Welcome to Python Cheatsheet!¶ Welcome to pysheeet. This project aims at collecting useful Python snippets in order to enhance pythoneers’ coding experiences. Please feel free to contribute if you have any awesome ideas for improvements to code snippets, explanations, etc. Any snippets are welcome. The python cheat sheet is a one-page reference sheet for the Python 3 programming language. Press J to jump to the feed. Press question mark to learn the rest of the keyboard shortcuts.
You can use Python with RStudio professional products to develop and publish interactive applications with Shiny, Dash, Streamlit, or Bokeh; reports with R Markdown or Jupyter Notebooks; and REST APIs with Plumber or Flask.
For an overview of how RStudio helps support Data Science teams using R & Python together, see R & Python: A Love Story.
For more information on administrator workflows for configuring RStudio with Python and Jupyter, refer to the resources on configuring Python with RStudio.
Developing with Python#
Data scientists and analysts can:
- Work with the RStudio IDE, Jupyter Notebook, JupyterLab, or VS Code editors from RStudio Server Pro
Want to learn more about RStudio Server Pro and Python?#
For more information on integrating RStudio Server Pro with Python, refer to the resources on configuring Python with RStudio.
Publishing Python Content#
Data scientists and analysts can publish Python content to RStudio Connect by:
- Publishing Jupyter Notebooks that can be scheduled and emailed as reports
- Publishing Flask applications and APIs
- Publishing Dash applications
- Publishing Streamlit applications
- Publishing Bokeh applications
Ready to publish Jupyter Notebooks to RStudio Connect?#
View the user documentation for publishing Jupyter Notebooks to RStudio Connect
Ready to share interactive Python content on RStudio Connect?#
Learn more about publishing dash or flask applications and APIs.
Beginners Python Cheat Sheet Pdf
View example code as well as samples in the user guide.
Publishing Python and R Content#
Data scientists and analysts can publish mixed Python and R content to RStudio Connect by publishing:
- Shiny applications that call Python scripts
- R Markdown reports that call Python scripts
- Plumber APIs that call Python scripts
Mixed content relies on the reticulate package, which you can read more about on the project's website.
View the user documentation for publishing content that uses Python and R to RStudio Connect
Cheat sheet for using Python with R and reticulate
R To Python Cheat Sheet Example
Managing Python Packages#
Python Cheat Code
RStudio Package Manager supports both R and Python packages. Visit this guide to learn more about how you can securely mirror PyPI.
Additional Resources#
Want to learn more about RStudio Connect and Python?#
Frequently asked questions for using Python with RStudio Connect
Learn about best practices for using Python with RStudio Connect
Want to see examples of using Python with RStudio?#
View code examples on GitHub of Using Python with RStudio
View examples of Flask APIs published to RStudio Connect