2019-02-21 in class

1st.py

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+#!/usr/bin/env python3
+# vim: set ts=4 sw=4 et tw=80:
+
+import sys
+
+def find(A, x):
+    i = 0
+    while i < len(A):
+        if A[i] == x:
+            return i
+        i = i + 1
+    return None
+
+if __name__ == "__main__":
+    A = [int(x) for x in sys.argv[1:]]
+    print(find(A[1:], A[0]))

notes.md

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+<!-- vim: set ts=2 sw=2 et tw=80: -->
+
+# Complexity
+General way to describe efficiency algorithms (linear vs exponential)
+indipendent from the computer architecture/speed.
+
+## The RAM - random-access machine
+Model of computer used in this course.
+
+Has random-access memory.
+
+### Basic types and basic operations
+Has basic types (like int, float, 64bit words). A basic step is an operation on
+a basic type (load, store, add, sub, ...). A branch is a basic step. Invoking a
+function and returning is a basic step as well, but the entire execution takes
+longer.
+
+Complexity is not measured by the input value but by the input size in bits.
+`Fibonacci(10)` in linear in `n` (size of the value) but exponential in `l`
+(number of bits in `n`, or size of the input).
+
+By default, WORST complexity is considered.
+
+## Donald Knuth's A-notation
+A(c) indicates a quantity that is absolutely at most c
+
+Antonio's weight = (pronounced "is") A(100)
+
+## (big-) O-notation
+f(n) = O(g(n))
+
+*Definition:* if f(n) is such that f(n) = k * A(g(n)) for all _n_ sufficiently
+large and for some constant k > 0, then we say that
+

pair_equal.py

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+#!/usr/bin/env python3
+# vim: set ts=4 sw=4 et tw=80:
+
+import sys
+
+def contains_two_equal(A):
+    i = 0
+    while i < len(A) - 1:
+        j = i + 1
+        while j < len(A):
+            if A[i] == A[j]:
+                return True
+            j = j + 1
+        i = i + 1
+    return False
+
+if __name__ == "__main__":
+    A = [int(x) for x in sys.argv[1:]]
+    print(contains_two_equal(A))