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How to use _pretty_print method in hypothesis

Best Python code snippet using hypothesis

mcli.py

Source:mcli.py

...27                               '__init__.py')):28    sys.path.insert(0, possible_topdir)29from troveclient.compat import common30oparser = None31def _pretty_print(info):32    print(json.dumps(info, sort_keys=True, indent=4))33class HostCommands(common.AuthedCommandsBase):34    """Commands to list info on hosts."""35    params = [36        'name',37    ]38    def update_all(self):39        """Update all instances on a host."""40        self._require('name')41        self.dbaas.hosts.update_all(self.name)42    def get(self):43        """List details for the specified host."""44        self._require('name')45        self._pretty_print(self.dbaas.hosts.get, self.name)46    def list(self):47        """List all compute hosts."""48        self._pretty_list(self.dbaas.hosts.index)49class QuotaCommands(common.AuthedCommandsBase):50    """List and update quota limits for a tenant."""51    params = ['id',52              'instances',53              'volumes',54              'backups']55    def list(self):56        """List all quotas for a tenant."""57        self._require('id')58        self._pretty_print(self.dbaas.quota.show, self.id)59    def update(self):60        """Update quota limits for a tenant."""61        self._require('id')62        self._pretty_print(self.dbaas.quota.update, self.id,63                           dict((param, getattr(self, param))64                                for param in self.params if param != 'id'))65class RootCommands(common.AuthedCommandsBase):66    """List details about the root info for an instance."""67    params = [68        'id',69    ]70    def history(self):71        """List root history for the instance."""72        self._require('id')73        self._pretty_print(self.dbaas.management.root_enabled_history, self.id)74class AccountCommands(common.AuthedCommandsBase):75    """Commands to list account info."""76    params = [77        'id',78    ]79    def list(self):80        """List all accounts with non-deleted instances."""81        self._pretty_print(self.dbaas.accounts.index)82    def get(self):83        """List details for the account provided."""84        self._require('id')85        self._pretty_print(self.dbaas.accounts.show, self.id)86class InstanceCommands(common.AuthedCommandsBase):87    """List details about an instance."""88    params = [89        'deleted',90        'id',91        'limit',92        'marker',93        'host',94    ]95    def get(self):96        """List details for the instance."""97        self._require('id')98        self._pretty_print(self.dbaas.management.show, self.id)99    def list(self):100        """List all instances for account."""101        deleted = None102        if self.deleted is not None:103            if self.deleted.lower() in ['true']:104                deleted = True105            elif self.deleted.lower() in ['false']:106                deleted = False107        self._pretty_paged(self.dbaas.management.index, deleted=deleted)108    def hwinfo(self):109        """Show hardware information details about an instance."""110        self._require('id')111        self._pretty_print(self.dbaas.hwinfo.get, self.id)112    def diagnostic(self):113        """List diagnostic details about an instance."""114        self._require('id')115        self._pretty_print(self.dbaas.diagnostics.get, self.id)116    def stop(self):117        """Stop MySQL on the given instance."""118        self._require('id')119        self._pretty_print(self.dbaas.management.stop, self.id)120    def reboot(self):121        """Reboot the instance."""122        self._require('id')123        self._pretty_print(self.dbaas.management.reboot, self.id)124    def migrate(self):125        """Migrate the instance."""126        self._require('id')127        self._pretty_print(self.dbaas.management.migrate, self.id, self.host)128    def reset_task_status(self):129        """Set the instance's task status to NONE."""130        self._require('id')131        self._pretty_print(self.dbaas.management.reset_task_status, self.id)132class StorageCommands(common.AuthedCommandsBase):133    """Commands to list devices info."""134    params = []135    def list(self):136        """List details for the storage device."""137        self._pretty_list(self.dbaas.storage.index)138class FlavorsCommands(common.AuthedCommandsBase):139    """Commands for managing Flavors."""140    params = [141        'name',142        'ram',143        'disk',144        'vcpus',145        'flavor_id',146        'ephemeral',147        'swap',148        'rxtx_factor',149        'service_type'150    ]151    def create(self):152        """Create a new flavor."""153        self._require('name', 'ram', 'disk', 'vcpus',154                      'flavor_id', 'service_type')155        self._pretty_print(self.dbaas.mgmt_flavor.create, self.name,156                           self.ram, self.disk, self.vcpus, self.flavor_id,157                           self.ephemeral, self.swap, self.rxtx_factor,158                           self.service_type)159def config_options(oparser):160    oparser.add_option("-u", "--url", default="http://localhost:5000/v1.1",161                       help="Auth API endpoint URL with port and version. \162                            Default: http://localhost:5000/v1.1")163COMMANDS = {164    'account': AccountCommands,165    'host': HostCommands,166    'instance': InstanceCommands,167    'root': RootCommands,168    'storage': StorageCommands,169    'quota': QuotaCommands,...

redis-faina.py

Source:redis-faina.py

...97            self._record_key(entry['key'])98    def _top_n(self, stat, n=8):99        sorted_items = sorted(stat.iteritems(), key = lambda x: x[1], reverse = True)100        return sorted_items[:n]101    def _pretty_print(self, result, title, percentages=False):102        print title103        print '=' * 40104        if not result:105            print 'n/a\n'106            return107        max_key_len = max((len(x[0]) for x in result))108        max_val_len = max((len(str(x[1])) for x in result))109        for key, val in result:110            key_padding = max(max_key_len - len(key), 0) * ' '111            if percentages:112                val_padding = max(max_val_len - len(str(val)), 0) * ' '113                val = '%s%s\t(%.2f%%)' % (val, val_padding, (float(val) / self.line_count) * 100)114            print key,key_padding,'\t',val115        print116    def print_stats(self):117        self._pretty_print(self._general_stats(), 'Overall Stats')118        self._pretty_print(self._top_n(self.prefixes), 'Top Prefixes', percentages = True)119        self._pretty_print(self._top_n(self.keys), 'Top Keys', percentages = True)120        self._pretty_print(self._top_n(self.commands), 'Top Commands', percentages = True)121        self._pretty_print(self._time_stats(self.times), 'Command Time (microsecs)')122        self._pretty_print(self._heaviest_commands(self.times), 'Heaviest Commands (microsecs)')123        self._pretty_print(self._slowest_commands(self.times), 'Slowest Calls')124    def process_input(self, input):125        for line in input:126            self.line_count += 1127            line = line.strip()128            match = self.line_re.match(line)129            if not match:130                if line != "OK":131                    self.skipped_lines += 1132                continue133            self.process_entry(match.groupdict())134if __name__ == '__main__':135    parser = argparse.ArgumentParser()136    parser.add_argument(137        'input',...

analyzer.py

Source:analyzer.py

...3from pandas import DataFrame4logger = logging.getLogger(__name__)5class Analyzer(object):6    """Analyzer for transformed data"""7    def _pretty_print(self, data_frame, title=''):8        """Pretty print DataFrame to console9        :param data_frame: DataFrame to print10        :param title: title to print before printing DataFrame11        """12        print('\n')13        print(title)14        print(tabulate(data_frame, headers='keys', tablefmt='fancy_grid'))15    def analyze(self, storage, top_n=10):16        """Output statistics based on transformed data17        :param storage: storage to read data for analyzing18        :param top_n: number of top results19        """20        result_df = storage.read_data(orient='records')21        # Output vacancies count22        print()23        count_stats = result_df.shape[0]24        print('Vacancies count')25        print(count_stats)26        # Output vacancies period27        date_stats = DataFrame(result_df['created_at'].aggregate(['min', 'max'])).astype(str)28        self._pretty_print(date_stats, 'Vacancies period')29        # Output vacancies by cities30        city_stats = DataFrame(result_df['area.name'].value_counts()[:top_n])31        self._pretty_print(city_stats, 'Top cities with vacancies')32        # Output key skills information from nested json structure33        key_skills_df = storage.read_data(normalize=True, record_path='key_skills')34        key_skills_stats = DataFrame(key_skills_df['name'].str.lower().value_counts().head(top_n))35        self._pretty_print(key_skills_stats, 'Top key skills for vacancies')36        # Output schedule information37        schedule_stats = DataFrame(result_df['schedule.name'].value_counts())38        self._pretty_print(schedule_stats, 'Schedule distribution')39        # Output experience information40        experience_stats = DataFrame(result_df['experience.name'].value_counts())41        self._pretty_print(experience_stats, 'Required experience distribution')42        # Output employer information43        employer_stats = DataFrame(result_df['employer.name'].value_counts().head(top_n))44        self._pretty_print(employer_stats, 'Top companies with vacancies')45        # Output specializations information form nested json structure46        spec_df = storage.read_data(normalize=True, record_path='specializations')47        spec_stats = DataFrame(spec_df['name'].value_counts().head(top_n))48        self._pretty_print(spec_stats, 'Top specializations with vacancies')49        # Output salaries stats regardless of whether salary is net or gross50        # due to different tax rates in different countries51        salary_stats = result_df.aggregate({'salary.from.rur': ['min', 'max', 'mean', 'std'],52                                            'salary.to.rur': ['min', 'max', 'mean', 'std']})...

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