Data Extract API
Enterprise Reporting data can be downloaded from Cloud using the Cypress Cloud API. The data is returned in file formats that allow you to easily incorporate it into your BI reporting platform, as well as a JSON file that can be programmatically parsed. This API allows you to retrieve your test data at a variety of levels, including all the way down to the individual test result data which includes status, error messages, runs tags and groups, Test Replay links, and much more.
All of the data that is viewable in Enterprise Reporting can be retrieved using this API.
Premium Cypress Cloud Feature
Data extract API is available to users with an Enterprise Cypress Cloud plan.
Overview of the API​
The reporting data is accessed using an API key that can be accessed from Cloud. Visit Integrations → Enterprise API in Cypress Cloud and copy the API key that has been created for your organization. There is nothing to enable. If you are subscribed to the Enterprise Cypress Cloud plan the ability to access your test data via API is already enabled.
A couple of things to note:
- Data shown in Enterprise Reporting is not real-time. It is available as of midnight UTC of the current day. I.e. - data will be populated through "end of day yesterday".
- Historical data is available as specified by your data retention limit in Cypress Cloud.
API endpoint details​
The following API endpoint will be used. Substitute your assigned API key
where indicated by the YOUR-API-KEY placeholder text. The report_id specifies
the type of data that will be retrieved.
The following query parameters are available for use:
-
start_date. Required and should be passed in either yyyy-MM-dd or yyyy-MM-ddTHH:mm:ss format.
For example, to request a start date of September 1, 2024, use:
?start_date=2024-09-01. To request a start date of 12:30p UTC on that day, use:?start_date=2024-09-01T12%3A30%3A00 -
end_date. Optional and should be passed in either yyyy-MM-dd or yyyy-MM-ddTHH:mm:ss format. If no end date is specified the query will default to today.
For example, to request an end date of start of day September 1, 2024, use:
?end_date=2024-09-01. To request an end date of 12:30p UTC on that day, use:?end_date=2024-09-01T12%3A30%3A00 -
projects. Optional, and accepts the name of your Cypress project. The project name should be URL encoded. You can pass as many projects parameters as needed.
For example, to request that the data be filtered for projects Project e2e and Phoenix, use:
&projects=Project%20e2e&projects=Phoenix -
export_format. Specify the type of data format that will be returned in the response file. Valid options include:
csv,json,xlsx
Project list​
Retrieves a list of all projects in Cypress Cloud that have had tests recorded since the start_date. The ID returned is used in the URL for project level analytics in Cypress Cloud and can be helpful to generate direct links to Cypress Cloud project analytics for a given project.
The report_id is: project-list
Data returned includes:
- project_name
- id
Tests per project​
This data helps you understand which projects in your organization are utilizing the most or least tests. Data is returned in a simple summary per project.
The report_id is: usage-per-project-summary
Data returned includes:
- project_name
- test_run_count
Tests per project over time​
This data helps you understand which projects in your organization are utilizing the most or least tests and how that usage looks over time.
The report_id is: usage-per-project-over-time
Data returned includes:
- project_name
- test_run_count
- week
- day
Status by run​
This data helps you understand the success and failure rates at the run level. If any part of the run fails then the entire run is failed.
The report_id is: status-per-build-summary
Data returned includes:
- status
- test_run_count
Status by run over time​
This data helps you understand the success and failure rates at the run level. If any part of the run fails then the entire run is failed. The data is reported over time.
The report_id is: status-per-build-over-time
Data returned includes:
- status
- test_run_count
- week
- day
Status by spec​
This data helps you understand the success and failure rates at the spec level. If any part of the spec fails then the entire spec is failed.
The report_id is: status-per-spec-summary
Data returned includes:
- status
- test_run_count
Status by spec over time​
This data helps you understand the success and failure rates at the spec level. If any part of the spec fails then the entire spec is failed. The data is reported over time.
The report_id is: status-per-spec-over-time
Data returned includes:
- status
- test_run_count
- week
- day
Status by test run​
This data helps you understand the success and failure rates at the individual test level.
The report_id is: status-per-test-summary
Data returned includes:
- failed
- passed
Status by test run over time​
This data helps you understand the success and failure rates at the individual test level. The data is reported over time.
The report_id is: status-per-test-over-time
Data returned includes:
- project_name
- test_run_count
- week
- status
Cypress run versions​
This data helps you monitor and track which versions of the Cypress app are being used in your organization.
The report_id is: cypress-build-versions-summary
Data returned includes:
- run_count
- cypress_version
Cypress run versions over time​
This data helps you monitor and track which versions of the Cypress app are being used in your organization. This data is reported over time.
The report_id is: cypress-build-versions-over-time
Data returned includes:
- run_count
- cypress_version
- week
Cypress run versions per project over time​
This data helps you monitor and track which versions of the Cypress app are being used in your organization. The versions are reported at the project level. This data is reported over time.
The report_id is: cypress-build-versions-per-project-over-time
Data returned includes:
- project_name
- run_count
- cypress_version
- week
Browsers tested​
This data helps you monitor and track which web browsers are being tested in your organization.
The report_id is: browsers-tested
Data returned includes:
- spec_count
- browser
Browser versions tested​
This data helps you monitor and track which web browsers and specific versions are being tested in your organization.
The report_id is: browser-versions
Data returned includes:
- spec_count
- browser
- version
Browser versions tested over time​
This data helps you monitor and track which web browsers and specific versions are being tested in your organization. This data is reported over time.
The report_id is: browser-versions-over-time
Data returned includes:
- spec_count
- browser
- version
- day
- week
Browser versions tested per project over time​
This data about browser versions goes a step deeper and helps you monitor and track which web browsers and specific versions are being tested within your specific projects. This data is reported over time.
The report_id is: browser-versions-per-project-over-time
Data returned includes:
- project_name
- spec_count
- browser
- version
- day
- week
Cypress test types​
This data helps you to grow and manage your Cypress test suite by understanding how you are adopting end-to-end and component testing in your organization.
The report_id is: cypress-test-types
Data returned includes:
- testing_type (e2e or component)
- total_tests
- total_e2e
- total_ct
- week
- day
Cypress test suite size​
This data helps you to understand and manage the growth of your test suite size across all projects in your organization. It calculates the average number of test cases executed per run and excludes runs that errored or timed out since they don't accurately represent the size of your test suite.
The report_id is: test-suite-size-summary
Data returned includes:
- total_tests
- total_e2e
- total_ct
- week
Cypress test suite over time​
This data helps you to understand and manage the growth of your test suite size across all projects in your organization. It calculates the average number of test cases executed per run and excludes runs that errored or timed out since they don't accurately represent the size of your test suite. This data is reported over time.
The report_id is: test-suite-size-over-time
Data returned includes:
- project_name
- total_tests
- total_e2e
- total_ct
- week
Project test count and status​
This data allows you to extract consolidated run status at the project level. Data is accumulated from the status of each individual test result. This data is reported over time.
The report_id is: status-per-test-daily
Data returned includes:
- project_name
- status
- test_run_count
- week
- day
Individual spec results​
This data allows you to extract all spec results regardless of spec result status. The maximum number of records returned is 500,000. Make multiple requests with different start_date and end_date parameter values if your volume of records will exceed 500k for a single request.
The report_id is: spec-details
Data returned includes:
- project_name
- created_at (date and time)
- run_number
- commit_author_name
- spec (path and filename)
- status
- total_tests
- pass_tests
- flaky_tests
- fail_tests
- parallel_enabled
- commit_branch
- group_name
- failed_spec_prioritized
- spec_duration (milliseconds)
- browser_name
- browser_version
- os_name
- os_version
Individual failed test results​
This report allows you to extract all test result details for failed tests. The maximum number of records returned is 500,000. Make multiple requests with different start_date and end_date parameter values if your volume of records will exceed 500k for a single request.
The report_id is: failed-test-details
Data returned includes:
- project_name
- created_at (date and time)
- run_number
- commit_author_name
- commit_branch
- commit_sha
- ci_build_id
- status
- group_name
- run_tags (string array)
- error_name (string array)
- error_message (string array)
- test_replay_url
Individual test results​
This report allows you to extract all test result details regardless of test result status. The maximum number of records returned is 500,000. Make multiple requests with different start_date and end_date parameter values if your volume of records will exceed 500k for a single request.
The report_id is: test-details
Data returned includes:
- project_name
- created_at (date and time)
- run_number
- commit_author_name
- commit_branch
- commit_sha
- ci_build_id
- status
- group_name
- run_tags (string array)
- test_duration
- error_name (string array)
- error_message (string array)
- test_replay_url
Average run duration over time​
This report allows you to retrieve the average, median, min and max durations of passing runs. This data is reported over time.
The report_id is: average-passing-build-duration
Data returned includes:
- project_name
- run_count
- avg_pass_run_duration (average)
- mdn_pass_run_duration (median)
- min_pass_run_duration (min)
- max_pass_run_duration (max)
- day
- week
Average spec duration over time​
This report allows you to retrieve the average, median, min and max durations of specs. This data is reported over time. The maximum number of records returned is 500,000. Make multiple requests with different start_date and end_date parameter values if your volume of records will exceed 500k for a single request.
The report_id is: average-passing-spec-duration
Data returned includes:
- project_name
- spec (path and filename)
- spec_count
- avg_pass_spec_duration (average)
- mdn_pass_spec_duration (median)
- min_pass_spec_duration (min)
- max_pass_spec_duration (max)
- day
- week
Test flake detail over time​
This data helps you identify where flake is occurring in your organization and how that changes over time.
The report_id is: flake-per-project-over-time
Data returned includes:
- project_name
- flaky_test_count
- week
- day
Flaky rate per project​
This report allows you to understand the flaky rate occuring in your projects, not just the count of flaky tests. Sometimes a high flake count is seen simply because the test runs very frequently, but the % of flake could be lower than in other tests that run less often. The flaky rate per project is calculated for the time period requested. Flaky rate is shown as a whole number. For example: 1 flaky test over 4 runs has a flaky rate of 25.
The report_id is: flake-rate-per-project
Data returned includes:
- project_name
- flaky_test_count
- pass_test_count
- flaky_rate
Flaky rate per project over time​
This report allows you to understand the flaky rate occuring in your projects, not just the count of flaky tests. Sometimes a high flake count is seen simply because the test runs very frequently, but the % of flake could be lower than in other tests that run less often. The flaky rate per project is calculated for the time period requested. Flaky rate is shown as a whole number. For example: 1 flaky test over 4 runs has a flaky rate of 25.
The report_id is: flake-rate-per-project-over-time
Data returned includes:
- project_name
- flaky_test_count
- pass_test_count
- flaky_rate
- day
- week
Flaky test details​
This report allows you to extract all test result details of flaky tests. The maximum number of records returned is 500,000. Make multiple requests with different start_date and end_date parameter values if your volume of records will exceed 500k for a single request.
The report_id is: flaky-test-details
Data returned includes:
- project_name
- created_at (date and time)
- run_number
- commit_author_name
- commit_branch
- commit_sha
- ci_build_id
- status
- group_name
- run_tags (string array)
- error_name (string array)
- error_message (string array)
- test_replay_url
Top flaky tests per project​
This report allows you to understand which tests have the highest flaky count and provides a URL to an example of a recent occurrence of this flake. Enables teams to jump directly to Cypress Cloud for troubleshooting using test replay.
The report_id is: top-flaky-per-project
Data returned includes:
- project_name
- flaky_count
- spec (path and filename)
- test_replay_url
Top failures per project​
This report allows you to understand which tests have the highest number of failures and provides a URL to an example of a recent occurrence of this failure. Enables teams to jump directly to Cypress Cloud and understand the full context surrounding the failure. Fail rate is shown as a whole number. For example: 1 failed test over 4 runs has a fail rate of 25.
The report_id is: top-failures-per-project
Data returned includes:
- project_name
- cnt_passed
- cnt_failed
- cnt_total
- fail_rate
- spec (path and filename)
- test_replay_url
Top errors per project​
This report allows you to understand which tests have the highest number of errors and provides a URL to an example of a recent occurrence of this error. Data is grouped by the error type and the error message. Enables teams to jump directly to Cypress Cloud and understand the full context surrounding the failure.
The report_id is: top-errors-per-project
Data returned includes:
- project_name
- test_result_uuid (the unique ID of the test in Cypress Cloud that can provide a direct URL to the test)
- error_type
- error_message
- error_count
- test_replay_url