q
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q | Nuitka | |
---|---|---|
46 | 91 | |
10,098 | 10,582 | |
- | 2.0% | |
3.6 | 10.0 | |
2 months ago | 7 days ago | |
Python | Python | |
GNU General Public License v3.0 only | Apache License 2.0 |
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.
q
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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
Nuitka
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Faster Blogging: A Developer's Dream Setup
glee is rich in blogging features but has some drawbacks. One of the main drawbacks is its compatibility with multiple operating systems and system architectures. We lost one potential customer due to glee incompatibility in macOS. Another major issue is the deployment time. We built the first version of glee entirely in Python and used nuitka, nuitka compiles Python programs into a single executable binary file. We need to create three separate stages for creating executable binaries for Windows, Mac, and Linux in deployment, and it takes around 20 minutes to complete.
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Python 3.13 Gets a JIT
There is already an AOT compiler for Python: Nuitka[0]. But I don't think it's much faster.
And then there is mypyc[1] which uses mypy's static type annotations but is only slightly faster.
And various other compilers like Numba and Cython that work with specialized dialects of Python to achieve better results, but then it's not quite Python anymore.
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Briefcase: Convert a Python project into a standalone native application
Nuitka deals pretty well with those in general: https://nuitka.net/
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Why not tell people to “simply” use pyenv, poetry or anaconda
That's more of cultural problem in the Python community.
If I provide an end user software to my client written an Python (so not a backend, not a lib...), I will compile it with nuitka (https://github.com/Nuitka/Nuitka) and hide the stack trace (https://www.bitecode.dev/p/why-and-how-to-hide-the-python-st...) to provide a stand alone executable.
This means the users don't have to know it's made with Python or install anything, and it just works.
However, Python is not like Go or Rust, and providing such an installer requires more than work, so a huge part of the user base (which have a lot of non professional coders) don't have the skill, time or resources to do it.
And few people make the promotion of it.
I should write an article on that because really, nobody wants to setup python just to use a tool.
- Python cruising on back of c++
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Extending web applications with WebAssembly and Python
> Your comment would make sense if Python code could be compiled into x86 or ARM assembly in the first place.
It can actually be compiled (or transpiled) into C code [1] with few limitations, so I can't see why not.
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Codon: Python Compiler
Just for reference,
* Nuitka[0] "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."
* Pypy[1] "is a replacement for CPython" with builtin optimizations such as on the fly JIT compiles.
* Cython[2] "is an optimising static compiler for both the Python programming language and the extended Cython programming language... makes writing C extensions for Python as easy as Python itself."
* Numba[3] "is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code."
* Pyston[4] "is a performance-optimizing JIT for Python, and is drop-in compatible with ... CPython 3.8.12"
- Is there a way to use turn a project into a single executable file that doesn't require anyone to do anything like install Python before using it?
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Python-based compiler achieves orders-of-magnitude speedups
So the differences:
https://docs.exaloop.io/codon/general/differences
So more limited types (integers) and more type checking and collections have to have one kind of thing in them.
There are other python compilers though, like https://github.com/Nuitka/Nuitka
I wonder really what the advantages/disadvantages of these are?
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List of all subreddits on reddit
I also compiled it with Nuitka and was able to process a ~35 million line file in 1 hour and 22 minutes, averaging about 6,800 lines per second.
What are some alternatives?
PyInstaller - Freeze (package) Python programs into stand-alone executables
pyarmor - A tool used to obfuscate python scripts, bind obfuscated scripts to fixed machine or expire obfuscated scripts.
PyOxidizer - A modern Python application packaging and distribution tool
py2exe - modified py2exe to support unicode paths
false-positive-malware-reporting - Trying to release your software sucks, mostly because of antivirus false positives. I don't have an answer, but I do have a list of links to help get your code whitelisted.
py2app
ttkbootstrap - A supercharged theme extension for tkinter that enables on-demand modern flat style themes inspired by Bootstrap.
pynsist - Build Windows installers for Python applications
Poetry - Python packaging and dependency management made easy
dh-virtualenv - Python virtualenvs in Debian packages
textql - Execute SQL against structured text like CSV or TSV
false-positive-malware-reporti