HackerReposA FIELD GUIDE TO OPEN SOURCE
ProSponsor the shelf♧ 0
← Back to top all-time
asavinov
bistro
Java2017–2019
asavinov / bistro

bistro

A general-purpose data analysis engine radically changing the way batch and stream data is processed

2Distinct people
15Mentions
0Explicit recommenders
8GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

A general-purpose data analysis engine radically changing the way batch and stream data is processed

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 7:24:48 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month15 dated mentions

Observed mentions: 2017-12-31 18:05:32 UTC to 2019-01-30 10:33:01 UTC.

01232017-12-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsDec 20172018-01-01 00:00:00 UTC to 2018-02-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2018-02-01 00:00:00 UTC to 2018-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-03-01 00:00:00 UTC to 2018-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-04-01 00:00:00 UTC to 2018-05-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2018-05-01 00:00:00 UTC to 2018-06-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2018-06-01 00:00:00 UTC to 2018-07-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 commentsJun 20182018-07-01 00:00:00 UTC to 2018-08-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2018-08-01 00:00:00 UTC to 2018-09-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2018-09-01 00:00:00 UTC to 2018-10-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2018-10-01 00:00:00 UTC to 2018-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-11-01 00:00:00 UTC to 2018-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-12-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019-01-01 00:00:00 UTC to 2019-02-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJan 2019

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Dec 20172017-12-01 00:00:00 UTC2018-01-01 00:00:00 UTC101
Jan 20182018-01-01 00:00:00 UTC2018-02-01 00:00:00 UTC211
Feb 20182018-02-01 00:00:00 UTC2018-03-01 00:00:00 UTC000
Mar 20182018-03-01 00:00:00 UTC2018-04-01 00:00:00 UTC000
Apr 20182018-04-01 00:00:00 UTC2018-05-01 00:00:00 UTC202
May 20182018-05-01 00:00:00 UTC2018-06-01 00:00:00 UTC101
Jun 20182018-06-01 00:00:00 UTC2018-07-01 00:00:00 UTC312
Jul 20182018-07-01 00:00:00 UTC2018-08-01 00:00:00 UTC101
Aug 20182018-08-01 00:00:00 UTC2018-09-01 00:00:00 UTC202
Sep 20182018-09-01 00:00:00 UTC2018-10-01 00:00:00 UTC101
Oct 20182018-10-01 00:00:00 UTC2018-11-01 00:00:00 UTC000
Nov 20182018-11-01 00:00:00 UTC2018-12-01 00:00:00 UTC000
Dec 20182018-12-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
Jan 20192019-01-01 00:00:00 UTC2019-02-01 00:00:00 UTC101

What Hacker News says

1 sources
Lambdo is a workflow engine which simplifies data analysis by combining in one analysis pipeline * Feature engineering and machine learning: Lambdo does not distinguish them and treats them as data transformations * Model training and prediction: both feature definitions and ML models can be trained as part of one workflow * Table population and column evaluation: workflow consists of nodes of these two types. This makes it similar to Bistro: https://github.com/asavinov/bistro Lambdo is intended for the following use cases: * Numerous derived features with parameters derived from the data * Regular re-training is required by using the same features as those to be used during prediction * Time series analysis because it is where the quality of derived features is especially important * Customization via user-defined Python functions
In Show HN: Lambdo – Feature engineering and machine learning together

MAKE YOURSELF AT HOME

A few shortcuts

/
Search the collection
?
Open this guide
Esc
Close dialogs and navigation

Your saved repositories and interests stay in this browser.