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apjanuszapjanusz
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fix bug in python code (#34)
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+174
-176
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‎src/python_code/getMatrix.ts‎

Lines changed: 174 additions & 176 deletions
Original file line numberDiff line numberDiff line change
@@ -1,177 +1,175 @@
11
export const getMatrix = (
2-
varName: string,
3-
startRow: number,
4-
endRow: number,
5-
startColumn: number,
6-
endColumn: number
7-
): string =>
8-
`
9-
import importlib
10-
from IPython.display import JSON
11-
12-
def __get_variable_shape(obj):
13-
if hasattr(obj, 'shape'):
14-
return " x ".join(map(str, obj.shape))
15-
if isinstance(obj, list):
16-
if obj and all(isinstance(el, list) for el in obj):
17-
if len(set(map(len, obj))) == 1:
18-
return f"{len(obj)} x {len(obj[0])}"
19-
else:
20-
return f"{len(obj)}"
21-
return str(len(obj))
22-
return ""
23-
24-
def __format_content(item):
25-
if isinstance(item, list):
26-
return [__format_content(subitem) for subitem in item]
27-
elif isinstance(item, str):
28-
return item[:50] + "..." if len(item) > 50 else item
29-
elif isinstance(item, (int, float, bool)) or item is None:
30-
return item
31-
elif isinstance(item, dict):
32-
return {k: __format_content(v) for k, v in item.items()}
33-
else:
34-
if hasattr(item, "name"):
35-
return getattr(item, "name")
36-
return type(item).__name__
37-
38-
def __mljar_variable_inspector_get_matrix_content(
39-
var_name="${varName}",
40-
start_row=${startRow},
41-
end_row=${endRow},
42-
start_column=${startColumn},
43-
end_column=${endColumn}
44-
):
45-
if var_name not in globals():
46-
return JSON({"error": "Variable not found."})
47-
48-
obj = globals()[var_name]
49-
module_name = type(obj).__module__
50-
var_type = type(obj).__name__
51-
var_shape = __get_variable_shape(obj)
52-
53-
if "numpy" in module_name:
54-
try:
55-
np = importlib.import_module("numpy")
56-
except ImportError:
57-
return JSON({"error": "Numpy is not installed."})
58-
if isinstance(obj, np.ndarray):
59-
if obj.ndim > 2:
60-
return JSON({
61-
"variable": var_name,
62-
"variableType": var_type,
63-
"variableShape": var_shape,
64-
"error": "Numpy array has more than 2 dimensions."
65-
})
66-
if obj.ndim == 1:
67-
actual_end_row = min(end_row, len(obj))
68-
sliced = obj[start_row:actual_end_row]
69-
returnedSize = [start_row, actual_end_row, 0, 1]
70-
else:
71-
actual_end_row = min(end_row, obj.shape[0])
72-
actual_end_column = min(end_column, obj.shape[1])
73-
sliced = obj[start_row:actual_end_row, start_column:actual_end_column]
74-
returnedSize = [start_row, actual_end_row, start_column, actual_end_column]
75-
return JSON({
76-
"variable": var_name,
77-
"variableType": var_type,
78-
"variableShape": var_shape,
79-
"returnedSize": returnedSize,
80-
"content": __format_content(sliced.tolist())
81-
})
82-
83-
if "pandas" in module_name:
84-
try:
85-
pd = importlib.import_module("pandas")
86-
except ImportError:
87-
return JSON({"error": "Pandas is not installed."})
88-
if isinstance(obj, pd.DataFrame):
89-
actual_end_row = min(end_row, len(obj.index))
90-
actual_end_column = min(end_column, len(obj.columns))
91-
sliced = obj.iloc[start_row:actual_end_row, start_column:actual_end_column]
92-
result = []
93-
for col in sliced.columns:
94-
col_values = [col] + sliced[col].tolist()
95-
result.append(col_values)
96-
returnedSize = [start_row, actual_end_row, start_column, actual_end_column]
97-
return JSON({
98-
"variable": var_name,
99-
"variableType": var_type,
100-
"variableShape": var_shape,
101-
"returnedSize": returnedSize,
102-
"content": __format_content(result)
103-
})
104-
elif isinstance(obj, pd.Series):
105-
actual_end_row = min(end_row, len(obj))
106-
sliced = obj.iloc[start_row:actual_end_row]
107-
df = sliced.to_frame()
108-
result = []
109-
for col in df.columns:
110-
col_values = [col] + df[col].tolist()
111-
result.append(col_values)
112-
returnedSize = [start_row, actual_end_row, 0, 1]
113-
return JSON({
114-
"variable": var_name,
115-
"variableType": var_type,
116-
"variableShape": var_shape,
117-
"returnedSize": returnedSize,
118-
"content": __format_content(result)
119-
})
120-
121-
if isinstance(obj, list):
122-
if all(isinstance(el, list) for el in obj):
123-
if len(set(map(len, obj))) == 1:
124-
actual_end_row = min(end_row, len(obj))
125-
actual_end_column = min(end_column, len(obj[0]))
126-
sliced = [row[start_column:actual_end_column] for row in obj[start_row:actual_end_row]]
127-
returnedSize = [start_row, actual_end_row, start_column, actual_end_column]
128-
content = __format_content(sliced)
129-
else:
130-
actual_end_row = min(end_row, len(obj))
131-
sliced = obj[start_row:actual_end_row]
132-
returnedSize = [start_row, actual_end_row, 0, 1]
133-
content = ["list" for _ in sliced]
134-
var_shape = f"{len(obj)}"
135-
return JSON({
136-
"variable": var_name,
137-
"variableType": var_type,
138-
"variableShape": var_shape,
139-
"returnedSize": returnedSize,
140-
"content": content
141-
})
142-
else:
143-
actual_end_row = min(end_row, len(obj))
144-
sliced = obj[start_row:actual_end_row]
145-
returnedSize = [start_row, actual_end_row, 0, 1]
146-
return JSON({
147-
"variable": var_name,
148-
"variableType": var_type,
149-
"variableShape": str(len(obj)),
150-
"returnedSize": returnedSize,
151-
"content": __format_content(sliced)
152-
})
153-
154-
if isinstance(obj, dict):
155-
items = list(obj.items())[start_row:end_row]
156-
sliced_dict = dict(items)
157-
returnedSize = [start_row, end_row, 0, 1]
158-
var_shape = str(len(obj))
159-
return JSON({
160-
"variable": var_name,
161-
"variableType": var_type,
162-
"variableShape": var_shape,
163-
"returnedSize": returnedSize,
164-
"content": __format_content(sliced_dict)
165-
})
166-
167-
return JSON({
168-
"variable": var_name,
169-
"variableType": var_type,
170-
"variableShape": "unknown",
171-
"error": "Variable is not a supported array type.",
172-
"content": [10,10,10]
173-
})
174-
175-
__mljar_variable_inspector_get_matrix_content()
176-
`;
177-
2+
varName: string,
3+
startRow: number,
4+
endRow: number,
5+
startColumn: number,
6+
endColumn: number
7+
): string => `
8+
import importlib
9+
from IPython.display import JSON
10+
11+
def __get_variable_shape(obj):
12+
if hasattr(obj, 'shape'):
13+
return " x ".join(map(str, obj.shape))
14+
if isinstance(obj, list):
15+
if obj and all(isinstance(el, list) for el in obj):
16+
if len(set(map(len, obj))) == 1:
17+
return f"{len(obj)} x {len(obj[0])}"
18+
else:
19+
return f"{len(obj)}"
20+
return str(len(obj))
21+
return ""
22+
23+
def __format_content(item):
24+
if isinstance(item, list):
25+
return [__format_content(subitem) for subitem in item]
26+
elif isinstance(item, dict):
27+
return {k: __format_content(v) for k, v in item.items()}
28+
elif isinstance(item, str):
29+
return item[:50] + "..." if len(item) > 50 else item
30+
elif isinstance(item, (int, float, bool)) or item is None:
31+
return item
32+
else:
33+
if hasattr(item, "name"):
34+
return getattr(item, "name")
35+
return type(item).__name__
36+
37+
def __mljar_variable_inspector_get_matrix_content(
38+
var_name="${varName}",
39+
start_row=${startRow},
40+
end_row=${endRow},
41+
start_column=${startColumn},
42+
end_column=${endColumn}
43+
):
44+
if var_name not in globals():
45+
return JSON({"error": "Variable not found."})
46+
47+
obj = globals()[var_name]
48+
module_name = type(obj).__module__
49+
var_type = type(obj).__name__
50+
var_shape = __get_variable_shape(obj)
51+
52+
if "numpy" in module_name:
53+
try:
54+
np = importlib.import_module("numpy")
55+
except ImportError:
56+
return JSON({"error": "Numpy is not installed."})
57+
if isinstance(obj, np.ndarray):
58+
if obj.ndim > 2:
59+
return JSON({
60+
"variable": var_name,
61+
"variableType": var_type,
62+
"variableShape": var_shape,
63+
"error": "Numpy array has more than 2 dimensions."
64+
})
65+
if obj.ndim == 1:
66+
actual_end_row = min(end_row, len(obj))
67+
sliced = obj[start_row:actual_end_row]
68+
returnedSize = [start_row, actual_end_row, 0, 1]
69+
else:
70+
actual_end_row = min(end_row, obj.shape[0])
71+
actual_end_column = min(end_column, obj.shape[1])
72+
sliced = obj[start_row:actual_end_row, start_column:actual_end_column]
73+
returnedSize = [start_row, actual_end_row, start_column, actual_end_column]
74+
return JSON({
75+
"variable": var_name,
76+
"variableType": var_type,
77+
"variableShape": var_shape,
78+
"returnedSize": returnedSize,
79+
"content": __format_content(sliced.tolist())
80+
})
81+
82+
if "pandas" in module_name:
83+
try:
84+
pd = importlib.import_module("pandas")
85+
except ImportError:
86+
return JSON({"error": "Pandas is not installed."})
87+
if isinstance(obj, pd.DataFrame):
88+
actual_end_row = min(end_row, len(obj.index))
89+
actual_end_column = min(end_column, len(obj.columns))
90+
sliced = obj.iloc[start_row:actual_end_row, start_column:actual_end_column]
91+
result = []
92+
for col in sliced.columns:
93+
col_values = [col] + sliced[col].tolist()
94+
result.append(col_values)
95+
returnedSize = [start_row, actual_end_row, start_column, actual_end_column]
96+
return JSON({
97+
"variable": var_name,
98+
"variableType": var_type,
99+
"variableShape": var_shape,
100+
"returnedSize": returnedSize,
101+
"content": __format_content(result)
102+
})
103+
elif isinstance(obj, pd.Series):
104+
actual_end_row = min(end_row, len(obj))
105+
sliced = obj.iloc[start_row:actual_end_row]
106+
df = sliced.to_frame()
107+
result = []
108+
for col in df.columns:
109+
col_values = [col] + df[col].tolist()
110+
result.append(col_values)
111+
returnedSize = [start_row, actual_end_row, 0, 1]
112+
return JSON({
113+
"variable": var_name,
114+
"variableType": var_type,
115+
"variableShape": var_shape,
116+
"returnedSize": returnedSize,
117+
"content": __format_content(result)
118+
})
119+
120+
if isinstance(obj, list):
121+
if all(isinstance(el, list) for el in obj):
122+
if len(set(map(len, obj))) == 1:
123+
actual_end_row = min(end_row, len(obj))
124+
actual_end_column = min(end_column, len(obj[0]))
125+
sliced = [row[start_column:actual_end_column] for row in obj[start_row:actual_end_row]]
126+
returnedSize = [start_row, actual_end_row, start_column, actual_end_column]
127+
content = __format_content(sliced)
128+
else:
129+
actual_end_row = min(end_row, len(obj))
130+
sliced = obj[start_row:actual_end_row]
131+
returnedSize = [start_row, actual_end_row, 0, 1]
132+
content = ["list" for _ in sliced]
133+
var_shape = f"{len(obj)}"
134+
return JSON({
135+
"variable": var_name,
136+
"variableType": var_type,
137+
"variableShape": var_shape,
138+
"returnedSize": returnedSize,
139+
"content": content
140+
})
141+
else:
142+
actual_end_row = min(end_row, len(obj))
143+
sliced = obj[start_row:actual_end_row]
144+
returnedSize = [start_row, actual_end_row, 0, 1]
145+
return JSON({
146+
"variable": var_name,
147+
"variableType": var_type,
148+
"variableShape": str(len(obj)),
149+
"returnedSize": returnedSize,
150+
"content": __format_content(sliced)
151+
})
152+
153+
if isinstance(obj, dict):
154+
items = list(obj.items())[start_row:end_row]
155+
sliced_dict = dict(items)
156+
returnedSize = [start_row, end_row, 0, 1]
157+
var_shape = str(len(obj))
158+
return JSON({
159+
"variable": var_name,
160+
"variableType": var_type,
161+
"variableShape": var_shape,
162+
"returnedSize": returnedSize,
163+
"content": __format_content(sliced_dict)
164+
})
165+
166+
return JSON({
167+
"variable": var_name,
168+
"variableType": var_type,
169+
"variableShape": "unknown",
170+
"error": "Variable is not a supported array type.",
171+
"content": [10, 10, 10]
172+
})
173+
174+
__mljar_variable_inspector_get_matrix_content()
175+
`;

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