Yesterday the Plotly team announced the release of Plotly.py 4.0 version which is now available for download from PyPI. This version includes some exciting new features and changes, including a switch to “offline” mode by default, the inclusion of Plotly Express as the recommended entry point into the library, and a new rendering framework compatible with not only Jupyter notebooks but other notebook systems such as Colab, Azure and Kaggle notebooks, as well as popular IDEs such as PyCharm, VSCode, Spyder and others.
To upgrade to the latest version, you can run pip install plotly==4.0.0 or conda install -c plotly plotly==4.0.0. More details can be found from the page Getting Started and Migrating to Version 4 guides.
Let us check out the key features in Plotly 4.0
Offline Only
Prior versions of plotly contained functionality for creating figures in both “online” and “offline” modes. In “online” mode, figures were uploaded to an instance of Plotly’s Chart Studio service and then displayed, whereas in “offline” mode figures were rendered locally. This duality was a common source of confusion for several years, and so in version 4 the team made some important changes to help clear this up.
In this version, the only supported mode of operation in the plotly package is “offline” mode, which requires no internet connection, no account, no authentication tokens, and no payment of any kind. Support for “online” mode has been moved into a separately-installed package called chart-studio.
Express First
Earlier this year the team released a standalone library called Plotly Express aimed at making it significantly easier and faster to create plotly figures from tidy data—as easy as a single line of Python. Plotly Express was extremely well-received by the community and starting with version 4, plotly now includes Plotly Express built-in which is accessible as plotly.express.
Displayable anywhere
In addition to “offline” mode, the plotly.offline package has been reimplemented on top of a new extensible renderers framework which enables Plotly figures to be displayed not only in Jupyter notebooks, but just about anywhere, like:
- JupyterLab & classic Jupyter notebook
- Other notebooks like Colab, nteract, Azure & Kaggle
- IDEs and CLIs like VSCode, PyCharm, QtConsole & Spyder
- Other contexts such as sphinx-gallery
- Dash apps (with dash_core_components.Graph())
- Static raster and vector files (with fig.write_image())
- Standalone interactive HTML files (with fig.write_html())
- Embedded into any website (with fig.to_json() and Plotly.js)
In addition to the above new features, there are other changes like a new default theme available in Plotly.py 4.0. The team has introduced a suite of new figure methods for updating figures after they have been constructed. It also supports all subplot and trace types: 2D, 3D, polar, ternary, maps, pie charts, sunbursts, Sankey diagrams etc. Plotly.py 4.0 is also supported by JupyterLab 1.0.
To know about these feature updates in detail, check out the Medium post by the Plotly team.
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