I'm wondering where I find the source to show how the operator ** is implemented in Python. Can someone point me in the right direction?
The python grammar definition (from which the parser is generated using pgen), look for 'power': Gramar/Gramar
The python ast, look for 'ast_for_power': Python/ast.c
The python eval loop, look for 'BINARY_POWER': Python/ceval.c
Which calls PyNumber_Power (implemented in Objects/abstract.c):
PyObject *
PyNumber_Power(PyObject *v, PyObject *w, PyObject *z)
{
return ternary_op(v, w, z, NB_SLOT(nb_power), "** or pow()");
}
Essentially, invoke the pow slot. For long objects (the only default integer type in 3.0) this is implemented in the long_pow function Objects/longobject.c, for int objects (in the 2.x branches) it is implemented in the int_pow function Object/intobject.c
If you dig into long_pow, you can see that after vetting the arguments and doing a bit of set up, the heart of the exponentiation can be see here:
if (Py_SIZE(b) <= FIVEARY_CUTOFF) {
/* Left-to-right binary exponentiation (HAC Algorithm 14.79) */
/* http://www.cacr.math.uwaterloo.ca/hac/about/chap14.pdf */
for (i = Py_SIZE(b) - 1; i >= 0; --i) {
digit bi = b->ob_digit[i];
for (j = 1 << (PyLong_SHIFT-1); j != 0; j >>= 1) {
MULT(z, z, z)
if (bi & j)
MULT(z, a, z)
}
}
}
else {
/* Left-to-right 5-ary exponentiation (HAC Algorithm 14.82) */
Py_INCREF(z); /* still holds 1L */
table[0] = z;
for (i = 1; i < 32; ++i)
MULT(table[i-1], a, table[i])
for (i = Py_SIZE(b) - 1; i >= 0; --i) {
const digit bi = b->ob_digit[i];
for (j = PyLong_SHIFT - 5; j >= 0; j -= 5) {
const int index = (bi >> j) & 0x1f;
for (k = 0; k < 5; ++k)
MULT(z, z, z)
if (index)
MULT(z, table[index], z)
}
}
}
Which uses algorithms discussed in Chapter 14.6 of the Handbook of Applied Cryptography which describes efficient exponentiation algorithms for arbitrary precision arithmetic.
There are two different implementations one for int (long in 3.0) objects and another one for float objects.
The float pow is the float_pow(PyObject *v, PyObject *w, PyObject *z) function defined in Objects/floatobject.c file of the Python source code. This functions calls pow() from C stdlib's math.h
The int pow has its own implementation, is the function int_pow(PyIntObject *v, PyIntObject *w, PyIntObject *z) defined in Objects/intobject.c (longobject.c for 3.0) of the Python source code.
I think caseysrandomthoughts are asking about asterisks at functions definition.
You could find answer at this Python doc page: http://docs.python.org/tutorial/controlflow.html#more-on-defining-functions
When a final formal parameter of the form **name is present, it receives a dictionary containing all keyword arguments except for those corresponding to a formal parameter.
I've sow description of this stuff somewhere else at python doc but I can't to remember.
It's the power to operator
python.org doc - Power operator
Edit: Oh, dang, the code, right. Hope the link still helps. Sloppy read from my part
Related
I know that the best way to compare two floats for equality is usually to use math.isclose(float_a, float_b). But I was curious to know how python does it if you simply do float_a == float_b.
I suppose it's implemented in C, but what is the logic behind it ?
Here is the source code for float object comparisons
Essentially. It looks super complex, but that complexity is mostly in handling the case where a float is compared to an int (int objects in Python are arbitrarily sized, they aren't C-int's wrapped in a Python object).
But for the simple case of float and float:
static PyObject*
float_richcompare(PyObject *v, PyObject *w, int op)
{
double i, j;
int r = 0;
assert(PyFloat_Check(v));
i = PyFloat_AS_DOUBLE(v);
/* Switch on the type of w. Set i and j to doubles to be compared,
* and op to the richcomp to use.
*/
if (PyFloat_Check(w))
j = PyFloat_AS_DOUBLE(w);
So it just creates two C doubles from the float objects, then (skipping all the int handling stuff):
Compare:
switch (op) {
case Py_EQ:
r = i == j;
break;
case Py_NE:
r = i != j;
break;
case Py_LE:
r = i <= j;
break;
case Py_GE:
r = i >= j;
break;
case Py_LT:
r = i < j;
break;
case Py_GT:
r = i > j;
break;
}
return PyBool_FromLong(r);
It just does a C-level == comparison, ultimately. So it does not do math.isclose(float_a, float_b). underneath the hood.
As the title says: I wold like to make a python binding in C++ that does some algebraic operations on some array. For this, I have to parse the python "array object" into C++ as a vector of double or integer or whatever the case may be.
I tried to do this but I face some issues. I've created a new python type and a class with the name Typer where I have this method that tries to get the elements of a python array, then compute the sum (as a first step).
tatic PyObject *Typer_vectorsum(Typer *self, PyObject *args)
{
PyObject *retval;
PyObject *list;
if (!PyArg_ParseTuple(args, "O", &list))
return NULL;
double *arr;
arr = (double *)malloc(sizeof(double) * PyTuple_Size(list));
int length;
length = PyTuple_Size(list);
PyObject *item = NULL;
for (int i = 0; i < length; ++i)
{
item = PyTuple_GetItem(list, i);
if (!PyFloat_Check(item))
{
exit(1);
}
arr[i] = PyFloat_AsDouble(item);
}
double result = 0.0;
for (int i = 0; i < length; ++i)
{
result += arr[i];
}
retval = PyFloat_FromDouble(result);
free(arr);
return retval;
}
In this method I parse the python array object into a C array (allocating the memory of the array with malloc). Then I add every element from the object to my C array and just compute the sum in the last for-loop.
If I build the project and then create a python test file, nothing happens (the file compiles without any issues but it is not printing anything).
y = example.Typer() . #typer is the init
tuple = (1, 2, 3)
print(y.vectorsum(tuple))
Am I missing something? And also, Is there a nice and easy way of getting a python array object into C++, but as a std::vector instead of a classic C array?
Thank you in advance!
The tuple contains ints, not floats, so your PyFloat_Check fails. And no, there is no direct way from Python tuple to C array or C++ std::vector. The reason being that the tuple is an array of Python objects, not an array of C values such as doubles.
Here's your example with improved error checking, after which it should work:
PyObject *retval;
PyObject *list;
if (!PyArg_ParseTuple(args, "O!", &PyTuple_Type, &list))
return NULL;
double *arr =
arr = (double *)malloc(sizeof(double) * PyTuple_GET_SIZE(list));
int length;
length = PyTuple_GET_SIZE(list);
PyObject *item = NULL;
for (int i = 0; i < length; ++i)
{
item = PyTuple_GET_ITEM(list, i);
arr[i] = PyFloat_AsDouble(item);
if (arr[i] == -1. && PyErr_Occurred())
{
exit(1);
}
}
double result = 0.0;
for (int i = 0; i < length; ++i)
{
result += arr[i];
}
retval = PyFloat_FromDouble(result);
free(arr);
return retval;
I have a piece of python code I need to use in c++. The algorithm is a recursion that uses yield.
Here is the python function:
def getSubSequences(self, s, minLength=1):
if len(s) >= minLength:
for i in range(minLength, len(s) + 1):
for p in self.getSubSequences(s[i:], 1 if i > 1 else 2):
yield [s[:i]] + p
elif not s:
yield []
and here is my attempt so far
vector< vector<string> > getSubSequences(string number, unsigned int minLength=1) {
if (number.length() >= minLength) {
for (unsigned int i=minLength; i<=number.length()+1; i++) {
string sub = "";
if (i <= number.length())
sub = number.substr(i);
vector< vector<string> > res = getSubSequences(sub, (i > 1 ? 1 : 2));
vector< vector<string> > container;
vector<string> tmp;
tmp.push_back(number.substr(0, i));
container.push_back(tmp);
for (unsigned int j=0; j<res.size(); j++) {
container.push_back(res.at(j));
return container;
}
}
} else if (number.length() == 0)
return vector< vector<string> >();
}
Unfortunately I get a segmentation fault when executing it. Is this even the right attempt or is there an easier way to do this? The data structures are not fixed I just need the same result as I get in the python code!
The loops in your above code snippets are not equivalent.
The Python code has
for i in range(minLength, len(s) + 1):
The C++ code has
for (unsigned int i=minLength; i<=number.length()+1; i++) {
So the Python loop terminates one iteration sooner than the C++ one.
The question has really nothing to do with yield. I think you should print stuff out from implementations, in these cases, and study them. In this case, it would have shown that the two algorithms diverge.
First of all, I know that nested functions are not supported by the C standard.
However, it's often very useful, in other languages, to define an auxiliary recursive function that will make use of data provided by the outer function.
Here is an example, computing the number of solutions of the N-queens problem, in Python. It's easy to write the same in Lisp, Ada or Fortran for instance, which all allow some kind of nested function.
def queens(n):
a = list(range(n))
u = [True]*(2*n - 1)
v = [True]*(2*n - 1)
m = 0
def sub(i):
nonlocal m
if i == n:
m += 1
else:
for j in range(i, n):
p = i + a[j]
q = i + n - 1 - a[j]
if u[p] and v[q]:
u[p] = v[q] = False
a[i], a[j] = a[j], a[i]
sub(i + 1)
u[p] = v[q] = True
a[i], a[j] = a[j], a[i]
sub(0)
return m
Now my question: is there a way to do something like this in C? I would think of two solutions: using globals or passing data as parameters, but they both look rather unsatisfying.
There is also a way to write this as an iterative program, but it's clumsy:actually, I first wrote the iterative solution in Fortran 77 for Rosetta Code and then wanted to sort out this mess. Fortran 77 does not have recursive functions.
For those who wonder, the function manages the NxN board as a permutation of [0, 1 ... N-1], so that queens are alone on lines and columns. The function is looking for all permutations that are also solutions of the problem, starting to check the first column (actually nothing to check), then the second, and recursively calling itself only when the first i columns are in a valid configuration.
Of course. You need to simulate the special environment in use by your nested function, as static variables on the module level. Declare them above your nested function.
To not mess things up, you put this whole thing into a separate module.
Editor's Note: This answer was moved from the content of a question edit, it is written by the Original Poster.
Thanks all for the advice. Here is a solution using a structure passed as an argument. This is roughly equivalent to what gfortran and gnat do internally to deal with nested functions. The argument i could also be passed in the structure, by the way.
The inner function is declared static so as to help compiler optimizations. If it's not recursive, the code can then be integrated to the outer function (tested with GCC on a simple example), since the compiler knows the function will not be called from the "outside".
#include <stdio.h>
#include <stdlib.h>
struct queens_data {
int n, m, *a, *u, *v;
};
static void queens_sub(int i, struct queens_data *e) {
if(i == e->n) {
e->m++;
} else {
int p, q, j;
for(j = i; j < e->n; j++) {
p = i + e->a[j];
q = i + e->n - 1 - e->a[j];
if(e->u[p] && e->v[q]) {
int k;
e->u[p] = e->v[q] = 0;
k = e->a[i];
e->a[i] = e->a[j];
e->a[j] = k;
queens_sub(i + 1, e);
e->u[p] = e->v[q] = 1;
k = e->a[i];
e->a[i] = e->a[j];
e->a[j] = k;
}
}
}
}
int queens(int n) {
int i;
struct queens_data s;
s.n = n;
s.m = 0;
s.a = malloc((5*n - 2)*sizeof(int));
s.u = s.a + n;
s.v = s.u + 2*n - 1;
for(i = 0; i < n; i++) {
s.a[i] = i;
}
for(i = 0; i < 2*n - 1; i++) {
s.u[i] = s.v[i] = 1;
}
queens_sub(0, &s);
free(s.a);
return s.m;
}
int main() {
int n;
for(n = 1; n <= 16; n++) {
printf("%d %d\n", n, queens(n));
}
return 0;
}
I wrote same program in C++ and Python. In Python it takes unusual amount of time(Actually I did't get answer in it). Can anybody explain why is that?
C++ code:
#include<iostream>
using namespace std;
int main(){
int n = 1000000;
int *solutions = new int[n];
for (int i = 1; i <= n; i++){
solutions[i] = 0;
}
for (int v = 1; v <= n; v++){
for (int u = 1; u*v <= n; u++){
if ((3 * v>u) & (((u + v) % 4) == 0) & (((3 * v - u) % 4) == 0)){
solutions[u*v]++;
}
}
}
int count = 0;
for (int i = 1; i < n; i++){
if ((solutions[i])==10)
count += 1;
}
cout << count;
}
Python code:
n=1000000
l=[0 for x in range(n+1)]
for u in range(1,n+1):
v=1
while u*v<n+1:
if (((u+v)%4)==0) and (((3*v-u)%4)==0) and (3*v>u):
l[u*v]+=1
v+=1
l.count(10)
You can try optimizing this loop, for example make it a single block with no ifs in it, or otherwise use a module in C.
C++ compiler does optimalizations Python runtime can't, so with pure interpreter you will never get performance being anything close.
And 1M interactions is a lot, I woulnt start with any interpreter in that range, you'd be better doing it in a browser and JavaScript.