Python made easier with Posit
Tom Mock, Workbench Product Manager at Posit, discusses our commitment to Python from open-source projects to enterprise support. Specifically, Tom discusses Posit Team, the all-in-one solution for your data science team to build, share and maintain your R & Python data products. Posit Team comprises our three professional products, Posit Workbench, Connect, and Package Manager. Posit Workbench give your data scientists access to their favorite development tools in a centralized environment. Enabling them to work in the language they prefer, all while sharing IT resources and collaborating to find actionable insights. Posit Connect is where your team can securely host all of their data products and share them with the push of a button. Schedule reports to update automatically and give users access to only the insights they need. Posit Package Manager allows your team to deliver reproducible data science without the burden of manual package management. Organize and centralize R and Python packages across your team, department, or organization. Posit Team: https://posit.co/products/enterprise/team/ Posit Workbench: https://posit.co/products/enterprise/workbench/ Posit Connect: https://posit.co/products/enterprise/connect/ Posit Package Manager: https://posit.co/products/enterprise/package-manager/
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Transcript#
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My name is Tom Mock. I'm the Workbench product manager here at Posit. I've kind of built my career thinking about the developer experience, so worked in the Quarto team as a product manager thinking about how we integrate R and Python together for notebooks and extending them, and now I'm focusing almost all of my time on the developer experience for Workbench and integrating R and Python there for data scientists and their daily work.
Posit Team overview
Posit team is kind of our crown jewel or a bundle of all of our professional products. So you have three kind of parts to this that all are complementary, but also isolated products. So maybe you only need one or maybe you need all of them, but y'all get to make that choice in terms of flexibility. So Posit Workbench is your workbench where your data scientists, your data analysts, the people who write R, Python, SQL, they get their work done. We provide an authenticated workspace with best-in-class enterprise, single sign-on, and SAML and the things you would expect, but we also provide multiple environments for those data scientists to get their work done.
So of course you have RStudio for people who are maybe doing a mix of R and Python. You can execute code there. We've also got more traditional and kind of expected pure Python environments. So we have access to JupyterLab as well as classic Jupyter notebooks. And then VS Code, which is this very open-ended and flexible integrated development environment, is also available on Workbench. Posit Workbench provides an IDE, VS Code, Jupyter, JupyterLab, RStudio, some place to do that work.
Deploying with Posit Connect
Eventually though, you want to get it off of that environment where you both track how it's performing there, but also how it affect part of your business or integrate with other parts of your company. So as soon as you're ready to get it off of your local environment, you can deploy it to Connect. You can have a command line where you kind of write it up the application and then you deploy it with authentication into Connect, but you can also integrate it into version control or kind of continuous integration and continuous deployment where it goes into something like GitHub or GitLab and then gets pulled automatically into Connect.
Posit Package Manager
The last part of it would be Posit Package Manager. Again, with open source, you have all this flexibility, but with flexibility can sometimes come complexity. Posit Package Manager is really this backbone behind all of our other tooling. Ultimately, to do open source data science, you need open source data science libraries and packages. So Posit Package Manager allows you to host both your own Python packages, so you can create your own wheels, upload them to Posit Package Manager and have them stored there, as well as grab subsets or all of PyPI and kind of the other open source packages that the whole community is working on.
So that really takes away a lot of the headache of having to manage more complex structures. You don't have to use Docker. You don't have to use tools like Conda. You don't have to manage all these system dependencies. You're really focused on purely writing Python code and indicating what are the libraries or packages that provide the functionality I want. So Python at its most simple is part of what Posit team provides for you.
You're really focused on purely writing Python code and indicating what are the libraries or packages that provide the functionality I want. So Python at its most simple is part of what Posit team provides for you.
Open source investment
Posit historically has been known for the RStudio IDE. That's kind of our crown jewel of developer experience for our users. We've done a lot of investments for Python users as well, however, and so we have Quarto, we have Vetiver, we have all these open source tools that really try to make data science seamless for Python users. So part of our investment in open source is that we are both doing it ourselves and integrating with others.
So if you think about Posit the company, about half of our company is engineering and about half of our engineers are working purely on open source. So we're making huge investments in terms of people hours in improving and maintaining professionally supported open source data science packages. Over time you might have shifts in how you're developing your tooling or writing your models and we want to kind of future-proof the platform so that as new framers come out we're adding those in and making sure that they're supported and we're testing against them as well as allowing them to be deployed into things on production.