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Use RIO_TILER_MAX_THREADS instead of MAX_THREADS #432

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merged 4 commits into from
Oct 8, 2021
Merged

Use RIO_TILER_MAX_THREADS instead of MAX_THREADS #432

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792a030
MAX_THREADS to RIO_TILER_MAX_THREADS
Oct 7, 2021
c88ace8
Update env variable in docs
Oct 8, 2021
c9f4c55
Add to changelog
Oct 8, 2021
9792f7a
Update CHANGES.md
vincentsarago Oct 8, 2021
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1 change: 1 addition & 0 deletions CHANGES.md
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Expand Up @@ -6,6 +6,7 @@
* remove python 3.6 support (https://github.com/cogeotiff/rio-tiler/pull/418)
* remove `max_size` defaults for `COGReader.part` and `COGReader.feature`, which will now default to full resolution reading.
* Deprecate `.metadata` methods (https://github.com/cogeotiff/rio-tiler/pull/423)
* Use `RIO_TILER_MAX_THREADS` environment variable instead of `MAX_THREADS` (author @rodrigoalmeida94, https://github.com/cogeotiff/rio-tiler/pull/432)

# 2.1.3 (2021-09-14)

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2 changes: 1 addition & 1 deletion docs/mosaic.md
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Expand Up @@ -134,7 +134,7 @@ By default the chunck_size is equal to the number or threads (or the number of a

#### More on threading

The number of threads used can be set in the function call with the `threads=` options. By default it will be equal to `multiprocessing.cpu_count() * 5` or to the `MAX_THREADS` environment variable.
The number of threads used can be set in the function call with the `threads=` options. By default it will be equal to `multiprocessing.cpu_count() * 5` or to the `RIO_TILER_MAX_THREADS` environment variable.
In some case, threading can slow down your application. You can set threads to `0` or `1` to run the tiler in a loop without using a ThreadPool (ref: [#207](https://github.com/cogeotiff/rio-tiler/issues/207)).

Benchmark:
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4 changes: 3 additions & 1 deletion rio_tiler/constants.py
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Expand Up @@ -13,7 +13,9 @@
NoData = Union[float, int, str]
Indexes = Union[Sequence[int], int]

MAX_THREADS = int(os.environ.get("MAX_THREADS", multiprocessing.cpu_count() * 5))
MAX_THREADS = int(
os.environ.get("RIO_TILER_MAX_THREADS", multiprocessing.cpu_count() * 5)
)
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WEB_MERCATOR_CRS = CRS.from_epsg(3857)
WGS84_CRS = CRS.from_epsg(4326)
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