The purpose of this program,
license_identifier, is to scan the source code
files and identify the license text region and the type of license.
Copyright (c) 2019, The Linux Foundation. All rights reserved.
See License.txt for full license text.
Installation for end users and client applications
If you wish to install
license_identifier as an end user, or if you are
developing an application that depends on
license_identifier, please install
it as follows:
# Set up a virtualenv virtualenv ENV source ENV/bin/activate # Get the latest versions of pip and setuptools: pip install -U setuptools pip pip install git+https://github.com/codeauroraforum/lid.git
At this point, you can test the installation by running, for example:
./ENV/bin/license-identifier -I path/to/source/files
Note for the developers who want to integrate this module into their code:
The program reads all the license files when it begins - it takes a few seconds.
For efficiency gain, I would recommend instantiating one instance, and running
Running under pypy for improved performance
You need a recent version of pypy (5.4.1 or later), only newer Ubuntu releases have a sufficiently new version available, e.g. Ubuntu 16.10 onwards. Otherwise you need to install pypy from http://pypy.org. For example, to install from the pypy.org binary:
mkdir /opt/pypy wget -qO - https://bitbucket.org/pypy/pypy/downloads/pypy2-v5.6.0-linux64.tar.bz2 | tar -xvj -C /opt/pypy --strip-components=1 ln -s /opt/pypy/bin/pypy /usr/local/bin/pypy
Once pypy is installed on the system, the only change to the process above is to create the virtualenv specifying the correct interpreter:
# Set up a virtualenv virtualenv -p pypy ENV source ENV/bin/activate
Alternatively if you have pypy installed locally provide the full path to the interpreter.
# Set up a virtualenv virtualenv -p /path_to_pypy_install/bin/pypy ENV source ENV/bin/activate
Then follow the remaining instructions above to install LiD and dependencies into the environment.
You can also use the dockerfile provided to spin up a container with the correct dependencies installed.
Installation for project maintainers
If you wish to install
license_identifier for development and testing,
please follow the instructions in this section.
Please use virtualenv:
virtualenv ENV source ENV/bin/activate pip install -U setuptools pip # get the latest versions of pip and setuptools
To install dependencies:
To update the licenses from the web:
make update-licenses # OPTIONAL
To generate the default license library as a pickle file:
To run tests:
usage: license-identifier -I '/your/input/file/dir_or_file' -F 'easy_read' optional arguments: -T, --threshold Set the threshold for similarity measure (ranging from 0 to 1, default value is 0.04) -L, --license_folder Specify the directory where the license text files are. -I, --input_path Specify the input path that needs scanning - to a file or a directory (when pointed to a directory, it considers subdirectories recursively) -F, --output_format Specify the output format (options are 'csv', 'easy_read') -O, --output_file_path Specify the output directory and prefix of the file name. User name, date, time and '.csv' will be added to the file name automatically. (a must for 'csv' file format option) -P, --pickle_file_path Specify the file where all the n-gram objects will be stored for the future runs
There are four main modes:
# 1. Use the default pickled license library file (recommended) license-identifier -I /path/to/source/code # 2. Use a particular pickled license library file license-identifier -P /path/to/pickled_licenses -I /path/to/source_code # 3. Use a license directory without building a pickled file (please make sure license files have .txt extensions) license-identifier -L /path/to/license_directory -I /path/to/source_code # 4. Build a pickled file from the specified license directory license-identifier -L /path/to/license_directory -P /path/to/output_pickled_licenses
To call LiD, first instantiate a LicenseIdentifier object, and then call one of the "analyze_" methods on a file/directory path.
lid = license_identifier.LicenseIdentifier( threshold = 0.07, run_in_parallel=False) results = lid.analyze_input_path(path_to_files)
The results will be named a list of named tuples for each file, each named tuple representing a detected license in that file. The named tuple contains the following fields: input_fp - input file path matched_license - matched license type score - Score using whole input test start_line_ind - Start line number end_line_ind - End line number start_offset - Start byte offset end_offset - End byte offset region_score - Score using only the license text portion found_region - Found license text original_region - Matched license text without context
If you want to add more licenses, please create a text file with the license text.
Then, save it into the
Then, build the n-gram license library using