Scalene

- fixed synchronization and multiprocessing support for `--profile-interval`;
- fixed certain profiling data possibly being included when profiling was turned off;
- wheels (binary builds) now available from [pypi](https://pypi.org/project/scalene/) for Linux (x86_64) and MacOS (x86_64 and M1);

Fixes a bug exposed on Mac OS X when using packages that include SQLite.

This release includes the following major new features:
* **GPU profiling**. If your system has an nvidia GPU, the profiler will automatically do line-level GPU utilization profiling (just like it already does for CPU).
* **Suspend/resume**. When Scalene is profiling a program launched in the background (via `&`), you can now suspend and resume profiling. To suspend profiling of pid `12345` (Scalene will print the pid when launched in the background): `python3 -m scalene.profile --off --pid 12345`. To resume profiling: `python3 -m scalene.profile --on --pid 12345`.
* **Improved Jupyter support**. Scalene now indicates in its profiles which Jupyter cell a function was defined in, as in `[5]`.
* **Various bug fixes** that improve Scalene's robustness, especially when profiling code using multithreaded libraries like `numpy`.

* **Jupyter** support (currently CPU profiling only); use `%scrun` or `%%scalene`
* **Function summaries**: sorted list of functions by CPU time
* **Memory consumption**: reports top K lines allocating the most memory
* Reports **memory growth** over time (indicating possible leaks)
* **Line-level memory leak detection** "for free"
* Full `multiprocessing` support
* Adds `--profile-only` flag to restrict profiling to files that contain the given string
* Massive refactoring and cleanup of codebase