JDFTx uses the GC-SCF and AuxH electronic algorithms, which outperform outer-loop grand canonical electronic algorithms found in other codes. Advanced solvation models are available including the non-linear non-local SaLSA implicit solvent model as well as CANDLE, a linear implicit solvent model with asymmetric charge response. JDFTx can also be integrated directly into excited state calculations in BerkeleyGW, although atomate2 support for GW workflows with JDFTx is not expected soon. JDFTx output and input files are parsed with code in pymatgen.io.jdftx. JDFTx log files, eigenvalue and bandProjection files are currently supported by the parsers.