gurudesh/pytracebugs huggingface dataset:
# Buggy code
def _f1(precision: float, recall: float) -> float:
    """
    Compute f1

    :param float precision
    :param float recall

    :return: f1
    :rtype: float
    """
    if precision == recall == 0:
        return 0
    return 2 * precision * recall / (precision + recall)


# Traceback (ModuleNotFoundError)
# Install with no extras
pip install pythainlp

python
Python 3.7.6 (default, Dec 30 2019, 19:38:26)
[Clang 11.0.0 (clang-1100.0.33.16)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
import pythainlp
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/__init__.py", line 26, in <module>
from pythainlp.benchmarks import benchmark
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/benchmarks/__init__.py", line 1, in <module>
from .word_tokenization import benchmark
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/benchmarks/word_tokenization.py", line 6, in <module>
import numpy as np
ModuleNotFoundError: No module named 'numpy'

# Fixed code
def _f1(precision: float, recall: float) -> float:
    """
    Compute f1.

    :param float precision
    :param float recall

    :return: f1
    :rtype: float
    """
    if precision == recall == 0:
        return 0
    return 2 * precision * recall / (precision + recall)
# Buggy code
def _flatten_result(my_dict: dict, sep: str = ":") -> dict:
    """
    Flatten two-level dictionary

    Use keys in the first level as a prefix for keys in the two levels.
    For example,
    my_dict = { "a": { "b": 7 } }
    flatten(my_dict)
    { "a:b": 7 }


    :param dict my_dict: contains stats dictionary
    :param str sep: separator between the two keys (default: ":")

    :return: a one-level dictionary with key combined
    :rtype: dict[str, float | str]
    """
    items = []
    for k1, kv2 in my_dict.items():
        for k2, v in kv2.items():
            new_key = f"{k1}{sep}{k2}"
            items.append((new_key, v))

    return dict(items)


# Traceback (ModuleNotFoundError)
# Install with no extras
pip install pythainlp

python
Python 3.7.6 (default, Dec 30 2019, 19:38:26)
[Clang 11.0.0 (clang-1100.0.33.16)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
import pythainlp
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/__init__.py", line 26, in <module>
from pythainlp.benchmarks import benchmark
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/benchmarks/__init__.py", line 1, in <module>
from .word_tokenization import benchmark
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/benchmarks/word_tokenization.py", line 6, in <module>
import numpy as np
ModuleNotFoundError: No module named 'numpy'

# Fixed code
def _flatten_result(my_dict: dict, sep: str = ":") -> dict:
    """
    Flatten two-level dictionary.

    Use keys in the first level as a prefix for keys in the two levels.
    For example,
    my_dict = { "a": { "b": 7 } }
    flatten(my_dict)
    { "a:b": 7 }


    :param dict my_dict: contains stats dictionary
    :param str sep: separator between the two keys (default: ":")

    :return: a one-level dictionary with key combined
    :rtype: dict[str, float | str]
    """
    items = []
    for k1, kv2 in my_dict.items():
        for k2, v in kv2.items():
            new_key = f"{k1}{sep}{k2}"
            items.append((new_key, v))

    return dict(items)
# Buggy code
def benchmark(ref_samples: list, samples: list):
    """
    Performace benchmark of samples

    Please see :meth:`pythainlp.benchmarks.word_tokenization.compute_stats` for
    metrics being computed.

    :param list[str] ref_samples: ground truth samples
    :param list[str] samples: samples that we want to evaluate

    :return: dataframe with row x col = len(samples) x len(metrics)
    :rtype: pandas.DataFrame
    """

    results = []
    for i, (r, s) in enumerate(zip(ref_samples, samples)):
        try:
            r, s = preprocessing(r), preprocessing(s)
            if r and s:
                stats = compute_stats(r, s)
                stats = _flatten_result(stats)
                stats["expected"] = r
                stats["actual"] = s
                results.append(stats)
        except:
            reason = """
[Error]
Reason: %s

Pair (i=%d)
--- label
%s
--- sample
%s
""" % (sys.exc_info(), i, r, s)

            raise SystemExit(reason)

    return pd.DataFrame(results)


# Traceback (ModuleNotFoundError)
# Install with no extras
pip install pythainlp

python
Python 3.7.6 (default, Dec 30 2019, 19:38:26)
[Clang 11.0.0 (clang-1100.0.33.16)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
import pythainlp
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/__init__.py", line 26, in <module>
from pythainlp.benchmarks import benchmark
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/benchmarks/__init__.py", line 1, in <module>
from .word_tokenization import benchmark
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/benchmarks/word_tokenization.py", line 6, in <module>
import numpy as np
ModuleNotFoundError: No module named 'numpy'

# Fixed code
def benchmark(ref_samples: list, samples: list):
    """
    Performace benchmark of samples.

    Please see :meth:`pythainlp.benchmarks.word_tokenization.compute_stats` for
    metrics being computed.

    :param list[str] ref_samples: ground truth samples
    :param list[str] samples: samples that we want to evaluate

    :return: dataframe with row x col = len(samples) x len(metrics)
    :rtype: pandas.DataFrame
    """
    results = []
    for i, (r, s) in enumerate(zip(ref_samples, samples)):
        try:
            r, s = preprocessing(r), preprocessing(s)
            if r and s:
                stats = compute_stats(r, s)
                stats = _flatten_result(stats)
                stats["expected"] = r
                stats["actual"] = s
                results.append(stats)
        except:
            reason = """
[Error]
Reason: %s

Pair (i=%d)
--- label
%s
--- sample
%s
""" % (
                sys.exc_info(),
                i,
                r,
                s,
            )
            raise SystemExit(reason)

    return pd.DataFrame(results)
# Buggy code
def preprocessing(txt: str, remove_space: bool = True) -> str:
    """
    Clean up text before performing evaluation

    :param str text: text to be preprocessed
    :param bool remove_space: whether remove white space

    :return: preprocessed text
    :rtype: str
    """
    txt = re.sub(SURROUNDING_SEPS_RX, "", txt)

    if remove_space:
        txt = re.sub("\s+", "", txt)

    txt = re.sub(MULTIPLE_SEPS_RX, SEPARATOR, txt)

    txt = re.sub(TAG_RX, "", txt)

    txt = re.sub(TAILING_SEP_RX, "", txt).strip()

    return txt


# Traceback (ModuleNotFoundError)
# Install with no extras
pip install pythainlp

python
Python 3.7.6 (default, Dec 30 2019, 19:38:26)
[Clang 11.0.0 (clang-1100.0.33.16)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
import pythainlp
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/__init__.py", line 26, in <module>
from pythainlp.benchmarks import benchmark
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/benchmarks/__init__.py", line 1, in <module>
from .word_tokenization import benchmark
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/benchmarks/word_tokenization.py", line 6, in <module>
import numpy as np
ModuleNotFoundError: No module named 'numpy'

# Fixed code
def preprocessing(txt: str, remove_space: bool = True) -> str:
    """
    Clean up text before performing evaluation.

    :param str text: text to be preprocessed
    :param bool remove_space: whether remove white space

    :return: preprocessed text
    :rtype: str
    """
    txt = re.sub(SURROUNDING_SEPS_RX, "", txt)

    if remove_space:
        txt = re.sub("\s+", "", txt)

    txt = re.sub(MULTIPLE_SEPS_RX, SEPARATOR, txt)

    txt = re.sub(TAG_RX, "", txt)

    txt = re.sub(TAILING_SEP_RX, "", txt).strip()

    return txt
# Buggy code
def _binary_representation(txt: str, verbose: bool = False):
    """
    Transform text to {0, 1} sequence

    where (1) indicates that the corresponding character is the beginning of
    a word. For example, ผม|ไม่|ชอบ|กิน|ผัก -> 10100...

    :param str txt: input text that we want to transform
    :param bool verbose: for debugging purposes

    :return: {0, 1} sequence
    :rtype: str
    """

    chars = np.array(list(txt))

    boundary = np.argwhere(chars == SEPARATOR).reshape(-1)
    boundary = boundary - np.array(range(boundary.shape[0]))

    bin_rept = np.zeros(len(txt) - boundary.shape[0])
    bin_rept[list(boundary) + [0]] = 1

    sample_wo_seps = list(txt.replace(SEPARATOR, ""))

    # sanity check
    assert len(sample_wo_seps) == len(bin_rept)

    if verbose:
        for c, m in zip(sample_wo_seps, bin_rept):
            print("%s -- %d" % (c, m))

    return bin_rept


# Traceback (ModuleNotFoundError)
# Install with no extras
pip install pythainlp

python
Python 3.7.6 (default, Dec 30 2019, 19:38:26)
[Clang 11.0.0 (clang-1100.0.33.16)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
import pythainlp
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/__init__.py", line 26, in <module>
from pythainlp.benchmarks import benchmark
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/benchmarks/__init__.py", line 1, in <module>
from .word_tokenization import benchmark
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/benchmarks/word_tokenization.py", line 6, in <module>
import numpy as np
ModuleNotFoundError: No module named 'numpy'

# Fixed code
def _binary_representation(txt: str, verbose: bool = False):
    """
    Transform text to {0, 1} sequence.

    where (1) indicates that the corresponding character is the beginning of
    a word. For example, ผม|ไม่|ชอบ|กิน|ผัก -> 10100...

    :param str txt: input text that we want to transform
    :param bool verbose: for debugging purposes

    :return: {0, 1} sequence
    :rtype: str
    """
    chars = np.array(list(txt))

    boundary = np.argwhere(chars == SEPARATOR).reshape(-1)
    boundary = boundary - np.array(range(boundary.shape[0]))

    bin_rept = np.zeros(len(txt) - boundary.shape[0])
    bin_rept[list(boundary) + [0]] = 1

    sample_wo_seps = list(txt.replace(SEPARATOR, ""))

    # sanity check
    assert len(sample_wo_seps) == len(bin_rept)

    if verbose:
        for c, m in zip(sample_wo_seps, bin_rept):
            print("%s -- %d" % (c, m))

    return bin_rept
# Buggy code
def _find_word_boudaries(bin_reps) -> list:
    """
    Find start and end location of each word

    :param str bin_reps: binary representation of a text

    :return: list of tuples (start, end)
    :rtype: list[tuple(int, int)]
    """

    boundary = np.argwhere(bin_reps == 1).reshape(-1)
    start_idx = boundary
    end_idx = boundary[1:].tolist() + [bin_reps.shape[0]]

    return list(zip(start_idx, end_idx))


# Traceback (ModuleNotFoundError)
# Install with no extras
pip install pythainlp

python
Python 3.7.6 (default, Dec 30 2019, 19:38:26)
[Clang 11.0.0 (clang-1100.0.33.16)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
import pythainlp
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/__init__.py", line 26, in <module>
from pythainlp.benchmarks import benchmark
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/benchmarks/__init__.py", line 1, in <module>
from .word_tokenization import benchmark
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/benchmarks/word_tokenization.py", line 6, in <module>
import numpy as np
ModuleNotFoundError: No module named 'numpy'

# Fixed code
def _find_word_boudaries(bin_reps) -> list:
    """
    Find start and end location of each word.

    :param str bin_reps: binary representation of a text

    :return: list of tuples (start, end)
    :rtype: list[tuple(int, int)]
    """
    boundary = np.argwhere(bin_reps == 1).reshape(-1)
    start_idx = boundary
    end_idx = boundary[1:].tolist() + [bin_reps.shape[0]]

    return list(zip(start_idx, end_idx))
# Buggy code
def _find_words_correctly_tokenised(
    ref_boundaries: list, predicted_boundaries: list
) -> tuple:
    """
    Find whether each word is correctly tokenized

    :param list[tuple(int, int)] ref_boundaries: word boundaries of reference tokenization
    :param list[tuple(int, int)] predicted_boundaries: word boundareies of predicted tokenization

    :return: binary sequence where 1 indicates the corresponding word is tokenized correctly
    :rtype: tuple[int]
    """

    ref_b = dict(zip(ref_boundaries, [1] * len(ref_boundaries)))

    labels = tuple(map(lambda x: ref_b.get(x, 0), predicted_boundaries))
    return labels


# Traceback (ModuleNotFoundError)
# Install with no extras
pip install pythainlp

python
Python 3.7.6 (default, Dec 30 2019, 19:38:26)
[Clang 11.0.0 (clang-1100.0.33.16)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
import pythainlp
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/__init__.py", line 26, in <module>
from pythainlp.benchmarks import benchmark
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/benchmarks/__init__.py", line 1, in <module>
from .word_tokenization import benchmark
File "/Users/maybeno/workspace/Envs/newspaper-nvz7rtlC/lib/python3.7/site-packages/pythainlp/benchmarks/word_tokenization.py", line 6, in <module>
import numpy as np
ModuleNotFoundError: No module named 'numpy'

# Fixed code
def _find_words_correctly_tokenised(
    ref_boundaries: list, predicted_boundaries: list
) -> tuple:
    """
    Find whether each word is correctly tokenized.

    :param list[tuple(int, int)] ref_boundaries: word boundaries of reference tokenization
    :param list[tuple(int, int)] predicted_boundaries: word boundareies of predicted tokenization

    :return: binary sequence where 1 indicates the corresponding word is tokenized correctly
    :rtype: tuple[int]
    """
    ref_b = dict(zip(ref_boundaries, [1] * len(ref_boundaries)))

    labels = tuple(map(lambda x: ref_b.get(x, 0), predicted_boundaries))
    return labels
# Buggy code
def get_hashes(self, ireq):
    """
    Given a pinned InstallRequire, returns a set of hashes that represent
    all of the files for a given requirement. It is not acceptable for an
    editable or unpinned requirement to be passed to this function.
    """
    if not is_pinned_requirement(ireq):
        raise TypeError(
            "Expected pinned requirement, not unpinned or editable, got {}".format(ireq)
        )

    # We need to get all of the candidates that match our current version
    # pin, these will represent all of the files that could possibly
    # satisify this constraint.
    all_candidates = self.find_all_candidates(ireq.name)
    candidates_by_version = lookup_table(all_candidates, key=lambda c: c.version)
    matching_versions = list(
        ireq.specifier.filter((candidate.version for candidate in all_candidates))
    )
    matching_candidates = candidates_by_version[matching_versions[0]]

    return {
        self._get_file_hash(candidate.location) for candidate in matching_candidates
    }


# Traceback (SyntaxError)
Collecting python-ldap==2.4.42 (from -r /requirements/dev.txt (line 18))
Downloading python-ldap-2.4.42.tar.gz (297kB)
Complete output from command python setup.py egg_info:
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/tmp/pip-build-32v49evs/python-ldap/setup.py", line 53
print name + ': ' + cfg.get('_ldap', name)
^
SyntaxError: invalid syntax

# Fixed code
def get_hashes(self, ireq):
    """
    Given a pinned InstallRequire, returns a set of hashes that represent
    all of the files for a given requirement. It is not acceptable for an
    editable or unpinned requirement to be passed to this function.
    """
    if not is_pinned_requirement(ireq):
        raise TypeError(
            "Expected pinned requirement, not unpinned or editable, got {}".format(ireq)
        )

    # We need to get all of the candidates that match our current version
    # pin, these will represent all of the files that could possibly
    # satisfy this constraint.
    with self.allow_all_wheels():
        all_candidates = self.find_all_candidates(ireq.name)
        candidates_by_version = lookup_table(all_candidates, key=lambda c: c.version)
        matching_versions = list(
            ireq.specifier.filter((candidate.version for candidate in all_candidates))
        )
        matching_candidates = candidates_by_version[matching_versions[0]]

    return {
        self._get_file_hash(candidate.location) for candidate in matching_candidates
    }
# Buggy code
def repo_all_list(self, project_key):
    """
    Get all repositories list from project
    :param project_key:
    :return:
    """
    url = self._url_repos(project_key)
    return self.repo_list(url, limit=None)


# Traceback (requests.exceptions.HTTPError)
Traceback (most recent call last):
File "[ProjectPath]/task/fetch_from_git.py", line 112, in <module>
repo_all = list_of_repo()
File "[ProjectPath]/task/fetch_from_git.py", line 17, in list_of_repo
list_of_repositories = fetch()
File "[ProjectPath]\tools\bitbucket.py", line 51, in fetch
for repo in bitbucket_api.repo_all_list(project['key']):
File "[ProjectPath]\.tox\py3\lib\site-packages\atlassian\bitbucket.py", line 659, in repo_all_list
return self.repo_list(url, limit=None)
File "[ProjectPath]\.tox\py3\lib\site-packages\atlassian\bitbucket.py", line 650, in repo_list
return self._get_paged(url, params=params)
File "[ProjectPath]\.tox\py3\lib\site-packages\atlassian\bitbucket.py", line 32, in _get_paged
response = self.get(url, params=params)
File "[ProjectPath]\.tox\py3\lib\site-packages\atlassian\rest_client.py", line 257, in get
response = self.request(
File "[ProjectPath]\.tox\py3\lib\site-packages\atlassian\rest_client.py", line 233, in request
response.raise_for_status()
File "[ProjectPath]\.tox\py3\lib\site-packages\requests\models.py", line 941, in raise_for_status
raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 404 Client Error:  for url: https://[onPremURL]/rest/api/1.0/projects/rest/api/1.0/projects/ABACUS/repos/repos

# Fixed code
def repo_all_list(self, project_key):
    """
    Get all repositories list from project
    :param project_key:
    :return:
    """
    return self.repo_list(project_key, limit=None)
# Buggy code
def build(target_python, requirements):
    """
    Builds an APK given a target Python and a set of requirements.
    """
    if not requirements:
        return
    testapp = "setup_testapp_python2.py"
    android_sdk_home = os.environ["ANDROID_SDK_HOME"]
    android_ndk_home = os.environ["ANDROID_NDK_HOME"]
    crystax_ndk_home = os.environ["CRYSTAX_NDK_HOME"]
    if target_python == TargetPython.python3crystax:
        android_ndk_home = crystax_ndk_home
        testapp = "setup_testapp_python3.py"
    requirements.add(target_python.name)
    requirements = ",".join(requirements)
    print("requirements:", requirements)
    with current_directory("testapps/"):
        try:
            for line in sh.python(
                testapp,
                "apk",
                "--sdk-dir",
                android_sdk_home,
                "--ndk-dir",
                android_ndk_home,
                "--bootstrap",
                "sdl2",
                "--requirements",
                requirements,
                _err_to_out=True,
                _iter=True,
            ):
                print(line)
        except sh.ErrorReturnCode as e:
            raise


# Traceback (KeyError)
Traceback (most recent call last):
File "./ci/rebuild_updated_recipes.py", line 99, in <module>
main()
File "./ci/rebuild_updated_recipes.py", line 95, in main
build(target_python, recipes)
File "./ci/rebuild_updated_recipes.py", line 59, in build
crystax_ndk_home = os.environ['CRYSTAX_NDK_HOME']
File "/home/user/venv/lib/python2.7/UserDict.py", line 40, in __getitem__
raise KeyError(key)
KeyError: 'CRYSTAX_NDK_HOME'

# Fixed code
def build(target_python, requirements):
    """
    Builds an APK given a target Python and a set of requirements.
    """
    if not requirements:
        return
    testapp = "setup_testapp_python2.py"
    android_sdk_home = os.environ["ANDROID_SDK_HOME"]
    android_ndk_home = os.environ["ANDROID_NDK_HOME"]
    if target_python == TargetPython.python3:
        testapp = "setup_testapp_python3.py"
    requirements.add(target_python.name)
    requirements = ",".join(requirements)
    print("requirements:", requirements)
    with current_directory("testapps/"):
        try:
            for line in sh.python(
                testapp,
                "apk",
                "--sdk-dir",
                android_sdk_home,
                "--ndk-dir",
                android_ndk_home,
                "--bootstrap",
                "sdl2",
                "--requirements",
                requirements,
                _err_to_out=True,
                _iter=True,
            ):
                print(line)
        except sh.ErrorReturnCode as e:
            raise
# Buggy code
def main():
    target_python = TargetPython.python3crystax
    recipes = modified_recipes()
    print("recipes modified:", recipes)
    recipes -= CORE_RECIPES
    print("recipes to build:", recipes)
    context = Context()
    build_order, python_modules, bs = get_recipe_order_and_bootstrap(
        context, recipes, None
    )
    # fallback to python2 if default target is not compatible
    if target_python.name not in build_order:
        print("incompatible with {}".format(target_python.name))
        target_python = TargetPython.python2
        print("falling back to {}".format(target_python.name))
    # removing the known broken recipe for the given target
    broken_recipes = BROKEN_RECIPES[target_python]
    recipes -= broken_recipes
    print("recipes to build (no broken):", recipes)
    build(target_python, recipes)


# Traceback (KeyError)
Traceback (most recent call last):
File "./ci/rebuild_updated_recipes.py", line 99, in <module>
main()
File "./ci/rebuild_updated_recipes.py", line 95, in main
build(target_python, recipes)
File "./ci/rebuild_updated_recipes.py", line 59, in build
crystax_ndk_home = os.environ['CRYSTAX_NDK_HOME']
File "/home/user/venv/lib/python2.7/UserDict.py", line 40, in __getitem__
raise KeyError(key)
KeyError: 'CRYSTAX_NDK_HOME'

# Fixed code
def main():
    target_python = TargetPython.python3
    recipes = modified_recipes()
    print("recipes modified:", recipes)
    recipes -= CORE_RECIPES
    print("recipes to build:", recipes)
    context = Context()
    build_order, python_modules, bs = get_recipe_order_and_bootstrap(
        context, recipes, None
    )
    # fallback to python2 if default target is not compatible
    if target_python.name not in build_order:
        print("incompatible with {}".format(target_python.name))
        target_python = TargetPython.python2
        print("falling back to {}".format(target_python.name))
    # removing the known broken recipe for the given target
    broken_recipes = BROKEN_RECIPES[target_python]
    recipes -= broken_recipes
    print("recipes to build (no broken):", recipes)
    build(target_python, recipes)
# Buggy code
def _get_command_to_run(query):
    params = shlex_split(query.decode("utf-8"))
    __check_query_params(params)

    cmd = []
    for c in command:
        if c == "{{QUERY}}":
            cmd.extend(params)
        else:
            cmd.append(c)

    return cmd


# Traceback (AttributeError)
: Traceback (most recent call last):
:   File "/opt/searx/searx/searx/search.py", line 281, in search_one_offline_request_safe
:     search_results = search_one_offline_request(engine, query, request_params)
:   File "/opt/searx/searx/searx/search.py", line 274, in search_one_offline_request
:     return engine.search(query, request_params)
:   File "/opt/searx/searx/searx/engines/command.py", line 70, in search
:     cmd = _get_command_to_run(query)
:   File "/opt/searx/searx/searx/engines/command.py", line 83, in _get_command_to_run
:     params = shlex_split(query.decode('utf-8'))
: AttributeError: 'str' object has no attribute 'decode'

# Fixed code
def _get_command_to_run(query):
    params = shlex_split(query)
    __check_query_params(params)

    cmd = []
    for c in command:
        if c == "{{QUERY}}":
            cmd.extend(params)
        else:
            cmd.append(c)

    return cmd
# Buggy code
def __init__(self, **kwargs):
    super().__init__(**kwargs)
    Window.bind(on_resize=self.check_position_caller)
    self.register_event_type("on_dismiss")
    self.register_event_type("on_enter")
    self.register_event_type("on_leave")
    self.menu = self.ids.md_menu
    self.target_height = 0


# Traceback (TypeError)
Traceback (most recent call last):
File "C:/Users/User/PycharmProjects/New MO Inventory System/sigh.py", line 24, in <module>
App().run()
File "C:\Users\User\AppData\Local\Programs\Python\Python38\lib\site-packages\kivy\app.py", line 949, in run
self._run_prepare()
File "C:\Users\User\AppData\Local\Programs\Python\Python38\lib\site-packages\kivy\app.py", line 919, in _run_prepare
root = self.build()
File "C:/Users/User/PycharmProjects/New MO Inventory System/sigh.py", line 21, in build
b.add_widget(Layout())
File "C:/Users/User/PycharmProjects/New MO Inventory System/sigh.py", line 9, in __init__
self.b = MDBoxLayout(orientation='vertical')
File "kivy\properties.pyx", line 498, in kivy.properties.Property.__set__
File "kivy\properties.pyx", line 533, in kivy.properties.Property.set
File "kivy\properties.pyx", line 1176, in kivy.properties.BoundedNumericProperty.check
TypeError: '<' not supported between instances of 'MDBoxLayout' and 'float'

# Fixed code
def __init__(self, **kwargs):
    super().__init__(**kwargs)
    Window.bind(on_resize=self.check_position_caller)
    Window.bind(on_maximize=self.set_menu_properties)
    Window.bind(on_restore=self.set_menu_properties)
    self.register_event_type("on_dismiss")
    self.register_event_type("on_enter")
    self.register_event_type("on_leave")
    self.menu = self.ids.md_menu
    self.target_height = 0
# Buggy code
def angle(x1, x2):
    xx = np.arccos((x1 * x2).sum(axis=0))
    xx[np.isnan(xx)] = 0
    return xx


# Traceback (TypeError)
======================================================================
ERROR: dipy.core.tests.test_sphere.test_interp_rbf
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/travis/build/nipy/dipy/venv/lib/python3.4/site-packages/nose/case.py", line 198, in runTest
self.test(*self.arg)
File "/home/travis/build/nipy/dipy/venv/lib/python3.4/site-packages/dipy/core/tests/test_sphere.py", line 375, in test_interp_rbf
interp_data_a = interp_rbf(data, s0, s1, norm="angle")
File "/home/travis/build/nipy/dipy/venv/lib/python3.4/site-packages/dipy/core/sphere.py", line 572, in interp_rbf
**kwargs)
File "/home/travis/build/nipy/dipy/venv/lib/python3.4/site-packages/scipy/interpolate/rbf.py", line 241, in __init__
self.nodes = linalg.solve(self.A, self.di)
File "/home/travis/build/nipy/dipy/venv/lib/python3.4/site-packages/scipy/interpolate/rbf.py", line 247, in A
r = squareform(pdist(self.xi.T, self.norm))  # Pairwise norm
File "/home/travis/build/nipy/dipy/venv/lib/python3.4/site-packages/scipy/spatial/distance.py", line 2030, in pdist
dm[k] = metric(X[i], X[j], **kwargs)
File "/home/travis/build/nipy/dipy/venv/lib/python3.4/site-packages/dipy/core/sphere.py", line 544, in angle
xx[np.isnan(xx)] = 0
TypeError: 'numpy.float64' object does not support item assignment
----------------------------------------------------------------------

# Fixed code
def angle(x1, x2):
    xx = np.arccos(np.clip((x1 * x2).sum(axis=0), -1, 1))
    return np.nan_to_num(xx)
# Buggy code
def lb_forecast(sh_order):
    r"""Returns the Laplace-Beltrami regularization matrix for FORECAST"""
    n_c = int((sh_order + 1) * (sh_order + 2) / 2)
    diag_lb = np.zeros(n_c)
    counter = 0
    for l in range(0, sh_order + 1, 2):
        for m in range(-l, l + 1):
            diag_lb[counter] = (l * (l + 1)) ** 2
            counter += 1

    return np.diag(diag_lb)


# Traceback (AssertionError)
dipy (master)$nosetests dipy/reconst/tests/test_forecast.py
F.....
======================================================================
FAIL: dipy.reconst.tests.test_forecast.test_forecast_positive_constrain
----------------------------------------------------------------------
Traceback (most recent call last):
File "/Users/arokem/.virtualenvs/dipy/lib/python3.7/site-packages/nose/case.py", line 198, in runTest
self.test(*self.arg)
File "/Users/arokem/.virtualenvs/dipy/lib/python3.7/site-packages/numpy/testing/_private/decorators.py", line 155, in skipper_func
return f(*args, **kwargs)
File "/Users/arokem/source/dipy/dipy/reconst/tests/test_forecast.py", line 53, in test_forecast_positive_constrain
assert_almost_equal(fodf[fodf < 0].sum(), 0, 2)
File "/Users/arokem/.virtualenvs/dipy/lib/python3.7/site-packages/numpy/testing/_private/utils.py", line 584, in assert_almost_equal
raise AssertionError(_build_err_msg())
AssertionError:
Arrays are not almost equal to 2 decimals
ACTUAL: -0.015931951384411995
DESIRED: 0

----------------------------------------------------------------------
Ran 6 tests in 0.264s

# Fixed code
def lb_forecast(sh_order):
    r"""Returns the Laplace-Beltrami regularization matrix for FORECAST"""
    n_c = int((sh_order + 1) * (sh_order + 2) / 2)
    diag_lb = np.zeros(n_c)
    counter = 0
    for l in range(0, sh_order + 1, 2):
        stop = 2 * l + 1 + counter
        diag_lb[counter:stop] = (l * (l + 1)) ** 2
        counter = stop

    return np.diag(diag_lb)
# Buggy code
def comparator(operator: Comparator) -> Comparator:
    """Wrap a Version binary op method in a type-check."""

    @wraps(operator)
    def wrapper(self: "Version", other: Comparable) -> bool:
        comparable_types = (
            Version,
            dict,
            tuple,
            list,
            *String.__args__,  # type: ignore
        )
        if not isinstance(other, comparable_types):
            raise TypeError(
                "other type %r must be in %r" % (type(other), comparable_types)
            )
        return operator(self, other)

    return wrapper


# Traceback (TypeError)
class Foo:
...    pass

v1 = semver.version.Version(1, 2, 3)
v1 < Foo()
Traceback (most recent call last)
...
TypeError: other type <class '__main__.Foo'> must be in (<class 'semver.version.Version'>, <class 'dict'>, <class 'tuple'>, <class 'list'>, <class 'str'>, <class 'bytes'>)

# Fixed code
def comparator(operator: Comparator) -> Comparator:
    """Wrap a Version binary op method in a type-check."""

    @wraps(operator)
    def wrapper(self: "Version", other: Comparable) -> bool:
        comparable_types = (
            Version,
            dict,
            tuple,
            list,
            *String.__args__,  # type: ignore
        )
        if not isinstance(other, comparable_types):
            return NotImplemented
        return operator(self, other)

    return wrapper
# Buggy code
def wrapper(self: "Version", other: Comparable) -> bool:
    comparable_types = (
        Version,
        dict,
        tuple,
        list,
        *String.__args__,  # type: ignore
    )
    if not isinstance(other, comparable_types):
        raise TypeError("other type %r must be in %r" % (type(other), comparable_types))
    return operator(self, other)


# Traceback (TypeError)
class Foo:
...    pass

v1 = semver.version.Version(1, 2, 3)
v1 < Foo()
Traceback (most recent call last)
...
TypeError: other type <class '__main__.Foo'> must be in (<class 'semver.version.Version'>, <class 'dict'>, <class 'tuple'>, <class 'list'>, <class 'str'>, <class 'bytes'>)

# Fixed code
def wrapper(self: "Version", other: Comparable) -> bool:
    comparable_types = (
        Version,
        dict,
        tuple,
        list,
        *String.__args__,  # type: ignore
    )
    if not isinstance(other, comparable_types):
        return NotImplemented
    return operator(self, other)
# Buggy code
def comparator(operator):
    """Wrap a VersionInfo binary op method in a type-check."""

    @wraps(operator)
    def wrapper(self, other):
        comparable_types = (VersionInfo, dict, tuple)
        if not isinstance(other, comparable_types):
            raise TypeError(
                "other type %r must be in %r" % (type(other), comparable_types)
            )
        return operator(self, other)

    return wrapper


# Traceback (TypeError)
v1 < [1, 2, 4]
Traceback (most recent call last):
...
TypeError: other type <class 'list'> must be in (<class 'semver.VersionInfo'>, <class 'dict'>, <class 'tuple'>)
v1 < "1.2.4"
Traceback (most recent call last):
...
TypeError: other type <class 'str'> must be in (<class 'semver.VersionInfo'>, <class 'dict'>, <class 'tuple'>)

# Fixed code
def comparator(operator):
    """Wrap a VersionInfo binary op method in a type-check."""

    @wraps(operator)
    def wrapper(self, other):
        comparable_types = (VersionInfo, dict, tuple, list, str)
        if not isinstance(other, comparable_types):
            raise TypeError(
                "other type %r must be in %r" % (type(other), comparable_types)
            )
        return operator(self, other)

    return wrapper
# Buggy code
def wrapper(self, other):
    comparable_types = (VersionInfo, dict, tuple)
    if not isinstance(other, comparable_types):
        raise TypeError("other type %r must be in %r" % (type(other), comparable_types))
    return operator(self, other)


# Traceback (TypeError)
v1 < [1, 2, 4]
Traceback (most recent call last):
...
TypeError: other type <class 'list'> must be in (<class 'semver.VersionInfo'>, <class 'dict'>, <class 'tuple'>)
v1 < "1.2.4"
Traceback (most recent call last):
...
TypeError: other type <class 'str'> must be in (<class 'semver.VersionInfo'>, <class 'dict'>, <class 'tuple'>)

# Fixed code
def wrapper(self, other):
    comparable_types = (VersionInfo, dict, tuple, list, str)
    if not isinstance(other, comparable_types):
        raise TypeError("other type %r must be in %r" % (type(other), comparable_types))
    return operator(self, other)
# Buggy code
def run(self):
    super(CleanCommand, self).run()
    delete_in_root = ["build", ".cache", "dist", ".eggs", "*.egg-info", ".tox"]
    delete_everywhere = ["__pycache__", "*.pyc"]
    for candidate in delete_in_root:
        rmtree_glob(candidate)
    for visible_dir in glob("[A-Za-z0-9]*"):
        for candidate in delete_everywhere:
            rmtree_glob(join(visible_dir, candidate))
            rmtree_glob(join(visible_dir, "*", candidate))


# Traceback (RuntimeError)
ERROR: Execution of '/yocto/build/3.0-zeus/bbb/tmp/work/cortexa8hf-neon-poky-linux-gnueabi/python3-semver/2.9.1-r0/temp/run.do_configure.28554' failed with exit code 1:
running clean
Traceback (most recent call last):
File "setup.py", line 101, in <module>
entry_points={"console_scripts": ["pysemver = semver:main"]},
File "/yocto/build/3.0-zeus/bbb/tmp/work/cortexa8hf-neon-poky-linux-gnueabi/python3-semver/2.9.1-r0/recipe-sysroot-native/usr/lib/python3.7/site-packages/setuptools/__init__.py", line 145, in setup
return distutils.core.setup(**attrs)
File "/yocto/build/3.0-zeus/bbb/tmp/work/cortexa8hf-neon-poky-linux-gnueabi/python3-semver/2.9.1-r0/recipe-sysroot-native/usr/lib/python3.7/distutils/core.py", line 148, in setup
dist.run_commands()
File "/yocto/build/3.0-zeus/bbb/tmp/work/cortexa8hf-neon-poky-linux-gnueabi/python3-semver/2.9.1-r0/recipe-sysroot-native/usr/lib/python3.7/distutils/dist.py", line 966, in run_commands
self.run_command(cmd)
File "/yocto/build/3.0-zeus/bbb/tmp/work/cortexa8hf-neon-poky-linux-gnueabi/python3-semver/2.9.1-r0/recipe-sysroot-native/usr/lib/python3.7/distutils/dist.py", line 985, in run_command
cmd_obj.run()
File "setup.py", line 41, in run
super(CleanCommand, self).run()
File "/yocto/build/3.0-zeus/bbb/tmp/work/cortexa8hf-neon-poky-linux-gnueabi/python3-semver/2.9.1-r0/recipe-sysroot-native/usr/lib/python3.7/distutils/cmd.py", line 176, in run
% self.__class__)
RuntimeError: abstract method -- subclass <class '__main__.Clean'> must override
WARNING: exit code 1 from a shell command.

# Fixed code
def run(self):
    CleanCommand.run(self)
    delete_in_root = ["build", ".cache", "dist", ".eggs", "*.egg-info", ".tox"]
    delete_everywhere = ["__pycache__", "*.pyc"]
    for candidate in delete_in_root:
        rmtree_glob(candidate)
    for visible_dir in glob("[A-Za-z0-9]*"):
        for candidate in delete_everywhere:
            rmtree_glob(join(visible_dir, candidate))
            rmtree_glob(join(visible_dir, "*", candidate))
# Buggy code
def process(args):
    """Process the input from the CLI

    :param args: The parsed arguments
    :type args: :class:`argparse.Namespace`
    :param parser: the parser instance
    :type parser: :class:`argparse.ArgumentParser`
    :return: result of the selected action
    :rtype: str
    """
    if args.which == "bump":
        maptable = {
            "major": "bump_major",
            "minor": "bump_minor",
            "patch": "bump_patch",
            "prerelease": "bump_prerelease",
            "build": "bump_build",
        }
        ver = parse_version_info(args.version)
        # get the respective method and call it
        func = getattr(ver, maptable[args.bump])
        return str(func())

    elif args.which == "compare":
        return str(compare(args.version1, args.version2))


# Traceback (AttributeError)
$ tox -e py36
$ .tox/py36/bin/pysemver
Traceback (most recent call last):
File ".tox/py36/bin/pysemver", line 8, in <module>
sys.exit(main())
File ".tox/py36/lib/python3.6/site-packages/semver.py", line 720, in main
result = process(args)
File ".tox/py36/lib/python3.6/site-packages/semver.py", line 693, in process
if args.which == "bump":
AttributeError: 'Namespace' object has no attribute 'which'

# Fixed code
def process(args):
    """Process the input from the CLI

    :param args: The parsed arguments
    :type args: :class:`argparse.Namespace`
    :param parser: the parser instance
    :type parser: :class:`argparse.ArgumentParser`
    :return: result of the selected action
    :rtype: str
    """
    if not hasattr(args, "which"):
        args.parser.print_help()
        raise SystemExit()
    elif args.which == "bump":
        maptable = {
            "major": "bump_major",
            "minor": "bump_minor",
            "patch": "bump_patch",
            "prerelease": "bump_prerelease",
            "build": "bump_build",
        }
        if args.bump is None:
            # When bump is called without arguments,
            # print the help and exit
            args.parser.parse_args([args.which, "-h"])

        ver = parse_version_info(args.version)
        # get the respective method and call it
        func = getattr(ver, maptable[args.bump])
        return str(func())

    elif args.which == "compare":
        return str(compare(args.version1, args.version2))
# Buggy code
def main(cliargs=None):
    """Entry point for the application script

    :param list cliargs: Arguments to parse or None (=use :class:`sys.argv`)
    :return: error code
    :rtype: int
    """
    try:
        parser = createparser()
        args = parser.parse_args(args=cliargs)
        # args.parser = parser
        result = process(args)
        print(result)
        return 0

    except (ValueError, TypeError) as err:
        print("ERROR", err, file=sys.stderr)
        return 2


# Traceback (AttributeError)
$ tox -e py36
$ .tox/py36/bin/pysemver
Traceback (most recent call last):
File ".tox/py36/bin/pysemver", line 8, in <module>
sys.exit(main())
File ".tox/py36/lib/python3.6/site-packages/semver.py", line 720, in main
result = process(args)
File ".tox/py36/lib/python3.6/site-packages/semver.py", line 693, in process
if args.which == "bump":
AttributeError: 'Namespace' object has no attribute 'which'

# Fixed code
def main(cliargs=None):
    """Entry point for the application script

    :param list cliargs: Arguments to parse or None (=use :class:`sys.argv`)
    :return: error code
    :rtype: int
    """
    try:
        parser = createparser()
        args = parser.parse_args(args=cliargs)
        # Save parser instance:
        args.parser = parser
        result = process(args)
        print(result)
        return 0

    except (ValueError, TypeError) as err:
        print("ERROR", err, file=sys.stderr)
        return 2
# Buggy code
def record_from_name(name):
    """Search `dastcom.idx` and return logical records that match a given string.

    Body name, SPK-ID, or alternative designations can be used.

    Parameters
    ----------
    name : str
        Body name.

    Returns
    -------
    records : list (int)
        DASTCOM5 database logical records matching str.

    """
    records = []
    lines = string_record_from_name(name)
    for line in lines:
        records.append(int(line[:6].lstrip()))
    return records


# Traceback (OSError)
---------------------------------------------------------------------------
OSError                                   Traceback (most recent call last)
<ipython-input-9-3bb5fa7c99be> in <module>
----> 1 halleys = dastcom5.orbit_from_name("1P")
2
3 frame = StaticOrbitPlotter()
4 frame.plot(halleys[0], label="Halley")
5 frame.plot(halleys[5], label="Halley")

~/.pyenv/versions/3.8.0/envs/poliastro38/lib/python3.8/site-packages/poliastro/neos/dastcom5.py in orbit_from_name(name)
339     orbits = []
340     for record in records:
--> 341         orbits.append(orbit_from_record(record))
342     return orbits
343

~/.pyenv/versions/3.8.0/envs/poliastro38/lib/python3.8/site-packages/poliastro/neos/dastcom5.py in orbit_from_record(record)
359
360         """
--> 361     body_data = read_record(record)
362     a = body_data["A"].item() * u.au
363     ecc = body_data["EC"].item() * u.one

~/.pyenv/versions/3.8.0/envs/poliastro38/lib/python3.8/site-packages/poliastro/neos/dastcom5.py in read_record(record)
508
509         with open(ast_path, "rb") as f:
--> 510             f.seek(phis_rec, os.SEEK_SET)
511             body_data = np.fromfile(f, dtype=AST_DTYPE, count=1)
512     else:

OSError: [Errno 22] Invalid argument

# Fixed code
def record_from_name(name):
    """Search `dastcom.idx` and return logical records that match a given string.

    Body name, SPK-ID, or alternative designations can be used.

    Parameters
    ----------
    name : str
        Body name.

    Returns
    -------
    records : list (int)
        DASTCOM5 database logical records matching str.

    """
    records = []
    lines = string_record_from_name(name)
    for line in lines:
        records.append(int(line[:8].lstrip()))
    return records
# Buggy code
def norm(vec):
    r"""Returns the norm of a 3 dimension vector.


    .. math::

        \left \| \vec{v} \right \| = \sqrt{\sum_{i=1}^{n}v_{i}^2}

    Parameters
    ----------

    vec: ndarray
        Dimension 3 vector.


    Examples
    --------
    >>> from poliastro.core.util import norm
    >>> from astropy import units as u
    >>> vec = [1, 1, 1] * u.m
    >>> norm(vec)
    1.7320508075688772

    """

    vec = 1.0 * vec  # Cast to float
    return np.sqrt(vec.dot(vec))


# Traceback (astropy.units.core.UnitConversionError)
_____________________ [doctest] poliastro.core.util.cross ______________________
143     b : ndarray
144         3 Dimension vector.
145
146     Examples
147     --------
148     >>> from poliastro.core.util import cross
149     >>> from astropy import units as u
150     >>> i = [1, 0, 0] * u.m
151     >>> j = [0, 1, 0] * u.m
152     >>> cross(i, j)
UNEXPECTED EXCEPTION: TypeError('only dimensionless scalar quantities can be converted to Python scalars')
Traceback (most recent call last):

File "/usr/lib/python3/dist-packages/astropy/units/quantity.py", line 715, in to_value
scale = self.unit._to(unit)

File "/usr/lib/python3/dist-packages/astropy/units/core.py", line 953, in _to
"'{0!r}' is not a scaled version of '{1!r}'".format(self, other))

astropy.units.core.UnitConversionError: 'Unit("m2")' is not a scaled version of 'Unit(dimensionless)'

# Fixed code
def norm(vec):
    r"""Returns the norm of a 3 dimension vector.


    .. math::

        \left \| \vec{v} \right \| = \sqrt{\sum_{i=1}^{n}v_{i}^2}

    Parameters
    ----------

    vec: ndarray
        Dimension 3 vector.


    Examples
    --------
    >>> vec = np.array([1, 1, 1])
    >>> norm(vec)
    1.7320508075688772

    """

    vec = 1.0 * vec  # Cast to float
    return np.sqrt(vec.dot(vec))