🔧 Added sourcery config file

[s-weigand]

Added sourcery config file and added 'simplify-boolean-comparison' to ignore.
This prevents expressions like if something is True to be refactored.

Background

'if something is True' prevents bugs where something is a callable, where 'if something():' would evaluate to False but 'if something:' evaluated to true since the callable object exists.

While using this explicit syntax creates a longer instruction list, the performance impact is neglectable.

In [1]: from dis import dis

In [2]: def foo():
   ...:     var = True
   ...:     if var is True:
   ...:         return False
   ...:

In [3]: def bar():
   ...:     var = True
   ...:     if var:
   ...:         return False
   ...:

In [4]: dis(foo)
  2           0 LOAD_CONST               1 (True)
              2 STORE_FAST               0 (var)

  3           4 LOAD_FAST                0 (var)
              6 LOAD_CONST               1 (True)
              8 COMPARE_OP               8 (is)
             10 POP_JUMP_IF_FALSE       16

  4          12 LOAD_CONST               2 (False)
             14 RETURN_VALUE
        >>   16 LOAD_CONST               0 (None)
             18 RETURN_VALUE

In [5]: dis(bar)
  2           0 LOAD_CONST               1 (True)
              2 STORE_FAST               0 (var)

  3           4 LOAD_FAST                0 (var)
              6 POP_JUMP_IF_FALSE       12

  4           8 LOAD_CONST               2 (False)
             10 RETURN_VALUE
        >>   12 LOAD_CONST               0 (None)
             14 RETURN_VALUE

In [6]: %timeit foo()
117 ns ± 0.643 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)

In [7]: %timeit bar()
115 ns ± 1.36 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)

Change summary

• Added sourcery config file and added simplify-boolean-comparison to ignore

Checklist

• ✔️ Passing the tests (mandatory for all PR's)

[github-actions]

👈 Launch a binder notebook on branch s-weigand/pyglotaran/configure-sourcery

[codecov]

Codecov Report

Merging #811 (dffcac2) into staging (ae63eb4) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           staging    #811   +/-   ##
=======================================
  Coverage     84.5%   84.5%           
=======================================
  Files           75      75           
  Lines         4201    4201           
  Branches       757     757           
=======================================
  Hits          3553    3553           
  Misses         515     515           
  Partials       133     133           

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[jsnel]

👌 LGTM

[sonarqubecloud]

Kudos, SonarCloud Quality Gate passed!   

0 Bugs
0 Vulnerabilities
0 Security Hotspots
0 Code Smells

No Coverage information
0.0% Duplication

[github-actions]

Benchmark is done. Checkout the benchmark result page.
Benchmark differences below 5% might be due to CI noise.

Benchmark diff

Parametrized benchmark signatures:

BenchmarkOptimize.time_optimize(index_dependent, grouped, weight)

All benchmarks:

       before           after         ratio
     [dc00e6da]       [dffcac27]
     <v0.4.0>                   
-        43.0±1ms       32.4±0.1ms     0.75  BenchmarkOptimize.time_optimize(False, False, False)
-       245±0.8ms         37.1±1ms     0.15  BenchmarkOptimize.time_optimize(False, False, True)
-      63.6±0.2ms       53.7±0.3ms     0.84  BenchmarkOptimize.time_optimize(False, True, False)
-      65.4±0.3ms       56.9±0.3ms     0.87  BenchmarkOptimize.time_optimize(False, True, True)
         43.3±1ms       42.0±0.1ms     0.97  BenchmarkOptimize.time_optimize(True, False, False)
-         243±2ms        51.0±30ms     0.21  BenchmarkOptimize.time_optimize(True, False, True)
       63.5±0.3ms       64.6±0.4ms     1.02  BenchmarkOptimize.time_optimize(True, True, False)
       65.4±0.3ms        68.2±40ms     1.04  BenchmarkOptimize.time_optimize(True, True, True)
             182M             180M     0.99  IntegrationTwoDatasets.peakmem_create_result
             200M             195M     0.98  IntegrationTwoDatasets.peakmem_optimize
-         202±1ms          162±1ms     0.80  IntegrationTwoDatasets.time_create_result
-      4.33±0.01s       1.60±0.07s     0.37  IntegrationTwoDatasets.time_optimize

[s-weigand]

Just for reference when we need to tweak sourcery again here are the rules