Metadata-Version: 2.1
Name: ibis-vega-transform
Version: 5.2.2
Summary: Evaluate Vega transforms using Ibis expressions
Home-page: https://github.com/Quansight/ibis-vega-transform
Author: Ian Rose and Saul Shanabrook
Author-email: ian.rose@quansight.com
License: Apache-2.0 license
Description: # ibis-vega-transform <br /> [![binder logo](https://beta.mybinder.org/badge.svg)](https://mybinder.org/v2/gh/Quansight/ibis-vega-transform/master?urlpath=lab/tree/examples/vega-compiler.ipynb) [![Tests](https://github.com/Quansight/ibis-vega-transform/workflows/Run%20tests%20on%20example%20notebooks/badge.svg)](https://github.com/Quansight/ibis-vega-transform/actions?query=workflow%3A%22Run+tests+on+example+notebooks%22) [![](https://img.shields.io/pypi/v/ibis-vega-transform.svg?style=flat-square)](https://pypi.python.org/pypi/ibis-vega-transform) [![](https://img.shields.io/npm/v/ibis-vega-transform.svg?style=flat-square)](https://www.npmjs.com/package/ibis-vega-transform)
        
        Python evaluation of Vega transforms using Ibis expressions.
        
        For inspiration, see https://github.com/jakevdp/altair-transform
        
        ## Getting started
        
        ```sh
        pip install ibis-vega-transform
        jupyter labextension 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 interactiosn 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
        ```
        
        ## Development
        
        To install from source, run the following in a terminal:
        
        ```sh
        git clone git@github.com:Quansight/ibis-vega-transform.git
        
        cd ibis-vega-transform
        conda env create -f binder/environment.yml
        conda activate ibis-vega-transform
        
        pip install -e ".[dev]"
        jlpm
        jupyter labextension install . --no-build
        
        jupyter lab --watch
        jlpm run watch
        ```
        
        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.
        
Platform: UNKNOWN
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: dev
