# Stackdriver Monitoring API . projects . collectdTimeSeries

## Instance Methods

Stackdriver Monitoring Agent only: Creates a new time series.

This method is only for use by the Stackdriver Monitoring Agent. Use projects.timeSeries.create instead.

### Method Details

`create(name, body, x__xgafv=None)`

    Stackdriver Monitoring Agent only: Creates a new time series.This method is only for use by the Stackdriver Monitoring Agent. Use projects.timeSeries.create instead.

    Args:
      name: string, The project in which to create the time series. The format is "projects/PROJECT_ID_OR_NUMBER". (required)
      body: object, The request body. (required)
        The object takes the form of:

    { # The CreateCollectdTimeSeries request.
        "collectdPayloads": [ # The collectd payloads representing the time series data. You must not include more than a single point for each time series, so no two payloads can have the same values for all of the fields plugin, plugin_instance, type, and type_instance.
          { # A collection of data points sent from a collectd-based plugin. See the collectd documentation for more information.
            "plugin": "A String", # The name of the plugin. Example: "disk".
            "typeInstance": "A String", # The measurement type instance. Example: "used".
            "values": [ # The measured values during this time interval. Each value must have a different dataSourceName.
              { # A single data point from a collectd-based plugin.
                "dataSourceType": "A String", # The type of measurement.
                "dataSourceName": "A String", # The data source for the collectd value. For example there are two data sources for network measurements: "rx" and "tx".
                "value": { # A single strongly-typed value. # The measurement value.
                  "distributionValue": { # Distribution contains summary statistics for a population of values. It optionally contains a histogram representing the distribution of those values across a set of buckets.The summary statistics are the count, mean, sum of the squared deviation from the mean, the minimum, and the maximum of the set of population of values. The histogram is based on a sequence of buckets and gives a count of values that fall into each bucket. The boundaries of the buckets are given either explicitly or by formulas for buckets of fixed or exponentially increasing widths.Although it is not forbidden, it is generally a bad idea to include non-finite values (infinities or NaNs) in the population of values, as this will render the mean and sum_of_squared_deviation fields meaningless. # A distribution value.
                    "count": "A String", # The number of values in the population. Must be non-negative. This value must equal the sum of the values in bucket_counts if a histogram is provided.
                    "bucketCounts": [ # Required in the Stackdriver Monitoring API v3. The values for each bucket specified in bucket_options. The sum of the values in bucketCounts must equal the value in the count field of the Distribution object. The order of the bucket counts follows the numbering schemes described for the three bucket types. The underflow bucket has number 0; the finite buckets, if any, have numbers 1 through N-2; and the overflow bucket has number N-1. The size of bucket_counts must not be greater than N. If the size is less than N, then the remaining buckets are assigned values of zero.
                      "A String",
                    ],
                    "bucketOptions": { # BucketOptions describes the bucket boundaries used to create a histogram for the distribution. The buckets can be in a linear sequence, an exponential sequence, or each bucket can be specified explicitly. BucketOptions does not include the number of values in each bucket.A bucket has an inclusive lower bound and exclusive upper bound for the values that are counted for that bucket. The upper bound of a bucket must be strictly greater than the lower bound. The sequence of N buckets for a distribution consists of an underflow bucket (number 0), zero or more finite buckets (number 1 through N - 2) and an overflow bucket (number N - 1). The buckets are contiguous: the lower bound of bucket i (i > 0) is the same as the upper bound of bucket i - 1. The buckets span the whole range of finite values: lower bound of the underflow bucket is -infinity and the upper bound of the overflow bucket is +infinity. The finite buckets are so-called because both bounds are finite. # Required in the Stackdriver Monitoring API v3. Defines the histogram bucket boundaries.
                      "exponentialBuckets": { # Specifies an exponential sequence of buckets that have a width that is proportional to the value of the lower bound. Each bucket represents a constant relative uncertainty on a specific value in the bucket.There are num_finite_buckets + 2 (= N) buckets. Bucket i has the following boundaries:Upper bound (0 <= i < N-1): scale * (growth_factor ^ i).  Lower bound (1 <= i < N): scale * (growth_factor ^ (i - 1)). # The exponential buckets.
                        "scale": 3.14, # Must be greater than 0.
                        "growthFactor": 3.14, # Must be greater than 1.
                        "numFiniteBuckets": 42, # Must be greater than 0.
                      },
                      "linearBuckets": { # Specifies a linear sequence of buckets that all have the same width (except overflow and underflow). Each bucket represents a constant absolute uncertainty on the specific value in the bucket.There are num_finite_buckets + 2 (= N) buckets. Bucket i has the following boundaries:Upper bound (0 <= i < N-1): offset + (width * i).  Lower bound (1 <= i < N): offset + (width * (i - 1)). # The linear bucket.
                        "width": 3.14, # Must be greater than 0.
                        "numFiniteBuckets": 42, # Must be greater than 0.
                        "offset": 3.14, # Lower bound of the first bucket.
                      },
                      "explicitBuckets": { # Specifies a set of buckets with arbitrary widths.There are size(bounds) + 1 (= N) buckets. Bucket i has the following boundaries:Upper bound (0 <= i < N-1): boundsi  Lower bound (1 <= i < N); boundsi - 1The bounds field must contain at least one element. If bounds has only one element, then there are no finite buckets, and that single element is the common boundary of the overflow and underflow buckets. # The explicit buckets.
                        "bounds": [ # The values must be monotonically increasing.
                          3.14,
                        ],
                      },
                    },
                    "range": { # The range of the population values. # If specified, contains the range of the population values. The field must not be present if the count is zero. This field is presently ignored by the Stackdriver Monitoring API v3.
                      "max": 3.14, # The maximum of the population values.
                      "min": 3.14, # The minimum of the population values.
                    },
                    "sumOfSquaredDeviation": 3.14, # The sum of squared deviations from the mean of the values in the population. For values x_i this is:
                        # Sum[i=1..n]((x_i - mean)^2)
                        # Knuth, "The Art of Computer Programming", Vol. 2, page 323, 3rd edition describes Welford's method for accumulating this sum in one pass.If count is zero then this field must be zero.
                    "mean": 3.14, # The arithmetic mean of the values in the population. If count is zero then this field must be zero.
                  },
                  "stringValue": "A String", # A variable-length string value.
                  "int64Value": "A String", # A 64-bit integer. Its range is approximately ±9.2x1018.
                  "doubleValue": 3.14, # A 64-bit double-precision floating-point number. Its magnitude is approximately ±10±300 and it has 16 significant digits of precision.
                  "boolValue": True or False, # A Boolean value: true or false.
                },
              },
            ],
            "startTime": "A String", # The start time of the interval.
            "endTime": "A String", # The end time of the interval.
            "type": "A String", # The measurement type. Example: "memory".
            "pluginInstance": "A String", # The instance name of the plugin Example: "hdcl".
            "metadata": { # The measurement metadata. Example: "process_id" -> 12345
              "a_key": { # A single strongly-typed value.
                "distributionValue": { # Distribution contains summary statistics for a population of values. It optionally contains a histogram representing the distribution of those values across a set of buckets.The summary statistics are the count, mean, sum of the squared deviation from the mean, the minimum, and the maximum of the set of population of values. The histogram is based on a sequence of buckets and gives a count of values that fall into each bucket. The boundaries of the buckets are given either explicitly or by formulas for buckets of fixed or exponentially increasing widths.Although it is not forbidden, it is generally a bad idea to include non-finite values (infinities or NaNs) in the population of values, as this will render the mean and sum_of_squared_deviation fields meaningless. # A distribution value.
                  "count": "A String", # The number of values in the population. Must be non-negative. This value must equal the sum of the values in bucket_counts if a histogram is provided.
                  "bucketCounts": [ # Required in the Stackdriver Monitoring API v3. The values for each bucket specified in bucket_options. The sum of the values in bucketCounts must equal the value in the count field of the Distribution object. The order of the bucket counts follows the numbering schemes described for the three bucket types. The underflow bucket has number 0; the finite buckets, if any, have numbers 1 through N-2; and the overflow bucket has number N-1. The size of bucket_counts must not be greater than N. If the size is less than N, then the remaining buckets are assigned values of zero.
                    "A String",
                  ],
                  "bucketOptions": { # BucketOptions describes the bucket boundaries used to create a histogram for the distribution. The buckets can be in a linear sequence, an exponential sequence, or each bucket can be specified explicitly. BucketOptions does not include the number of values in each bucket.A bucket has an inclusive lower bound and exclusive upper bound for the values that are counted for that bucket. The upper bound of a bucket must be strictly greater than the lower bound. The sequence of N buckets for a distribution consists of an underflow bucket (number 0), zero or more finite buckets (number 1 through N - 2) and an overflow bucket (number N - 1). The buckets are contiguous: the lower bound of bucket i (i > 0) is the same as the upper bound of bucket i - 1. The buckets span the whole range of finite values: lower bound of the underflow bucket is -infinity and the upper bound of the overflow bucket is +infinity. The finite buckets are so-called because both bounds are finite. # Required in the Stackdriver Monitoring API v3. Defines the histogram bucket boundaries.
                    "exponentialBuckets": { # Specifies an exponential sequence of buckets that have a width that is proportional to the value of the lower bound. Each bucket represents a constant relative uncertainty on a specific value in the bucket.There are num_finite_buckets + 2 (= N) buckets. Bucket i has the following boundaries:Upper bound (0 <= i < N-1): scale * (growth_factor ^ i).  Lower bound (1 <= i < N): scale * (growth_factor ^ (i - 1)). # The exponential buckets.
                      "scale": 3.14, # Must be greater than 0.
                      "growthFactor": 3.14, # Must be greater than 1.
                      "numFiniteBuckets": 42, # Must be greater than 0.
                    },
                    "linearBuckets": { # Specifies a linear sequence of buckets that all have the same width (except overflow and underflow). Each bucket represents a constant absolute uncertainty on the specific value in the bucket.There are num_finite_buckets + 2 (= N) buckets. Bucket i has the following boundaries:Upper bound (0 <= i < N-1): offset + (width * i).  Lower bound (1 <= i < N): offset + (width * (i - 1)). # The linear bucket.
                      "width": 3.14, # Must be greater than 0.
                      "numFiniteBuckets": 42, # Must be greater than 0.
                      "offset": 3.14, # Lower bound of the first bucket.
                    },
                    "explicitBuckets": { # Specifies a set of buckets with arbitrary widths.There are size(bounds) + 1 (= N) buckets. Bucket i has the following boundaries:Upper bound (0 <= i < N-1): boundsi  Lower bound (1 <= i < N); boundsi - 1The bounds field must contain at least one element. If bounds has only one element, then there are no finite buckets, and that single element is the common boundary of the overflow and underflow buckets. # The explicit buckets.
                      "bounds": [ # The values must be monotonically increasing.
                        3.14,
                      ],
                    },
                  },
                  "range": { # The range of the population values. # If specified, contains the range of the population values. The field must not be present if the count is zero. This field is presently ignored by the Stackdriver Monitoring API v3.
                    "max": 3.14, # The maximum of the population values.
                    "min": 3.14, # The minimum of the population values.
                  },
                  "sumOfSquaredDeviation": 3.14, # The sum of squared deviations from the mean of the values in the population. For values x_i this is:
                      # Sum[i=1..n]((x_i - mean)^2)
                      # Knuth, "The Art of Computer Programming", Vol. 2, page 323, 3rd edition describes Welford's method for accumulating this sum in one pass.If count is zero then this field must be zero.
                  "mean": 3.14, # The arithmetic mean of the values in the population. If count is zero then this field must be zero.
                },
                "stringValue": "A String", # A variable-length string value.
                "int64Value": "A String", # A 64-bit integer. Its range is approximately ±9.2x1018.
                "doubleValue": 3.14, # A 64-bit double-precision floating-point number. Its magnitude is approximately ±10±300 and it has 16 significant digits of precision.
                "boolValue": True or False, # A Boolean value: true or false.
              },
            },
          },
        ],
        "resource": { # An object representing a resource that can be used for monitoring, logging, billing, or other purposes. Examples include virtual machine instances, databases, and storage devices such as disks. The type field identifies a MonitoredResourceDescriptor object that describes the resource's schema. Information in the labels field identifies the actual resource and its attributes according to the schema. For example, a particular Compute Engine VM instance could be represented by the following object, because the MonitoredResourceDescriptor for "gce_instance" has labels "instance_id" and "zone": # The monitored resource associated with the time series.
            # { "type": "gce_instance",
            #   "labels": { "instance_id": "12345678901234",
            #               "zone": "us-central1-a" }}
          "labels": { # Required. Values for all of the labels listed in the associated monitored resource descriptor. For example, Compute Engine VM instances use the labels "project_id", "instance_id", and "zone".
            "a_key": "A String",
          },
          "type": "A String", # Required. The monitored resource type. This field must match the type field of a MonitoredResourceDescriptor object. For example, the type of a Compute Engine VM instance is gce_instance.
        },
        "collectdVersion": "A String", # The version of collectd that collected the data. Example: "5.3.0-192.el6".
      }

      x__xgafv: string, V1 error format.
        Allowed values
          1 - v1 error format
          2 - v2 error format

    Returns:
      An object of the form:

        { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance:
          # service Foo {
          #   rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty);
          # }
          # The JSON representation for Empty is empty JSON object {}.
      }