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PyCG - Practical Python Call Graphs

PyCG generates call graphs for Python code using static analysis. It efficiently supports

• Higher order functions
• Twisted class inheritance schemes
• Automatic discovery of imported modules for further analysis
• Nested definitions

You can read the full methodology as well as a complete evaluation on the ICSE 2021 paper.

You can cite PyCG as follows. Vitalis Salis, Thodoris Sotiropoulos, Panos Louridas, Diomidis Spinellis and Dimitris Mitropoulos. PyCG: Practical Call Graph Generation in Python. In 43rd International Conference on Software Engineering, ICSE '21, 25–28 May 2021.

PyCG is archived. Due to limited availability, no further development improvements are planned. Happy to help anyone that wants to create a fork to continue development.

Installation

PyCG is implemented in Python3 and requires Python version 3.4 or higher. It also has no dependencies. Simply:

pip install pycg

Usage

~ >>> pycg -h
usage: __main__.py [-h] [--package PACKAGE] [--fasten] [--product PRODUCT]
                        [--forge FORGE] [--version VERSION] [--timestamp TIMESTAMP]
                        [--max-iter MAX_ITER] [--operation {call-graph,key-error}]
                        [--as-graph-output AS_GRAPH_OUTPUT] [-o OUTPUT]
                        [entry_point ...]

positional arguments:
  entry_point           Entry points to be processed

optional arguments:
  -h, --help            show this help message and exit
  --package PACKAGE     Package containing the code to be analyzed
  --fasten              Produce call graph using the FASTEN format
  --product PRODUCT     Package name
  --forge FORGE         Source the product was downloaded from
  --version VERSION     Version of the product
  --timestamp TIMESTAMP
                        Timestamp of the package's version
  --max-iter MAX_ITER   Maximum number of iterations through source code. If not specified a fix-point iteration will be performed.
  --operation {call-graph,key-error}
                        Operation to perform. Choose call-graph for call graph generation (default) or key-error for key error detection on dictionaries.
  --as-graph-output AS_GRAPH_OUTPUT
                        Output for the assignment graph
  -o OUTPUT, --output OUTPUT
                        Output path

The following command line arguments should used only when --fasten is provied:

• --product: The name of the package.
• --forge: Source the package was downloaded from.
• --version: The version of the package.
• --timestamp : The timestamp of the package's version.

Call Graph Output

Simple JSON format

The call edges are in the form of an adjacency list where an edge (src, dst) is represented as an entry of dst in the list assigned to key src:

{
    "node1": ["node2", "node3"],
    "node2": ["node3"],
    "node3": []
}

FASTEN Format

For an up-to-date description of the FASTEN format refer to the FASTEN wiki.

Key Errors Output

We are currently experimenting on identifying potential invalid dictionary accesses on Python dictionaries (key errors). The output format for key errors is a list of dictionaries containing:

• The file name in which the key error was identified
• The line number inside the file
• The namespace of the accessed dictionary
• The key used to access the dictionary

[{
    "filename": "mod.py",
    "lineno": 2,
    "namespace": "mod.<dict1>",
    "key": "key2"
},
{
    "filename": "mod.py",
    "lineno": 8,
    "namespace": "mod.<dict1>",
    "key": "nokey"
}]

Examples

All the entry points are known and we want the simple JSON format

~ >>> pycg --package pkg_root pkg_root/module1.py pkg_root/subpackage/module2.py -o cg.json

All entry points are not known and we want the simple JSON format

~ >>> pycg --package django $(find django -type f -name "*.py") -o django.json

We want the FASTEN format:

~ >>> pycg --package pypi_pkg --fasten --product "pypipkg" --forge "PyPI" \
        --version "0.1" --timestamp 42 \
        pypi_pkg/module1.py pkg_root/subpackage/module2.py -o cg.json

Running Tests

From the root directory, first install the mock package:

pip3 install mock

Τhen, simply run the tests by executing:

make test