preligens-lab / buzzard Goto Github PK

Advanced raster and geometry manipulations

License: Apache License 2.0

Dockerfile 0.72% Python 99.28%

python gis geospatial raster image vector geometry gdal ogr osr

buzzard's Introduction

`buzzard`

In a nutshell, the buzzard library provides powerful abstractions to manipulate together images and geometries that come from different kind of sources (GeoTIFF, PNG, GeoJSON, Shapefile, numpy array, buzzard pipelines, ...).

`buzzard` is

A python library.
Primarily designed to hide all cumbersome operations when doing data-science with GIS files.
A multipurpose computer vision library, it can be used in all kind of situations where images or geometries are involved.
A pythonic wrapper for osgeo's gdal/ogr/osr.
A solution to work with arbitrary large images by simplifying and automating the manipulation of image slices.

`buzzard` contains

A Dataset class that oversees a set of opened raster and vector files.
An immutable toolbox class, the Footprint, designed to locate a rectangle in both an image space and a geometry space.

How to open and read files

This example demonstrates how to visualize a large raster polygon per polygon.

import buzzard as buzz
import numpy as np
import matplotlib.pyplot as plt

# Open the files. Only metadata are kept in memory
r = buzz.open_raster('path/to/rgba-image.tif')
v = buzz.open_vector('path/to/polygons.geojson', driver='GeoJSON')


# Load the polygons from disk one by one as shapely objects
for poly in v.iter_data():

    # Compute the Footprint bounding `poly`
    fp = r.fp.intersection(poly)
    print(fp)

    # Load the image from disk at `fp` to a numpy array
    rgb = r.get_data(fp=fp, channels=(0, 1, 2))
    alpha = r.get_data(fp=fp, channels=3)

    # Create a boolean mask as a numpy array from the shapely polygon
    mask = np.invert(fp.burn_polygons(poly))

    # Darken pixels outside of polygon and set transparent pixels to orange
    rgb[mask] = (rgb[mask] * 0.5).astype(np.uint8)
    rgb[alpha == 0] = [236, 120, 57]

    # Show the result with matplotlib
    plt.imshow(rgb)
    plt.show()

Images from the ISPRS's Potsdam dataset.

Footprint(tl=(3183.600000, -914.550000), br=(3689.700000, -1170.450000), size=(506.100000, 255.900000), rsize=(3374, 1706))

Footprint(tl=(3171.600000, -1321.500000), br=(4553.400000, -2400.000000), size=(1381.800000, 1078.500000), rsize=(9212, 7190))

How to create files and manipulate Footprints

import buzzard as buzz
import numpy as np
import matplotlib.pyplot as plt
import keras

r = buzz.open_raster('path/to/rgba-image.tif')
km = keras.models.load_model('path/to/deep-learning-model.hdf5')

# Chunk the raster's Footprint to Footprints of size
# 1920 x 1080 pixels stored in a 2d numpy array
tiles = r.fp.tile((1920, 1080))

all_roads = []

# Perform an inference for each tile
for i, fp in enumerate(tiles.flat):
    rgb = r.get_data(fp=fp, channels=(0, 1, 2))

    # Perform pixelwise semantic segmentation with a keras model
    predictions_heatmap = km.predict(rgb[np.newaxis, ...])[0]
    predictions_top1 = np.argmax(predictions_heatmap, axis=-1)

    # Save the prediction to a `geotiff`
    path = f'predictions_{i}.tif'
    with buzz.create_raster(path=path, fp=fp, dtype='uint8', channel_count=1).close as out:
        out.set_data(predictions_top1)

    # Extract the road polygons by transforming a numpy boolean mask to shapely polygons
    road_polygons = fp.find_polygons(predictions_top1 == 3)
    all_roads += road_polygons

    # Show the result with matplotlib for one tile
    if i == 2:
        plt.imshow(rgb)
        plt.imshow(predictions_top1)
        plt.show()

# Save all roads found to a single `shapefile`
with buzz.create_vector(path='roads.shp', type='polygon').close as out:
    for poly in all_roads:
        out.insert_data(poly)

Advanced examples

Additional examples can be found here:

`buzzard` allows

Opening and creating raster and vector files. Supports all GDAL drivers (GTiff, PNG, ...) and all OGR drivers (GeoJSON, DXF, Shapefile, ...).
Reading raster files pixels from disk to numpy.ndarray.
- Options: sub-rectangle reading, rotated and scaled sub-rectangle reading (thanks to on-the-fly remapping with OpenCV), automatic parallelization of read and remapping (soon), async (soon), be the source of an image processing pipeline (soon).
- Properties: thread-safe parallel reads.
Writing raster files pixels to disk from numpy.ndarray.
- Options: sub-rectangle writing, rotated and scaled sub-rectangle writing (thanks to on-the-fly remapping with OpenCV), masked writing (slow).
Reading vector files geometries from disk to shapely objects, geojson dict and raw coordinates.
- Options: masking.
- Properties: thread-safe parallel reads.
Writing vector files geometries to disk from shapely objects, geojson dict and raw coordinates.
Powerful manipulations of raster windows
Instantiation of image processing pipelines where each node is a raster, and each edge is a user defined python function transforming numpy.ndarray objects (beta, partially implemented).
- Options: automatic parallelization using user defined thread or process pools, disk caching.
- Properties: lazy evaluation, deterministic, automatic tasks chunking into tiles, fine grain task prioritization, backpressure prevention.
Spatial reference homogenization between opened files like a GIS software does (beta)

Documentation

https://buzzard.readthedocs.io/

Dependencies

The following table lists dependencies along with the minimum version, their status for the project and the related license.

Library	Version	Mandatory	License	Comment
gdal	>=2.3.3	Yes	MIT/X	Hard to install. Will be included in `buzzard` wheels
opencv-python	>=3.1.0	Yes	3-clause BSD	Easy to install with `opencv-python` wheels. Will be optional
shapely	>=1.6.1	Yes	3-clause BSD
affine	>=2.0.0	Yes	3-clause BSD
numpy	>=1.15.0	Yes	numpy
scipy	>=0.19.1	Yes	scipy
pint	>=0.8.1	Yes	3-clause BSD
sortedcontainers	>=1.5.9	Yes	apache
Rtree	>=0.8.3	Yes	MIT
scikit-image	>=0.14.0	Yes	scikit-image
pytest	>=3.2.2	No	MIT	Only for tests

How to install from terminal

Anaconda and pip

# Step 1 - Install Anaconda
# https://www.anaconda.com/download/

# Step 2 - Create env
conda create -n buzz python gdal>=2.3.3 shapely rtree -c 'conda-forge'

# Step 3 - Activate env
conda activate buzz

# Step 4 - Install buzzard
pip install buzzard

Docker

docker build -t buzz --build-arg PYTHON_VERSION=3.7 https://raw.githubusercontent.com/earthcube-lab/buzzard/master/.circleci/images/base-python/Dockerfile
docker run -it --rm buzz bash
pip install buzzard

Package manager and pip

# Step 1 - Install GDAL and rtree ******************************************* **
# Windows
# https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal
# https://www.lfd.uci.edu/~gohlke/pythonlibs/#rtree

# MacOS
brew install gdal
brew tap osgeo/osgeo4mac
brew tap --repair
brew install gdal2
brew install spatialindex
export PATH="/usr/local/opt/gdal2/bin:$PATH"
python3 -m pip install 'gdal==2.3.3'

# Ubuntu
# Run the commands from the following Dockerfile:
# https://github.com/earthcube-lab/buzzard/blob/master/doc/ubuntu_install/Dockerfile

# Step 2 - Install buzzard ************************************************** **
python3 -m pip install buzzard

Supported Python versions

To enjoy the latest buzzard features, update your python!

Full python support

Latest tested version: 3.8 (June 2018)
Oldest tested version: 3.6 (Sept 2015)

Partial python support

For python 2.7: use buzzard version 0.4.4
For python 3.4: use buzzard version 0.6.3
For python 3.5: use buzzard version 0.6.4

Slack

You want some help? You have a question? You want to contribute? Join us on Slack!

How to test

git clone https://github.com/earthcube-lab/buzzard
pip install -r buzzard/requirements-dev.txt
pytest buzzard/buzzard/test

How to build documentation

cd docs
make html
open _build/html/index.html

Contributions and feedback

Welcome to the buzzard project! We appreciate any contribution and feedback, your proposals and pull requests will be considered and responded to. For more information, see the CONTRIBUTING.md file.

Authors

See AUTHORS

License and Notice

See LICENSE and NOTICE.

Other pages

TODO on notion.so

buzzard's People

Contributors

Stargazers

Watchers

Forkers

nicolasnanass mohitsahunitrr trendingtechnology wzp8023391 romain-keramitas-prl

buzzard's Issues

Empty documentation pages with `latest`

Most pages of the latest documentation are empty: https://buzzard.readthedocs.io/en/latest/footprint.html

This works fine with the stable one: https://buzzard.readthedocs.io/en/stable/footprint.html

Flaky test: `buzzard/test/test_cached_raster_recipe.py::test_[pools0-cache_tiles0]`

#!/bin/bash -eo pipefail
. venvs/37/bin/activate
python scripts/pytest_parallel.py -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage.xml --junitxml=test-reports/pytest-report.xml
ls -l test-reports
# codecov first concatenate the coverage*.xml files and upload it
# it does not seem to care about the pytest-report*.xml, is it a problem?
# https://circleci.com/gh/airware/buzzard/1564#queue-placeholder/containers/0
# It used to upload those.
# https://circleci.com/gh/airware/buzzard/1506#artifacts/containers/0
codecov

-- Discovering tests --
$ bash -c "pytest --collect-only -x &>/tmp/pytest-collection-tmp"
  bash -c "pytest --collect-only -x &>/tmp/pytest-collection-tmp" (took 10.3sec)
Found 17520 tests scattered on 20 files
  buzzard/test/test_cached_raster_recipe.py -> (12 calls of 1 test)
  buzzard/test/test_dataset_activations.py -> (1 call of 3 tests)
  buzzard/test/test_dataset_modes.py -> (1 call of 4 tests)
  buzzard/test/test_dataset_registering.py -> (1 call of 2 tests)
  buzzard/test/test_env.py -> (1 call of 1 tests)
  buzzard/test/test_footprint.py -> (1 call of 17 tests)
  buzzard/test/test_footprint_convs.py -> (1 call of 576 tests)
  buzzard/test/test_footprint_findburn_polygons.py -> (1 call of 51 tests)
  buzzard/test/test_footprint_intersection.py -> (1 call of 4 tests)
  buzzard/test/test_footprint_move.py -> (1 call of 504 tests)
  buzzard/test/test_footprint_precision.py -> (1 call of 36 tests)
  buzzard/test/test_footprint_tile.py -> (1 call of 1638 tests)
  buzzard/test/test_footprint_tile_count.py -> (1 call of 5121 tests)
  buzzard/test/test_footprint_tile_occurrence.py -> (1 call of 2177 tests)
  buzzard/test/test_multi_ordered_dict.py -> (1 call of 1 tests)
  buzzard/test/test_rastersource_getsetdata_basic.py -> (1 call of 192 tests)
  buzzard/test/test_rastersource_opencreate.py -> (1 call of 29 tests)
  buzzard/test/test_rastersource_resampling.py -> (1 call of 6960 tests)
  buzzard/test/test_vectorsource_getsetdata_general.py -> (6 calls of 1 test)
  buzzard/test/test_vectorsource_opencreate.py -> (1 call of 186 tests)
-- Running tests, 36 calls to pytest, 36 simulateneous --
$ COVERAGE_FILE=.coverage.e996de86-b2e3-4f8b-8cb3-202ff0fae316 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-e996de86-b2e3-4f8b-8cb3-202ff0fae316.xml --junitxml=test-reports/pytest-report-e996de86-b2e3-4f8b-8cb3-202ff0fae316.xml 'buzzard/test/test_vectorsource_opencreate.py' &>/tmp/e996de86-b2e3-4f8b-8cb3-202ff0fae316"
$ COVERAGE_FILE=.coverage.7fd395b1-60c6-440d-b1a9-37fe22e8ee5d bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-7fd395b1-60c6-440d-b1a9-37fe22e8ee5d.xml --junitxml=test-reports/pytest-report-7fd395b1-60c6-440d-b1a9-37fe22e8ee5d.xml 'buzzard/test/test_vectorsource_getsetdata_general.py::test_value_error[ESRI Shapefile-.shp]' &>/tmp/7fd395b1-60c6-440d-b1a9-37fe22e8ee5d"
$ COVERAGE_FILE=.coverage.2bf08196-ca6c-437c-9dab-9b081da6c4be bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-2bf08196-ca6c-437c-9dab-9b081da6c4be.xml --junitxml=test-reports/pytest-report-2bf08196-ca6c-437c-9dab-9b081da6c4be.xml 'buzzard/test/test_vectorsource_getsetdata_general.py::test_run[Memory--True-True]' &>/tmp/2bf08196-ca6c-437c-9dab-9b081da6c4be"
$ COVERAGE_FILE=.coverage.669d967d-182c-406b-a3e3-9d7353a81350 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-669d967d-182c-406b-a3e3-9d7353a81350.xml --junitxml=test-reports/pytest-report-669d967d-182c-406b-a3e3-9d7353a81350.xml 'buzzard/test/test_vectorsource_getsetdata_general.py::test_run[GeoJson-.json-True-True]' &>/tmp/669d967d-182c-406b-a3e3-9d7353a81350"
$ COVERAGE_FILE=.coverage.5dd205ee-0652-4af7-a28c-86e1ad2487cf bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-5dd205ee-0652-4af7-a28c-86e1ad2487cf.xml --junitxml=test-reports/pytest-report-5dd205ee-0652-4af7-a28c-86e1ad2487cf.xml 'buzzard/test/test_vectorsource_getsetdata_general.py::test_run[ESRI Shapefile-.shp-True-True]' &>/tmp/5dd205ee-0652-4af7-a28c-86e1ad2487cf"
$ COVERAGE_FILE=.coverage.56a7abb0-7e96-4a49-a0d4-fbf1d1d21711 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-56a7abb0-7e96-4a49-a0d4-fbf1d1d21711.xml --junitxml=test-reports/pytest-report-56a7abb0-7e96-4a49-a0d4-fbf1d1d21711.xml 'buzzard/test/test_vectorsource_getsetdata_general.py::test_iter_data_fields_behavior[ESRI Shapefile-.shp]' &>/tmp/56a7abb0-7e96-4a49-a0d4-fbf1d1d21711"
$ COVERAGE_FILE=.coverage.9423a3b0-b47d-42b0-924f-a6dd211d2a42 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-9423a3b0-b47d-42b0-924f-a6dd211d2a42.xml --junitxml=test-reports/pytest-report-9423a3b0-b47d-42b0-924f-a6dd211d2a42.xml 'buzzard/test/test_rastersource_opencreate.py' &>/tmp/9423a3b0-b47d-42b0-924f-a6dd211d2a42"
$ COVERAGE_FILE=.coverage.eb813f53-5f93-4c12-86e9-84cd5f500a6b bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-eb813f53-5f93-4c12-86e9-84cd5f500a6b.xml --junitxml=test-reports/pytest-report-eb813f53-5f93-4c12-86e9-84cd5f500a6b.xml 'buzzard/test/test_multi_ordered_dict.py' &>/tmp/eb813f53-5f93-4c12-86e9-84cd5f500a6b"
$ COVERAGE_FILE=.coverage.9a72611b-0f72-4ebf-a445-eec0dedf0a23 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-9a72611b-0f72-4ebf-a445-eec0dedf0a23.xml --junitxml=test-reports/pytest-report-9a72611b-0f72-4ebf-a445-eec0dedf0a23.xml 'buzzard/test/test_footprint_tile_occurrence.py' &>/tmp/9a72611b-0f72-4ebf-a445-eec0dedf0a23"
$ COVERAGE_FILE=.coverage.e72af6be-f9c9-4eee-adb0-344f319fbaa1 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-e72af6be-f9c9-4eee-adb0-344f319fbaa1.xml --junitxml=test-reports/pytest-report-e72af6be-f9c9-4eee-adb0-344f319fbaa1.xml 'buzzard/test/test_footprint_tile.py' &>/tmp/e72af6be-f9c9-4eee-adb0-344f319fbaa1"
$ COVERAGE_FILE=.coverage.35fd1b49-9896-4d08-899b-744a58ff293a bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-35fd1b49-9896-4d08-899b-744a58ff293a.xml --junitxml=test-reports/pytest-report-35fd1b49-9896-4d08-899b-744a58ff293a.xml 'buzzard/test/test_rastersource_resampling.py' &>/tmp/35fd1b49-9896-4d08-899b-744a58ff293a"
$ COVERAGE_FILE=.coverage.72a30369-6698-4cf0-8d16-9266705a24ea bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-72a30369-6698-4cf0-8d16-9266705a24ea.xml --junitxml=test-reports/pytest-report-72a30369-6698-4cf0-8d16-9266705a24ea.xml 'buzzard/test/test_footprint_intersection.py' &>/tmp/72a30369-6698-4cf0-8d16-9266705a24ea"
$ COVERAGE_FILE=.coverage.b592e168-f550-45da-85df-005672b3598e bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-b592e168-f550-45da-85df-005672b3598e.xml --junitxml=test-reports/pytest-report-b592e168-f550-45da-85df-005672b3598e.xml 'buzzard/test/test_footprint_findburn_polygons.py' &>/tmp/b592e168-f550-45da-85df-005672b3598e"
$ COVERAGE_FILE=.coverage.63b69eed-173f-4a91-aee0-af7730c71962 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-63b69eed-173f-4a91-aee0-af7730c71962.xml --junitxml=test-reports/pytest-report-63b69eed-173f-4a91-aee0-af7730c71962.xml 'buzzard/test/test_footprint_convs.py' &>/tmp/63b69eed-173f-4a91-aee0-af7730c71962"
$ COVERAGE_FILE=.coverage.87a325ae-9ea5-4a90-8934-5e95fd15d177 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-87a325ae-9ea5-4a90-8934-5e95fd15d177.xml --junitxml=test-reports/pytest-report-87a325ae-9ea5-4a90-8934-5e95fd15d177.xml 'buzzard/test/test_footprint_move.py' &>/tmp/87a325ae-9ea5-4a90-8934-5e95fd15d177"
$ COVERAGE_FILE=.coverage.96a9823b-fc40-4106-8284-dac00b8fae9b bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-96a9823b-fc40-4106-8284-dac00b8fae9b.xml --junitxml=test-reports/pytest-report-96a9823b-fc40-4106-8284-dac00b8fae9b.xml 'buzzard/test/test_dataset_registering.py' &>/tmp/96a9823b-fc40-4106-8284-dac00b8fae9b"
$ COVERAGE_FILE=.coverage.8af50906-06ef-4c1c-95de-22c31854f572 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-8af50906-06ef-4c1c-95de-22c31854f572.xml --junitxml=test-reports/pytest-report-8af50906-06ef-4c1c-95de-22c31854f572.xml 'buzzard/test/test_dataset_modes.py' &>/tmp/8af50906-06ef-4c1c-95de-22c31854f572"
$ COVERAGE_FILE=.coverage.f3c43c8a-56fd-4e2a-a7c3-14445e0693cb bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-f3c43c8a-56fd-4e2a-a7c3-14445e0693cb.xml --junitxml=test-reports/pytest-report-f3c43c8a-56fd-4e2a-a7c3-14445e0693cb.xml 'buzzard/test/test_dataset_activations.py' &>/tmp/f3c43c8a-56fd-4e2a-a7c3-14445e0693cb"
$ COVERAGE_FILE=.coverage.07cc5e29-1459-4ef7-8b2a-747cb57da700 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-07cc5e29-1459-4ef7-8b2a-747cb57da700.xml --junitxml=test-reports/pytest-report-07cc5e29-1459-4ef7-8b2a-747cb57da700.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools3-cache_tiles2]' &>/tmp/07cc5e29-1459-4ef7-8b2a-747cb57da700"
$ COVERAGE_FILE=.coverage.35342788-06ad-4b51-a456-4417168a30ff bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-35342788-06ad-4b51-a456-4417168a30ff.xml --junitxml=test-reports/pytest-report-35342788-06ad-4b51-a456-4417168a30ff.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools3-cache_tiles0]' &>/tmp/35342788-06ad-4b51-a456-4417168a30ff"
$ COVERAGE_FILE=.coverage.268dcf02-8d38-4e22-88d2-d6028d8278e5 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-268dcf02-8d38-4e22-88d2-d6028d8278e5.xml --junitxml=test-reports/pytest-report-268dcf02-8d38-4e22-88d2-d6028d8278e5.xml 'buzzard/test/test_vectorsource_getsetdata_general.py::test_run[DXF-.dxf-False-False]' &>/tmp/268dcf02-8d38-4e22-88d2-d6028d8278e5"
$ COVERAGE_FILE=.coverage.a69df320-f5fe-4b7e-ad55-5ad78301b7f5 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-a69df320-f5fe-4b7e-ad55-5ad78301b7f5.xml --junitxml=test-reports/pytest-report-a69df320-f5fe-4b7e-ad55-5ad78301b7f5.xml 'buzzard/test/test_rastersource_getsetdata_basic.py' &>/tmp/a69df320-f5fe-4b7e-ad55-5ad78301b7f5"
$ COVERAGE_FILE=.coverage.6eab878a-d7ff-412f-9411-a30663ae511a bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-6eab878a-d7ff-412f-9411-a30663ae511a.xml --junitxml=test-reports/pytest-report-6eab878a-d7ff-412f-9411-a30663ae511a.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools2-cache_tiles2]' &>/tmp/6eab878a-d7ff-412f-9411-a30663ae511a"
$ COVERAGE_FILE=.coverage.96c59d0b-dd97-4573-a2cb-a540d91b210e bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-96c59d0b-dd97-4573-a2cb-a540d91b210e.xml --junitxml=test-reports/pytest-report-96c59d0b-dd97-4573-a2cb-a540d91b210e.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools2-cache_tiles1]' &>/tmp/96c59d0b-dd97-4573-a2cb-a540d91b210e"
$ COVERAGE_FILE=.coverage.70e1b85b-4880-4e01-a901-530d96440fe6 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-70e1b85b-4880-4e01-a901-530d96440fe6.xml --junitxml=test-reports/pytest-report-70e1b85b-4880-4e01-a901-530d96440fe6.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools2-cache_tiles0]' &>/tmp/70e1b85b-4880-4e01-a901-530d96440fe6"
$ COVERAGE_FILE=.coverage.6fc250c7-8111-4823-9ca3-441f6370f7f6 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-6fc250c7-8111-4823-9ca3-441f6370f7f6.xml --junitxml=test-reports/pytest-report-6fc250c7-8111-4823-9ca3-441f6370f7f6.xml 'buzzard/test/test_footprint_tile_count.py' &>/tmp/6fc250c7-8111-4823-9ca3-441f6370f7f6"
$ COVERAGE_FILE=.coverage.6631d530-1da8-4707-b167-0bd6c9cfd460 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-6631d530-1da8-4707-b167-0bd6c9cfd460.xml --junitxml=test-reports/pytest-report-6631d530-1da8-4707-b167-0bd6c9cfd460.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools3-cache_tiles1]' &>/tmp/6631d530-1da8-4707-b167-0bd6c9cfd460"
$ COVERAGE_FILE=.coverage.c112d267-dfc7-44ca-b4ef-cf2b1f600e05 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-c112d267-dfc7-44ca-b4ef-cf2b1f600e05.xml --junitxml=test-reports/pytest-report-c112d267-dfc7-44ca-b4ef-cf2b1f600e05.xml 'buzzard/test/test_footprint.py' &>/tmp/c112d267-dfc7-44ca-b4ef-cf2b1f600e05"
$ COVERAGE_FILE=.coverage.5c16d734-f536-47f7-bb93-c1f4cfb5536d bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-5c16d734-f536-47f7-bb93-c1f4cfb5536d.xml --junitxml=test-reports/pytest-report-5c16d734-f536-47f7-bb93-c1f4cfb5536d.xml 'buzzard/test/test_footprint_precision.py' &>/tmp/5c16d734-f536-47f7-bb93-c1f4cfb5536d"
$ COVERAGE_FILE=.coverage.ceb18bb4-50a0-4020-9645-e3ac38538b20 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-ceb18bb4-50a0-4020-9645-e3ac38538b20.xml --junitxml=test-reports/pytest-report-ceb18bb4-50a0-4020-9645-e3ac38538b20.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools1-cache_tiles2]' &>/tmp/ceb18bb4-50a0-4020-9645-e3ac38538b20"
$ COVERAGE_FILE=.coverage.2dc7561e-02c5-4a4c-ae4a-19add5cb09f8 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-2dc7561e-02c5-4a4c-ae4a-19add5cb09f8.xml --junitxml=test-reports/pytest-report-2dc7561e-02c5-4a4c-ae4a-19add5cb09f8.xml 'buzzard/test/test_env.py' &>/tmp/2dc7561e-02c5-4a4c-ae4a-19add5cb09f8"
$ COVERAGE_FILE=.coverage.a4a59c9d-fda9-4b9f-be3a-28e72e810a4b bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-a4a59c9d-fda9-4b9f-be3a-28e72e810a4b.xml --junitxml=test-reports/pytest-report-a4a59c9d-fda9-4b9f-be3a-28e72e810a4b.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools1-cache_tiles1]' &>/tmp/a4a59c9d-fda9-4b9f-be3a-28e72e810a4b"
$ COVERAGE_FILE=.coverage.7e6c6c0f-099e-4c89-9ecc-1ab976bf2e2c bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-7e6c6c0f-099e-4c89-9ecc-1ab976bf2e2c.xml --junitxml=test-reports/pytest-report-7e6c6c0f-099e-4c89-9ecc-1ab976bf2e2c.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools1-cache_tiles0]' &>/tmp/7e6c6c0f-099e-4c89-9ecc-1ab976bf2e2c"
$ COVERAGE_FILE=.coverage.87ef8482-7c6b-4156-9575-2b4ba31427a0 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-87ef8482-7c6b-4156-9575-2b4ba31427a0.xml --junitxml=test-reports/pytest-report-87ef8482-7c6b-4156-9575-2b4ba31427a0.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools0-cache_tiles2]' &>/tmp/87ef8482-7c6b-4156-9575-2b4ba31427a0"
$ COVERAGE_FILE=.coverage.b36c96f2-cc9a-4b91-ad20-8dd5d8e100cc bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-b36c96f2-cc9a-4b91-ad20-8dd5d8e100cc.xml --junitxml=test-reports/pytest-report-b36c96f2-cc9a-4b91-ad20-8dd5d8e100cc.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools0-cache_tiles1]' &>/tmp/b36c96f2-cc9a-4b91-ad20-8dd5d8e100cc"
$ COVERAGE_FILE=.coverage.a75c11b5-3410-47e4-bf79-e3f56806ba96 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-a75c11b5-3410-47e4-bf79-e3f56806ba96.xml --junitxml=test-reports/pytest-report-a75c11b5-3410-47e4-bf79-e3f56806ba96.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools0-cache_tiles0]' &>/tmp/a75c11b5-3410-47e4-bf79-e3f56806ba96"
  COVERAGE_FILE=.coverage.56a7abb0-7e96-4a49-a0d4-fbf1d1d21711 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-56a7abb0-7e96-4a49-a0d4-fbf1d1d21711.xml --junitxml=test-reports/pytest-report-56a7abb0-7e96-4a49-a0d4-fbf1d1d21711.xml 'buzzard/test/test_vectorsource_getsetdata_general.py::test_iter_data_fields_behavior[ESRI Shapefile-.shp]' &>/tmp/56a7abb0-7e96-4a49-a0d4-fbf1d1d21711" (took 88.5sec)
  COVERAGE_FILE=.coverage.9423a3b0-b47d-42b0-924f-a6dd211d2a42 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-9423a3b0-b47d-42b0-924f-a6dd211d2a42.xml --junitxml=test-reports/pytest-report-9423a3b0-b47d-42b0-924f-a6dd211d2a42.xml 'buzzard/test/test_rastersource_opencreate.py' &>/tmp/9423a3b0-b47d-42b0-924f-a6dd211d2a42" (took 97.3sec)
  COVERAGE_FILE=.coverage.96a9823b-fc40-4106-8284-dac00b8fae9b bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-96a9823b-fc40-4106-8284-dac00b8fae9b.xml --junitxml=test-reports/pytest-report-96a9823b-fc40-4106-8284-dac00b8fae9b.xml 'buzzard/test/test_dataset_registering.py' &>/tmp/96a9823b-fc40-4106-8284-dac00b8fae9b" (took 99.7sec)
  COVERAGE_FILE=.coverage.2dc7561e-02c5-4a4c-ae4a-19add5cb09f8 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-2dc7561e-02c5-4a4c-ae4a-19add5cb09f8.xml --junitxml=test-reports/pytest-report-2dc7561e-02c5-4a4c-ae4a-19add5cb09f8.xml 'buzzard/test/test_env.py' &>/tmp/2dc7561e-02c5-4a4c-ae4a-19add5cb09f8" (took 99.9sec)
  COVERAGE_FILE=.coverage.7fd395b1-60c6-440d-b1a9-37fe22e8ee5d bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-7fd395b1-60c6-440d-b1a9-37fe22e8ee5d.xml --junitxml=test-reports/pytest-report-7fd395b1-60c6-440d-b1a9-37fe22e8ee5d.xml 'buzzard/test/test_vectorsource_getsetdata_general.py::test_value_error[ESRI Shapefile-.shp]' &>/tmp/7fd395b1-60c6-440d-b1a9-37fe22e8ee5d" (took 100.9sec)
  COVERAGE_FILE=.coverage.c112d267-dfc7-44ca-b4ef-cf2b1f600e05 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-c112d267-dfc7-44ca-b4ef-cf2b1f600e05.xml --junitxml=test-reports/pytest-report-c112d267-dfc7-44ca-b4ef-cf2b1f600e05.xml 'buzzard/test/test_footprint.py' &>/tmp/c112d267-dfc7-44ca-b4ef-cf2b1f600e05" (took 102.8sec)
  COVERAGE_FILE=.coverage.f3c43c8a-56fd-4e2a-a7c3-14445e0693cb bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-f3c43c8a-56fd-4e2a-a7c3-14445e0693cb.xml --junitxml=test-reports/pytest-report-f3c43c8a-56fd-4e2a-a7c3-14445e0693cb.xml 'buzzard/test/test_dataset_activations.py' &>/tmp/f3c43c8a-56fd-4e2a-a7c3-14445e0693cb" (took 108.2sec)
  COVERAGE_FILE=.coverage.b592e168-f550-45da-85df-005672b3598e bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-b592e168-f550-45da-85df-005672b3598e.xml --junitxml=test-reports/pytest-report-b592e168-f550-45da-85df-005672b3598e.xml 'buzzard/test/test_footprint_findburn_polygons.py' &>/tmp/b592e168-f550-45da-85df-005672b3598e" (took 111.3sec)
  COVERAGE_FILE=.coverage.72a30369-6698-4cf0-8d16-9266705a24ea bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-72a30369-6698-4cf0-8d16-9266705a24ea.xml --junitxml=test-reports/pytest-report-72a30369-6698-4cf0-8d16-9266705a24ea.xml 'buzzard/test/test_footprint_intersection.py' &>/tmp/72a30369-6698-4cf0-8d16-9266705a24ea" (took 116.5sec)
  COVERAGE_FILE=.coverage.8af50906-06ef-4c1c-95de-22c31854f572 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-8af50906-06ef-4c1c-95de-22c31854f572.xml --junitxml=test-reports/pytest-report-8af50906-06ef-4c1c-95de-22c31854f572.xml 'buzzard/test/test_dataset_modes.py' &>/tmp/8af50906-06ef-4c1c-95de-22c31854f572" (took 125.6sec)
  COVERAGE_FILE=.coverage.e996de86-b2e3-4f8b-8cb3-202ff0fae316 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-e996de86-b2e3-4f8b-8cb3-202ff0fae316.xml --junitxml=test-reports/pytest-report-e996de86-b2e3-4f8b-8cb3-202ff0fae316.xml 'buzzard/test/test_vectorsource_opencreate.py' &>/tmp/e996de86-b2e3-4f8b-8cb3-202ff0fae316" (took 129.2sec)
  COVERAGE_FILE=.coverage.5c16d734-f536-47f7-bb93-c1f4cfb5536d bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-5c16d734-f536-47f7-bb93-c1f4cfb5536d.xml --junitxml=test-reports/pytest-report-5c16d734-f536-47f7-bb93-c1f4cfb5536d.xml 'buzzard/test/test_footprint_precision.py' &>/tmp/5c16d734-f536-47f7-bb93-c1f4cfb5536d" (took 147.2sec)
  COVERAGE_FILE=.coverage.a75c11b5-3410-47e4-bf79-e3f56806ba96 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-a75c11b5-3410-47e4-bf79-e3f56806ba96.xml --junitxml=test-reports/pytest-report-a75c11b5-3410-47e4-bf79-e3f56806ba96.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools0-cache_tiles0]' &>/tmp/a75c11b5-3410-47e4-bf79-e3f56806ba96" (took 159.1sec)
  COVERAGE_FILE=.coverage.70e1b85b-4880-4e01-a901-530d96440fe6 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-70e1b85b-4880-4e01-a901-530d96440fe6.xml --junitxml=test-reports/pytest-report-70e1b85b-4880-4e01-a901-530d96440fe6.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools2-cache_tiles0]' &>/tmp/70e1b85b-4880-4e01-a901-530d96440fe6" (took 168.4sec)
  COVERAGE_FILE=.coverage.35342788-06ad-4b51-a456-4417168a30ff bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-35342788-06ad-4b51-a456-4417168a30ff.xml --junitxml=test-reports/pytest-report-35342788-06ad-4b51-a456-4417168a30ff.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools3-cache_tiles0]' &>/tmp/35342788-06ad-4b51-a456-4417168a30ff" (took 178.7sec)
  COVERAGE_FILE=.coverage.b36c96f2-cc9a-4b91-ad20-8dd5d8e100cc bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-b36c96f2-cc9a-4b91-ad20-8dd5d8e100cc.xml --junitxml=test-reports/pytest-report-b36c96f2-cc9a-4b91-ad20-8dd5d8e100cc.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools0-cache_tiles1]' &>/tmp/b36c96f2-cc9a-4b91-ad20-8dd5d8e100cc" (took 185.8sec)
  COVERAGE_FILE=.coverage.e72af6be-f9c9-4eee-adb0-344f319fbaa1 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-e72af6be-f9c9-4eee-adb0-344f319fbaa1.xml --junitxml=test-reports/pytest-report-e72af6be-f9c9-4eee-adb0-344f319fbaa1.xml 'buzzard/test/test_footprint_tile.py' &>/tmp/e72af6be-f9c9-4eee-adb0-344f319fbaa1" (took 194.2sec)
  COVERAGE_FILE=.coverage.7e6c6c0f-099e-4c89-9ecc-1ab976bf2e2c bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-7e6c6c0f-099e-4c89-9ecc-1ab976bf2e2c.xml --junitxml=test-reports/pytest-report-7e6c6c0f-099e-4c89-9ecc-1ab976bf2e2c.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools1-cache_tiles0]' &>/tmp/7e6c6c0f-099e-4c89-9ecc-1ab976bf2e2c" (took 203.8sec)
  COVERAGE_FILE=.coverage.6631d530-1da8-4707-b167-0bd6c9cfd460 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-6631d530-1da8-4707-b167-0bd6c9cfd460.xml --junitxml=test-reports/pytest-report-6631d530-1da8-4707-b167-0bd6c9cfd460.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools3-cache_tiles1]' &>/tmp/6631d530-1da8-4707-b167-0bd6c9cfd460" (took 214.2sec)
  COVERAGE_FILE=.coverage.96c59d0b-dd97-4573-a2cb-a540d91b210e bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-96c59d0b-dd97-4573-a2cb-a540d91b210e.xml --junitxml=test-reports/pytest-report-96c59d0b-dd97-4573-a2cb-a540d91b210e.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools2-cache_tiles1]' &>/tmp/96c59d0b-dd97-4573-a2cb-a540d91b210e" (took 227.5sec)
  COVERAGE_FILE=.coverage.87a325ae-9ea5-4a90-8934-5e95fd15d177 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-87a325ae-9ea5-4a90-8934-5e95fd15d177.xml --junitxml=test-reports/pytest-report-87a325ae-9ea5-4a90-8934-5e95fd15d177.xml 'buzzard/test/test_footprint_move.py' &>/tmp/87a325ae-9ea5-4a90-8934-5e95fd15d177" (took 228.3sec)
  COVERAGE_FILE=.coverage.eb813f53-5f93-4c12-86e9-84cd5f500a6b bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-eb813f53-5f93-4c12-86e9-84cd5f500a6b.xml --junitxml=test-reports/pytest-report-eb813f53-5f93-4c12-86e9-84cd5f500a6b.xml 'buzzard/test/test_multi_ordered_dict.py' &>/tmp/eb813f53-5f93-4c12-86e9-84cd5f500a6b" (took 245.0sec)
  COVERAGE_FILE=.coverage.a4a59c9d-fda9-4b9f-be3a-28e72e810a4b bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-a4a59c9d-fda9-4b9f-be3a-28e72e810a4b.xml --junitxml=test-reports/pytest-report-a4a59c9d-fda9-4b9f-be3a-28e72e810a4b.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools1-cache_tiles1]' &>/tmp/a4a59c9d-fda9-4b9f-be3a-28e72e810a4b" (took 245.9sec)
  COVERAGE_FILE=.coverage.a69df320-f5fe-4b7e-ad55-5ad78301b7f5 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-a69df320-f5fe-4b7e-ad55-5ad78301b7f5.xml --junitxml=test-reports/pytest-report-a69df320-f5fe-4b7e-ad55-5ad78301b7f5.xml 'buzzard/test/test_rastersource_getsetdata_basic.py' &>/tmp/a69df320-f5fe-4b7e-ad55-5ad78301b7f5" (took 250.4sec)
  COVERAGE_FILE=.coverage.87ef8482-7c6b-4156-9575-2b4ba31427a0 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-87ef8482-7c6b-4156-9575-2b4ba31427a0.xml --junitxml=test-reports/pytest-report-87ef8482-7c6b-4156-9575-2b4ba31427a0.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools0-cache_tiles2]' &>/tmp/87ef8482-7c6b-4156-9575-2b4ba31427a0" (took 276.0sec)
  COVERAGE_FILE=.coverage.07cc5e29-1459-4ef7-8b2a-747cb57da700 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-07cc5e29-1459-4ef7-8b2a-747cb57da700.xml --junitxml=test-reports/pytest-report-07cc5e29-1459-4ef7-8b2a-747cb57da700.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools3-cache_tiles2]' &>/tmp/07cc5e29-1459-4ef7-8b2a-747cb57da700" (took 333.9sec)
  COVERAGE_FILE=.coverage.6eab878a-d7ff-412f-9411-a30663ae511a bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-6eab878a-d7ff-412f-9411-a30663ae511a.xml --junitxml=test-reports/pytest-report-6eab878a-d7ff-412f-9411-a30663ae511a.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools2-cache_tiles2]' &>/tmp/6eab878a-d7ff-412f-9411-a30663ae511a" (took 388.0sec)
  COVERAGE_FILE=.coverage.9a72611b-0f72-4ebf-a445-eec0dedf0a23 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-9a72611b-0f72-4ebf-a445-eec0dedf0a23.xml --junitxml=test-reports/pytest-report-9a72611b-0f72-4ebf-a445-eec0dedf0a23.xml 'buzzard/test/test_footprint_tile_occurrence.py' &>/tmp/9a72611b-0f72-4ebf-a445-eec0dedf0a23" (took 395.6sec)
  COVERAGE_FILE=.coverage.6fc250c7-8111-4823-9ca3-441f6370f7f6 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-6fc250c7-8111-4823-9ca3-441f6370f7f6.xml --junitxml=test-reports/pytest-report-6fc250c7-8111-4823-9ca3-441f6370f7f6.xml 'buzzard/test/test_footprint_tile_count.py' &>/tmp/6fc250c7-8111-4823-9ca3-441f6370f7f6" (took 404.9sec)
  COVERAGE_FILE=.coverage.2bf08196-ca6c-437c-9dab-9b081da6c4be bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-2bf08196-ca6c-437c-9dab-9b081da6c4be.xml --junitxml=test-reports/pytest-report-2bf08196-ca6c-437c-9dab-9b081da6c4be.xml 'buzzard/test/test_vectorsource_getsetdata_general.py::test_run[Memory--True-True]' &>/tmp/2bf08196-ca6c-437c-9dab-9b081da6c4be" (took 407.2sec)
  COVERAGE_FILE=.coverage.ceb18bb4-50a0-4020-9645-e3ac38538b20 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-ceb18bb4-50a0-4020-9645-e3ac38538b20.xml --junitxml=test-reports/pytest-report-ceb18bb4-50a0-4020-9645-e3ac38538b20.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools1-cache_tiles2]' &>/tmp/ceb18bb4-50a0-4020-9645-e3ac38538b20" (took 414.6sec)
  COVERAGE_FILE=.coverage.5dd205ee-0652-4af7-a28c-86e1ad2487cf bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-5dd205ee-0652-4af7-a28c-86e1ad2487cf.xml --junitxml=test-reports/pytest-report-5dd205ee-0652-4af7-a28c-86e1ad2487cf.xml 'buzzard/test/test_vectorsource_getsetdata_general.py::test_run[ESRI Shapefile-.shp-True-True]' &>/tmp/5dd205ee-0652-4af7-a28c-86e1ad2487cf" (took 507.5sec)
  COVERAGE_FILE=.coverage.63b69eed-173f-4a91-aee0-af7730c71962 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-63b69eed-173f-4a91-aee0-af7730c71962.xml --junitxml=test-reports/pytest-report-63b69eed-173f-4a91-aee0-af7730c71962.xml 'buzzard/test/test_footprint_convs.py' &>/tmp/63b69eed-173f-4a91-aee0-af7730c71962" (took 510.8sec)
  COVERAGE_FILE=.coverage.268dcf02-8d38-4e22-88d2-d6028d8278e5 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-268dcf02-8d38-4e22-88d2-d6028d8278e5.xml --junitxml=test-reports/pytest-report-268dcf02-8d38-4e22-88d2-d6028d8278e5.xml 'buzzard/test/test_vectorsource_getsetdata_general.py::test_run[DXF-.dxf-False-False]' &>/tmp/268dcf02-8d38-4e22-88d2-d6028d8278e5" (took 525.8sec)
  COVERAGE_FILE=.coverage.35fd1b49-9896-4d08-899b-744a58ff293a bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-35fd1b49-9896-4d08-899b-744a58ff293a.xml --junitxml=test-reports/pytest-report-35fd1b49-9896-4d08-899b-744a58ff293a.xml 'buzzard/test/test_rastersource_resampling.py' &>/tmp/35fd1b49-9896-4d08-899b-744a58ff293a" (took 555.6sec)
  COVERAGE_FILE=.coverage.669d967d-182c-406b-a3e3-9d7353a81350 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-669d967d-182c-406b-a3e3-9d7353a81350.xml --junitxml=test-reports/pytest-report-669d967d-182c-406b-a3e3-9d7353a81350.xml 'buzzard/test/test_vectorsource_getsetdata_general.py::test_run[GeoJson-.json-True-True]' &>/tmp/669d967d-182c-406b-a3e3-9d7353a81350" (took 559.2sec)
Traceback (most recent call last):
  File "scripts/pytest_parallel.py", line 153, in <module>
    list(ex.map(_run_test, tests))
  File "/usr/local/lib/python3.7/concurrent/futures/_base.py", line 598, in result_iterator
    yield fs.pop().result()
  File "/usr/local/lib/python3.7/concurrent/futures/_base.py", line 428, in result
    return self.__get_result()
  File "/usr/local/lib/python3.7/concurrent/futures/_base.py", line 384, in __get_result
    raise self._exception
  File "/usr/local/lib/python3.7/concurrent/futures/thread.py", line 57, in run
    result = self.fn(*self.args, **self.kwargs)
  File "scripts/pytest_parallel.py", line 139, in _run_test
    cmd, code, res
Exception: COVERAGE_FILE=.coverage.a75c11b5-3410-47e4-bf79-e3f56806ba96 bash -c "pytest -x --cov=buzzard --cov-report=term --cov-report=xml:test-reports/coverage-a75c11b5-3410-47e4-bf79-e3f56806ba96.xml --junitxml=test-reports/pytest-report-a75c11b5-3410-47e4-bf79-e3f56806ba96.xml 'buzzard/test/test_cached_raster_recipe.py::test_[pools0-cache_tiles0]' &>/tmp/a75c11b5-3410-47e4-bf79-e3f56806ba96" failed with code 256
============= output:
============================= test session starts ==============================
platform linux -- Python 3.7.9, pytest-7.1.2, pluggy-1.0.0
rootdir: /tmp/circleci/buzzard
plugins: cov-3.0.0
collected 1 item

buzzard/test/test_cached_raster_recipe.py F                              [100%]

=================================== FAILURES ===================================
__________________________ test_[pools0-cache_tiles0] __________________________

pools = {'computation': {'computation_pool': None}, 'io': {'io_pool': None}, 'merge': {'merge_pool': None}, 'resample': {'resample_pool': None}}
test_prefix = '/tmp/buzz-ut-5e14f161-6525-46cc-8f29-e2a7857ab0d8'
cache_tiles = (100, 100)
test_prefix2 = '/tmp/buzz-ut-0a07cee9-8e43-4d87-b997-0940cb33a06f'

    def test_(pools, test_prefix, cache_tiles, test_prefix2):
        def _open(**kwargs):
            d = dict(
                fp=fp, dtype='float32', channel_count=2,
                compute_array=functools.partial(_meshgrid_raster_in, reffp=fp),
                cache_dir=test_prefix,
                cache_tiles=cache_tiles,
                **dict(itertools.chain(
                    pools['merge'].items(),
                    pools['resample'].items(),
                    pools['computation'].items(),
                    pools['io'].items(),
                ))
            )
            d.update(kwargs)
            return ds.acreate_cached_raster_recipe(**d)
    
        def _test_get():
            arrs = r.get_data(band=-1)
            assert arrs.shape == tuple(np.r_[fp.shape, 2])
            x, y = arrs[..., 0], arrs[..., 1]
            xref, yref = fp.meshgrid_raster
            assert np.all(x == xref)
            assert np.all(y == yref)
    
        def _test_resampling(fp):
            arr = r.get_data(band=-1, fp=fp)
            ref = npr.get_data(band=-1, fp=fp)
            assert np.allclose(arr, ref)
    
        def _corrupt_files(files):
            for path in files:
                with open(path, 'wb') as stream:
                    stream.write(b'42')
    
        print() # debug line
        fp = buzz.Footprint(
            rsize=(100, 100),
            size=(100, 100),
            tl=(1000, 1100),
        )
        compute_same_address_space = (
            type(pools['computation']['computation_pool']) in {str, mp.pool.ThreadPool, type(None)}
        )
    
        with buzz.Dataset(allow_interpolation=1).close as ds:
            # Create a numpy raster with the same data, useful to compare resampling
            npr = ds.awrap_numpy_raster(fp, np.stack(fp.meshgrid_raster, axis=2).astype('float32'))
    
            # Test lazyness of cache
            r = _open()
            files = glob.glob(os.path.join(test_prefix, '*.tif'))
            assert len(files) == 0
    
            # Test get_data results
            _test_get()
            files = glob.glob(os.path.join(test_prefix, '*.tif'))
            assert len(files) > 0
            mtimes0 = {f: os.stat(f).st_mtime for f in files}
    
            # Test persistence of cache
            # Test get_data results
            r.close()
            r = _open(compute_array=_should_not_be_called)
            _test_get()
            files = glob.glob(os.path.join(test_prefix, '*.tif'))
            assert len(files) > 0
            mtimes1 = {f: os.stat(f).st_mtime for f in files}
            assert mtimes0 == mtimes1
    
            # Test overwrite parameter
            # Test get_data results
            r.close()
            r = _open(ow=True)
            _test_get()
            files = glob.glob(os.path.join(test_prefix, '*.tif'))
            assert len(files) > 0
            mtimes1 = {f: os.stat(f).st_mtime for f in files}
            assert mtimes0.keys() == mtimes1.keys()
            for k, t0 in mtimes0.items():
                t1 = mtimes1[k]
                assert t0 < t1
    
            # Test remapping #1 - Interpolation - Fully Inside
            fp_within_upscaled = fp.intersection(fp, scale=fp.scale / 2) & fp.erode(fp.rsemiminoraxis // 4)
            _test_resampling(fp_within_upscaled)
    
            # Test remapping #2 - Interpolation - Fully Outside
            _test_resampling(fp_within_upscaled.move(fp.br + fp.diagvec))
    
            # Test remapping #3 - No Interpolation - Fully Outside
            _test_resampling(fp.move(fp.br + fp.diagvec))
    
            # Test remapping #4 - Interpolation - Both in and out
            _test_resampling(fp_within_upscaled.move(fp.br - fp_within_upscaled.diagvec / 2))
    
            # Test remapping #5 - No Interpolation - Both in and out
            _test_resampling(fp.move(fp.br - fp.pxvec * fp.rsemiminoraxis))
    
            # Test remapping #6 - Interpolation - Fully Inside - Tiled
            r.close()
            r = _open(max_resampling_size=20)
            _test_resampling(fp_within_upscaled)
    
            # Concurrent queries that need a cache file checksum
            r.close()
            r = _open()
            for it in [r.iter_data(fps=[fp], band=-1) for _ in range(10)]:
                next(it)
    
            # Concurrent queries that need a cache file missing, all but one computation aborted
            # because already launched
            r.close()
            r = _open(ow=True)
            for it in [r.iter_data(fps=[fp], band=-1) for _ in range(10)]:
                next(it)
    
            # Query garbage collected
            it1 = r.iter_data(fps=[fp] * 2, max_queue_size=1) # 2/2 ready, 1/2 sinked
            it2 = r.iter_data(fps=[fp] * 1, max_queue_size=1) # 1/1 ready, 0/1 sinked
            it3 = r.iter_data(fps=[fp] * 2, max_queue_size=1) # 1/2 ready, 0/2 sinked
            next(it1)
            time.sleep(1/2)
    
            del it1, it2, it3
            gc.collect()
            time.sleep(1 / 2)
            r.get_data() # This line will reraise any exception from scheduler
    
            # Raster closing during query
            it1 = r.iter_data(fps=[fp] * 2, max_queue_size=1) # 2/2 ready, 1/2 sinked
            it2 = r.iter_data(fps=[fp] * 1, max_queue_size=1) # 1/1 ready, 0/1 sinked
            it3 = r.iter_data(fps=[fp] * 2, max_queue_size=1) # 1/2 ready, 0/2 sinked
            next(it1)
            time.sleep(1/2)
            # Close Dataset instead of Raster, because Dataset.close is currently blocking
    
        with buzz.Dataset(allow_interpolation=1).close as ds:
            npr = ds.awrap_numpy_raster(fp, np.stack(fp.meshgrid_raster, axis=2).astype('float32'))
    
            # Corrupted cache file
            files = glob.glob(os.path.join(test_prefix, '*.tif'))
            mtimes0 = {f: os.stat(f).st_mtime for f in files}
            corrupted_path = files[0]
            _corrupt_files([corrupted_path])
            r = _open()
    
            r.get_data()
            mtimes1 = {f: os.stat(f).st_mtime for f in files}
            assert mtimes0.keys() == mtimes1.keys()
            for path in files:
                if path == corrupted_path:
                    assert mtimes0[path] != mtimes1[path]
                else:
                    assert mtimes0[path] == mtimes1[path]
    
        with buzz.Dataset(allow_interpolation=1).close as ds:
            npr = ds.awrap_numpy_raster(fp, np.stack(fp.meshgrid_raster, axis=2).astype('float32'))
    
            # In iter_data, the first one(s) don't need cache, the next ones need cache file checking and then recomputation
            _corrupt_files(glob.glob(os.path.join(test_prefix, '*.tif')))
            r = _open()
            fps = [
                fp.move(fp.br + fp.diagvec), # Outside
            ] + [fp] * 12
            arrs = list(r.iter_data(band=-1, fps=fps))
            assert len(arrs) == 13
            for tile, arr in zip(fps, arrs):
                assert np.all(arr == npr.get_data(band=-1, fp=tile))
    
        with buzz.Dataset(allow_interpolation=1).close as ds:
            npr = ds.awrap_numpy_raster(fp, np.stack(fp.meshgrid_raster, axis=2).astype('float32'))
    
            # Test channels order versus numpy raster
            r = _open()
            for channels in [
                    0, 1, None, slice(None), [0, 1], [1, 0], [1, 0, 1],
            ]:
                assert np.all(r.get_data(channels=channels) == npr.get_data(channels=channels))
    
        with buzz.Dataset(allow_interpolation=1).close as ds:
            # Derived and primitive rasters not computed
            if compute_same_address_space:
                ac0, ac1 = _AreaCounter(fp), _AreaCounter(fp)
            else:
                ac0, ac1 = None, None
            r0 = _open(
                compute_array=functools.partial(_base_computation, area_counter=ac0, reffp=fp),
                ow=True,
            )
            r1 = _open(
                compute_array=functools.partial(_derived_computation, area_counter=ac1, reffp=fp),
                queue_data_per_primitive={'prim': functools.partial(r0.queue_data, band=-1)},
                cache_dir=test_prefix2,
                ow=True,
            )
            assert len(r0.primitives) == 0
            assert len(r1.primitives) == 1
            assert r1.primitives['prim'] is r0
    
            r1.get_data()
            if compute_same_address_space:
                ac0.check_done()
                ac1.check_done()
            r0.close()
            r1.close()
    
            # Derived raster not computed
            if compute_same_address_space:
                ac0, ac1 = _AreaCounter(fp), _AreaCounter(fp)
            else:
                ac0, ac1 = None, None
            r0 = _open(
                compute_array=functools.partial(_base_computation, area_counter=ac0, reffp=fp),
                ow=False,
            )
            r1 = _open(
                compute_array=functools.partial(_derived_computation, area_counter=ac1, reffp=fp),
                queue_data_per_primitive={'prim': functools.partial(r0.queue_data, band=-1)},
                cache_dir=test_prefix2,
                ow=True,
            )
            r1.get_data()
            if compute_same_address_space:
                ac0.check_not_done()
                ac1.check_done()
            r0.close()
            r1.close()
    
            # Primitive raster not computed
            if compute_same_address_space:
                ac0, ac1 = _AreaCounter(fp), _AreaCounter(fp)
            else:
                ac0, ac1 = None, None
            r0 = _open(
                compute_array=functools.partial(_base_computation, area_counter=ac0, reffp=fp),
                ow=True,
            )
            r1 = _open(
                compute_array=functools.partial(_derived_computation, area_counter=ac1, reffp=fp),
                queue_data_per_primitive={'prim': functools.partial(r0.queue_data, band=-1)},
                cache_dir=test_prefix2,
                ow=False,
            )
            r1.get_data()
            if compute_same_address_space:
                ac0.check_not_done()
                ac1.check_not_done()
            r0.close()
            r1.close()
    
            # Test computation tiles
            if compute_same_address_space:
                ac0, ac1 = _AreaCounter(fp), _AreaCounter(fp)
            else:
                ac0, ac1 = None, None
            r0 = _open(
                compute_array=functools.partial(_base_computation, area_counter=ac0, reffp=fp),
                computation_tiles=(11, 11),
                ow=True,
            )
            r1 = _open(
                compute_array=functools.partial(_derived_computation, area_counter=ac1, reffp=fp),
                queue_data_per_primitive={'prim': functools.partial(r0.queue_data, band=-1)},
                cache_dir=test_prefix2,
                computation_tiles=(22, 22),
                ow=True,
            )
            r1.get_data()
            if compute_same_address_space:
                ac0.check_done()
                ac1.check_done()
            r0.close()
            r1.close()
    
            # Several queries, one is dropped, the rest is still working
            r0 = _open(
                compute_array=functools.partial(_base_computation, reffp=fp),
                ow=True,
            )
            r1 = _open(
                compute_array=functools.partial(_derived_computation, reffp=fp),
                queue_data_per_primitive={'prim': functools.partial(r0.queue_data, band=-1)},
                cache_dir=test_prefix2,
                ow=True,
            )
            t = r1.cache_tiles.flatten()
            fps0 = t.tolist() * 2
            fps1 = fps0[::-1]
            fps2 = np.roll(t, t.size // 2).tolist() * 2
            fps3 = fps2[::-1]
    
            it0 = r1.iter_data(fps=fps0)
            it1 = r1.iter_data(fps=fps1)
            it2 = r1.iter_data(fps=fps2)
            it3 = r1.iter_data(fps=fps3)
            del it1
    
            assert len(list(it3)) == t.size * 2
            assert len(list(it0)) == t.size * 2
            assert len(list(it2)) == t.size * 2
    
>           r0.close()

buzzard/test/test_cached_raster_recipe.py:361: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
buzzard/_tools/helper_classes.py:94: in __call__
    self._routine()
buzzard/_a_source.py:75: in _close
    self._back.close()
buzzard/_a_async_raster.py:203: in close
    self.back_ds.deactivate_many(self.async_dict_path_of_cache_fp.values())
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <buzzard._dataset_back.BackDataset object at 0x7f323c58da90>
uid_set = dict_values(['/tmp/buzz-ut-5e14f161-6525-46cc-8f29-e2a7857ab0d8/buzz_x000-y000_x00000-y00000_0e79770b32280b4e.tif'])

    def deactivate_many(self, uid_set):
        # TODO idea: allow recursive uids to group activated rasters and allow group deactivation
        if len(uid_set) == 0:
            return
        with self._ap_lock:
            being_used = uid_set & self._ap_used.keys()
            if being_used:
                raise RuntimeError('Attempting to deactivate {} source currently used'.format(
>                   len(being_used)
                ))
E               RuntimeError: Attempting to deactivate 1 source currently used

buzzard/_dataset_back_activation_pool.py:44: RuntimeError
----------------------------- Captured stdout call -----------------------------

------------------------------ Captured log call -------------------------------
WARNING  root:parameters.py:340 `band` parameter in `ASourceRaster.get_data` is deprecated since v0.6.0, use `channels` instead
WARNING  root:parameters.py:340 `band` parameter in `Raster.iter_data` is deprecated since v0.6.0, use `channels` instead
WARNING  buzzard._actors.cached.queries_handler:queries_handler.py:203 Dropping a query with 1/2 arrays produced.
WARNING  buzzard._actors.cached.queries_handler:queries_handler.py:203 Dropping a query with 1/2 arrays produced.
WARNING  buzzard._actors.cached.file_checker:file_checker.py:149 Removing /tmp/buzz-ut-5e14f161-6525-46cc-8f29-e2a7857ab0d8/buzz_x000-y000_x00000-y00000_0e79770b32280b4e.tif because invalid checksum (0000000000003234 instead of 0e79770b32280b4e)
WARNING  buzzard._actors.cached.file_checker:file_checker.py:149 Removing /tmp/buzz-ut-5e14f161-6525-46cc-8f29-e2a7857ab0d8/buzz_x000-y000_x00000-y00000_0e79770b32280b4e.tif because invalid checksum (0000000000003234 instead of 0e79770b32280b4e)
WARNING  root:parameters.py:340 `band` parameter in `Raster.create_raster_recipe` is deprecated since v0.6.0, use `channels` instead
=============================== warnings summary ===============================
venvs/37/lib/python3.7/site-packages/osgeo/__init__.py:8
  /tmp/circleci/buzzard/venvs/37/lib/python3.7/site-packages/osgeo/__init__.py:8: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
    import imp

buzzard/test/test_cached_raster_recipe.py: 316 warnings
  /tmp/circleci/buzzard/buzzard/_dataset_back_scheduler.py:38: PendingDeprecationWarning: isAlive() is deprecated, use is_alive() instead
    if not self._thread.isAlive():

buzzard/test/test_cached_raster_recipe.py: 21 warnings
  /tmp/circleci/buzzard/buzzard/_footprint_intersection.py:127: ShapelyDeprecationWarning: The array interface is deprecated and will no longer work in Shapely 2.0. Convert the '.coords' to a numpy array instead.
    points = np.concatenate(list(_exterior_coords_iterator(geom)), axis=0)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
- generated xml file: /tmp/circleci/buzzard/test-reports/pytest-report-a75c11b5-3410-47e4-bf79-e3f56806ba96.xml -

----------- coverage: platform linux, python 3.7.9-final-0 -----------
Name                                           Stmts   Miss  Cover
------------------------------------------------------------------
buzzard/__init__.py                               32      0   100%
buzzard/_a_async_raster.py                        55      5    91%
buzzard/_a_emissary.py                            26     10    62%
buzzard/_a_emissary_raster.py                      6      0   100%
buzzard/_a_emissary_vector.py                      9      3    67%
buzzard/_a_gdal_raster.py                        109     49    55%
buzzard/_a_gdal_vector.py                        153    132    14%
buzzard/_a_pooled_emissary.py                     28     10    64%
buzzard/_a_pooled_emissary_raster.py               6      0   100%
buzzard/_a_pooled_emissary_vector.py               6      0   100%
buzzard/_a_raster_recipe.py                       32      1    97%
buzzard/_a_source.py                              55     14    75%
buzzard/_a_source_raster.py                       69     15    78%
buzzard/_a_source_raster_remap.py                 97     22    77%
buzzard/_a_source_vector.py                       82     53    35%
buzzard/_a_stored.py                               8      0   100%
buzzard/_a_stored_raster.py                       47     29    38%
buzzard/_a_stored_vector.py                       30     21    30%
buzzard/_actors/__init__.py                        0      0   100%
buzzard/_actors/cached/__init__.py                 0      0   100%
buzzard/_actors/cached/cache_extractor.py         49      4    92%
buzzard/_actors/cached/cache_supervisor.py       124      2    98%
buzzard/_actors/cached/file_checker.py           120     25    79%
buzzard/_actors/cached/merger.py                  84     21    75%
buzzard/_actors/cached/producer.py                57      1    98%
buzzard/_actors/cached/queries_handler.py         89      2    98%
buzzard/_actors/cached/query_infos.py            125      0   100%
buzzard/_actors/cached/reader.py                 140     35    75%
buzzard/_actors/cached/writer.py                  92     16    83%
buzzard/_actors/computation_accumulator.py        32      0   100%
buzzard/_actors/computation_gate1.py              69      1    99%
buzzard/_actors/computation_gate2.py              59      1    98%
buzzard/_actors/computer.py                      108     33    69%
buzzard/_actors/global_priorities_watcher.py     129     11    91%
buzzard/_actors/message.py                        16      0   100%
buzzard/_actors/pool_job.py                       24     11    54%
buzzard/_actors/pool_waiting_room.py             146    115    21%
buzzard/_actors/pool_working_room.py              37     26    30%
buzzard/_actors/priorities.py                     16      8    50%
buzzard/_actors/production_gate.py                47      0   100%
buzzard/_actors/resampler.py                     181     39    78%
buzzard/_actors/top_level.py                      50     10    80%
buzzard/_cached_raster_recipe.py                  74      1    99%
buzzard/_dataset.py                              327    159    51%
buzzard/_dataset_back.py                          10      0   100%
buzzard/_dataset_back_activation_pool.py          79     24    70%
buzzard/_dataset_back_conversions.py              89     56    37%
buzzard/_dataset_back_scheduler.py               167     14    92%
buzzard/_dataset_pools_container.py               61     33    46%
buzzard/_dataset_register.py                      19      4    79%
buzzard/_debug_observers_manager.py               14      1    93%
buzzard/_env.py                                   80     26    68%
buzzard/_footprint.py                            920    497    46%
buzzard/_footprint_intersection.py               122     47    61%
buzzard/_footprint_move.py                        72     68     6%
buzzard/_footprint_tile.py                       135     67    50%
buzzard/_gdal_file_raster.py                      41      7    83%
buzzard/_gdal_file_vector.py                      52     37    29%
buzzard/_gdal_mem_raster.py                       28     17    39%
buzzard/_gdal_memory_vector.py                    33     23    30%
buzzard/_numpy_raster.py                          77     23    70%
buzzard/_pint_interop.py                           4      0   100%
buzzard/_tools/__init__.py                         5      0   100%
buzzard/_tools/helper_classes.py                  49      9    82%
buzzard/_tools/multi_ordered_dict.py              66     23    65%
buzzard/_tools/parameters.py                     276    148    46%
buzzard/_tools/rect.py                            87     44    49%
buzzard/_tools/slices_of_matrix.py                39     33    15%
buzzard/utils/__init__.py                          1      0   100%
buzzard/utils/_merge_functions.py                 12      0   100%
------------------------------------------------------------------
TOTAL                                           5583   2086    63%
Coverage XML written to file test-reports/coverage-a75c11b5-3410-47e4-bf79-e3f56806ba96.xml

=========================== short test summary info ============================
FAILED buzzard/test/test_cached_raster_recipe.py::test_[pools0-cache_tiles0]
!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!
================= 1 failed, 338 warnings in 144.51s (0:02:24) ==================

=============


Exited with code exit status 1
CircleCI received exit code 1

Outdated recommendation?

Is the recommendation to use python >= 3.6.7 still relevant? It dates from Nov 7, 2018 but the changes introduced in https://bugs.python.org/issue34172 were reverted on Dec 6, 2018.

Issue with adding fields while inserting data

I've encountered an error while setting fields to a file that I'm writing to.

with buzz.create_vector(path=f'out{suffix}.geojson', type='polygon', driver="GeoJSON", ow=True,
 sr=self.geoim.wkt_virtual).close as out:
        for det in detections:
            out.insert_data(det['geom'], fields={'class': det['class'], 'score': det['score']})

Running the above snippet, throws an error as follows:

File "/home/ashwin/Desktop/Projects/demo/predictor.py", line 165, in post_process
    out.insert_data(det['geom'], fields={'class': det['class'], 'score': det['score']})
  File "/home/ashwin/anaconda3/envs/rdet/lib/python3.7/site-packages/buzzard/_a_stored_vector.py", line 64, in insert_data
    fields = self._normalize_field_values(fields)
  File "/home/ashwin/anaconda3/envs/rdet/lib/python3.7/site-packages/buzzard/_a_stored_vector.py", line 75, in _normalize_field_values
    i = self._back.index_of_field_name[k]
KeyError: 'class'

Source of the error as seen from above trace is here. If the fields I'm setting are not in self._back.index_of_field_name, setting will fail.

I'm not sure why this is the case. Is this not the correct way to set fields for a vector file? What exactly is self._back and what does it have to do with the fields I'm setting?

r = buzz.open_raster('path/to/my.tif')

tiles = r.fp.tile((512,512))

for i, fp in enumerate(tiles.flat):
    rgb = r.get_data(fp=fp, channels=(0, 1, 2))

However, the following error is thrown IndexError: too many indices for array: array is 1-dimensional, but 3 were indexed.

I checked my tiff and can confirm it has 3 channels

>>> r.channel_schema
{'nodata': [None, None, None], 'interpretation': ['redband', 'greenband', 'blueband'], 'offset': [0.0, 0.0, 0.0], 'scale': [1.0, 1.0, 1.0], 'mask': ['all_valid', 'all_valid', 'all_valid']}

So I'm not exactly sure why this is happening.

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