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IDEA-CR-52512: PY-26541 Fix formatting in data view panel
GitOrigin-RevId: ddcb33ebe7ad16c46def53c0cfd40e3bbcd27c77
This commit is contained in:
Andrey Lisin
committed by
intellij-monorepo-bot
intellij-monorepo-bot
parent
34ea8fb853
commit
4e5852d366
@@ -1238,7 +1238,7 @@ class InternalGetArray(InternalThreadCommand):
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try:
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frame = pydevd_vars.find_frame(self.thread_id, self.frame_id)
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var = pydevd_vars.eval_in_context(self.name, frame.f_globals, frame.f_locals)
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xml = pydevd_vars.table_like_struct_to_xml(var, self.name, self.roffset, self.coffset, self.rows, self.cols, self.format )
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xml = pydevd_vars.table_like_struct_to_xml(var, self.name, self.roffset, self.coffset, self.rows, self.cols, self.format)
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cmd = dbg.cmd_factory.make_get_array_message(self.sequence, xml)
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dbg.writer.add_command(cmd)
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except:
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@@ -76,6 +76,8 @@ IS_MACOS = sys.platform == 'darwin'
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IS_PYTHON_STACKLESS = "stackless" in sys.version.lower()
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CYTHON_SUPPORTED = False
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NUMPY_NUMERIC_TYPES = "biufc"
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try:
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import platform
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python_implementation = platform.python_implementation()
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@@ -11,9 +11,10 @@ from _pydev_bundle import pydev_log
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from _pydevd_bundle import pydevd_extension_utils
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from _pydevd_bundle import pydevd_resolver
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from _pydevd_bundle.pydevd_constants import dict_iter_items, dict_keys, IS_PY3K, \
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BUILTINS_MODULE_NAME, MAXIMUM_VARIABLE_REPRESENTATION_SIZE, RETURN_VALUES_DICT, LOAD_VALUES_POLICY, ValuesPolicy, DEFAULT_VALUES_DICT
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BUILTINS_MODULE_NAME, MAXIMUM_VARIABLE_REPRESENTATION_SIZE, RETURN_VALUES_DICT, LOAD_VALUES_POLICY, ValuesPolicy, DEFAULT_VALUES_DICT, \
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NUMPY_NUMERIC_TYPES
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from _pydevd_bundle.pydevd_extension_api import TypeResolveProvider, StrPresentationProvider
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from _pydevd_bundle.pydevd_vars import get_label, array_default_format, MAXIMUM_ARRAY_SIZE
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from _pydevd_bundle.pydevd_vars import get_label, array_default_format, is_able_to_format_number, MAXIMUM_ARRAY_SIZE
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from pydev_console.protocol import DebugValue, GetArrayResponse, ArrayData, ArrayHeaders, ColHeader, RowHeader, \
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UnsupportedArrayTypeException, ExceedingArrayDimensionsException
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from _pydevd_bundle.pydevd_utils import take_first_n_coll_elements
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@@ -280,7 +281,7 @@ def frame_vars_to_struct(frame_f_locals, hidden_ns=None):
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return return_values + values
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def var_to_struct(val, name, do_trim=True, evaluate_full_value=True):
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def var_to_struct(val, name, format='%s', do_trim=True, evaluate_full_value=True):
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""" single variable or dictionary to Thrift struct representation """
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debug_value = DebugValue()
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@@ -317,7 +318,7 @@ def var_to_struct(val, name, do_trim=True, evaluate_full_value=True):
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else:
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value = '%s: %s' % (str(v.__class__, v))
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else:
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value = str(v)
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value = format % v
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else:
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value = str(v)
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except:
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@@ -362,8 +363,8 @@ def var_to_struct(val, name, do_trim=True, evaluate_full_value=True):
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return debug_value
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def var_to_str(val, do_trim=True, evaluate_full_value=True):
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struct = var_to_struct(val, '', do_trim, evaluate_full_value)
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def var_to_str(val, format, do_trim=True, evaluate_full_value=True):
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struct = var_to_struct(val, '', format, do_trim, evaluate_full_value)
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value = struct.value
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return value if value is not None else ''
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@@ -413,7 +414,7 @@ def array_to_thrift_struct(array, name, roffset, coffset, rows, cols, format):
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value = array[row][col]
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return value
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array_chunk.data = array_data_to_thrift_struct(rows, cols, lambda r: (get_value(r, c) for c in range(cols)))
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array_chunk.data = array_data_to_thrift_struct(rows, cols, lambda r: (get_value(r, c) for c in range(cols)), format)
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return array_chunk
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@@ -472,13 +473,13 @@ def array_to_meta_thrift_struct(array, name, format):
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slice += reslice
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bounds = (0, 0)
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if type in "biufc":
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if type in NUMPY_NUMERIC_TYPES:
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bounds = (array.min(), array.max())
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array_chunk = GetArrayResponse()
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array_chunk.slice = slice
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array_chunk.rows = rows
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array_chunk.cols = cols
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array_chunk.format = format
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array_chunk.format = "%" + format
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array_chunk.type = type
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array_chunk.max = "%s" % bounds[1]
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array_chunk.min = "%s" % bounds[0]
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@@ -504,10 +505,23 @@ def dataframe_to_thrift_struct(df, name, roffset, coffset, rows, cols, format):
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array_chunk.slice = name
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array_chunk.rows = num_rows
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array_chunk.cols = num_cols
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array_chunk.format = ""
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array_chunk.type = ""
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array_chunk.max = "0"
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array_chunk.min = "0"
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format = format.replace("%", "")
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if not format:
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if num_rows > 0 and num_cols == 1: # series or data frame with one column
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try:
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kind = df.dtype.kind
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except AttributeError:
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try:
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kind = df.dtypes[0].kind
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except IndexError:
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kind = "O"
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format = array_default_format(kind)
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else:
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format = array_default_format("f")
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array_chunk.format = "%" + format
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if (rows, cols) == (-1, -1):
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rows, cols = num_rows, num_cols
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@@ -521,7 +535,7 @@ def dataframe_to_thrift_struct(df, name, roffset, coffset, rows, cols, format):
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for col in range(cols):
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dtype = df.dtypes.iloc[coffset + col].kind
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dtypes[col] = dtype
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if dtype in "biufc":
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if dtype in NUMPY_NUMERIC_TYPES:
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cvalues = df.iloc[:, coffset + col]
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bounds = (cvalues.min(), cvalues.max())
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else:
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@@ -530,33 +544,32 @@ def dataframe_to_thrift_struct(df, name, roffset, coffset, rows, cols, format):
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else:
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dtype = df.dtype.kind
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dtypes[0] = dtype
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col_bounds[0] = (df.min(), df.max()) if dtype in "biufc" else (0, 0)
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col_bounds[0] = (df.min(), df.max()) if dtype in NUMPY_NUMERIC_TYPES else (0, 0)
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df = df.iloc[roffset: roffset + rows, coffset: coffset + cols] if dim > 1 else df.iloc[roffset: roffset + rows]
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rows = df.shape[0]
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cols = df.shape[1] if dim > 1 else 1
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format = format.replace('%', '')
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def col_to_format(c):
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return format if dtypes[c] == 'f' and format else array_default_format(dtypes[c])
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return format if dtypes[c] in NUMPY_NUMERIC_TYPES and format else array_default_format(dtypes[c])
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iat = df.iat if dim == 1 or len(df.columns.unique()) == len(df.columns) else df.iloc
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array_chunk.headers = header_data_to_thrift_struct(rows, cols, dtypes, col_bounds, col_to_format, df, dim)
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array_chunk.data = array_data_to_thrift_struct(rows, cols,
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lambda r: (("%" + col_to_format(c)) % (iat[r, c] if dim > 1 else iat[r])
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for c in range(cols)))
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for c in range(cols)), format)
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return array_chunk
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def array_data_to_thrift_struct(rows, cols, get_row):
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def array_data_to_thrift_struct(rows, cols, get_row, format):
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array_data = ArrayData()
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array_data.rows = rows
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array_data.cols = cols
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# `ArrayData.data`
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data = []
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for row in range(rows):
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data.append([var_to_str(value) for value in get_row(row)])
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data.append([var_to_str(value, format) for value in get_row(row)])
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array_data.data = data
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return array_data
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@@ -598,6 +611,7 @@ def table_like_struct_to_thrift_struct(array, name, roffset, coffset, rows, cols
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The `array` might be either `numpy.ndarray`, `pandas.DataFrame` or `pandas.Series`.
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"""
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_, type_name, _ = get_type(array)
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format = format if is_able_to_format_number(format) else '%'
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if type_name in TYPE_TO_THRIFT_STRUCT_CONVERTERS:
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return TYPE_TO_THRIFT_STRUCT_CONVERTERS[type_name](array, name, roffset, coffset, rows, cols, format)
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else:
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@@ -1,12 +1,12 @@
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""" pydevd_vars deals with variables:
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resolution/conversion to XML.
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"""
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import math
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import pickle
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from _pydevd_bundle.pydevd_constants import get_frame, get_current_thread_id, xrange
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from _pydev_imps._pydev_saved_modules import thread
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from _pydevd_bundle.pydevd_constants import get_frame, get_current_thread_id, xrange
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from _pydev_bundle.pydev_imports import quote
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from _pydevd_bundle.pydevd_constants import get_frame, get_current_thread_id, xrange, NUMPY_NUMERIC_TYPES
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from _pydevd_bundle.pydevd_custom_frames import get_custom_frame
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from _pydevd_bundle.pydevd_xml import ExceptionOnEvaluate, get_type, var_to_xml
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@@ -516,7 +516,7 @@ def array_to_xml(array, name, roffset, coffset, rows, cols, format):
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else:
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value = array[row][col]
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return value
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xml += array_data_to_xml(rows, cols, lambda r: (get_value(r, c) for c in range(cols)))
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xml += array_data_to_xml(rows, cols, lambda r: (get_value(r, c) for c in range(cols)), format)
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return xml
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@@ -579,7 +579,7 @@ def array_to_meta_xml(array, name, format):
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slice += reslice
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bounds = (0, 0)
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if type in "biufc":
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if type in NUMPY_NUMERIC_TYPES:
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bounds = (array.min(), array.max())
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return array, slice_to_xml(slice, rows, cols, format, type, bounds), rows, cols, format
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@@ -612,7 +612,22 @@ def dataframe_to_xml(df, name, roffset, coffset, rows, cols, format):
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dim = len(df.axes)
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num_rows = df.shape[0]
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num_cols = df.shape[1] if dim > 1 else 1
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xml = slice_to_xml(name, num_rows, num_cols, "", "", (0, 0))
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format = format.replace('%', '')
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if not format:
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if num_rows > 0 and num_cols == 1: # series or data frame with one column
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try:
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kind = df.dtype.kind
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except AttributeError:
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try:
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kind = df.dtypes[0].kind
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except IndexError:
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kind = 'O'
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format = array_default_format(kind)
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else:
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format = array_default_format('f')
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xml = slice_to_xml(name, num_rows, num_cols, format, "", (0, 0))
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if (rows, cols) == (-1, -1):
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rows, cols = num_rows, num_cols
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@@ -626,7 +641,7 @@ def dataframe_to_xml(df, name, roffset, coffset, rows, cols, format):
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for col in range(cols):
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dtype = df.dtypes.iloc[coffset + col].kind
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dtypes[col] = dtype
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if dtype in "biufc":
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if dtype in NUMPY_NUMERIC_TYPES:
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cvalues = df.iloc[:, coffset + col]
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bounds = (cvalues.min(), cvalues.max())
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else:
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@@ -635,36 +650,35 @@ def dataframe_to_xml(df, name, roffset, coffset, rows, cols, format):
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else:
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dtype = df.dtype.kind
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dtypes[0] = dtype
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col_bounds[0] = (df.min(), df.max()) if dtype in "biufc" else (0, 0)
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col_bounds[0] = (df.min(), df.max()) if dtype in NUMPY_NUMERIC_TYPES else (0, 0)
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df = df.iloc[roffset: roffset + rows, coffset: coffset + cols] if dim > 1 else df.iloc[roffset: roffset + rows]
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rows = df.shape[0]
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cols = df.shape[1] if dim > 1 else 1
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format = format.replace('%', '')
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def col_to_format(c):
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return format if dtypes[c] == 'f' and format else array_default_format(dtypes[c])
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return format if dtypes[c] in NUMPY_NUMERIC_TYPES and format else array_default_format(dtypes[c])
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iat = df.iat if dim == 1 or len(df.columns.unique()) == len(df.columns) else df.iloc
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xml += header_data_to_xml(rows, cols, dtypes, col_bounds, col_to_format, df, dim)
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xml += array_data_to_xml(rows, cols, lambda r: (("%" + col_to_format(c)) % (iat[r, c] if dim > 1 else iat[r])
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for c in range(cols)))
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for c in range(cols)), format)
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return xml
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def array_data_to_xml(rows, cols, get_row):
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def array_data_to_xml(rows, cols, get_row, format):
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xml = "<arraydata rows=\"%s\" cols=\"%s\"/>\n" % (rows, cols)
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for row in range(rows):
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xml += "<row index=\"%s\"/>\n" % to_string(row)
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for value in get_row(row):
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xml += var_to_xml(value, '')
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xml += var_to_xml(value, '', format=format)
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return xml
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def slice_to_xml(slice, rows, cols, format, type, bounds):
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return '<array slice=\"%s\" rows=\"%s\" cols=\"%s\" format=\"%s\" type=\"%s\" max=\"%s\" min=\"%s\"/>' % \
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(slice, rows, cols, format, type, bounds[1], bounds[0])
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(slice, rows, cols, quote(format), type, bounds[1], bounds[0])
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def header_data_to_xml(rows, cols, dtypes, col_bounds, col_to_format, df, dim):
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@@ -680,11 +694,21 @@ def header_data_to_xml(rows, cols, dtypes, col_bounds, col_to_format, df, dim):
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xml += "</headerdata>\n"
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return xml
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def is_able_to_format_number(format):
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try:
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format % math.pi
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except Exception:
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return False
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return True
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TYPE_TO_XML_CONVERTERS = {"ndarray": array_to_xml, "DataFrame": dataframe_to_xml, "Series": dataframe_to_xml}
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def table_like_struct_to_xml(array, name, roffset, coffset, rows, cols, format):
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_, type_name, _ = get_type(array)
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format = format if is_able_to_format_number(format) else '%'
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if type_name in TYPE_TO_XML_CONVERTERS:
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return "<xml>%s</xml>" % TYPE_TO_XML_CONVERTERS[type_name](array, name, roffset, coffset, rows, cols, format)
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else:
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@@ -290,7 +290,7 @@ def frame_vars_to_xml(frame_f_locals, hidden_ns=None):
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return return_values_xml + xml
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def var_to_xml(val, name, doTrim=True, additional_in_xml='', evaluate_full_value=True):
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def var_to_xml(val, name, doTrim=True, additional_in_xml='', evaluate_full_value=True, format='%s'):
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""" single variable or dictionary to xml representation """
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try:
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@@ -338,7 +338,7 @@ def var_to_xml(val, name, doTrim=True, additional_in_xml='', evaluate_full_value
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except:
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cName = str(v.__class__)
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value = '%s: %s' % (cName, v)
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value = ('%s: ' + format) % (cName, v)
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else:
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value = str(v)
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except:
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@@ -1,7 +1,7 @@
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import pandas as pd
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import numpy as np
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frame = pd.DataFrame(data=np.random.randint(0, high=10, size=(4, 2)), columns=['a', 'b'], index=pd.MultiIndex([['s', 'd'], [2, 3]], [[0, 0, 1, 1], [0, 1, 0, 1]]))
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frame = pd.DataFrame(data=np.arange(8, dtype='f').reshape((4, 2)), columns=['a', 'b'], index=pd.MultiIndex([['s', 'd'], [2, 3]], [[0, 0, 1, 1], [0, 1, 0, 1]]))
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series = frame.a
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@@ -54,8 +54,8 @@ public class PythonDataViewerTest extends PyEnvTestCase {
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doTest("df3", 7, 3, arrayChunk -> {
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ArrayChunk.ColHeader header = arrayChunk.getColHeaders().get(2);
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assertEquals("Sales", header.getLabel());
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assertEquals(16, (int)Integer.valueOf(header.getMax()));
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assertEquals(1, (int)Integer.valueOf(header.getMin()));
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assertEquals(16, Float.valueOf(header.getMax()).intValue());
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assertEquals(1, Float.valueOf(header.getMin()).intValue());
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});
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}
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});
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@@ -96,14 +96,47 @@ public class PythonDataViewerTest extends PyEnvTestCase {
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ImmutableSet.of(7)) {
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@Override
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public void testing() throws Exception {
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doTest("c", 10, 2, arrayChunk -> {
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doTest("c", 10, 2, (varName, session) -> getChunk(varName, "%d", session), arrayChunk -> {
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for (ArrayChunk.ColHeader header : arrayChunk.getColHeaders())
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assertEquals("A", header.getLabel());
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Object[][] data = arrayChunk.getData();
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assertEquals("0", data[0][0].toString());
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assertEquals("0", data[0][1].toString());
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assertEquals("6", data[6][0].toString());
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assertEquals("9", data[9][0].toString());
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assertEquals("'0'", data[0][0].toString());
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assertEquals("'0'", data[0][1].toString());
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assertEquals("'6'", data[6][0].toString());
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assertEquals("'9'", data[9][0].toString());
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});
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}
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});
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}
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@Test
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@Staging
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public void testDataFrameFormatting() {
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runPythonTest(new PyDataFrameDebuggerTask(getRelativeTestDataPath(), "test_dataframe.py", ImmutableSet.of(7)) {
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@Override
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public void testing() throws Exception {
|
||||
doTest("df1", 3, 5, (varName, session) -> getChunk(varName, "%.2f", session), arrayChunk -> {
|
||||
Object[][] data = arrayChunk.getData();
|
||||
assertEquals("'1.10'", data[0][1].toString());
|
||||
assertEquals("'1.20'", data[0][2].toString());
|
||||
assertEquals("'1.22'", data[1][4].toString());
|
||||
});
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
@Test
|
||||
@Staging
|
||||
public void testSeriesFormatting() {
|
||||
runPythonTest(new PyDataFrameDebuggerTask(getRelativeTestDataPath(), "test_series.py", ImmutableSet.of(7)) {
|
||||
@Override
|
||||
public void testing() throws Exception {
|
||||
doTest("series", 4, 1, (varName, session) -> getChunk(varName, "%03d", session), arrayChunk -> {
|
||||
Object[][] data = arrayChunk.getData();
|
||||
assertEquals("'000'", data[0][0].toString());
|
||||
assertEquals("'002'", data[1][0].toString());
|
||||
assertEquals("'004'", data[2][0].toString());
|
||||
assertEquals("'006'", data[3][0].toString());
|
||||
});
|
||||
}
|
||||
});
|
||||
@@ -113,6 +146,11 @@ public class PythonDataViewerTest extends PyEnvTestCase {
|
||||
|
||||
private final Set<Integer> myLines;
|
||||
|
||||
@FunctionalInterface
|
||||
private interface ChunkSupplier {
|
||||
ArrayChunk supply(String varName, XDebugSession session) throws PyDebuggerException;
|
||||
}
|
||||
|
||||
PyDataFrameDebuggerTask(@Nullable String relativeTestDataPath, String scriptName, Set<Integer> lines) {
|
||||
super(relativeTestDataPath, scriptName);
|
||||
myLines = lines;
|
||||
@@ -125,13 +163,18 @@ public class PythonDataViewerTest extends PyEnvTestCase {
|
||||
|
||||
protected void doTest(String name, int expectedRows, int expectedColumns, @Nullable Consumer<ArrayChunk> test)
|
||||
throws InterruptedException, PyDebuggerException {
|
||||
waitForPause();
|
||||
ArrayChunk arrayChunk = getDefaultChunk(name, mySession);
|
||||
testShape(arrayChunk, expectedRows, expectedColumns);
|
||||
if (test != null) {
|
||||
test.consume(arrayChunk);
|
||||
}
|
||||
resume();
|
||||
doTest(name, expectedRows, expectedColumns, PythonDataViewerTest::getDefaultChunk, test);
|
||||
}
|
||||
|
||||
protected void doTest(String name, int expectedRows, int expectedColumns, @NotNull ChunkSupplier getChunk,
|
||||
@Nullable Consumer<ArrayChunk> test) throws InterruptedException, PyDebuggerException {
|
||||
waitForPause();
|
||||
ArrayChunk arrayChunk = getChunk.supply(name, mySession);
|
||||
testShape(arrayChunk, expectedRows, expectedColumns);
|
||||
if (test != null) {
|
||||
test.consume(arrayChunk);
|
||||
}
|
||||
resume();
|
||||
}
|
||||
|
||||
@Override
|
||||
@@ -149,8 +192,12 @@ public class PythonDataViewerTest extends PyEnvTestCase {
|
||||
}
|
||||
|
||||
private static ArrayChunk getDefaultChunk(String varName, XDebugSession session) throws PyDebuggerException {
|
||||
return getChunk(varName, "%.5f", session);
|
||||
}
|
||||
|
||||
private static ArrayChunk getChunk(String varName, String format, XDebugSession session) throws PyDebuggerException {
|
||||
PyDebugValue dbgVal = (PyDebugValue)XDebuggerTestUtil.evaluate(session, varName).first;
|
||||
return dbgVal.getFrameAccessor().getArrayItems(dbgVal, 0, 0, -1, -1, ".%5f");
|
||||
return dbgVal.getFrameAccessor().getArrayItems(dbgVal, 0, 0, -1, -1, format);
|
||||
}
|
||||
|
||||
private static String getRelativeTestDataPath() {
|
||||
|
||||
Reference in New Issue
Block a user