Library to allow users inspect a software project folder (i.e., a directory and its subdirectories) and extract all the most relevant information, such as class, method and parameter documentation, classes (and their methods), functions, etc.
Given a folder with code, inspect4py will:
- Extract all imported modules and how each module is imported as (i.e., whether they are internal or external).
- Extract all functions in the code, including their documentation, parameters, accepted values, and call list.
- Extract all classes in the code, with all their methods and respective documentation
- Extract the control flow of each file.
- Extract the hierarchy of directories and files.
- Extract the requirements used in the software project.
- Classify which files are tests
- Classify the main type of software project (script, package, library or service). Only one type is returned as main type (e.g., if a library has the option to be deployed as a service,
inspect4pywill returnLibraryas its main type) - Return a ranking of the different ways in which a a software component can be run, ordered by relevance.
All metadata is extracted as a JSON file.
Inspect4py currently works only for Python 3 projects.
inspect4py added the functionality of capture Data Flow Graphs for each function inspired by GraphCodeBERT: Github & Paper. The illustration is given:
| Source Code | List Output | Networkx Image |
|---|---|---|
def max(a, b): |
('a', 3, 'comesFrom', [], []) |
 |
inspect4py uses ASTs, more specifically
the ast module in Python, generating
a tree of objects (per file) whose classes all inherit from ast.AST.
inspect4py parses each of the input file(s) as an AST tree, extracting the relevant information and storing it as a JSON file. Furthermore, it also captures the control flow of each input file(s), by using another two libraries:
- staticfg: StatiCFG is a package that can be used to produce control flow graphs (CFGs) for Python 3 programs. The CFGs it generates can be easily visualised with graphviz and used for static analysis. We have a flag in the code (FLAG_PNG) to indicate if we want to generate this type of control flow graphs or not. Note: The original code of this package can be found here, which has been fixed it in our repository
We also use docstring_parser, which has support for ReST, Google, and Numpydoc-style docstrings. Some (basic) tests done using this library can be found at here.
Finally, we reuse Pigar for generating automatically the requirements of a given repository. This is an optional funcionality. In order to activate the argument (-r) has to be indicated when running inspect4py.
Please cite our MSR 2022 demo paper:
@inproceedings{FilgueiraG22,
author = {Rosa Filgueira and
Daniel Garijo},
title = {Inspect4py: {A} Knowledge Extraction Framework for Python Code Repositories},
booktitle = {{IEEE/ACM} 19th International Conference on Mining Software Repositories,
{MSR} 2022, Pittsburgh, PA, USA, May 23-24, 2022},
pages = {232--236},
publisher = {{IEEE}},
year = {2022},
url = {https://dgarijo.com/papers/inspect4py_MSR2022.pdf},
doi = {10.1145/3524842.3528497}
}
Make sure you have tree-sitter installed, C complier is needed, more info:
pip install tree-sitter
Note that if the ".so" file is not working properly, it is recommended that run the following commeds to generate a so file for your OS:
git clone https://github.com/tree-sitter/tree-sitter-python
python inspect4py/build.py
Make sure you have graphviz installed:
sudo apt-get install graphviz
We have tested inspect4py in Python 3.7+. Our recommended version is Python 3.9.
We have tested inspect4py in Unix, MacOS and Windows 11(22621.1265).
inspect4py is available in pypi! Just install it like a regular package:
pip install inspect4py
You are done!
Then try to update the python-dev utilities: sudo apt-get install python3.X-dev (where X is your python version)
Prepare a virtual Python3 enviroment, cd into the inspect4py folder and install the package as follows:
git clone https://github.com/SoftwareUnderstanding/inspect4py
cd inspect4py
pip install -e .
You are done!
docstring_parser==0.7
astor
graphviz
click
pigar
setuptools==54.2.0
json2html
configparser
bigcode_astgen
GitPython
tree-sitter
If you want to run the evaluations, do not forget to add pandas to the previous set.
You need to have Docker installed.
Next, clone the inspect4py repository:
git clone https://github.com/SoftwareUnderstanding/inspect4py/
Generate a Docker image for inspect4py:
docker build --tag inspect4py:1.0 .
Run the inspect4py image:
docker run -it --rm inspect4py:1.0 /bin/bash
Now you can run inspect4py:
root@e04792563e6a:/# inspect4py --help
For more information about inspect4py execution options, please see the section below (Execution).
Note that when running inspect4py with Docker, you will need to need to provide a path to the target repository to analyze. You can do this by:
- Cloning the target repository. For example:
docker run -it --rm inspect4py:1.0 /bin/bash
# Docker image starts
root@e04792563e6a:/# git clone https://github.com/repo/id
root@e04792563e6a:/# inspect4py -i id
- Creating a volume. For example, for mounting the $PWD folder:
docker run -it -v -v $PWD:/out --rm inspect4py:1.0 /bin/bash
# Docker image starts
root@e04792563e6a:/# inspect4py -i /out/path/to/repo
Other useful commands when using Docker:
docker cp [OPTIONS] CONTAINER:SRC_PATH DEST_PATH|-
docker image rm -f inspect4py:1.0
The tool can be executed to inspect a file, or all the files of a given directory (and its subdirectories). For example, it can be used to inspect all the python files of a given GitHub repository (that has been previously cloned locally).
The tool by default stores the results in the OutputDir directory, but users can specify their own directory name by using -o or --output flags.
inspect4py --input_path <FILE.py | DIRECTORY> [--output_dir "OutputDir", --ignore_dir_pattern "__", ignore_file_pattern "__" --requirements --html_output]
For clarity, we have added a help command to explain each input parameter:
inspect4py --help
Usage: inspect4py [OPTIONS]
Options:
--version Show the version and exit.
-i, --input_path TEXT input path of the file or directory to
inspect. [required]
-o, --output_dir TEXT output directory path to store results. If
the directory does not exist, the tool will
create it.
-ignore_dir, --ignore_dir_pattern TEXT
ignore directories starting with a certain
pattern. This parameter can be provided
multiple times to ignore multiple directory
patterns.
-ignore_file, --ignore_file_pattern TEXT
ignore files starting with a certain
pattern. This parameter can be provided
multiple times to ignore multiple file
patterns.
-r, --requirements find the requirements of the repository.
-html, --html_output generates an html file of the DirJson in the
output directory.
-cl, --call_list generates the call list in a separate html
file.
-cf, --control_flow generates the call graph for each file in a
different directory.
-dt, --directory_tree captures the file directory tree from the
root path of the target repository.
-si, --software_invocation generates which are the software
invocation commands to run and test the
target repository.
-ast, -—abstract_syntax_tree generates abstract syntax tree in json format.
-sc, --source_code generates source code of each ast node.
-ld, --license_detection detects the license of the target repository.
-rm, --readme extract all readme files in the target repository.
-md, --metadata extract metadata of the target repository using
Github API.
-df, --data_flow extract data flow graph for every function, BOOL
-st, --symbol_table symbol table file location. STR
--help Show this message and exit.
For additional documentation and examples, please have a look at our online documentation
Contributions to address any of the current issues are welcome. In order to push your contribution, just push your pull request to the development branch (dev). The master branch has only the code associated to the latest release.
We would like to thank Laura Camacho, designer of the logo