GH-100234: Set a default value for random.expovariate()

Doc/library/random.rst

@@ -320,14 +320,17 @@ be found in any statistics text.
    ``beta > 0``. Returned values range between 0 and 1.
 
 
-.. function:: expovariate(lambd)
+.. function:: expovariate(lambd = 1.0)
 
    Exponential distribution.  *lambd* is 1.0 divided by the desired
    mean.  It should be nonzero.  (The parameter would be called
    "lambda", but that is a reserved word in Python.)  Returned values
    range from 0 to positive infinity if *lambd* is positive, and from
    negative infinity to 0 if *lambd* is negative.
 
+   .. versionchanged:: 3.12
+      Added the default value for ``lambd``.
+
 
 .. function:: gammavariate(alpha, beta)
 

Lib/random.py

@@ -577,7 +577,7 @@ def lognormvariate(self, mu, sigma):
         """
         return _exp(self.normalvariate(mu, sigma))
 
-    def expovariate(self, lambd):
+    def expovariate(self, lambd=1.0):
         """Exponential distribution.
 
         lambd is 1.0 divided by the desired mean.  It should be

Lib/test/test_random.py

@@ -988,6 +988,7 @@ def test_zeroinputs(self):
         g.random = x[:].pop; g.uniform(1,10)
         g.random = x[:].pop; g.paretovariate(1.0)
         g.random = x[:].pop; g.expovariate(1.0)
+        g.random = x[:].pop; g.expovariate()
         g.random = x[:].pop; g.weibullvariate(1.0, 1.0)
         g.random = x[:].pop; g.vonmisesvariate(1.0, 1.0)
         g.random = x[:].pop; g.normalvariate(0.0, 1.0)

Misc/NEWS.d/next/Library/2022-12-14-11-45-38.gh-issue-100234.kn6yWV.rst

@@ -0,0 +1,2 @@
+Set a default value of 1.0 for the ``lambd`` parameter in
+random.expovariate().