A set of Python notebooks for the calibration, azimuthal integration and caking of synchrotron X-ray diffraction (SXRD) pattern images, using the pyFAI and FabIO packages. The notebooks can be used for calibration, and then for azimuthal integration or caking of synchrotron diffraction images, to enable further processing and analysis of synchrotron data using software packages such as TOPAS, xrdfit, or MAUD. Azimuthal integration is the first step necessary for calculating bulk phase fraction from the ratio of different phase peak intensities using TOPAS. Caking is neccessary for determining elastic lattice strain, from peak shifts along particular directions, using xrdfit. And caking can also be used to determine crystallographic texture from intensity variations of different lattice plane peaks along different directions, using xrdfit or MAUD. This package supports these analyses by converting the diffraction pattern images into calibrated integrated and caked data in different text formats. The package works with diffraction pattern image data in the form of .cbf or .tiff images. And also includes a notebook for converting diffraction pattern images from .cbf to .tiff format. The azimuthally integrated and caked data can be output as .xy, .dat, or in other text formats, along with a .poni calibration file. Contents It is recommended the user works through the examples in the notebooks in the following order: 1. `pyFAI-calibration-example.ipynb` - An example notebook demonstrating calibration of the detector and beamline setup based on a calibrant standard diffraction pattern image, such as CeO2 of LaB6. The calibration paramaters are saved as a .poni file. 2. `pyFAI-caking-example.ipynb` - An example notebook demonstrating azimuthal integration and caking of diffraction pattern images for saving as text files. Includes an example for saving data in a format to be used in TOPAS, xrdfit and MAUD. 3. `pyFAI-sample-rotation-example.ipynb` - An example notebook demonstrating how the diffraction pattern image is displayed in the notebook and how to rotate the data if required. 4. `pyFAI-analysis.ipynb` - A notebook for automatically calibrating, azimuthally integrating and caking large synchrotron diffraction pattern image datasets, using input parameters contained in .yaml input files. 5. `cbf_to_tif_image_converter.ipynb` - A notebook for converting diffraction pattern images from .cbf to .tiff format, using input parameters contained in .yaml input files. Note, the `example-data/`, `example-calibration/` and `example-analysis/` folders contain data that can be used as an example analysis, but a clear external file structure should be setup to support the analysis of large synchrotron datasets. Installation Instructions for installing the Python libraries to run the notebooks can be found in the README.md file.