Python background.is_running函数代码示例

    def test_workflow_update_methods(self):
        """Workflow update methods"""

        def fake(wf):
            return

        Workflow().reset()
        # Initialise with outdated version
        wf = Workflow(update_settings={
            'github_slug': 'deanishe/alfred-workflow-dummy',
            'version': 'v2.0',
            'frequency': 1,
        })

        wf.run(fake)

        # Check won't have completed yet
        self.assertFalse(wf.update_available)

        # wait for background update check
        self.assertTrue(is_running('__workflow_update_check'))
        while is_running('__workflow_update_check'):
            time.sleep(0.05)
        time.sleep(1)

        # There *is* a newer version in the repo
        self.assertTrue(wf.update_available)

        # Mock out subprocess and check the correct command is run
        c = WorkflowMock()
        with c:
            self.assertTrue(wf.start_update())
        # wf.logger.debug('start_update : {}'.format(c.cmd))
        self.assertEquals(c.cmd[0], '/usr/bin/python')
        self.assertEquals(c.cmd[2], '__workflow_update_install')

        # Grab the updated release data, then reset the cache
        update_info = wf.cached_data('__workflow_update_status')

        wf.reset()

        # Initialise with latest available release
        wf = Workflow(update_settings={
            'github_slug': 'deanishe/alfred-workflow-dummy',
            'version': update_info['version'],
        })

        wf.run(fake)

        # Wait for background update check
        self.assertTrue(is_running('__workflow_update_check'))
        while is_running('__workflow_update_check'):
            time.sleep(0.05)

        # Remote version is same as the one we passed to Workflow
        self.assertFalse(wf.update_available)
        self.assertFalse(wf.start_update())

 def test_kill(self):
     """Kill"""
     assert kill('test') is False
     cmd = ['sleep', '1']
     assert run_in_background('test', cmd) == 0
     assert is_running('test')
     assert kill('test') is True
     sleep(0.3)  # give process time to exit
     assert not is_running('test')

 def test_run_in_background(self):
     """Run in background"""
     cmd = ['sleep', '1']
     assert run_in_background('test', cmd) == 0
     assert is_running('test')
     assert os.path.exists(_pidfile('test'))
     # Already running
     assert run_in_background('test', cmd) is None
     sleep(1.1)  # wait for job to finish
     assert not is_running('test')
     assert not os.path.exists(_pidfile('test'))

 def test_run_in_background(self):
     """Run in background"""
     cmd = ['sleep', '1']
     run_in_background('test', cmd)
     sleep(0.5)
     self.assertTrue(is_running('test'))
     self.assertTrue(os.path.exists(self._pidfile('test')))
     self.assertEqual(run_in_background('test', cmd), None)
     sleep(0.6)
     self.assertFalse(is_running('test'))
     self.assertFalse(os.path.exists(self._pidfile('test')))

 def test_existing_process(self):
     """Existing process"""
     _write_pidfile('test', os.getpid())
     try:
         assert is_running('test')
         assert os.path.exists(_pidfile('test'))
     finally:
         _delete_pidfile('test')

def main(wf):
    """Run workflow Script Filter.

    Args:
        wf (workflow.Workflow): Current Workflow object.

    """
    global ureg
    ureg = UnitRegistry(wf.decode(DEFAULT_UNIT_DEFINITIONS))
    ureg.default_format = 'P'

    wf.magic_arguments['appkey'] = open_currency_instructions

    if not len(wf.args):
        return

    query = wf.args[0]  # .lower()
    log.debug('query : %s', query)

    handle_update(wf)
    # Create data files if necessary
    bootstrap(wf)

    # Add workflow and user units to unit registry
    register_units()

    # Notify of available update
    if wf.update_available:
        wf.add_item('A newer version is available',
                    'Action this item to download & install the new version',
                    autocomplete='workflow:update',
                    icon=ICON_UPDATE)

    # Load cached data
    exchange_rates = wf.cached_data(CURRENCY_CACHE_NAME, max_age=0)

    if exchange_rates:  # Add exchange rates to conversion database
        register_exchange_rates(exchange_rates)

    if not wf.cached_data_fresh(CURRENCY_CACHE_NAME, CURRENCY_CACHE_AGE):
        # Update currency rates
        cmd = ['/usr/bin/python', wf.workflowfile('currency.py')]
        run_in_background('update', cmd)
        wf.rerun = 0.5

    if is_running('update'):
        wf.rerun = 0.5
        if exchange_rates is None:  # No data cached yet
            wf.add_item(u'Fetching exchange rates…',
                        'Currency conversions will be momentarily possible',
                        icon=ICON_INFO)
        else:
            wf.add_item(u'Updating exchange rates…',
                        icon=ICON_INFO)

    return convert(query)

def generate_all_icons():
    """Callback for magic argument"""
    if background.is_running('icongen'):
        return 'Generation already in progress.'

    background.run_in_background(
        'icongen',
        ['/usr/bin/python', wf.workflowfile('icons.py')]
    )
    return 'Starting icon generation. This may take up to 15 minutes.'

    def run(self, wf):
        from docopt import docopt
        self.wf = wf

        args = docopt(__usage__, argv=self.wf.args)

        self.workflows = self.wf.cached_data('workflows', None,
                                             max_age=0)

        if self.workflows:
            log.debug('%d workflows in cache', len(self.workflows))
        else:
            log.debug('0 workflows in cache')

        # Start update scripts if cached data is too old
        if not self.wf.cached_data_fresh('workflows',
                                         max_age=CACHE_MAXAGE):
            self._update()

        # Notify user if cache is being updated
        if is_running('update'):
            self.wf.add_item('Updating from Packal…',
                             'Please try again in a second or two',
                             valid=False, icon=ICON_INFO)

        if not self.workflows:
            self.wf.send_feedback()
            return 0

        self.workflows.sort(key=itemgetter('updated'), reverse=True)

        log.debug('%d workflows found in cache', len(self.workflows))

        self.query = args.get('<query>')
        self.author = args.get('<author>')
        self.bundleid = args.get('<bundleid>')

        for key in ('tags', 'categories', 'versions', 'authors'):
            if args.get(key):
                return self._two_stage_filter(key)

        if args.get('author-workflows'):
            return self.do_author_workflows()
        elif args.get('workflows'):
            return self._filter_workflows(self.workflows, self.query)
        elif args.get('update'):
            return self.do_update()
        elif args.get('open'):
            return self.do_open()
        elif args.get('status'):
            return self.do_status()
        elif args.get('ignore-author'):
            return self.do_ignore_author()
        else:
            raise ValueError('No action specified')

def do_import_search(wf, url):
    """Parse URL for OpenSearch config."""
    ctx = Context(wf)
    # ICON_IMPORT = ctx.icon('import')
    ICONS_PROGRESS = [
        ctx.icon('progress-1'),
        ctx.icon('progress-2'),
        ctx.icon('progress-3'),
        ctx.icon('progress-4'),
    ]

    data = wf.cached_data('import', None, max_age=0, session=True)
    if data:
        error = data['error']
        search = data['search']
        # Clear cache data
        wf.cache_data('import', None, session=True)
        wf.cache_data('import-status', None, session=True)

        if error:
            wf.add_item(error, icon=ICON_ERROR)
            wf.send_feedback()
            return

        it = wf.add_item(u'Add "{}"'.format(search['name']),
                         u'↩ to add search',
                         valid=True,
                         icon=search['icon'])

        for k, v in search.items():
            it.setvar(k, v)

    else:
        progress = int(os.getenv('progress') or '0')
        i = progress % len(ICONS_PROGRESS)
        picon = ICONS_PROGRESS[i]
        log.debug('progress=%d, i=%d, picon=%s', progress, i, picon)
        wf.setvar('progress', progress + 1)
        if not is_running('import'):
            run_in_background('import', ['./searchio', 'fetch', url])

        status = wf.cached_data('import-status', None, max_age=0, session=True)
        title = status or u'Fetching OpenSearch Configuration …'

        wf.rerun = 0.2
        wf.add_item(title,
                    u'Results will be shown momentarily',
                    icon=picon)

    wf.send_feedback()

def main(wf):
    args = Args(wf.args)

    actions = wf.cached_data('actions', None, max_age=0)

    if wf.update_available:
        # Add a notification to top of Script Filter results
        wf.add_item(u'New version available',
                    u'Action this item to install the update',
                    autocomplete='workflow:update',
                    icon=ICON_INFO)

    if not wf.cached_data_fresh('actions', max_age=CACHE_MAX_AGE):
        cmd = ['/usr/bin/python', wf.workflowfile('alfredhelp.py'), '--scan']
        run_in_background(u'scan', cmd)

    if is_running(u'scan'):
        wf.add_item(
            title=u'Scanning alfred workflows...',
            valid=False,
            icon=ICON_INFO
        )

    if args.show_keywords and actions:
        if args.query:
            actions = wf.filter(args.query, actions, key=search_key)

        for action in actions:
            argument = action.keyword
            if action.add_space:
                argument += u' '
            wf.add_item(
                title=u'{keyword} - {title}'.format(keyword=action.keyword, title=action.title),
                subtitle=action.subtitle,
                icon=action.icon,
                arg=argument,
                valid=True
            )

    elif args.scan:
        def get_posts():
            return scan(path.join(wf.alfred_env['preferences'], 'workflows'))

        wf.cached_data('actions', get_posts, max_age=CACHE_MAX_AGE)
        scan(path.join(wf.alfred_env['preferences'], 'workflows'))

    wf.send_feedback()
    return 0

def output_query_vault_results(ap):
    """
    A simple helper function to manage outputting LastPass vault items to an
    Alfred Script Filter. Uses an ArgParser instance to figure out which
    command and argument to use.
    """
    # Notify the user if the cache is being updated:
    if is_running('update'):
        log.debug('Currenly running update; notifying user...')
        wf.add_item(
            'Getting new data from LastPass.',
            'This should only take a few moments, so hang tight.',
            valid=False,
            icon='icons/loading.png',
            uid='1'
        )

    results = util.search_vault_for_query(ap.arg)
    if results:
        for result in results:
            wf.add_item(
                result['hostname'],
                'TAB to explore; ' +
                'ENTER to copy password; ' +
                '\u2318-Click to copy username; ' +
                'Shift-Click to open URL',
                modifier_subtitles={
                    'cmd': '\u2318-Click to copy username.',
                    'shift': 'Shift-Click to open the URL.'
                },
                valid=True,
                arg='{} {}***{}'.format(ap.command,
                                        result['hostname'],
                                        result['url']),
                autocomplete='view-details {}'.format(result['hostname']),
            )
    else:
        wf.add_item(
            'No items matching "{}".'.format(ap.arg),
            'View the `lpvs` debug log for more information.',
            valid=False,
            icon='icons/warning.png'
        )

    wf.send_feedback()
    return

def main(workflow):
    parser = argparse.ArgumentParser()
    parser.add_argument("--set-token", dest="api_token", nargs="?", default=None)
    parser.add_argument("query", nargs="?", default=None)
    arguments = parser.parse_args(workflow.args)

    if arguments.api_token:
        workflow.save_password("hipchat_api_token", arguments.api_token)
        return 0

    try:
        api_token = workflow.get_password("hipchat_api_token")
    except PasswordNotFound:
        workflow.add_item(
            "No API key set.", "Please use hcsettoken to set your Hipchat API token.", valid=False, icon=ICON_WARNING
        )
        workflow.send_feedback()

        return 0

    users = workflow.cached_data("users", None, max_age=0)

    if not workflow.cached_data_fresh("users", max_age=60):  # 60s
        cmd = ["/usr/bin/python", workflow.workflowfile("update.py")]
        run_in_background("update", cmd)

    if is_running("update"):
        logger.debug("updating users")

    if arguments.query and users:
        users = workflow.filter(arguments.query, users, key=search_terms_for_user, min_score=20)

    if not users:
        workflow.add_item("Whoops, no users found", icon=ICON_WARNING)
        workflow.send_feedback()

        return 0

    for user in users:
        status_icon = get_status_icon(user["presence"]["show"] if user["presence"] else None)
        workflow.add_item(
            user["name"], user["email"], arg=actionTemplate.format(user["mention_name"]), valid=True, icon=status_icon
        )

    workflow.send_feedback()
    logger.debug("returned {} results".format(len(users)))

    def run(self, wf):
        """Run workflow."""
        self.wf = wf
        wf.args  # check for magic args
        self.keyword = self.wf.settings.get('keyword', DEFAULT_KEYWORD)
        args = docopt(__doc__)
        log.debug(u'args : %r', args)

        # Open Help file
        if args.get('--helpfile'):
            return self.do_open_help_file()

        # Perform search
        self.query = wf.decode(args.get('<query>') or '')

        # List Smart Folders with custom keywords
        if args.get('--config'):
            return self.do_configure_folders()

        # Was a configured folder passed?
        folder = wf.decode(args.get('--folder') or '')

        # Get list of Smart Folders. Update in background if necessary.
        self.folders = self.wf.cached_data('folders', max_age=0)
        if self.folders is None:
            self.folders = []

        # Update folder list if it's old
        if not self.wf.cached_data_fresh('folders', CACHE_AGE_FOLDERS):
            log.debug('updating list of Smart Folders in background...')
            run_in_background('folders',
                              ['/usr/bin/python',
                               self.wf.workflowfile('cache.py')])

        if is_running('folders'):
            self.wf.rerun = 0.5

        # Has a specific folder been specified?
        if folder:
            return self.do_search_in_folder(folder)

        return self.do_search_folders()

def build_wf_entry(wf):

    if is_running('bg'):
        """Update status"""
        phase = wf.stored_data('phase')
        log.info('PHASE: ', phase)
        if phase != 'done':
            wf.rerun = 0.5
        if phase == 'downloading':
            pct = None
            while pct is None:
                try:
                    pct = wf.stored_data('download_percent')
                except:
                    pass

            progress = wf.stored_data('download_progress')
            file = wf.stored_data('download_file')

            # wf.rerun = 0.5

            title = "Downloading {} [{}]".format(file, progress)
            subtitle = string_from_percent(pct) + " " + str(pct) + "%"
            wf.add_item(title, subtitle=subtitle)

        if phase == 'processing':

            try:
                emoji_count = wf.stored_data('emoji_count')
                subtitle = "Parsed {} emoji".format(emoji_count)
            except:
                subtitle = "Parsed ... emoji"
                pass

            title = 'Parsing Emoji'
            wf.add_item(title, subtitle=subtitle)

    else:
        """Last case"""
        wf.add_item("Complete", subtitle='Emoji searching is now ready to use',
                    icon="images/Checkmark.png")

def main(wf):
    # Workflow requires a query
    query = wf.args[0]

    index_exists = True

    # Create index if it doesn't exist
    if not os.path.exists(INDEX_DB):
        index_exists = False
        run_in_background('indexer', ['/usr/bin/python', 'index.py'])

    # Can't search without an index. Inform user and exit
    if not index_exists:
        wf.add_item('Creating search index…', 'Please wait a moment',
                    icon=ICON_INFO)
        wf.send_feedback()
        return

    # Inform user of update in case they're looking for something
    # recently added (and it isn't there)
    if is_running('indexer'):
        wf.add_item('Updating search index…',
                    'Fresher results will be available shortly',
                    icon=ICON_INFO)

    # Search!
    start = time()
    db = sqlite3.connect(INDEX_DB)
    # Set ranking function with weightings for each column.
    # `make_rank_function` must be called with a tuple/list of the same
    # length as the number of columns "selected" from the database.
    # In this case, `url` is set to 0 because we don't want to search on
    # that column
    db.create_function('rank', 1, make_rank_func((1.0, 1.0, 0)))
    cursor = db.cursor()
    try:
        cursor.execute("""SELECT author, title, url FROM
                            (SELECT rank(matchinfo(books))
                             AS r, author, title, url
                             FROM books WHERE books MATCH ?)
                          ORDER BY r DESC LIMIT 100""", (query,))
        results = cursor.fetchall()
    except sqlite3.OperationalError as err:
        # If the query is invalid, show an appropriate warning and exit
        if b'malformed MATCH' in err.message:
            wf.add_item('Invalid query', icon=ICON_WARNING)
            wf.send_feedback()
            return
        # Otherwise raise error for Workflow to catch and log
        else:
            raise err

    if not results:
        wf.add_item('No matches', 'Try a different query', icon=ICON_WARNING)

    log.info('{} results for `{}` in {:0.3f} seconds'.format(
             len(results), query, time() - start))

    # Output results to Alfred
    for (author, title, url) in results:
        wf.add_item(title, author, valid=True, arg=url, icon='icon.png')

    wf.send_feedback()