<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def getReportTable(reportzipfile,tablefilename,inReportsDir=True,verbose=False):
 """Get a pandas table from a previous report Args: reportzipfile (str):
 Zip folder location, '.zip' extension is optional. tablefilename (str or list int):
 Table location within the zip folder. Can be provided as the filename within the zip folder, or a list of integers indicating its exact position (1-indexed). If you provide an empty string or list, all available table filenames in the zip folder will be printed. inReportsDir (bool):
 Search reportzipfile relative to reportsDir. Returns: pd.DataFrame """

        import zipfile, io, re

        # zipfilename preparation
        if not reportzipfile.endswith('.zip'): reportzipfile+='.zip'
        if inReportsDir: reportzipfile = os.path.join(reportsDir,reportzipfile)
        with zipfile.ZipFile(reportzipfile) as z:
            # print all table filenames if tablefilename is not provided
            if not tablefilename:
                for f in z.filelist:
                    if 'table' in f.filename: print(f.filename)
                return
            # tablefilename preparation if int list
            if isinstance(tablefilename,list):
                tablelocation = tablefilename
                tablefilename = None
                location = re.compile(r'(s|table)(\d+)_')
                for f in z.filelist:
                    if 'table' not in f.filename or f.filename.count('/') != (len(tablelocation)-1): continue
                    if [int(location.match(s).groups()[1]) for s in f.filename.split('/')] == tablelocation:
                        tablefilename = f.filename
                        if verbose: print('Loading',tablefilename)
                        break
                if tablefilename is None: raise FileNotFoundError('Table location not found in zip folder.')
            # read table
            with z.open(tablefilename) as f:
                ft = io.TextIOWrapper(f)
                return pd.read_csv(ft,index_col=0,sep=csvsep,decimal=csvdec)