asteval VS TheAlgorithms

There is asteval project. It makes more poweful (ans slower) virtual python interpreter which you can use to run many commands in shared context. My benchmark (100 000 runs of simple python expressions):

If compare to asteval (which is actually has much more features), evalidate is much faster in my benchmarks (benchmark code in repo): 0.017s vs 1.232s

But, literals are not good enough very often, and one may want to do "len(foo)+bar[i]" , so I went searching trying to find a good implementation. I dug and found asteval, but this issue I raised breaks it for me, apart from the fact that I try not to rely on too many modules beyond the standard library + it has a bunch of peculiarities that make it not a real drop-in replacement to eval().

Is it me or does it not seem very well thought out? Every example I've seen only has implementations in JavaScript and/or Python. I haven't seen any other languages nor a way to search by language. What a "string" means in one language can be completely different in another language. The primitive data types that the project assumes are not really supported across all programming languages.

Also if anyone hasn't already seen them, similar projects already exist and are more complete. E.g.

* https://rosettacode.org/

* https://programming-idioms.org/

* https://the-algorithms.com/

Not to mention LeetCode, CodeWars, Project Euler, Exercism can kinda serve the same role.

Hey Everyone, My name is Rachit Chawla and Its my first blog on dev.to. I am currently a student of Computer Programming and Analysis at Seneca College. Also I'm currently on my co-op term working as an Automation Developer at Ontario Public Service. In this role, I am currently working with PowerShell scripting and Microsoft Azure for automating every manual tasks to reduce workload and increase efficiency. This blog is a part of OSD600 course at Seneca College. I am taking this course as I am big fan of open source and always wanted to contribute in open source projects but I am unaware of proper documentation and standards used for open source contributions. I am hoping to learn all the required stuff by the end of this course and I aim to be one of the 15k contributors to Linux's repo by Linus Torvald. Open Source interests me because it gives developers the power to customise the application they want to use, also a chance to help others and improve their skills. I found https://github.com/TheAlgorithms/Python interesting from the Monthly trending feed on Github as it has all the algorithms which help us improve time complexity and write better codes. I has about 1000 contributors which helped to code all the algorithms in Python which may help others for working or learning purposes. I myself was a student of Data Structures and Algorithms in Python Winter 2023 and hoping to even able to contribute to this repo itself, once I learn more about documentation & proper standards to be followed.

The Algorithms Contains many open source implementations of algorithms. Check it out.

If you want to see implementations of all possible traversal algorithms you can find it here.

The mother load of all algorithms in python is here. dfs/bfs in particular are in the graph section.

There is no one way to learn all these but here are some resources: 1. Gooking algorithms [https://edu.anarcho-copy.org/Algorithm/grokking-algorithms-illustrated-programmers-curious.pdf\] 2. Algorithms in all languages [https://the-algorithms.com/] 3. Node js best practices. [https://github.com/goldbergyoni/nodebestpractices] 4. Refactoring [https://refactoring.guru/] 5. Learn about Clean Code and Clean Architecture from uncle bob. https://www.youtube.com/watch?v=NeXQEJNWO5w&ab_channel=StreamAConStreamingConferences

DSA basics

I would recommend The Algorithms, it comes with descriptions and examples in multiple programming languages.

There's also The Algorithms. Many implementations are unfortunately low quality. The Lua ones (disclaimer: I wrote them) should be fine however.

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