# Ad Exchange Buyer API II . bidders . filterSets . bidMetrics

## Instance Methods

Lists all metrics that are measured in terms of number of bids.

Retrieves the next page of results.

### Method Details

`list(filterSetName=None, 123, pageToken=None, pageSize=None, x__xgafv=None)`

    Lists all metrics that are measured in terms of number of bids.

    Args:
      filterSetName: string, Name of the filter set that should be applied to the requested metrics.
    For example:

    - For a bidder-level filter set for bidder 123:
      `bidders/123/filterSets/abc`

    - For an account-level filter set for the buyer account representing bidder
      123: `bidders/123/accounts/123/filterSets/abc`

    - For an account-level filter set for the child seat buyer account 456
      whose bidder is 123: `bidders/123/accounts/456/filterSets/abc` (required)
      pageToken: string, A token identifying a page of results the server should return.
    Typically, this is the value of
    ListBidMetricsResponse.nextPageToken
    returned from the previous call to the bidMetrics.list
    method.
      pageSize: integer, Requested page size. The server may return fewer results than requested.
    If unspecified, the server will pick an appropriate default.
      x__xgafv: string, V1 error format.
        Allowed values
          1 - v1 error format
          2 - v2 error format

    Returns:
      An object of the form:

        { # Response message for listing the metrics that are measured in number of bids.
        "bidMetricsRows": [ # List of rows, each containing a set of bid metrics.
          { # The set of metrics that are measured in numbers of bids, representing how
              # many bids with the specified dimension values were considered eligible at
              # each stage of the bidding funnel;
            "rowDimensions": { # A response may include multiple rows, breaking down along various dimensions. # The values of all dimensions associated with metric values in this row.
                # Encapsulates the values of all dimensions for a given row.
              "timeInterval": { # An interval of time, with an absolute start and end. # The time interval that this row represents.
                "endTime": "A String", # The timestamp marking the end of the range (exclusive) for which data is
                    # included.
                "startTime": "A String", # The timestamp marking the start of the range (inclusive) for which data is
                    # included.
              },
              "publisherIdentifier": "A String", # The publisher identifier for this row, if a breakdown by
                  # [BreakdownDimension.PUBLISHER_IDENTIFIER](https://developers.google.com/authorized-buyers/apis/reference/rest/v2beta1/bidders.accounts.filterSets#FilterSet.BreakdownDimension)
                  # was requested.
            },
            "impressionsWon": { # A metric value, with an expected value and a variance; represents a count # The number of bids that won the auction.
                # that may be either exact or estimated (i.e. when sampled).
              "variance": "A String", # The variance (i.e. square of the standard deviation) of the metric value.
                  # If value is exact, variance is 0.
                  # Can be used to calculate margin of error as a percentage of value, using
                  # the following formula, where Z is the standard constant that depends on the
                  # desired size of the confidence interval (e.g. for 90% confidence interval,
                  # use Z = 1.645):
                  #
                  #   marginOfError = 100 * Z * sqrt(variance) / value
              "value": "A String", # The expected value of the metric.
            },
            "viewableImpressions": { # A metric value, with an expected value and a variance; represents a count # The number of bids for which the corresponding impression was viewable (as
                # defined by Active View).
                # that may be either exact or estimated (i.e. when sampled).
              "variance": "A String", # The variance (i.e. square of the standard deviation) of the metric value.
                  # If value is exact, variance is 0.
                  # Can be used to calculate margin of error as a percentage of value, using
                  # the following formula, where Z is the standard constant that depends on the
                  # desired size of the confidence interval (e.g. for 90% confidence interval,
                  # use Z = 1.645):
                  #
                  #   marginOfError = 100 * Z * sqrt(variance) / value
              "value": "A String", # The expected value of the metric.
            },
            "billedImpressions": { # A metric value, with an expected value and a variance; represents a count # The number of bids for which the buyer was billed.
                # that may be either exact or estimated (i.e. when sampled).
              "variance": "A String", # The variance (i.e. square of the standard deviation) of the metric value.
                  # If value is exact, variance is 0.
                  # Can be used to calculate margin of error as a percentage of value, using
                  # the following formula, where Z is the standard constant that depends on the
                  # desired size of the confidence interval (e.g. for 90% confidence interval,
                  # use Z = 1.645):
                  #
                  #   marginOfError = 100 * Z * sqrt(variance) / value
              "value": "A String", # The expected value of the metric.
            },
            "measurableImpressions": { # A metric value, with an expected value and a variance; represents a count # The number of bids for which the corresponding impression was measurable
                # for viewability (as defined by Active View).
                # that may be either exact or estimated (i.e. when sampled).
              "variance": "A String", # The variance (i.e. square of the standard deviation) of the metric value.
                  # If value is exact, variance is 0.
                  # Can be used to calculate margin of error as a percentage of value, using
                  # the following formula, where Z is the standard constant that depends on the
                  # desired size of the confidence interval (e.g. for 90% confidence interval,
                  # use Z = 1.645):
                  #
                  #   marginOfError = 100 * Z * sqrt(variance) / value
              "value": "A String", # The expected value of the metric.
            },
            "bidsInAuction": { # A metric value, with an expected value and a variance; represents a count # The number of bids that were permitted to compete in the auction.
                # that may be either exact or estimated (i.e. when sampled).
              "variance": "A String", # The variance (i.e. square of the standard deviation) of the metric value.
                  # If value is exact, variance is 0.
                  # Can be used to calculate margin of error as a percentage of value, using
                  # the following formula, where Z is the standard constant that depends on the
                  # desired size of the confidence interval (e.g. for 90% confidence interval,
                  # use Z = 1.645):
                  #
                  #   marginOfError = 100 * Z * sqrt(variance) / value
              "value": "A String", # The expected value of the metric.
            },
            "reachedQueries": { # A metric value, with an expected value and a variance; represents a count # The number of bids that won the auction and also won the mediation
                # waterfall (if any).
                # that may be either exact or estimated (i.e. when sampled).
              "variance": "A String", # The variance (i.e. square of the standard deviation) of the metric value.
                  # If value is exact, variance is 0.
                  # Can be used to calculate margin of error as a percentage of value, using
                  # the following formula, where Z is the standard constant that depends on the
                  # desired size of the confidence interval (e.g. for 90% confidence interval,
                  # use Z = 1.645):
                  #
                  #   marginOfError = 100 * Z * sqrt(variance) / value
              "value": "A String", # The expected value of the metric.
            },
            "bids": { # A metric value, with an expected value and a variance; represents a count # The number of bids that Ad Exchange received from the buyer.
                # that may be either exact or estimated (i.e. when sampled).
              "variance": "A String", # The variance (i.e. square of the standard deviation) of the metric value.
                  # If value is exact, variance is 0.
                  # Can be used to calculate margin of error as a percentage of value, using
                  # the following formula, where Z is the standard constant that depends on the
                  # desired size of the confidence interval (e.g. for 90% confidence interval,
                  # use Z = 1.645):
                  #
                  #   marginOfError = 100 * Z * sqrt(variance) / value
              "value": "A String", # The expected value of the metric.
            },
          },
        ],
        "nextPageToken": "A String", # A token to retrieve the next page of results.
            # Pass this value in the
            # ListBidMetricsRequest.pageToken
            # field in the subsequent call to the bidMetrics.list
            # method to retrieve the next page of results.
      }

`list_next(previous_request, previous_response)`

    Retrieves the next page of results.

    Args:
      previous_request: The request for the previous page. (required)
      previous_response: The response from the request for the previous page. (required)

    Returns:
      A request object that you can call 'execute()' on to request the next
      page. Returns None if there are no more items in the collection.