rhg-compute-tools 1.2

Tools for using compute.rhg.com and compute.impactlab.org

Tools for using compute.rhg.com and compute.impactlab.org

• Free software: MIT license

• Documentation: https://rhg-compute-tools.readthedocs.io.

Installation

pip:

pip install rhg_compute_tools

Features

Kubernetes tools

• easily spin up a preconfigured cluster with get_cluster(), or flavors with get_micro_cluster(), get_standard_cluster(), get_big_cluster(), or get_giant_cluster().

>>> import rhg_compute_tools.kubernetes as rhgk
>>> cluster, client = rhgk.get_cluster()

Google cloud storage utilities

• Utilities for managing google cloud storage directories in parallel from the command line or via a python API

>>> import rhg_compute_tools.gcs as gcs
>>> gcs.sync_gcs('my_data_dir', 'gs://my-bucket/my_data_dir')

History

v1.1.4

• Add dask_kwargs to the rhg_compute_tools.xarray functions

v1.1.3

• Add retry_with_timeout to rhg_compute_tools.utils.py

v1.1.2

• Drop matplotlib.font_manager._rebuild() call in design.__init__ - no longer supported

v1.1.1

• Refactor datasets_from_delayed to speed up

v1.1

• Add gcs.ls function

v1.0.1

• Fix tag kwarg in get_cluster

v1.0.0

• Make the gsutil API consistent, so that we have cp, sync and rm, each of which accept the same args and kwargs

• Swap bumpversion for setuptools_scm to handle versioning

• Cast coordinates to dict before gathering in rhg_compute_tools.xarray.dataarrays_from_delayed and rhg_compute_tools.xarray.datasets_from_delayed. This avoids a mysterious memory explosion on the local machine. Also add name in the metadata used by those functions so that the name of each dataarray or Variable is preserved.

• Use dask-gateway when available when creating a cluster in rhg_compute_tools.kubernetes. Add some tests using a local gateway cluster. TODO: More tests.

• Add tag kwarg to rhg_compute_tools.kuberentes.get_cluster function (PR #87)

v0.2.2

• ?

v0.2.1

• Add remote scheduler deployment (part of dask_kubernetes 0.10)

• Remove extraneous GCSFUSE_TOKENS env var no longer used in new worker images

• Set library thread limits based on how many cpus are available for a single dask thread

• Change formatting of the extra env_items passed to get_cluster to be a list rather than a list of dict-like name/value pairs

v0.2.0

• Add CLI tools . See rctools gcs repdirstruc --help to start

• Add new function rhg_compute_tools.gcs.replicate_directory_structure_on_gcs to copy directory trees into GCS. Users can authenticate with cred_file or with default google credentials

• Fixes to docstrings and metadata

• Add new function rhg_compute_tools.gcs.rm to remove files/directories on GCS using the google.cloud.storage API

• Store one additional environment variable when passing cred_path to rhg_compute_tools.kubernetes.get_cluster so that the google.cloud.storage API will be authenticated in addition to gsutil

v0.1.8

• Deployment fixes

v0.1.7

• Design tools: use RHG & CIL colors & styles

• Plotting helpers: generate cmaps with consistent colors & norms, and apply a colorbar to geopandas plots with nonlinear norms

• Autoscaling fix for kubecluster: switch to dask_kubernetes.KubeCluster to allow use of recent bug fixes

v0.1.6

• Add rhg_compute_tools.gcs.cp_gcs and rhg_compute_tools.gcs.sync_gcs utilities

v0.1.5

• need to figure out how to use this rever thing

v0.1.4

• Bug fix again in rhg_compute_tools.kubernetes.get_worker

v0.1.3

• Bug fix in rhg_compute_tools.kubernetes.get_worker

v0.1.2

• Add xarray from delayed methods in rhg_compute_tools.xarray

• rhg_compute_tools.gcs.cp_to_gcs now calls gsutil in a subprocess instead of google.storage operations. This dramatically improves performance when transferring large numbers of small files

• Additional cluster creation helpers

v0.1.1

• New google compute helpers (see rhg_compute_tools.gcs.cp_to_gcs, rhg_compute_tools.gcs.get_bucket)

• New cluster creation helper (see rhg_compute_tools.kubernetes.get_worker)

• Dask client.map helpers (see rhg_compute_tools.utils submodule)

v0.1.0

• First release on PyPI.