diff --git a/quil-py/src/waveforms.rs b/quil-py/src/waveforms.rs
index 912cfa2c..486c2345 100644
--- a/quil-py/src/waveforms.rs
+++ b/quil-py/src/waveforms.rs
@@ -109,6 +109,35 @@ impl_into_iq_values!(PyErfSquare);
 impl_repr!(PyErfSquare);
 impl_eq!(PyErfSquare);
 
+#[pymethods]
+impl PyErfSquare {
+    #[new]
+    #[allow(clippy::too_many_arguments)]
+    fn __new__(
+        duration: f64,
+        risetime: f64,
+        sample_rate: f64,
+        pad_left: f64,
+        pad_right: f64,
+        positive_polarity: bool,
+        scale: f64,
+        phase: f64,
+        detuning: f64,
+    ) -> Self {
+        PyErfSquare(ErfSquare {
+            duration,
+            risetime,
+            sample_rate,
+            pad_left,
+            pad_right,
+            positive_polarity,
+            scale,
+            phase,
+            detuning,
+        })
+    }
+}
+
 py_wrap_data_struct! {
     #[derive(Debug, PartialEq)]
     #[pyo3(subclass)]
@@ -126,6 +155,30 @@ impl_into_iq_values!(PyGaussian);
 impl_repr!(PyGaussian);
 impl_eq!(PyGaussian);
 
+#[pymethods]
+impl PyGaussian {
+    #[new]
+    fn __new__(
+        duration: f64,
+        fwhm: f64,
+        t0: f64,
+        sample_rate: f64,
+        scale: f64,
+        phase: f64,
+        detuning: f64,
+    ) -> Self {
+        PyGaussian(Gaussian {
+            duration,
+            fwhm,
+            t0,
+            sample_rate,
+            scale,
+            phase,
+            detuning,
+        })
+    }
+}
+
 py_wrap_data_struct! {
     #[derive(Debug, PartialEq)]
     #[pyo3(subclass)]
@@ -145,6 +198,35 @@ impl_into_iq_values!(PyDragGaussian);
 impl_repr!(PyDragGaussian);
 impl_eq!(PyDragGaussian);
 
+#[pymethods]
+impl PyDragGaussian {
+    #[new]
+    #[allow(clippy::too_many_arguments)]
+    fn __new__(
+        duration: f64,
+        fwhm: f64,
+        t0: f64,
+        anh: f64,
+        alpha: f64,
+        sample_rate: f64,
+        scale: f64,
+        phase: f64,
+        detuning: f64,
+    ) -> Self {
+        PyDragGaussian(DragGaussian {
+            duration,
+            fwhm,
+            t0,
+            anh,
+            alpha,
+            sample_rate,
+            scale,
+            phase,
+            detuning,
+        })
+    }
+}
+
 py_wrap_data_struct! {
     #[derive(Debug, PartialEq)]
     #[pyo3(subclass)]
@@ -164,3 +246,34 @@ py_wrap_data_struct! {
 impl_into_iq_values!(PyHermiteGaussian);
 impl_repr!(PyHermiteGaussian);
 impl_eq!(PyHermiteGaussian);
+
+#[pymethods]
+impl PyHermiteGaussian {
+    #[allow(clippy::too_many_arguments)]
+    #[new]
+    fn __new__(
+        duration: f64,
+        fwhm: f64,
+        t0: f64,
+        anh: f64,
+        alpha: f64,
+        sample_rate: f64,
+        second_order_hrm_coeff: f64,
+        scale: f64,
+        phase: f64,
+        detuning: f64,
+    ) -> Self {
+        PyHermiteGaussian(HermiteGaussian {
+            duration,
+            fwhm,
+            t0,
+            anh,
+            alpha,
+            sample_rate,
+            second_order_hrm_coeff,
+            scale,
+            phase,
+            detuning,
+        })
+    }
+}
diff --git a/quil-py/tests_py/test_waveform.py b/quil-py/tests_py/test_waveform.py
new file mode 100644
index 00000000..e7e1e354
--- /dev/null
+++ b/quil-py/tests_py/test_waveform.py
@@ -0,0 +1,24 @@
+from quil.waveforms import ErfSquare, BoxcarKernel, apply_phase_and_detuning, DragGaussian, Gaussian, HermiteGaussian
+
+
+def test_apply_phase_and_detuning():
+    iq_values = [1.0, 0.0, 1.0, 0.0]
+    apply_phase_and_detuning(iq_values, 0, 0, 44100)
+    assert iq_values == [0, 0, 0, 0]
+
+
+class TestConstrutor:
+    def test_boxcar_kernel(self):
+        BoxcarKernel(0.0, 0.0, 0.0)
+
+    def test_erf_square(self):
+        ErfSquare(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)
+
+    def test_gaussian(self):
+        Gaussian(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)
+
+    def test_drag_gaussian(self):
+        DragGaussian(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)
+
+    def test_hermite_gaussian(self):
+        DragGaussian(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)