Since its start in 2014, the lightweight open source Python library Gammapy has come a long way to become a popular data analysis package for high-energy astrophysics. Selected as the official CTAO Science Analysis tool, it is also an approved analysis software within the H.E.S.S. and MAGIC collaborations. The first long-term version, Gammapy v1.0 was released on late 2022. It is compliant with several well-established data conventions in high-energy astrophysics, and provides serialised data products that are interoperable with other software. Event lists and instrument response functions curated within the same format from various instruments can be reduced to data binned in energy, time or spatial coordinates. Thereafter, the flux and morphology of one or more gamma-ray sources can be estimated using Poisson maximum likelihood fitting and assuming a variety of spectral, temporal and spatial models. Flux points, likelihood profiles and light curves extractions are supported. Complex user defined likelihoods and models can also be implemented. In this contribution, we will highlight the main features of Gammapy v1.0, including data reduction and analysis examples from different space and ground-based instruments, applications of various background rejection techniques, and a simultaneous fitting across multiple instruments with astrophysical models. We will also present our plans for the future, showcasing new features such as the support of different event types, unbinned likelihood analysis, spectral unfolding and transient source detections. In addition to an improved API with distributed computing for scalable analysis, enhanced support for all-sky instruments like Fermi-LAT and HAWC is foreseen.