mux_python.MetricsApi

All URIs are relative to https://api.mux.com

Method	HTTP request	Description
get_metric_timeseries_data	GET /data/v1/metrics/{METRIC_ID}/timeseries	Get metric timeseries data
get_overall_values	GET /data/v1/metrics/{METRIC_ID}/overall	Get Overall values
list_all_metric_values	GET /data/v1/metrics/comparison	List all metric values
list_breakdown_values	GET /data/v1/metrics/{METRIC_ID}/breakdown	List breakdown values
list_insights	GET /data/v1/metrics/{METRIC_ID}/insights	List Insights

get_metric_timeseries_data

GetMetricTimeseriesDataResponse get_metric_timeseries_data(metric_id, timeframe=timeframe, filters=filters, metric_filters=metric_filters, measurement=measurement, order_direction=order_direction, group_by=group_by)

Get metric timeseries data

Returns timeseries data for a specific metric. Each interval represented in the data array contains an array with the following values: * the first element is the interval time * the second element is the calculated metric value * the third element is the number of views in the interval that have a valid metric value

Example

Basic Authentication (accessToken):

from __future__ import print_function
import time
import mux_python
from mux_python.rest import ApiException
from pprint import pprint
# Defining the host is optional and defaults to https://api.mux.com
# See configuration.py for a list of all supported configuration parameters.
configuration = mux_python.Configuration(
    host = "https://api.mux.com"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure HTTP basic authorization: accessToken
configuration = mux_python.Configuration(
    username = 'YOUR_USERNAME',
    password = 'YOUR_PASSWORD'
)

# Enter a context with an instance of the API client
with mux_python.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = mux_python.MetricsApi(api_client)
    metric_id = 'video_startup_time' # str | ID of the Metric
timeframe = ['timeframe_example'] # list[str] | Timeframe window to limit results by. Must be provided as an array query string parameter (e.g. timeframe[]=).  Accepted formats are...    * array of epoch timestamps e.g. `timeframe[]=1498867200&timeframe[]=1498953600`   * duration string e.g. `timeframe[]=24:hours or timeframe[]=7:days`  (optional)
filters = ['filters_example'] # list[str] | Limit the results to rows that match conditions from provided key:value pairs. Must be provided as an array query string parameter.  To exclude rows that match a certain condition, prepend a `!` character to the dimension.  Possible filter names are the same as returned by the List Filters endpoint.  Example:    * `filters[]=operating_system:windows&filters[]=!country:US`  (optional)
metric_filters = ['metric_filters_example'] # list[str] | Limit the results to rows that match inequality conditions from provided metric comparison clauses. Must be provided as an array query string parameter.  Possible filterable metrics are the same as the set of metric ids, with the exceptions of `exits_before_video_start`, `unique_viewers`, `video_startup_failure_percentage`, `view_dropped_percentage`, and `views`.  Example:    * `metric_filters[]=aggregate_startup_time>=1000`  (optional)
measurement = 'measurement_example' # str | Measurement for the provided metric. If omitted, the default for the metric will be used. The default measurement for each metric is: \"sum\" : `ad_attempt_count`, `ad_break_count`, `ad_break_error_count`, `ad_error_count`, `ad_impression_count`, `playing_time` \"median\" : `ad_preroll_startup_time`, `aggregate_startup_time`, `content_startup_time`, `max_downscale_percentage`, `max_upscale_percentage`, `page_load_time`, `player_average_live_latency`, `player_startup_time`, `rebuffer_count`, `rebuffer_duration`, `requests_for_first_preroll`, `video_startup_preroll_load_time`, `video_startup_preroll_request_time`, `video_startup_time`, `view_average_request_latency`, `view_average_request_throughput`, `view_max_request_latency`, `weighted_average_bitrate` \"avg\" : `ad_break_error_percentage`, `ad_error_percentage`, `ad_exit_before_start_count`, `ad_exit_before_start_percentage`, `ad_playback_failure_percentage`, `ad_startup_error_count`, `ad_startup_error_percentage`, `content_playback_failure_percentage`, `downscale_percentage`, `exits_before_video_start`, `playback_business_exception_percentage`, `playback_failure_percentage`, `playback_success_score`, `rebuffer_frequency`, `rebuffer_percentage`, `seek_latency`, `smoothness_score`, `startup_time_score`, `upscale_percentage`, `video_quality_score`, `video_startup_business_exception_percentage`, `video_startup_failure_percentage`, `view_dropped_percentage`, `viewer_experience_score` \"count\" : `started_views`, `unique_viewers`  (optional)
order_direction = 'order_direction_example' # str | Sort order. (optional)
group_by = 'group_by_example' # str | Time granularity to group results by. If this value is omitted, a default granularity is chosen based on the timeframe.  For timeframes of less than 90 minutes, the default granularity is `minute`. Between 90 minutes and 6 hours, the default granularity is `ten_minutes`. Between 6 hours and 15 days inclusive, the default granularity is `hour`. The granularity of timeframes that exceed 15 days is `day`. This default behavior is subject to change; it is strongly suggested that you explicitly specify the granularity.  (optional)

    try:
        # Get metric timeseries data
        api_response = api_instance.get_metric_timeseries_data(metric_id, timeframe=timeframe, filters=filters, metric_filters=metric_filters, measurement=measurement, order_direction=order_direction, group_by=group_by)
        pprint(api_response)
    except ApiException as e:
        print("Exception when calling MetricsApi->get_metric_timeseries_data: %s\n" % e)

Parameters

Name	Type	Description	Notes
metric_id	str	ID of the Metric
timeframe	list[str]	Timeframe window to limit results by. Must be provided as an array query string parameter (e.g. timeframe[]=). Accepted formats are... * array of epoch timestamps e.g. `timeframe[]=1498867200&timeframe[]=1498953600` * duration string e.g. `timeframe[]=24:hours or timeframe[]=7:days`	[optional]
filters	list[str]	Limit the results to rows that match conditions from provided key:value pairs. Must be provided as an array query string parameter. To exclude rows that match a certain condition, prepend a `!` character to the dimension. Possible filter names are the same as returned by the List Filters endpoint. Example: * `filters[]=operating_system:windows&filters[]=!country:US`	[optional]
metric_filters	list[str]	Limit the results to rows that match inequality conditions from provided metric comparison clauses. Must be provided as an array query string parameter. Possible filterable metrics are the same as the set of metric ids, with the exceptions of `exits_before_video_start`, `unique_viewers`, `video_startup_failure_percentage`, `view_dropped_percentage`, and `views`. Example: * `metric_filters[]=aggregate_startup_time>=1000`	[optional]
measurement	str	Measurement for the provided metric. If omitted, the default for the metric will be used. The default measurement for each metric is: "sum" : `ad_attempt_count`, `ad_break_count`, `ad_break_error_count`, `ad_error_count`, `ad_impression_count`, `playing_time` "median" : `ad_preroll_startup_time`, `aggregate_startup_time`, `content_startup_time`, `max_downscale_percentage`, `max_upscale_percentage`, `page_load_time`, `player_average_live_latency`, `player_startup_time`, `rebuffer_count`, `rebuffer_duration`, `requests_for_first_preroll`, `video_startup_preroll_load_time`, `video_startup_preroll_request_time`, `video_startup_time`, `view_average_request_latency`, `view_average_request_throughput`, `view_max_request_latency`, `weighted_average_bitrate` "avg" : `ad_break_error_percentage`, `ad_error_percentage`, `ad_exit_before_start_count`, `ad_exit_before_start_percentage`, `ad_playback_failure_percentage`, `ad_startup_error_count`, `ad_startup_error_percentage`, `content_playback_failure_percentage`, `downscale_percentage`, `exits_before_video_start`, `playback_business_exception_percentage`, `playback_failure_percentage`, `playback_success_score`, `rebuffer_frequency`, `rebuffer_percentage`, `seek_latency`, `smoothness_score`, `startup_time_score`, `upscale_percentage`, `video_quality_score`, `video_startup_business_exception_percentage`, `video_startup_failure_percentage`, `view_dropped_percentage`, `viewer_experience_score` "count" : `started_views`, `unique_viewers`	[optional]
order_direction	str	Sort order.	[optional]
group_by	str	Time granularity to group results by. If this value is omitted, a default granularity is chosen based on the timeframe. For timeframes of less than 90 minutes, the default granularity is `minute`. Between 90 minutes and 6 hours, the default granularity is `ten_minutes`. Between 6 hours and 15 days inclusive, the default granularity is `hour`. The granularity of timeframes that exceed 15 days is `day`. This default behavior is subject to change; it is strongly suggested that you explicitly specify the granularity.	[optional]

Return type

GetMetricTimeseriesDataResponse

Authorization

accessToken

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	OK	-

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get_overall_values

GetOverallValuesResponse get_overall_values(metric_id, timeframe=timeframe, filters=filters, metric_filters=metric_filters, measurement=measurement)

Get Overall values

Returns the overall value for a specific metric, as well as the total view count, watch time, and the Mux Global metric value for the metric.

Example

Basic Authentication (accessToken):

from __future__ import print_function
import time
import mux_python
from mux_python.rest import ApiException
from pprint import pprint
# Defining the host is optional and defaults to https://api.mux.com
# See configuration.py for a list of all supported configuration parameters.
configuration = mux_python.Configuration(
    host = "https://api.mux.com"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure HTTP basic authorization: accessToken
configuration = mux_python.Configuration(
    username = 'YOUR_USERNAME',
    password = 'YOUR_PASSWORD'
)

# Enter a context with an instance of the API client
with mux_python.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = mux_python.MetricsApi(api_client)
    metric_id = 'video_startup_time' # str | ID of the Metric
timeframe = ['timeframe_example'] # list[str] | Timeframe window to limit results by. Must be provided as an array query string parameter (e.g. timeframe[]=).  Accepted formats are...    * array of epoch timestamps e.g. `timeframe[]=1498867200&timeframe[]=1498953600`   * duration string e.g. `timeframe[]=24:hours or timeframe[]=7:days`  (optional)
filters = ['filters_example'] # list[str] | Limit the results to rows that match conditions from provided key:value pairs. Must be provided as an array query string parameter.  To exclude rows that match a certain condition, prepend a `!` character to the dimension.  Possible filter names are the same as returned by the List Filters endpoint.  Example:    * `filters[]=operating_system:windows&filters[]=!country:US`  (optional)
metric_filters = ['metric_filters_example'] # list[str] | Limit the results to rows that match inequality conditions from provided metric comparison clauses. Must be provided as an array query string parameter.  Possible filterable metrics are the same as the set of metric ids, with the exceptions of `exits_before_video_start`, `unique_viewers`, `video_startup_failure_percentage`, `view_dropped_percentage`, and `views`.  Example:    * `metric_filters[]=aggregate_startup_time>=1000`  (optional)
measurement = 'measurement_example' # str | Measurement for the provided metric. If omitted, the default for the metric will be used. The default measurement for each metric is: \"sum\" : `ad_attempt_count`, `ad_break_count`, `ad_break_error_count`, `ad_error_count`, `ad_impression_count`, `playing_time` \"median\" : `ad_preroll_startup_time`, `aggregate_startup_time`, `content_startup_time`, `max_downscale_percentage`, `max_upscale_percentage`, `page_load_time`, `player_average_live_latency`, `player_startup_time`, `rebuffer_count`, `rebuffer_duration`, `requests_for_first_preroll`, `video_startup_preroll_load_time`, `video_startup_preroll_request_time`, `video_startup_time`, `view_average_request_latency`, `view_average_request_throughput`, `view_max_request_latency`, `weighted_average_bitrate` \"avg\" : `ad_break_error_percentage`, `ad_error_percentage`, `ad_exit_before_start_count`, `ad_exit_before_start_percentage`, `ad_playback_failure_percentage`, `ad_startup_error_count`, `ad_startup_error_percentage`, `content_playback_failure_percentage`, `downscale_percentage`, `exits_before_video_start`, `playback_business_exception_percentage`, `playback_failure_percentage`, `playback_success_score`, `rebuffer_frequency`, `rebuffer_percentage`, `seek_latency`, `smoothness_score`, `startup_time_score`, `upscale_percentage`, `video_quality_score`, `video_startup_business_exception_percentage`, `video_startup_failure_percentage`, `view_dropped_percentage`, `viewer_experience_score` \"count\" : `started_views`, `unique_viewers`  (optional)

    try:
        # Get Overall values
        api_response = api_instance.get_overall_values(metric_id, timeframe=timeframe, filters=filters, metric_filters=metric_filters, measurement=measurement)
        pprint(api_response)
    except ApiException as e:
        print("Exception when calling MetricsApi->get_overall_values: %s\n" % e)

Parameters

Name	Type	Description	Notes
metric_id	str	ID of the Metric
timeframe	list[str]	Timeframe window to limit results by. Must be provided as an array query string parameter (e.g. timeframe[]=). Accepted formats are... * array of epoch timestamps e.g. `timeframe[]=1498867200&timeframe[]=1498953600` * duration string e.g. `timeframe[]=24:hours or timeframe[]=7:days`	[optional]
filters	list[str]	Limit the results to rows that match conditions from provided key:value pairs. Must be provided as an array query string parameter. To exclude rows that match a certain condition, prepend a `!` character to the dimension. Possible filter names are the same as returned by the List Filters endpoint. Example: * `filters[]=operating_system:windows&filters[]=!country:US`	[optional]
metric_filters	list[str]	Limit the results to rows that match inequality conditions from provided metric comparison clauses. Must be provided as an array query string parameter. Possible filterable metrics are the same as the set of metric ids, with the exceptions of `exits_before_video_start`, `unique_viewers`, `video_startup_failure_percentage`, `view_dropped_percentage`, and `views`. Example: * `metric_filters[]=aggregate_startup_time>=1000`	[optional]
measurement	str	Measurement for the provided metric. If omitted, the default for the metric will be used. The default measurement for each metric is: "sum" : `ad_attempt_count`, `ad_break_count`, `ad_break_error_count`, `ad_error_count`, `ad_impression_count`, `playing_time` "median" : `ad_preroll_startup_time`, `aggregate_startup_time`, `content_startup_time`, `max_downscale_percentage`, `max_upscale_percentage`, `page_load_time`, `player_average_live_latency`, `player_startup_time`, `rebuffer_count`, `rebuffer_duration`, `requests_for_first_preroll`, `video_startup_preroll_load_time`, `video_startup_preroll_request_time`, `video_startup_time`, `view_average_request_latency`, `view_average_request_throughput`, `view_max_request_latency`, `weighted_average_bitrate` "avg" : `ad_break_error_percentage`, `ad_error_percentage`, `ad_exit_before_start_count`, `ad_exit_before_start_percentage`, `ad_playback_failure_percentage`, `ad_startup_error_count`, `ad_startup_error_percentage`, `content_playback_failure_percentage`, `downscale_percentage`, `exits_before_video_start`, `playback_business_exception_percentage`, `playback_failure_percentage`, `playback_success_score`, `rebuffer_frequency`, `rebuffer_percentage`, `seek_latency`, `smoothness_score`, `startup_time_score`, `upscale_percentage`, `video_quality_score`, `video_startup_business_exception_percentage`, `video_startup_failure_percentage`, `view_dropped_percentage`, `viewer_experience_score` "count" : `started_views`, `unique_viewers`	[optional]

Return type

GetOverallValuesResponse

Authorization

accessToken

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	OK	-

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list_all_metric_values

ListAllMetricValuesResponse list_all_metric_values(timeframe=timeframe, filters=filters, metric_filters=metric_filters, dimension=dimension, value=value)

List all metric values

List all of the values across every breakdown for a specific metric.

Example

Basic Authentication (accessToken):

from __future__ import print_function
import time
import mux_python
from mux_python.rest import ApiException
from pprint import pprint
# Defining the host is optional and defaults to https://api.mux.com
# See configuration.py for a list of all supported configuration parameters.
configuration = mux_python.Configuration(
    host = "https://api.mux.com"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure HTTP basic authorization: accessToken
configuration = mux_python.Configuration(
    username = 'YOUR_USERNAME',
    password = 'YOUR_PASSWORD'
)

# Enter a context with an instance of the API client
with mux_python.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = mux_python.MetricsApi(api_client)
    timeframe = ['timeframe_example'] # list[str] | Timeframe window to limit results by. Must be provided as an array query string parameter (e.g. timeframe[]=).  Accepted formats are...    * array of epoch timestamps e.g. `timeframe[]=1498867200&timeframe[]=1498953600`   * duration string e.g. `timeframe[]=24:hours or timeframe[]=7:days`  (optional)
filters = ['filters_example'] # list[str] | Limit the results to rows that match conditions from provided key:value pairs. Must be provided as an array query string parameter.  To exclude rows that match a certain condition, prepend a `!` character to the dimension.  Possible filter names are the same as returned by the List Filters endpoint.  Example:    * `filters[]=operating_system:windows&filters[]=!country:US`  (optional)
metric_filters = ['metric_filters_example'] # list[str] | Limit the results to rows that match inequality conditions from provided metric comparison clauses. Must be provided as an array query string parameter.  Possible filterable metrics are the same as the set of metric ids, with the exceptions of `exits_before_video_start`, `unique_viewers`, `video_startup_failure_percentage`, `view_dropped_percentage`, and `views`.  Example:    * `metric_filters[]=aggregate_startup_time>=1000`  (optional)
dimension = 'dimension_example' # str | Dimension the specified value belongs to (optional)
value = 'value_example' # str | Value to show all available metrics for (optional)

    try:
        # List all metric values
        api_response = api_instance.list_all_metric_values(timeframe=timeframe, filters=filters, metric_filters=metric_filters, dimension=dimension, value=value)
        pprint(api_response)
    except ApiException as e:
        print("Exception when calling MetricsApi->list_all_metric_values: %s\n" % e)

Parameters

Name	Type	Description	Notes
timeframe	list[str]	Timeframe window to limit results by. Must be provided as an array query string parameter (e.g. timeframe[]=). Accepted formats are... * array of epoch timestamps e.g. `timeframe[]=1498867200&timeframe[]=1498953600` * duration string e.g. `timeframe[]=24:hours or timeframe[]=7:days`	[optional]
filters	list[str]	Limit the results to rows that match conditions from provided key:value pairs. Must be provided as an array query string parameter. To exclude rows that match a certain condition, prepend a `!` character to the dimension. Possible filter names are the same as returned by the List Filters endpoint. Example: * `filters[]=operating_system:windows&filters[]=!country:US`	[optional]
metric_filters	list[str]	Limit the results to rows that match inequality conditions from provided metric comparison clauses. Must be provided as an array query string parameter. Possible filterable metrics are the same as the set of metric ids, with the exceptions of `exits_before_video_start`, `unique_viewers`, `video_startup_failure_percentage`, `view_dropped_percentage`, and `views`. Example: * `metric_filters[]=aggregate_startup_time>=1000`	[optional]
dimension	str	Dimension the specified value belongs to	[optional]
value	str	Value to show all available metrics for	[optional]

Return type

ListAllMetricValuesResponse

Authorization

accessToken

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	OK	-

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list_breakdown_values

ListBreakdownValuesResponse list_breakdown_values(metric_id, group_by=group_by, measurement=measurement, filters=filters, metric_filters=metric_filters, limit=limit, page=page, order_by=order_by, order_direction=order_direction, timeframe=timeframe)

List breakdown values

List the breakdown values for a specific metric.

Example

Basic Authentication (accessToken):

from __future__ import print_function
import time
import mux_python
from mux_python.rest import ApiException
from pprint import pprint
# Defining the host is optional and defaults to https://api.mux.com
# See configuration.py for a list of all supported configuration parameters.
configuration = mux_python.Configuration(
    host = "https://api.mux.com"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure HTTP basic authorization: accessToken
configuration = mux_python.Configuration(
    username = 'YOUR_USERNAME',
    password = 'YOUR_PASSWORD'
)

# Enter a context with an instance of the API client
with mux_python.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = mux_python.MetricsApi(api_client)
    metric_id = 'video_startup_time' # str | ID of the Metric
group_by = 'group_by_example' # str | Breakdown value to group the results by (optional)
measurement = 'measurement_example' # str | Measurement for the provided metric. If omitted, the default for the metric will be used. The default measurement for each metric is: \"sum\" : `ad_attempt_count`, `ad_break_count`, `ad_break_error_count`, `ad_error_count`, `ad_impression_count`, `playing_time` \"median\" : `ad_preroll_startup_time`, `aggregate_startup_time`, `content_startup_time`, `max_downscale_percentage`, `max_upscale_percentage`, `page_load_time`, `player_average_live_latency`, `player_startup_time`, `rebuffer_count`, `rebuffer_duration`, `requests_for_first_preroll`, `video_startup_preroll_load_time`, `video_startup_preroll_request_time`, `video_startup_time`, `view_average_request_latency`, `view_average_request_throughput`, `view_max_request_latency`, `weighted_average_bitrate` \"avg\" : `ad_break_error_percentage`, `ad_error_percentage`, `ad_exit_before_start_count`, `ad_exit_before_start_percentage`, `ad_playback_failure_percentage`, `ad_startup_error_count`, `ad_startup_error_percentage`, `content_playback_failure_percentage`, `downscale_percentage`, `exits_before_video_start`, `playback_business_exception_percentage`, `playback_failure_percentage`, `playback_success_score`, `rebuffer_frequency`, `rebuffer_percentage`, `seek_latency`, `smoothness_score`, `startup_time_score`, `upscale_percentage`, `video_quality_score`, `video_startup_business_exception_percentage`, `video_startup_failure_percentage`, `view_dropped_percentage`, `viewer_experience_score` \"count\" : `started_views`, `unique_viewers`  (optional)
filters = ['filters_example'] # list[str] | Limit the results to rows that match conditions from provided key:value pairs. Must be provided as an array query string parameter.  To exclude rows that match a certain condition, prepend a `!` character to the dimension.  Possible filter names are the same as returned by the List Filters endpoint.  Example:    * `filters[]=operating_system:windows&filters[]=!country:US`  (optional)
metric_filters = ['metric_filters_example'] # list[str] | Limit the results to rows that match inequality conditions from provided metric comparison clauses. Must be provided as an array query string parameter.  Possible filterable metrics are the same as the set of metric ids, with the exceptions of `exits_before_video_start`, `unique_viewers`, `video_startup_failure_percentage`, `view_dropped_percentage`, and `views`.  Example:    * `metric_filters[]=aggregate_startup_time>=1000`  (optional)
limit = 25 # int | Number of items to include in the response (optional) (default to 25)
page = 1 # int | Offset by this many pages, of the size of `limit` (optional) (default to 1)
order_by = 'order_by_example' # str | Value to order the results by (optional)
order_direction = 'order_direction_example' # str | Sort order. (optional)
timeframe = ['timeframe_example'] # list[str] | Timeframe window to limit results by. Must be provided as an array query string parameter (e.g. timeframe[]=).  Accepted formats are...    * array of epoch timestamps e.g. `timeframe[]=1498867200&timeframe[]=1498953600`   * duration string e.g. `timeframe[]=24:hours or timeframe[]=7:days`  (optional)

    try:
        # List breakdown values
        api_response = api_instance.list_breakdown_values(metric_id, group_by=group_by, measurement=measurement, filters=filters, metric_filters=metric_filters, limit=limit, page=page, order_by=order_by, order_direction=order_direction, timeframe=timeframe)
        pprint(api_response)
    except ApiException as e:
        print("Exception when calling MetricsApi->list_breakdown_values: %s\n" % e)

Parameters

Name	Type	Description	Notes
metric_id	str	ID of the Metric
group_by	str	Breakdown value to group the results by	[optional]
measurement	str	Measurement for the provided metric. If omitted, the default for the metric will be used. The default measurement for each metric is: "sum" : `ad_attempt_count`, `ad_break_count`, `ad_break_error_count`, `ad_error_count`, `ad_impression_count`, `playing_time` "median" : `ad_preroll_startup_time`, `aggregate_startup_time`, `content_startup_time`, `max_downscale_percentage`, `max_upscale_percentage`, `page_load_time`, `player_average_live_latency`, `player_startup_time`, `rebuffer_count`, `rebuffer_duration`, `requests_for_first_preroll`, `video_startup_preroll_load_time`, `video_startup_preroll_request_time`, `video_startup_time`, `view_average_request_latency`, `view_average_request_throughput`, `view_max_request_latency`, `weighted_average_bitrate` "avg" : `ad_break_error_percentage`, `ad_error_percentage`, `ad_exit_before_start_count`, `ad_exit_before_start_percentage`, `ad_playback_failure_percentage`, `ad_startup_error_count`, `ad_startup_error_percentage`, `content_playback_failure_percentage`, `downscale_percentage`, `exits_before_video_start`, `playback_business_exception_percentage`, `playback_failure_percentage`, `playback_success_score`, `rebuffer_frequency`, `rebuffer_percentage`, `seek_latency`, `smoothness_score`, `startup_time_score`, `upscale_percentage`, `video_quality_score`, `video_startup_business_exception_percentage`, `video_startup_failure_percentage`, `view_dropped_percentage`, `viewer_experience_score` "count" : `started_views`, `unique_viewers`	[optional]
filters	list[str]	Limit the results to rows that match conditions from provided key:value pairs. Must be provided as an array query string parameter. To exclude rows that match a certain condition, prepend a `!` character to the dimension. Possible filter names are the same as returned by the List Filters endpoint. Example: * `filters[]=operating_system:windows&filters[]=!country:US`	[optional]
metric_filters	list[str]	Limit the results to rows that match inequality conditions from provided metric comparison clauses. Must be provided as an array query string parameter. Possible filterable metrics are the same as the set of metric ids, with the exceptions of `exits_before_video_start`, `unique_viewers`, `video_startup_failure_percentage`, `view_dropped_percentage`, and `views`. Example: * `metric_filters[]=aggregate_startup_time>=1000`	[optional]
limit	int	Number of items to include in the response	[optional] [default to 25]
page	int	Offset by this many pages, of the size of `limit`	[optional] [default to 1]
order_by	str	Value to order the results by	[optional]
order_direction	str	Sort order.	[optional]
timeframe	list[str]	Timeframe window to limit results by. Must be provided as an array query string parameter (e.g. timeframe[]=). Accepted formats are... * array of epoch timestamps e.g. `timeframe[]=1498867200&timeframe[]=1498953600` * duration string e.g. `timeframe[]=24:hours or timeframe[]=7:days`	[optional]

Return type

ListBreakdownValuesResponse

Authorization

accessToken

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	OK	-

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list_insights

ListInsightsResponse list_insights(metric_id, measurement=measurement, order_direction=order_direction, timeframe=timeframe, filters=filters, metric_filters=metric_filters)

List Insights

Returns a list of insights for a metric. These are the worst performing values across all breakdowns sorted by how much they negatively impact a specific metric.

Example

Basic Authentication (accessToken):

from __future__ import print_function
import time
import mux_python
from mux_python.rest import ApiException
from pprint import pprint
# Defining the host is optional and defaults to https://api.mux.com
# See configuration.py for a list of all supported configuration parameters.
configuration = mux_python.Configuration(
    host = "https://api.mux.com"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure HTTP basic authorization: accessToken
configuration = mux_python.Configuration(
    username = 'YOUR_USERNAME',
    password = 'YOUR_PASSWORD'
)

# Enter a context with an instance of the API client
with mux_python.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = mux_python.MetricsApi(api_client)
    metric_id = 'video_startup_time' # str | ID of the Metric
measurement = 'measurement_example' # str | Measurement for the provided metric. If omitted, the default for the metric will be used. The default measurement for each metric is: \"sum\" : `ad_attempt_count`, `ad_break_count`, `ad_break_error_count`, `ad_error_count`, `ad_impression_count`, `playing_time` \"median\" : `ad_preroll_startup_time`, `aggregate_startup_time`, `content_startup_time`, `max_downscale_percentage`, `max_upscale_percentage`, `page_load_time`, `player_average_live_latency`, `player_startup_time`, `rebuffer_count`, `rebuffer_duration`, `requests_for_first_preroll`, `video_startup_preroll_load_time`, `video_startup_preroll_request_time`, `video_startup_time`, `view_average_request_latency`, `view_average_request_throughput`, `view_max_request_latency`, `weighted_average_bitrate` \"avg\" : `ad_break_error_percentage`, `ad_error_percentage`, `ad_exit_before_start_count`, `ad_exit_before_start_percentage`, `ad_playback_failure_percentage`, `ad_startup_error_count`, `ad_startup_error_percentage`, `content_playback_failure_percentage`, `downscale_percentage`, `exits_before_video_start`, `playback_business_exception_percentage`, `playback_failure_percentage`, `playback_success_score`, `rebuffer_frequency`, `rebuffer_percentage`, `seek_latency`, `smoothness_score`, `startup_time_score`, `upscale_percentage`, `video_quality_score`, `video_startup_business_exception_percentage`, `video_startup_failure_percentage`, `view_dropped_percentage`, `viewer_experience_score` \"count\" : `started_views`, `unique_viewers`  (optional)
order_direction = 'order_direction_example' # str | Sort order. (optional)
timeframe = ['timeframe_example'] # list[str] | Timeframe window to limit results by. Must be provided as an array query string parameter (e.g. timeframe[]=).  Accepted formats are...    * array of epoch timestamps e.g. `timeframe[]=1498867200&timeframe[]=1498953600`   * duration string e.g. `timeframe[]=24:hours or timeframe[]=7:days`  (optional)
filters = ['filters_example'] # list[str] | Limit the results to rows that match conditions from provided key:value pairs. Must be provided as an array query string parameter.  To exclude rows that match a certain condition, prepend a `!` character to the dimension.  Possible filter names are the same as returned by the List Filters endpoint.  Example:    * `filters[]=operating_system:windows&filters[]=!country:US`  (optional)
metric_filters = ['metric_filters_example'] # list[str] | Limit the results to rows that match inequality conditions from provided metric comparison clauses. Must be provided as an array query string parameter.  Possible filterable metrics are the same as the set of metric ids, with the exceptions of `exits_before_video_start`, `unique_viewers`, `video_startup_failure_percentage`, `view_dropped_percentage`, and `views`.  Example:    * `metric_filters[]=aggregate_startup_time>=1000`  (optional)

    try:
        # List Insights
        api_response = api_instance.list_insights(metric_id, measurement=measurement, order_direction=order_direction, timeframe=timeframe, filters=filters, metric_filters=metric_filters)
        pprint(api_response)
    except ApiException as e:
        print("Exception when calling MetricsApi->list_insights: %s\n" % e)

Parameters

Name	Type	Description	Notes
metric_id	str	ID of the Metric
measurement	str	Measurement for the provided metric. If omitted, the default for the metric will be used. The default measurement for each metric is: "sum" : `ad_attempt_count`, `ad_break_count`, `ad_break_error_count`, `ad_error_count`, `ad_impression_count`, `playing_time` "median" : `ad_preroll_startup_time`, `aggregate_startup_time`, `content_startup_time`, `max_downscale_percentage`, `max_upscale_percentage`, `page_load_time`, `player_average_live_latency`, `player_startup_time`, `rebuffer_count`, `rebuffer_duration`, `requests_for_first_preroll`, `video_startup_preroll_load_time`, `video_startup_preroll_request_time`, `video_startup_time`, `view_average_request_latency`, `view_average_request_throughput`, `view_max_request_latency`, `weighted_average_bitrate` "avg" : `ad_break_error_percentage`, `ad_error_percentage`, `ad_exit_before_start_count`, `ad_exit_before_start_percentage`, `ad_playback_failure_percentage`, `ad_startup_error_count`, `ad_startup_error_percentage`, `content_playback_failure_percentage`, `downscale_percentage`, `exits_before_video_start`, `playback_business_exception_percentage`, `playback_failure_percentage`, `playback_success_score`, `rebuffer_frequency`, `rebuffer_percentage`, `seek_latency`, `smoothness_score`, `startup_time_score`, `upscale_percentage`, `video_quality_score`, `video_startup_business_exception_percentage`, `video_startup_failure_percentage`, `view_dropped_percentage`, `viewer_experience_score` "count" : `started_views`, `unique_viewers`	[optional]
order_direction	str	Sort order.	[optional]
timeframe	list[str]	Timeframe window to limit results by. Must be provided as an array query string parameter (e.g. timeframe[]=). Accepted formats are... * array of epoch timestamps e.g. `timeframe[]=1498867200&timeframe[]=1498953600` * duration string e.g. `timeframe[]=24:hours or timeframe[]=7:days`	[optional]
filters	list[str]	Limit the results to rows that match conditions from provided key:value pairs. Must be provided as an array query string parameter. To exclude rows that match a certain condition, prepend a `!` character to the dimension. Possible filter names are the same as returned by the List Filters endpoint. Example: * `filters[]=operating_system:windows&filters[]=!country:US`	[optional]
metric_filters	list[str]	Limit the results to rows that match inequality conditions from provided metric comparison clauses. Must be provided as an array query string parameter. Possible filterable metrics are the same as the set of metric ids, with the exceptions of `exits_before_video_start`, `unique_viewers`, `video_startup_failure_percentage`, `view_dropped_percentage`, and `views`. Example: * `metric_filters[]=aggregate_startup_time>=1000`	[optional]

Return type

ListInsightsResponse

Authorization

accessToken

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	OK	-

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mux_python.MetricsApi

get_metric_timeseries_data

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

get_overall_values

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

list_all_metric_values

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

list_breakdown_values

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

list_insights

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details