Python shutil.rmtree() Examples

def test_multiprocessing_download_successful():
    """ test download with multiprocessing """
    tmp = tempfile.mkdtemp()
    tmpfile = os.path.join(tmp, 'README.md')
    process_list = []
    # test it with 10 processes
    for i in range(10):
        process_list.append(mp.Process(
            target=_download_successful, args=(tmpfile,)))
        process_list[i].start()
    for i in range(10):
        process_list[i].join()
    assert os.path.getsize(tmpfile) > 100, os.path.getsize(tmpfile)
    # check only one file we want left
    pattern = os.path.join(tmp, 'README.md*')
    assert len(glob.glob(pattern)) == 1, glob.glob(pattern)
    # delete temp dir
    shutil.rmtree(tmp) 

def __call__(self, args, env):
        samples_dir = env.get('samples-dir')

        print("Downloading unique objects to {}.".format(samples_dir))

        src_dir = self.download_files([_URL], env=env, dir=env.get('cache-dir'))
        path = os.path.join(src_dir, "ObjectsAll.zip")

        zipf = zipfile.ZipFile(path, 'r')
        zipf.extractall(src_dir)
        zipf.close()

        for file in os.listdir(os.path.join(src_dir, "OBJECTSALL")):
            shutil.copy(os.path.join(src_dir, "OBJECTSALL", file), samples_dir)

        shutil.rmtree(src_dir)

        print("Finished downloading unique objects.") 

def __call__(self, args, env):
        samples_dir = env.get('samples-dir')
        for label in ("cat", "dog"):
            dest = os.path.join(samples_dir, label)
            if os.path.exists(dest):
                raise VergeMLError("Directory {} already exists in samples dir: {}".format(label, dest))
        print("Downloading cats and dogs to {}.".format(samples_dir))
        src_dir = self.download_files([(_URL, "catsdogs.zip")], env)
        path = os.path.join(src_dir, "catsdogs.zip")

        print("Extracting data.")
        zipf = zipfile.ZipFile(path, 'r')
        zipf.extractall(src_dir)
        zipf.close()

        for file, dest in (("PetImages/Dog", "dog"), ("PetImages/Cat", "cat")):
            shutil.copytree(os.path.join(src_dir, file), os.path.join(samples_dir, dest))

        shutil.rmtree(src_dir)

        # WTF?
        os.unlink(os.path.join(samples_dir, "cat", "666.jpg"))
        os.unlink(os.path.join(samples_dir, "dog", "11702.jpg"))

        print("Finished downloading cats and dogs.") 

def do_iteration(self, mutation_fn, aggression):
        """
        This method is called with an output mutation filename and a
        real aggression (see :ref:`aggression`) indicating the amount
        of aggression the fuzzing algorithm should use.  *mutation_fn*
        is unique for every invokation of :meth:`do_iteration`.

        It is an error for this method not to write the mutated
        template to *mutation_fn* before returning a result.  If a
        result is not found, the mutation filename may be written to
        if needed, but it is not required.

        If a notable result is found, it should be returned as a
        :class:`FuzzResult` instance.  This will be stored and reported
        to the ALF central server at the next check-in interval.  A
        return of None indicates a result was not found.

        The filenames of any temporary files or folders created during
        execution can be safely removed using :func:`alf.delete`.  This
        is safer than using :func:`os.remove` or :func:`shutil.rmtree`
        directly.  *mutation_fn* does not need to be deleted, it is
        cleaned up automatically.
        """
        raise NotImplementedError() 

def _delete_directory_contents(self, dirpath, filter_func):
        """Delete all files in a directory.

        :param dirpath: path to directory to clear
        :type dirpath: ``unicode`` or ``str``
        :param filter_func function to determine whether a file shall be
            deleted or not.
        :type filter_func ``callable``

        """
        if os.path.exists(dirpath):
            for filename in os.listdir(dirpath):
                if not filter_func(filename):
                    continue
                path = os.path.join(dirpath, filename)
                if os.path.isdir(path):
                    shutil.rmtree(path)
                else:
                    os.unlink(path)
                self.logger.debug('deleted : %r', path) 

def test_extraction():
    import shutil

    src = 'c:/Users/shinj/Downloads/clonezilla-live-2.5.2-31-amd64.iso'
    tmp_dir = 'c:/Users/shinj/Documents/tmp'
    for subdir, pattern in [
            ('single_string', 'EFI/'),
            ('single_list', ['EFI/']),
            ('multi', ['EFI/', 'syslinux/']),
            ('all', None) ]:
        dest_dir = os.path.join(tmp_dir, subdir)
        if os.path.exists(dest_dir):
            shutil.rmtree(dest_dir)
        os.mkdir(dest_dir)
        args = [src, dest_dir]
        if pattern is not None:
            args.append(pattern)
        print ('Calling extract_iso(%s)' % args)
        extract_iso(*args) 

def save_dictionary(config):
    """
    :param config: config
    :return:
    """
    if config.save_dict is True:
        if os.path.exists(config.dict_directory):
            shutil.rmtree(config.dict_directory)
        if not os.path.isdir(config.dict_directory):
            os.makedirs(config.dict_directory)

        config.word_dict_path = "/".join([config.dict_directory, config.word_dict])
        config.label_dict_path = "/".join([config.dict_directory, config.label_dict])
        print("word_dict_path : {}".format(config.word_dict_path))
        print("label_dict_path : {}".format(config.label_dict_path))
        save_dict2file(config.create_alphabet.word_alphabet.words2id, config.word_dict_path)
        save_dict2file(config.create_alphabet.label_alphabet.words2id, config.label_dict_path)
        # copy to mulu
        print("copy dictionary to {}".format(config.save_dir))
        shutil.copytree(config.dict_directory, "/".join([config.save_dir, config.dict_directory]))


# load data / create alphabet / create iterator 

def test_creation(self):
        if os.path.exists(self.base_dir):
            shutil.rmtree(self.checkpoints_dir, ignore_errors=True)

        try:
            FileStructManager(base_dir=self.base_dir, is_continue=False)
        except FileStructManager.FSMException as err:
            self.fail("Raise error when base directory exists: [{}]".format(err))

        self.assertFalse(os.path.exists(self.base_dir))

        try:
            FileStructManager(base_dir=self.base_dir, is_continue=False)
        except FileStructManager.FSMException as err:
            self.fail("Raise error when base directory exists but empty: [{}]".format(err))

        os.makedirs(os.path.join(self.base_dir, 'new_dir'))
        try:
            FileStructManager(base_dir=self.base_dir, is_continue=False)
        except:
            self.fail("Error initialize when exists non-registered folders in base directory")

        shutil.rmtree(self.base_dir, ignore_errors=True) 

def _download_straight_dope_notebooks():
    """Downloads the Straight Dope Notebooks.

    Returns:
        True if it succeeds in downloading the notebooks without error.
    """
    logging.info('Cleaning and setting up notebooks directory "{}"'.format(NOTEBOOKS_DIR))
    shutil.rmtree(NOTEBOOKS_DIR, ignore_errors=True)

    cmd = [GIT_PATH,
           'clone',
           GIT_REPO,
           NOTEBOOKS_DIR]

    proc, msg = _run_command(cmd)

    if proc.returncode != 0:
        err_msg = 'Error downloading Straight Dope notebooks.\n'
        err_msg += msg
        logging.error(err_msg)
        return False
    return True 

def dotplot2(s1, s2, wordsize=5, overlap=5, verbose=1):
        """ verbose = 0 (no progress), 1 (progress if s1 and s2 are long) or
        2 (progress in any case) """
        doProgress = False
        if verbose > 1 or len(s1)*len(s2) > 1e6:
            doProgress = True

        mat = numpy.ones(((len(s1)-wordsize)/overlap+2, (len(s2)-wordsize)/overlap+2))

        for i in range(0, len(s1)-wordsize, overlap):
            if i % 1000 == 0 and doProgress:
                logging.info("  dotplot progress: {} of {} rows done".format(i, len(s1)-wordsize))
            word1 = s1[i:i+wordsize]

            for j in range(0, len(s2)-wordsize, overlap):
                word2 = s2[j:j+wordsize]

                if word1 == word2 or word1 == word2[::-1]:
                    mat[i/overlap, j/overlap] = 0
        
        imgData = None
        tempDir = tempfile.mkdtemp()
        try:
            path = os.path.join(tempDir, "dotplot.png")
            misc.imsave(path, mat)
            imgData = open(path).read()
        except Exception as e:
            logging.error("Error generating dotplots:'{}'".format(e))
        finally:
            shutil.rmtree(tempDir)
        return imgData 

def __del__(self):
        '''
            Called when the instance is about to be destroyed.
        '''
        if hasattr(self, '_tmpdir'):
            self._logger.info('Clean up temporary directory "{0}".'.format(self._tmpdir))
            shutil.rmtree(self._tmpdir) 

def fix_plugin_directories(dest):
    """
    Loops through all folders in the output directory, reads the their manifest
    file, and renames the directory to the standard <platform>_<guid> format
    """
    # Loop through directories in the destination directory
    for existing_dir in os.listdir(dest):
        existing_path = os.path.join(dest, existing_dir)

        # Skip non-directories
        if not os.path.isdir(existing_path):
            continue

        try:
            with open(os.path.join(existing_path, 'manifest.json')) as m:
                data = json.load(m)
                platform = data['platform']
                guid = data['guid']

                # Close json file
                m.close()

                expected_dir = platform + '_' + guid
                expected_path = os.path.join(dest, expected_dir)

                if existing_path != expected_path:
                    print('NOTICE: Folder should be "{}", but it is named "{}"'
                          .format(expected_dir, existing_dir))

                    if os.path.isdir(expected_path):
                        print('NOTICE: Correct pathed plugin already exists,'
                              + ' deleting extra plugin')
                        shutil.rmtree(existing_path)
                    else:
                        print('NOTICE: Renaming folder to proper name')
                        shutil.move(existing_path, expected_path)
        except (FileNotFoundError, json.decoder.JSONDecodeError, KeyError):
            print('ERROR: Could not read plugin data from {} folder'
                  .format(existing_path)) 

def delete_old_plugins(data, dest):
    """
    Deletes versions of plugins that don't match the yaml manifest. In theory
    this should only be older versions, but any version that doesn't match
    the yaml definition will be deleted

    This explicitly does not touch other directories that do not match the
    known plugin names.

    If the version doesn't match the yaml definition, the directory is removed
    """
    # Loop over each plugin
    for name, data in data.items():
        expected_plugin_dir = name + '_' + data['guid']

        # Loop through directories in the destination directory
        for item in os.listdir(dest):
            full_path = os.path.join(dest, item)

            # Skip non-directories
            if not os.path.isdir(full_path):
                continue

            # Skip directory names that are in the valid plugin directory array
            if item == expected_plugin_dir:
                continue

            # If any other directory begins with <plugin_name>_, delete it
            if item.startswith(name + '_'):
                print('Deleting wrong version "{}" from "{}"'
                      .format(item, dest))
                shutil.rmtree(full_path) 

def download(env):
    """60000 tiny colour images in 100 classes.

The CIFAR-100 dataset consists of 60000 32x32 colour images in 100 
classes, with 6000 images per class. There are 500 training images
and 100 testing images per class.

Credits:
  Alex Krizhevsky
  Vinod Nair
  Geoffrey Hinton

For more information visit: 
https://www.cs.toronto.edu/~kriz/cifar.html"""

    url = "https://www.cs.toronto.edu/~kriz/cifar-100-python.tar.gz"

    samples_dir = env.get('base.samples_dir')

    print("Downloading CIFAR-100 to {}.".format(samples_dir))

    src_dir = download_files([url], dir=env.get('base.cache_dir'))
    path = os.path.join(src_dir, "cifar-100-python.tar.gz")

    tarf = tarfile.TarFile(path, 'r:gz')
    tarf.extractall(src_dir)
    tarf.close()

    shutil.rmtree(src_dir)

    print("Finished downloading CIFAR-100.") 

def download(env):
    """60000 tiny colour images in 10 classes.

The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 
classes, with 6000 images per class. There are 50000 training 
images and 10000 test images.

Credits:
  Alex Krizhevsky
  Vinod Nair
  Geoffrey Hinton

For more information visit: 
https://www.cs.toronto.edu/~kriz/cifar.html"""

    url = "https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz"

    samples_dir = env.get('base.samples_dir')

    print("Downloading CIFAR-10 to {}.".format(samples_dir))

    src_dir = download_files([url], dir=env.get('base.cache_dir'))
    path = os.path.join(src_dir, "cifar-10-python.tar.gz")

    tarf = tarfile.TarFile(path, 'r:gz')
    tarf.extractall(src_dir)
    tarf.close()

    shutil.rmtree(src_dir)

    print("Finished downloading CIFAR-10.") 

def __call__(self, args, env):
        samples_dir = env.get('samples-dir')

        for label in ['affenpinscher', 'afghan-hound', 'african-hunting-dog', 'airedale', 'american-staffordshire-terrier', 'appenzeller', 'australian-terrier', 'basenji', 'basset', 'beagle', 'bedlington-terrier', 'bernese-mountain-dog', 'black-and-tan-coonhound', 'blenheim-spaniel', 'bloodhound', 'bluetick', 'border-collie', 'border-terrier', 'borzoi', 'boston-bull', 'bouvier-des-flandres', 'boxer', 'brabancon-griffon', 'briard', 'brittany-spaniel', 'bull-mastiff', 'cairn', 'cardigan', 'chesapeake-bay-retriever', 'chihuahua', 'chow', 'clumber', 'cocker-spaniel', 'collie', 'curly-coated-retriever', 'dandie-dinmont', 'dhole', 'dingo', 'doberman', 'english-foxhound', 'english-setter', 'english-springer', 'entlebucher', 'eskimo-dog', 'flat-coated-retriever', 'french-bulldog', 'german-shepherd', 'german-short-haired-pointer', 'giant-schnauzer', 'golden-retriever', 'gordon-setter', 'great-dane', 'great-pyrenees', 'greater-swiss-mountain-dog', 'groenendael', 'ibizan-hound', 'irish-setter', 'irish-terrier', 'irish-water-spaniel', 'irish-wolfhound', 'italian-greyhound', 'japanese-spaniel', 'keeshond', 'kelpie', 'kerry-blue-terrier', 'komondor', 'kuvasz', 'labrador-retriever', 'lakeland-terrier', 'leonberg', 'lhasa', 'malamute', 'malinois', 'maltese-dog', 'mexican-hairless', 'miniature-pinscher', 'miniature-poodle', 'miniature-schnauzer', 'newfoundland', 'norfolk-terrier', 'norwegian-elkhound', 'norwich-terrier', 'old-english-sheepdog', 'otterhound', 'papillon', 'pekinese', 'pembroke', 'pomeranian', 'pug', 'redbone', 'rhodesian-ridgeback', 'rottweiler', 'saint-bernard', 'saluki', 'samoyed', 'schipperke', 'scotch-terrier', 'scottish-deerhound', 'sealyham-terrier', 'shetland-sheepdog', 'shih-tzu', 'siberian-husky', 'silky-terrier', 'soft-coated-wheaten-terrier', 'staffordshire-bullterrier', 'standard-poodle', 'standard-schnauzer', 'sussex-spaniel', 'tibetan-mastiff', 'tibetan-terrier', 'toy-poodle', 'toy-terrier', 'vizsla', 'walker-hound', 'weimaraner', 'welsh-springer-spaniel', 'west-highland-white-terrier', 'whippet', 'wire-haired-fox-terrier', 'yorkshire-terrier']:
            dest = os.path.join(samples_dir, label)
            if os.path.exists(dest):
                raise VergeMLError("Directory {} already exists in samples dir: {}".format(label, dest))

        print("Downloading Stanford dogs to {}.".format(samples_dir))

        src_dir = self.download_files([_URL], env=env, dir=env.get('cache-dir'))
        path = os.path.join(src_dir, "images.tar")

        print("Extracting data...")

        tarf = tarfile.TarFile(path, 'r')
        tarf.extractall(src_dir)
        tarf.close()

        for src_file in os.listdir(os.path.join(src_dir, "Images")):
            if src_file.startswith("."):
                continue

            _, dest_file = src_file.split("-", maxsplit=1)
            dest_file = dest_file.replace("_", "-")
            dest_file = dest_file.lower()
            shutil.copytree(os.path.join(src_dir, "Images", src_file),
                            os.path.join(samples_dir, dest_file))

        shutil.rmtree(src_dir)

        print("Finished downloading Stanford dogs.") 

def download(env):
    """The Street View House Numbers (SVHN) Dataset.

SVHN is a real-world image dataset for developing machine 
learning and object recognition algorithms with minimal 
requirement on data preprocessing and formatting. It can be 
seen as similar in flavor to MNIST (e.g., the images are of 
small cropped digits), but incorporates an order of magnitude 
more labeled data (over 600,000 digit images) and comes from a 
significantly harder, unsolved, real world problem 
(recognizing digits and numbers in natural scene images). SVHN
 is obtained from house numbers in Google Street View images.



Authors:
  Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, 
  Bo Wu, Andrew Y. Ng 
  Reading Digits in Natural Images with Unsupervised Feature 
  Learning NIPS Workshop on Deep Learning and Unsupervised 
  Feature Learning 2011. 

  http://ufldl.stanford.edu/housenumbers/nips2011_housenumbers.pdf

For more information visit: http://ufldl.stanford.edu/housenumbers/"""

    urls = ["http://ufldl.stanford.edu/housenumbers/train_32x32.mat",
            "http://ufldl.stanford.edu/housenumbers/test_32x32.mat"]

    samples_dir = env.get('base.samples_dir')
    print("Downloading SVHN to {}.".format(samples_dir))

    src_dir = download_files(urls, dir=env.get('base.cache_dir'))

    for file in ("train_32x32.mat", "test_32x32.mat", ):
        shutil.copy(os.path.join(src_dir, file), samples_dir)

    shutil.rmtree(src_dir)

    print("Finished downloading SVHN.") 

def download(env):
    """The MNIST database of handwritten digits.

The MNIST database of handwritten digits has a training set of
60,000 examples, and a test set of 10,000 examples. It is a
subset of a larger set available from NIST. The digits have been
size-normalized and centered in a fixed-size image.

It is a good database for people who want to try learning
techniques and pattern recognition methods on real-world data
while spending minimal efforts on preprocessing and formatting.

Authors:
  Yann LeCun, Courant Institute, NYU
  Corinna Cortes, Google Labs, New York
  Christopher J.C. Burges, Microsoft Research, Redmond

For more information visit:http://yann.lecun.com/exdb/mnist/"""

    urls = ["http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz",
            "http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz",
            "http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz",
            "http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz"]

    samples_dir = env.get('base.samples_dir')
    print("Downloading mnist to {}.".format(samples_dir))

    src_dir = download_files(urls, dir=env.get('base.cache_dir'))

    for file in ("train-images-idx3-ubyte.gz", "train-labels-idx1-ubyte.gz",
                 "t10k-images-idx3-ubyte.gz", "t10k-labels-idx1-ubyte.gz"):
        shutil.copy(os.path.join(src_dir, file), samples_dir)

    shutil.rmtree(src_dir)

    print("Finished downloading mnist.") 

def clean(config):
    """ Clean the filesystem.
    """
    os.unlink(config.KERNEL)
    os.unlink(config.DTB)
    os.unlink(config.ROOTFS)
    shutil.rmtree(config.DIR, ignore_errors=True) 

def _clean_test_direcs():
    for direc in [example_proj.direc_out, example_proj.tar_direc_out]:
        try:
            shutil.rmtree(direc)
        except OSError:
            pass 

def calcsuite_init_specs_single_calc(calcsuite_init_specs):
    specs = calcsuite_init_specs.copy()
    specs['variables'] = [condensation_rain]
    specs['regions'] = [None]
    specs['output_time_regional_reductions'] = ['av']
    yield specs
    # Teardown procedure
    for direc in [example_proj.direc_out, example_proj.tar_direc_out]:
        shutil.rmtree(direc, ignore_errors=True) 

def calcsuite_init_specs_two_calcs(calcsuite_init_specs):
    specs = calcsuite_init_specs.copy()
    specs['variables'] = [condensation_rain, convection_rain]
    specs['regions'] = [None]
    specs['output_time_regional_reductions'] = ['av']
    yield specs
    # Teardown procedure
    for direc in [example_proj.direc_out, example_proj.tar_direc_out]:
        shutil.rmtree(direc, ignore_errors=True) 

def bindiff_pickle_export(self, sample, is_64_bit = True, timeout = None):
        """
        Load a sample into IDA Pro, perform autoanalysis and export a pickle file. 
        :param sample: The sample's path
        :param is_64_bit: If the sample needs to be analyzed by the 64 bit version of IDA
        :param timeout: Timeout for the analysis in seconds
        :return: The file name of the exported pickle database. The file needs
        to be deleted by the caller. Returns None on error.
        """

        data_to_send = {
            "timeout": timeout,
            "is_64_bit": is_64_bit}
        url = "%s/binexport_pickle" % next(self._urls)
        log.debug("curl -XPOST --data '%s' '%s'", json.dumps(data_to_send), url)
        response = requests.post(url, data = data_to_send, files = {os.path.basename(sample): open(sample, "rb")})
        if response.status_code == 200:
            handle_tar, path_tar = tempfile.mkstemp(suffix = ".tar.gz")
            with os.fdopen(handle_tar, "wb") as f:
                map(f.write, response.iter_content(1024))
            directory = tempfile.mkdtemp()
            subprocess.check_call(["tar", "xf", path_tar], cwd = directory)

            handle_bindiff, output_bindiff = tempfile.mkstemp(suffix = ".BinExport")
            with os.fdopen(handle_bindiff, "wb") as f:
                with open(os.path.join(directory, "output.BinExport"), "rb") as f2:
                    shutil.copyfileobj(f2, f)
            handle_pickle, output_pickle = tempfile.mkstemp(suffix = ".pickle")
            with os.fdopen(handle_pickle, "wb") as f:
                with open(os.path.join(directory, "output.pickle"), "rb") as f2:
                    shutil.copyfileobj(f2, f)
            os.unlink(path_tar)
            shutil.rmtree(directory)
            return output_bindiff, output_pickle
        else:
            log.error("Bindiff server responded with status code %d: %s", response.status_code, response.content)
            return None 

def bindiff_export():
    """
    Run the IDA Pro autoanalysis on the input file and export a BinExport database.
    :param input: The input file
    :return: Status code 200 and a JSON object containing the output database
        name in key 'output', or status code 422 on invalid parameters, 408 on
        timeout or 500 on other errors.
    """
    logger.info("bindiff_export called")

    directory = None
    try:
        directory = tempfile.mkdtemp()
        if len(request.files) != 1:
            return make_response(jsonify(error = "Missing file parameter"), 422)

        filename, file_ = request.files.items()[0]
        input_ = os.path.join(directory, sanitize_filename(filename))
        file_.save(input_)

        output = os.path.join(directory, "output.BinExport")

        timeout = request.form.get('timeout', None)
        is_64_bit = request.form.get('is_64_bit', True)
        try:
            run_ida(input_, is_64_bit, timeout, os.path.join(PREFIX, "export_binexport_pickle.py"), "binexport", output)
            logger.info("Command completed successfully")
            return send_file(open(output, "rb"), as_attachment = True, attachment_filename = "%s.BinExport" % filename, mimetype = "application/binary")
        except TimeoutError:
            return jsonify(error = "Program execution timed out"), 408
        except OSError as err:
            return jsonify(error = "Program execution failed with error %d" % err.errno), 500
            
    finally:
        if directory is not None:
            shutil.rmtree(directory) 

def bindiff_pickle_export():
    """
    Run the IDA Pro autoanalysis on the input file and export a BinExport database.
    :param input: The input file
    :return: Status code 200 and a JSON object containing the output database
        name in key 'output', or status code 422 on invalid parameters, 408 on
        timeout or 500 on other errors.
    """
    logger.info("bindiff_pickle_export called")

    directory = None
    try:
        directory = tempfile.mkdtemp()
        if len(request.files) != 1:
            return make_response(jsonify(error = "Missing file parameter"), 422)

        filename, file_ = request.files.items()[0]
        input_ = os.path.join(directory, sanitize_filename(filename))
        file_.save(input_)

        output_binexport = os.path.join(directory, "output.BinExport")
        output_pickle = os.path.join(directory, "output.pickle")

        timeout = request.form.get('timeout', None)
        is_64_bit = request.form.get('is_64_bit', True)
        try:
            run_ida(input_, is_64_bit, timeout, os.path.join(PREFIX, "export_binexport_pickle.py"), "binexport_pickle", output_binexport, output_pickle)
            logger.info("Command completed successfully")
            output_tar = os.path.join(directory, "output.tar.gz")
            subprocess.check_call(["tar", "czf", output_tar, os.path.relpath(output_binexport, directory), os.path.relpath(output_pickle, directory)], cwd = directory)
            return send_file(open(output_tar, "rb"), as_attachment = True, attachment_filename = "%s.tar.gz" % filename, mimetype = "application/gzip")
        except TimeoutError:
            return jsonify(error = "Program execution timed out"), 408
        except OSError as err:
            return jsonify(error = "Program execution failed with error %d" % err.errno), 500
    finally:
        if directory is not None:
            shutil.rmtree(directory) 

def pickle_export():
    """
    Run the IDA Pro autoanalysis on the input file and export a BinExport database.
    :param input: The input file
    :return: Status code 200 and a JSON object containing the output database
        name in key 'output', or status code 422 on invalid parameters, 408 on
        timeout or 500 on other errors.
    """
    logger.info("bindiff_export called")

    directory = None
    try:
        directory = tempfile.mkdtemp()
        if len(request.files) != 1:
            return make_response(jsonify(error = "Missing file parameter"), 422)

        filename, file_ = request.files.items()[0]
        input_ = os.path.join(directory, sanitize_filename(filename))
        file_.save(input_)

        output = os.path.join(directory, "output.pickle")

        timeout = request.form.get('timeout', None)
        is_64_bit = request.form.get('is_64_bit', False)
        try:
            run_ida(input_, is_64_bit, timeout, os.path.join(PREFIX, "export_binexport_pickle.py"), "pickle", output)
            logger.info("Command completed successfully")
            return send_file(open(output, "rb"), as_attachment = True, attachment_filename = "%s.pickle" % filename, mimetype = "application/binary")
        except TimeoutError:
            return jsonify(error = "Program execution timed out"), 408
        except OSError as err:
            return jsonify(error = "Program execution failed with error %d" % err.errno), 500
    finally:
        if directory is not None:
            shutil.rmtree(directory) 

def bindiff_compare():
    logger.info("bindiff_compare called")

    input_dir = tempfile.mkdtemp()
    output_dir = tempfile.mkdtemp()
    try:
        primary = os.path.join(input_dir, "primary")
        secondary = os.path.join(input_dir, "secondary")
        try:
            request.files["primary"].save(primary)
            request.files["secondary"].save(secondary)
        except KeyError:
            return make_response(jsonify(error="Missing parameter 'primary' or 'secondary'"), 422)

        timeout = request.form.get('timeout', None)

        cmd = (BINDIFF_DIFFER, "--primary", primary, "--secondary", secondary, "--output_dir", output_dir)
        logger.info("Executing %s", " ".join("'%s'" % x for x in cmd))
        check_call(cmd, cwd = output_dir, timeout = timeout)
        db_path = [os.path.join(output_dir, x) for x in os.listdir(output_dir)]
        if len(db_path) != 1:
            return make_response(jsonify(error = "BinDiff generated 0 or several output files"), 500)
        return send_file(open(db_path[0], "rb"), as_attachment = True, attachment_filename = "BinDiff.sqlite3", mimetype = "application/binary")
    except OSError as err:
        if err.errno == -9:
            return make_response(jsonify(error = "Program execution timed out"), 408)
        else:
            return make_response(jsonify(error = "Program execution failed with error %d" % err.errno), 500)
    finally:
        shutil.rmtree(input_dir)
        shutil.rmtree(output_dir) 

def bindiff_export():
    """
    Run the IDA Pro autoanalysis on the input file and export a BinExport database.
    :param input: The input file
    :return: Status code 200 and a JSON object containing the output database
        name in key 'output', or status code 422 on invalid parameters, 408 on
        timeout or 500 on other errors.
    """
    logger.info("bindiff_export called")

    directory = None
    try:
        directory = tempfile.mkdtemp()
        if len(request.files) != 1:
            return make_response(jsonify(error = "Missing file parameter"), 422)

        filename, file_ = request.files.items()[0]
        input_ = os.path.join(directory, sanitize_filename(filename))
        file_.save(input_)

        output = os.path.join(directory, "output.BinExport")

        timeout = request.form.get('timeout', None)
        is_64_bit = request.form.get('is_64_bit', True)
        try:
            run_ida(input_, is_64_bit, timeout, os.path.join(PREFIX, "export_binexport_pickle.py"), "binexport", output)
            logger.info("Command completed successfully")
            return send_file(open(output, "rb"), as_attachment = True, attachment_filename = "%s.BinExport" % filename, mimetype = "application/binary")
        except TimeoutError:
            return jsonify(error = "Program execution timed out"), 408
        except OSError as err:
            return jsonify(error = "Program execution failed with error %d" % err.errno), 500
            
    finally:
        if directory is not None:
            shutil.rmtree(directory) 

def bindiff_pickle_export():
    """
    Run the IDA Pro autoanalysis on the input file and export a BinExport database.
    :param input: The input file
    :return: Status code 200 and a JSON object containing the output database
        name in key 'output', or status code 422 on invalid parameters, 408 on
        timeout or 500 on other errors.
    """
    logger.info("bindiff_pickle_export called")

    directory = None
    try:
        directory = tempfile.mkdtemp()
        if len(request.files) != 1:
            return make_response(jsonify(error = "Missing file parameter"), 422)

        filename, file_ = request.files.items()[0]
        input_ = os.path.join(directory, sanitize_filename(filename))
        file_.save(input_)

        output_binexport = os.path.join(directory, "output.BinExport")
        output_pickle = os.path.join(directory, "output.pickle")

        timeout = request.form.get('timeout', None)
        is_64_bit = request.form.get('is_64_bit', True)
        try:
            run_ida(input_, is_64_bit, timeout, os.path.join(PREFIX, "export_binexport_pickle.py"), "binexport_pickle", output_binexport, output_pickle)
            logger.info("Command completed successfully")
            output_tar = os.path.join(directory, "output.tar.gz")
            subprocess.check_call(["tar", "czf", output_tar, os.path.relpath(output_binexport, directory), os.path.relpath(output_pickle, directory)], cwd = directory)
            return send_file(open(output_tar, "rb"), as_attachment = True, attachment_filename = "%s.tar.gz" % filename, mimetype = "application/gzip")
        except TimeoutError:
            return jsonify(error = "Program execution timed out"), 408
        except OSError as err:
            return jsonify(error = "Program execution failed with error %d" % err.errno), 500
    finally:
        if directory is not None:
            shutil.rmtree(directory) 

def pickle_export():
    """
    Run the IDA Pro autoanalysis on the input file and export a BinExport database.
    :param input: The input file
    :return: Status code 200 and a JSON object containing the output database
        name in key 'output', or status code 422 on invalid parameters, 408 on
        timeout or 500 on other errors.
    """
    logger.info("bindiff_export called")

    directory = None
    try:
        directory = tempfile.mkdtemp()
        if len(request.files) != 1:
            return make_response(jsonify(error = "Missing file parameter"), 422)

        filename, file_ = request.files.items()[0]
        input_ = os.path.join(directory, sanitize_filename(filename))
        file_.save(input_)

        output = os.path.join(directory, "output.pickle")

        timeout = request.form.get('timeout', None)
        is_64_bit = request.form.get('is_64_bit', False)
        try:
            run_ida(input_, is_64_bit, timeout, os.path.join(PREFIX, "export_binexport_pickle.py"), "pickle", output)
            logger.info("Command completed successfully")
            return send_file(open(output, "rb"), as_attachment = True, attachment_filename = "%s.pickle" % filename, mimetype = "application/binary")
        except TimeoutError:
            return jsonify(error = "Program execution timed out"), 408
        except OSError as err:
            return jsonify(error = "Program execution failed with error %d" % err.errno), 500
    finally:
        if directory is not None:
            shutil.rmtree(directory)