tanin

12 ms·

121.
by tanin 5y ago
Welp, I was gonna post my web0 desktop Electron app for working with CSVs using SQL: https://superintendent.app
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Analyze log files with SQL using Superintendent.app(tanin.nanakorn.com)
3 points by tanin 5y ago|0 comments
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by tanin 5y ago
For programmers, how about using SQL instead? https://superintendent.app Anyway, the design of Tinysheet looks refined and slick. Very nice job.
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by tanin 5y ago
IMO it depends on the expertise, comfort level, and many other factors since it is a personal tool. I'm comfortable with programming languages, but I rarely write a Ruby code to process a CSV file. I still prefer using spreadsheet or S
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Ask HN: Code signing an app on Windows. Which EV cert provider do you recommend?
1 points by tanin 5y ago|1 comments
126.
by tanin 5y ago
US economy is so crappy sometimes. Eating out is so expensive. Servers can't live off their wages. The restaurants are not profitable. Where the hell does the money go? Why is a restaurant business not viable?
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by tanin 5y ago
I've built a similar project (backed by Sqlite), though it's full GUI. At work, I work with a lot of CSVs. I often hit the limit of Excel and Google Sheets. Plus, using formula is difficult. The ergonomics around it is also not gr
128.
by tanin 5y ago
It's great to see more desktop app in this space. Desktop app can handle big data much better (and cheaper) than a web app if the dataset is not terabytes. I built a similar Desktop application where you can write SQL, though you will
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by tanin 5y ago
I've built a desktop app where you can load a CSV and start writing SQL on it. A lower barrier to try it out might be helpful in learning SQL. See: https://superintendent.app
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by tanin 5y ago
This is actually quite important. Some tasks that are seemingly simple in a normal programming language can sometimes be impossible to achieve in SQL (e.g. dynamically generated columns...)
131.
by tanin 5y ago
Yes, it supports all 3 platforms. Hope you enjoy it!
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by tanin 5y ago
Yes! with few additionalfunctionality added (e.g. regex, parse_date, tsv). Initially, I wanted it for myself because I used Excel a lot but I never loaded CSVs into a database (dunno why). Using SQL is much more convenient than Excel's
133.
by tanin 5y ago
I've built a desktop app that enables you to load CSV files and perform SQL on the CSVs. I imagine it would be handy for anyone who starts learning SQL because you don't need to setup the database or use command-line. If you are i
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by tanin 5y ago
I'm not sure why Excel is suitable in the first place. It has 1M row limit. Plus, generally, a log file is JSON-based, not CSV. If you are looking for a quick tool to perform SQL on CSV (maybe your log is in CSV), I've built a des
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by tanin 5y ago
Spreadsheet is incredibly powerful However, if your use case is narrower (e.g. only use CSVs), there are more suitable tools. As a person who knows how to code, using a real programming language or SQL is way way better. To that end, I&#x27
136.
by tanin 5y ago
I use a mouse with 3 extra buttons. 2 are for copying and pasting, and 1 is for activating a programmable tooltip. Here are the apps to achieve above (I built them): 1. Mouse config tool for Mac https://github.com/tanin47&#x
137.
by tanin 5y ago
Shameless plug: I'm building a Desktop app that serves the niche between Excel and Python. It enables you to load CSVs and write SQL on those CSVs. The main benefit is that it is very fast when compared to Excel or Python. Excel cannot
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by tanin 5y ago
My use case is a bit more complex. I have to compile it with an electron app and etc. I filed a few GitHub issues with them as well. This has great potential. The dialect is much more comprehensive than the Sqlite one.
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by tanin 5y ago
OP here. It is not that automatic. We simply import every column as TEXT, which seems to work well enough :)
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by tanin 5y ago
I probably model it off myself too much. I know Postgresql very well... But I rarely use psql. I still use pgadmin. That said, I never load CSVs into Postgresql. I still tried very hard to load CSVs into Excel. My personal opinion is that p
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by tanin 5y ago
OP here. Yes! we use Sqlite under the hood with modified C extensions, so it can be as fast as it can be. (Just try not to touch JS code for this) However, I have recently learned that SIMD is even faster than C, but I haven't explored
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by tanin 5y ago
Any feedback or suggestion is very welcome! Please don't hesitate to email me at tanin@superintendent.app
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by tanin 5y ago
I use MacBook Pro 2020, so it is probably faster. Also 1.4 GB is quite difference from 1GB. These factors can multiply the run time. Superintendent uses the same approach (i.e. use the CSV extension). But I don't think we should call t
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by tanin 5y ago
I built https://superintendent.app and experimented a lot with this feature. I can import 1GB CSV file in 10 seconds on my MacBook. This queries from a virtual table and puts it in actual table
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by tanin 5y ago
This is OP, but that is amazing. I tried reading 1GB CSV and add all the rows into Sqlite, and it definitely takes minutes. This happens to both JS and python. Constructing a giant INSERT should already exceed 1 minutes (or transforming any
146.
by tanin 5y ago
Hi! I'm the OP here. The performance gain is mainly from reading/writing files in C and/or by Sqlite (which is also C). Any other tool that use dynamic languages like python will immediately takes minutes to handle any GB-siz
147.
by tanin 5y ago
The difference is between GUI and command-line. I work with a lot of CSV files, and for some reason I rarely load them into Postgres or use Python script. I still try very hard to use Excel. There is some degree of convenience that GUI off
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by tanin 5y ago
Thank you for your feedback. I'm a non native English speaker, so I would like to ask if you can point out a few places you feel they are off putting. I would really really love to fix those.
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Show HN: Work with CSV files using SQL. For data scientists and engineers(superintendent.app)
99 points by tanin 5y ago|61 comments
150.
by tanin 5y ago
Hi HNers, I'm Tanin and have built Superintendent.app which enables you to load (large) CSV files and write SQL on them. You can export the output back and/or make charts. There are 2 problems working with CSVs using Excel: 1. Exc

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