How to use the gsutil.path_from_course_id function in gsutil

def date_parse(field):
        (m, d, y) = map(int, data[field].split('/'))
        return datetime.datetime(y, m, d)

    launch = date_parse('Course Launch')
    wrap = date_parse('Course Wrap')
    ndays = (wrap - launch).days
    nweeks = ndays / 7.0

    print "Course length = %6.2f weeks (%d days)" % (nweeks, ndays)

    if pin_date:
        datedir = pin_date
    course_dir = find_course_sql_dir(course_id, basedir, datedir, use_dataset_latest and not pin_date)
    cfn = gsutil.path_from_course_id(course_id)

    xbfn = course_dir / ("xbundle_%s.xml" % cfn)
    
    if not xbfn.exists():
        print "[analyze_content] cannot find xbundle file %s for %s!" % (xbfn, course_id)

        if use_dataset_latest:
            # try looking in earlier directories for xbundle file
            import glob
            spath = course_dir / ("../*/xbundle_%s.xml" % cfn)
            files = list(glob.glob(spath))
            if files:
                xbfn = path(files[-1])
            if not xbfn.exists():
                print "   --> also cannot find any %s ; aborting!" % spath
            else:

def load_all_daily_logs_for_course(course_id, gsbucket="gs://x-data", verbose=True, wait=False,
                                   check_dates=True):
    '''
    Load daily tracking logs for course from google storage into BigQuery.
    
    If wait=True then waits for loading jobs to be completed.  It's desirable to wait
    if subsequent jobs which need these tables (like person_day) are to be run
    immediately afterwards.
    '''

    print "Loading daily tracking logs for course %s into BigQuery (start: %s)" % (course_id, datetime.datetime.now())
    sys.stdout.flush()
    gsroot = gsutil.path_from_course_id(course_id)

    mypath = os.path.dirname(os.path.realpath(__file__))
    SCHEMA = json.loads(open('%s/schemas/schema_tracking_log.json' % mypath).read())['tracking_log']

    gsdir = '%s/%s/DAILY/' % (gsbucket, gsroot)

    fnset = gsutil.get_gs_file_list(gsdir)
  
    dataset = bqutil.course_id2dataset(gsroot, dtype="logs")
  
    # create this dataset if necessary
    bqutil.create_dataset_if_nonexistent(dataset)

    tables = bqutil.get_list_of_table_ids(dataset)
    tables = [x for x in tables if x.startswith('track')]

def course_key_version(course_id, logs_dir="TRACKING_LOGS", verbose=False):

    cdir = path(logs_dir) / gsutil.path_from_course_id(course_id)
    
    log_files = glob.glob(cdir / "*.json.gz")
    
    # find a file that's not too small
    for fn in log_files:
        if path(fn).stat().st_size > 65536:
            break

    if verbose:
        print "Using %s for course_key_version determination" % fn
    count = 0
    n = 0
    with gzip.GzipFile(fn) as fp:
        for k in fp:
            n += 1
            if 'block-v1:' in k:

print "extracting logs for course %s" % course_id

    # list of dates to dump
    dates = daterange(d2dt(start), d2dt(end))
    
    if verbose:
        print "Dates to dump:", [x['dstr'] for x in dates]

    # what files already on gs?
    gspath = "%s/DAILY" % gs_path_from_course_id(course_id)
    gsfiles = get_gs_file_list(gspath)

    DIR = tracking_logs_directory
    if not os.path.exists(DIR):
        os.mkdir(DIR)
    DIR += '/' + path_from_course_id(course_id)
    if not os.path.exists(DIR):
        os.mkdir(DIR)

    filebuf = []
    for k in range(len(dates)-1):
                          
        d = dates[k]
        ofn = '%s/tracklog-%s.json.gz' % (DIR, d['dstr'])
        start = d['start']
        end = d['end']

        ofnb = os.path.basename(ofn)

        if ofnb in gsfiles:
            print "Already have %s, skipping" % ofnb
            sys.stdout.flush()

def process_dir(course_id, gspath='gs://x-data', logs_directory="TRACKING_LOGS", verbose=True):

    cdir = path(logs_directory) / gsutil.path_from_course_id(course_id)

    print "="*77
    print "Transferring tracking logs for %s from directory %s (start %s)" % (course_id, cdir, datetime.datetime.now())
    print "="*77

    if not os.path.exists(cdir):
        print "Oops!  non-existent course tracking logs directory %s" % cdir
        return

    sys.stdout.flush()
    cdir = path(cdir)
    gp = path(gspath + "/" + cdir.basename()) / 'DAILY'
    filelist = gsutil.get_gs_file_list(gp)
    # print filelist
    local_files = glob.glob(cdir / 'tracklog*.gz')
    local_files.sort()