0.5.1

Changes in 0.5.1

• normalize_dataset now ensures that latitudes are decreasing.

0.5.0

Changes in 0.5.0

New in 0.5.0

• xcube gen2 CONFIG will generate a cube from a data input store and a user given cube configuration.
  It will write the resulting cube in a user defined output store.

  • Input Stores: CCIODP, CDS, SentinelHub
  • Output stores: memory, directory, S3

• xcube serve CUBE will now use the last path component of CUBE as dataset title.

• xcube serve can now be run with AWS credentials (#296).

  • In the form xcube serve --config CONFIG, a Datasets entry in CONFIG
    may now contain the two new keys AccessKeyId: ... and SecretAccessKey: ...
    given that FileSystem: obs.
  • In the form xcube serve --aws-prof PROFILE CUBE
    the cube stored in bucket with URL CUBE will be accessed using the
    credentials found in section [PROFILE] of your ~/.aws/credentials file.
  • In the form xcube serve --aws-env CUBE
    the cube stored in bucket with URL CUBE will be accessed using the
    credentials found in environment variables AWS_ACCESS_KEY_ID and
    AWS_SECRET_ACCESS_KEY.

Enhancements in 0.5.0

• Added possibility to specify packing of variables within the configuration of
  xcube gen (#269). The user now may specify a different packing variables,
  which might be useful for reducing the storage size of the datacubes.
  Currently it is only implemented for zarr format.
  This may be done by passing the parameters for packing as the following:

  output_writer_params: 
  
    packing: 
      analysed_sst: 
        scale_factor: 0.07324442274239326
        add_offset: -300.0
        dtype: 'uint16'
        _FillValue: 0.65535

• Example configurations for xcube gen2 were added.

Fixes

• From 0.4.1: Fixed time-series performance drop (#299).

• Fixed xcube gen CLI tool to correctly insert time slices into an
  existing cube stored as Zarr (#317).

• When creating an ImageGeom from a dataset, correct the height if it would
  otherwise give a maximum latitude >90°.

• Disable the display of warnings in the CLI by default, only showing them if
  a --warnings flag is given.

• xcube has been extended by a new Data Store Framework (#307).
  It is provided by the xcube.core.store package.
  It's usage is currently documented only in the form of Jupyter Notebook examples,
  see examples/store/*.ipynb.

• During the development of the new Data Store Framework, some
  utility packages have been added:

  • xcube.util.jsonschema - classes that represent JSON Schemas for types null, boolean,
    number, string, object, and array. Schema instances are used for JSON validation,
    and object marshalling.
  • xcube.util.assertions - numerous assert_* functions that are used for function
    parameter validation. All functions raise ValueError in case an assertion is not met.
  • xcube.util.ipython - functions that can be called for better integration of objects with
    Jupyter Notebooks.

• Fixed a regression when running "xcube serve" with cube path as parameter (#314)

• From 0.4.3: Extended xcube serve by reverse URL prefix option.

• From 0.4.1: Fixed time-series performance drop (#299).

0.4.2

Changes in 0.4.2

• Fixed a problem during release process. No code changes.

Changes in 0.4.1

• Fixed time-series performance drop (#299).

0.4.1

Changes in 0.4.1

• Fixed time-series performance drop (#299).

0.4.0

Changes in 0.4.0

New

• Added new /timeseries/{dataset}/{variable} POST operation to xcube web API.
  It extracts time-series for a given GeoJSON object provided as body.
  It replaces all of the /ts/{dataset}/{variable}/{geom-type} operations.
  The latter are still maintained for compatibility with the "VITO viewer".

• The xcube web API provided through xcube serve can now serve RGBA tiles using the
  dataset/{dataset}/rgb/tiles/{z}/{y}/{x} operation. The red, green, blue
  channels are computed from three configurable variables and normalisation ranges,
  the alpha channel provides transparency for missing values. To specify a default
  RGB schema for a dataset, a colour mapping for the "pseudo-variable" named rbg
  is provided in the configuration of xcube serve:

  Datasets:
    - Identifyer: my_dataset
      Style: my_style
      ...
    ...
  Styles:
    - Identifier: my_style
      ColorMappings:
        rgb:
          Red:
            Variable: rtoa_8
            ValueRange: [0., 0.25]
          Green:
            Variable: rtoa_6
            ValueRange: [0., 0.25]
          Blue:
            Variable: rtoa_4
            ValueRange: [0., 0.25]
        ...

  Note that this concept works nicely in conjunction with the new Augmentation feature (#272) used
  to compute new variables that could be input to the RGB generation.

• Introduced new (ortho-)rectification algorithm allowing reprojection of
  satellite images that come with (terrain-corrected) geo-locations for every pixel.

  • new CLI tool xcube rectify
  • new API function xcube.core.rectify.rectify_dataset()

• Utilizing the new rectification in xcube gen tool. It is now the default
  reprojection method in xcube.core.gen.iproc.XYInputProcessor and
  xcube.core.gen.iproc.DefaultInputProcessor, if ground control points are not
  specified, i.e. the input processor is configured with xy_gcp_step=None. (#206)

• Tile sizes for rectification in xcube gen are now derived from output_writer_params if given in configuration and
  if it contains a chunksizes parameter for 'lat' or 'lon'. This will force the generation of a chunked xcube dataset
  and will utilize Dask arrays for out-of-core computations. This is very useful for large data cubes whose time slices
  would otherwise not fit into memory.

• Introduced new function xcube.core.select.select_spatial_subset().

• Renamed function xcube.core.select.select_vars() into xcube.core.select.select_variables_subset().

• Now supporting xarray and numpy functions in expressions used by the
  xcube.core.evaluate.evaluate_dataset() function and in the configuration of the
  xcube gen tool. You can now use xr and np contexts in expressions, e.g.
  xr.where(CHL >= 0.0, CHL). (#257)

• The performance of the xcube gen tool for the case that expressions or
  expression parts are reused across multiple variables can now be improved.
  Such as expressions can now be assigned to intermediate variables and loaded
  into memory, so they are not recomputed again.
  For example, let the expression quality_flags.cloudy and CHL > 25.0 occur often
  in the configuration, then this is how recomputation can be avoided:

    processed_variables:
      no_cloud_risk:
        expression: not (quality_flags.cloudy and CHL_raw > 25.0)
        load: True
      CHL:
        expression: CHL_raw
        valid_pixel_expression: no_cloud_risk
      ...        
  

• Added ability to write xcube datasets in Zarr format into object storage bucket using the xcube python api
  xcube.core.dsio.write_cube(). (#224) The user needs to pass provide user credentials via

  client_kwargs = {'provider_access_key_id': 'user_id', 'provider_secret_access_key': 'user_secret'}
  

  and
  write to existing bucket by executing

  write_cube(ds1, 'https://s3.amazonaws.com/upload_bucket/cube-1-250-250.zarr', 'zarr',
                       client_kwargs=client_kwargs)
  

• Added new CLI tool xcube tile which is used to generate a tiled RGB image
  pyramid from any xcube dataset. The format and file organisation of the generated
  tile sets conforms to the TMS 1.0 Specification
  (#209).

• The configuration of xcube serve has been enhanced to support
  augmentation of data cubes by new variables computed on-the-fly (#272).
  You can now add a section Augmentation into a dataset descriptor, e.g.:

    Datasets:
      - Identifier: abc
        ...
        Augmentation:
          Path: compute_new_vars.py
          Function: compute_variables
          InputParameters:
            ...
      - ...

  where compute_variables is a function that receives the parent xcube dataset
  and is expected to return a new dataset with new variables.

• The xcube serve tool now provides basic access control via OAuth2 bearer tokens (#263).
  To configure a service instance with access control, add the following to the
  xcube serve configuration file:

    Authentication:
      Domain: "<your oauth2 domain>"
      Audience: "<your audience or API identifier>"
  

  Individual datasets can now be protected using the new AccessControl entry
  by configuring the RequiredScopes entry whose value is a list
  of required scopes, e.g. "read:datasets":

    Datasets:
      ...
      - Identifier: <some dataset id>
        ...
        AccessControl:
          RequiredScopes:
            - "read:datasets"
  

  If you want a dataset to disappear for authorized requests, set the
  IsSubstitute flag:

    Datasets:
      ...
      - Identifier: <some dataset id>
        ...
        AccessControl:
          IsSubstitute: true
  

Enhancements

• The xcube serve tool now also allows for per-dataset configuration
  of chunk caches for datasets read from remote object storage locations.
  Chunk caching avoids recurring fetching of remote data chunks for same
  region of interest.
  It can be configured as default for all remote datasets at top-level of
  the configuration file:

  DatasetChunkCacheSize: 100M
  

  or in individual dataset definitions:

  Datasets: 
     - Identifier: ...
       ChunkCacheSize: 2G
       ...
  

• Retrieval of time series in Python API function xcube.core.timeseries.get_time_series()
  has been optimized and is now much faster for point geometries.
  This enhances time-series performance of xcube serve.

  • The log-output of xcube serve now contains some more details time-series request
    so performance bottlenecks can be identified more easily from xcube-serve.log,
    if the server is started together with the flag --traceperf.

• CLI command xcube resample has been enhanced by a new value for the
  frequency option --frequency all
  With this value it will be possible to create mean, max , std, ... of the whole dataset,
  in other words, create an overview of a cube.
  By Alberto S. Rabaneda.

• The xcube serve tool now also serves dataset attribution information which will be
  displayed in the xcube-viewer's map. To add attribution information, use the DatasetAttribution
  in to your xcube serve configuration. It can be used on top-level (for all dataset),
  or on individual datasets. Its value may be a single text entry or a list of texts:
  For example:

  DatasetAttribution: 
    - "© by Brockmann Consult GmbH 2020, contains modified Copernicus Data 2019, processed by ESA."
    - "Funded by EU H2020 DCS4COP project."

• The xcube gen tool now always produces consolidated xcube datasets when the output format is zarr.
  Furthermore when appending to an existing zarr xcube dataset, the output now will be consolidated as well.
  In addition, xcube gen can now append input time slices to existing optimized (consolidated) zarr xcube datasets.

• The unchunk_coords keyword argument of Python API function
  xcube.core.optimize.optimize_dataset() can now be a name, or list of names
  of the coordinate variable(s) to be consolidated. If boolean True is used
  all variables will be consolidated.

• The xcube serve API operations datasets/ and datasets/{ds_id} now also
  return the metadata attributes of a given dataset and it variables in a property
  named attrs. For variables we added a new metadata property htmlRepr that is
  a string returned by a variable's var.data._repr_html_() method, if any.

• Renamed default log file for xcube serve command to xcube-serve.log.

• xcube gen now immediately flushes logging output to standard out

0.3.0

Changes in 0.3.0

New

• Added new parameter in xcube gen called --no_sort. Using --no_sort,
  the input file list wont be sorted before creating the xcube dataset.
  If --no_sort parameter is passed, order the input list will be kept.
  The parameter --sort is deprecated and the input files will be sorted
  by default.
• xcube now discovers plugin modules by module naming convention
  and by Setuptools entry points. See new chapter
  Plugins
  in xcube's documentation for details. (#211)
• Added new xcube compute CLI command and xcube.core.compute.compute_cube() API
  function that can be used to generate an output cube computed from a Python
  function that is applied to one or more input cubes. Replaces the formerly
  hidden xcube apply command. (#167)
• Added new function xcube.core.geom.rasterize_features()
  to rasterize vector-data features into a dataset. (#222)
• Extended CLI command xcube verify and API function xcube.core.verify.verify_cube to check whether spatial coordinate variables and their associated bounds variables are equidistant. (#231)
• Made xarray version 0.14.1 minimum requirement due to deprecation of xarray's Dataset.drop
  method and replaced it with drop_sel and drop_vars accordingly.

Enhancements

• CLI commands execute much faster now when invoked with the --help and --info options.
• Added serverPID property to response of web API info handler.
• Functions and classes exported by following modules no longer require data cubes to use
  the lon and lat coordinate variables, i.e. using WGS84 CRS coordinates. Instead, the
  coordinates' CRS may be a projected coordinate system and coordinate variables may be called
  x and y (#112):
  • xcube.core.new
  • xcube.core.geom
  • xcube.core.schema
  • xcube.core.verify
• Sometimes the cell bounds coordinate variables of a given coordinate variables are not in a proper,
  CF compliant
  order, e.g. for decreasing latitudes lat the respective bounds coordinate
  lat_bnds is decreasing for lat_bnds[:, 0] and lat_bnds[:, 1], but lat_bnds[i, 0] < lat_bnds[i, 1]
  for all i. xcube is now more tolerant w.r.t. to such wrong ordering of cell boundaries and will
  compute the correct spatial extent. (#233)
• For xcube serve, any undefined color bar name will default to "viridis". (#238)

Fixes

• xcube resample now correctly re-chunks its output. By default, chunking of the
  time dimension is set to one. (#212)

Incompatible changes

The following changes introduce incompatibilities with former xcube 0.2.x
versions.

• The function specified by xcube_plugins entry points now receives an single argument of
  type xcube.api.ExtensionRegistry. Plugins are asked to add their extensions
  to this registry. As an example, have a look at the default xcube_plugins entry points
  in ./setup.py.

• xcube.api.compute_dataset() function has been renamed to
  xcube.api.evaluate_dataset(). This has been done in order avoid confusion
  with new API function xcube.api.compute_cube().

• xcube's package structure has been drastically changed:

  • all of xcube's __init__.py files are now empty and no longer
    have side effects such as sub-module aggregations.
    Therefore, components need to be imported from individual modules.
  • renamed xcube.api into xcube.core
  • moved several modules from xcube.util into xcube.core
  • the new xcube.constants module contains package level constants
  • the new xcube.plugin module now registers all standard extensions
  • moved contents of module xcube.api.readwrite into xcube.core.dsio.
  • removed functions read_cube and read_dataset as open_cube and open_dataset are sufficient
  • all internal module imports are now absolute, rather than relative

0.2.1

Changes in 0.2.1

Enhancements

• Added new CLI tool xcube edit and API function xcube.api.edit_metadata
  which allows editing the metadata of an existing xcube dataset. (#170)
• xcube serve now recognises xcube datasets with
  metadata consolidated by the xcube opmimize command. (#141)

Fixes

• xcube gen now parses time stamps correcly from input data. (#207)
• Dataset multi-resolution pyramids (*.levels directories) can be stored in cloud object storage and are now usable with xcube serve (#179)
• xcube optimize now consolidates metadata only after consolidating
  coordinate variables. (#194)
• Removed broken links from ./README.md (#197)
• Removed obsolete entry points from ./setup.py.

0.2.0

Changes in 0.2.0

New

• Added first version of the xcube documentation generated from ./docs folder.

Enhancements

• Reorganisation of the Documentation and Examples Section (partly addressing #106)

• Loosened python conda environment to satisfy conda-forge requirements

• Making CLI parameters consistent and removing or changing parameter abbreviations in case they were used twice for different params. (partly addressing #91). For every CLI command which is generating an output a path must be provided by the option -o, --output. If not provided by the user, a default output_path is generated. The following CLI parameter have changed and their abbreviation is not enabled anymore :

  • xcube gen -v is now only xcube gen --vars or xcube gen --variables
  • xcube gen -p is now xcube gen -P
  • xcube gen -i is now xcube gen -I
  • xcube gen -r is now xcube gen -R
  • xcube gen -s is now xcube gen -S
  • xcube chunk -c is now xcube chunk -C
  • xcube level -l is now xcube level -L
  • xcube dump -v is now xcube dump --variable or xcube dump --var
  • xcube dump -e is now xcube dump -E
  • xcube vars2dim -v is now xcube vars2dim --variable or xcube vars2dim --var
  • xcube vars2dim --var_name is now xcube vars2dim --variable or xcube vars2dim --var
  • xcube vars2dim -d is now xcube vars2dim -D
  • xcube grid res -d is now xcube grid res -D
  • xcube grid res -c is now xcube grid res --cov or xcube grid res --coverage
  • xcube grid res -n is now xcube grid res -N or xcube grid res --num_results
  • xcube serve -p is now xcube serve -P
  • xcube serve -a is now xcube serve -A

• Added option inclStDev and inclCount query parameters to ts/{dataset}/{variable}/geometry and derivates.
  If used with inclStDev=1, Xcube Viewer will show error bars for each time series point.

• xcube.api.new_cube function now accepts callables as values for variables.
  This allows to compute variable values depending on the (t, y, x) position
  in the cube. Useful for testing.

• xcube.api now exports the MaskSet class which is useful for decoding flag values encoding following the
  CF conventions.

• Added new CLI tool xcube optimize and API function xcube.api.optimize_dataset
  optimizes data cubes for cloud object storage deployment. (#141)

• Added two new spatial dataset operations to Python API xcube.api (#148):

  • mask_dataset_by_geometry(dataset, geometry) clip and mask a dataset by geometry
  • clip_dataset_by_geometry(dataset, geometry) just clip a dataset by geometry

• Changed the dev version tag from 0.2.0.dev3 to 0.2.0.dev

• The behavior of web API /datasets?details=1 has changed.
  The call no longer includes associated vector data as GeoJSON. Instead new API
  has beed added to fetch new vector data on demand:
  /datasets/{dataset}/places and /datasets/{dataset}/places/{place} (#130)

• xcube serve accepts custom SNAP colormaps. The path to a SAP .cpd file can be passed via the server
  configuration file with the paramter [ColorFile] instead of [ColorBar]. (#84)

• xcube serve can now be configured to serve cubes that are associated
  with another cube with same data but different chunking (#115).
  E.g. using chunks such as time=512,lat=1,lon=1 can drastically improve
  time-series extractions.
  Have a look at the demo config in xube/webapi/res/demo/config.yml.

• xcube serve does now offer a AWS S3 compatible data access API (#97):

  • List bucket objects: /s3bucket, see AWS
    docs GET
  • Get bucket object: /s3bucket/{ds_id}/{path},
    see AWS docs HEAD
    and GET

• xcube serve now verifies that a configured cube is valid once it is opened. (#107)

• Added new CLI command xcube verify performing xcube dataset verification. (#19)

• Reworked xcube extract to be finally useful and effective for point data extraction. (#102)

• xcube servercan now filter datasets by point coordinate, e.g. /datasets?point=12.5,52.8. (#50)

• xcube servercan now limit time series to a maximum number of
  valid (not NaN) values. To activate, pass optional query parameter maxValids to the various /ts
  functions. The special value -1 will restrict the result to contain only valid values. (#113)

• Reworked xcube gen to be more user-friendly and more consistent with other tools.
  The changes are

  • Removed --dir and --name options and replaced it by single --output option,
    whose default value is out.zarr. (#45)
  • The --format option no longer has a default value. If not given,
    format is guessed from --output option.
  • Renamed following parameters in the configuration file:
    • input_files into input_paths, also because paths may point into object storage
      locations (buckets);
    • output_file into output_path, to be consistent with input_paths.

• Added new CLI command xcube prune. The tool deletes all block files associated with empty (NaN-
  only) chunks in given INPUT cube, which must have ZARR format. This can drastically reduce files
  in sparse cubes and improve cube reading performance. (#92)

• xcube serve has a new prefix option which is a path appended to the server's host.
  The prefix option replaces the name option which is now deprecated but kept
  for backward compatibility. (#79)

• Added new CLI command xcube resample that is used to generate temporarily up- or downsampled
  data cubes from other data cubes.

• xcube serve can now be run with xcube dataset paths and styling information given via the CLI rather
  than a configuration file. For example xcube serve --styles conc_chl=(0,20,"viridis") /path/to/my/chl-cube.zarr.
  This allows for quick inspection of newly generated cubes via xcube gen.
  Also added option --show that starts the Xcube viewer on desktop environments in a browser.

• Added new xcube apply command that can be used to generate an output cube computed from a Python function
  that is applied to one or more input cubes.
  The command is still in development and therefore hidden.

• Added new xcube timeit command that can be used to measure the time required for
  parameterized command invocations.
  The command is still in development and therefore hidden.

• Added global xcube --scheduler SCHEDULER option for Dask distributed computing (#58)

• Added global xcube --traceback option, removed local xcube gen --traceback option

• Completed version 1 of an xcube developer guide.

• Added xcube serve command (#43)

• xcube serve: Time-series web API now also returns "uncertainty" (#48)

• Added xcube level command to allow for creating spatial pyramid levels (#38)

• xcube gen accepts multiple configuration files that will be merged in order (#21)

• Added xcube gen option --sort when input data list should be sorted (#33)

• Added xcube vars2dim command to make variables a cube dimension (#31)

• Added xcube serve option --traceperf that allows switching on performance diagnostics.

• Included possibility to read the input file paths from a text file. (#47)

• Restructured and clarified code base (#27)

• Moved to Python 3.7 (#25)

• Excluding all input processors except for the default one. They are now plugins and have own repositories within the
  xcube's organisation. (#49)

Fixes

• xcube gen CLI now updates metadata correctly. (#181)
• It was no longer possible to use the xcube gen CLI with --proc option. (#120)
• totalCount attribute of time series returned by Web API ts/{dataset}/{variable}/{geom-type} now
  contains the correct number of possible observations. Was always 1 before.
• Renamed Web API function ts/{dataset}/{variable}/places into
  ts/{dataset}/{variable}/features.
• xcube gen is now taking care that when new time slices are added to an existing
  cube, this is done by maintaining the chronological order. New time slices are
  either appended, inserted, or replaced. (#64) (#139)
• Fixed xcube serve issue with WMTS KVP method GetTile with query parameter time
  whose value can now also have the two forms <start-date>/<end-date> and just <date>. (#132)
• Fixed xcube extract regression that stopped working after Pandas update (#95)
• Fixed problem where CTRL+C didn't function anymore with xcube serve. (#87)
• Fixed error indexes along dimension 'y' are not equal occurred when using
  xcube gen with processed variables that used flag values (#86)
• Fixed xcube serve WMTS KVP API to allow for case-insensitive query parameters. (#77)
• Fixed error in plugins when importing xcube.api.gen (#62)
• Fixed import of plugins only when executing xcube.cli (#66)

0.2.0.dev1

Changes in 0.2.0.dev1

Enhancements

• Added new CLI tool xcube optimize and API function xcube.api.optimize_dataset
  optimizes data cubes for cloud object storage deployment. (#141)
• Added two new spatial dataset operations to Python API xcube.api (#148):
  • mask_dataset_by_geometry(dataset, geometry) clip and mask a dataset by geometry
  • clip_dataset_by_geometry(dataset, geometry) just clip a dataset by geometry
• Changed the dev version tag from 0.2.0.dev3 to 0.2.0.dev
• The behavior of web API /datasets?details=1 has changed.
  The call no longer includes associated vector data as GeoJSON. Instead new API
  has beed added to fetch new vector data on demand:
  /datasets/{dataset}/places and /datasets/{dataset}/places/{place} (#130)
• xcube gen is now taking care that when new time slices are added to an existing
  cube, this is done by maintaining the chronological order. New time slices are
  either appended or inserted. (#64)
• xcube serve accepts custom SNAP colormaps. The path to a SAP .cpd file can be passed via the server
  configuration file with the paramter [ColorFile] instead of [ColorBar]. (#84)
• xcube serve can now be configured to serve cubes that are associated
  with another cube with same data but different chunking (#115).
  E.g. using chunks such as time=512,lat=1,lon=1 can drastically improve
  time-series extractions.
  Have a look at the demo config in xube/webapi/res/demo/config.yml.
• xcube serve does now offer a AWS S3 compatible data access API (#97):
  • List bucket objects: /s3bucket, see AWS
    docs GET
  • Get bucket object: /s3bucket/{ds_id}/{path},
    see AWS docs HEAD
    and GET
• xcube serve now verifies that a configured cube is valid once it is opened. (#107)
• Added new CLI command xcube verify performing data cube verification. (#19)
• Reworked xcube extract to be finally useful and effective for point data extraction. (#102)
• xcube servercan now filter datasets by point coordinate, e.g. /datasets?point=12.5,52.8. (#50)
• xcube servercan now limit time series to a maximum number of
  valid (not NaN) values. To activate, pass optional query parameter maxValids to the various /ts
  functions. The special value -1 will restrict the result to contain only valid values. (#113)
• Reworked xcube gen to be more user-friendly and more consistent with other tools.
  The changes are
  • Removed --dir and --name options and replaced it by single --output option,
    whose default value is out.zarr. (#45)
  • The --format option no longer has a default value. If not given,
    format is guessed from --output option.
  • Renamed following parameters in the configuration file:
    • input_files into input_paths, also because paths may point into object storage
      locations (buckets);
    • output_file into output_path, to be consistent with input_paths.
• Added new CLI command xcube prune. The tool deletes all block files associated with empty (NaN-
  only) chunks in given INPUT cube, which must have ZARR format. This can drastically reduce files
  in sparse cubes and improve cube reading performance. (#92)
• xcube serve has a new prefix option which is a path appended to the server's host.
  The prefix option replaces the name option which is now deprecated but kept
  for backward compatibility. (#79)
• Added new CLI command xcube resample that is used to generate temporarily up- or downsampled
  data cubes from other data cubes.
• xcube serve can now be run with data cube paths and styling information given via the CLI rather
  than a configuration file. For example xcube serve --styles conc_chl=(0,20,"viridis") /path/to/my/chl-cube.zarr.
  This allows for quick inspection of newly generated cubes via xcube gen.
  Also added option --show that starts the Xcube viewer on desktop environments in a browser.
• Added new xcube apply command that can be used to generate an output cube computed from a Python function
  that is applied to one or more input cubes.
  The command is still in development and therefore hidden.
• Added new xcube timeit command that can be used to measure the time required for
  parameterized command invocations.
  The command is still in development and therefore hidden.
• Added global xcube --scheduler <scheduler> option for Dask distributed computing (#58)
• Added global xcube --traceback option, removed local xcube gen --traceback option
• Completed version 1 of an xcube developer guide.
• Added xcube serve command (#43)
• xcube serve: Time-series web API now also returns "uncertainty" (#48)
• Added xcube level command to allow for creating spatial pyramid levels (#38)
• xcube gen accepts multiple configuration files that will be merged in order (#21)
• Added xcube gen option --sort when input data list should be sorted (#33)
• Added xcube vars2dim command to make variables a cube dimension (#31)
• Added xcube serve option --traceperf that allows switching on performance diagnostics.
• Included possibility to read the input file paths from a text file. (#47)
• Restructured and clarified code base (#27)
• Moved to Python 3.7 (#25)
• Excluding all input processors except for the default one. They are now plugins and have own repositories within the
  xcube's organisation. (#49)

Fixes

• Fixed xcube serve issue with WMTS KVP method GetTile with query parameter time
  whose value can now also have the two forms <start-date>/<end-date> and just <date>. (#132)
• Fixed xcube extract regression that stopped working after Pandas update (#95)
• Fixed problem where CTRL+C didn't function anymore with xcube serve. (#87)
• Fixed error indexes along dimension 'y' are not equal occurred when using
  xcube gen with processed variables that used flag values (#86)
• Fixed xcube serve WMTS KVP API to allow for case-insensitive query parameters. (#77)
• Fixed error in plugins when importing xcube.api.gen (#62)
• Fixed import of plugins only when executing xcube.cli (#66)