Skip to main content

A small package with fast numpy routines written in cython

Documentation

https://numpyx.readthedocs.io

Installation

pip install numpyx


Functions in this package

All functions here are specialized for double arrays only

Short-cut functions

These functions are similar to numpy functions but are faster by exiting out of a loop when one element satisfies the given condition

  • any_less_than

  • any_less_or_equal_than

  • any_greater_than

  • any_greater_or_equal_than

  • any_equal_to

  • array_is_sorted

  • allequal

minmax1d

Calculate min. and max. value in one go

searchsorted1

like search sorted, but for 1d double arrays. It is faster than the more generic numpy version

searchsorted2

like search sorted but allows to search across any column of a 2d array

nearestidx

Return the index of the item in an array which is nearest to a given value. The array does not need to be sorted (this is a simple linear search)

nearestitem

For any value of an array, search the nearest item in another array and put its value in the output result

weightedavg

Weighted averageof a time-series

trapz

trapz integration specialized for contiguous / double arrays. Quite faster than generic numpy/scipy

Release files for numpyx 1.6.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distributions (wheels)

Table of built distributions (wheels) for numpyx 1.6.0
File
numpyx-1.6.0-cp313-cp313-win_amd64.whl CPython 3.13 CPython 3.13 Windows x86-64 Details
numpyx-1.6.0-cp313-cp313-win32.whl CPython 3.13 CPython 3.13 Windows x86-32 Details
numpyx-1.6.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl CPython 3.13 CPython 3.13 Linux glibc 2.17+ x86-64, Linux glibc 2.28+ x86-64 Details
numpyx-1.6.0-cp313-cp313-macosx_11_0_arm64.whl CPython 3.13 CPython 3.13 macOS 11.0+ ARM64 Details
numpyx-1.6.0-cp313-cp313-macosx_10_13_x86_64.whl CPython 3.13 CPython 3.13 macOS 10.13+ x86-64 Details
numpyx-1.6.0-cp312-cp312-win_amd64.whl CPython 3.12 CPython 3.12 Windows x86-64 Details
numpyx-1.6.0-cp312-cp312-win32.whl CPython 3.12 CPython 3.12 Windows x86-32 Details
numpyx-1.6.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl CPython 3.12 CPython 3.12 Linux glibc 2.28+ x86-64, Linux glibc 2.17+ x86-64 Details
numpyx-1.6.0-cp312-cp312-macosx_11_0_arm64.whl CPython 3.12 CPython 3.12 macOS 11.0+ ARM64 Details
numpyx-1.6.0-cp312-cp312-macosx_10_13_x86_64.whl CPython 3.12 CPython 3.12 macOS 10.13+ x86-64 Details
numpyx-1.6.0-cp311-cp311-win_amd64.whl CPython 3.11 CPython 3.11 Windows x86-64 Details
numpyx-1.6.0-cp311-cp311-win32.whl CPython 3.11 CPython 3.11 Windows x86-32 Details
numpyx-1.6.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl CPython 3.11 CPython 3.11 Linux glibc 2.17+ x86-64, Linux glibc 2.28+ x86-64 Details
numpyx-1.6.0-cp311-cp311-macosx_11_0_arm64.whl CPython 3.11 CPython 3.11 macOS 11.0+ ARM64 Details
numpyx-1.6.0-cp311-cp311-macosx_10_9_x86_64.whl CPython 3.11 CPython 3.11 macOS 10.9+ x86-64 Details
numpyx-1.6.0-cp310-cp310-win_amd64.whl CPython 3.10 CPython 3.10 Windows x86-64 Details
numpyx-1.6.0-cp310-cp310-win32.whl CPython 3.10 CPython 3.10 Windows x86-32 Details
numpyx-1.6.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl CPython 3.10 CPython 3.10 Linux glibc 2.17+ x86-64, Linux glibc 2.28+ x86-64 Details
numpyx-1.6.0-cp310-cp310-macosx_11_0_arm64.whl CPython 3.10 CPython 3.10 macOS 11.0+ ARM64 Details
numpyx-1.6.0-cp310-cp310-macosx_10_9_x86_64.whl CPython 3.10 CPython 3.10 macOS 10.9+ x86-64 Details
numpyx-1.6.0-cp39-cp39-win_amd64.whl CPython 3.9 CPython 3.9 Windows x86-64 Details
numpyx-1.6.0-cp39-cp39-win32.whl CPython 3.9 CPython 3.9 Windows x86-32 Details
numpyx-1.6.0-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl CPython 3.9 CPython 3.9 Linux glibc 2.17+ x86-64, Linux glibc 2.28+ x86-64 Details
numpyx-1.6.0-cp39-cp39-macosx_11_0_arm64.whl CPython 3.9 CPython 3.9 macOS 11.0+ ARM64 Details
numpyx-1.6.0-cp39-cp39-macosx_10_9_x86_64.whl CPython 3.9 CPython 3.9 macOS 10.9+ x86-64 Details

Total release size: 5.6 MB

Release files / numpyx-1.6.0-cp313-cp313-win_amd64.whl

Download URL numpyx-1.6.0-cp313-cp313-win_amd64.whl
Size 111.6 kB
Tags CPython 3.13 Windows x86-64
SHA-256 checksum
How to use checksums
be97a97ee479ed5561725eca298dffd8c2cdd9f9524a27db71e79d6ebebfef33
BLAKE2b-256 checksum
How to use checksums
2f3dfc8e4515430c4124032adf7e49e0a8174fb3a7c8e4f6ab34d8131972f434
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp313-cp313-win32.whl

Download URL numpyx-1.6.0-cp313-cp313-win32.whl
Size 93.6 kB
Tags CPython 3.13 Windows x86-32
SHA-256 checksum
How to use checksums
372c6d9c49330634828368da4fd0a39a0f89a29a84c0104de8bb3a40bcb27539
BLAKE2b-256 checksum
How to use checksums
d8767e072fd16a96c9ed58f315b11e5af34864364ccaefbf17ca0137c18807e6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl

Download URL numpyx-1.6.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Size 671.9 kB
Tags CPython 3.13 Linux glibc 2.17+ x86-64 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
242b8f4515040b4e1c43ded26020838fd9bccb2425294d474d1340e8cefed864
BLAKE2b-256 checksum
How to use checksums
4ced8b75e35a4353b0c2152e8b2b2c7d568e3a7d2968317269b452b0d3fbba2e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.12

Release files / numpyx-1.6.0-cp313-cp313-macosx_11_0_arm64.whl

Download URL numpyx-1.6.0-cp313-cp313-macosx_11_0_arm64.whl
Size 122.3 kB
Tags CPython 3.13 macOS 11.0+ ARM64
SHA-256 checksum
How to use checksums
a1d5f721a5be02dbb9b2dd2219ce51bf5a8fe7d796523ac36a32a834821434af
BLAKE2b-256 checksum
How to use checksums
820f7e38cba69d3a2162fbc6ca15814337fd01ec08ec43307e2286db7842f1c1
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp313-cp313-macosx_10_13_x86_64.whl

Download URL numpyx-1.6.0-cp313-cp313-macosx_10_13_x86_64.whl
Size 126.6 kB
Tags CPython 3.13 macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
f9e4158eafaf8e3a33831460414a5752945d5e4418034e8cc3545f6f1aedc58a
BLAKE2b-256 checksum
How to use checksums
bdf7ba59450527576e8ddcfd380033ec42e5465b2d0486a233faa16aa4ea0d2c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp312-cp312-win_amd64.whl

Download URL numpyx-1.6.0-cp312-cp312-win_amd64.whl
Size 111.6 kB
Tags CPython 3.12 Windows x86-64
SHA-256 checksum
How to use checksums
1a9470753d406718abcaa72c4662b0c026d6fd7134dbbd30f1a9b554acd858be
BLAKE2b-256 checksum
How to use checksums
6799e860a6462cfd33698ee5e1b9319396d5b2442d1f01313d736bb9323c1884
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp312-cp312-win32.whl

Download URL numpyx-1.6.0-cp312-cp312-win32.whl
Size 93.7 kB
Tags CPython 3.12 Windows x86-32
SHA-256 checksum
How to use checksums
c44e8070fcad2e881eb4877b22f6eaf047abec4eafd47244774fb0aa32128d88
BLAKE2b-256 checksum
How to use checksums
95a22e18901401f98e089d1153fe9061aa8234bb9cb01320bd13161200edf6b5
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl

Download URL numpyx-1.6.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Size 679.3 kB
Tags CPython 3.12 Linux glibc 2.17+ x86-64 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
3e5f5e2c9d469f85d6885a91a151af91d0c8cd1409d1e193c1f8b216835b4133
BLAKE2b-256 checksum
How to use checksums
59044ae6ac0e30da4ccd6bbd1d5082d9f18a949a751582a70253022039186cfb
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.12

Release files / numpyx-1.6.0-cp312-cp312-macosx_11_0_arm64.whl

Download URL numpyx-1.6.0-cp312-cp312-macosx_11_0_arm64.whl
Size 122.9 kB
Tags CPython 3.12 macOS 11.0+ ARM64
SHA-256 checksum
How to use checksums
be954b587f82e1e2f457f3dcfb1b8c87163c16327faede7598ea3af625ea52b9
BLAKE2b-256 checksum
How to use checksums
b3fb0a8a486fbbb20ed37c1fe1423028267e8f7b6e91d11060df5e9a781792c0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp312-cp312-macosx_10_13_x86_64.whl

Download URL numpyx-1.6.0-cp312-cp312-macosx_10_13_x86_64.whl
Size 127.4 kB
Tags CPython 3.12 macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
a4020af2d68edb8c191cb2aec3d75ede64639f0be3e4b308e7697157e3b5f2de
BLAKE2b-256 checksum
How to use checksums
bd852caf281a46aa689f9b6971426c0152730335a49d71ee51f3233155b21bfd
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp311-cp311-win_amd64.whl

Download URL numpyx-1.6.0-cp311-cp311-win_amd64.whl
Size 111.1 kB
Tags CPython 3.11 Windows x86-64
SHA-256 checksum
How to use checksums
8f200adf8ea8e45e41ae3aa2b857d85f954ae54a11d1cec6d695b17a60f7ffe2
BLAKE2b-256 checksum
How to use checksums
adaa96c8106f72d680091204fa26ae396d782130ca85c7f24951f00fc998773f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp311-cp311-win32.whl

Download URL numpyx-1.6.0-cp311-cp311-win32.whl
Size 93.5 kB
Tags CPython 3.11 Windows x86-32
SHA-256 checksum
How to use checksums
89865c1b352f0185532909d02b92e889dfa5dc5e21f940ef38d969ac2adedf7e
BLAKE2b-256 checksum
How to use checksums
9d5f6d387975d6b69732b2998af92835994e52f1ecc7fc53998352504659403c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl

Download URL numpyx-1.6.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Size 679.0 kB
Tags CPython 3.11 Linux glibc 2.17+ x86-64 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
3af81c895beffe06e67342e83d7e50d39c911d6f3f2ddb8004e3c0ac6ca37b30
BLAKE2b-256 checksum
How to use checksums
6fbb182bbc475814d63b87efedf857cf6593cccca80e12e013650530dc766e28
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.12

Release files / numpyx-1.6.0-cp311-cp311-macosx_11_0_arm64.whl

Download URL numpyx-1.6.0-cp311-cp311-macosx_11_0_arm64.whl
Size 122.5 kB
Tags CPython 3.11 macOS 11.0+ ARM64
SHA-256 checksum
How to use checksums
b35b4a0fcacdf72f772a256401d19d525f3f1c08e385bf2554f2628bfdb83b52
BLAKE2b-256 checksum
How to use checksums
677448009c864a3ea334fb16adeb79ff82bc65f2537d554d28b04b9f376bb284
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp311-cp311-macosx_10_9_x86_64.whl

Download URL numpyx-1.6.0-cp311-cp311-macosx_10_9_x86_64.whl
Size 125.6 kB
Tags CPython 3.11 macOS 10.9+ x86-64
SHA-256 checksum
How to use checksums
9ec472c8c3724dff3e2bc7d527f9a612514c9c115066f358cd856dc3be181a43
BLAKE2b-256 checksum
How to use checksums
f94a9323867822a62b8e282e64f1316a66845555c14be32bfafef1e07ae48840
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp310-cp310-win_amd64.whl

Download URL numpyx-1.6.0-cp310-cp310-win_amd64.whl
Size 111.1 kB
Tags CPython 3.10 Windows x86-64
SHA-256 checksum
How to use checksums
51704e0c9fb935256c6ec4ee50ac6d66c80982df946a10ec41d306c50a81d36d
BLAKE2b-256 checksum
How to use checksums
2d3c55d012bf0479b1ba0bed6b9af744d436b5b70a5d0f8f12f4be33dc2646d0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp310-cp310-win32.whl

Download URL numpyx-1.6.0-cp310-cp310-win32.whl
Size 93.9 kB
Tags CPython 3.10 Windows x86-32
SHA-256 checksum
How to use checksums
239f5cd71388d28547f673d27dc712270dbb70fbb3742aaced0fd602167eba95
BLAKE2b-256 checksum
How to use checksums
bfa811100e9cdea93d086077d12ea72ce9a3c962f5e1c10d9447be812416ee58
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl

Download URL numpyx-1.6.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Size 650.4 kB
Tags CPython 3.10 Linux glibc 2.17+ x86-64 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
dab097fca1ade13ac2bdb923c791f51bac78ced42bc562a9b2a28cc4d12d63f0
BLAKE2b-256 checksum
How to use checksums
af9d631b145dcdd246c5ba8e62b5afd3a7b3c73889e968db90dca3c339518fb1
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.12

Release files / numpyx-1.6.0-cp310-cp310-macosx_11_0_arm64.whl

Download URL numpyx-1.6.0-cp310-cp310-macosx_11_0_arm64.whl
Size 122.7 kB
Tags CPython 3.10 macOS 11.0+ ARM64
SHA-256 checksum
How to use checksums
8f05fc3ece39c5e97d4af419f103f4db7c97b4cbf5b4f66d974e8020df4019ae
BLAKE2b-256 checksum
How to use checksums
c9c8b213df1c13ed4fc37f960a7790de279314f77e52f5ba054a1f8c51fc63c5
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp310-cp310-macosx_10_9_x86_64.whl

Download URL numpyx-1.6.0-cp310-cp310-macosx_10_9_x86_64.whl
Size 126.3 kB
Tags CPython 3.10 macOS 10.9+ x86-64
SHA-256 checksum
How to use checksums
c5d94d3679e499292b44f2f6bc1bcb14963c609c0c7e7019e58f90fdedff824b
BLAKE2b-256 checksum
How to use checksums
7ef4368c28544000aefb7d36754d00cfcef6be8fd866a59764be5936a1f80684
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp39-cp39-win_amd64.whl

Download URL numpyx-1.6.0-cp39-cp39-win_amd64.whl
Size 111.4 kB
Tags CPython 3.9 Windows x86-64
SHA-256 checksum
How to use checksums
7f1eef1055c170e3c606287cfdacf4ed858fadd83a6a6251518c0fbab7c1a86c
BLAKE2b-256 checksum
How to use checksums
dcbcd59b627f885e630ae5832c4a4cc24cf49a7fcf87cbbff25b3f30d0d6a20a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp39-cp39-win32.whl

Download URL numpyx-1.6.0-cp39-cp39-win32.whl
Size 94.1 kB
Tags CPython 3.9 Windows x86-32
SHA-256 checksum
How to use checksums
639e4bd454052eb16caae48b8c9291f136f48ea9ffec5dc87babc94b13f6db64
BLAKE2b-256 checksum
How to use checksums
a43ef8866981832f5a9030861480fc9b7df1bb27a5d18b496353cd5aef294dae
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl

Download URL numpyx-1.6.0-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Size 647.2 kB
Tags CPython 3.9 Linux glibc 2.17+ x86-64 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
e934c727080547babe116c77f3211ab266ce076ae3bb5050c2ecf52cfe78142c
BLAKE2b-256 checksum
How to use checksums
2d1fb3d8eb323750d3ad4f30934ebd15984fc45d69503364bb5d83cccf5382b2
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.12

Release files / numpyx-1.6.0-cp39-cp39-macosx_11_0_arm64.whl

Download URL numpyx-1.6.0-cp39-cp39-macosx_11_0_arm64.whl
Size 123.0 kB
Tags CPython 3.9 macOS 11.0+ ARM64
SHA-256 checksum
How to use checksums
35b08478b0f937bb38f204b86873f3c5b9bdd1875a3f1b45a8a2b5a9af0b1ee5
BLAKE2b-256 checksum
How to use checksums
f6a8a464bfe7994036dabb1e5bf2a2c87a049eef6b3f474087f3b72c2704b8b3
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release files / numpyx-1.6.0-cp39-cp39-macosx_10_9_x86_64.whl

Download URL numpyx-1.6.0-cp39-cp39-macosx_10_9_x86_64.whl
Size 126.8 kB
Tags CPython 3.9 macOS 10.9+ x86-64
SHA-256 checksum
How to use checksums
8dcebd3601157a0f07e6ec847cbb9efc7e7978e28ea4d52e365fed637258d4a0
BLAKE2b-256 checksum
How to use checksums
e57b688e3e69219f2c0d9c1bccd38c1524417f1b5353ec2d64c8c39b8810d35b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.10

Release history Release notifications | RSS feed

This release

1.6.0 This release

25 release files

1.5.2

30 release files

1.5.1

20 release files

1.4.4

20 release files

1.4.3

20 release files

1.4.2

21 release files

1.4.1

20 release files

1.3.3

20 release files

1.3.0

31 release files

1.2.3

1 release file

1.2.2

31 release files

1.2.0

7 release files

1.1.0

10 release files

0.6.0

6 release files

0.5.0

5 release files

0.4.1

1 release file

0.4.0

1 release file

0.3.4

1 release file

0.3.3

5 release files

0.3.2

5 release files

0.3.1

1 release file

0.3.0

1 release file

0.2.1

1 release file

0.1.5

1 release file

0.1.4

1 release file

0.1.3

1 release file

0.1.2

1 release file

0.1.1

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page