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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def clusterflow_pipelines_section(self):
 """ Generate HTML for section about pipelines, generated from information parsed from run files. """

        data = dict()
        pids_guessed = ''
        for f,d in self.clusterflow_runfiles.items():
            pid = d.get('pipeline_id', 'unknown')
            if d.get('pipeline_id_guess', False) is True:
                pid += '*'
                pids_guessed = ' Project IDs with an asterisk may be inaccurate.'
            # Count the number of files going into the first module
            num_starting_files = 0
            for step_name, files in d.get('files',{}).items():
                if step_name.startswith('start'):
                    num_starting_files += len(files)
            # Reformat the date so that column sorting works nicely
            if 'pipeline_start_dateparts' in d:
                dt = d['pipeline_start_dateparts']
                d['pipeline_start'] = '{}-{:02d}-{:02d} {:02d}:{:02d}'.format(dt['year'], dt['month'], dt['day'], dt['hour'], dt['minute'])
            if pid not in data:
                data[pid] = d
                data[pid]['num_starting_files'] = int(num_starting_files)
            else:
                data[pid]['num_starting_files'] += int(num_starting_files)

        headers = OrderedDict()
        headers['pipeline_name'] = {'title': 'Pipeline Name'}
        headers['pipeline_start'] = {'title': 'Date Started', 'description': 'Date and time that pipeline was started (YYYY-MM-DD HH:SS)'}
        headers['genome'] = {'title': 'Genome ID', 'description': 'ID of reference genome used'}
        headers['num_starting_files'] = {'title': '# Starting Files', 'format': '{:,.0f}', 'description': 'Number of input files at start of pipeline run.'}
        table_config = {
            'namespace': 'Cluster Flow',
            'id': 'clusterflow-pipelines-table',
            'table_title': 'Cluster Flow Pipelines',
            'col1_header': 'Pipeline ID',
            'no_beeswarm': True,
            'save_file': True
        }
        self.add_section (
            name = 'Pipelines',
            anchor = 'clusterflow-pipelines',
            description = 'Information about pipelines is parsed from <code>*.run</code> files. {}'.format(pids_guessed),
            plot = table.plot(data, headers, table_config),
            content = self.clusterflow_pipelines_printout()
        )