Python sys.stdin 模块，encoding() 实例源码

我们从Python开源项目中，提取了以下9个代码示例，用于说明如何使用sys.stdin.encoding()。

项目：Price-Comparator 作者：Thejas-1 | 项目源码 | 文件源码

def _classify_many(self, featuresets, options):
        # Make sure we can find java & weka.
        config_weka()

        temp_dir = tempfile.mkdtemp()
        try:
            # Write the test data file.
            test_filename = os.path.join(temp_dir, 'test.arff')
            self._formatter.write(test_filename, featuresets)

            # Call weka to classify the data.
            cmd = ['weka.classifiers.bayes.NaiveBayes',
                   '-l', self._model, '-T', test_filename] + options
            (stdout, stderr) = java(cmd, classpath=_weka_classpath,
                                    stdout=subprocess.PIPE,
                                    stderr=subprocess.PIPE)

            # Check if something went wrong:
            if stderr and not stdout:
                if 'Illegal options: -distribution' in stderr:
                    raise ValueError('The installed version of weka does '
                                     'not support probability distribution '
                                     'output.')
                else:
                    raise ValueError('Weka failed to generate output:\n%s'
                                     % stderr)

            # Parse weka's output.
            return self.parse_weka_output(stdout.decode(stdin.encoding).split('\n'))

        finally:
            for f in os.listdir(temp_dir):
                os.remove(os.path.join(temp_dir, f))
            os.rmdir(temp_dir)

项目：PyDataLondon29-EmbarrassinglyParallelDAWithAWSLambda 作者：SignalMedia | 项目源码 | 文件源码

def _classify_many(self, featuresets, options):
        # Make sure we can find java & weka.
        config_weka()

        temp_dir = tempfile.mkdtemp()
        try:
            # Write the test data file.
            test_filename = os.path.join(temp_dir, 'test.arff')
            self._formatter.write(test_filename, featuresets)

            # Call weka to classify the data.
            cmd = ['weka.classifiers.bayes.NaiveBayes',
                   '-l', self._model, '-T', test_filename] + options
            (stdout, stderr) = java(cmd, classpath=_weka_classpath,
                                    stdout=subprocess.PIPE,
                                    stderr=subprocess.PIPE)

            # Check if something went wrong:
            if stderr and not stdout:
                if 'Illegal options: -distribution' in stderr:
                    raise ValueError('The installed version of weka does '
                                     'not support probability distribution '
                                     'output.')
                else:
                    raise ValueError('Weka failed to generate output:\n%s'
                                     % stderr)

            # Parse weka's output.
            return self.parse_weka_output(stdout.decode(stdin.encoding).split('\n'))

        finally:
            for f in os.listdir(temp_dir):
                os.remove(os.path.join(temp_dir, f))
            os.rmdir(temp_dir)

项目：neighborhood_mood_aws 作者：jarrellmark | 项目源码 | 文件源码

def _classify_many(self, featuresets, options):
        # Make sure we can find java & weka.
        config_weka()

        temp_dir = tempfile.mkdtemp()
        try:
            # Write the test data file.
            test_filename = os.path.join(temp_dir, 'test.arff')
            self._formatter.write(test_filename, featuresets)

            # Call weka to classify the data.
            cmd = ['weka.classifiers.bayes.NaiveBayes',
                   '-l', self._model, '-T', test_filename] + options
            (stdout, stderr) = java(cmd, classpath=_weka_classpath,
                                    stdout=subprocess.PIPE,
                                    stderr=subprocess.PIPE)

            # Check if something went wrong:
            if stderr and not stdout:
                if 'Illegal options: -distribution' in stderr:
                    raise ValueError('The installed version of weka does '
                                     'not support probability distribution '
                                     'output.')
                else:
                    raise ValueError('Weka failed to generate output:\n%s'
                                     % stderr)

            # Parse weka's output.
            return self.parse_weka_output(stdout.decode(stdin.encoding).split('\n'))

        finally:
            for f in os.listdir(temp_dir):
                os.remove(os.path.join(temp_dir, f))
            os.rmdir(temp_dir)

项目：hate-to-hugs 作者：sdoran35 | 项目源码 | 文件源码

def _classify_many(self, featuresets, options):
        # Make sure we can find java & weka.
        config_weka()

        temp_dir = tempfile.mkdtemp()
        try:
            # Write the test data file.
            test_filename = os.path.join(temp_dir, 'test.arff')
            self._formatter.write(test_filename, featuresets)

            # Call weka to classify the data.
            cmd = ['weka.classifiers.bayes.NaiveBayes',
                   '-l', self._model, '-T', test_filename] + options
            (stdout, stderr) = java(cmd, classpath=_weka_classpath,
                                    stdout=subprocess.PIPE,
                                    stderr=subprocess.PIPE)

            # Check if something went wrong:
            if stderr and not stdout:
                if 'Illegal options: -distribution' in stderr:
                    raise ValueError('The installed version of weka does '
                                     'not support probability distribution '
                                     'output.')
                else:
                    raise ValueError('Weka failed to generate output:\n%s'
                                     % stderr)

            # Parse weka's output.
            return self.parse_weka_output(stdout.decode(stdin.encoding).split('\n'))

        finally:
            for f in os.listdir(temp_dir):
                os.remove(os.path.join(temp_dir, f))
            os.rmdir(temp_dir)

项目：FancyWord 作者：EastonLee | 项目源码 | 文件源码

def _classify_many(self, featuresets, options):
        # Make sure we can find java & weka.
        config_weka()

        temp_dir = tempfile.mkdtemp()
        try:
            # Write the test data file.
            test_filename = os.path.join(temp_dir, 'test.arff')
            self._formatter.write(test_filename, featuresets)

            # Call weka to classify the data.
            cmd = ['weka.classifiers.bayes.NaiveBayes',
                   '-l', self._model, '-T', test_filename] + options
            (stdout, stderr) = java(cmd, classpath=_weka_classpath,
                                    stdout=subprocess.PIPE,
                                    stderr=subprocess.PIPE)

            # Check if something went wrong:
            if stderr and not stdout:
                if 'Illegal options: -distribution' in stderr:
                    raise ValueError('The installed version of weka does '
                                     'not support probability distribution '
                                     'output.')
                else:
                    raise ValueError('Weka failed to generate output:\n%s'
                                     % stderr)

            # Parse weka's output.
            return self.parse_weka_output(stdout.decode(stdin.encoding).split('\n'))

        finally:
            for f in os.listdir(temp_dir):
                os.remove(os.path.join(temp_dir, f))
            os.rmdir(temp_dir)

项目：beepboop 作者：nicolehe | 项目源码 | 文件源码

def _classify_many(self, featuresets, options):
        # Make sure we can find java & weka.
        config_weka()

        temp_dir = tempfile.mkdtemp()
        try:
            # Write the test data file.
            test_filename = os.path.join(temp_dir, 'test.arff')
            self._formatter.write(test_filename, featuresets)

            # Call weka to classify the data.
            cmd = ['weka.classifiers.bayes.NaiveBayes',
                   '-l', self._model, '-T', test_filename] + options
            (stdout, stderr) = java(cmd, classpath=_weka_classpath,
                                    stdout=subprocess.PIPE,
                                    stderr=subprocess.PIPE)

            # Check if something went wrong:
            if stderr and not stdout:
                if 'Illegal options: -distribution' in stderr:
                    raise ValueError('The installed version of weka does '
                                     'not support probability distribution '
                                     'output.')
                else:
                    raise ValueError('Weka failed to generate output:\n%s'
                                     % stderr)

            # Parse weka's output.
            return self.parse_weka_output(stdout.decode(stdin.encoding).split('\n'))

        finally:
            for f in os.listdir(temp_dir):
                os.remove(os.path.join(temp_dir, f))
            os.rmdir(temp_dir)

项目：kind2anki 作者：prz3m | 项目源码 | 文件源码

def _classify_many(self, featuresets, options):
        # Make sure we can find java & weka.
        config_weka()

        temp_dir = tempfile.mkdtemp()
        try:
            # Write the test data file.
            test_filename = os.path.join(temp_dir, 'test.arff')
            self._formatter.write(test_filename, featuresets)

            # Call weka to classify the data.
            cmd = ['weka.classifiers.bayes.NaiveBayes',
                   '-l', self._model, '-T', test_filename] + options
            (stdout, stderr) = java(cmd, classpath=_weka_classpath,
                                    stdout=subprocess.PIPE,
                                    stderr=subprocess.PIPE)

            # Check if something went wrong:
            if stderr and not stdout:
                if 'Illegal options: -distribution' in stderr:
                    raise ValueError('The installed version of weka does '
                                     'not support probability distribution '
                                     'output.')
                else:
                    raise ValueError('Weka failed to generate output:\n%s'
                                     % stderr)

            # Parse weka's output.
            return self.parse_weka_output(stdout.decode(stdin.encoding).split('\n'))

        finally:
            for f in os.listdir(temp_dir):
                os.remove(os.path.join(temp_dir, f))
            os.rmdir(temp_dir)

项目：but_sentiment 作者：MixedEmotions | 项目源码 | 文件源码

def _classify_many(self, featuresets, options):
        # Make sure we can find java & weka.
        config_weka()

        temp_dir = tempfile.mkdtemp()
        try:
            # Write the test data file.
            test_filename = os.path.join(temp_dir, 'test.arff')
            self._formatter.write(test_filename, featuresets)

            # Call weka to classify the data.
            cmd = ['weka.classifiers.bayes.NaiveBayes',
                   '-l', self._model, '-T', test_filename] + options
            (stdout, stderr) = java(cmd, classpath=_weka_classpath,
                                    stdout=subprocess.PIPE,
                                    stderr=subprocess.PIPE)

            # Check if something went wrong:
            if stderr and not stdout:
                if 'Illegal options: -distribution' in stderr:
                    raise ValueError('The installed version of weka does '
                                     'not support probability distribution '
                                     'output.')
                else:
                    raise ValueError('Weka failed to generate output:\n%s'
                                     % stderr)

            # Parse weka's output.
            return self.parse_weka_output(stdout.decode(stdin.encoding).split('\n'))

        finally:
            for f in os.listdir(temp_dir):
                os.remove(os.path.join(temp_dir, f))
            os.rmdir(temp_dir)

项目：grklsh 作者：xtonousou | 项目源码 | 文件源码

def cat(lang):
    """
        Translate any text into Greeklish by [typing + enter]

        @param lang: a string to check which mode to activate {'greek', anything}
    """

    if lang == 'greek':
        while True:
            try:
                text = raw_input().decode(stdin.encoding
                                          or locale.getpreferredencoding(True))

                new_data = to_greeklish(list(text))
                print ''.join(new_data)
            except KeyboardInterrupt:
                print '\nexit'
                exit()
    else:
        while True:
            try:
                text = raw_input().decode(stdin.encoding
                                          or locale.getpreferredencoding(True))

                translated = Translator().translate(''.join(text), dest='el')
                new_data = to_greeklish(list(unicode(translated.text)))
                print ''.join(new_data)
            except KeyboardInterrupt:
                print '\nexit'
                exit()