pxi
ipython-sql
Our great sponsors
| pxi | ipython-sql | |
|---|---|---|
| 4 | 3 | |
| 267 | 1,760 | |
| - | - | |
| 0.0 | 1.0 | |
| over 3 years ago | 29 days ago | |
| JavaScript | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pxi
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The fastest tool for querying large JSON files is written in Python! (benchmark)
Very interesting piece of software :). I have put a lot of work in pxi, a very similar tool written in pure JavaScript. I am not here to start a flame war between Python and JavaScript btw., I am actually thrilled to find another person that has written a very similar project :).
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New command-line parser with 35+ opt-in features developed for 5 months needs your feedback
I have been working on a command-line parser for one of my open source projects (pxi) for about 5 months now. Today I have reached a milestone and wanted to collect feedback before I move on:
- List of JSON tools for command line
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[OC] pjs is an awk-like tool for processing text, CSV, JSON, HTML, and XML
Hey, good job! If you wrote this to get a task done, you may also want to have a look at pxi (disclosure, I am the author).
ipython-sql
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Anyone here using Hex or DeepNote?
I've seen folks talk about this before. Is the ability to switch much better than what's offered by this ipython-sql magic?
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Making Jupyter notebooks more SQL-friendly?
Sometimes I use the ipython-sql extension, allowing me to write simpler code than pandas.read_sql. However, I think some features would come in handy.
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The fastest tool for querying large JSON files is written in Python! (benchmark)
It makes sense considering A because lots of stuff that runs on top of SQLAlchemy would be able to use the spyql engine to query files using SQL. One example would be the IPython extension that allows typing SQL queries on Jupyter notebooks ipython-sql.
What are some alternatives?
jid - json incremental digger
jfq - JSONata on the command line
yamlpath - YAML/JSON/EYAML/Compatible get/set/merge/validate/scan/convert/diff processors using powerful, intuitive, command-line friendly syntax.
spyql - Query data on the command line with SQL-like SELECTs powered by Python expressions
Textrude - Code generation from YAML/JSON/CSV models via SCRIBAN templates
fx - Terminal JSON viewer & processor
nvim-jqx - Populate the quickfix with json entries
dasel - Select, put and delete data from JSON, TOML, YAML, XML and CSV files with a single tool. Supports conversion between formats and can be used as a Go package.
block-content-to-react - Deprecated in favor of @portabletext/react
jj - JSON Stream Editor (command line utility)