\n\n```\nCheck mortgage_data for missing values and data quality issues\n```\n\nPosit Assistant has many of the affordances other AI agents have, such as plan mode and memory. It additionally have built-in skills to work specifically with Posit Products and their open source packages. Hence why it is able to work on the shiny for Python app so easily.\n\nWhen you are done exploring you can use the `/report` skill to create a Quarto document from the conversation. This is especially useful as it is a document we can work with in the future if we need to.\n\nFor the full feature set, see the [Posit Assistant documentation](https://assistant.posit.co/docs/getting-started/).\n\n\u003C!-- ------------------------ --\u003E\n## Build the Dashboard\n\nNow build the dashboard. The complete app is `app.py` in the repository you cloned. Open it and read through it. The remainder of this section will explain some of the specifics.\n\n### Credentials Are Resolved Per Session\n\n```python\ndef credentials(session):\n    # POSIT_PRODUCT since Connect 2025.02.0; RSTUDIO_PRODUCT is the deprecated\n    # spelling, kept as a fallback for older Connect versions.\n    on_connect = \"CONNECT\" in (\n        os.getenv(\"POSIT_PRODUCT\"),\n        os.getenv(\"RSTUDIO_PRODUCT\"),\n    )\n    if on_connect:\n        token = session.http_conn.headers.get(\"Posit-Connect-User-Session-Token\")\n        if token is None:\n            raise RuntimeError(\n                \"No Posit-Connect-User-Session-Token header. Attach the \"\n                \"Snowflake integration to this content in Connect.\"\n            )\n        auth = PositAuthenticator(\n            local_authenticator=\"EXTERNALBROWSER\",\n            user_session_token=token,\n        )\n        return {\n            # Connect sets SNOWFLAKE_ACCOUNT from the attached integration.\n            \"account\": os.getenv(\"SNOWFLAKE_ACCOUNT\"),\n            \"authenticator\": auth.authenticator,\n            \"token\": auth.token,\n        }\n\n    if os.getenv(\"SNOWFLAKE_HOME\") is not None:\n        return {\"connection_name\": \"workbench\"}\n\n    raise RuntimeError(\"No Snowflake credentials found.\")\n```\n\nThe same file has to work in two places. In Workbench it uses the managed credentials, exactly as the Quarto document did. On Connect, the viewer's identity arrives as the `Posit-Connect-User-Session-Token` header on their Shiny session, and `PositAuthenticator` exchanges it for a Snowflake OAuth token.\n\nBecause that token is per viewer and arrives on the session, `credentials(session)` is called from inside `server()`, not at the top of the file. Every connection in the app is built from its result, so every query the dashboard runs is attributed to the person looking at it. This is all done to make sure the people looking at the dashboard have the right permissions.\n\n### The Filters Stay Lazy\n\n```python\n@reactive.calc\ndef filtered():\n    low, high = input.loan_amount()\n    data = mortgage_data.filter(\n        mortgage_data.LOAN_AMOUNT \u003E= low,\n        mortgage_data.LOAN_AMOUNT \u003C= high,\n    )\n    if input.loan_type() != \"All\":\n        data = data.filter(mortgage_data.LOAN_TYPE == input.loan_type())\n    if input.state() != \"All\":\n        data = data.filter(mortgage_data.STATE_NAME == input.state())\n    return data\n```\n\n`filtered()` returns an Ibis expression, not a dataframe. No rows have moved. Each output then narrows it further and materializes only what it needs, so we don't have to move the data in and out of the database, instead only fetching what we need.\n\n```python\n@reactive.calc\ndef metrics():\n    return (\n        filtered()\n        .aggregate(\n            n=lambda t: t.count(),\n            avg=lambda t: t.LOAN_AMOUNT.mean(),\n            total=lambda t: t.LOAN_AMOUNT.sum(),\n        )\n        .to_pandas()\n        .iloc[0]\n    )\n```\n\nThat query returns one row regardless of how many applications matched.\n\n### Anything Row-Level Is Bounded\n\nThe histogram is the one output that needs individual rows rather than an aggregate, so it is capped explicitly.\n\n```python\n@reactive.calc\ndef amount_sample():\n    return filtered().select(\"LOAN_AMOUNT\").limit(50_000).to_pandas()\n```\n\nIf we didn't do this, the dashboard would try to fetch the entire table into the app process. This would not only be very time consuming with larger datasets, leading to significant hangs, but could also try to pull in more data than the session has room for.\n\nNote that for this dashboard we have decided to return the first 50,000 rows Snowflake happens to produce. This may or may not be what you want in your application.\n\n### Run It\n\nFrom the terminal:\n\n```bash\nshiny run --reload app.py\n```\n\nOr open `app.py` and click the **Run App** button in the editor toolbar. The dashboard opens in the Viewer pane. The `--reload` flag enables auto-reload, meaning that it will watch for changes in `app.py` and restart the app accordingly.\n\n![The dashboard running in the Positron Viewer pane, with filters, three value boxes, and both plots populated.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/shiny_run_app.png?v=cfc33e69)\n\n### Refine It with Posit Assistant\n\nThe dashboard is deliberately plain. Use Posit Assistant to take it further. It can see `app.py`, and the built-in `shiny-bslib` skill in Posit Assistant loads automatically when it is relevant to your request. Try:\n\n```\nAdd a tab that shows approval rates by state\n```\n\n```\nPopulate the state dropdown from the distinct STATE_NAME values in the table rather than hardcoding five states\n```\n\n```\nImprove the layout and color palette of this dashboard\n```\n\nKeep iterating until you are happy with it.\n\n\u003C!-- ------------------------ --\u003E\n## Publish to Posit Connect\n\nBecause Workbench and Connect run inside the Posit Team Native App, publishing does not involve any network or authentication setup.\n\n### Create an API Key\n\n1. Open Posit Connect from the Posit Team Native App.\n\n![The Posit Team Native App landing page with the Posit Connect tile.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/snowflake_launch_connect.png?v=cfc33e69)\n\n2. Click your account in the upper right, then **Manage Your API Keys**.\n\n![The Connect account menu expanded, showing the Manage Your API Keys item.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/connect_manage_api_keys.png?v=cfc33e69)\n\n3. Click **Add API key**. In the drawer that opens, name the key, select the **Publisher** role, and choose when it expires. Then create it.\n\n![The Add API key drawer in Connect with a name filled in and the Publisher role selected.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/connect_new_api_key.png?v=cfc33e69)\n\n4. Copy the key somewhere safe. Once you close, it is not shown again.\n\n### Deploy in One Click\n\n1. In Positron, click the Posit Publisher icon in the tool menu.\n\n![The Positron activity bar with the Posit Publisher icon highlighted.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/posit_publisher.png?v=cfc33e69)\n\n2. Under **Deployment**, click **Select...** and create a new deployment. Choose `app.py` as the entrypoint.\n\n3. Select the Connect server, or add a new one with the URL `https://connect/`, and paste in your API key.\n\n![The Posit Publisher credential dialog with a Connect server URL and API key field.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/deploy_connect.png?v=cfc33e69)\n\n4. Include these files:\n\n- [x] `app.py`\n- [x] `requirements.txt`\n- [x] `.python-version`\n\n![The Posit Publisher deployment configuration panel listing the files included in the bundle.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/publisher_deployment_config.png?v=cfc33e69)\n\nThe `.python-version` file that selected your session interpreter also travels into the deployment, so confirm it sits alongside `app.py` and reads `3.12`. Publisher reads it when generating the deployment manifest, which records `\u003E=3.12` as an explicit version constraint rather than just noting whichever interpreter you happened to author with. Connect then picks a matching Python installation. It ships in the repository; if you are adapting this pattern in a project of your own, create it with:\n\n```bash\necho \"3.12\" \u003E .python-version\n```\n\n5. Click **Integration requests** \u003E **+** \u003E the available Snowflake integration.\n\n![The Integration Requests section of the Posit Publisher panel with a Snowflake OAuth integration listed.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/publisher_snowflake_integration.png?v=cfc33e69)\n\n6. Click **Deploy your project** and watch the log.\n\n![A Connect deployment log ending in a success message.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/deploy_log_success.png?v=cfc33e69)\n\nSee [Publishing from VS Code or Positron](https://docs.posit.co/connect/user/publishing-positron-vscode/) for more on this step.\n\n### Finish the Setup in Connect\n\nWhen the deployment succeeds, click the link to your content at the end of the deployment log. This opens the app in Connect, where the remaining settings live.\n\nOne step does not travel in the bundle. Open **Content Settings**, go to the **Runtime** tab, and in the **Integrations** section click **Add Integrations** and select the Snowflake integration. Clicking **Integration requests** in Publisher records a *request* in the bundle; associating the integration is a separate action in Connect.\n\n![The Runtime tab of Connect content settings with a Snowflake OAuth integration associated in the Integrations section.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/connect_runtime_integration.png?v=cfc33e69)\n\nIf the dashboard errors on first load, this is almost always why: without the association Connect reports `No OAuth integrations have been associated with this content item`.\n\nAttaching the integration also sets `SNOWFLAKE_ACCOUNT` on the content, which is where the app's connection gets its account identifier. You do not have to add it yourself.\n\nFinally, decide who can open the dashboard. Connect defaults a new deployment to specific users or groups, so only you (and anyone you add) can see it. Still in **Content Settings**, open the **Access** tab and change the setting to **All users - login required**. Anyone with an account on this Connect server can then open the dashboard, and each viewer's queries still run under their own Snowflake identity.\n\n\u003C!-- ------------------------ --\u003E\n## Use and Share the Dashboard\n\n1. In Connect, open the **Content** tab and click your dashboard.\n\n2. Exercise the filters and confirm the metrics and plots update.\n\n![The published Shiny for Python dashboard running on Connect, with filters, value boxes, and plots showing HMDA mortgage data.](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-and-deploy-an-interactive-python-dashboard-with-posit-team-and-cortex/dashboard_published.png?v=cfc33e69)\n\n3. To share it, open the **Content Settings** pane in the upper right, and on the **General** tab copy the URL from the **Content URL** section. Send that to your team.\n\nBecause you attached the Snowflake integration, the dashboard uses viewer-level authentication: each person who opens it connects to Snowflake as themselves. Two colleagues with different grants on `SNOWFLAKE_PUBLIC_DATA_FREE` will see different results from the same dashboard, with no filtering logic in your code. Your Snowflake RBAC policy decides what data each person sees.\n\n\u003E **Note:** Viewers still need an account on Posit Connect to open the dashboard, because the access setting above requires a login. Snowflake RBAC controls which data they see, not whether they can reach the dashboard. Ask your Connect administrator to add the people you want to share with.\n\n\u003C!-- ------------------------ --\u003E\n## Conclusion And Resources\n\nYou connected to Snowflake from Positron Pro in Workbench using managed credentials, queried the data from Python with Ibis without moving it out of the database, explored it with Posit Assistant backed by a Cortex model, built an interactive Shiny for Python dashboard, and published it to Connect where it runs under each viewer's own Snowflake identity.\n\n### What You Learned\n\n- How to connect Positron Pro to Snowflake with Workbench-managed credentials, keeping secrets out of your code\n- How to use Ibis to keep filtering and aggregation in Snowflake instead of in Python\n- How to use Posit Assistant with Snowflake Cortex AI for exploratory analysis and app refinement\n- How to build an interactive Shiny for Python dashboard over a Snowflake table without collecting it\n- How to write one app file that authenticates correctly in both Workbench and Connect\n- How to publish to Connect with viewer-level Snowflake authentication, so RBAC is enforced per viewer\n\n### Related Resources\n\n- Materials for this guide: [snowflake-posit-python-dashboard-cortex](https://github.com/posit-dev/snowflake-posit-python-dashboard-cortex)\n- The R version of this guide: [Build and Deploy an Interactive Shiny Dashboard with the Posit Team Native App and Snowflake Cortex AI](https://www.snowflake.com/en/developers/guides/build-and-deploy-interactive-dashboard-with-posit-team-and-cortex/)\n- [Analyze Data with Python using the Posit Team Native App and Snowflake](https://www.snowflake.com/en/developers/guides/analyze-data-with-python-using-posit-team/)\n- Snowflake Cortex AI: [LLM Functions](https://docs.snowflake.com/en/user-guide/snowflake-cortex/llm-functions)\n- Posit Assistant: [documentation](https://assistant.posit.co/docs/getting-started/) and [Positron overview](https://positron.posit.co/assistant.html)\n- [Ibis](https://ibis-project.org/) and its [Snowflake backend](https://ibis-project.org/backends/snowflake)\n- [Shiny for Python](https://shiny.posit.co/py/)\n- [Posit Workbench user guide](https://docs.posit.co/ide/server-pro/user/) and [Posit Connect user guide](https://docs.posit.co/connect/user/)\n- [Posit Team Native App documentation](https://docs.posit.co/partnerships/snowflake/posit-team/)\n","multiValue":false,":type":"text/x-markdown"},"quickstartArticleLogoImage":{"dataType":"string","title":"Quickstart Article Logo Image","multiValue":false,":type":"text/plain"}},"elementsOrder":["quickstartArticleBody","quickstartArticleLogoImage"],"model":"snowflake-site/models/quickstart-article"},"flexible_column_cont":{"id":"flexible-column-container-9e9a2e92c0","type":"2-column-75-25","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"none","bottomPadding":"none","spaceBetween":"none","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-2fdeca3079",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"quickstart_last_modi":{"id":"quickstart-last-modified-d994b5596b","icon":{"id":"icon","icon":"calendar",":type":"snowflake-site/components/icon","appliedCssClassNames":"snowflake-icon-blue"},"lastModifiedDatePrefix":"Updated","lastModifiedDate":"2026-11-06",":type":"snowflake-site/components/quickstart/quickstart-last-modified","appliedCssClassNames":"snowflake-responsive-component-top-padding-small"},"text":{"id":"text-b1eebf1a73","additionalClasses":"qs-disclaimer-text","text":"\u003Cp\u003E\u003Cspan style=\"color: #666;\"\u003EThis content is provided as is, and is not maintained on an ongoing basis. It may be out of date with current Snowflake 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