Clean PythonCodePrinter and add dtype property

CHANGELOG.md

@@ -10,6 +10,8 @@ All notable changes to this project will be documented in this file.
 -   Allow interfaces in classes.
 -   Python support for a simple class.
 -   #1430 : Added conjugate support to booleans.
+-   #1260 : Add support for NumPy `dtype` property: `a.dtype`.
+-   #1260 : Add support for NumPy `result_type` function.
 
 ### Fixed
 
@@ -30,6 +32,7 @@ All notable changes to this project will be documented in this file.
 
 ### Deprecated
 
+-   Stop generating `numpy.bool` (deprecated from NumPy) in code.
 -   \[INTERNALS\] Removed `obsolete` folder.
 -   \[INTERNALS\] Removed out of date `samples` folder.
 -   \[INTERNALS\] Removed out of date `doc` folder.

ci_tools/json_pytest_output.py

@@ -18,7 +18,7 @@
 import re
 import sys
 
-def     mini_md_summary(title, outcome, c, f, py):
+def     mini_md_summary(title, outcome, failed_tests):
     """
     Generate Markdown.
 
@@ -30,12 +30,8 @@ def     mini_md_summary(title, outcome, c, f, py):
         The title of the summary.
     outcome : str
         The result of a completed step, Possible values are success, failure, cancelled, or skipped.
-    c : list
-        A list of C test summaries, (Failed tests).
-    f : list
-        A list of Fortran test summaries, (Failed tests).
-    py : list
-        A list of Python test summaries, (Failed tests).
+    failed_tests : dict
+        A dictionary whose keys are languages and whose values are lists of failed test summaries.
 
     Returns
     -------
@@ -44,21 +40,12 @@ def     mini_md_summary(title, outcome, c, f, py):
     """
     md = f"## {title} - {outcome} "
     if outcome == "failure":
-        if len(c) != 0:
-            md = md + '\n' + "### C Test summary: "
-            md = md + '\n'
-            for i in c:
-                md = md + i + "\n"
-        if len(f) != 0:
-            md = md + '\n' + "### Fortran Test summary: "
-            md = md + '\n'
-            for i in f:
-                md = md + i + "\n"
-        if len(py) != 0:
-            md = md + '\n' + "### Python Test summary: "
-            md = md + '\n'
-            for i in py:
-                md = md + i + "\n"
+        for lang, errs in failed_tests.items():
+            if len(errs) != 0:
+                md = md + '\n' + f"### {lang.capitalize()} Test summary: "
+                md = md + '\n'
+                for i in errs:
+                    md = md + i + "\n"
     md = md + "\n"
     return(md)
 
@@ -73,6 +60,10 @@ def     mini_md_summary(title, outcome, c, f, py):
     output_file = 'test_json_result.json'
     summary = ""
 
+    failed_pattern = re.compile(r".*FAILED.*")
+    languages = ('c', 'fortran', 'python')
+    pattern = {lang: re.compile(r".*\["+lang+r"\]\ \_.*") for lang in languages}
+
     for i in p_args.tests:
         values = i.split(':')
         mini_title = values[0] if len(values) >= 1 else None
@@ -86,28 +77,18 @@ def     mini_md_summary(title, outcome, c, f, py):
             c_tests = []
             f_tests = []
             py_tests = []
-            failed_pattern = r".*FAILED.*"
-            c_pattern = r".*\[c\].*"
-            f_pattern = r".*\[fortran\]\ \_.*"
-            py_pattern = r".*\[python\]\ \_.*"
 
-            failed_matches = re.findall(failed_pattern, outfile, re.MULTILINE)
+            failed_matches = failed_pattern.findall(outfile, re.MULTILINE)
             failed_matches = [re.sub(r'.*FAILED ', "- ``", string) for string in failed_matches]
 
-            r = re.compile(c_pattern)
-            c_failed = list(filter(r.match, failed_matches))
-            c_failed = [re.sub(r'\[c\]', "`` :heavy_multiplication_x:", string) for string in c_failed]
-
-            failed_matches = re.findall(f_pattern, outfile, re.MULTILINE)
-            failed_matches = ["- ``" + string.strip('_') for string in failed_matches]
-            f_failed = [re.sub(r'\[fortran\]', "`` :heavy_multiplication_x:", string) for string in failed_matches]
-
-            failed_matches = re.findall(py_pattern, outfile, re.MULTILINE)
-            failed_matches = ["- ``" + string.strip('_') for string in failed_matches]
-            py_failed = [re.sub(r'\[python\]', "`` :heavy_multiplication_x:", string) for string in failed_matches]
+            fails = {}
 
+            for lang in languages:
+                failed_matches = pattern[lang].findall(outfile, re.MULTILINE)
+                failed_matches = ["- ``" + string.strip('_') for string in failed_matches]
+                fails[lang] = [re.sub(r'\['+lang+r'\]', "`` :heavy_multiplication_x:", string) for string in failed_matches]
 
-        summary = summary + mini_md_summary(mini_title, outcome, c_failed, f_failed, py_failed)
+        summary = summary + mini_md_summary(mini_title, outcome, fails)
 
     print(summary)
     json_ouput = {

docs/numpy-functions.md

@@ -570,6 +570,6 @@ In Pyccel we try to support the NumPy functions which developers use the most..
 
 -   others:
 
-    -   `amax`, `amin`, `sum`, `shape`, `size`, `floor`, `sign`
+    -   `amax`, `amin`, `sum`, `shape`, `size`, `floor`, `sign`, `result_type`
 
 If discrepancies beyond round-off error are found between [NumPy](https://numpy.org/doc/stable/reference/)'s and [Pyccel](https://github.com/pyccel/pyccel)'s results, please create an issue at <https://github.com/pyccel/pyccel/issues> and provide a small example of your problem. Do not forget to specify your target language.

pyccel/ast/class_defs.py

@@ -11,17 +11,17 @@
                         NativeComplex, NativeString, NativeNumeric)
 from .numpyext  import (NumpyShape, NumpySum, NumpyAmin, NumpyAmax,
                         NumpyImag, NumpyReal, NumpyTranspose,
-                        NumpyConjugate, NumpySize)
+                        NumpyConjugate, NumpySize, NumpyResultType)
 
 __all__ = ('BooleanClass',
         'IntegerClass',
         'RealClass',
         'ComplexClass',
         'StringClass',
         'NumpyArrayClass',
         'TupleClass',
         'literal_classes',
         'get_cls_base')
 
 #=======================================================================================
 
@@ -158,7 +158,9 @@
             PyccelFunctionDef('conj', func_class = NumpyConjugate,
                 decorators = {'numpy_wrapper': 'numpy_wrapper'}),
             PyccelFunctionDef('conjugate', func_class = NumpyConjugate,
-                decorators = {'numpy_wrapper': 'numpy_wrapper'})
+                decorators = {'numpy_wrapper': 'numpy_wrapper'}),
+            PyccelFunctionDef('dtype', func_class = NumpyResultType,
+                decorators = {'property': 'property', 'numpy_wrapper': 'numpy_wrapper'}),
         ]
 )
 

pyccel/ast/cwrapper.py

@@ -29,27 +29,27 @@
 
 errors = Errors()
 
 __all__ = (
 #
 # --------- CLASSES -----------
 #
     'PyccelPyObject',
     'PyArgKeywords',
     'PyArg_ParseTupleNode',
     'PyBuildValueNode',
     'PyModule_AddObject',
 #--------- CONSTANTS ----------
     'Py_True',
     'Py_False',
     'Py_None',
     'flags_registry',
 #----- C / PYTHON FUNCTIONS ---
     'Py_DECREF',
     'set_python_error_message',
 #----- CHECK FUNCTIONS ---
     'generate_datatype_error',
     'scalar_object_check',
 )
 
 #-------------------------------------------------------------------
 #                        Python DataTypes
@@ -108,7 +108,7 @@
     (NativeFloat(), 4)         : 'f',
     (NativeComplex(), 4)       : 'O',
     (NativeComplex(), 8)       : 'O',
-    (NativeBool(), 4)          : 'p',
+    (NativeBool(), -1)         : 'p',
     (NativeString(), 0)        : 's',
     (PyccelPyObject(), 0)      : 'O',
     }
@@ -366,7 +366,7 @@
 
 # Functions definitions are defined in pyccel/stdlib/cwrapper/cwrapper.c
 py_to_c_registry = {
-    (NativeBool(), 4)      : 'PyBool_to_Bool',
+    (NativeBool(), -1)     : 'PyBool_to_Bool',
     (NativeInteger(), 1)   : 'PyInt8_to_Int8',
     (NativeInteger(), 2)   : 'PyInt16_to_Int16',
     (NativeInteger(), 4)   : 'PyInt32_to_Int32',
@@ -412,7 +412,6 @@
 # Functions definitions are defined in pyccel/stdlib/cwrapper/cwrapper.c
 c_to_py_registry = {
     (NativeBool(), -1)     : 'Bool_to_PyBool',
-    (NativeBool(), 4)      : 'Bool_to_PyBool',
     (NativeInteger(), -1)  : 'Int'+str(default_precision['int']*8)+'_to_PyLong',
     (NativeInteger(), 1)   : 'Int8_to_NumpyLong',
     (NativeInteger(), 2)   : 'Int16_to_NumpyLong',
@@ -510,7 +509,6 @@
 # Functions definitions are defined in pyccel/stdlib/cwrapper/cwrapper.c
 check_type_registry = {
     (NativeBool(), -1)     : 'PyIs_Bool',
-    (NativeBool(), 4)      : 'PyIs_Bool',
     (NativeInteger(), -1)  : 'PyIs_NativeInt',
     (NativeInteger(), 1)   : 'PyIs_Int8',
     (NativeInteger(), 2)   : 'PyIs_Int16',

pyccel/ast/datatypes.py

@@ -15,50 +15,50 @@
 
 # TODO [YG, 12.03.2020] verify why we need all these types
 # NOTE: symbols not used in pyccel are commented out
 __all__ = (
 #
 # --------- CLASSES -----------
 #
     'CustomDataType',
     'DataType',
     'NativeBool',
     'NativeComplex',
     'NativeGeneric',
     'NativeInteger',
     'NativeTuple',
     'NativeNil',
     'NativeRange',
     'NativeFloat',
     'NativeString',
     'NativeSymbol',
     'NativeVoid',
     'UnionType',
     'DataTypeFactory',
 #
 # --------- FUNCTIONS -----------
 #
     'datatype',
     'is_iterable_datatype',
     'is_pyccel_datatype',
     'is_with_construct_datatype',
     'str_dtype',
 #
 # --------- VARIABLES -----------
 #
     'Bool',
     'Cmplx',
     'Generic',
     'Int',
     'Nil',
     'Float',
     'String',
     'Void',
 	'NativeNumeric',
 #    '_Symbol',
     'default_precision',
     'dtype_and_precision_registry',
     'dtype_registry'
 )
 
 #==============================================================================
 iso_c_binding = {
@@ -77,7 +77,7 @@
         8  : 'C_DOUBLE_COMPLEX',
         16 : 'C_LONG_DOUBLE_COMPLEX'},
     "logical" : {
-        4  : "C_BOOL"}
+        -1 : "C_BOOL"}
 }
 iso_c_binding_shortcut_mapping = {
     'C_INT8_T'              : 'i8',
@@ -91,31 +91,40 @@
     'C_FLOAT_COMPLEX'       : 'c32',
     'C_DOUBLE_COMPLEX'      : 'c64',
     'C_LONG_DOUBLE_COMPLEX' : 'c128',
-    'C_BOOL'                : 'b4'
+    'C_BOOL'                : 'b1'
 }
 default_precision = {'float': 8,
                     'int': numpy.dtype(int).alignment,
                     'integer': numpy.dtype(int).alignment,
                     'complex': 8,
-                    'bool':4}
+                    'bool':-1}
 dtype_and_precision_registry = { 'float':('float', -1),
                                  'double':('float', -1),
                                  'real':('float', -1),
                                  'pythonfloat':('float', -1), # built-in float
                                  'float32':('float',4),
                                  'float64':('float',8),
+                                 'f4':('float',4),
+                                 'f8':('float',8),
                                  'pythoncomplex':('complex', -1),
                                  'complex':('complex', -1),  # to create numpy array with dtype='complex'
                                  'complex64':('complex',4),
                                  'complex128':('complex',8),
+                                 'c8':('complex',4),
+                                 'c16':('complex',8),
                                  'int8' :('int',1),
                                  'int16':('int',2),
                                  'int32':('int',4),
                                  'int64':('int',8),
+                                 'i1' :('int',1),
+                                 'i2':('int',2),
+                                 'i4':('int',4),
+                                 'i8':('int',8),
                                  'int'  :('int', -1),
                                  'pythonint'  :('int', -1),
                                  'integer':('int',-1),
                                  'bool' :('bool',-1),
+                                 'b1' :('bool',-1),
                                  'pythonbool' :('bool',-1)}
 
 

pyccel/ast/numpy_wrapper.py

@@ -28,20 +28,20 @@
 
 errors = Errors()
 
 __all__ = (
     #------- CAST FUNCTIONS ------
     'pyarray_to_ndarray',
     #-------CHECK FUNCTIONS ------
     'array_type_check',
     'scalar_type_check',
     #-------HELPERS ------
     'array_get_dim',
     'array_get_data',
     'array_get_c_step',
     'array_get_f_step',
     #-------OTHERS--------
     'get_numpy_max_acceptable_version_file'
 )
 
 #-------------------------------------------------------------------
 #                      Numpy functions
@@ -181,7 +181,7 @@
         4 : np.dtype(np.int32).num,
         8 : np.dtype(np.int64).num}
 
-numpy_dtype_registry = {('bool',4)     : numpy_bool_type,
+numpy_dtype_registry = {('bool',-1)    : numpy_bool_type,
                         ('int',1)      : numpy_num_to_type[numpy_int_type_precision_map[1]],
                         ('int',2)      : numpy_num_to_type[numpy_int_type_precision_map[2]],
                         ('int',4)      : numpy_num_to_type[numpy_int_type_precision_map[4]],