We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Wrong BSD license tag in the distribution
Although you clearly state in the repository that the software is licensed under AGPLv3, you do not explicitly specify the license type in the `setup.py` script. The license metadata is then derived from a wrong classifier: 
https://github.com/deepchecks/deepchecks/blob/7974e66d95358f4bccdd2ea16591b98e1ae74529/setup.py#L114

It's reflected in the [PyPI](https://pypi.org/project/deepchecks/) distribution:
![image](https://user-images.githubusercontent.com/36337649/148455950-abdd6865-9bf6-473a-88f4-3e86efa925a8.png)



--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `setup.py`
Content:
```
1 # ----------------------------------------------------------------------------
2 # Copyright (C) 2021 Deepchecks (https://www.deepchecks.com)
3 #
4 # This file is part of Deepchecks.
5 # Deepchecks is distributed under the terms of the GNU Affero General
6 # Public License (version 3 or later).
7 # You should have received a copy of the GNU Affero General Public License
8 # along with Deepchecks.  If not, see <http://www.gnu.org/licenses/>.
9 # ----------------------------------------------------------------------------
10 #
11 """
12 
13 |build| |Documentation Status| |pkgVersion| |pyVersions|
14 |Maintainability| |Coverage Status|
15 
16 .. image:: https://raw.githubusercontent.com/deepchecks/deepchecks/main/docs/images/deepchecks-logo-with-white-wide-back.png
17   :target: https://github.com/deepchecks/deepchecks
18 
19 Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort.
20 This includes checks related to various types of issues, such as model performance, data integrity,
21 distribution mismatches, and more.
22 
23 What Do You Need in Order to Start Validating?
24 ----------------------------------------------
25 
26 Depending on your phase and what you wise to validate, you'll need a
27 subset of the following:
28 
29 -  Raw data (before pre-processing such as OHE, string processing,
30    etc.), with optional labels
31 
32 -  The model's training data with labels
33 
34 -  Test data (which the model isn't exposed to) with labels
35 
36 -  A model compatible with scikit-learn API that you wish to validate
37    (e.g. RandomForest, XGBoost)
38 
39 Deepchecks validation accompanies you from the initial phase when you
40 have only raw data, through the data splits, and to the final stage of
41 having a trained model that you wish to evaluate. Accordingly, each
42 phase requires different assets for the validation. See more about
43 typical usage scenarios and the built-in suites in the
44 `docs <https://docs.deepchecks.com/?utm_source=pypi.org&utm_medium=referral&utm_campaign=readme>`__.
45 
46 Installation
47 ------------
48 
49 Using pip
50 ~~~~~~~~~
51 
52 .. code:: bash
53 
54    pip install deepchecks #--upgrade --user
55 
56 Using conda
57 ~~~~~~~~~~~
58 
59 .. code:: bash
60 
61    conda install -c deepchecks deepchecks
62 
63 .. |build| image:: https://github.com/deepchecks/deepchecks/actions/workflows/build.yml/badge.svg
64 .. |Documentation Status| image:: https://readthedocs.org/projects/deepchecks/badge/?version=latest
65    :target: https://docs.deepchecks.com/en/latest/?badge=latest
66 .. |pkgVersion| image:: https://img.shields.io/pypi/v/deepchecks
67 .. |pyVersions| image:: https://img.shields.io/pypi/pyversions/deepchecks
68 .. |Maintainability| image:: https://api.codeclimate.com/v1/badges/970b11794144139975fa/maintainability
69    :target: https://codeclimate.com/github/deepchecks/deepchecks/maintainability
70 .. |Coverage Status| image:: https://coveralls.io/repos/github/deepchecks/deepchecks/badge.svg?branch=main
71    :target: https://coveralls.io/github/deepchecks/deepchecks?branch=main
72 
73 """
74 
75 import setuptools
76 from setuptools import setup
77 from distutils.util import convert_path
78 import os
79 
80 main_ns = {}
81 DOCLINES = (__doc__ or '').split("\n")
82 
83 with open(os.path.join('./', 'VERSION')) as version_file:
84     VER = version_file.read().strip()
85 
86 requirementPath = os.path.dirname(os.path.realpath(__file__)) + '/requirements.txt'
87 install_requires = []
88 if os.path.isfile(requirementPath):
89     with open(requirementPath) as f:
90         install_requires = f.read().splitlines()
91 
92 
93 
94 
95 setup(
96     name='deepchecks',
97     version=VER,
98     packages=setuptools.find_packages(),
99     install_requires=install_requires,
100     license_files = ('LICENSE', ),
101     description = DOCLINES[0],
102     long_description="\n".join(DOCLINES[2:]),
103     author = 'deepchecks',  
104     author_email = 'info@deepchecks.com', 
105     url = 'https://github.com/deepchecks/deepchecks',
106     download_url = "https://github.com/deepchecks/deepchecks/releases/download/{0}/deepchecks-{0}.tar.gz".format(VER),
107     keywords = ['Software Development', 'Machine Learning'],
108     include_package_data=True,
109     classifiers         = [
110         'Intended Audience :: Developers',
111         'Intended Audience :: Science/Research',
112         'Topic :: Software Development',
113         'Topic :: Scientific/Engineering',
114         'License :: OSI Approved :: BSD License',
115         'Programming Language :: Python :: 3',
116         'Programming Language :: Python :: 3.6',
117         'Programming Language :: Python :: 3.7',
118         'Programming Language :: Python :: 3.8',
119         'Programming Language :: Python :: 3.9',
120         'Programming Language :: Python :: 3.10',
121     ],
122 )
123
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/setup.py b/setup.py
--- a/setup.py
+++ b/setup.py
@@ -111,7 +111,7 @@
         'Intended Audience :: Science/Research',
         'Topic :: Software Development',
         'Topic :: Scientific/Engineering',
-        'License :: OSI Approved :: BSD License',
+        'License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)',
         'Programming Language :: Python :: 3',
         'Programming Language :: Python :: 3.6',
         'Programming Language :: Python :: 3.7',

{"golden_diff": "diff --git a/setup.py b/setup.py\n--- a/setup.py\n+++ b/setup.py\n@@ -111,7 +111,7 @@\n         'Intended Audience :: Science/Research',\n         'Topic :: Software Development',\n         'Topic :: Scientific/Engineering',\n-        'License :: OSI Approved :: BSD License',\n+        'License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)',\n         'Programming Language :: Python :: 3',\n         'Programming Language :: Python :: 3.6',\n         'Programming Language :: Python :: 3.7',\n", "issue": "Wrong BSD license tag in the distribution\nAlthough you clearly state in the repository that the software is licensed under AGPLv3, you do not explicitly specify the license type in the `setup.py` script. The license metadata is then derived from a wrong classifier: \r\nhttps://github.com/deepchecks/deepchecks/blob/7974e66d95358f4bccdd2ea16591b98e1ae74529/setup.py#L114\r\n\r\nIt's reflected in the [PyPI](https://pypi.org/project/deepchecks/) distribution:\r\n![image](https://user-images.githubusercontent.com/36337649/148455950-abdd6865-9bf6-473a-88f4-3e86efa925a8.png)\r\n\r\n\n", "before_files": [{"content": "# ----------------------------------------------------------------------------\n# Copyright (C) 2021 Deepchecks (https://www.deepchecks.com)\n#\n# This file is part of Deepchecks.\n# Deepchecks is distributed under the terms of the GNU Affero General\n# Public License (version 3 or later).\n# You should have received a copy of the GNU Affero General Public License\n# along with Deepchecks.  If not, see <http://www.gnu.org/licenses/>.\n# ----------------------------------------------------------------------------\n#\n\"\"\"\n\n|build| |Documentation Status| |pkgVersion| |pyVersions|\n|Maintainability| |Coverage Status|\n\n.. image:: https://raw.githubusercontent.com/deepchecks/deepchecks/main/docs/images/deepchecks-logo-with-white-wide-back.png\n  :target: https://github.com/deepchecks/deepchecks\n\nDeepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort.\nThis includes checks related to various types of issues, such as model performance, data integrity,\ndistribution mismatches, and more.\n\nWhat Do You Need in Order to Start Validating?\n----------------------------------------------\n\nDepending on your phase and what you wise to validate, you'll need a\nsubset of the following:\n\n-  Raw data (before pre-processing such as OHE, string processing,\n   etc.), with optional labels\n\n-  The model's training data with labels\n\n-  Test data (which the model isn't exposed to) with labels\n\n-  A model compatible with scikit-learn API that you wish to validate\n   (e.g. RandomForest, XGBoost)\n\nDeepchecks validation accompanies you from the initial phase when you\nhave only raw data, through the data splits, and to the final stage of\nhaving a trained model that you wish to evaluate. Accordingly, each\nphase requires different assets for the validation. See more about\ntypical usage scenarios and the built-in suites in the\n`docs <https://docs.deepchecks.com/?utm_source=pypi.org&utm_medium=referral&utm_campaign=readme>`__.\n\nInstallation\n------------\n\nUsing pip\n~~~~~~~~~\n\n.. code:: bash\n\n   pip install deepchecks #--upgrade --user\n\nUsing conda\n~~~~~~~~~~~\n\n.. code:: bash\n\n   conda install -c deepchecks deepchecks\n\n.. |build| image:: https://github.com/deepchecks/deepchecks/actions/workflows/build.yml/badge.svg\n.. |Documentation Status| image:: https://readthedocs.org/projects/deepchecks/badge/?version=latest\n   :target: https://docs.deepchecks.com/en/latest/?badge=latest\n.. |pkgVersion| image:: https://img.shields.io/pypi/v/deepchecks\n.. |pyVersions| image:: https://img.shields.io/pypi/pyversions/deepchecks\n.. |Maintainability| image:: https://api.codeclimate.com/v1/badges/970b11794144139975fa/maintainability\n   :target: https://codeclimate.com/github/deepchecks/deepchecks/maintainability\n.. |Coverage Status| image:: https://coveralls.io/repos/github/deepchecks/deepchecks/badge.svg?branch=main\n   :target: https://coveralls.io/github/deepchecks/deepchecks?branch=main\n\n\"\"\"\n\nimport setuptools\nfrom setuptools import setup\nfrom distutils.util import convert_path\nimport os\n\nmain_ns = {}\nDOCLINES = (__doc__ or '').split(\"\\n\")\n\nwith open(os.path.join('./', 'VERSION')) as version_file:\n    VER = version_file.read().strip()\n\nrequirementPath = os.path.dirname(os.path.realpath(__file__)) + '/requirements.txt'\ninstall_requires = []\nif os.path.isfile(requirementPath):\n    with open(requirementPath) as f:\n        install_requires = f.read().splitlines()\n\n\n\n\nsetup(\n    name='deepchecks',\n    version=VER,\n    packages=setuptools.find_packages(),\n    install_requires=install_requires,\n    license_files = ('LICENSE', ),\n    description = DOCLINES[0],\n    long_description=\"\\n\".join(DOCLINES[2:]),\n    author = 'deepchecks',  \n    author_email = 'info@deepchecks.com', \n    url = 'https://github.com/deepchecks/deepchecks',\n    download_url = \"https://github.com/deepchecks/deepchecks/releases/download/{0}/deepchecks-{0}.tar.gz\".format(VER),\n    keywords = ['Software Development', 'Machine Learning'],\n    include_package_data=True,\n    classifiers         = [\n        'Intended Audience :: Developers',\n        'Intended Audience :: Science/Research',\n        'Topic :: Software Development',\n        'Topic :: Scientific/Engineering',\n        'License :: OSI Approved :: BSD License',\n        'Programming Language :: Python :: 3',\n        'Programming Language :: Python :: 3.6',\n        'Programming Language :: Python :: 3.7',\n        'Programming Language :: Python :: 3.8',\n        'Programming Language :: Python :: 3.9',\n        'Programming Language :: Python :: 3.10',\n    ],\n)\n", "path": "setup.py"}], "after_files": [{"content": "# ----------------------------------------------------------------------------\n# Copyright (C) 2021 Deepchecks (https://www.deepchecks.com)\n#\n# This file is part of Deepchecks.\n# Deepchecks is distributed under the terms of the GNU Affero General\n# Public License (version 3 or later).\n# You should have received a copy of the GNU Affero General Public License\n# along with Deepchecks.  If not, see <http://www.gnu.org/licenses/>.\n# ----------------------------------------------------------------------------\n#\n\"\"\"\n\n|build| |Documentation Status| |pkgVersion| |pyVersions|\n|Maintainability| |Coverage Status|\n\n.. image:: https://raw.githubusercontent.com/deepchecks/deepchecks/main/docs/images/deepchecks-logo-with-white-wide-back.png\n  :target: https://github.com/deepchecks/deepchecks\n\nDeepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort.\nThis includes checks related to various types of issues, such as model performance, data integrity,\ndistribution mismatches, and more.\n\nWhat Do You Need in Order to Start Validating?\n----------------------------------------------\n\nDepending on your phase and what you wise to validate, you'll need a\nsubset of the following:\n\n-  Raw data (before pre-processing such as OHE, string processing,\n   etc.), with optional labels\n\n-  The model's training data with labels\n\n-  Test data (which the model isn't exposed to) with labels\n\n-  A model compatible with scikit-learn API that you wish to validate\n   (e.g. RandomForest, XGBoost)\n\nDeepchecks validation accompanies you from the initial phase when you\nhave only raw data, through the data splits, and to the final stage of\nhaving a trained model that you wish to evaluate. Accordingly, each\nphase requires different assets for the validation. See more about\ntypical usage scenarios and the built-in suites in the\n`docs <https://docs.deepchecks.com/?utm_source=pypi.org&utm_medium=referral&utm_campaign=readme>`__.\n\nInstallation\n------------\n\nUsing pip\n~~~~~~~~~\n\n.. code:: bash\n\n   pip install deepchecks #--upgrade --user\n\nUsing conda\n~~~~~~~~~~~\n\n.. code:: bash\n\n   conda install -c deepchecks deepchecks\n\n.. |build| image:: https://github.com/deepchecks/deepchecks/actions/workflows/build.yml/badge.svg\n.. |Documentation Status| image:: https://readthedocs.org/projects/deepchecks/badge/?version=latest\n   :target: https://docs.deepchecks.com/en/latest/?badge=latest\n.. |pkgVersion| image:: https://img.shields.io/pypi/v/deepchecks\n.. |pyVersions| image:: https://img.shields.io/pypi/pyversions/deepchecks\n.. |Maintainability| image:: https://api.codeclimate.com/v1/badges/970b11794144139975fa/maintainability\n   :target: https://codeclimate.com/github/deepchecks/deepchecks/maintainability\n.. |Coverage Status| image:: https://coveralls.io/repos/github/deepchecks/deepchecks/badge.svg?branch=main\n   :target: https://coveralls.io/github/deepchecks/deepchecks?branch=main\n\n\"\"\"\n\nimport setuptools\nfrom setuptools import setup\nfrom distutils.util import convert_path\nimport os\n\nmain_ns = {}\nDOCLINES = (__doc__ or '').split(\"\\n\")\n\nwith open(os.path.join('./', 'VERSION')) as version_file:\n    VER = version_file.read().strip()\n\nrequirementPath = os.path.dirname(os.path.realpath(__file__)) + '/requirements.txt'\ninstall_requires = []\nif os.path.isfile(requirementPath):\n    with open(requirementPath) as f:\n        install_requires = f.read().splitlines()\n\n\n\n\nsetup(\n    name='deepchecks',\n    version=VER,\n    packages=setuptools.find_packages(),\n    install_requires=install_requires,\n    license_files = ('LICENSE', ),\n    description = DOCLINES[0],\n    long_description=\"\\n\".join(DOCLINES[2:]),\n    author = 'deepchecks',  \n    author_email = 'info@deepchecks.com', \n    url = 'https://github.com/deepchecks/deepchecks',\n    download_url = \"https://github.com/deepchecks/deepchecks/releases/download/{0}/deepchecks-{0}.tar.gz\".format(VER),\n    keywords = ['Software Development', 'Machine Learning'],\n    include_package_data=True,\n    classifiers         = [\n        'Intended Audience :: Developers',\n        'Intended Audience :: Science/Research',\n        'Topic :: Software Development',\n        'Topic :: Scientific/Engineering',\n        'License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)',\n        'Programming Language :: Python :: 3',\n        'Programming Language :: Python :: 3.6',\n        'Programming Language :: Python :: 3.7',\n        'Programming Language :: Python :: 3.8',\n        'Programming Language :: Python :: 3.9',\n        'Programming Language :: Python :: 3.10',\n    ],\n)\n", "path": "setup.py"}]}