## Get certificates time series

`radar.ct.timeseries(CTTimeseriesParams**kwargs)  -> CTTimeseriesResponse`

**get** `/radar/ct/timeseries`

Retrieves certificate volume over time.

### Parameters

- `agg_interval: Optional[Literal["15m", "1h", "1d", "1w"]]`

  Aggregation interval of the results (e.g., in 15 minutes or 1 hour intervals). Refer to [Aggregation intervals](https://edgetunnel-b2h.pages.dev/radar/concepts/aggregation-intervals/). When omitted, the interval is auto-selected from the requested date range; finer intervals are only available for shorter ranges. If the requested interval is too granular for the date range, the request is rejected.

  - `"15m"`

  - `"1h"`

  - `"1d"`

  - `"1w"`

- `ca: Optional[Sequence[str]]`

  Filters results by certificate authority.

- `ca_owner: Optional[Sequence[str]]`

  Filters results by certificate authority owner.

- `date_end: Optional[Sequence[Union[str, datetime]]]`

  End of the date range (inclusive). Alternative to `dateRange`; provide together with `dateStart`. When requesting comparison series, every series must resolve to the same duration as the main series. Each `dateStart`/`dateEnd` is floored to the nearest 15 minutes before evaluation, so windows whose durations match only before alignment may be rejected.

- `date_range: Optional[Sequence[str]]`

  Filters results by relative date range ending at the current time, with each value producing a separate series. Use `<n>d` for days (up to `364d`) or `<n>w` for weeks (up to `52w`). Append `control` to request the equivalent previous period for comparison: the comparison window is shifted back by the current window's length rounded up to a whole number of weeks, so it keeps the same weekday alignment and does not overlap the current window (e.g. `7dcontrol` covers days -14 to -7, `10dcontrol` covers days -24 to -14). For example, pass `7d` and `7dcontrol` to compare this week with the previous week. All series must resolve to the same duration as the main series; relative ranges (including `control`) satisfy this automatically. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters).

- `date_start: Optional[Sequence[Union[str, datetime]]]`

  Start of the date range. Alternative to `dateRange`; provide together with `dateEnd`. When requesting comparison series, every series must resolve to the same duration as the main series. Each `dateStart`/`dateEnd` is floored to the nearest 15 minutes before evaluation, so windows whose durations match only before alignment may be rejected.

- `duration: Optional[List[Literal["LTE_3D", "GT_3D_LTE_7D", "GT_7D_LTE_10D", 4 more]]]`

  Filters results by certificate duration.

  - `"LTE_3D"`

  - `"GT_3D_LTE_7D"`

  - `"GT_7D_LTE_10D"`

  - `"GT_10D_LTE_47D"`

  - `"GT_47D_LTE_100D"`

  - `"GT_100D_LTE_200D"`

  - `"GT_200D"`

- `entry_type: Optional[List[Literal["PRECERTIFICATE", "CERTIFICATE"]]]`

  Filters results by entry type (certificate vs. pre-certificate). Incompatible with the `tld` filter/dimension.

  - `"PRECERTIFICATE"`

  - `"CERTIFICATE"`

- `expiration_status: Optional[List[Literal["EXPIRED", "VALID"]]]`

  Filters results by expiration status (expired vs. valid).

  - `"EXPIRED"`

  - `"VALID"`

- `format: Optional[Literal["JSON", "CSV"]]`

  Format in which results will be returned.

  - `"JSON"`

  - `"CSV"`

- `has_ips: Optional[Iterable[bool]]`

  Filters results based on whether the certificates are bound to specific IP addresses.

- `has_wildcards: Optional[Iterable[bool]]`

  Filters results based on whether the certificates contain wildcard domains.

- `log: Optional[Sequence[str]]`

  Filters results by certificate log. Incompatible with the `tld` filter/dimension.

- `log_api: Optional[List[Literal["RFC6962", "STATIC"]]]`

  Filters results by certificate log API (RFC6962 vs. static). Incompatible with the `tld` filter/dimension.

  - `"RFC6962"`

  - `"STATIC"`

- `log_operator: Optional[Sequence[str]]`

  Filters results by certificate log operator. Incompatible with the `tld` filter/dimension.

- `name: Optional[Sequence[str]]`

  Array of names used to label the series in the response.

- `public_key_algorithm: Optional[List[Literal["DSA", "ECDSA", "RSA"]]]`

  Filters results by public key algorithm.

  - `"DSA"`

  - `"ECDSA"`

  - `"RSA"`

- `signature_algorithm: Optional[List[Literal["DSA_SHA_1", "DSA_SHA_256", "ECDSA_SHA_1", 12 more]]]`

  Filters results by signature algorithm.

  - `"DSA_SHA_1"`

  - `"DSA_SHA_256"`

  - `"ECDSA_SHA_1"`

  - `"ECDSA_SHA_256"`

  - `"ECDSA_SHA_384"`

  - `"ECDSA_SHA_512"`

  - `"PSS_SHA_256"`

  - `"PSS_SHA_384"`

  - `"PSS_SHA_512"`

  - `"RSA_MD2"`

  - `"RSA_MD5"`

  - `"RSA_SHA_1"`

  - `"RSA_SHA_256"`

  - `"RSA_SHA_384"`

  - `"RSA_SHA_512"`

- `tld: Optional[Sequence[str]]`

  Filters results by top-level domain. Incompatible with the `log`, `logApi`, `logOperator`, and `entryType` filters/dimensions.

- `unique_entries: Optional[List[Literal["true", "false"]]]`

  Specifies whether to filter out duplicate certificates and pre-certificates. Set to true for unique entries only.

  - `"true"`

  - `"false"`

- `validation_level: Optional[List[Literal["DOMAIN", "ORGANIZATION", "EXTENDED"]]]`

  Filters results by validation level.

  - `"DOMAIN"`

  - `"ORGANIZATION"`

  - `"EXTENDED"`

### Returns

- `class CTTimeseriesResponse: …`

  - `meta: Meta`

    Metadata for the results.

    - `agg_interval: Literal["FIFTEEN_MINUTES", "ONE_HOUR", "ONE_DAY", 2 more]`

      Aggregation interval of the results (e.g., in 15 minutes or 1 hour intervals). Refer to [Aggregation intervals](https://edgetunnel-b2h.pages.dev/radar/concepts/aggregation-intervals/).

      - `"FIFTEEN_MINUTES"`

      - `"ONE_HOUR"`

      - `"ONE_DAY"`

      - `"ONE_WEEK"`

      - `"ONE_MONTH"`

    - `confidence_info: MetaConfidenceInfo`

      - `annotations: List[MetaConfidenceInfoAnnotation]`

        - `data_source: Literal["ALL", "AI_BOTS", "AI_GATEWAY", 22 more]`

          Data source for annotations.

          - `"ALL"`

          - `"AI_BOTS"`

          - `"AI_GATEWAY"`

          - `"BGP"`

          - `"BOTS"`

          - `"CONNECTION_ANOMALY"`

          - `"CT"`

          - `"DNS"`

          - `"DNS_MAGNITUDE"`

          - `"DNS_AS112"`

          - `"DOS"`

          - `"EMAIL_ROUTING"`

          - `"EMAIL_SECURITY"`

          - `"FW"`

          - `"FW_PG"`

          - `"HTTP"`

          - `"HTTP_CONTROL"`

          - `"HTTP_CRAWLER_REFERER"`

          - `"HTTP_ORIGINS"`

          - `"IQI"`

          - `"LEAKED_CREDENTIALS"`

          - `"NET"`

          - `"ROBOTS_TXT"`

          - `"SPEED"`

          - `"WORKERS_AI"`

        - `description: str`

        - `end_date: datetime`

        - `event_type: Literal["EVENT", "GENERAL", "OUTAGE", 3 more]`

          Event type for annotations.

          - `"EVENT"`

          - `"GENERAL"`

          - `"OUTAGE"`

          - `"PARTIAL_PROJECTION"`

          - `"PIPELINE"`

          - `"TRAFFIC_ANOMALY"`

        - `is_instantaneous: bool`

          Whether event is a single point in time or a time range.

        - `linked_url: str`

        - `start_date: datetime`

        - `tags: Optional[List[str]]`

      - `level: int`

        Provides an indication of how much confidence Cloudflare has in the data.

    - `date_range: List[MetaDateRange]`

      - `end_time: datetime`

        Adjusted end of date range.

      - `start_time: datetime`

        Adjusted start of date range.

    - `last_updated: datetime`

      Timestamp of the last dataset update.

    - `normalization: Literal["PERCENTAGE", "MIN0_MAX", "MIN_MAX", 5 more]`

      Normalization method applied to the results. Refer to [Normalization methods](https://edgetunnel-b2h.pages.dev/radar/concepts/normalization/).

      - `"PERCENTAGE"`

      - `"MIN0_MAX"`

      - `"MIN_MAX"`

      - `"RAW_VALUES"`

      - `"PERCENTAGE_CHANGE"`

      - `"ROLLING_AVERAGE"`

      - `"OVERLAPPED_PERCENTAGE"`

      - `"RATIO"`

    - `units: List[MetaUnit]`

      Measurement units for the results.

      - `name: str`

      - `value: str`

### Example

```python
import os
from cloudflare import Cloudflare

client = Cloudflare(
    api_token=os.environ.get("CLOUDFLARE_API_TOKEN"),  # This is the default and can be omitted
)
response = client.radar.ct.timeseries()
print(response.meta)
```

#### Response

```json
{
  "result": {
    "meta": {
      "aggInterval": "FIFTEEN_MINUTES",
      "confidenceInfo": {
        "annotations": [
          {
            "dataSource": "ALL",
            "description": "Cable cut in Tonga",
            "endDate": "2019-12-27T18:11:19.117Z",
            "eventType": "EVENT",
            "isInstantaneous": true,
            "linkedUrl": "https://example.com",
            "startDate": "2019-12-27T18:11:19.117Z",
            "tags": [
              "BOT_CLASS"
            ]
          }
        ],
        "level": 0
      },
      "dateRange": [
        {
          "endTime": "2022-09-17T10:22:57.555Z",
          "startTime": "2022-09-16T10:22:57.555Z"
        }
      ],
      "lastUpdated": "2019-12-27T18:11:19.117Z",
      "normalization": "PERCENTAGE",
      "units": [
        {
          "name": "*",
          "value": "requests"
        }
      ]
    }
  },
  "success": true
}
```