Lark
tensorflow
Our great sponsors
Lark | tensorflow | |
---|---|---|
35 | 221 | |
4,471 | 182,323 | |
2.7% | 0.7% | |
7.5 | 10.0 | |
4 days ago | about 16 hours ago | |
Python | C++ | |
MIT License | 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.
Lark
-
Show HN: I wrote a RDBMS (SQLite clone) from scratch in pure Python
Lark supports, and recommends, writing and storing the grammar in a .lark file. We have syntax highlighting support in all major IDEs, and even in github itself. For example, here is Lark's built-in grammar for Python: https://github.com/lark-parser/lark/blob/master/lark/grammar...
You can also test grammars "live" in our online IDE: https://www.lark-parser.org/ide/
The rationale is that it's more terse and has less visual clutter than a DSL over Python, which makes it easier to read and write.
-
Oops, I wrote yet another SQLAlchemy alternative (looking for contributors!)
First, let me introduce myself. My name is Erez. You may know some of the Python libraries I wrote in the past: Lark, Preql and Data-diff.
-
Hey guys, have any of you tried creating your own language using Python? I'm interested in giving it a shot and was wondering if anyone has any tips or resources to recommend. Thanks in advance!
It's not super maintained but you might enjoy building something with ppci, Pure Python Compiler Infrastructure. It has some front-ends and some back-ends. There's also PeachPy for an assembler. People like using Lark for parsing, I hear.
-
Is it possible to propagate higher level constructs (+, *) to the generated parse tree in an LR-style parser?
lark, a parsing library where I am somewhat involved has a really nice solution to this: Rules starting with _ are inlined in a post processing step.
-
can you create your own program language in python, if yes how?
Lark is a good library to assist with this.
- Lark a Python lexer/parser library
-
Create your own scripting language in Python with Sly
If I may ask, did you consider Lark, and if so, why wasn't it fit for your purposes?
- Creating a language with Python.
-
Not Your Grandfather’s Perl
A grammar provides the high level constructs you need to define the "shape" of your data, and it largely takes care of the rest. Grammar libraries exist in other language (eg. lark or Parsimonius in Python) and they weren't created just to make XML parsing easier.
-
Earley Parsing Explained
I made a solid attempt at an Earley parser framework of my own, but apparently to get the most reliable performance from Earley parsing you need to implement Joop Leo's improvement for right-recursive grammars, which nobody has been able to adequately explain to me. I've read Kegler's open letter to Vaillant, I've tried to read other implementations, I've even tried to beat my head against the original academic paper, but I don't have the background knowledge to make sense of it all.
tensorflow
- TensorFlow-metal on Apple Mac is junk for training
-
🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
To get up to speed with TensorFlow, check their quickstart Support TensorFlow on GitHub ⭐
- One .gitignore to rule them all
-
10 Github repositories to achieve Python mastery
Explore here.
-
GitHub and Developer Ecosystem Control
Part of the major userbase pull in GitHub revolves around hosting a considerable number of popular projects including Angular, React, Kubernetes, cpython, Ruby, tensorflow, and well even the software that powers this site Forem.
-
Non-determinism in GPT-4 is caused by Sparse MoE
Right but that's not an inherent GPU determinism issue. It's a software issue.
https://github.com/tensorflow/tensorflow/issues/3103#issueco... is correct that it's not necessary, it's a choice.
Your line of reasoning appears to be "GPUs are inherently non-deterministic don't be quick to judge someone's code" which as far as I can tell is dead wrong.
Admittedly there are some cases and instructions that may result in non-determinism but they are inherently necessary. The author should thinking carefully before introducing non-determinism. There are many scenarios where it is irrelevant, but ultimately the issue we are discussing here isn't the GPU's fault.
-
Can someone explain how keras code gets into the Tensorflow package?
and things like y = layers.ELU()(y) work as expected. I wanted to see a list of the available layers so I went to the Tensorflow GitHub repository and to the keras directory. There's a warning in that directory that says:
-
Is it even possible to design a ML model without using Python or MATLAB? Like using C++, C or Java?
Exactly what language do you think TensorFlow is written in? :)
-
How to do deep learning with Caffe?
You can use Tensorflow's deep learning API for this.
-
When the documentation has TODOs
Since you've specifically mentioned ML, here's Tenserflow's GitHub. I'm sure a quick glance through that will change your mind.
What are some alternatives?
pyparsing - Python library for creating PEG parsers [Moved to: https://github.com/pyparsing/pyparsing]
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
PLY - Python Lex-Yacc
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
pydantic - Data validation using Python type hints
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
sqlparse - A non-validating SQL parser module for Python
LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Atoma - Atom, RSS and JSON feed parser for Python 3
scikit-learn - scikit-learn: machine learning in Python
Construct - Construct: Declarative data structures for python that allow symmetric parsing and building
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.