Filprofiler

Features

- Added support for profiling inside Jupyter. ([12](https://github.com/pythonspeed/filprofiler/issues/12))
- Fil can now be installed via Conda-Forge. ([20](https://github.com/pythonspeed/filprofiler/issues/20))

Features

- When tracking large numbers of allocations, Fil now runs _much_ faster, and has much less memory overhead. ([65](https://github.com/pythonspeed/filprofiler/issues/65))
- Added support for tracking allocations done using `posix_memalign(3)`. ([61](https://github.com/pythonspeed/filprofiler/issues/61))

Bugfixes

- Fixed edge case for large allocations, where wrong number of bytes was recorded as freed. ([66](https://github.com/pythonspeed/filprofiler/issues/66))

Features

- Switched to using jemalloc on Linux, which should deal better both in terms of memory usage and speed with many small allocations.
It also simplifies the code. ([42](https://github.com/pythonspeed/filprofiler/issues/42))
- Further reduced memory overhead for tracking objects, at the cost of slightly lower resolution when tracking allocations >2GB.
Large allocations >2GB will only be accurate to a resoluion of ~1MB, i.e. they might be off by approximately 0.05%. ([47](https://github.com/pythonspeed/filprofiler/issues/47))

Bugfixes

- Significantly reduced the memory used to generate the SVG report. ([38](https://github.com/pythonspeed/filprofiler/issues/38))
- Reduced memory overhead of Fil somewhat, specifically when tracking large numbers of small allocations. ([43](https://github.com/pythonspeed/filprofiler/issues/43))

Bugfixes

- Fix bug that prevented Fil from running on macOS Mojave and older. ([36](https://github.com/pythonspeed/filprofiler/issues/36))

Features

- C++ allocations get tracked more reliably, especially on macOS. ([10](https://github.com/pythonspeed/filprofiler/issues/10))
- Validated that Fortran 90 allocations are tracked by Fil. ([11](https://github.com/pythonspeed/filprofiler/issues/11))


Misc

- [26](https://github.com/pythonspeed/filprofiler/issues/26)