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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 lifetimes(self, dates, include_start_date, country_codes):
 """ Compute a DataFrame representing asset lifetimes for the specified date range. Parameters dates : pd.DatetimeIndex The dates for which to compute lifetimes. include_start_date : bool Whether or not to count the asset as alive on its start_date. This is useful in a backtesting context where `lifetimes` is being used to signify "do I have data for this asset as of the morning of this date?" For many financial metrics, (e.g. daily close), data isn't available for an asset until the end of the asset's first day. country_codes : iterable[str] The country codes to get lifetimes for. Returns ------- lifetimes : pd.DataFrame A frame of dtype bool with `dates` as index and an Int64Index of assets as columns. The value at `lifetimes.loc[date, asset]` will be True iff `asset` existed on `date`. If `include_start_date` is False, then lifetimes.loc[date, asset] will be false when date == asset.start_date. See Also -------- numpy.putmask zipline.pipeline.engine.SimplePipelineEngine._compute_root_mask """

        if isinstance(country_codes, string_types):
            raise TypeError(
                "Got string {!r} instead of an iterable of strings in "
                "AssetFinder.lifetimes.".format(country_codes),
            )

        # normalize to a cache-key so that we can memoize results.
        country_codes = frozenset(country_codes)

        lifetimes = self._asset_lifetimes.get(country_codes)
        if lifetimes is None:
            self._asset_lifetimes[country_codes] = lifetimes = (
                self._compute_asset_lifetimes(country_codes)
            )

        raw_dates = as_column(dates.asi8)
        if include_start_date:
            mask = lifetimes.start <= raw_dates
        else:
            mask = lifetimes.start < raw_dates
        mask &= (raw_dates <= lifetimes.end)

        return pd.DataFrame(mask, index=dates, columns=lifetimes.sid)