remove use of attr repr_ns (#1331)

doc/long_vignettes/tskitconvert_vignette.md

@@ -158,7 +158,13 @@ We can pass the `params` object on when exporting the data to `tskit`:
 
 ```{code-cell} python
 ts = pop.dump_tables_to_tskit(model_params=params)
-recovered_params = fwdpy11.ModelParams(**eval(ts.metadata["model_params"])) 
+def rebuild_params(md):
+    import fwdpy11
+    for i in dir(fwdpy11):
+        exec(f"from fwdpy11 import {i}")
+    recovered_params = fwdpy11.ModelParams(**eval(md)) 
+    return recovered_params
+recovered_params = rebuild_params(ts.metadata["model_params"])
 assert recovered_params == params
 ```
 Note that we can recover our demographic model from the restored parameters:

fwdpy11/_types/demographic_model_citation.py

@@ -10,7 +10,7 @@
 
 @attr_class_pickle
 @attr_class_to_from_dict
-@attr.s(kw_only=True, frozen=True, auto_attribs=True, repr_ns="fwdpy11")
+@attr.s(kw_only=True, frozen=True, auto_attribs=True)
 @deprecated(reason="prefer ForwardDemesGraph")
 class DemographicModelCitation(object):
     """

fwdpy11/_types/demographic_model_details.py

@@ -15,7 +15,7 @@
 
 @attr_class_pickle
 @attr_class_to_from_dict_no_recurse
-@attr.s(kw_only=True, frozen=True, auto_attribs=True, repr_ns="fwdpy11")
+@attr.s(kw_only=True, frozen=True, auto_attribs=True)
 @deprecated(reason="prefer ForwardDemesGraph")
 class DemographicModelDetails(object):
     """

fwdpy11/_types/forward_demes_graph.py

@@ -33,7 +33,7 @@ class ForwardTimeInterval:
     end_time: int
 
 
-@attr.s(repr_ns="fwdpy11")
+@attr.s()
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
 class ForwardDemesGraph(fwdpy11._fwdpy11._ForwardDemesGraph):

fwdpy11/_types/model_params.py

@@ -34,7 +34,7 @@
 
 
 @attr_class_to_from_dict_no_recurse
-@attr.s(kw_only=True, frozen=True, slots=True, repr_ns="fwdpy11")
+@attr.s(kw_only=True, frozen=True, slots=True)
 class MutationAndRecombinationRates(object):
     """
     Stores and validates the mutation and recombination rate parameters
@@ -111,7 +111,7 @@ def validate_timings(
 
 
 @attr_class_to_from_dict_no_recurse
-@attr.s(kw_only=True, frozen=True, slots=True, repr_ns="fwdpy11")
+@attr.s(kw_only=True, frozen=True, slots=True)
 class ModelParams(object):
     """
     This class stores and validates the parameters of a simulation.

fwdpy11/_types/new_mutation_data.py

@@ -5,7 +5,7 @@
 from .._fwdpy11 import ll_NewMutationData
 
 
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11", kw_only=True)
+@attr.s(auto_attribs=True, frozen=True, kw_only=True)
 class NewMutationData(ll_NewMutationData):
     """
     Data object for :func:`fwdpy11.DiploidPopulation.add_mutation`

fwdpy11/genetic_map_unit.py

@@ -36,7 +36,7 @@ def _is_integer_if_discrete(self, attribute, value):
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class PoissonInterval(fwdpy11._fwdpy11._ll_PoissonInterval):
     """
     Generate poisson number of crossover breakpoints.
@@ -90,7 +90,7 @@ def __attrs_post_init__(self):
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class PoissonPoint(fwdpy11._fwdpy11._ll_PoissonPoint):
     """
     Generate a recombination breakpoint at a fixed position if the
@@ -149,7 +149,7 @@ def __setstate__(self, d):
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class BinomialInterval(fwdpy11._fwdpy11._ll_BinomialInterval):
     """
     Generate exactly one crossover with a given probability
@@ -202,7 +202,7 @@ def __attrs_post_init__(self):
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class BinomialPoint(fwdpy11._fwdpy11._ll_BinomialPoint):
     """
     Generate a crossover breakpoint at a fixed position with a
@@ -255,7 +255,7 @@ def __attrs_post_init__(self):
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class FixedCrossovers(fwdpy11._fwdpy11._ll_FixedCrossovers):
     """
     Generate a fixed number of crossover breakpoints.
@@ -312,7 +312,7 @@ def __attrs_post_init__(self):
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class BinomialIntervalMap(fwdpy11._fwdpy11._ll_BinomialIntervalMap):
     """
     Generate exactly one crossover with a given probability

fwdpy11/genetic_values.py

@@ -57,7 +57,7 @@ class TimingError(Exception):
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True, auto_detect=True)
 class Optimum(_ll_Optimum):
     """
     Parameters for a trait optimum.
@@ -93,10 +93,15 @@ def validate_when(self, attribute, value):
     def __attrs_post_init__(self):
         super(Optimum, self).__init__(self.optimum, self.VS, self.when)
 
+    def __repr__(self) -> str:
+        return (
+            f"fwdpy11.Optimum(optimum={self.optimum}, VS={self.VS}, when={self.when})"
+        )
+
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11", eq=False)
+@attr.s(auto_attribs=True, frozen=True, eq=False, auto_detect=True)
 class PleiotropicOptima(_ll_PleiotropicOptima):
     """
     Parameters for multiple trait optima
@@ -141,8 +146,12 @@ def __eq__(self, other):
 
         return optima_equal and VS_equal and when_equal
 
+    def __repr__(self) -> str:
+        args = f"optima={self.optima}, VS={self.VS}, when={self.when}"
+        return f"(fwdpy11.PleiotropicOptima({args}))"
+
 
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class GaussianStabilizingSelection(_ll_GaussianStabilizingSelection):
     """
     Define a mapping of phenotype-to-fitness according to a
@@ -224,7 +233,7 @@ def validate_timings(self, deme: int, demography: ForwardDemesGraph) -> None:
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class NoNoise(_ll_NoNoise):
     """
     No random effects on genetic values
@@ -241,7 +250,7 @@ def __attrs_post_init__(self):
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class GaussianNoise(_ll_GaussianNoise):
     """
     Gaussian noise added to genetic values.
@@ -269,7 +278,7 @@ def __attrs_post_init__(self):
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict_no_recurse
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class Additive(_ll_Additive):
     """
     Additive effects on genetic values.
@@ -320,7 +329,7 @@ def validate_timings(self, deme: int, demography: ForwardDemesGraph) -> None:
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict_no_recurse
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class Multiplicative(_ll_Multiplicative):
     """
     Multiplicative effects on genetic values.
@@ -371,7 +380,7 @@ def validate_timings(self, deme: int, demography: ForwardDemesGraph) -> None:
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict_no_recurse
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class GBR(_ll_GBR):
     """
     The "gene-based recessive" trait model described in Thornton et al.
@@ -411,7 +420,7 @@ def validate_timings(self, deme: int, demography: ForwardDemesGraph) -> None:
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict_no_recurse
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class AdditivePleiotropy(_ll_StrictAdditiveMultivariateEffects):
     """
     Multivariate trait values under strictly additive effects.

fwdpy11/mutation_dominance.py

@@ -29,7 +29,7 @@
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class FixedDominance(fwdpy11._fwdpy11.MutationDominance):
     """
     Fixed heterozygous effects.
@@ -48,7 +48,7 @@ def __attrs_post_init__(self):
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class ExponentialDominance(fwdpy11._fwdpy11.MutationDominance):
     """
     Exponential distribution of heterozygous effects.
@@ -69,7 +69,7 @@ def __attrs_post_init__(self):
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class UniformDominance(fwdpy11._fwdpy11.MutationDominance):
     """
     Uniform distribution of heterozygous effects.
@@ -93,7 +93,7 @@ def __attrs_post_init__(self):
 
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
-@attr.s(auto_attribs=True, frozen=True, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True)
 class LargeEffectExponentiallyRecessive(fwdpy11._fwdpy11.MutationDominance):
     """
     Large effect mutations are more recessive according to

fwdpy11/regions.py

@@ -35,7 +35,7 @@
 @region_custom_repr
 @attr_class_pickle_with_super
 @attr_class_to_from_dict
-@attr.s(auto_attribs=True, frozen=True, repr=False, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True, repr=False)
 class Region(fwdpy11._fwdpy11._ll_Region):
     """
     A genomic region, defined by half-open interval [beg, end)
@@ -85,7 +85,7 @@ def __attrs_post_init__(self):
 @region_custom_repr
 @attr_class_pickle_with_super
 @attr_class_to_from_dict_no_recurse
-@attr.s(auto_attribs=True, frozen=True, repr=False, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True, repr=False)
 class ConstantS(fwdpy11._fwdpy11._ll_ConstantS):
     """
     Mutations with fixed effect sizes
@@ -145,7 +145,7 @@ def __attrs_post_init__(self):
 @region_custom_repr
 @attr_class_pickle_with_super
 @attr_class_to_from_dict_no_recurse
-@attr.s(auto_attribs=True, frozen=True, repr=False, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True, repr=False)
 class ExpS(fwdpy11._fwdpy11._ll_ExpS):
     """
     Exponential distribution of effect sizes
@@ -207,7 +207,7 @@ def __attrs_post_init__(self):
 @region_custom_repr
 @attr_class_pickle_with_super
 @attr_class_to_from_dict_no_recurse
-@attr.s(auto_attribs=True, frozen=True, repr=False, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True, repr=False)
 class GammaS(fwdpy11._fwdpy11._ll_GammaS):
     """
     Gamma distribution of effect sizes
@@ -271,7 +271,7 @@ def __attrs_post_init__(self):
 @region_custom_repr
 @attr_class_pickle_with_super
 @attr_class_to_from_dict_no_recurse
-@attr.s(auto_attribs=True, frozen=True, repr=False, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True, repr=False)
 class GaussianS(fwdpy11._fwdpy11._ll_GaussianS):
     """
     Gaussian distribution of effect sizes
@@ -331,7 +331,7 @@ def __attrs_post_init__(self):
 @region_custom_repr
 @attr_class_pickle_with_super
 @attr_class_to_from_dict_no_recurse
-@attr.s(auto_attribs=True, frozen=True, repr=False, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True, repr=False)
 class LogNormalS(fwdpy11._fwdpy11._ll_LogNormalS):
     """
     Log-normal distribution of effect sizes.
@@ -441,7 +441,7 @@ def mv(
 @region_custom_repr
 @attr_class_pickle_with_super
 @attr_class_to_from_dict_no_recurse
-@attr.s(auto_attribs=True, frozen=True, repr=False, repr_ns="fwdpy11")
+@attr.s(auto_attribs=True, frozen=True, repr=False)
 class UniformS(fwdpy11._fwdpy11._ll_UniformS):
     """
     Uniform distrubution of effect sizes
@@ -505,7 +505,7 @@ def __attrs_post_init__(self):
 @region_custom_repr
 @attr_class_pickle_with_super
 @attr_class_to_from_dict_no_recurse
-@attr.s(eq=False, auto_attribs=True, frozen=True, repr=False, repr_ns="fwdpy11")
+@attr.s(eq=False, auto_attribs=True, frozen=True, repr=False)
 class MultivariateGaussianEffects(fwdpy11._fwdpy11._ll_MultivariateGaussianEffects):
     """
     Pleiotropic effects via a multivariate Gaussian distribution.
@@ -596,7 +596,7 @@ def __eq__(self, other):
 @region_custom_repr
 @attr_class_pickle_with_super
 @attr_class_to_from_dict_no_recurse
-@attr.s(eq=False, auto_attribs=True, frozen=True, repr=False, repr_ns="fwdpy11")
+@attr.s(eq=False, auto_attribs=True, frozen=True, repr=False)
 class mvDES(fwdpy11._fwdpy11._ll_mvDES):
     """
     General multivariate distribution of effect sizes.
@@ -631,7 +631,7 @@ def __attrs_post_init__(self):
 @region_custom_repr
 @attr_class_pickle_with_super
 @attr_class_to_from_dict_no_recurse
-@attr.s(eq=False, auto_attribs=True, frozen=True, repr=False, repr_ns="fwdpy11")
+@attr.s(eq=False, auto_attribs=True, frozen=True, repr=False)
 class DiscreteDESD(fwdpy11._fwdpy11._ll_DiscreteDESD):
     """
     Discretized distribution of effect sizes and dominance.

pyproject.toml

@@ -24,7 +24,7 @@ classifiers = [
 ]
 dynamic = ["version"]
 dependencies = [
-    "attrs >= 20.3.0, < 24.1.0",
+    "attrs >= 20.3.0",
     "numpy>=1.23.5",
     "tskit >= 0.5.6",
     "demes ~= 0.2.2",

requirements/minimal_install_requirements.txt

@@ -1,4 +1,4 @@
-attrs < 20.4
+attrs >= 20.30.0
 demes == 0.2.2
 numpy >= 1.23.5
 tskit >= 0.5.6

tests/test_metadata_roundtrips_via_simulation.py

@@ -199,8 +199,16 @@ def test_metadata_roundtrip_single_deme_sim_with_parameters(rng, pdict, pop, inc
     )
 
     provenance = json.loads(ts.provenance(0).record)
-    print(provenance["parameters"]["params_dict"])
-    params_dict = eval(provenance["parameters"]["params_dict"])
+
+    def rebuild_pdict(provenance):
+        import fwdpy11
+
+        for i in dir(fwdpy11):
+            exec(f"from fwdpy11 import {i}")
+        params_dict = eval(provenance["parameters"]["params_dict"])
+        return params_dict
+
+    params_dict = rebuild_pdict(provenance)
 
     assert params_dict == params.asdict()
     script = provenance["parameters"]["script"]

tests/test_tskit_metadata.py

@@ -59,6 +59,9 @@ def test_single_model_params(pop, pdict1):
     ts = pop.dump_tables_to_tskit(model_params=mp)
 
     # reconstruct
+    for i in dir(fwdpy11):
+        exec(f"from fwdpy11 import {i}")
+
     mp_rebuilt = fwdpy11.ModelParams(**eval(ts.metadata["model_params"]))
 
     assert mp == mp_rebuilt