ParaMonte::Python (standing for Parallel Monte Carlo in Python) is a serial and MPI-parallelized library of (Markov Chain) Monte Carlo (MCMC) routines for sampling mathematical objective functions, in particular, the posterior distributions of parameters in Bayesian modeling and analysis in data science, Machine Learning, and scientific inference in general. In addition to providing access to fast high-performance serial/parallel Monte Carlo and MCMC sampling routines, the ParaMonte::Python library provides extensive post-processing and visualization tools that aim to automate and streamline the process of model calibration and uncertainty quantification in Bayesian data analysis. Furthermore, the automatically-enabled restart functionality of ParaMonte::Python samplers ensure seamless fully-deterministic into-the-future restart of Monte Carlo simulations, should any interruptions happen. The ParaMonte::Python library is MIT-licensed and is permanently maintained on GitHub at https://github.com/cdslaborg/paramonte/tree/master/src/interface/Python.

中文翻译：

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通过 ParaMonte::Python 库进行快速、完全可重复的串行/并行 Monte Carlo 和 MCMC 模拟和可视化

ParaMonte::Python（代表 Python 中的 Parallel Monte Carlo）是（马尔可夫链）Monte Carlo (MCMC) 例程的串行和 MPI 并行库，用于采样数学目标函数，特别是贝叶斯建模中参数的后验分布和数据科学、机器学习和一般科学推理的分析。除了提供对快速高性能串行/并行蒙特卡罗和 MCMC 采样例程的访问之外，ParaMonte::Python 库还提供了广泛的后处理和可视化工具，旨在自动化和简化贝叶斯模型校准和不确定性量化的过程数据分析。此外，ParaMonte 的自动启用重启功能:: 如果发生任何中断，Python 采样器可确保蒙特卡洛模拟在未来重新启动的无缝完全确定性。ParaMonte::Python 库是 MIT 许可的，并在 GitHub 上永久维护，网址为 https://github.com/cdslaborg/paramonte/tree/master/src/interface/Python。