Compatibility Testing Tool¶

This notebook walks you how to check compatibility of a given dataset with TiTiler-CMR.

See also How to use the Compatibility API.

In this notebook, you'll learn:

1. Use earthaccess to authenticate to NASA Earthdata and query the CMR catalog
2. Collect collection-level metadata (concept IDs, temporal range, spatial bounds)
3. Run check_titiler_cmr_compatibility against your TiTiler-CMR endpoint to validate whether a dataset can be successfully accessed via TiTiler-CMR.

Before you begin, you need:

• An Earthdata login account: https://urs.earthdata.nasa.gov/
• A valid netrc file with your Earthdata credentials or use interactive login.

For this walkthrough, we will use https://staging.openveda.cloud/api/titiler-cmr/.

In [1]:

import earthaccess
import xarray as xr

from datacube_benchmark import (
    DatasetParams,
    create_bbox_feature,
    check_titiler_cmr_compatibility,
)

endpoint = "https://staging.openveda.cloud/api/titiler-cmr"

import earthaccess import xarray as xr from datacube_benchmark import ( DatasetParams, create_bbox_feature, check_titiler_cmr_compatibility, ) endpoint = "https://staging.openveda.cloud/api/titiler-cmr"

titiler-cmr supports two different backends:

• xarray → for gridded/cloud-native datasets (e.g., NetCDF4/HDF5), typically exposed as variables.
• rasterio → for COG/raster imagery-style datasets exposed as bands (optionally via a regex).

Here, we first explore a dataset using earthaccess to collect the necessary information such as concept_id, backend, and variable, then run a compatibility check using the check_titiler_cmr_compatibility helper function. If you already know your dataset, you can skip the exploration step.

Step 1: Explore data with earthaccess¶

You can use earthaccess to search for dataset and inspect the individual granules used in your query. This helps you validate which files were accessed, their sizes, and the temporal range.

First you need to authenticate to Earthdata.

In [2]:

# Authenticate to Earthdata
try:
    auth = earthaccess.login(strategy="environment")
except Exception:
    auth = earthaccess.login(strategy="interactive")

# Authenticate to Earthdata try: auth = earthaccess.login(strategy="environment") except Exception: auth = earthaccess.login(strategy="interactive")

---------------------------------------------------------------------------
OSError                                   Traceback (most recent call last)
File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/urllib3/connection.py:204, in HTTPConnection._new_conn(self)
    203 try:
--> 204     sock = connection.create_connection(
    205         (self._dns_host, self.port),
    206         self.timeout,
    207         source_address=self.source_address,
    208         socket_options=self.socket_options,
    209     )
    210 except socket.gaierror as e:

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/urllib3/util/connection.py:85, in create_connection(address, timeout, source_address, socket_options)
     84 try:
---> 85     raise err
     86 finally:
     87     # Break explicitly a reference cycle

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/urllib3/util/connection.py:73, in create_connection(address, timeout, source_address, socket_options)
     72     sock.bind(source_address)
---> 73 sock.connect(sa)
     74 # Break explicitly a reference cycle

OSError: [Errno 101] Network is unreachable

The above exception was the direct cause of the following exception:

NewConnectionError                        Traceback (most recent call last)
File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/urllib3/connectionpool.py:787, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)
    786 # Make the request on the HTTPConnection object
--> 787 response = self._make_request(
    788     conn,
    789     method,
    790     url,
    791     timeout=timeout_obj,
    792     body=body,
    793     headers=headers,
    794     chunked=chunked,
    795     retries=retries,
    796     response_conn=response_conn,
    797     preload_content=preload_content,
    798     decode_content=decode_content,
    799     **response_kw,
    800 )
    802 # Everything went great!

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/urllib3/connectionpool.py:488, in HTTPConnectionPool._make_request(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)
    487         new_e = _wrap_proxy_error(new_e, conn.proxy.scheme)
--> 488     raise new_e
    490 # conn.request() calls http.client.*.request, not the method in
    491 # urllib3.request. It also calls makefile (recv) on the socket.

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/urllib3/connectionpool.py:464, in HTTPConnectionPool._make_request(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)
    463 try:
--> 464     self._validate_conn(conn)
    465 except (SocketTimeout, BaseSSLError) as e:

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/urllib3/connectionpool.py:1093, in HTTPSConnectionPool._validate_conn(self, conn)
   1092 if conn.is_closed:
-> 1093     conn.connect()
   1095 # TODO revise this, see https://github.com/urllib3/urllib3/issues/2791

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/urllib3/connection.py:759, in HTTPSConnection.connect(self)
    758 sock: socket.socket | ssl.SSLSocket
--> 759 self.sock = sock = self._new_conn()
    760 server_hostname: str = self.host

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/urllib3/connection.py:219, in HTTPConnection._new_conn(self)
    218 except OSError as e:
--> 219     raise NewConnectionError(
    220         self, f"Failed to establish a new connection: {e}"
    221     ) from e
    223 sys.audit("http.client.connect", self, self.host, self.port)

NewConnectionError: HTTPSConnection(host='urs.earthdata.nasa.gov', port=443): Failed to establish a new connection: [Errno 101] Network is unreachable

The above exception was the direct cause of the following exception:

MaxRetryError                             Traceback (most recent call last)
File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/requests/adapters.py:645, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies)
    644 try:
--> 645     resp = conn.urlopen(
    646         method=request.method,
    647         url=url,
    648         body=request.body,
    649         headers=request.headers,
    650         redirect=False,
    651         assert_same_host=False,
    652         preload_content=False,
    653         decode_content=False,
    654         retries=self.max_retries,
    655         timeout=timeout,
    656         chunked=chunked,
    657     )
    659 except (ProtocolError, OSError) as err:

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/urllib3/connectionpool.py:841, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)
    839     new_e = ProtocolError("Connection aborted.", new_e)
--> 841 retries = retries.increment(
    842     method, url, error=new_e, _pool=self, _stacktrace=sys.exc_info()[2]
    843 )
    844 retries.sleep()

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/urllib3/util/retry.py:535, in Retry.increment(self, method, url, response, error, _pool, _stacktrace)
    534     reason = error or ResponseError(cause)
--> 535     raise MaxRetryError(_pool, url, reason) from reason  # type: ignore[arg-type]
    537 log.debug("Incremented Retry for (url='%s'): %r", url, new_retry)

MaxRetryError: HTTPSConnectionPool(host='urs.earthdata.nasa.gov', port=443): Max retries exceeded with url: /api/users/find_or_create_token (Caused by NewConnectionError("HTTPSConnection(host='urs.earthdata.nasa.gov', port=443): Failed to establish a new connection: [Errno 101] Network is unreachable"))

During handling of the above exception, another exception occurred:

ConnectionError                           Traceback (most recent call last)
Cell In[2], line 3
      2 try:
----> 3     auth = earthaccess.login(strategy="environment")
      4 except Exception:

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/earthaccess/api.py:373, in login(strategy, persist, system)
    372 else:
--> 373     earthaccess.__auth__.login(
    374         strategy=strategy,
    375         persist=persist,
    376         system=system,
    377     )
    378     if earthaccess.__auth__.authenticated:

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/earthaccess/auth.py:148, in Auth.login(self, strategy, persist, system)
    147 elif strategy == "environment":
--> 148     self._environment()
    150 return self

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/earthaccess/auth.py:300, in Auth._environment(self)
    299 logger.debug("Using environment variables for EDL")
--> 300 return self._get_credentials(username, password, token)

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/earthaccess/auth.py:314, in Auth._get_credentials(self, username, password, user_token)
    313 self.password = password
--> 314 token_resp = self._find_or_create_token()
    316 if not (token_resp.ok):  # type: ignore

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/earthaccess/auth.py:332, in Auth._find_or_create_token(self)
    331 with self.get_session() as session:
--> 332     return session.post(
    333         self.EDL_FIND_OR_CREATE_TOKEN_URL,
    334         headers={"Accept": "application/json"},
    335         timeout=10,
    336     )

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/requests/sessions.py:640, in Session.post(self, url, data, json, **kwargs)
    630 r"""Sends a POST request. Returns :class:`Response` object.
    631 
    632 :param url: URL for the new :class:`Request` object.
   (...)
    637 :rtype: requests.Response
    638 """
--> 640 return self.request("POST", url, data=data, json=json, **kwargs)

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/requests/sessions.py:592, in Session.request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
    591 send_kwargs.update(settings)
--> 592 resp = self.send(prep, **send_kwargs)
    594 return resp

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/requests/sessions.py:706, in Session.send(self, request, **kwargs)
    705 # Send the request
--> 706 r = adapter.send(request, **kwargs)
    708 # Total elapsed time of the request (approximately)

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/requests/adapters.py:678, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies)
    676         raise SSLError(e, request=request)
--> 678     raise ConnectionError(e, request=request)
    680 except ClosedPoolError as e:

ConnectionError: HTTPSConnectionPool(host='urs.earthdata.nasa.gov', port=443): Max retries exceeded with url: /api/users/find_or_create_token (Caused by NewConnectionError("HTTPSConnection(host='urs.earthdata.nasa.gov', port=443): Failed to establish a new connection: [Errno 101] Network is unreachable"))

During handling of the above exception, another exception occurred:

StdinNotImplementedError                  Traceback (most recent call last)
Cell In[2], line 5
      3     auth = earthaccess.login(strategy="environment")
      4 except Exception:
----> 5     auth = earthaccess.login(strategy="interactive")

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/earthaccess/api.py:373, in login(strategy, persist, system)
    371             break
    372 else:
--> 373     earthaccess.__auth__.login(
    374         strategy=strategy,
    375         persist=persist,
    376         system=system,
    377     )
    378     if earthaccess.__auth__.authenticated:
    379         earthaccess.__store__ = Store(earthaccess.__auth__)

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/earthaccess/auth.py:144, in Auth.login(self, strategy, persist, system)
    141     return self
    143 if strategy == "interactive":
--> 144     self._interactive(persist)
    145 elif strategy == "netrc":
    146     self._netrc()

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/earthaccess/auth.py:241, in Auth._interactive(self, persist_credentials)
    237 def _interactive(
    238     self,
    239     persist_credentials: bool = False,
    240 ) -> bool:
--> 241     username = input("Enter your Earthdata Login username: ")
    242     password = getpass.getpass(prompt="Enter your Earthdata password: ")
    243     authenticated = self._get_credentials(username, password, None)

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/ipykernel/kernelbase.py:1274, in Kernel.raw_input(self, prompt)
   1272 if not self._allow_stdin:
   1273     msg = "raw_input was called, but this frontend does not support input requests."
-> 1274     raise StdinNotImplementedError(msg)
   1275 return self._input_request(
   1276     str(prompt),
   1277     self._parent_ident["shell"],
   1278     self.get_parent("shell"),
   1279     password=False,
   1280 )

StdinNotImplementedError: raw_input was called, but this frontend does not support input requests.

Next, you can search for datasets using concept_id, keywords, temporal range, and spatial bounds.

In [3]:

datasets = earthaccess.search_datasets(concept_id="C1996881146-POCLOUD")
ds = datasets[0]

concept_id = ds["meta"]["concept-id"]
print("Concept-Id: ", concept_id)
print("Abstract:", ds["umm"]["Abstract"])

datasets = earthaccess.search_datasets(concept_id="C1996881146-POCLOUD") ds = datasets[0] concept_id = ds["meta"]["concept-id"] print("Concept-Id: ", concept_id) print("Abstract:", ds["umm"]["Abstract"])

Concept-Id:  C1996881146-POCLOUD
Abstract: A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced as a retrospective dataset (four day latency) and near-real-time dataset (one day latency) at the JPL Physical Oceanography DAAC using wavelets as basis functions in an optimal interpolation approach on a global 0.01 degree grid. The version 4 Multiscale Ultrahigh Resolution (MUR) L4 analysis is based upon nighttime GHRSST L2P skin and subskin SST observations from several instruments including the NASA Advanced Microwave Scanning Radiometer-EOS (AMSR-E), the JAXA Advanced Microwave Scanning Radiometer 2 on GCOM-W1, the Moderate Resolution Imaging Spectroradiometers (MODIS) on the NASA Aqua and Terra platforms, the US Navy microwave WindSat radiometer, the Advanced Very High Resolution Radiometer (AVHRR) on several NOAA satellites, and in situ SST observations from the NOAA iQuam project. The ice concentration data are from the archives at the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) High Latitude Processing Center and are also used for an improved SST parameterization for the high-latitudes.  The dataset also contains additional variables for some granules including the SST anomaly (variable sst_anomaly) derived from a MUR climatology, and the temporal distance in hours to the nearest IR measurement for each pixel (variable dt_1km_data). Variable dt_1km_data first appears in the time series on October 4, 2015,  while sst_anomaly starts July 23, 2019.  This dataset was originally funded by the NASA MEaSUREs program (http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects), and created by a team led by Dr. Toshio M. Chin from JPL. It adheres to the GHRSST Data Processing Specification (GDS) version 2 format specifications. Use the file global metadata "history:" attribute to determine if a granule is near-realtime or retrospective.

Examine the granules¶

With a selected data collection, we'll now use earthaccess.search_data to find individual data granules within a specific temporal window.

In [4]:

time_range = ("2024-10-12", "2024-10-13")

results = earthaccess.search_data(
    count=1,
    concept_id=concept_id,
    temporal=("2024-10-12", "2024-10-13"),
)
print(f"Found {len(results)} granules between {time_range[0]} and {time_range[1]}")

for g in results:
    start = g["umm"]["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
    size = float(g["size"])  # or use g["granule_size_mb"]

    print(f"\n{start} → {size:.2f} MB")

    for link in g.data_links(access="external"):
        print(" ", link)

time_range = ("2024-10-12", "2024-10-13") results = earthaccess.search_data( count=1, concept_id=concept_id, temporal=("2024-10-12", "2024-10-13"), ) print(f"Found {len(results)} granules between {time_range[0]} and {time_range[1]}") for g in results: start = g["umm"]["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"] size = float(g["size"]) # or use g["granule_size_mb"] print(f"\n{start} → {size:.2f} MB") for link in g.data_links(access="external"): print(" ", link)

Found 1 granules between 2024-10-12 and 2024-10-13

2024-10-11T21:00:00.000Z → 707.34 MB
  https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/MUR-JPL-L4-GLOB-v4.1/20241012090000-JPL-L4_GHRSST-SSTfnd-MUR-GLOB-v02.0-fv04.1.nc

From the output above, the returned link ends with .nc, indicating a NetCDF file. We can open it directly with xarray using the authenticated HTTPS session from earthaccess and quickly list the variables (plus a peek at dimensions and coordinates).

In [5]:

fs = earthaccess.get_fsspec_https_session()

ds = xr.open_dataset(
    fs.open(results[0].data_links(access="external")[0]),
    engine="h5netcdf",
    decode_timedelta=True,
)
data_vars = ds.data_vars
data_vars

fs = earthaccess.get_fsspec_https_session() ds = xr.open_dataset( fs.open(results[0].data_links(access="external")[0]), engine="h5netcdf", decode_timedelta=True, ) data_vars = ds.data_vars data_vars

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[5], line 1
----> 1 fs = earthaccess.get_fsspec_https_session()
      3 ds = xr.open_dataset(
      4     fs.open(results[0].data_links(access="external")[0]),
      5     engine="h5netcdf",
      6     decode_timedelta=True,
      7 )
      8 data_vars = ds.data_vars

File ~/work/titiler-cmr/titiler-cmr/.venv/lib/python3.12/site-packages/earthaccess/api.py:553, in get_fsspec_https_session()
    537 def get_fsspec_https_session() -> AbstractFileSystem:
    538     """Returns a fsspec session that can be used to access datafiles across many different DAACs.
    539 
    540     Returns:
   (...)
    551         ```
    552     """
--> 553     session = earthaccess.__store__.get_fsspec_session()
    554     return session

AttributeError: 'NoneType' object has no attribute 'get_fsspec_session'

Now, that we know the concept_id, backend, and variable, we can run a quick compatibility check using check_titiler_cmr_compatibility() helper function.

Step 2: Check Compatibility¶

check_titiler_cmr_compatibility() helper function performs the following steps:

• Validate the CMR collection and granule search
• Resolve collection/granule metadata and fetch TileJSON
• Determine how many time steps fall within the requested temporal range
• Query the /timeseries/statistics endpoint for a small, bounded preview window to check if the dataset can be opened and processed with the selected backend.

The result is a summary of compatibility, tiling parameters, and dataset statistics.

In [6]:

concept_id = "C2723754864-GES_DISC"
datetime_range = "2024-10-12T00:00:01Z/2024-10-12T23:59:59Z"
variable = "precipitation"

ds_xarray = DatasetParams(
    concept_id=concept_id,
    backend="xarray",
    datetime_range=datetime_range,
    variable=variable,
    step="P1D",
    temporal_mode="point",
)

concept_id = "C2723754864-GES_DISC" datetime_range = "2024-10-12T00:00:01Z/2024-10-12T23:59:59Z" variable = "precipitation" ds_xarray = DatasetParams( concept_id=concept_id, backend="xarray", datetime_range=datetime_range, variable=variable, step="P1D", temporal_mode="point", )

In [7]:

compat = await check_titiler_cmr_compatibility(
    endpoint=endpoint,
    dataset=ds_xarray,
    timeout_s=250.0,
)

print(f"Compatibility: {compat['compatibility']}")

compat = await check_titiler_cmr_compatibility( endpoint=endpoint, dataset=ds_xarray, timeout_s=250.0, ) print(f"Compatibility: {compat['compatibility']}")

=== TiTiler-CMR Compatibility Check ===
Client: 2 physical / 4 logical cores | RAM: 15.61 GiB
Dataset: C2723754864-GES_DISC (xarray)

~~~~~~~~~~~~~~~~ ERROR JSON REQUEST ~~~~~~~~~~~~~~~~
URL: https://staging.openveda.cloud/api/titiler-cmr/WebMercatorQuad/tilejson.json?concept_id=C2723754864-GES_DISC&backend=xarray&datetime=2024-10-12T00%3A00%3A01Z%2F2024-10-12T23%3A59%3A59Z&variable=precipitation&step=P1D&temporal_mode=point
Error: 301 Moved Permanently
Body: 
HTTP 301 error during compatibility check
Statistics request failed: HTTP 301: 
Compatibility: issues_detected

Now, we want to check the summary of data is valid:

In [8]:

print(f"Statistics preview:\n{compat['statistics']}")

print(f"Statistics preview:\n{compat['statistics']}")

Statistics preview:
Empty DataFrame
Columns: []
Index: []

rasterio backend¶

Similar to the xarray example above, we can check compatibility for a CMR collection that is better suited for the rasterio backend.

In [9]:

ds_hls_day = DatasetParams(
    concept_id="C2021957295-LPCLOUD",
    backend="rasterio",
    datetime_range="2024-07-01T00:00:00Z/2024-07-10T23:59:59Z",
    bands=["B05", "B04"],
    bands_regex="B[0-9][0-9]",
    step="P1D",
    temporal_mode="point",
)
compat = await check_titiler_cmr_compatibility(
    endpoint=endpoint,
    dataset=ds_hls_day,
    timeout_s=250.0,
)

print(f"Compatibility: {compat['compatibility']}")

ds_hls_day = DatasetParams( concept_id="C2021957295-LPCLOUD", backend="rasterio", datetime_range="2024-07-01T00:00:00Z/2024-07-10T23:59:59Z", bands=["B05", "B04"], bands_regex="B[0-9][0-9]", step="P1D", temporal_mode="point", ) compat = await check_titiler_cmr_compatibility( endpoint=endpoint, dataset=ds_hls_day, timeout_s=250.0, ) print(f"Compatibility: {compat['compatibility']}")

=== TiTiler-CMR Compatibility Check ===
Client: 2 physical / 4 logical cores | RAM: 15.61 GiB
Dataset: C2021957295-LPCLOUD (rasterio)
~~~~~~~~~~~~~~~~ ERROR JSON REQUEST ~~~~~~~~~~~~~~~~
URL: https://staging.openveda.cloud/api/titiler-cmr/WebMercatorQuad/tilejson.json?concept_id=C2021957295-LPCLOUD&backend=rasterio&datetime=2024-07-01T00%3A00%3A00Z%2F2024-07-10T23%3A59%3A59Z&bands=B04&bands_regex=B%5B0-9%5D%5B0-9%5D&step=P1D&temporal_mode=point
Error: 301 Moved Permanently
Body: 
HTTP 301 error during compatibility check
Statistics request failed: HTTP 301: 
Compatibility: issues_detected

☝️ If your area of interest is too large, the API will return an “AOI is too large” error. Use the create_bbox_feature function to define a smaller bounding box before retrying.

In [10]:

gulf_geometry = create_bbox_feature(
    -91.65432884883238, 47.86503396133904, -91.53842043960762, 47.9221313337365
)
compat = await check_titiler_cmr_compatibility(
    endpoint=endpoint,
    dataset=ds_hls_day,
    geometry=gulf_geometry,
    timeout_s=300.0,
)
print(f"Compatibility: {compat['compatibility']}")

gulf_geometry = create_bbox_feature( -91.65432884883238, 47.86503396133904, -91.53842043960762, 47.9221313337365 ) compat = await check_titiler_cmr_compatibility( endpoint=endpoint, dataset=ds_hls_day, geometry=gulf_geometry, timeout_s=300.0, ) print(f"Compatibility: {compat['compatibility']}")

=== TiTiler-CMR Compatibility Check ===
Client: 2 physical / 4 logical cores | RAM: 15.61 GiB
Dataset: C2021957295-LPCLOUD (rasterio)

~~~~~~~~~~~~~~~~ ERROR JSON REQUEST ~~~~~~~~~~~~~~~~
URL: https://staging.openveda.cloud/api/titiler-cmr/WebMercatorQuad/tilejson.json?concept_id=C2021957295-LPCLOUD&backend=rasterio&datetime=2024-07-01T00%3A00%3A00Z%2F2024-07-10T23%3A59%3A59Z&bands=B04&bands_regex=B%5B0-9%5D%5B0-9%5D&step=P1D&temporal_mode=point
Error: 301 Moved Permanently
Body: 
HTTP 301 error during compatibility check
Statistics request failed: HTTP 301: 
Compatibility: issues_detected

Alternatively, you can specify bounds_fraction to create a much smaller bounding box within the original bounds.

In [11]:

compat = await check_titiler_cmr_compatibility(
    endpoint=endpoint,
    dataset=ds_hls_day,
    bounds_fraction=1e-5,
    timeout_s=300.0,
)
print(f"Compatibility: {compat['compatibility']}")

compat = await check_titiler_cmr_compatibility( endpoint=endpoint, dataset=ds_hls_day, bounds_fraction=1e-5, timeout_s=300.0, ) print(f"Compatibility: {compat['compatibility']}")

=== TiTiler-CMR Compatibility Check ===
Client: 2 physical / 4 logical cores | RAM: 15.61 GiB
Dataset: C2021957295-LPCLOUD (rasterio)

~~~~~~~~~~~~~~~~ ERROR JSON REQUEST ~~~~~~~~~~~~~~~~
URL: https://staging.openveda.cloud/api/titiler-cmr/WebMercatorQuad/tilejson.json?concept_id=C2021957295-LPCLOUD&backend=rasterio&datetime=2024-07-01T00%3A00%3A00Z%2F2024-07-10T23%3A59%3A59Z&bands=B04&bands_regex=B%5B0-9%5D%5B0-9%5D&step=P1D&temporal_mode=point
Error: 301 Moved Permanently
Body: 
HTTP 301 error during compatibility check
Statistics request failed: HTTP 301: 
Compatibility: issues_detected

Conclusion¶

This notebook demonstrated how to use earthaccess to explore CMR datasets and validate their compatibility with a TiTiler-CMR deployment using the check_titiler_cmr_compatibility helper function.

📚 Useful Resources¶

• Titiler-CMR GitHub
• Earthaccess GitHub
• CMR Search