https://github.com/quansight/ibis-vega-transform
@vega transforms with @ibis-project expressions
https://github.com/quansight/ibis-vega-transform
Last synced: about 1 year ago
JSON representation
@vega transforms with @ibis-project expressions
- Host: GitHub
- URL: https://github.com/quansight/ibis-vega-transform
- Owner: Quansight
- License: apache-2.0
- Created: 2019-05-13T22:01:23.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2021-04-16T16:52:21.000Z (about 5 years ago)
- Last Synced: 2024-11-09T16:49:58.901Z (over 1 year ago)
- Language: Python
- Homepage:
- Size: 15.7 MB
- Stars: 29
- Watchers: 36
- Forks: 7
- Open Issues: 20
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE.txt
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README
# ibis-vega-transform
[](https://mybinder.org/v2/gh/Quansight/ibis-vega-transform/master?urlpath=lab/tree/examples/vega-compiler.ipynb) [](https://github.com/Quansight/ibis-vega-transform/actions?query=workflow%3A%22Run+tests+on+example+notebooks%22) [](https://pypi.python.org/pypi/ibis-vega-transform) [](https://www.npmjs.com/package/ibis-vega-transform) [](https://mybinder.org/v2/gh/Quansight/ibis-vega-transform/master?urlpath=lab)
A JupyterLab extension for performing Vega transforms lazily using Ibis.
Python evaluation of Vega transforms using Ibis expressions.
For inspiration, see https://github.com/jakevdp/altair-transform
This extension is composed of a Python package named `ibis-vega-transform`
for the server extension and a NPM package named `ibis-vega-transform`
for the frontend extension.
## Requirements
- JupyterLab >= 3.0
## Getting started
```sh
pip install ibis-vega-transform
```
Then in a notebook, import the Python package and pass in an ibis expression
to a Altair chart:
```python
import altair as alt
import ibis_vega_transform
import ibis
import pandas as pd
source = pd.DataFrame({
'a': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I'],
'b': [28, 55, 43, 91, 81, 53, 19, 87, 52]
})
# or ibis.pandas if ibis version < 1.4
connection = ibis.backends.pandas.connect({'source': source })
table = connection.table('source')
alt.Chart(table).mark_bar().encode(
x='a',
y='b'
)
```
Check out the notebooks in the [`./examples/`](./examples/) directory to see
some options using interactive charts and the OmniSci backend.
## Usage
Importing `ibis_vega_transform` sets the `altair` renderer and data transformer to `"ibis"`. It also monkeypatches the Ibis chart constructor to handle `ibis` expressions.
Now, whenever you pass an `ibis` expression to a chart constructor, it will use the custom ibis renderer, which pushes all data aggregates to ibis, instead of in the browser.
You can also set a debug flag, to have it instead pull in the first N rows of the ibis expression and use the default renderer. This is useful to see how the default pipeline would have rendered your chart. If you are getting some error, I reccomend setting this first to see if the error was on the Altair side or on the `ibis-vega-transform` side. If the fallback chart rendered correctly, it means the error is in this codebase. If it's wrong, then the error is in your code or in altair or in Vega.
```python
# enable fallback mode
ibis_vega_transform.set_fallback(True)
# disable fallback mode (the default)
ibis_vega_transform.set_fallback(False)
```
### Tracing
If you want to see traces of the interactions for debugging and performance analysis,
install the `jaeger-all-in-one` binary and the `jupyterlab-server-proxy`
lab extension to see the Jaeger icon in the launcher.
```bash
conda install jaeger -c conda-forge
jupyter labextension install jupyterlab-server-proxy-saulshanabrook
```
The Jaeger server won't actually be started until a HTTP request is sent to it,
so before you run your visualization, click the "Jaeger" icon in the JupyterLab launcher or go to
`/jaeger` to open the UI. Then run your visualization and you should see the traces appear in Jaeger.
You also will likely have to increase the max UDP packet size on your OS to [accomdate for the large logs](https://github.com/jaegertracing/jaeger-client-node/issues/124#issuecomment-324222456):
### Mac
```sh
# Edit now
sudo sysctl net.inet.udp.maxdgram=200000
# Edit on restart
echo net.inet.udp.maxdgram=200000 | sudo tee -a /etc/sysctl.conf
```
## Troubleshoot
If you are seeing the frontend extension, but it is not working, check
that the server extension is enabled:
```bash
jupyter server extension list
```
If the server extension is installed and enabled, but you are not seeing
the frontend extension, check the frontend extension is installed:
```bash
jupyter labextension list
```
## Contributing
### Development install
Note: You will need NodeJS to build the extension package.
The `jlpm` command is JupyterLab's pinned version of
[yarn](https://yarnpkg.com/) that is installed with JupyterLab. You may use
`yarn` or `npm` in lieu of `jlpm` below.
```bash
# Clone the repo to your local environment
git clone git@github.com:Quansight/ibis-vega-transform.git
# Change directory to the ibis-vega-transform directory and
# Create a conda environment
cd ibis-vega-transform
conda env create -f binder/environment.yml
conda activate ibis-vega-transform
# Install package in development mode
pip install -e .
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Rebuild extension Typescript source after making changes
jlpm run build
```
You can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.
```bash
# Watch the source directory in one terminal, automatically rebuilding when needed
jlpm run watch
# Run JupyterLab in another terminal
jupyter lab
```
With the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).
By default, the `jlpm run build` command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:
```bash
jupyter lab build --minimize=False
```
A pre-commit hook is installed usig Husky (Git > 2.13 is required!) to format files.
Run the formatting tools at any time using:
```sh
black ibis_vega_transform
jlpm run prettier
```
### Tracing
We are using [`jupyter-jaeger`](https://github.com/Quansight/jupyter-jaeger) to trace each interaction
for benchmarking.
### Uninstall
```bash
pip uninstall ibis-vega-transform
```