IParse
Crate
| IParse | Crate | |
|---|---|---|
| 5 | 6 | |
| 11 | 3,957 | |
| - | 0.5% | |
| 3.3 | 9.9 | |
| 5 months ago | 6 days ago | |
| C++ | Java | |
| 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.
IParse
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I Wrote a String Type
Nice library with many features. But I do not always understand the focus on memory usage. I guess that the reason behind this is that less memory allocations, have a positive effect on execution times. In a parser, where you often have to compare identifiers, it is a good idea to put all strings for identifiers into a unique pointer with the help of a hash table.
In my interpreting parser [1] I use a hexa hash tree [2] for storing identifiers. It is not very memory efficient, but very fast. It turns every string (from the input buffer) into a unique pointer for that string pointing to a copy of the string. In this way comparing string (identifiers) is equivalent to comparing pointers.
The idea of the hexa hash tree is that is a tree where each node has sixteen child nodes. Which node is selected is based on a step wise evaluated hash function that first takes the lower four bytes of the string, and after reaching the end of the string, the higher four bytes of the string. The nodes often taken up more memory space than the strings themselves.
[1] https://github.com/FransFaase/IParse/
[2] https://github.com/FransFaase/IParse/blob/master/software/Id...
- Noulith: A new programming language currently used by the Advent of Code leader
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The Tools I Use to Write Books (2018)
I wrote a tool that can process a number of MarkDown files with fragments of C code and put all those fragments in the right order to produce a file that can be compiled. It is grammar based and works with manipulating Abstract Syntax Trees, so I guess, it could be adapted for different programming languages. See: https://github.com/FransFaase/IParse#markdownc
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C++ Compile Time Parser Generator
Interesting. I have not looked into the code, but I wonder whether it is a compiler, or just an interpreter, e.g. it converts the grammar into some internal representation that is executed by an interpreter or virtual machine. I started worked on an interpreting parser in C many years ago. And later also made Java, C++ and JavaScript version of it. For the JavaScript implementation, see: https://fransfaase.github.io/ParserWorkshop/Online_inter_par... For the C++ version, see: https://github.com/FransFaase/IParse
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Parser generators vs. handwritten parsers: surveying major languages in 2021
I implemented an unparse function in IParse, which is not a parser generator, but a parser that interprets a grammar. See for example https://github.com/FransFaase/IParse/blob/master/software/c_... where symbols starting with a back slash are a kind of white space terminals during the unparse. For example, \inc stands for incrementing the indentation where \dec decrements it. The \s is used to indicate that at given location a space should be included.
Crate
- FLaNK AI - 01 April 2024
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Creating an advanced search engine with PostgreSQL
I'm wondering if CrateDB [https://github.com/crate/crate] could fit your use case.
It's a relational SQL database which aims for compatibility with PostgreSQL. Internally it uses Lucene as a storage and such can offer fulltext functionality which is exposed via MATCH.
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Distributed query execution in CrateDB: What you need to know
A logical execution plan does not take into account the information about data distribution. CrateDB is a distributed database and data is sharded: a table can be split into many parts - so-called shards. Shards can be independently replicated and moved from one node to another. The number of shards a table can have is specified at the time the table is created.
- Parser generators vs. handwritten parsers: surveying major languages in 2021
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Querying time series data with SQL: examples
PD: If you liked this post... We'd really appreciate a ⭐️ in Github!
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What is CrateDB? 🤔 FAQ
But there's nothing better than trying things by yourself... So Download CrateDB, experiment, and tell us what you think! 😁
What are some alternatives?
aoc - My Advent of Code solutions.
Presto - The official home of the Presto distributed SQL query engine for big data
ruby - The Ruby Programming Language
OrientDB - OrientDB is the most versatile DBMS supporting Graph, Document, Reactive, Full-Text and Geospatial models in one Multi-Model product. OrientDB can run distributed (Multi-Master), supports SQL, ACID Transactions, Full-Text indexing and Reactive Queries.
ctpg - Compile Time Parser Generator is a C++ single header library which takes a language description as a C++ code and turns it into a LR1 table parser with a deterministic finite automaton lexical analyzer, all in compile time.
MapDB - MapDB provides concurrent Maps, Sets and Queues backed by disk storage or off-heap-memory. It is a fast and easy to use embedded Java database engine.
wefx - Basic WASM graphics package to draw to an HTML Canvas using C. In the style of the gfx library
jOOQ - jOOQ is the best way to write SQL in Java
pp - PP - Generic preprocessor (with pandoc in mind) - macros, literate programming, diagrams, scripts...
Flyway - Flyway by Redgate • Database Migrations Made Easy.
nearley - 📜🔜🌲 Simple, fast, powerful parser toolkit for JavaScript.
sql2o - sql2o is a small library, which makes it easy to convert the result of your sql-statements into objects. No resultset hacking required. Kind of like an orm, but without the sql-generation capabilities. Supports named parameters.