Python-graphblas

- Add `"__weakref__"` to `__slots__` so objects are weakref-able.
- Test with Python 3.9

- Add infix sugar for `ewise_plus`, `ewise_mult`, `mxm`, `apply`, etc! For example:
- `C << op(A | B) ewise_plus`
- `C << op(A & B) ewise_mult`
- `C << op(A B) mxm, vxm, mxv`
- `C << op(A) apply unary`
- `C << op(A, 1) apply binary, right=1`
- `C << op(1, A) apply binary, left=1`
- Operators:
- Add `grblas.op` namespace that has all unary, binary, and semiring objects.
- Automatically convert binaryop to monoid or vice versa where appropriate if possible.
- Hence, one can use a binaryop from `grblas.op` namespace as a monoid.
- Add attributes such as `binop.monoid`, `monoid.identity`, and `semiring.binaryop` to operators.
- Don't allow a semiring where a monoid or binaryop is expected (do e.g. `semiring.monoid` instead).
- Renamed `grblas.ops` to `grblas.operator`, which defines the base classes of operators.
- Add `my_matrix.ss.head(n)` and `my_vector.ss.head(n)` that returns the indices and values of n elements.
- Improve repr of very sparse Vector and Matrix objects by using the new `C.ss.head()` methods.
- Add `grblas.replace` singleton, so one can do e.g. `C(mask, replace) << A.mxm(V)`.
- Add ability to read and write Matrix Market files with `grblas.io.mmread` and `grblas.io.mmwrite`.
- Allow Scalar, Vector, and Matrix objects to be serialized with pickle.
- Added `__slots__` to all the things.

- Update to SuiteSparse 4.0.3 (new unary and binary ops, etc.)
- Added Windows support (without complex dtypes)
- Use NumPy's malloc/free, so Python knows memory usage of GraphBLAS objects
- Many improvements to import and export with SuiteSparse
- Renamed `fast_export` to `export` and `fast_import` to `import_any`
- Added other import methods such as `Matrix.ss.import_csr`
- support zero-copy import and export if possible (user must opt in)
- formats: csr, csc, hypercsr, hypercsc, bitmapr, bitmapc, fullr, fullc
- Matrix and Vector
- allow contains expressions
- `1 in v`, True if there is a value at `v[1]`
- `(1, 2) in A`, True if there is a value at `A[1, 2]`
- iteration
- Yields the indices of the structure
- Add `.wait()` method
- Add format attribute as e.g. `my_matrix.ss.format`
- One of "csr", "hypercsc", "bitmapr", etc
- Scalar
- Add `.shape` attribute (like Vector and Matrix, and like numpy scalars)
- Able to cast to float and int
- Allow things like `__eq__` where `.value` is or computes a scalar
- Don't allow `__eq__` or `__bool__` where they don't make sense

- Subassign syntax to allow masks sized for the assignment dimensions rather than the full output dimensions
- `input_mask` allows masks to apply to the full input object rather than the extracted dimensions
- Call recorder to auto-generate C code from grblas code
- `to_values()` returns numpy arrays rather than tuples
- `fast_import`/`fast_export` suitesparse extensions are exposed under the `.ss` namespace

- Much nicer reprs (plain and html) for objects (both data and expressions), which replaces `.show()`
- Add "pygraphblas" as a backend choice. This add ability to convert between `grblas` and `pygraphblas`.
- Data objects now have names! (passed in at construction time)
- Moved tests/ inside the grblas package so we can test it after install.
- Use versioneer.py to manage version.
- Apply black code formatter.
- More extensive testing and a few minor bug fixes.