Changelog

AI Copilot & HIPAA compliance

AI code completion in closed Beta

We're thrilled to announce that intelligent code assistance is soon coming to Deepnote! With AI code completion (currently in closed Beta), you'll enjoy lightning-fast suggestions that consider the entire notebook as context, including text, code, and markdown.

Say goodbye to manual searches and time-consuming boilerplate code – our AI companion effortlessly anticipates your next steps. This is especially valuable for exploratory data analysis, empowering you to focus on gaining insights rather than getting caught up in syntax details.

Limited seats are available for interested individuals to join our closed beta. Claim your spot by clicking on the link below. Priority will be given to our Team and Enterprise plan customers.

Join waitlist

Code completion is just the first step in our journey to transform data work in notebooks via the power of AI. We have many more exciting features planned, all aimed at enhancing your productivity. Keep an eye out for updates as we continue to unveil these exciting developments!

Announcing our HIPAA compliance

We are pleased to announce that Deepnote is now HIPAA compliant, which means that companies can securely process PHI on our platform while adhering to the US federal law that sets national standards for protecting medical records and personal health information.

If you would like to learn more about HIPAA and how to sign a BAA, please reach out to our sales team at sales@deepnote.com.

Push notebooks to GitHub & import Python packages or files from a GitHub repository

Push notebooks to GitHub

We are bringing some more software engineering best practices to Deepnote. Export your work directly to GitHub with a new feature that allows you to commit & push your work to a specified path in a GitHub repository.

Enable this in your project setting’s versions tab by connecting your public or private GitHub repository and a path within the repository. Deepnote allows you to specify a commit message & pushes all notebooks as .ipynb files.⁠

Read more ->

Import Python packages and files from GitHub

We are not stopping with a single GitHub feature. The next update is about importing Python packages, modules or other files from GitHub. You can now easily import a repository (or several if you’d like!) to your project via the Files section. All you need to do is specify the repository & we will set you all up!

If you need to pull fresh updates of your repo, right-click the imported folder in the Files section and hit Refresh.

Read more ->

Table info in schema browser, automated connection testing, SSH tunnel integration & schema browser for Dremio

Table info in schema browser

It’s officially even easier to find the dataset you’re after. Now you can view key information about any table directly from Deepnote’s schema browser.

If you’re a Snowflake, BigQuery, Amazon Redshift, or PostgreSQL user, you can simply click on a table in the schema browser and switch to the Table info tab to see metadata sourced directly from your data warehouse or database. This includes description (if present), date of last change, date of creation, and table size.

No more leaving the comfort of your notebook to make sure you’re working with the right data.

Read more on our schema browser here →

Automated connection testing

Deepnote is making it easier to get your integrations up and running correctly. Next time you create or edit a data warehouse or database integration, we’ll automatically test the connection for you.

Accidentally set up an integration with the wrong credentials? No need to ask an admin for a fix. We’ll make sure all integrations are set up and working as intended. If there are any connection problems, we’ll highlight the issues.

SSH tunnel integration

Need to connect to a resource in a private network? We’ve got you covered. Our new SSH tunnel integration makes it easy to securely connect to all the tools in your stack.

Simply create an SSH tunnel integration from the Integrations section in the right-hand sidebar and connect it to your project. Deepnote will generate a key pair for your workspace and provide a public key for you to add to your server.

Your SSH tunnel will start up in the background and display the host and port you can use to access your data. Easily connect to any service behind a firewall, from experiment tracking tools and feature stores to databases without native integrations.

Read more on our SSH tunnel integration here →

Schema browser for Dremio

Deepnote’s powerful new schema browser is now available to Dremio users. Explore the structure of your Dremio data — lightning-fast and directly from your notebook.

Simply click the View schema button on a Deepnote SQL block or click on your connected integration in the Integrations section in the right-hand sidebar. Enjoy full visibility into every table and column, as well as intelligent autocomplete to help you write your SQL queries even faster.

Read more on our Dremio integration here →

OAuth for Snowflake & BigQuery, schema browser for Athena & ClickHouse, upgraded SQL autocomplete & Dremio integration

OAuth for Snowflake & BigQuery

Snowflake and Google BigQuery users now have more ways to keep their data secure. Using OAuth, you can give every member of your Deepnote workspace their own set of credentials.

Enable multi-factor authentication, get granular with access controls for specific resources, and improve your ability to audit data access — all while allowing team members to run queries from Deepnote using their individual Snowflake or BigQuery accounts.

Read more on our Snowflake integration here →

Read more on our BigQuery integration here →

Schema browser for Athena & ClickHouse

Deepnote’s powerful new schema browser is officially available to Amazon Athena and ClickHouse users. Now you can explore the structure of your Athena or ClickHouse data directly from your notebook.

Simply click the View schema button on a Deepnote SQL block or click on your connected integration in the Integrations section in the right-hand sidebar. Blazing-fast speed, SQL query autocomplete, and full visibility into every table and column — all at your fingertips.

Read more on our schema browser here →

Upgraded SQL autocomplete

Our new and improved autocomplete now provides more relevant suggestions at every stage of the query writing process. You can compose your SQL queries faster than ever before.

Simply start typing after your SELECT statements to receive matching column names or press Tab to see all column names within your schema. If you already selected or joined tables in your query, column suggestions will be limited to only the relevant ones.

Plus, schema object suggestions are now more tightly scoped — you can build fully qualified table names by adding to each hierarchical level. Type after your FROM statement to see suggestions, first for matching databases and datasets, then for schemas, and finally for tables.

Dremio integration

We’re excited to announce our integration with Dremio! Now you can enjoy Dremio’s lightning-fast querying speed using Deepnote’s SQL blocks.

Our new integration lets you query your Dremio lakehouse, extract relevant insights, and start analyzing and modeling data from the comfort of your notebook. Create your integration, connect it to your notebook, and start querying in just a few clicks.

Need to switch between Dremio and another distributed SQL engine? No SQL statement rewriting is necessary. Just switch your SQL block’s assigned integration.

Read more on our Dremio integration here →

Brand-new schema browser, Trino integration & flexible integration creation

🔍 New & improved schema browser

We’re excited to share Deepnote’s powerful new schema browsing experience! Explore the structure of your data and write SQL faster than ever before.

⁠Here are the highlights of what’s new:

• It's blazing fast! Quickly navigate your schema across thousands of tables and receive results almost instantly.
• There’s no need to start from scratch. See matching table/column suggestions as you type to autocomplete SQL queries.
• You get visibility into everything. Search for tables and columns across your whole data source.
• It’s easier to speed up your SQL workflows. Apply handy shortcut actions to preview a table, copy table/column names with a click, and more.

Our new schema browser is currently available for Snowflake, Google BigQuery, Amazon Redshift, PostgreSQL, Microsoft SQL Server, and MySQL. Keep an eye out for more integrations coming soon!

Read more on our schema browser here →

🔌 Trino integration

We’re happy to announce our integration with Trino. Now you can use Deepnote’s SQL blocks to query Trino instances at lightning speed.

Our new Trino integration allows you to query, extract, analyze, and model data in your Trino instance from the comfort of your notebook. And if you need to switch between Trino and other distributed SQL engines, there’s no need to rewrite your SQL statements — simply switch the SQL block’s assigned integration.

Read more on our Trino integration here →

📓 Add integrations directly from your notebook

Need to create a new data source connection? Now you can do it directly from your notebook instead of navigating to a separate page.

Just open the Project tab in the right-hand sidebar and click the plus (+) button in the Integrations section. No workflow disruptions necessary.

Read more on integrations here →

Redshift schema browser, SSH & SSL connections & integration updates

🔍 Redshift schema browser

Now you can find the Amazon Redshift data you need from the comfort of your notebook.

Next time you want to explore your Redshift schema tree, simply click on the connected Redshift integration in the right sidebar.

You can also access the schema right from an SQL block by clicking on the View schema button. Discovering your data’s never been easier.

And stay tuned for a brand new schema browsing experience for Redshift and other data sources coming to a product update near you!

Read more on our Amazon Redshift integration here →

🔒 SSH & SSL database connections

You now have more options for securely connecting to databases on private networks.

In the past you had the option of authorizing Deepnote’s IP addresses. Now you also have the option of specifying an SSH connection in the Integrations menu. We’ll automatically generate a public SSH key that can be added to your SSH bastion.

Meanwhile, if the database supports it, any queries executed from an SQL block will automatically connect to your database via an SSH tunnel.

We’ve also added new options for enforcing SSL encryption and verifying server certificates to help you keep your data secure.

Read more on securing connections here →

🔌 Integrations added to the right sidebar

Reviewing and updating workspace integrations just got easier.

Instead of living in a separate tab, project integrations are now displayed in the main project tab of your notebook.

No more clicking away to find out which integrations are connected or need to be added.

Read more on integrations here →

Updated SSO, upgraded audit logs, new billing controls & much more

🔒 SSO updates & directory sync

It’s easier than ever to control which team members or groups can log into Deepnote using the identity provider of your choice.

If you’re on the Enterprise plan, you can now use single sign-on via SAML or OIDC connection, including Google, Okta, Azure AD, OneLogin, and more.

You can also sync users from your directory provider — such as Okta or Active Directory — into Deepnote via SCIM. This makes it a breeze for companies with larger teams to manage users.

Read more on SSO & directory sync here →

🔍 Audit log metadata & exports

Get more out of your data warehouse audit logs with Deepnote. Queries from Deepnote’s SQL blocks now include helpful metadata, such as who ran a query and in which project, so you can keep tabs on those overly expensive queries.

And if you’re an admin on the Enterprise plan, we’ve made it even easier to investigate activity for security incidents. Admins can now export an audit log as a CSV from the General settings menu.

Read more on audit logs here →

💰 Billing alerts & limits

Stay on top of your machine costs without breaking a sweat.

You can now send billing alerts to all admins for a workspace. Simply set up a monthly dollar limit for pay-as-you-go machines in the Billing & usage menu and all admins will be notified via email when it’s reached.

Looking for other ways to keep costs predictable? Admins can now also disable pay-as-you-go machines for a workspace, shutting off this option for users (this will move any running projects to a Basic machine at the next start).

Read more on billing alerts & limits here →

🎨 New color scales for charts

Dress up your charts in truly eye-catching colors!

When you’re selecting colors for a quantitative or temporal column in charts, you now have a much wider range of choices, including single-hue, multi-hue, and divergent color scale options.

🔢 Customize axis number format in charts

Want to change the displayed number format of your chart’s quantitative axis? Now you can just point and click — no code necessary.

Simply go to the Format tab and choose your preferred option from the Number dropdown menu. If you want to get even more granular, you can also customize the number of decimals you wish to show.

Chart recommendations, flexible chart filtering & Microsoft sign-in (plus SSO support)

🤖 Smart chart recommendations

Get ready to accelerate your data visualizations with chart recommendations.

Next time you create a chart block, you’ll have the option to click on the Explore button, which will bring up a gallery of recommended charts based on your DataFrame.

The gallery includes the most commonly used chart types for data summarization. Simply select an option to use it as your own (Replace chart) or create a new chart based on it (Add new chart).

No more starting from scratch each time you need to build a chart. Quickly browse a wide range of data summaries, pick your starting point, and customize from there.

🖱 Interval selection on charts

Chart filtering just got a lot more flexible.

You can now select a range of data points directly with your mouse when you want to apply a filter to your chart.

Click and drag over an area on the chart to highlight your data. Then hit the Filter button to include or exclude the selected data or inspect it in a new DataFrame.

Zooming in on outlier data points is now easier — and more precise — than ever.

Read more on interactive filtering here →

🔐 Microsoft sign-in & enforcing SSO

You can now sign up and log in to Deepnote using your Microsoft 365 account.

And if you’re an admin on the Enterprise plan, you can enforce specific single sign-on methods — including Microsoft, Google, Okta, and more — for all members of a workspace.

Authenticate users and keep workspaces secure with ease.

Read more on SSO here →

Chart updates: export to DataFrame & value labels

📊 Export chart to DataFrame

Want to explore the data behind a specific part of your chart? Now you can create a new DataFrame from filtered data when you apply a filter on a chart block.

Close the analytical loop without having to manually write any code — simply click the DF button and a new code block will be added below your chart.

🔢 Value labels on charts

It’s easier than ever to improve the readability of your charts (always handy when you’re sharing your results with others). When you create a bar, line, or area chart, you now have the option to turn on Value labels in the Format tab.

Just use the toggle to display the numerical values of individual data points. And voilà — your charts are that much easier to read.

Interactive chart filtering

📊 Chart blocks now support interactive filtering

No need to interrupt your workflow by writing SQL or Python for a simple chart filter — just click on the items you'd like to focus on within your chart and press the Filter button to include or exclude the selected series. You can even combine multiple filtering steps to drill down the data as much as you need.

More chart color options, flexible dates for charts & CSVs in notebooks

🌈 More color options for charts

Add more color (and context) to your charts with a wider range of color palettes. When you select a categorical column in the Color option, you can now choose between multiple color palettes.

If you want to apply a single color to the whole chart, simply select it (or add a custom color of your own).

🗓 Flexible date units for charts

It just got much easier to adjust the granularity of time series analysis on the fly. When you add a temporal column to an axis, you can now change the displayed time unit.

Pick from multiple time intervals/formats in the dropdown menu and the temporal axis will be grouped by the selected unit. No more having to reshape your dataset with code!

🗂️ Drop a CSV into a notebook

Easier workflow alert! You can now drag and drop a CSV into a notebook(either from your computer or from your project files in the right sidebar) and query away.

Add-ons to charts: exporting into code & adding secondary measures

🐍 Export charts into code

If you need even more flexibility to customize your charts, you can now duplicate your chart block into code by selecting the option in the block actions menu.

This adds a new Python code block to your notebook, containing the configuration of your chart in the Vega-litespecification format. Vega-lite is very powerful and fairly easy to learn, so it’s a great option if you need to create a finely customized or super-advanced visualization.

📐 Secondary measures on charts

You can now add secondary measures to charts with one click.

When you create a chart with a categorical and measure (quantitative) column on the X and Y axes, we now display a plus (+) button next to the selected measure. Click on it, pick your secondary measure, and we'll create a new chart layer with all settings pre-configured for you, including the legends. It’s as easy as it sounds!

If your secondary measure happens to be on a different scale, you can also switch to dual axis mode under the Display tab. This will visualize the two measure axes independently.

👋 Share private projects by name

To simplify sharing private projects with other workspace members, we’ve updated our project-sharing options to accept names in addition to emails.

More on project sharing options in our docs →

Data visualization for everyone: Introducing the new chart block

We've overhauled chart blocks in Deepnote to bring you a more intuitive and flexible no-code data visualization experience. Chart blocks are rolled out to everyone using Deepnote as of November 16, 2022!

Here are some highlights of what’s new:

• More chart types, including compound charts with multiple layers
• Essential formatting options to customize your chart axis and canvas with a few clicks
• Simplified workflow for building your exploratory graphs even faster
• Many quality-of-life improvements, including chart resizing and an option to hide the configuration details

And don't forget to check out these additional resources:

• You can learn more about new chart block capabilities in our docs →
• For practical examples of how to use the chart block for data exploration without writing a single line of code, check out our showcase notebook →
• If you’d like to take a peek into our product kitchen, we also wrote a blog post about our thought process and design approach for this major upgrade — read it here →

Bulk domain invites, favorites & new integrations with Snowflake & Keboola

✅ Invite anyone with your email domain as a viewer

We’ve introduced an easier way to share notebooks with anyone at your company: domain invites.

Admins can turn this setting on to enable anyone with a matching email domain (e.g., @yourcompany.com) to join your workspace as a Viewer. And because Viewer seats don’t count toward plan limits, you can add as many team members as you’d like for free.

💙 Favorite projects for fast access

We’ve added the option to favorite Deepnote projects for faster access. When viewing a notebook or project, simply click the star ⭐ icon (located in the top right navigation bar) and we’ll pin it to a favorites section in your workspace.

❄️ Exploratory data analysis with Snowflake & Deepnote

We shipped a Snowflake quick-start guide for building an accelerated exploratory data analysis (EDA) workflow with Snowflake and Deepnote. Specifically, the guide covers methods for effectively cleaning and visualizing weather readings, which can be applied more generally to any dataset used within Deepnote.

Check it out →

🐙 Trigger notebooks to run with Keboola & the Deepnote API

Our friends at Keboola released a new component that enables you to trigger the run of a specified notebook in Deepnote using the Deepnote API.

Read the docs →

dbt Semantic Layer

🔌 dbt Semantic Layer is now an official Deepnote integration!

With the dbt Semantic Layer and Deepnote, you can import metrics defined in dbt directly into your Deepnote notebook and give your data team a consistent, reliable way of defining and consuming metrics.

Combining Deepnote and dbt unlocks use cases that include: speeding up ad-hoc reporting, mixing historical and predictive analytics, dashboard prototyping, and much more.

Here are some resources for using dbt and Deepnote:

• Blog post →
• Demo notebook →
• Documentation →
• Walkthrough video →

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A faster way to query SQL integrations & add blocks

⚡New block buttons for faster querying

We’ve simplified the way to add blocks to your notebook: Each block type (code, text, SQL, etc.) now has its own dedicated button to save you a few clicks. Even better, clicking the SQL button now lists all available data source integrations set up for your workspace (and those not yet connected to your project).

Simply select an integration from the SQL dropdown and your linked SQL block will be added. In case you can’t find the integration you need, you can also click on the set up a new integration button to quickly navigate to the Integrations page (only available for workspace admins).

🤝 Block presence is back

We’ve brought back a real-time collaboration feature: block presence. You'll now see the profile photo of a team member when they are active within a block in your shared notebook.

Remember that only one user will be able to edit a code block at a time.

📓 Featured notebook

• Time wasted waiting for websites to load: Check out this deep dive into how loading times have changed (or not changed) from 2016 to today.

Public API, full-width mode & featured notebooks

🤖 Introducing a public API to run notebooks programmatically

Introducing our first public API endpoint for executing notebooks! You can now programmatically trigger notebooks to run from external applications.

This opens up a host of automation opportunities, from customized scheduling to integrating notebooks deeper into existing workflows together with other applications.

Read the docs for more on this release →

Releasing a public API is just our first step toward building a rich API ecosystem around data notebooks. We'd love to hear what endpoints and capabilities you'd like to see — head to our Product Portal and share what you'd like us to build next.

🧱 Change text block types

We’ve added the option to easily change text blocks to a different type (e.g., turn a paragraph into a callout).

Simply click the hamburger (Block action) menu and select the block type you’d like to convert to.

More on this update (and all of our recent rich text improvements) in our docs →

↔️ Full-width mode for notebooks

By popular demand, we’ve added full-width mode to notebooks so you can take full advantage of those large displays. Just toggle to full-width mode in the right-hand settings of Deepnote and your notebook will automatically expand to the width of available space.

Pro tip: Full-width mode is particularly handy when working with long lines of queries and wide outputs — no more long scrolling!

📓 Featured notebooks

• The Whopper Index 🍔: Robert Ritz uses a dataset of Burger King’s Whopper prices and exchange rates across 49 countries to uncover purchasing power parity around the globe.

• Probabilistic sales forecasting 🔮: Here's part one (the exploratory programming part) of a two-part series that uses discrete distribution models to forecast consumer behavior and purchasing patterns.

To-do lists, callouts & faster notebook performance

✨ Fancy rich text editing: to-do lists & callouts!

With our latest upgrade to rich text editing, you can now create task lists in your notebooks. Select to-do list from the add block (+) menu and start listing items relevant to your work.

The check marks are collaborative, so you can keep track of outstanding tasks together with your team members.

We’ve also added callout blocks to bring even more style to your storytelling. Create a callout from the add block (+) menu and select one of four colors to highlight important blocks of text in your notebook.

📓 A better, faster notebook experience

We’re changing how notebooks are stored by moving them out of the Files section and into a dedicated Notebooks section in your right sidebar. This change will unlock a handful of upcoming features for versioning, collaboration, and editing (stay tuned) and will make your notebook loading times about 90% faster by our estimates!

While this update introduces many improvements, it also impacts how command-line tools (such as Git) interact with Deepnote notebooks.

Read more about this migration in our documentation →

📓 Featured notebooks from the community

• What songs were popular when I was in high school?: See why algorithmic recommendations leave much to be desired. Robert Ritz shares his trials and tribulations in building a personalized and nostalgic playlist using a bit of data and APIs.

• Analyzing and predicting employee attrition in healthcare data: Sadrach Pierre shares his experience in exploratory data analysis and building a classification model that predicts attrition outcomes in the healthcare industry.

• Predicting price elasticity of demand with Python: Asish Biswas uses logistic regression to understand how the price of a product influences a purchase decision and whether or not price elasticity exists.

Restore notebook variables & an easier way to add links

🔁 Restore variables from your previous session

Jump straight back into your work from where you left off without losing context. When you return to your notebook after your machine went offline (e.g., after a period of inactivity), you now have the option to restore your variables.

Just click on the Restore variables link displayed in the status bar on the top and all variables will be restored from your previous session.

Learn more about this feature →

🔗 More rich text additions: links!

We’ve added hyperlinks to our formatting palette. Highlight any piece of text and include a URL by clicking on the link icon.

Shortcuts for copy-pasting links are also supported (Cmd+V) for maximum efficiency.

📓 Featured notebooks

• Dealing with imperfect experimental designs: Learn how to deal with imperfect real-life data. Quentin Gallea shares his experience on Towards Data Science.
• QR code image generator: Make QR codes more visually stimulating by adding image backgrounds.
• Scraping images with Python and Selenium: Create a script that will scrape a Google webpage, extract images, and create datasets using Python and Selenium.

More rich text features (lists!) & SQL Server support

↔️ SQL Server integration (Azure SQL & Synapse SQL, too!)

We’ve added a built-in integration for Microsoft SQL Server, allowing data teams to query Microsoft SQL Server instances (as well as Azure SQL & Synapse SQL) from the comfort of a notebook environment.

With the SQL Server integration, you can query and browse the schema of your databases from within Deepnote. In addition, Deepnote’s SQL blocks supercharge your analytics workflows through features like auto-complete or saving query results to pandas DataFrames.

✍️ Rich text editor upgrade: numbered & bulleted lists

Our rich text editor got a small (but mighty) upgrade: numbered and bulleted lists. You can create formatted lists from the add block (+) menu, as well as by typing - or a number sequence 1. and space at the beginning of a block.

📓 Featured notebooks

• Snowpark for Python: Bring Python to your warehouse with Deepnote.
• Interactive visualizations to level up your statistical knowledge: Check out this interactive stats playground featured in our talk at SciPy 2022 — "The Myth of the Normal Curve and What to Do About It."
• The magic of Matplotlib stylesheets: Use this notebook to level up your data visualizations with Matplotlib and Deepnote.
• Python built-ins for beginners: Here's a handy list of built-in Python functions to simplify and improve your code from Katy Hagerty.

Rich text editing and fast integration connectivity

✍️ Rich text editor

Our new powered-up paragraph and heading blocks now support rich text editing. Simply highlight a piece of text and apply various styling options right from the formatting toolbar. You can also format text via keyboard shortcuts for even more efficiency.

Creating a compelling textual narrative in your notebooks is now simpler than ever — with no Markdown needed!

We’re making text editing a first-class citizen in notebooks and rich text editing. We'll soon be adding support for bulleted lists, numbered lists, links, and more.

⚡Faster integration connectivity

We’ve decreased the time it takes to connect to integrations by 90% — no more hardware restarts. Simply click to connect an integration and we’ll handle the rest.

❄️ Snowflake Select Technology Partner

We’re thrilled to share that Deepnote is officially a Snowflake Select Technology Partner, giving you even more support, resources, and flexibility when using Snowflake and Deepnote together.

📓 Featured notebooks from the community

• Product metrics: Objectiv (objectiv.io) recently announced support for Deepnote along with a sample notebook that includes how to run and visualize core product metrics (retention, acquisiton, etc.) in Deepnote.

• Detecting edible mushrooms: Shaked Zychlinski created a notebook that identifies characteristics of edible mushrooms if you’re ever alone in the woods with your laptop.

• Customer segmentation with Python: Avi Chawla built a notebook that explores the sentiment of conversational data using the AssemblyAI API and Python. Check out the notebook here or read the full walk-through on Towards Data Science.

ClickHouse integration

↔️ ClickHouse integration

We are expanding our list of data sources. The ClickHouse integration allows data teams to efficiently query very large datasets, extract relevant data, and start analyzing and modeling in the comfort of their own notebook environment.

With the ClickHouse integration, you can leverage the performance and scalability that comes with ClickHouse's open-source column-oriented DBMS right from within Deepnote. ClickHouse allows users to handle thousands of sub-second queries per second on petabyte-scale datasets.

🐛 Smaller things and bug fixes

• We added support for Python 3.10. Version 3.9 is now the default for all new projects.
• We added support for TensorFlow 2.9.1 and R 4.2.0. You can switch your project to this version in the environment section.