ohayo

19.2.0 • Public • Published

Ohayo

Build Status

Ohayo is a fast and free tool for data science. Ohayo consists of a very high level programming language and a visual web studio for that language.

You can try ohayo at https://ohayo.computer, download Ohayo on GitHub, try Ohayo hosted on GitHub, or install it using npm install ohayo.

Slides

Mission

Let's make it faster to do data science. Much faster. So fast that you can do data science as fast as you can speak.

Key Concepts

OhayoLang Ohayo the language is a Tree Language, built using Tree Notation. Ohayo is a dataflow language.

Scripts OhayoLang is a scripting language like any other and you can write programs in it by hand or using the Ohayo Studio. OhayoLang scripts generally have the file extension ".ohayo".

Tiles An Ohayo program is composed of Tiles. Tiles can display UI to the user. Tiles are recursive and can be the parent of other tiles. Tiles are namespaced and all must contain at least one ".".

Tile Properties Tiles can define and use their own Properties. The names of Tile Properties cannot contain a ".".

DataTables All Tiles can access the tables of their ancestor tiles and also pass on a new table to their descendants. The data tables currently use the jTable library.

Common Tile Types All Tiles extend from a base class. The three most common core Tile Types are Provider, Transformer, and Chart. In data science you have 3 main kinds of things: datasets, data transformations, and visualizations. Datasets include everything from weather forecasts to emails to business transactions. There are millions of possible datasets. In Ohayo tiles that provide datasets generally extend the Provider base tile type. Transformations are things like filtering, grouping, and joining. In Ohayo tiles that transform data generally extend the Transformer tile type. Charts include bar charts, line charts, scatterplots and word clouds. In Ohayo charts generally extend the Chart base tile type.

Creating Tiles If you need a new tile—to add a new user friendly data source or visualization type, for example—you can implement it using TypeScript/Javascript/Grammar language. See the packages folder for examples. Documentation for this will come out later in 2020.

BETA!

Ohayo is still beta and iterating frequently. Post feedback here or on the Ohayo subreddit. Ohayo hopefully will be stable by July 2020.

Marketing Jumbo

If you are looking for some marketing-speak, here you go:

  1. The simplest syntax possible. No parentheses, no brackets, no semicolons. Just words you can speak.
  2. Write by hand or program visually. The first visual editor that generates perfectly clean code.
  3. Autocomplete like you've never seen before. AI powered autocomplete that keeps getting better.
  4. Free and open source. The price is $0, and extensions and collaboration are welcome.
  5. No installing required. Run Ohayo instantly in your browser, even on your mobile device.
  6. No tracking, no cookies. Ohayo doesn't track users, use cookies, or store your data.
  7. Secure by design. Your data stays on your machines, we never see it.
  8. Runs anywhere. Run it from our sites, host it yourself, or run it on your local machine.

Other Tools For Data Scientists

Ohayo is just one of my tools that are trying to make data science easier. Here's a list of related products:

Name Website Year WikipediaPage
Grid Studio https://github.com/ricklamers/gridstudio 2019
Observable https://observablehq.com/ 2017
Idyll https://idyll-lang.org/ 2017
Google Data Studio https://datastudio.google.com/overview 2016 https://de.wikipedia.org/wiki/Google_Data_Studio
Tidyverse https://www.tidyverse.org/ 2016 https://en.wikipedia.org/wiki/Tidyverse
Vega Editor https://vega.github.io/editor/ 2015
Amazon QuickSight https://aws.amazon.com/quicksight/ 2015
xsv https://github.com/BurntSushi/xsv 2014
dplyr https://dplyr.tidyverse.org/ 2014
JupyterLab https://github.com/jupyterlab/jupyterlab 2014 https://en.wikipedia.org/wiki/Project_Jupyter
OmniSci https://www.omnisci.com/ 2013 https://en.wikipedia.org/wiki/OmniSci
xlwings https://www.xlwings.org/ 2013
RAWGraphs https://github.com/rawgraphs/raw 2013
DataBricks https://databricks.com/ 2013 https://en.wikipedia.org/wiki/Databricks
Julia https://julialang.org/ 2012 https://en.wikipedia.org/wiki/Julia_(programming_language)
Looker https://looker.com/ 2012 https://en.wikipedia.org/wiki/Looker_(company)
AirTable https://airtable.com/ 2012 https://en.wikipedia.org/wiki/Airtable
Anaconda https://www.anaconda.com/ 2012 https://en.wikipedia.org/wiki/Anaconda_(Python_distribution)
Plotly https://plot.ly/ 2012 https://en.wikipedia.org/wiki/Plotly
RStudio https://www.rstudio.com/ 2011 https://en.wikipedia.org/wiki/RStudio
Microsoft SandDance https://github.com/microsoft/SandDance 2011 https://en.wikipedia.org/wiki/Microsoft_Garage
Microsoft PowerBI https://powerbi.microsoft.com/en-us/ 2011 https://en.wikipedia.org/wiki/Power_BI
d3 https://d3js.org/ 2011 https://en.wikipedia.org/wiki/D3.js
Google Kaggle https://www.kaggle.com/ 2010 https://en.wikipedia.org/wiki/Kaggle
ChartIO https://chartio.com/ 2010
Google BigQuery https://cloud.google.com/bigquery/ 2015 https://en.wikipedia.org/wiki/BigQuery
Wolfram Alpha https://www.wolframalpha.com/ 2009 https://en.wikipedia.org/wiki/Wolfram_Alpha
LucidChart https://www.lucidchart.com/ 2008 https://en.wikipedia.org/wiki/Lucidchart
Pandas https://pandas.pydata.org/ 2008 https://en.wikipedia.org/wiki/Pandas_(software)
Apple Numbers https://www.apple.com/numbers/ 2007 https://en.wikipedia.org/wiki/Numbers_(spreadsheet)
scikit-learn https://scikit-learn.org/stable/ 2007 https://en.wikipedia.org/wiki/Scikit-learn
Smartsheet https://www.smartsheet.com/ 2006 https://en.wikipedia.org/wiki/Smartsheet
Google Sheets https://www.google.com/sheets/about/ 2006 https://en.wikipedia.org/wiki/Google_Sheets
Alteryx https://www.alteryx.com/ 2006 https://en.wikipedia.org/wiki/Alteryx
RapidMiner https://rapidminer.com/ 2006 https://en.wikipedia.org/wiki/RapidMiner
Sisense https://www.sisense.com/ 2004 https://en.wikipedia.org/wiki/Sisense
KNIME https://www.knime.com/ 2004 https://www.knime.com/
Matplotlib https://matplotlib.org/ 2003 https://en.wikipedia.org/wiki/Matplotlib
Tableau https://www.tableau.com/ 2003 https://en.wikipedia.org/wiki/Tableau_Software
Visual-Paradigm Chart Maker https://online.visual-paradigm.com/features/chart-maker/pyramid-chart-maker/ 2002 https://en.wikipedia.org/wiki/Visual_Paradigm
NumPy https://www.numpy.org/ 1995
Qlik https://www.qlik.com/ 1993 https://en.wikipedia.org/wiki/Qlik
JMP https://www.jmp.com/ 1989 https://en.wikipedia.org/wiki/JMP_(statistical_software)
Mathematica http://www.wolfram.com/mathematica/ 1988 https://en.wikipedia.org/wiki/Wolfram_Mathematica
Microsoft Excel https://products.office.com/en-us/excel 1987 https://en.wikipedia.org/wiki/Microsoft_Excel
MATLAB http://mathworks.com/products/matlab 1984 https://en.wikipedia.org/wiki/MATLAB
SAS https://www.sas.com/ 1976 https://en.wikipedia.org/wiki/SAS_language
SPSS https://www.ibm.com/us-en/marketplace/spss-statistics 1968 https://en.wikipedia.org/wiki/SPSS

How to Give Feedback

Open an issue here, post to the Ohayo subreddit, the Tree Notation subreddit or email ohayo@treenotation.org.

Unlicense

This is free and unencumbered software released into the public domain.

Anyone is free to copy, modify, publish, use, compile, sell, or distribute this software, either in source code form or as a compiled binary, for any purpose, commercial or non-commercial, and by any means.

In jurisdictions that recognize copyright laws, the author or authors of this software dedicate any and all copyright interest in the software to the public domain. We make this dedication for the benefit of the public at large and to the detriment of our heirs and successors. We intend this dedication to be an overt act of relinquishment in perpetuity of all present and future rights to this software under copyright law.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

For more information, please refer to http://unlicense.org/

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19.2.0

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