57e36419b2
So far CSA was relying on the LLVM Statistic package that allowed us to gather some data about analysis of an entire translation unit. However, the translation unit consists of a collection of loosely related entry points. Aggregating data across multiple such entry points is often counter productive. This change introduces a new lightweight always-on facility to collect Boolean or numerical statistics for each entry point and dump them in a CSV format. Such format makes it easy to aggregate data across multiple translation units and analyze it with common data-processing tools. We break down the existing statistics that were collected on the per-TU basis into values per entry point. Additionally, we enable the statistics unconditionally (STATISTIC -> ALWAYS_ENABLED_STATISTIC) to facilitate their use (you can gather the data with a simple run-time flag rather than having to recompile the analyzer). These statistics are very light and add virtually no overhead. Co-authored-by: Balazs Benics <benicsbalazs@gmail.com> CPP-6160
103 lines
2.9 KiB
Python
103 lines
2.9 KiB
Python
#!/usr/bin/env python
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#
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# ===- csv2json.py - Static Analyzer test helper ---*- python -*-===#
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#
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# Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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# See https://llvm.org/LICENSE.txt for license information.
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# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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#
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# ===------------------------------------------------------------------------===#
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r"""
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Clang Static Analyzer test helper
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=================================
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This script converts a CSV file to a JSON file with a specific structure.
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The JSON file contains a single dictionary. The keys of this dictionary
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are taken from the first column of the CSV. The values are dictionaries
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themselves, mapping the CSV header names (except the first column) to
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the corresponding row values.
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Usage:
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csv2json.py <source-file>
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Example:
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// RUN: %csv2json.py %t | FileCheck %s
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"""
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import csv
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import sys
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import json
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def csv_to_json_dict(csv_filepath):
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"""
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Args:
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csv_filepath: The path to the input CSV file.
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Raises:
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FileNotFoundError: If the CSV file does not exist.
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csv.Error: If there is an error parsing the CSV file.
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Exception: For any other unexpected errors.
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"""
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try:
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with open(csv_filepath, "r", encoding="utf-8") as csvfile:
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reader = csv.reader(csvfile)
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# Read the header row (column names)
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try:
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header = next(reader)
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except StopIteration: # Handle empty CSV file
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json.dumps({}, indent=2) # write an empty dict
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return
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# handle a csv file that contains no rows, not even a header row.
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if not header:
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json.dumps({}, indent=2)
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return
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other_column_names = [name.strip() for name in header[1:]]
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data_dict = {}
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for row in reader:
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if len(row) != len(header):
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raise csv.Error("Inconsistent CSV file")
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exit(1)
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key = row[0]
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value_map = {}
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for i, col_name in enumerate(other_column_names):
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# +1 to skip the first column
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value_map[col_name] = row[i + 1].strip()
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data_dict[key] = value_map
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return json.dumps(data_dict, indent=2)
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except FileNotFoundError:
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raise FileNotFoundError(f"Error: CSV file not found at {csv_filepath}")
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except csv.Error as e:
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raise csv.Error(f"Error parsing CSV file: {e}")
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except Exception as e:
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raise Exception(f"An unexpected error occurred: {e}")
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def main():
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"""Example usage with error handling."""
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csv_file = sys.argv[1]
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try:
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print(csv_to_json_dict(csv_file))
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except (FileNotFoundError, csv.Error, Exception) as e:
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print(str(e))
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except:
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print("An error occured")
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if __name__ == "__main__":
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main()
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