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mdbartos
error when importing Grid class
Hi, I'm getting an error running the command below within Google Colab (I've pip installed using "%pip install "git+https://github.com/mdbartos/pysheds.git"). Any ideas on what might be happening? Thanks!
from pysheds.grid import Grid
/usr/local/lib/python3.7/dist-packages/numba/np/ufunc/parallel.py:363: NumbaWarning: The TBB threading layer requires TBB version 2019.5 or later i.e., TBB_INTERFACE_VERSION >= 11005. Found TBB_INTERFACE_VERSION = 9107. The TBB threading layer is disabled.
warnings.warn(problem)
---------------------------------------------------------------------------
TypingError Traceback (most recent call last)
[<ipython-input-7-c8708fc12346>](https://localhost:8080/#) in <module>()
----> 1 from pysheds.grid import Grid
25 frames
[/usr/local/lib/python3.7/dist-packages/pysheds/grid.py](https://localhost:8080/#) in <module>()
5 _HAS_NUMBA = False
6 if _HAS_NUMBA:
----> 7 from pysheds.sgrid import sGrid as Grid
8 else:
9 from pysheds.pgrid import Grid as Grid
[/usr/local/lib/python3.7/dist-packages/pysheds/sgrid.py](https://localhost:8080/#) in <module>()
34
35 # Import numba functions
---> 36 import pysheds._sgrid as _self
37
38 class sGrid():
[/usr/local/lib/python3.7/dist-packages/pysheds/_sgrid.py](https://localhost:8080/#) in <module>()
1654 @njit(int64[:,:](int64[:,:], UniTuple(int64, 8)),
1655 parallel=True,
-> 1656 cache=True)
1657 def _flatten_fdir_numba(fdir, dirmap):
1658 r, c = fdir.shape
[/usr/local/lib/python3.7/dist-packages/numba/core/decorators.py](https://localhost:8080/#) in wrapper(func)
216 with typeinfer.register_dispatcher(disp):
217 for sig in sigs:
--> 218 disp.compile(sig)
219 disp.disable_compile()
220 return disp
[/usr/local/lib/python3.7/dist-packages/numba/core/compiler_lock.py](https://localhost:8080/#) in _acquire_compile_lock(*args, **kwargs)
30 def _acquire_compile_lock(*args, **kwargs):
31 with self:
---> 32 return func(*args, **kwargs)
33 return _acquire_compile_lock
34
[/usr/local/lib/python3.7/dist-packages/numba/core/dispatcher.py](https://localhost:8080/#) in compile(self, sig)
817 self._cache_misses[sig] += 1
818 try:
--> 819 cres = self._compiler.compile(args, return_type)
820 except errors.ForceLiteralArg as e:
821 def folded(args, kws):
[/usr/local/lib/python3.7/dist-packages/numba/core/dispatcher.py](https://localhost:8080/#) in compile(self, args, return_type)
80 return retval
81 else:
---> 82 raise retval
83
84 def _compile_cached(self, args, return_type):
[/usr/local/lib/python3.7/dist-packages/numba/core/dispatcher.py](https://localhost:8080/#) in _compile_cached(self, args, return_type)
90
91 try:
---> 92 retval = self._compile_core(args, return_type)
93 except errors.TypingError as e:
94 self._failed_cache[key] = e
[/usr/local/lib/python3.7/dist-packages/numba/core/dispatcher.py](https://localhost:8080/#) in _compile_core(self, args, return_type)
108 args=args, return_type=return_type,
109 flags=flags, locals=self.locals,
--> 110 pipeline_class=self.pipeline_class)
111 # Check typing error if object mode is used
112 if cres.typing_error is not None and not flags.enable_pyobject:
[/usr/local/lib/python3.7/dist-packages/numba/core/compiler.py](https://localhost:8080/#) in compile_extra(typingctx, targetctx, func, args, return_type, flags, locals, library, pipeline_class)
625 pipeline = pipeline_class(typingctx, targetctx, library,
626 args, return_type, flags, locals)
--> 627 return pipeline.compile_extra(func)
628
629
[/usr/local/lib/python3.7/dist-packages/numba/core/compiler.py](https://localhost:8080/#) in compile_extra(self, func)
361 self.state.lifted = ()
362 self.state.lifted_from = None
--> 363 return self._compile_bytecode()
364
365 def compile_ir(self, func_ir, lifted=(), lifted_from=None):
[/usr/local/lib/python3.7/dist-packages/numba/core/compiler.py](https://localhost:8080/#) in _compile_bytecode(self)
423 """
424 assert self.state.func_ir is None
--> 425 return self._compile_core()
426
427 def _compile_ir(self):
[/usr/local/lib/python3.7/dist-packages/numba/core/compiler.py](https://localhost:8080/#) in _compile_core(self)
403 self.state.status.fail_reason = e
404 if is_final_pipeline:
--> 405 raise e
406 else:
407 raise CompilerError("All available pipelines exhausted")
[/usr/local/lib/python3.7/dist-packages/numba/core/compiler.py](https://localhost:8080/#) in _compile_core(self)
394 res = None
395 try:
--> 396 pm.run(self.state)
397 if self.state.cr is not None:
398 break
[/usr/local/lib/python3.7/dist-packages/numba/core/compiler_machinery.py](https://localhost:8080/#) in run(self, state)
339 (self.pipeline_name, pass_desc)
340 patched_exception = self._patch_error(msg, e)
--> 341 raise patched_exception
342
343 def dependency_analysis(self):
[/usr/local/lib/python3.7/dist-packages/numba/core/compiler_machinery.py](https://localhost:8080/#) in run(self, state)
330 pass_inst = _pass_registry.get(pss).pass_inst
331 if isinstance(pass_inst, CompilerPass):
--> 332 self._runPass(idx, pass_inst, state)
333 else:
334 raise BaseException("Legacy pass in use")
[/usr/local/lib/python3.7/dist-packages/numba/core/compiler_lock.py](https://localhost:8080/#) in _acquire_compile_lock(*args, **kwargs)
30 def _acquire_compile_lock(*args, **kwargs):
31 with self:
---> 32 return func(*args, **kwargs)
33 return _acquire_compile_lock
34
[/usr/local/lib/python3.7/dist-packages/numba/core/compiler_machinery.py](https://localhost:8080/#) in _runPass(self, index, pss, internal_state)
289 mutated |= check(pss.run_initialization, internal_state)
290 with SimpleTimer() as pass_time:
--> 291 mutated |= check(pss.run_pass, internal_state)
292 with SimpleTimer() as finalize_time:
293 mutated |= check(pss.run_finalizer, internal_state)
[/usr/local/lib/python3.7/dist-packages/numba/core/compiler_machinery.py](https://localhost:8080/#) in check(func, compiler_state)
262
263 def check(func, compiler_state):
--> 264 mangled = func(compiler_state)
265 if mangled not in (True, False):
266 msg = ("CompilerPass implementations should return True/False. "
[/usr/local/lib/python3.7/dist-packages/numba/core/typed_passes.py](https://localhost:8080/#) in run_pass(self, state)
96 state.return_type,
97 state.locals,
---> 98 raise_errors=self._raise_errors)
99 state.typemap = typemap
100 if self._raise_errors:
[/usr/local/lib/python3.7/dist-packages/numba/core/typed_passes.py](https://localhost:8080/#) in type_inference_stage(typingctx, interp, args, return_type, locals, raise_errors)
67 infer.seed_type(k, v)
68
---> 69 infer.build_constraint()
70 infer.propagate(raise_errors=raise_errors)
71 typemap, restype, calltypes = infer.unify(raise_errors=raise_errors)
[/usr/local/lib/python3.7/dist-packages/numba/core/typeinfer.py](https://localhost:8080/#) in build_constraint(self)
1022 for blk in utils.itervalues(self.blocks):
1023 for inst in blk.body:
-> 1024 self.constrain_statement(inst)
1025
1026 def return_types_from_partial(self):
[/usr/local/lib/python3.7/dist-packages/numba/core/typeinfer.py](https://localhost:8080/#) in constrain_statement(self, inst)
1366 def constrain_statement(self, inst):
1367 if isinstance(inst, ir.Assign):
-> 1368 self.typeof_assign(inst)
1369 elif isinstance(inst, ir.SetItem):
1370 self.typeof_setitem(inst)
[/usr/local/lib/python3.7/dist-packages/numba/core/typeinfer.py](https://localhost:8080/#) in typeof_assign(self, inst)
1432 value = inst.value
1433 if isinstance(value, ir.Const):
-> 1434 self.typeof_const(inst, inst.target, value.value)
1435 elif isinstance(value, ir.Var):
1436 self.constraints.append(Propagate(dst=inst.target.name,
[/usr/local/lib/python3.7/dist-packages/numba/core/typeinfer.py](https://localhost:8080/#) in typeof_const(self, inst, target, const)
1467
1468 def typeof_const(self, inst, target, const):
-> 1469 ty = self.resolve_value_type(inst, const)
1470 if inst.value.use_literal_type:
1471 lit = types.maybe_literal(value=const)
[/usr/local/lib/python3.7/dist-packages/numba/core/typeinfer.py](https://localhost:8080/#) in resolve_value_type(self, inst, val)
1458 except ValueError as e:
1459 msg = str(e)
-> 1460 raise TypingError(msg, loc=inst.loc)
1461
1462 def typeof_arg(self, inst, target, arg):
TypingError: Failed in nopython mode pipeline (step: nopython frontend)
cannot determine Numba type of <class 'frozenset'>
File "../usr/local/lib/python3.7/dist-packages/pysheds/_sgrid.py", line 1679:
def _flatten_fdir_numba(fdir, dirmap):
<source elided>
# Left boundary
if i in {5, 6, 7}:
^
`
in google colab, try: !pip install pysheds I was having an issue with numba in google colab that wasn't occuring in Jupyter notebooks. this seemed to fix it:
!pip uninstall numba -y
!pip install --pre numba
!pip install pysheds
