As far as I know, there are mainly PyCDT, PyDEF, pylada and some part of pymatgen. As a new user to those tools, which one would be a good choice?

It would be appreciated if you could explain one of the tools below (or another tool not listed), in the format used here (for example):

One software description per answer please.

Here's some software that I do know, but I would like to know the advantages and disadvantages of them, and more detail:

pycdt: Python Charge Defects Toolkit (PyCDT) is a python package aimed at making charged defects modeling simpler, high throughput ready, and also accessible to researchers who don't have the required background. PyCDT can handle thermodynamic calculations and error corrections in the context of periodic boundary condition density functional calculations of charged defects in semiconductors and insulators. It can also generate the inputs for required DFT calculations and can process the output of the DFT calculations. The code is modular and any DFT code can be integrated into PyCDT for defect calculations.

PyDEF: PyDEF 2.1 is a scientific program. It is a post-treatment software for ab-initio calculations performed with the Vienna Ab-Initio Simulation Package (VASP) featuring a user-friendly Graphical User Interface (GUI).

pylada: An open-source Python framework that automates point defects calculations using VASP. Framework creates point defect structures (vacancies, interstitials, sustitutions) and automate computation of point defect formation energy by providing tools to compute finite size corrections (1. potential alignment, 2. image-charge correction, 3. band-filling correction to shallow defects) with the supercell approach. The high-throughput DFT calculations are performed using PyLada.

pymatgen: There is pymatgen.analysis.defects package, but I am not sure if it's okay to do defect calculation.

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    $\begingroup$ If you post on twitter and tag @StackMatter we can re-tweet for you. Also if you tag the authors of pycdt, PyDEF, pylada and pymatgen, it will help. It worked for this question: mattermodeling.stackexchange.com/questions/1926/…. As you see that the main developer of the software answered, and then someone also got their grad student to answer, both of them were not users of this site before, and both of them interacted with this tweet: twitter.com/StackMatter/status/1291159713636405249 $\endgroup$ Aug 7 '20 at 18:12
  • $\begingroup$ Hi Franksays, this is one of our longest-lasting unanswered questions, and one of our most upvoted ones too. I would like to try to help get it answered. Have you posted it on Twitter with the @StackMatter tag? We will try to spread it so that it is seen by more people. Is it difficult to access Twitter from Hangzhou? I have been to ZJU and managed to browse most websites okay. $\endgroup$ Nov 9 '20 at 20:05
  • $\begingroup$ The first comment should have posted to this link: mattermodeling.stackexchange.com/q/1926/5 ! Sorry for that mistake. $\endgroup$ Nov 9 '20 at 21:04
  • $\begingroup$ Just a note that the functionality in PyCDT and pymatgen include the same developers and are complementary (PyCDT uses pymatgen). I know many people using it with success but I do not personally so can't comment further. $\endgroup$ Mar 16 at 1:03
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    $\begingroup$ @MattHorton As this is now our highest voted unanswered question and one of our longest standing unanswered questions, do you think you might be able to ask those people you know that have been using those programs with success, if they might have some insight that they could share in an answer to this question? No answer has to 100% cover all grounds on a question with this much complexity anyway. $\endgroup$ Apr 29 at 2:57

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