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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Scout APM
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
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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
Official home of the DB Browser for SQLite (DB4S) project. Previously known as "SQLite Database Browser" and "Database Browser for SQLite". Website at:
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SonarQube
Static code analysis for 29 languages.. Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.
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Nuitka
Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, and 3.10. You feed it your Python app, it does a lot of clever things, and spits out an executable or extension module.
q reviews and mentions
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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
- OpenOffice. Necesito ver una hoja de cálculo que tiene 6 millones de columnas, pero no puedo
- Zq: An Easier (and Faster) Alternative to Jq
- Show HN: "q", a DNS Query Tool with Support for UDP, TCP, DoT, DoH, DoQ and ODoH
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MUST HAVE Linux Programs/Commands?
firejail to isolate applications within the same user account. tmux to have detachable multiple windows and multiple panes in the terminal. jq to parse JSON. q to run SQL queries on CSV files. yt-dlp to download videos from everywhere. ncdu to visualize and explore disk usage. htop to monitor processes and resources.
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How to use SQL to directly query files
q also has a standalone executable, which you can download from this link. If you want to use the Windows installer, you can run the executable and follow the prompts displayed on the screen.
You might consider using q to query your files if you are working with .csv or .tsv files and need something that works faster than TextQL. q aims to bring SQL’s expressive capability to the Linux command line by offering direct access to multi-file SQLite3 databases and simple access to text as actual data.
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Dsq: Commandline tool for running SQL queries against JSON, CSV, Parquet, etc.
dsq references a benchmark done by q (https://github.com/harelba/q/blob/master/test/BENCHMARK.md) that indicates that octosql is significantly slower.
However, octosql's GH repo claims otherwise.
Does anyone have any real world experience that they can share on these tools?
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A fast SQLite PWA notebook for CSV files
Second this recommendation for the terminal. For my CLI toolbox, VisiData is my favorite.
I find VisiData is great for quickly exploring and querying data that from the CLI. It can handle many types of files (SQLite, CSV, TSV, Excel, JSON, YAML, etc). Visidata loads all the data into memory, and so is very responsive when exploring the data. It allows you to quickly do all sorts of of adhoc queries interactively, without having to write a valid SQL query.
I haven't used Q. When I first heard of it, I liked the idea that Q allowed you to run random queries on CSV and TSV files. However, it seemed like it would be slow if you wanted to do follow up queries, since it had to repopulate the in memory SQLite file for each query. Though it looks like the latest version has a way to cache the generated sqlite file. So that seems like it could help.
Also, if I have some CSV, TSV, JSONL data sqlite-utils is useful for converting them to SQLite, and then exploring with Visidata or SQL queries.
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Compile Python applications into stand-alone executables
How did you go about developing against the Starlark API, any IDE support?
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Setting Up Gmail in Doom Emacs using mbsync and mu4e
Tables are fairly easy to extract from org-files, even with some sed/awk function, e.g. `getOrgTable() { awk -vT=$1 '/^#\+NAME: /&&$2~T{f=1;next};/----/{next};!/^\|/{f=0};f' $2 ; }`
The above should work for most tables, and you get back a pipe-separated-values output, that you could further refine with e.g. http://harelba.github.io/q/ to get tsv,csv output support and SQL query capabilities.
I regularly SQL-Query with INNER JOINs over tables in various org-files stored on multiple servers in one commandline using this combination.
John Kitchen has a description for a "cleaner" way to do it here:
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End of the snahp blog | Invitation for data hoarders
Use the tool q with the following command line: q --encoding=utf8 --tab-delimited --disable-double-double-quoting --input-quoting-mode=all --as-text --output-quoting-mode=none --output-encoding=utf8 --save-db-to-disk=wp_posts.sqlite3 "select * from ./wp_posts.csv"
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Does Java have an open source package that can execute SQL on txt/csv?
There are a whole pile of open source big data tools, largely written in Java, that are designed to “execute SQL on txt/csv”. Someone mentioned spark and drill. Hive is another big one. Another very reasonable approach, depending on your use case, is to use a command line tool like q (https://github.com/harelba/q) to process the data out of band (e.g., stdin if this is a script).
- Lokale SQL-DB zum schnellen Durchsuchen von Daten
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harelba/q is an open source project licensed under GNU General Public License v3.0 only which is an OSI approved license.
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