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Q Alternatives
Similar projects and alternatives to q
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octosql
OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
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Sonar
Write Clean Python Code. Always.. Sonar helps you commit clean code every time. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
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InquirerPy
:snake: Python port of Inquirer.js (A collection of common interactive command-line user interfaces)
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sqlitebrowser
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ONLYOFFICE
ONLYOFFICE Docs — document collaboration in your environment. Powerful document editing and collaboration in your app or environment. Ultimate security, API and 30+ ready connectors, SaaS or on-premises
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Nuitka
Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11. You feed it your Python app, it does a lot of clever things, and spits out an executable or extension module.
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InfluxDB
Access the most powerful time series database as a service. Ingest, store, & analyze all types of time series data in a fully-managed, purpose-built database. Keep data forever with low-cost storage and superior data compression.
q reviews and mentions
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I wrote this iCalendar (.ics) command-line utility to turn common calendar exports into more broadly compatible CSV files.
CSV utilities (still haven't pick a favorite one...): https://github.com/harelba/q https://github.com/BurntSushi/xsv https://github.com/wireservice/csvkit https://github.com/johnkerl/miller
- Segítség kérés Excel automatizáláshoz
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Show HN: ClickHouse-local – a small tool for serverless data analytics
I think they're talking about https://github.com/harelba/q, which is not very fast.
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sqly - execute SQL against CSV / JSON with shell
Apparently, there were many who thought the same thing; Tools to execute SQL against CSV were trdsql, q, csvq, TextQL. They were highly functional, hoewver, had many options and no input completion. I found it just a little difficult to use.
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Q – Run SQL Directly on CSV or TSV Files
http://harelba.github.io/q/#requirements
"q is packaged as a compiled standalone-executable that has no dependencies, not even python itself."
This is not quite true, on MacOS:
"q: A full installation of Xcode.app 12.4 is required to compile
Hi, author of q here.
Regarding the error you got, q currently does not autodetect headers, so you'd need to add -H as a flag in order to use the "country" column name. You're absolutely correct on failing-fast here - It's a bug which i'll fix.
In general regarding speed - q supports automatic caching of the CSV files (through the "-C readwrite" flag). Once it's activated, it will write the data into another file (with a .qsql extension), and will use it automatically in further queries in order to speed things considerably.
Effectively, the .qsql files are regular sqlite3 files (with some metadata), and q can be used to query them directly (or any regular sqlite3 file), including the ability to seamlessly join between multiple sqlite3 files.
- PostgreSQL alternative for Large amounts of data
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q VS trdsql - a user suggested alternative
2 projects | 25 Jun 2022
- One-liner for running queries against CSV files with SQLite
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A note from our sponsor - InfluxDB
www.influxdata.com | 1 Jun 2023
Stats
harelba/q is an open source project licensed under GNU General Public License v3.0 only which is an OSI approved license.
The primary programming language of q is Python.