Add in-memory parallel term map

- Fix parallelization by moving function call

src/api/python.rs

@@ -2424,7 +2424,7 @@ impl PythonExpression {
     }
 
     /// Map the transformations to every term in the expression.
-    /// The execution happen in parallel.
+    /// The execution happens in parallel, using `n_cores`.
     ///
     /// Examples
     /// --------
@@ -2457,30 +2457,23 @@ impl PythonExpression {
 
         // release the GIL as Python functions may be called from
         // within the term mapper
-        let mut stream = py.allow_threads(move || {
-            // map every term in the expression
-            let mut stream = TermStreamer::<CompressorWriter<_>>::new(TermStreamerConfig {
-                n_cores: n_cores.unwrap_or(1),
-                ..Default::default()
-            });
-            stream.push(self.expr.clone());
-
-            let m = stream.map(|x| {
-                let mut out = Atom::default();
-                Workspace::get_local().with(|ws| {
-                    Transformer::execute(x.as_view(), &t, ws, &mut out).unwrap_or_else(|e| {
-                        // TODO: capture and abort the parallel run
-                        panic!("Transformer failed during parallel execution: {:?}", e)
+        let r = py.allow_threads(move || {
+            self.expr.as_view().map_terms(
+                |x| {
+                    let mut out = Atom::default();
+                    Workspace::get_local().with(|ws| {
+                        Transformer::execute(x, &t, ws, &mut out).unwrap_or_else(|e| {
+                            // TODO: capture and abort the parallel run
+                            panic!("Transformer failed during parallel execution: {:?}", e)
+                        });
                     });
-                });
-                out
-            });
-            Ok::<_, PyErr>(m)
-        })?;
-
-        let b = stream.to_expression();
+                    out
+                },
+                n_cores.unwrap_or(1),
+            )
+        });
 
-        Ok(b.into())
+        Ok(r.into())
     }
 
     /// Set the coefficient ring to contain the variables in the `vars` list.

src/streaming.rs

@@ -11,7 +11,7 @@ use rayon::prelude::*;
 
 use crate::{
     atom::{Atom, AtomView},
-    state::RecycledAtom,
+    state::{RecycledAtom, Workspace},
     LicenseManager,
 };
 
@@ -460,7 +460,8 @@ impl<W: WriteableNamedStream> TermStreamer<W> {
             #[inline(always)]
             || {
                 reader.par_bridge().for_each(|x| {
-                    out_wrap.lock().unwrap().push(f(x));
+                    let r = f(x);
+                    out_wrap.lock().unwrap().push(r);
                 });
             },
         );
@@ -494,6 +495,62 @@ impl<W: WriteableNamedStream> TermStreamer<W> {
     }
 }
 
+impl<'a> AtomView<'a> {
+    /// Map the function `f` over all its terms, using parallel execution with `n_cores` cores.
+    pub fn map_terms(&self, f: impl Fn(AtomView) -> Atom + Send + Sync, n_cores: usize) -> Atom {
+        if let AtomView::Add(aa) = self {
+            if n_cores < 2 {
+                return Workspace::get_local().with(|ws| {
+                    let mut r = ws.new_atom();
+                    let rr = r.to_add();
+                    for arg in aa {
+                        rr.extend(f(arg).as_view());
+                    }
+                    let mut out = Atom::new();
+                    r.as_view().normalize(ws, &mut out);
+                    out
+                });
+            }
+
+            let out_wrap = Mutex::new(vec![]);
+
+            let t = rayon::ThreadPoolBuilder::new()
+                .num_threads(if LicenseManager::is_licensed() {
+                    n_cores
+                } else {
+                    1
+                })
+                .build()
+                .unwrap();
+
+            t.install(
+                #[inline(always)]
+                || {
+                    aa.iter().par_bridge().for_each(|x| {
+                        let r = f(x);
+                        out_wrap.lock().unwrap().push(r);
+                    });
+                },
+            );
+
+            let res = out_wrap.into_inner().unwrap();
+
+            Workspace::get_local().with(|ws| {
+                let mut r = ws.new_atom();
+                let rr = r.to_add();
+                for arg in res {
+                    rr.extend(arg.as_view());
+                }
+                let mut out = Atom::new();
+                r.as_view().normalize(ws, &mut out);
+                out
+            })
+        } else {
+            f(self.clone())
+        }
+    }
+}
+
 #[cfg(test)]
 mod test {
     use std::{fs::File, io::BufWriter};
@@ -595,4 +652,21 @@ mod test {
         let res = Atom::parse("11*v1+10*f1(v1)").unwrap();
         assert_eq!(r, res);
     }
+
+    #[test]
+    fn term_map() {
+        let input = Atom::parse("v1 + v2 + v3 + v4").unwrap();
+
+        let r = input
+            .as_view()
+            .map_terms(|x| Atom::new_num(1) + &x.to_owned(), 4);
+
+        let r2 = input
+            .as_view()
+            .map_terms(|x| Atom::new_num(1) + &x.to_owned(), 1);
+        assert_eq!(r, r2);
+
+        let res = Atom::parse("v1 + v2 + v3 + v4 + 4").unwrap();
+        assert_eq!(r, res);
+    }
 }

symbolica.pyi

@@ -625,12 +625,7 @@ class Expression:
     ) -> Expression:
         """
         Map the transformations to every term in the expression.
-        The execution happens in parallel.
-
-
-        No new functions or variables can be defined and no new
-        expressions can be parsed inside the map. Doing so will
-        result in a deadlock.
+        The execution happens in parallel using `n_cores`.
 
         Examples
         --------