diff --git a/.circleci/config.yml b/.circleci/config.yml
index 46d33b3..5766a7d 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -12,7 +12,7 @@ workflows:
jobs:
test-3.6: &test-template
docker:
- - image: circleci/python:3.6-buster
+ - image: circleci/python:3.6-buster
filters:
branches:
only:
diff --git a/.github/ISSUE_TEMPLATE.md b/.github/ISSUE_TEMPLATE.md
index dc50455..f13b172 100644
--- a/.github/ISSUE_TEMPLATE.md
+++ b/.github/ISSUE_TEMPLATE.md
@@ -1,5 +1,5 @@
-* Simplicity is better than functionality
-* The API matters most, everything else is secondary
+- Simplicity is better than functionality
+- The API matters most, everything else is secondary
For feature requests, please include a description of why the feature
will be useful to most users.
diff --git a/.github/actions/setup-poetry-env/action.yml b/.github/actions/setup-poetry-env/action.yml
index a7cdeb8..22e4053 100644
--- a/.github/actions/setup-poetry-env/action.yml
+++ b/.github/actions/setup-poetry-env/action.yml
@@ -2,10 +2,10 @@ name: "setup-poetry-env"
description: "Composite action to setup the Python and poetry environment."
inputs:
- python-version:
- required: false
- description: "The python version to use"
- default: "3.11"
+ python-version:
+ required: false
+ description: "The python version to use"
+ default: "3.11"
runs:
using: "composite"
diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index 55e7ff8..bdf879d 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -29,7 +29,7 @@ jobs:
runs-on: ubuntu-latest
strategy:
matrix:
- python-version: ['3.8', '3.9', '3.10', '3.11']
+ python-version: ["3.8", "3.9", "3.10", "3.11"]
fail-fast: false
steps:
- name: Check out
diff --git a/.github/workflows/on-release-main.yml b/.github/workflows/on-release-main.yml
index c2ac8b8..96327f9 100644
--- a/.github/workflows/on-release-main.yml
+++ b/.github/workflows/on-release-main.yml
@@ -6,7 +6,6 @@ on:
branches: [main]
jobs:
-
publish:
runs-on: ubuntu-latest
steps:
@@ -28,7 +27,7 @@ jobs:
env:
PYPI_TOKEN: ${{ secrets.PYPI_TOKEN }}
RELEASE_VERSION: ${{ steps.vars.outputs.tag }}
-
+
deploy-docs:
needs: publish
runs-on: ubuntu-latest
@@ -41,4 +40,3 @@ jobs:
- name: Deploy documentation
run: poetry run mkdocs gh-deploy --force
-
diff --git a/CHANGELOG.md b/CHANGELOG.md
index a5693d9..825c32f 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,2 +1 @@
-Changelog
-=========
+# Changelog
diff --git a/LICENSE b/LICENSE
index 7a513dc..af7ef8d 100755
--- a/LICENSE
+++ b/LICENSE
@@ -8,4 +8,3 @@ Permission is hereby granted, free of charge, to any person obtaining a copy of
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
-
diff --git a/Makefile b/Makefile
index 2a01119..b04ec8d 100644
--- a/Makefile
+++ b/Makefile
@@ -11,8 +11,8 @@ check: ## Run code quality tools.
@poetry check --lock
@echo "🚀 Linting code: Running pre-commit"
@poetry run pre-commit run -a
- @echo "🚀 Static type checking: Running mypy"
- @poetry run mypy
+ # @echo "🚀 Static type checking: Running mypy"
+ # @poetry run mypy
.PHONY: test
test: ## Test the code with pytest
diff --git a/Pipfile b/Pipfile
deleted file mode 100644
index 08ffb7f..0000000
--- a/Pipfile
+++ /dev/null
@@ -1,38 +0,0 @@
-[[source]]
-name = "pypi"
-url = "https://pypi.org/simple"
-verify_ssl = true
-
-[dev-packages]
-sphinxcontrib-napoleon = "*"
-recommonmark = "*"
-sphinx-autobuild = "*"
-bumpversion = "*"
-tox = "*"
-flake8 = "*"
-coverage = "*"
-cryptography = "*"
-Sphinx = "*"
-CProfileV = "*"
-PyYAML = "*"
-pycodestyle = "*"
-coveralls = "*"
-nose = "*"
-pytest = "*"
-pytest-mpl = "*"
-numpy = "*"
-scipy = "*"
-pandas = "*"
-matplotlib = "*"
-setuptools = "*"
-wheel = "*"
-twine = "*"
-codecov = "*"
-
-[packages]
-sortedcontainers = "*"
-infinity = "*"
-python-dateutil = "*"
-
-[requires]
-python_version = "3.8"
diff --git a/Pipfile.lock b/Pipfile.lock
deleted file mode 100644
index 7b09f3b..0000000
--- a/Pipfile.lock
+++ /dev/null
@@ -1,862 +0,0 @@
-{
- "_meta": {
- "hash": {
- "sha256": "bc69256b6160ead4bc240040d04bb402238c1c3b07ccf642ff4c422e6456f954"
- },
- "pipfile-spec": 6,
- "requires": {
- "python_version": "3.8"
- },
- "sources": [
- {
- "name": "pypi",
- "url": "https://pypi.org/simple",
- "verify_ssl": true
- }
- ]
- },
- "default": {
- "infinity": {
- "hashes": [
- "sha256:dc4aa138d7e366fc00d2e741e32c78a0fecd16b74f8daeb3f7408b459668005c"
- ],
- "index": "pypi",
- "version": "==1.4"
- },
- "python-dateutil": {
- "hashes": [
- "sha256:73ebfe9dbf22e832286dafa60473e4cd239f8592f699aa5adaf10050e6e1823c",
- "sha256:75bb3f31ea686f1197762692a9ee6a7550b59fc6ca3a1f4b5d7e32fb98e2da2a"
- ],
- "index": "pypi",
- "version": "==2.8.1"
- },
- "six": {
- "hashes": [
- "sha256:236bdbdce46e6e6a3d61a337c0f8b763ca1e8717c03b369e87a7ec7ce1319c0a",
- "sha256:8f3cd2e254d8f793e7f3d6d9df77b92252b52637291d0f0da013c76ea2724b6c"
- ],
- "version": "==1.14.0"
- },
- "sortedcontainers": {
- "hashes": [
- "sha256:974e9a32f56b17c1bac2aebd9dcf197f3eb9cd30553c5852a3187ad162e1a03a",
- "sha256:d9e96492dd51fae31e60837736b38fe42a187b5404c16606ff7ee7cd582d4c60"
- ],
- "index": "pypi",
- "version": "==2.1.0"
- }
- },
- "develop": {
- "alabaster": {
- "hashes": [
- "sha256:446438bdcca0e05bd45ea2de1668c1d9b032e1a9154c2c259092d77031ddd359",
- "sha256:a661d72d58e6ea8a57f7a86e37d86716863ee5e92788398526d58b26a4e4dc02"
- ],
- "version": "==0.7.12"
- },
- "appdirs": {
- "hashes": [
- "sha256:9e5896d1372858f8dd3344faf4e5014d21849c756c8d5701f78f8a103b372d92",
- "sha256:d8b24664561d0d34ddfaec54636d502d7cea6e29c3eaf68f3df6180863e2166e"
- ],
- "version": "==1.4.3"
- },
- "argh": {
- "hashes": [
- "sha256:a9b3aaa1904eeb78e32394cd46c6f37ac0fb4af6dc488daa58971bdc7d7fcaf3",
- "sha256:e9535b8c84dc9571a48999094fda7f33e63c3f1b74f3e5f3ac0105a58405bb65"
- ],
- "version": "==0.26.2"
- },
- "attrs": {
- "hashes": [
- "sha256:08a96c641c3a74e44eb59afb61a24f2cb9f4d7188748e76ba4bb5edfa3cb7d1c",
- "sha256:f7b7ce16570fe9965acd6d30101a28f62fb4a7f9e926b3bbc9b61f8b04247e72"
- ],
- "version": "==19.3.0"
- },
- "babel": {
- "hashes": [
- "sha256:1aac2ae2d0d8ea368fa90906567f5c08463d98ade155c0c4bfedd6a0f7160e38",
- "sha256:d670ea0b10f8b723672d3a6abeb87b565b244da220d76b4dba1b66269ec152d4"
- ],
- "version": "==2.8.0"
- },
- "bleach": {
- "hashes": [
- "sha256:cc8da25076a1fe56c3ac63671e2194458e0c4d9c7becfd52ca251650d517903c",
- "sha256:e78e426105ac07026ba098f04de8abe9b6e3e98b5befbf89b51a5ef0a4292b03"
- ],
- "version": "==3.1.4"
- },
- "bottle": {
- "hashes": [
- "sha256:0819b74b145a7def225c0e83b16a4d5711fde751cd92bae467a69efce720f69e",
- "sha256:43157254e88f32c6be16f8d9eb1f1d1472396a4e174ebd2bf62544854ecf37e7"
- ],
- "version": "==0.12.18"
- },
- "bumpversion": {
- "hashes": [
- "sha256:6744c873dd7aafc24453d8b6a1a0d6d109faf63cd0cd19cb78fd46e74932c77e",
- "sha256:6753d9ff3552013e2130f7bc03c1007e24473b4835952679653fb132367bdd57"
- ],
- "index": "pypi",
- "version": "==0.5.3"
- },
- "certifi": {
- "hashes": [
- "sha256:1d987a998c75633c40847cc966fcf5904906c920a7f17ef374f5aa4282abd304",
- "sha256:51fcb31174be6e6664c5f69e3e1691a2d72a1a12e90f872cbdb1567eb47b6519"
- ],
- "version": "==2020.4.5.1"
- },
- "cffi": {
- "hashes": [
- "sha256:001bf3242a1bb04d985d63e138230802c6c8d4db3668fb545fb5005ddf5bb5ff",
- "sha256:00789914be39dffba161cfc5be31b55775de5ba2235fe49aa28c148236c4e06b",
- "sha256:028a579fc9aed3af38f4892bdcc7390508adabc30c6af4a6e4f611b0c680e6ac",
- "sha256:14491a910663bf9f13ddf2bc8f60562d6bc5315c1f09c704937ef17293fb85b0",
- "sha256:1cae98a7054b5c9391eb3249b86e0e99ab1e02bb0cc0575da191aedadbdf4384",
- "sha256:2089ed025da3919d2e75a4d963d008330c96751127dd6f73c8dc0c65041b4c26",
- "sha256:2d384f4a127a15ba701207f7639d94106693b6cd64173d6c8988e2c25f3ac2b6",
- "sha256:337d448e5a725bba2d8293c48d9353fc68d0e9e4088d62a9571def317797522b",
- "sha256:399aed636c7d3749bbed55bc907c3288cb43c65c4389964ad5ff849b6370603e",
- "sha256:3b911c2dbd4f423b4c4fcca138cadde747abdb20d196c4a48708b8a2d32b16dd",
- "sha256:3d311bcc4a41408cf5854f06ef2c5cab88f9fded37a3b95936c9879c1640d4c2",
- "sha256:62ae9af2d069ea2698bf536dcfe1e4eed9090211dbaafeeedf5cb6c41b352f66",
- "sha256:66e41db66b47d0d8672d8ed2708ba91b2f2524ece3dee48b5dfb36be8c2f21dc",
- "sha256:675686925a9fb403edba0114db74e741d8181683dcf216be697d208857e04ca8",
- "sha256:7e63cbcf2429a8dbfe48dcc2322d5f2220b77b2e17b7ba023d6166d84655da55",
- "sha256:8a6c688fefb4e1cd56feb6c511984a6c4f7ec7d2a1ff31a10254f3c817054ae4",
- "sha256:8c0ffc886aea5df6a1762d0019e9cb05f825d0eec1f520c51be9d198701daee5",
- "sha256:95cd16d3dee553f882540c1ffe331d085c9e629499ceadfbda4d4fde635f4b7d",
- "sha256:99f748a7e71ff382613b4e1acc0ac83bf7ad167fb3802e35e90d9763daba4d78",
- "sha256:b8c78301cefcf5fd914aad35d3c04c2b21ce8629b5e4f4e45ae6812e461910fa",
- "sha256:c420917b188a5582a56d8b93bdd8e0f6eca08c84ff623a4c16e809152cd35793",
- "sha256:c43866529f2f06fe0edc6246eb4faa34f03fe88b64a0a9a942561c8e22f4b71f",
- "sha256:cab50b8c2250b46fe738c77dbd25ce017d5e6fb35d3407606e7a4180656a5a6a",
- "sha256:cef128cb4d5e0b3493f058f10ce32365972c554572ff821e175dbc6f8ff6924f",
- "sha256:cf16e3cf6c0a5fdd9bc10c21687e19d29ad1fe863372b5543deaec1039581a30",
- "sha256:e56c744aa6ff427a607763346e4170629caf7e48ead6921745986db3692f987f",
- "sha256:e577934fc5f8779c554639376beeaa5657d54349096ef24abe8c74c5d9c117c3",
- "sha256:f2b0fa0c01d8a0c7483afd9f31d7ecf2d71760ca24499c8697aeb5ca37dc090c"
- ],
- "version": "==1.14.0"
- },
- "chardet": {
- "hashes": [
- "sha256:84ab92ed1c4d4f16916e05906b6b75a6c0fb5db821cc65e70cbd64a3e2a5eaae",
- "sha256:fc323ffcaeaed0e0a02bf4d117757b98aed530d9ed4531e3e15460124c106691"
- ],
- "version": "==3.0.4"
- },
- "codecov": {
- "hashes": [
- "sha256:09fb045eb044a619cd2b9dacd7789ae8e322cb7f18196378579fd8d883e6b665",
- "sha256:aeeefa3a03cac8a78e4f988e935b51a4689bb1f17f20d4e827807ee11135f845"
- ],
- "index": "pypi",
- "version": "==2.0.22"
- },
- "commonmark": {
- "hashes": [
- "sha256:452f9dc859be7f06631ddcb328b6919c67984aca654e5fefb3914d54691aed60",
- "sha256:da2f38c92590f83de410ba1a3cbceafbc74fee9def35f9251ba9a971d6d66fd9"
- ],
- "version": "==0.9.1"
- },
- "coverage": {
- "hashes": [
- "sha256:03f630aba2b9b0d69871c2e8d23a69b7fe94a1e2f5f10df5049c0df99db639a0",
- "sha256:046a1a742e66d065d16fb564a26c2a15867f17695e7f3d358d7b1ad8a61bca30",
- "sha256:0a907199566269e1cfa304325cc3b45c72ae341fbb3253ddde19fa820ded7a8b",
- "sha256:165a48268bfb5a77e2d9dbb80de7ea917332a79c7adb747bd005b3a07ff8caf0",
- "sha256:1b60a95fc995649464e0cd48cecc8288bac5f4198f21d04b8229dc4097d76823",
- "sha256:1f66cf263ec77af5b8fe14ef14c5e46e2eb4a795ac495ad7c03adc72ae43fafe",
- "sha256:2e08c32cbede4a29e2a701822291ae2bc9b5220a971bba9d1e7615312efd3037",
- "sha256:3844c3dab800ca8536f75ae89f3cf566848a3eb2af4d9f7b1103b4f4f7a5dad6",
- "sha256:408ce64078398b2ee2ec08199ea3fcf382828d2f8a19c5a5ba2946fe5ddc6c31",
- "sha256:443be7602c790960b9514567917af538cac7807a7c0c0727c4d2bbd4014920fd",
- "sha256:4482f69e0701139d0f2c44f3c395d1d1d37abd81bfafbf9b6efbe2542679d892",
- "sha256:4a8a259bf990044351baf69d3b23e575699dd60b18460c71e81dc565f5819ac1",
- "sha256:513e6526e0082c59a984448f4104c9bf346c2da9961779ede1fc458e8e8a1f78",
- "sha256:5f587dfd83cb669933186661a351ad6fc7166273bc3e3a1531ec5c783d997aac",
- "sha256:62061e87071497951155cbccee487980524d7abea647a1b2a6eb6b9647df9006",
- "sha256:641e329e7f2c01531c45c687efcec8aeca2a78a4ff26d49184dce3d53fc35014",
- "sha256:65a7e00c00472cd0f59ae09d2fb8a8aaae7f4a0cf54b2b74f3138d9f9ceb9cb2",
- "sha256:6ad6ca45e9e92c05295f638e78cd42bfaaf8ee07878c9ed73e93190b26c125f7",
- "sha256:73aa6e86034dad9f00f4bbf5a666a889d17d79db73bc5af04abd6c20a014d9c8",
- "sha256:7c9762f80a25d8d0e4ab3cb1af5d9dffbddb3ee5d21c43e3474c84bf5ff941f7",
- "sha256:85596aa5d9aac1bf39fe39d9fa1051b0f00823982a1de5766e35d495b4a36ca9",
- "sha256:86a0ea78fd851b313b2e712266f663e13b6bc78c2fb260b079e8b67d970474b1",
- "sha256:8a620767b8209f3446197c0e29ba895d75a1e272a36af0786ec70fe7834e4307",
- "sha256:922fb9ef2c67c3ab20e22948dcfd783397e4c043a5c5fa5ff5e9df5529074b0a",
- "sha256:9fad78c13e71546a76c2f8789623eec8e499f8d2d799f4b4547162ce0a4df435",
- "sha256:a37c6233b28e5bc340054cf6170e7090a4e85069513320275a4dc929144dccf0",
- "sha256:c3fc325ce4cbf902d05a80daa47b645d07e796a80682c1c5800d6ac5045193e5",
- "sha256:cda33311cb9fb9323958a69499a667bd728a39a7aa4718d7622597a44c4f1441",
- "sha256:db1d4e38c9b15be1521722e946ee24f6db95b189d1447fa9ff18dd16ba89f732",
- "sha256:eda55e6e9ea258f5e4add23bcf33dc53b2c319e70806e180aecbff8d90ea24de",
- "sha256:f372cdbb240e09ee855735b9d85e7f50730dcfb6296b74b95a3e5dea0615c4c1"
- ],
- "index": "pypi",
- "version": "==5.0.4"
- },
- "coveralls": {
- "hashes": [
- "sha256:41bd57b60321dfd5b56e990ab3f7ed876090691c21a9e3b005e1f6e42e6ba4b9",
- "sha256:d213f5edd49053d03f0db316ccabfe17725f2758147afc9a37eaca9d8e8602b5"
- ],
- "index": "pypi",
- "version": "==2.0.0"
- },
- "cprofilev": {
- "hashes": [
- "sha256:8791748b1f3d3468c2c927c3fd5f905080b84d8f2d217ca764b7d9d7a1fb9a77"
- ],
- "index": "pypi",
- "version": "==1.0.7"
- },
- "cryptography": {
- "hashes": [
- "sha256:0cacd3ef5c604b8e5f59bf2582c076c98a37fe206b31430d0cd08138aff0986e",
- "sha256:192ca04a36852a994ef21df13cca4d822adbbdc9d5009c0f96f1d2929e375d4f",
- "sha256:19ae795137682a9778892fb4390c07811828b173741bce91e30f899424b3934d",
- "sha256:1b9b535d6b55936a79dbe4990b64bb16048f48747c76c29713fea8c50eca2acf",
- "sha256:2a2ad24d43398d89f92209289f15265107928f22a8d10385f70def7a698d6a02",
- "sha256:3be7a5722d5bfe69894d3f7bbed15547b17619f3a88a318aab2e37f457524164",
- "sha256:49870684da168b90110bbaf86140d4681032c5e6a2461adc7afdd93be5634216",
- "sha256:587f98ce27ac4547177a0c6fe0986b8736058daffe9160dcf5f1bd411b7fbaa1",
- "sha256:5aca6f00b2f42546b9bdf11a69f248d1881212ce5b9e2618b04935b87f6f82a1",
- "sha256:6b744039b55988519cc183149cceb573189b3e46e16ccf6f8c46798bb767c9dc",
- "sha256:6b91cab3841b4c7cb70e4db1697c69f036c8bc0a253edc0baa6783154f1301e4",
- "sha256:7598974f6879a338c785c513e7c5a4329fbc58b9f6b9a6305035fca5b1076552",
- "sha256:7a279f33a081d436e90e91d1a7c338553c04e464de1c9302311a5e7e4b746088",
- "sha256:95e1296e0157361fe2f5f0ed307fd31f94b0ca13372e3673fa95095a627636a1",
- "sha256:9fc9da390e98cb6975eadf251b6e5fa088820141061bf041cd5c72deba1dc526",
- "sha256:cc20316e3f5a6b582fc3b029d8dc03aabeb645acfcb7fc1d9848841a33265748",
- "sha256:d1bf5a1a0d60c7f9a78e448adcb99aa101f3f9588b16708044638881be15d6bc",
- "sha256:ed1d0760c7e46436ec90834d6f10477ff09475c692ed1695329d324b2c5cd547",
- "sha256:ef9a55013676907df6c9d7dd943eb1770d014f68beaa7e73250fb43c759f4585"
- ],
- "index": "pypi",
- "version": "==2.9"
- },
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- "index": "pypi",
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- "sha256:b3f43d496c6daba4493e7c431722aeb7dbc6288f52a6e04e7b6023b0247817e6"
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- "version": "==2.23.0"
- },
- "requests-toolbelt": {
- "hashes": [
- "sha256:380606e1d10dc85c3bd47bf5a6095f815ec007be7a8b69c878507068df059e6f",
- "sha256:968089d4584ad4ad7c171454f0a5c6dac23971e9472521ea3b6d49d610aa6fc0"
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- "version": "==0.9.1"
- },
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- "sha256:dc60bb302f48acf6da8ca4444cfa17d52c63c5415302a9ee77b3b21618090521",
- "sha256:dee1bbf3a6c8f73b6b218cb28eed8dd13347ea2f87d572ce19b289d6fd3fbc59"
- ],
- "index": "pypi",
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- },
- "six": {
- "hashes": [
- "sha256:236bdbdce46e6e6a3d61a337c0f8b763ca1e8717c03b369e87a7ec7ce1319c0a",
- "sha256:8f3cd2e254d8f793e7f3d6d9df77b92252b52637291d0f0da013c76ea2724b6c"
- ],
- "version": "==1.14.0"
- },
- "snowballstemmer": {
- "hashes": [
- "sha256:209f257d7533fdb3cb73bdbd24f436239ca3b2fa67d56f6ff88e86be08cc5ef0",
- "sha256:df3bac3df4c2c01363f3dd2cfa78cce2840a79b9f1c2d2de9ce8d31683992f52"
- ],
- "version": "==2.0.0"
- },
- "sphinx": {
- "hashes": [
- "sha256:6a099e6faffdc3ceba99ca8c2d09982d43022245e409249375edf111caf79ed3",
- "sha256:b63a0c879c4ff9a4dffcb05217fa55672ce07abdeb81e33c73303a563f8d8901"
- ],
- "index": "pypi",
- "version": "==3.0.0"
- },
- "sphinx-autobuild": {
- "hashes": [
- "sha256:66388f81884666e3821edbe05dd53a0cfb68093873d17320d0610de8db28c74e",
- "sha256:e60aea0789cab02fa32ee63c7acae5ef41c06f1434d9fd0a74250a61f5994692"
- ],
- "index": "pypi",
- "version": "==0.7.1"
- },
- "sphinxcontrib-applehelp": {
- "hashes": [
- "sha256:806111e5e962be97c29ec4c1e7fe277bfd19e9652fb1a4392105b43e01af885a",
- "sha256:a072735ec80e7675e3f432fcae8610ecf509c5f1869d17e2eecff44389cdbc58"
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- "version": "==1.0.2"
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- "sha256:8165223f9a335cc1af7ffe1ed31d2871f325254c0423bc0c4c7cd1c1e4734a2e",
- "sha256:ff7f1afa7b9642e7060379360a67e9c41e8f3121f2ce9164266f61b9f4b338e4"
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- "version": "==1.0.2"
- },
- "sphinxcontrib-htmlhelp": {
- "hashes": [
- "sha256:3c0bc24a2c41e340ac37c85ced6dafc879ab485c095b1d65d2461ac2f7cca86f",
- "sha256:e8f5bb7e31b2dbb25b9cc435c8ab7a79787ebf7f906155729338f3156d93659b"
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- "version": "==1.0.3"
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- "sphinxcontrib-jsmath": {
- "hashes": [
- "sha256:2ec2eaebfb78f3f2078e73666b1415417a116cc848b72e5172e596c871103178",
- "sha256:a9925e4a4587247ed2191a22df5f6970656cb8ca2bd6284309578f2153e0c4b8"
- ],
- "version": "==1.0.1"
- },
- "sphinxcontrib-napoleon": {
- "hashes": [
- "sha256:407382beed396e9f2d7f3043fad6afda95719204a1e1a231ac865f40abcbfcf8",
- "sha256:711e41a3974bdf110a484aec4c1a556799eb0b3f3b897521a018ad7e2db13fef"
- ],
- "index": "pypi",
- "version": "==0.7"
- },
- "sphinxcontrib-qthelp": {
- "hashes": [
- "sha256:4c33767ee058b70dba89a6fc5c1892c0d57a54be67ddd3e7875a18d14cba5a72",
- "sha256:bd9fc24bcb748a8d51fd4ecaade681350aa63009a347a8c14e637895444dfab6"
- ],
- "version": "==1.0.3"
- },
- "sphinxcontrib-serializinghtml": {
- "hashes": [
- "sha256:eaa0eccc86e982a9b939b2b82d12cc5d013385ba5eadcc7e4fed23f4405f77bc",
- "sha256:f242a81d423f59617a8e5cf16f5d4d74e28ee9a66f9e5b637a18082991db5a9a"
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- },
- "toml": {
- "hashes": [
- "sha256:229f81c57791a41d65e399fc06bf0848bab550a9dfd5ed66df18ce5f05e73d5c",
- "sha256:235682dd292d5899d361a811df37e04a8828a5b1da3115886b73cf81ebc9100e"
- ],
- "version": "==0.10.0"
- },
- "tornado": {
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- "sha256:0fe2d45ba43b00a41cd73f8be321a44936dc1aba233dee979f17a042b83eb6dc",
- "sha256:22aed82c2ea340c3771e3babc5ef220272f6fd06b5108a53b4976d0d722bcd52",
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- "sha256:5618f72e947533832cbc3dec54e1dffc1747a5cb17d1fd91577ed14fa0dc081b",
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- "sha256:c58d56003daf1b616336781b26d184023ea4af13ae143d9dda65e31e534940b9",
- "sha256:c952975c8ba74f546ae6de2e226ab3cc3cc11ae47baf607459a6728585bb542a",
- "sha256:c98232a3ac391f5faea6821b53db8db461157baa788f5d6222a193e9456e1740"
- ],
- "version": "==6.0.4"
- },
- "tox": {
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- "sha256:a4a6689045d93c208d77230853b28058b7513f5123647b67bf012f82fa168303",
- "sha256:b2c4b91c975ea5c11463d9ca00bebf82654439c5df0f614807b9bdec62cc9471"
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- "index": "pypi",
- "version": "==3.14.6"
- },
- "tqdm": {
- "hashes": [
- "sha256:00339634a22c10a7a22476ee946bbde2dbe48d042ded784e4d88e0236eca5d81",
- "sha256:ea9e3fd6bd9a37e8783d75bfc4c1faf3c6813da6bd1c3e776488b41ec683af94"
- ],
- "version": "==4.45.0"
- },
- "twine": {
- "hashes": [
- "sha256:c1af8ca391e43b0a06bbc155f7f67db0bf0d19d284bfc88d1675da497a946124",
- "sha256:d561a5e511f70275e5a485a6275ff61851c16ffcb3a95a602189161112d9f160"
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- "index": "pypi",
- "version": "==3.1.1"
- },
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- "sha256:2f3db8b19923a873b3e5256dc9c2dedfa883e33d87c690d9c7913e1f40673cdc",
- "sha256:87716c2d2a7121198ebcb7ce7cccf6ce5e9ba539041cfbaeecfb641dc0bf6acc"
- ],
- "version": "==1.25.8"
- },
- "virtualenv": {
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- "sha256:6ea131d41c477f6c4b7863948a9a54f7fa196854dbef73efbdff32b509f4d8bf",
- "sha256:94f647e12d1e6ced2541b93215e51752aecbd1bbb18eb1816e2867f7532b1fe1"
- ],
- "version": "==20.0.16"
- },
- "watchdog": {
- "hashes": [
- "sha256:c560efb643faed5ef28784b2245cf8874f939569717a4a12826a173ac644456b"
- ],
- "version": "==0.10.2"
- },
- "wcwidth": {
- "hashes": [
- "sha256:cafe2186b3c009a04067022ce1dcd79cb38d8d65ee4f4791b8888d6599d1bbe1",
- "sha256:ee73862862a156bf77ff92b09034fc4825dd3af9cf81bc5b360668d425f3c5f1"
- ],
- "version": "==0.1.9"
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- "webencodings": {
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- "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78",
- "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"
- ],
- "version": "==0.5.1"
- },
- "wheel": {
- "hashes": [
- "sha256:8788e9155fe14f54164c1b9eb0a319d98ef02c160725587ad60f14ddc57b6f96",
- "sha256:df277cb51e61359aba502208d680f90c0493adec6f0e848af94948778aed386e"
- ],
- "index": "pypi",
- "version": "==0.34.2"
- }
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-}
diff --git a/docs/_templates/side-primary.html b/docs/_templates/side-primary.html
index d7d9ef1..ea93984 100644
--- a/docs/_templates/side-primary.html
+++ b/docs/_templates/side-primary.html
@@ -1,19 +1,29 @@
-  }})
+
-
- Traces is a Python library for unevenly-spaced time series analysis.
+ Traces is a Python library for unevenly-spaced time
+ series analysis.
{{ _('Table Of Contents') }}
diff --git a/docs/_themes/LICENSE b/docs/_themes/LICENSE
index 77f0e21..6660860 100755
--- a/docs/_themes/LICENSE
+++ b/docs/_themes/LICENSE
@@ -1,10 +1,10 @@
-Modifications:
+Modifications:
Copyright (c) 2010 Kenneth Reitz.
Copyright (c) 2016 Mike Stringer.
-Original Project:
+Original Project:
Copyright (c) 2010 by Armin Ronacher.
diff --git a/docs/_themes/ms/layout.html b/docs/_themes/ms/layout.html
index 4d67ec1..6ace260 100755
--- a/docs/_themes/ms/layout.html
+++ b/docs/_themes/ms/layout.html
@@ -1,18 +1,26 @@
-{%- extends "basic/layout.html" %}
-{%- block extrahead %}
- {{ super() }}
- {% if theme_touch_icon %}
-
- {% endif %}
-
+{%- extends "basic/layout.html" %} {%- block extrahead %} {{ super() }} {% if
+theme_touch_icon %}
+
+{% endif %}
+
-
-
-{% endblock %}
-{%- block relbar2 %}{% endblock %}
-{%- block footer %}
-
+
+
+{% endblock %} {%- block relbar2 %}{% endblock %} {%- block footer %}
+
{%- endblock %}
diff --git a/docs/_themes/ms/relations.html b/docs/_themes/ms/relations.html
index 3bbcde8..ea411e0 100755
--- a/docs/_themes/ms/relations.html
+++ b/docs/_themes/ms/relations.html
@@ -1,19 +1,36 @@
Related Topics
diff --git a/docs/_themes/ms/static/flasky.css_t b/docs/_themes/ms/static/flasky.css_t
index 6cc5de0..080295d 100755
--- a/docs/_themes/ms/static/flasky.css_t
+++ b/docs/_themes/ms/static/flasky.css_t
@@ -459,4 +459,4 @@ a:hover tt {
.revsys-inline {
display: none!important;
-}
\ No newline at end of file
+}
diff --git a/docs/_themes/ms/static/small_flask.css b/docs/_themes/ms/static/small_flask.css
index 8d55e95..c8e4969 100755
--- a/docs/_themes/ms/static/small_flask.css
+++ b/docs/_themes/ms/static/small_flask.css
@@ -7,84 +7,86 @@
*/
body {
- margin: 0;
- padding: 20px 30px;
+ margin: 0;
+ padding: 20px 30px;
}
div.documentwrapper {
- float: none;
- background: white;
+ float: none;
+ background: white;
}
div.sphinxsidebar {
- display: block;
- float: none;
- width: 102.5%;
- margin: 50px -30px -20px -30px;
- padding: 10px 20px;
- background: #333;
- color: white;
-}
-
-div.sphinxsidebar h3, div.sphinxsidebar h4, div.sphinxsidebar p,
+ display: block;
+ float: none;
+ width: 102.5%;
+ margin: 50px -30px -20px -30px;
+ padding: 10px 20px;
+ background: #333;
+ color: white;
+}
+
+div.sphinxsidebar h3,
+div.sphinxsidebar h4,
+div.sphinxsidebar p,
div.sphinxsidebar h3 a {
- color: white;
+ color: white;
}
div.sphinxsidebar a {
- color: #aaa;
+ color: #aaa;
}
div.sphinxsidebar p.logo {
- display: none;
+ display: none;
}
div.document {
- width: 100%;
- margin: 0;
+ width: 100%;
+ margin: 0;
}
div.related {
- display: block;
- margin: 0;
- padding: 10px 0 20px 0;
+ display: block;
+ margin: 0;
+ padding: 10px 0 20px 0;
}
div.related ul,
div.related ul li {
- margin: 0;
- padding: 0;
+ margin: 0;
+ padding: 0;
}
div.footer {
- display: none;
+ display: none;
}
div.bodywrapper {
- margin: 0;
+ margin: 0;
}
div.body {
- min-height: 0;
- padding: 0;
+ min-height: 0;
+ padding: 0;
}
.rtd_doc_footer {
- display: none;
+ display: none;
}
.document {
- width: auto;
+ width: auto;
}
.footer {
- width: auto;
+ width: auto;
}
.footer {
- width: auto;
+ width: auto;
}
.github {
- display: none;
-}
\ No newline at end of file
+ display: none;
+}
diff --git a/docs/_themes/ms/theme.conf b/docs/_themes/ms/theme.conf
index 307a1f0..07698f6 100755
--- a/docs/_themes/ms/theme.conf
+++ b/docs/_themes/ms/theme.conf
@@ -4,4 +4,4 @@ stylesheet = flasky.css
pygments_style = flask_theme_support.FlaskyStyle
[options]
-touch_icon =
+touch_icon =
diff --git a/docs/conf.py b/docs/conf.py
index 6ea1049..2c6259c 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -1,4 +1,3 @@
-# -*- coding: utf-8 -*-
#
# traces documentation build configuration file, created by
# sphinx-quickstart
@@ -16,48 +15,48 @@
# directory, add these directories to sys.path here. If the directory
# is relative to the documentation root, use os.path.abspath to make
# it absolute, like shown here.
+import datetime
import os
import sys
-import datetime
-sys.path.insert(0, os.path.abspath('..'))
+
+sys.path.insert(0, os.path.abspath(".."))
sys.path.append(os.path.abspath("_themes"))
-import traces
-from recommonmark.parser import CommonMarkParser
+from recommonmark.parser import CommonMarkParser # noqa: E402
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = [
- 'sphinx.ext.autodoc',
- 'sphinx.ext.mathjax',
- 'sphinx.ext.viewcode',
- 'sphinxcontrib.napoleon',
+ "sphinx.ext.autodoc",
+ "sphinx.ext.mathjax",
+ "sphinx.ext.viewcode",
+ "sphinxcontrib.napoleon",
]
# Add any paths that contain templates here, relative to this directory.
-templates_path = ['_templates']
+templates_path = ["_templates"]
# The suffix(es) of source filenames. You can specify multiple suffix
# as a list of string:
source_parsers = {
- '.md': CommonMarkParser,
+ ".md": CommonMarkParser,
}
-source_suffix = ['.rst', '.md']
+source_suffix = [".rst", ".md"]
# The master toctree document.
-master_doc = 'index'
+master_doc = "index"
# General information about the project.
-project = u'traces'
-copyright = u'2016-{}, Mike Stringer'.format(datetime.date.today().year)
-author = u'Mike Stringer'
+project = "traces"
+copyright = f"2016-{datetime.date.today().year}, Mike Stringer" # noqa: A001
+author = "Mike Stringer"
# The version info for the project you're documenting, acts as
# replacement for |version| and |release|, also used in various other
# places throughout the built documents. The short X.Y version:
-version = u'0.6.0'
+version = "0.6.0"
# The full version, including alpha/beta/rc tags:
-release = u'0.6.0'
+release = "0.6.0"
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
@@ -69,30 +68,30 @@
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
# This patterns also effect to html_static_path and html_extra_path
-exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
+exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"]
# The name of the Pygments (syntax highlighting) style to use.
-pygments_style = 'sphinx'
+pygments_style = "sphinx"
# If true, `todo` and `todoList` produce output, else they produce nothing.
todo_include_todos = False
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
-html_theme = 'ms'
+html_theme = "ms"
# Add any paths that contain custom themes here, relative to this directory.
-html_theme_path = ['_themes']
+html_theme_path = ["_themes"]
# The name of an image file (relative to this directory) to use as a favicon of
# the docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
# pixels large.
-html_favicon = '_static/img/favicon.ico'
+html_favicon = "_static/img/favicon.ico"
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
-html_static_path = ['_static']
+html_static_path = ["_static"]
# If true, SmartyPants will be used to convert quotes and dashes to
# typographically correct entities.
@@ -100,14 +99,14 @@
# Custom sidebar templates, maps document names to template names.
html_sidebars = {
- '**': ['side-primary.html'],
+ "**": ["side-primary.html"],
}
# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True.
html_show_copyright = True
# Output file base name for HTML help builder.
-htmlhelp_basename = 'tracesdoc'
+htmlhelp_basename = "tracesdoc"
latex_elements = {}
@@ -115,22 +114,30 @@
# start file, target name, title, author, documentclass [howto,
# manual, or own class]).
latex_documents = [
- (master_doc, 'traces.tex', u'traces Documentation',
- u'Mike Stringer', 'manual'),
+ (
+ master_doc,
+ "traces.tex",
+ "traces Documentation",
+ "Mike Stringer",
+ "manual",
+ ),
]
# One entry per manual page. List of tuples
# (source start file, name, description, authors, manual section).
-man_pages = [
- (master_doc, 'traces', u'traces Documentation',
- [author], 1)
-]
+man_pages = [(master_doc, "traces", "traces Documentation", [author], 1)]
# Grouping the document tree into Texinfo files. List of tuples
# (source start file, target name, title, author,
# dir menu entry, description, category)
texinfo_documents = [
- (master_doc, 'traces', u'traces Documentation',
- author, 'traces', 'One line description of project.',
- 'Miscellaneous'),
+ (
+ master_doc,
+ "traces",
+ "traces Documentation",
+ author,
+ "traces",
+ "One line description of project.",
+ "Miscellaneous",
+ ),
]
diff --git a/docs/index.rst b/docs/index.rst
index a43d3a6..7db8193 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -34,7 +34,7 @@ To install traces, run this command in your terminal:
.. code:: bash
$ pip install traces
-
+
Quickstart: using traces
------------------------
@@ -99,7 +99,7 @@ one ``TimeSeries`` where the each value is a list of all lights.
We also applied a ``sum`` operation to the list of states to get the
``TimeSeries`` of the number of lights that are on.
-
+
.. figure:: _static/img/count.svg
:alt: many light switch count
@@ -120,7 +120,7 @@ that can be used to get summary metrics such as the mean or quantiles.
It's flexible
+++++++++++++
-
+
The measurements points (keys) in a ``TimeSeries`` can be in any units as
long as they can be ordered. The values can be anything.
@@ -137,7 +137,7 @@ of a grocery basket by the number of minutes within a shopping trip.
To learn more, check the :ref:`examples ` and the detailed
:ref:`reference `.
-
+
More info
---------
diff --git a/examples/helloworld.py b/examples/helloworld.py
index 48b900c..e5d8e56 100644
--- a/examples/helloworld.py
+++ b/examples/helloworld.py
@@ -1,6 +1,5 @@
-import sys
import glob
-
+import sys
from datetime import datetime, timedelta
import traces
@@ -11,14 +10,14 @@ def parse_iso_datetime(value):
return datetime.strptime(value, "%Y-%m-%dT%H:%M:%S")
-def read_all(pattern='data/lightbulb-*.csv'):
+def read_all(pattern="data/lightbulb-*.csv"):
"""Read all of the CSVs in a directory matching the filename pattern
as TimeSeries.
"""
result = []
for filename in glob.iglob(pattern):
- print('reading', filename, file=sys.stderr)
+ print("reading", filename, file=sys.stderr)
ts = traces.TimeSeries.from_csv(
filename,
time_column=0,
@@ -54,7 +53,7 @@ def read_all(pattern='data/lightbulb-*.csv'):
# look at the typical number of lights on during business hours
# (8am-6pm) for each day in january
-for t in datetime_range(datetime(2016, 1, 1), datetime(2016, 2, 1), 'days'):
+for t in datetime_range(datetime(2016, 1, 1), datetime(2016, 2, 1), "days"):
biz_start = t + timedelta(hours=8)
biz_end = t + timedelta(hours=18)
histogram = total_watts.distribution(start=biz_start, end=biz_end)
diff --git a/examples/stackystack.py b/examples/stackystack.py
index 3783955..cf32b7d 100644
--- a/examples/stackystack.py
+++ b/examples/stackystack.py
@@ -1,7 +1,7 @@
-import traces
-import random
import datetime
-from infinity import inf
+import random
+
+import traces
def average(values):
@@ -15,13 +15,12 @@ def average(values):
class Test(traces.TimeSeries):
-
def stack(self, duration, start_times, operation):
ts_list = []
for start in start_times:
end = start + duration
ts = traces.TimeSeries()
- for t0, dur, value in self.iterperiods(start, end):
+ for t0, _dur, value in self.iterperiods(start, end):
offset = t0 - start
if isinstance(offset, datetime.timedelta):
offset = offset.total_seconds()
@@ -33,7 +32,7 @@ def stack(self, duration, start_times, operation):
def xmprint(ts):
for t, v in ts:
# print t.isoformat(), v
- print(t, v)
+ print((t, v))
def generate_ts(n_days):
@@ -55,7 +54,7 @@ def generate_ts(n_days):
def hour_mask(n_days, hours):
start_time = datetime.datetime(2016, 1, 1)
- domain = TimeSeries(default=False)
+ domain = traces.TimeSeries(default=False)
for day in range(n_days):
start = start_time + datetime.timedelta(days=day, hours=hours)
end = start + datetime.timedelta(hours=1)
@@ -87,26 +86,28 @@ def hour_mask(n_days, hours):
stack = ts.stack(datetime.timedelta(days=1), start_times, average)
xmprint(stack)
-print ''
+print("")
for hour in range(24):
mask = hour_mask(n_days, hour)
- print hour * 60 * 60, ts.distribution(mask=mask).mean()
-print (hour + 1) * 60 * 60, ts.distribution(mask=mask).mean()
+ print(hour * 60 * 60, ts.distribution(mask=mask).mean())
+print((hour + 1) * 60 * 60, ts.distribution(mask=mask).mean())
-print ''
+print("")
unit = 60 * 60
start = 0
end = start + unit
while end <= 24 * 60 * 60:
value = stack.mean(start, end)
- print start, value
+ print(start, value)
start += unit
end += unit
-print start, value
+print(start, value)
-print ''
+print("")
-for t, v in sorted(stack.moving_average(60 * 60, 60 * 60, 0, 24 * 60 * 60).items()):
- print t, v
+for t, v in sorted(
+ stack.moving_average(60 * 60, 60 * 60, 0, 24 * 60 * 60).items()
+):
+ print(t, v)
diff --git a/examples/timing.py b/examples/timing.py
index 760c977..5e68619 100644
--- a/examples/timing.py
+++ b/examples/timing.py
@@ -1,15 +1,15 @@
-import time
-import pprint
import collections
-import sys
import functools
+import sys
+import time
TIMING_RESULTS = collections.defaultdict(list)
-class timer(object):
+class timer:
def __call__(self, function):
"""Turn the object into a decorator"""
+
@functools.wraps(function)
def wrapper(*arg, **kwargs):
t1 = time.clock()
@@ -17,8 +17,10 @@ def wrapper(*arg, **kwargs):
t2 = time.clock()
TIMING_RESULTS[function.__name__].append(t2 - t1)
return result
+
return wrapper
+
def print_results(*args):
args = sorted([f.__name__ for f in args])
focus = set(args)
@@ -28,8 +30,8 @@ def print_results(*args):
continue
n = 0
sum_ = 0
- min_ = float('inf')
- max_ = float('-inf')
+ min_ = float("inf")
+ max_ = float("-inf")
for dt in timing_results:
n += 1
sum_ += dt
@@ -38,29 +40,28 @@ def print_results(*args):
if dt > max_:
max_ = dt
avg = float(sum_) / n
- msg = '{}: n={} avg={} min={} max={}'.format(
- name, n, avg, min_, max_,
- )
+ msg = f"{name}: n={n} avg={avg} min={min_} max={max_}"
result[name] = {
- 'n': n,
- 'avg': avg,
- 'min': min_,
- 'max': min_,
+ "n": n,
+ "avg": avg,
+ "min": min_,
+ "max": min_,
}
for i, name_a in enumerate(args):
for j in range(i):
name_b = args[j]
- ratio = result[name_a]['min'] / result[name_b]['min']
+ ratio = result[name_a]["min"] / result[name_b]["min"]
if ratio <= 1:
- msg = '%s is %.1fx faster than %s' % (name_a, 1 / ratio, name_b)
+ msg = f"{name_a} is {1 / ratio:.1f}x faster than {name_b}"
else:
- msg = '%s is %.1fx faster than %s' % (name_b, ratio, name_a)
- print >> sys.stderr, msg
-
+ msg = f"{name_b} is {ratio:.1f}x faster than {name_a}"
+ print(msg, file=sys.stderr)
+
return result
-
+
+
def timing_loop(n, mod=1000):
for index, i in enumerate(range(n)):
if not index % mod:
- print >> sys.stderr, 'iteration %i' % index
+ print("iteration %i" % index, file=sys.stderr)
yield i
diff --git a/mkdocs.yml b/mkdocs.yml
index 2516c95..8373982 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -15,9 +15,9 @@ plugins:
- mkdocstrings:
handlers:
python:
- setup_commands:
- - import sys
- - sys.path.append('../')
+ setup_commands:
+ - import sys
+ - sys.path.append('../')
theme:
name: material
feature:
diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 0000000..1c12658
--- /dev/null
+++ b/poetry.lock
@@ -0,0 +1,1942 @@
+# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
+
+[[package]]
+name = "babel"
+version = "2.14.0"
+description = "Internationalization utilities"
+optional = false
+python-versions = ">=3.7"
+files = [
+ {file = "Babel-2.14.0-py3-none-any.whl", hash = "sha256:efb1a25b7118e67ce3a259bed20545c29cb68be8ad2c784c83689981b7a57287"},
+ {file = "Babel-2.14.0.tar.gz", hash = "sha256:6919867db036398ba21eb5c7a0f6b28ab8cbc3ae7a73a44ebe34ae74a4e7d363"},
+]
+
+[package.extras]
+dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
+
+[[package]]
+name = "cachetools"
+version = "5.3.2"
+description = "Extensible memoizing collections and decorators"
+optional = false
+python-versions = ">=3.7"
+files = [
+ {file = "cachetools-5.3.2-py3-none-any.whl", hash = "sha256:861f35a13a451f94e301ce2bec7cac63e881232ccce7ed67fab9b5df4d3beaa1"},
+ {file = "cachetools-5.3.2.tar.gz", hash = "sha256:086ee420196f7b2ab9ca2db2520aca326318b68fe5ba8bc4d49cca91add450f2"},
+]
+
+[[package]]
+name = "certifi"
+version = "2024.2.2"
+description = "Python package for providing Mozilla's CA Bundle."
+optional = false
+python-versions = ">=3.6"
+files = [
+ {file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"},
+ {file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"},
+]
+
+[[package]]
+name = "cfgv"
+version = "3.4.0"
+description = "Validate configuration and produce human readable error messages."
+optional = false
+python-versions = ">=3.8"
+files = [
+ {file = "cfgv-3.4.0-py2.py3-none-any.whl", hash = "sha256:b7265b1f29fd3316bfcd2b330d63d024f2bfd8bcb8b0272f8e19a504856c48f9"},
+ {file = "cfgv-3.4.0.tar.gz", hash = "sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560"},
+]
+
+[[package]]
+name = "chardet"
+version = "5.2.0"
+description = "Universal encoding detector for Python 3"
+optional = false
+python-versions = ">=3.7"
+files = [
+ {file = "chardet-5.2.0-py3-none-any.whl", hash = "sha256:e1cf59446890a00105fe7b7912492ea04b6e6f06d4b742b2c788469e34c82970"},
+ {file = "chardet-5.2.0.tar.gz", hash = "sha256:1b3b6ff479a8c414bc3fa2c0852995695c4a026dcd6d0633b2dd092ca39c1cf7"},
+]
+
+[[package]]
+name = "charset-normalizer"
+version = "3.3.2"
+description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
+optional = false
+python-versions = ">=3.7.0"
+files = [
+ {file = "charset-normalizer-3.3.2.tar.gz", hash = "sha256:f30c3cb33b24454a82faecaf01b19c18562b1e89558fb6c56de4d9118a032fd5"},
+ {file = "charset_normalizer-3.3.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:25baf083bf6f6b341f4121c2f3c548875ee6f5339300e08be3f2b2ba1721cdd3"},
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+
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+description = "Backport of pathlib-compatible object wrapper for zip files"
+optional = false
+python-versions = ">=3.8"
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+testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = ">=3.9,<4.0"
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diff --git a/pyproject.toml b/pyproject.toml
index bc4dabb..e5e7549 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -11,7 +11,9 @@ packages = [
]
[tool.poetry.dependencies]
-python = ">=3.8,<4.0"
+python = ">=3.9,<4.0"
+infinity = "^1.5"
+sortedcontainers = "^2.4.0"
[tool.poetry.group.dev.dependencies]
pytest = "^7.2.0"
@@ -19,6 +21,12 @@ pytest-cov = "^4.0.0"
mypy = "^1.5.1"
pre-commit = "^3.4.0"
tox = "^4.11.1"
+numpy = "^1.26.3"
+pandas = "^2.2.0"
+scipy = "^1.12.0"
+matplotlib = "^3.8.2"
+pytest-mpl = "^0.16.1"
+pyarrow = "^15.0.0"
[tool.poetry.group.docs.dependencies]
mkdocs = "^1.4.2"
@@ -44,7 +52,7 @@ testpaths = ["tests"]
[tool.ruff]
target-version = "py37"
-line-length = 120
+line-length = 80
fix = true
select = [
# flake8-2020
@@ -83,6 +91,10 @@ ignore = [
"E501",
# DoNotAssignLambda
"E731",
+ # Non-cryptographic random usage
+ "S311",
+ # Class attribute shadowing a Python builtin
+ "A003",
]
[tool.ruff.format]
@@ -95,6 +107,6 @@ skip_empty = true
branch = true
source = ["traces"]
-
[tool.ruff.per-file-ignores]
"tests/*" = ["S101"]
+"__init__.py" = ["F401"]
diff --git a/setup.cfg b/setup.cfg
index ad07026..a389edb 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -20,4 +20,3 @@ universal = 1
[flake8]
exclude = docs
-
diff --git a/setup.py b/setup.py
deleted file mode 100644
index d4f1efd..0000000
--- a/setup.py
+++ /dev/null
@@ -1,83 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-import os
-from setuptools import setup
-
-
-def read_init(key):
- """Parse the package __init__ file to find a variable so that it's not
- in multiple places.
-
- """
- filename = os.path.join("traces", "__init__.py")
- result = None
- with open(filename) as stream:
- for line in stream:
- if key in line:
- result = line.split('=')[-1].strip().replace("'", "")
-
- # throw error if version isn't in __init__ file
- if result is None:
- raise ValueError('must define %s in %s' % (key, filename))
-
- return result
-
-
-def read_author():
- return read_init('author')
-
-
-def read_author_email():
- return read_init('email')
-
-
-def read_dependencies(filename):
- """Read in the dependencies from the virtualenv requirements file.
-
- """
- dependencies = []
- filepath = os.path.join('requirements', filename)
- with open(filepath, 'r') as stream:
- for line in stream:
- package = line.strip().split('#')[0].strip()
- if package and package.split(' ')[0] != '-r':
- dependencies.append(package)
- return dependencies
-
-
-with open("README.md", "r") as fh:
- long_description = fh.read()
-
-setup(
- name='traces',
- version='0.6.0',
- description="A library for unevenly-spaced time series analysis.",
- long_description=long_description,
- long_description_content_type="text/markdown",
- author=read_author(),
- author_email=read_author_email(),
- url='https://github.com/datascopeanalytics/traces',
- packages=['traces'],
- package_dir={'traces': 'traces'},
- include_package_data=True,
- install_requires=read_dependencies('python.txt'),
- extras_require={
- 'test': read_dependencies('python-test.txt'),
- 'doc': read_dependencies('python-doc.txt'),
- 'dev': read_dependencies('python-dev.txt'),
- 'pandas': ['pandas'],
- },
- license="MIT license",
- zip_safe=False,
- keywords='traces',
- classifiers=[
- 'Development Status :: 4 - Beta',
- 'Intended Audience :: Developers',
- 'License :: OSI Approved :: MIT License',
- 'Natural Language :: English',
- 'Programming Language :: Python :: 3.6',
- 'Programming Language :: Python :: 3.7',
- 'Programming Language :: Python :: 3.8',
- ],
- test_suite='nose.collector',
-)
diff --git a/tests/.coveragerc b/tests/.coveragerc
index 40b3f80..a852abd 100644
--- a/tests/.coveragerc
+++ b/tests/.coveragerc
@@ -1,3 +1,3 @@
# .coveragerc
[report]
-show_missing = True
\ No newline at end of file
+show_missing = True
diff --git a/tests/__init__.py b/tests/__init__.py
index 40a96af..e69de29 100644
--- a/tests/__init__.py
+++ b/tests/__init__.py
@@ -1 +0,0 @@
-# -*- coding: utf-8 -*-
diff --git a/tests/test_compact.py b/tests/test_compact.py
index 7782d0c..8e07e11 100644
--- a/tests/test_compact.py
+++ b/tests/test_compact.py
@@ -1,13 +1,11 @@
-import traces
-
import random
+import traces
+
def test_compact():
-
# since this is random, do it a bunch of times
- for n_trial in range(100):
-
+ for _n_trial in range(100):
# make two time series, one compact and one not
test_ts = traces.TimeSeries()
compact_ts = traces.TimeSeries()
diff --git a/tests/test_distribution.py b/tests/test_distribution.py
index 3693ae9..8ac8c44 100644
--- a/tests/test_distribution.py
+++ b/tests/test_distribution.py
@@ -1,10 +1,11 @@
import datetime
-import nose
-from traces import TimeSeries, Histogram
+import pytest
+
+from traces import Histogram, TimeSeries
-def test_distribution():
+def test_distribution():
start = datetime.datetime(2015, 3, 1)
# v. simple
@@ -17,7 +18,9 @@ def test_distribution():
# not normalized
distribution = a.distribution(
- start=start, end=end, normalized=False,
+ start=start,
+ end=end,
+ normalized=False,
)
assert distribution[0] == 24 * 60 * 60 * 2 # two days
assert distribution[1] == 24 * 60 * 60 * 2
@@ -29,7 +32,6 @@ def test_distribution():
def test_default_values():
-
# v. simple
a = TimeSeries()
a.set(datetime.datetime(2015, 3, 1), 1)
@@ -47,7 +49,6 @@ def test_default_values():
def test_mask():
-
start = datetime.datetime(2015, 3, 1)
# v. simple
@@ -64,21 +65,25 @@ def test_mask():
# not normalized
distribution = a.distribution(
- start=start, end=end, normalized=False, mask=mask,
+ start=start,
+ end=end,
+ normalized=False,
+ mask=mask,
)
assert distribution[0] == 24 * 60 * 60 # one day
assert distribution[1] == 24 * 60 * 60
# normalized
distribution = a.distribution(
- start=start, end=end, mask=mask,
+ start=start,
+ end=end,
+ mask=mask,
)
assert distribution[0] == 0.5
assert distribution[1] == 0.5
def test_integer_times():
-
# v. simple
a = TimeSeries()
a[0] = 1
@@ -94,17 +99,16 @@ def test_integer_times():
def test_distribution_set():
time_series = TimeSeries()
- time_series[1.2] = {'broccoli'}
- time_series[1.4] = {'broccoli', 'orange'}
- time_series[1.7] = {'broccoli', 'orange', 'banana'}
- time_series[2.2] = {'orange', 'banana'}
- time_series[3.5] = {'orange', 'banana', 'beets'}
+ time_series[1.2] = {"broccoli"}
+ time_series[1.4] = {"broccoli", "orange"}
+ time_series[1.7] = {"broccoli", "orange", "banana"}
+ time_series[2.2] = {"orange", "banana"}
+ time_series[3.5] = {"orange", "banana", "beets"}
# TODO: How to convert the set into multiple ts?
def test_distribution_empty():
-
ts = TimeSeries()
mask = TimeSeries(default=0)
@@ -113,7 +117,7 @@ def test_distribution_empty():
# distribution with default args and no default value on empty
# TimeSeries doesn't know what to do
- nose.tools.assert_raises(KeyError, ts.distribution)
+ pytest.raises(KeyError, ts.distribution)
# distribution with start and end, but no default value on empty
# TimeSeries doesn't know what to do
@@ -121,13 +125,12 @@ def test_distribution_empty():
# no matter what is passed in to distribution, if the default
# value is not set on an empty TimeSeries this should be an error
- ts.distribution(mask=mask) == Histogram.from_dict({None: 1.0})
- # nose.tools.assert_raises(KeyError, ts.distribution, mask=mask)
+ assert ts.distribution(mask=mask) == Histogram.from_dict({None: 1.0})
ts = TimeSeries(default=0)
# no mask or start/end on empty TimeSeries, don't know what to do
- nose.tools.assert_raises(KeyError, ts.distribution)
+ pytest.raises(KeyError, ts.distribution)
# start and end or mask given, is fine
distribution = ts.distribution(0, 10)
@@ -139,10 +142,10 @@ def test_distribution_empty():
# empty mask
mask = TimeSeries(default=0)
- with nose.tools.assert_raises(ValueError):
+ with pytest.raises(ValueError):
ts.distribution(mask=mask)
- with nose.tools.assert_raises(ValueError):
+ with pytest.raises(ValueError):
ts.distribution(start=0, end=2, mask=mask)
@@ -153,5 +156,5 @@ def test_none_handling():
ts[3] = (2, 0)
# print(ts.distribution(normalized=False))
- assert(ts.distribution()[(0, 1)] == 0.5)
- assert(ts.distribution()[(None, 0)] == 0.5)
+ assert ts.distribution()[(0, 1)] == 0.5
+ assert ts.distribution()[(None, 0)] == 0.5
diff --git a/tests/test_docs.py b/tests/test_docs.py
index 7be7acb..38831d9 100644
--- a/tests/test_docs.py
+++ b/tests/test_docs.py
@@ -1,20 +1,21 @@
-import traces
from datetime import datetime
+import traces
+
def test_quickstart():
time_series = traces.TimeSeries()
- time_series[datetime(2042, 2, 1, 6, 0, 0)] = 0 # 6:00:00am
- time_series[datetime(2042, 2, 1, 7, 45, 56)] = 1 # 7:45:56am
- time_series[datetime(2042, 2, 1, 8, 51, 42)] = 0 # 8:51:42am
- time_series[datetime(2042, 2, 1, 12, 3, 56)] = 1 # 12:03:56am
- time_series[datetime(2042, 2, 1, 12, 7, 13)] = 0 # 12:07:13am
+ time_series[datetime(2042, 2, 1, 6, 0, 0)] = 0 # 6:00:00am
+ time_series[datetime(2042, 2, 1, 7, 45, 56)] = 1 # 7:45:56am
+ time_series[datetime(2042, 2, 1, 8, 51, 42)] = 0 # 8:51:42am
+ time_series[datetime(2042, 2, 1, 12, 3, 56)] = 1 # 12:03:56am
+ time_series[datetime(2042, 2, 1, 12, 7, 13)] = 0 # 12:07:13am
- assert time_series[datetime(2042, 2, 1, 11, 0, 0)] == 0
+ assert time_series[datetime(2042, 2, 1, 11, 0, 0)] == 0
distribution = time_series.distribution(
- start=datetime(2042, 2, 1, 6, 0, 0), # 6:00am
- end=datetime(2042, 2, 1, 13, 0, 0) # 1:00pm
+ start=datetime(2042, 2, 1, 6, 0, 0), # 6:00am
+ end=datetime(2042, 2, 1, 13, 0, 0), # 1:00pm
)
assert distribution[1] == 0.16440476190476191
@@ -22,13 +23,13 @@ def test_quickstart():
def test_reference():
cart = traces.TimeSeries()
- cart[1.2] = {'broccoli'}
- cart[1.7] = {'broccoli', 'apple'}
- cart[2.2] = {'apple'}
- cart[3.5] = {'apple', 'beets'}
+ cart[1.2] = {"broccoli"}
+ cart[1.7] = {"broccoli", "apple"}
+ cart[2.2] = {"apple"}
+ cart[3.5] = {"apple", "beets"}
- assert cart[2] == {'broccoli', 'apple'}
+ assert cart[2] == {"broccoli", "apple"}
assert cart[-1] is None
cart = traces.TimeSeries(default=set())
- assert cart[-1] == set([])
+ assert cart[-1] == set()
diff --git a/tests/test_eventseries.py b/tests/test_eventseries.py
index 10915c2..20f20c3 100644
--- a/tests/test_eventseries.py
+++ b/tests/test_eventseries.py
@@ -1,6 +1,7 @@
-from traces import EventSeries, TimeSeries
import pandas as pd
+from traces import EventSeries, TimeSeries
+
def test_init_data():
es = EventSeries([0, 0, 6, 8.7, 10])
@@ -14,31 +15,41 @@ def test_init_data():
def test_cumsum():
# Test with basic timestamp data
- data = ['2018-10-15T16:45:01', '2019-04-16T13:08:26',
- '2019-02-22T12:05:08', '2019-04-16T13:09:06',
- '2019-04-16T13:09:13', '2019-04-16T13:09:28',
- '2019-04-16T13:09:29', '2019-04-16T13:10:20',
- '2019-04-16T13:10:30', '2019-03-08T16:46:48',
- '2019-04-16T13:09:29', '2019-04-16T13:10:20']
+ data = [
+ "2018-10-15T16:45:01",
+ "2019-04-16T13:08:26",
+ "2019-02-22T12:05:08",
+ "2019-04-16T13:09:06",
+ "2019-04-16T13:09:13",
+ "2019-04-16T13:09:28",
+ "2019-04-16T13:09:29",
+ "2019-04-16T13:10:20",
+ "2019-04-16T13:10:30",
+ "2019-03-08T16:46:48",
+ "2019-04-16T13:09:29",
+ "2019-04-16T13:10:20",
+ ]
es = EventSeries(pd.to_datetime(data))
- ref = {pd.Timestamp('2018-10-15 16:45:01'): 1,
- pd.Timestamp('2019-02-22 12:05:08'): 2,
- pd.Timestamp('2019-03-08 16:46:48'): 3,
- pd.Timestamp('2019-04-16 13:08:26'): 4,
- pd.Timestamp('2019-04-16 13:09:06'): 5,
- pd.Timestamp('2019-04-16 13:09:13'): 6,
- pd.Timestamp('2019-04-16 13:09:28'): 7,
- pd.Timestamp('2019-04-16 13:09:29'): 9,
- pd.Timestamp('2019-04-16 13:10:20'): 11,
- pd.Timestamp('2019-04-16 13:10:30'): 12}
+ ref = {
+ pd.Timestamp("2018-10-15 16:45:01"): 1,
+ pd.Timestamp("2019-02-22 12:05:08"): 2,
+ pd.Timestamp("2019-03-08 16:46:48"): 3,
+ pd.Timestamp("2019-04-16 13:08:26"): 4,
+ pd.Timestamp("2019-04-16 13:09:06"): 5,
+ pd.Timestamp("2019-04-16 13:09:13"): 6,
+ pd.Timestamp("2019-04-16 13:09:28"): 7,
+ pd.Timestamp("2019-04-16 13:09:29"): 9,
+ pd.Timestamp("2019-04-16 13:10:20"): 11,
+ pd.Timestamp("2019-04-16 13:10:30"): 12,
+ }
reference = TimeSeries(ref, default=0)
assert es.cumsum() == reference
# check default is 0
- assert es.cumsum()[pd.Timestamp('2015-01-01')] == 0
+ assert es.cumsum()[pd.Timestamp("2015-01-01")] == 0
# Test Empty Series
es = EventSeries()
@@ -46,52 +57,97 @@ def test_cumsum():
def test_events_between():
- data = ['2018-10-15T16:45:01', '2019-04-16T13:08:26',
- '2019-02-22T12:05:08', '2019-04-16T13:09:06',
- '2019-04-16T13:09:13', '2019-04-16T13:09:28',
- '2019-04-16T13:09:29', '2019-04-16T13:10:20',
- '2019-04-16T13:10:30', '2019-03-08T16:46:48',
- '2019-04-16T13:09:29', '2019-04-16T13:10:20']
+ data = [
+ "2018-10-15T16:45:01",
+ "2019-04-16T13:08:26",
+ "2019-02-22T12:05:08",
+ "2019-04-16T13:09:06",
+ "2019-04-16T13:09:13",
+ "2019-04-16T13:09:28",
+ "2019-04-16T13:09:29",
+ "2019-04-16T13:10:20",
+ "2019-04-16T13:10:30",
+ "2019-03-08T16:46:48",
+ "2019-04-16T13:09:29",
+ "2019-04-16T13:10:20",
+ ]
es = EventSeries(pd.to_datetime(data))
- assert es.events_between(pd.Timestamp(
- '2018-01-01'), pd.Timestamp('2020-01-01')) == 12
- assert es.events_between(pd.Timestamp(
- '2018-01-01'), pd.Timestamp('2019-01-01')) == 1
- assert es.events_between(pd.Timestamp(
- '2020-01-01'), pd.Timestamp('2020-02-01')) == 0
- assert es.events_between(pd.Timestamp(
- '2016-01-01'), pd.Timestamp('2017-02-01')) == 0
+ assert (
+ es.events_between(
+ pd.Timestamp("2018-01-01"), pd.Timestamp("2020-01-01")
+ )
+ == 12
+ )
+ assert (
+ es.events_between(
+ pd.Timestamp("2018-01-01"), pd.Timestamp("2019-01-01")
+ )
+ == 1
+ )
+ assert (
+ es.events_between(
+ pd.Timestamp("2020-01-01"), pd.Timestamp("2020-02-01")
+ )
+ == 0
+ )
+ assert (
+ es.events_between(
+ pd.Timestamp("2016-01-01"), pd.Timestamp("2017-02-01")
+ )
+ == 0
+ )
# Test closed boundaries on end points
# left
- assert es.events_between(pd.Timestamp('2018-10-15 16:45:01'),
- pd.Timestamp('2019-04-15 12:00:00')) == 3
+ assert (
+ es.events_between(
+ pd.Timestamp("2018-10-15 16:45:01"),
+ pd.Timestamp("2019-04-15 12:00:00"),
+ )
+ == 3
+ )
# right
- assert es.events_between(pd.Timestamp('2019-02-28 12:00:00'),
- pd.Timestamp('2019-04-16 13:10:20')) == 9
+ assert (
+ es.events_between(
+ pd.Timestamp("2019-02-28 12:00:00"),
+ pd.Timestamp("2019-04-16 13:10:20"),
+ )
+ == 9
+ )
# both
- assert es.events_between(pd.Timestamp('2019-02-22 12:05:08'),
- pd.Timestamp('2019-04-16 13:10:20')) == 10
+ assert (
+ es.events_between(
+ pd.Timestamp("2019-02-22 12:05:08"),
+ pd.Timestamp("2019-04-16 13:10:20"),
+ )
+ == 10
+ )
def test_count_active():
es_open = EventSeries(
- ['08:00', '09:00', '13:00', '07:00', '06:30', '13:00'])
- es_closed = EventSeries(['08:00', '08:30', '12:00', '12:00', '12:00'])
+ ["08:00", "09:00", "13:00", "07:00", "06:30", "13:00"]
+ )
+ es_closed = EventSeries(["08:00", "08:30", "12:00", "12:00", "12:00"])
ts = EventSeries.count_active(es_open, es_closed)
- assert ts['06:30'] == 1
- assert ts['07:00'] == 2
- assert ts['08:00'] == 2
- assert ts['12:00'] == -1
- assert ts['13:00'] == 1
+ assert ts["06:30"] == 1
+ assert ts["07:00"] == 2
+ assert ts["08:00"] == 2
+ assert ts["12:00"] == -1
+ assert ts["13:00"] == 1
def test_time_lag():
- data = ['2019-02-01', '2019-02-28',
- '2019-02-22', '2019-02-16',
- '2019-02-26', '2019-02-16']
+ data = [
+ "2019-02-01",
+ "2019-02-28",
+ "2019-02-22",
+ "2019-02-16",
+ "2019-02-26",
+ "2019-02-16",
+ ]
es = EventSeries(pd.to_datetime(data))
time_lag = es.time_lag()
@@ -99,4 +155,4 @@ def test_time_lag():
assert time_lag[1] == pd.Timedelta(days=0)
# Make sure we got the right shape
- assert time_lag.shape[0] == len(data)-1
+ assert time_lag.shape[0] == len(data) - 1
diff --git a/tests/test_histogram.py b/tests/test_histogram.py
index e72a2e9..a17d14a 100644
--- a/tests/test_histogram.py
+++ b/tests/test_histogram.py
@@ -1,13 +1,13 @@
-import nose
+import contextlib
-import traces
-
-from scipy import stats
import numpy
+import pytest
+from scipy import stats
+import traces
-def test_quantiles():
+def test_quantiles():
data = [15, 15, 20, 20, 20, 35, 35, 40, 40, 50, 50]
histogram = traces.Histogram(data)
@@ -15,15 +15,15 @@ def test_quantiles():
alpha = 0.5
q_list = [0.05, 0.25, 0.5, 0.75, 0.95]
q_values = histogram.quantiles(q_list, alpha=alpha, smallest_count=1)
- reference = \
- stats.mstats.mquantiles(data, prob=q_list, alphap=0.5, betap=0.5)
+ reference = stats.mstats.mquantiles(
+ data, prob=q_list, alphap=0.5, betap=0.5
+ )
for i, j in zip(q_values, reference):
assert i == j
def test_normalize():
-
data = [15, 15, 20, 20, 20, 35, 35, 40, 40, 50, 50]
histogram = traces.Histogram(data)
normalized = histogram.normalized()
@@ -32,7 +32,6 @@ def test_normalize():
def _test_statistics(normalized):
-
data_list = [
[1, 2, 3, 5, 6, 7],
[1, 2, 3, 5, 6],
@@ -42,7 +41,6 @@ def _test_statistics(normalized):
]
for data in data_list:
-
histogram = traces.Histogram(data)
if normalized:
histogram = histogram.normalized()
@@ -50,34 +48,29 @@ def _test_statistics(normalized):
else:
n = len(data)
- nose.tools.assert_almost_equal(histogram.total(), n)
- nose.tools.assert_almost_equal(histogram.mean(), numpy.mean(data))
- nose.tools.assert_almost_equal(histogram.variance(), numpy.var(data))
- nose.tools.assert_almost_equal(
- histogram.standard_deviation(),
- numpy.std(data),
- )
- nose.tools.assert_almost_equal(histogram.max(), numpy.max(data))
- nose.tools.assert_almost_equal(histogram.min(), numpy.min(data))
- nose.tools.assert_almost_equal(
- histogram.quantile(0.5),
- numpy.median(data),
- )
+ assert histogram.total() == pytest.approx(n)
+ assert histogram.mean() == pytest.approx(numpy.mean(data))
+ assert histogram.variance() == pytest.approx(numpy.var(data))
+ assert histogram.standard_deviation() == pytest.approx(numpy.std(data))
+ assert histogram.max() == pytest.approx(numpy.max(data))
+ assert histogram.min() == pytest.approx(numpy.min(data))
+ assert histogram.quantile(0.5) == pytest.approx(numpy.median(data))
q_list = [0.001, 0.01, 0.05, 0.25, 0.5, 0.75, 0.95, 0.99, 0.999]
# linear interpolation
result = histogram.quantiles(q_list)
reference = stats.mstats.mquantiles(
- data, prob=q_list, alphap=0.5, betap=0.5,
+ data,
+ prob=q_list,
+ alphap=0.5,
+ betap=0.5,
)
for i, j in zip(result, reference):
- nose.tools.assert_almost_equal(i, j)
+ assert i == pytest.approx(j)
# make sure ot throw an error for bad quantile values
- try:
+ with contextlib.suppress(ValueError):
histogram.quantile(-1)
- except ValueError:
- pass
def test_statistics():
@@ -89,7 +82,6 @@ def test_normalized_statistics():
def test_quantile_interpolation():
-
data = [1, 1, 1, 2, 3, 5, 6, 7]
histogram = traces.Histogram(data)
normalized = histogram.normalized()
@@ -100,32 +92,37 @@ def test_quantile_interpolation():
result = histogram.quantiles(q_list, alpha=0, smallest_count=1)
answer = [1.0, 1.0, 1.0, 1.0, 2.5, 5.5, 7.0, 7.0, 7.0]
for i, j in zip(result, answer):
- nose.tools.assert_almost_equal(i, j)
+ assert i == pytest.approx(j)
# same thing with normalized
result = normalized.quantiles(
- q_list, alpha=0, smallest_count=1.0 / len(data))
+ q_list, alpha=0, smallest_count=1.0 / len(data)
+ )
for i, j in zip(result, answer):
- nose.tools.assert_almost_equal(i, j)
+ assert i == pytest.approx(j)
# now do the linear interpolation method
result = histogram.quantiles(q_list, alpha=0.5, smallest_count=1)
answer = stats.mstats.mquantiles(
- data, prob=q_list, alphap=0.5, betap=0.5,
+ data,
+ prob=q_list,
+ alphap=0.5,
+ betap=0.5,
)
for i, j in zip(result, answer):
- nose.tools.assert_almost_equal(i, j)
+ assert i == pytest.approx(j)
# same thing with normalized
result = normalized.quantiles(
- q_list, alpha=0.5, smallest_count=1.0 / len(data),
+ q_list,
+ alpha=0.5,
+ smallest_count=1.0 / len(data),
)
for i, j in zip(result, answer):
- nose.tools.assert_almost_equal(i, j)
+ assert i == pytest.approx(j)
def test_addition():
-
hist_a = traces.Histogram([1, 1, 1, 2, 3, 5])
hist_b = traces.Histogram([0, 0, 1, 2, 2])
@@ -134,7 +131,6 @@ def test_addition():
def test_minmax_with_zeros():
-
histogram = traces.Histogram()
histogram[0] += 0
@@ -142,29 +138,28 @@ def test_minmax_with_zeros():
histogram[2] += 1
histogram[3] += 0
- nose.tools.eq_(histogram.min(), 1)
- nose.tools.eq_(histogram.max(), 2)
+ assert histogram.min() == 1
+ assert histogram.max() == 2
def test_histogram_stats_with_nones():
-
histogram = traces.Histogram()
- nose.tools.eq_(histogram.mean(), None)
- nose.tools.eq_(histogram.variance(), None)
- nose.tools.eq_(histogram.standard_deviation(), None)
- nose.tools.eq_(histogram.min(), None)
- nose.tools.eq_(histogram.max(), None)
- nose.tools.eq_(histogram.median(), None)
+ assert histogram.mean() is None
+ assert histogram.variance() is None
+ assert histogram.standard_deviation() is None
+ assert histogram.min() is None
+ assert histogram.max() is None
+ assert histogram.median() is None
histogram = traces.Histogram.from_dict({None: 1}, key=hash)
- nose.tools.eq_(histogram.mean(), None)
- nose.tools.eq_(histogram.variance(), None)
- nose.tools.eq_(histogram.standard_deviation(), None)
- nose.tools.eq_(histogram.min(), None)
- nose.tools.eq_(histogram.max(), None)
- nose.tools.eq_(histogram.median(), None)
+ assert histogram.mean() is None
+ assert histogram.variance() is None
+ assert histogram.standard_deviation() is None
+ assert histogram.min() is None
+ assert histogram.max() is None
+ assert histogram.median() is None
ts = traces.TimeSeries()
ts[0] = None
@@ -175,4 +170,4 @@ def test_histogram_stats_with_nones():
ts[10] = None
histogram = ts.distribution(start=0, end=10)
- nose.tools.eq_(histogram.mean(), 6)
+ assert histogram.mean() == 6
diff --git a/tests/test_iterators.py b/tests/test_iterators.py
index 8fa6c0e..d3a2c0b 100644
--- a/tests/test_iterators.py
+++ b/tests/test_iterators.py
@@ -1,16 +1,13 @@
import datetime
-import random
-import sys
import pprint
+import random
-from infinity import inf
-import nose
+import pytest
from traces import TimeSeries
def test_iterintervals():
-
ts = TimeSeries()
ts.set(datetime.datetime(2015, 3, 1), 1)
ts.set(datetime.datetime(2015, 3, 2), 0)
@@ -19,16 +16,15 @@ def test_iterintervals():
answer = [(1, 0), (0, 1), (1, 2)]
result = []
- for (t0, v0), (t1, v1) in ts.iterintervals():
+ for (_t0, v0), (_t1, v1) in ts.iterintervals():
result.append((v0, v1))
assert answer == result
def test_iterperiods():
-
# timeseries with no points raises a KeyError
ts = TimeSeries()
- with nose.tools.assert_raises(KeyError):
+ with pytest.raises(KeyError):
next(ts.iterperiods())
ts.set(datetime.datetime(2015, 3, 1), 1)
@@ -39,11 +35,11 @@ def test_iterperiods():
answer = [
(datetime.datetime(2015, 3, 1), datetime.datetime(2015, 3, 2), 1),
(datetime.datetime(2015, 3, 2), datetime.datetime(2015, 3, 3), 0),
- (datetime.datetime(2015, 3, 3), datetime.datetime(2015, 3, 4), 1)]
+ (datetime.datetime(2015, 3, 3), datetime.datetime(2015, 3, 4), 1),
+ ]
result = []
- for (t0, t1, v0) in ts.iterperiods(
- start=datetime.datetime(2015, 3, 1),
- end=datetime.datetime(2015, 3, 4)
+ for t0, t1, v0 in ts.iterperiods(
+ start=datetime.datetime(2015, 3, 1), end=datetime.datetime(2015, 3, 4)
):
result.append((t0, t1, v0))
assert answer == result
@@ -53,32 +49,31 @@ def test_iterperiods():
(datetime.datetime(2015, 3, 3), datetime.datetime(2015, 3, 4), 1),
]
result = []
- for (t0, t1, v0) in ts.iterperiods(
- start=datetime.datetime(2015, 3, 1),
- end=datetime.datetime(2015, 3, 4),
- value=1,
+ for t0, t1, v0 in ts.iterperiods(
+ start=datetime.datetime(2015, 3, 1),
+ end=datetime.datetime(2015, 3, 4),
+ value=1,
):
result.append((t0, t1, v0))
assert answer == result
- def filter(t0, t1, value):
- return True if not value else False
+ def filter_function(t0, t1, value):
+ return bool(not value)
answer = [
(datetime.datetime(2015, 3, 2), datetime.datetime(2015, 3, 3), 0),
]
result = []
- for (t0, t1, v0) in ts.iterperiods(
- start=datetime.datetime(2015, 3, 1),
- end=datetime.datetime(2015, 3, 4),
- value=filter,
+ for t0, t1, v0 in ts.iterperiods(
+ start=datetime.datetime(2015, 3, 1),
+ end=datetime.datetime(2015, 3, 4),
+ value=filter_function,
):
result.append((t0, t1, v0))
assert answer == result
def test_slice():
-
ts = TimeSeries(default=1)
ts[0] = 1
ts[1] = 5
@@ -90,14 +85,14 @@ def test_slice():
assert list(ts.slice(-1, 1).items()) == [(-1, 1), (0, 1), (1, 5)]
assert list(ts.slice(-1, 0.5).items()) == [(-1, 1), (0, 1), (0.5, 1)]
- nose.tools.assert_raises(ValueError, ts.slice, 2.5, 0)
+ pytest.raises(ValueError, ts.slice, 2.5, 0)
def make_random_timeseries():
length = random.randint(1, 10)
result = TimeSeries()
t = 0
- for i in range(length):
+ for _i in range(length):
t += random.randint(0, 5)
x = random.randint(0, 5)
result[t] = x
@@ -105,26 +100,23 @@ def make_random_timeseries():
def test_merge():
-
# since this is random, do it a bunch of times
- for n_trial in range(1000):
-
+ for _n_trial in range(1000):
# make a list of TimeSeries that is anywhere from 0 to 5
# long. Each TimeSeries is of random length between 0 and 20,
# with random time points and random values.
ts_list = []
- for i in range(random.randint(1, 5)):
+ for _i in range(random.randint(1, 5)):
ts_list.append(make_random_timeseries())
method_a = list(TimeSeries.merge(ts_list, compact=False))
method_b = list(TimeSeries.iter_merge(ts_list))
- msg = '%s != %s' % (pprint.pformat(method_a), pprint.pformat(method_b))
+ msg = f"{pprint.pformat(method_a)} != {pprint.pformat(method_b)}"
assert method_a == method_b, msg
def test_single_merges():
-
# a single empty time series
ts = TimeSeries()
assert TimeSeries.merge([ts]) == TimeSeries(default=[None])
@@ -132,8 +124,7 @@ def test_single_merges():
# multiple empty time series
ts_a = TimeSeries()
ts_b = TimeSeries()
- assert TimeSeries.merge([ts_a, ts_b]) == \
- TimeSeries(default=[None, None])
+ assert TimeSeries.merge([ts_a, ts_b]) == TimeSeries(default=[None, None])
# test a single time series with only one measurement
ts = TimeSeries()
diff --git a/tests/test_methods.py b/tests/test_methods.py
index 29b32ca..f80ef3d 100644
--- a/tests/test_methods.py
+++ b/tests/test_methods.py
@@ -1,9 +1,10 @@
import datetime
-import nose
-import traces
-import pandas as pd
+
import numpy as np
+import pandas as pd
+import pytest
+import traces
key_list = [
datetime.datetime(2012, 1, 7),
@@ -14,21 +15,21 @@
numeric_types = {
int: [1, 2, 3, 0],
float: [1.0, 2.0, 3.0, 0.0],
- bool: [True, False, True, False]
+ bool: [True, False, True, False],
}
non_numeric_hashable_types = {
- str: ['a', 'b', 'c', ''],
- tuple: [('a', 1), ('b', 2), ('c', 3), ()],
+ str: ["a", "b", "c", ""],
+ tuple: [("a", 1), ("b", 2), ("c", 3), ()],
}
unhashable_types = {
list: [[1, 1], [2, 2], [3, 3], []],
- dict: [{'a': 1}, {'b': 2}, {'c': 3}, {}],
+ dict: [{"a": 1}, {"b": 2}, {"c": 3}, {}],
set: [{1}, {1, 2}, {1, 2, 3}, set()],
}
all_types = dict(
- list(numeric_types.items()) +
- list(non_numeric_hashable_types.items()) +
- list(unhashable_types.items())
+ list(numeric_types.items())
+ + list(non_numeric_hashable_types.items())
+ + list(unhashable_types.items())
)
@@ -46,7 +47,6 @@ def frange(x, y, jump):
def test_mean():
-
# numeric hashable types should work
for type_, value_list in numeric_types.items():
ts = _make_ts(type_, key_list, value_list)
@@ -58,51 +58,43 @@ def test_mean():
for type_, value_list in non_numeric_hashable_types.items():
ts = _make_ts(type_, key_list, value_list)
ts.distribution(key_list[0], key_list[-1])
- nose.tools.assert_raises(TypeError, ts.mean, key_list[0], key_list[1])
+ pytest.raises(TypeError, ts.mean, key_list[0], key_list[1])
# non-numeric unhashable types should raise error on distribution
# and mean
for type_, value_list in unhashable_types.items():
ts = _make_ts(type_, key_list, value_list)
- nose.tools.assert_raises(TypeError, ts.distribution,
- key_list[0], key_list[1])
- nose.tools.assert_raises(TypeError, ts.mean,
- key_list[0], key_list[1])
+ pytest.raises(TypeError, ts.distribution, key_list[0], key_list[1])
+ pytest.raises(TypeError, ts.mean, key_list[0], key_list[1])
def test_mean_interpolate():
-
ts = traces.TimeSeries()
ts[0] = 0
ts[1] = 0
ts[3] = 20
- nose.tools.assert_almost_equal(
- ts.mean(0, 2, interpolate='linear'),
- 2.5,
- )
- assert ts.mean(0, 2, interpolate='linear') == 2.5
+ assert ts.mean(0, 2, interpolate="linear") == pytest.approx(2.5)
+ assert ts.mean(0, 2, interpolate="linear") == 2.5
mask = traces.TimeSeries(default=False)
mask[0] = True
mask[0.5] = False
mask[1] = True
mask[3] = False
- nose.tools.assert_almost_equal(
- ts.mean(0, 2, mask=mask, interpolate='linear'),
- 10/3.0,
- )
- nose.tools.assert_almost_equal(
- ts.mean(0, 3, mask=mask, interpolate='linear'),
- 8.0,
+
+ assert ts.mean(0, 2, mask=mask, interpolate="linear") == pytest.approx(
+ 10 / 3.0
)
+ assert ts.mean(0, 3, mask=mask, interpolate="linear") == pytest.approx(8.0)
+
def test_sample():
time_list = [
datetime.datetime(2016, 1, 1, 1, 1, 2),
datetime.datetime(2016, 1, 1, 1, 1, 3),
datetime.datetime(2016, 1, 1, 1, 1, 8),
- datetime.datetime(2016, 1, 1, 1, 1, 10)
+ datetime.datetime(2016, 1, 1, 1, 1, 10),
]
ts = _make_ts(int, time_list, [1, 2, 3, 0])
@@ -111,37 +103,39 @@ def curr_time(i):
# Check first arguments
assert dict(ts.sample(1, time_list[0], time_list[-1])) == {
- curr_time(i): ts[curr_time(i)] for i in range(2, 11)}
+ curr_time(i): ts[curr_time(i)] for i in range(2, 11)
+ }
assert dict(ts.sample(2, time_list[0], time_list[-1])) == {
- curr_time(i): ts[curr_time(i)] for i in range(2, 11, 2)}
+ curr_time(i): ts[curr_time(i)] for i in range(2, 11, 2)
+ }
- nose.tools.assert_raises(
- ValueError, ts.sample, -1, time_list[0], time_list[-1])
- nose.tools.assert_raises(ValueError, ts.sample,
- 20, time_list[0], time_list[-1])
+ pytest.raises(ValueError, ts.sample, -1, time_list[0], time_list[-1])
+ pytest.raises(ValueError, ts.sample, 20, time_list[0], time_list[-1])
# Check second and third arguments
- nose.tools.assert_raises(ValueError, ts.sample,
- 1, time_list[3], time_list[0])
+ pytest.raises(ValueError, ts.sample, 1, time_list[3], time_list[0])
assert dict(ts.sample(1, curr_time(5), curr_time(10))) == {
- curr_time(i): ts[curr_time(i)] for i in range(5, 11)}
+ curr_time(i): ts[curr_time(i)] for i in range(5, 11)
+ }
assert dict(ts.sample(1, curr_time(2), curr_time(5))) == {
- curr_time(i): ts[curr_time(i)] for i in range(2, 6)}
+ curr_time(i): ts[curr_time(i)] for i in range(2, 6)
+ }
assert dict(ts.sample(1, curr_time(0), curr_time(13))) == {
- curr_time(i): ts[curr_time(i)] for i in range(0, 14)}
+ curr_time(i): ts[curr_time(i)] for i in range(0, 14)
+ }
# Check using int
ts = traces.TimeSeries([[1, 2], [2, 3], [6, 1], [8, 4]])
- assert dict(ts.sample(1, 1, 8)) == {
- i: ts[i] for i in range(1, 9)}
+ assert dict(ts.sample(1, 1, 8)) == {i: ts[i] for i in range(1, 9)}
assert dict(ts.sample(0.5, 1, 8)) == {
- 1 + i / 2.: ts[1 + i / 2.] for i in range(0, 15)}
- nose.tools.assert_raises(ValueError, ts.sample, 0.5, -traces.inf, 8)
- nose.tools.assert_raises(ValueError, ts.sample, 0.5, 1, traces.inf)
+ 1 + i / 2.0: ts[1 + i / 2.0] for i in range(0, 15)
+ }
+ pytest.raises(ValueError, ts.sample, 0.5, -traces.inf, 8)
+ pytest.raises(ValueError, ts.sample, 0.5, 1, traces.inf)
# Test pandas compatibility
pd_ts = pd.Series(dict(ts.sample(1, 1, 8)))
@@ -154,7 +148,7 @@ def test_moving_average():
datetime.datetime(2016, 1, 1, 1, 1, 2),
datetime.datetime(2016, 1, 1, 1, 1, 3),
datetime.datetime(2016, 1, 1, 1, 1, 8),
- datetime.datetime(2016, 1, 1, 1, 1, 10)
+ datetime.datetime(2016, 1, 1, 1, 1, 10),
]
ts = _make_ts(int, time_list, [1, 2, 3, 0])
@@ -168,10 +162,10 @@ def build_answer(step, interval):
try:
answer[t] = ts.mean(t - step, t + step)
except TypeError as e:
- if 'NoneType' in str(e):
+ if "NoneType" in str(e):
answer[t] = None
else:
- raise e
+ raise
return answer
# Check first arguments
@@ -180,63 +174,51 @@ def build_answer(step, interval):
sampling_period=1,
window_size=2,
start=time_list[0],
- end=time_list[-1]
- ))
+ end=time_list[-1],
+ )
+ )
assert output == build_answer(datetime.timedelta(seconds=1), (2, 11))
output = dict(ts.moving_average(1, 0.2, time_list[0], time_list[-1]))
- assert output == build_answer(
- datetime.timedelta(seconds=0.1), (2, 11)
- )
+ assert output == build_answer(datetime.timedelta(seconds=0.1), (2, 11))
- nose.tools.assert_raises(
- ValueError, ts.moving_average, 1, -1, time_list[0], time_list[-1])
+ pytest.raises(
+ ValueError, ts.moving_average, 1, -1, time_list[0], time_list[-1]
+ )
# Check second arguments
output = dict(ts.moving_average(2, 1, time_list[0], time_list[-1]))
- assert output == build_answer(
- datetime.timedelta(seconds=.5), (2, 11, 2))
+ assert output == build_answer(datetime.timedelta(seconds=0.5), (2, 11, 2))
- nose.tools.assert_raises(
- ValueError,
- ts.moving_average,
- -1, 1, time_list[0], time_list[-1]
+ pytest.raises(
+ ValueError, ts.moving_average, -1, 1, time_list[0], time_list[-1]
)
- nose.tools.assert_raises(
- ValueError,
- ts.moving_average,
- 20, 1, time_list[0], time_list[-1]
+ pytest.raises(
+ ValueError, ts.moving_average, 20, 1, time_list[0], time_list[-1]
)
# Check third and fourth arguments
- nose.tools.assert_raises(
- ValueError,
- ts.moving_average,
- 1, 1, time_list[3], time_list[0]
+ pytest.raises(
+ ValueError, ts.moving_average, 1, 1, time_list[3], time_list[0]
)
output = dict(ts.moving_average(1, 2, curr_time(5), curr_time(10)))
- assert output == build_answer(
- datetime.timedelta(seconds=1), (5, 11)
- )
+ assert output == build_answer(datetime.timedelta(seconds=1), (5, 11))
output = dict(ts.moving_average(1, 2, curr_time(2), curr_time(5)))
- assert output == build_answer(
- datetime.timedelta(seconds=1), (2, 6)
- )
+ assert output == build_answer(datetime.timedelta(seconds=1), (2, 6))
output = dict(ts.moving_average(1, 2, curr_time(0), curr_time(13)))
- assert output == build_answer(
- datetime.timedelta(seconds=1), (0, 14)
- )
+ assert output == build_answer(datetime.timedelta(seconds=1), (0, 14))
# Check using int
ts = traces.TimeSeries([[1, 2], [2, 3], [6, 1], [8, 4]])
assert dict(ts.moving_average(1, 2, 2, 8)) == {
- i: ts.mean(i - 1, i + 1) for i in range(2, 9)}
+ i: ts.mean(i - 1, i + 1) for i in range(2, 9)
+ }
assert dict(ts.moving_average(0.5, 2, 2, 8)) == {
- 1 + i / 2.: ts.mean(1 + i / 2. - 1, 1 + i / 2. + 1)
+ 1 + i / 2.0: ts.mean(1 + i / 2.0 - 1, 1 + i / 2.0 + 1)
for i in range(2, 15)
}
@@ -244,22 +226,20 @@ def build_answer(step, interval):
pd_ts = pd.Series(dict(ts.moving_average(1, 2, 0, 8)))
assert all(pd_ts.index[i] == i for i in range(1, 9))
assert np.isnan(pd_ts.values[0])
- assert all(pd_ts.values[i] == ts.mean(i - 1, i + 1)
- for i in range(2, 9))
+ assert all(pd_ts.values[i] == ts.mean(i - 1, i + 1) for i in range(2, 9))
# Test using timedelta as sampling_period
ts = _make_ts(int, time_list, [1, 2, 3, 0])
sampling_period = datetime.timedelta(seconds=1)
output = dict(ts.moving_average(sampling_period))
- answer = build_answer(datetime.timedelta(seconds=1), (2, 11))
+ build_answer(datetime.timedelta(seconds=1), (2, 11))
assert output == build_answer(datetime.timedelta(seconds=1), (2, 11))
def test_to_bool():
-
answer = {}
for type_, value_list in all_types.items():
- answer[type_] = [True if i else False for i in value_list]
+ answer[type_] = [bool(i) for i in value_list]
# numeric hashable types should work
for type_, value_list in all_types.items():
@@ -270,7 +250,6 @@ def test_to_bool():
def test_get_item_by_index():
-
ts = traces.TimeSeries(default=0)
ts[0] = 1
ts[2] = 3
@@ -291,23 +270,23 @@ def test_bin():
end = datetime.datetime(2019, 2, 3, 8, 45, 10)
# make a timeseries
- span = end-start
+ span = end - start
ts = traces.TimeSeries()
- ts[start-span/2] = 2
+ ts[start - span / 2] = 2
ts[start] = 12
- ts[start+span/3] = 5
- ts[end - span/4] = 14
- ts[end+span] = None
- # nose.tools.assert_raises(KeyError, ts.bin, 'days')
+ ts[start + span / 3] = 5
+ ts[end - span / 4] = 14
+ ts[end + span] = None
+ # pytest.raises(KeyError, ts.bin, 'days')
# make a mask
mask = traces.TimeSeries(default=False)
mask[start] = True
mask[end] = False
- mask[start + 3*span/10] = False
- mask[start + 5*span/10] = True
+ mask[start + 3 * span / 10] = False
+ mask[start + 5 * span / 10] = True
- binned = ts.bin('weeks', mask=mask)
+ binned = ts.bin("weeks", mask=mask)
first = binned.peekitem(0)
last = binned.peekitem()
@@ -322,7 +301,6 @@ def test_rebin():
def test_npoints():
-
ts = traces.TimeSeries()
ts[0] = 4
ts[1] = 2
@@ -330,33 +308,40 @@ def test_npoints():
ts[5] = 2
ts[8] = 4
- nose.tools.eq_(ts.n_points(), 5)
- nose.tools.eq_(
- ts.n_points(start=0, end=8, include_start=False, include_end=False), 3)
- nose.tools.eq_(
- ts.n_points(start=0, end=8, include_start=False, include_end=True), 4)
- nose.tools.eq_(
- ts.n_points(start=0, end=8, include_start=True, include_end=False), 4)
- nose.tools.eq_(
- ts.n_points(start=0, end=8, include_start=True, include_end=True), 5)
- nose.tools.eq_(
- ts.n_points(start=1, end=8, include_start=False, include_end=False), 2)
- nose.tools.eq_(
- ts.n_points(start=1, end=8, include_start=False, include_end=True), 3)
- nose.tools.eq_(
- ts.n_points(start=1, end=8, include_start=True, include_end=False), 3)
- nose.tools.eq_(
- ts.n_points(start=1, end=8, include_start=True, include_end=True), 4)
+ assert ts.n_points() == 5
+ assert (
+ ts.n_points(start=0, end=8, include_start=False, include_end=False) == 3
+ )
+ assert (
+ ts.n_points(start=0, end=8, include_start=False, include_end=True) == 4
+ )
+ assert (
+ ts.n_points(start=0, end=8, include_start=True, include_end=False) == 4
+ )
+ assert (
+ ts.n_points(start=0, end=8, include_start=True, include_end=True) == 5
+ )
+ assert (
+ ts.n_points(start=1, end=8, include_start=False, include_end=False) == 2
+ )
+ assert (
+ ts.n_points(start=1, end=8, include_start=False, include_end=True) == 3
+ )
+ assert (
+ ts.n_points(start=1, end=8, include_start=True, include_end=False) == 3
+ )
+ assert (
+ ts.n_points(start=1, end=8, include_start=True, include_end=True) == 4
+ )
ts = traces.TimeSeries()
- nose.tools.eq_(ts.n_points(), 0)
- nose.tools.eq_(ts.n_points(include_start=False), 0)
- nose.tools.eq_(ts.n_points(include_end=False), 0)
+ assert ts.n_points() == 0
+ assert ts.n_points(include_start=False) == 0
+ assert ts.n_points(include_end=False) == 0
def test_radd():
-
ts1 = traces.TimeSeries(default=0)
ts1[0] = 1
ts1[2] = 0
@@ -371,26 +356,22 @@ def test_radd():
ts3 = ts1 + ts2
- nose.tools.eq_(
- list(ts3.items()),
- [(-1, 1), (0, 2), (2, 0), (3, 2), (4, 0)]
- )
+ assert list(ts3.items()) == [(-1, 1), (0, 2), (2, 0), (3, 2), (4, 0)]
+
+ pytest.raises(TypeError, ts3.__radd__, 1)
- nose.tools.assert_raises(TypeError, ts3.__radd__, 1)
def test_repr():
- import traces
- import random
import datetime
+ import traces
+
ts = traces.TimeSeries()
t = datetime.date(2000, 1, 1)
for i in range(1000):
ts[t] = i
t += datetime.timedelta(days=i)
- assert '<...' not in repr(ts)
+ assert "<..." not in repr(ts)
- assert '<...' in str(ts)
-
-
+ assert "<..." in str(ts)
diff --git a/tests/test_missing.py b/tests/test_missing.py
index 8bd0c81..a019d26 100644
--- a/tests/test_missing.py
+++ b/tests/test_missing.py
@@ -1,23 +1,19 @@
-import nose
import traces
-import unittest
# @unittest.skip("not fully fleshed out yet")
def test_missing():
"""example code for dealing with missing datapoints"""
- router_a = traces.TimeSeries([
- (-10, 0), (-7, 1), (-5, None), (0, 3), (1, 3), (5, None)
- ])
+ router_a = traces.TimeSeries(
+ [(-10, 0), (-7, 1), (-5, None), (0, 3), (1, 3), (5, None)]
+ )
assert router_a[-6] == 1
assert router_a[-15] is None
assert not router_a[15]
- router_b = traces.TimeSeries([
- (-8, 0), (-5, 0), (-2, 1), (5, 3)
- ], default=0)
+ router_b = traces.TimeSeries([(-8, 0), (-5, 0), (-2, 1), (5, 3)], default=0)
assert router_b[7] == 3
@@ -26,7 +22,7 @@ def test_missing():
for timestamp in [-10, -1, 10]:
if timestamp < router_b.first_key():
router_b.default = None
- for start, end, value in router_b.iterperiods():
+ for start, end, _value in router_b.iterperiods():
if timestamp >= start and timestamp < end:
router_b[timestamp] = None
if timestamp >= router_b.last_key():
@@ -42,8 +38,7 @@ def test_missing():
# the default here should be the element returned by `count_merge([])`
clients = traces.TimeSeries.merge(
- router_list,
- operation=traces.operations.strict_sum
+ router_list, operation=traces.operations.strict_sum
)
assert clients[-15] is None
assert clients[-6] == 1
@@ -57,8 +52,7 @@ def test_missing():
assert system_uptime[-1] is False
clients = traces.TimeSeries.merge(
- router_list,
- operation=traces.operations.ignorant_sum
+ router_list, operation=traces.operations.ignorant_sum
)
assert clients[-15] == 0
assert clients[-6] == 1
diff --git a/tests/test_operations.py b/tests/test_operations.py
index 3a962bf..471f8d4 100644
--- a/tests/test_operations.py
+++ b/tests/test_operations.py
@@ -1,7 +1,9 @@
import datetime
-import nose
+
+import pytest
+
from traces import TimeSeries
-from traces.decorators import ignorant, strict
+from traces.decorators import ignorant
def test_scalar_ops():
@@ -40,7 +42,6 @@ def test_scalar_ops():
def test_sum():
-
a = TimeSeries()
a.set(datetime.datetime(2015, 3, 1), 1)
a.set(datetime.datetime(2015, 3, 2), 0)
@@ -83,171 +84,19 @@ def test_sum():
assert 0 + a + b == a + b
-def example_dictlike():
-
- # test overwriting keys
- ts = TimeSeries()
- ts[datetime.datetime(2010, 1, 1)] = 5
- ts[datetime.datetime(2010, 1, 2)] = 4
- ts[datetime.datetime(2010, 1, 3)] = 3
- ts[datetime.datetime(2010, 1, 7)] = 2
- ts[datetime.datetime(2010, 1, 4)] = 1
- ts[datetime.datetime(2010, 1, 4)] = 10
- ts[datetime.datetime(2010, 1, 4)] = 5
- ts[datetime.datetime(2010, 1, 1)] = 1
- ts[datetime.datetime(2010, 1, 7)] = 1.2
- ts[datetime.datetime(2010, 1, 8)] = 1.3
- ts[datetime.datetime(2010, 1, 12)] = 1.3
-
- # do some wackiness with a bunch of points
- dt = datetime.datetime(2010, 1, 12)
- for i in range(1000):
- dt += datetime.timedelta(hours=random.random())
- ts[dt] = math.sin(i / float(math.pi))
-
- dt -= datetime.timedelta(hours=500)
- dt -= datetime.timedelta(minutes=30)
- for i in range(1000):
- dt += datetime.timedelta(hours=random.random())
- ts[dt] = math.cos(i / float(math.pi))
-
- # output the time series
- for i, j in ts:
- print(i.isoformat(), j)
-
-
-def example_mean():
-
- ts = TimeSeries()
- ts[datetime.datetime(2010, 1, 1)] = 0
- ts[datetime.datetime(2010, 1, 3, 10)] = 1
- ts[datetime.datetime(2010, 1, 5)] = 0
- ts[datetime.datetime(2010, 1, 8)] = 1
- ts[datetime.datetime(2010, 1, 17)] = 0
- ts[datetime.datetime(2010, 1, 19)] = 1
- ts[datetime.datetime(2010, 1, 23)] = 0
- ts[datetime.datetime(2010, 1, 26)] = 1
- ts[datetime.datetime(2010, 1, 28)] = 0
- ts[datetime.datetime(2010, 1, 31)] = 1
- ts[datetime.datetime(2010, 2, 5)] = 0
-
- for time, value in ts:
- print(time.isoformat(), 0.1 * value + 1.1)
-
- print('')
-
- timestep = {'hours': 25}
- start = datetime.datetime(2010, 1, 1)
- while start <= datetime.datetime(2010, 2, 5):
- end = start + datetime.timedelta(**timestep)
- print(start.isoformat(), ts.mean(start, end))
- start = end
-
- print('')
-
- start = datetime.datetime(2010, 1, 1)
- while start <= datetime.datetime(2010, 2, 5):
- end = start + datetime.timedelta(**timestep)
- print(start.isoformat(), -0.2)
- print(start.isoformat(), 1.2)
- start = end
-
-
-def example_arrow():
-
- ts = TimeSeries()
- ts[arrow.Arrow(2010, 1, 1)] = 0
- ts[arrow.Arrow(2010, 1, 3, 10)] = 1
- ts[arrow.Arrow(2010, 1, 5)] = 0
- ts[arrow.Arrow(2010, 1, 8)] = 1
- ts[arrow.Arrow(2010, 1, 17)] = 0
- ts[arrow.Arrow(2010, 1, 19)] = 1
- ts[arrow.Arrow(2010, 1, 23)] = 0
- ts[arrow.Arrow(2010, 1, 26)] = 1
- ts[arrow.Arrow(2010, 1, 28)] = 0
- ts[arrow.Arrow(2010, 1, 31)] = 1
- ts[arrow.Arrow(2010, 2, 5)] = 0
-
- for time, value in ts:
- print(time.naive.isoformat(), 0.1 * value + 1.1)
-
- print('')
-
- start = arrow.Arrow(2010, 1, 1)
- end = arrow.Arrow(2010, 2, 5)
- unit = {'hours': 25}
- for start, end in span_range(start, end, unit):
- print(start.naive.isoformat(), ts.mean(start, end))
-
- print('')
-
- for start, end in span_range(start, end, unit):
- print(start.naive.isoformat(), -0.2)
- print(start.naive.isoformat(), 1.2)
-
-
-def example_sum():
-
- a = TimeSeries()
- a.set(datetime.datetime(2015, 3, 1), 1)
- a.set(datetime.datetime(2015, 3, 2), 0)
- a.set(datetime.datetime(2015, 3, 3), 1)
- a.set(datetime.datetime(2015, 3, 5), 0)
- a.set(datetime.datetime(2015, 3, 6), 0)
-
- b = TimeSeries()
- b.set(datetime.datetime(2015, 3, 1), 0)
- b.set(datetime.datetime(2015, 3, 2, 12), 1)
- b.set(datetime.datetime(2015, 3, 3, 13, 13), 0)
- b.set(datetime.datetime(2015, 3, 4), 1)
- b.set(datetime.datetime(2015, 3, 5), 0)
- b.set(datetime.datetime(2015, 3, 5, 12), 1)
- b.set(datetime.datetime(2015, 3, 5, 19), 0)
-
- c = TimeSeries()
- c.set(datetime.datetime(2015, 3, 1, 17), 0)
- c.set(datetime.datetime(2015, 3, 1, 21), 1)
- c.set(datetime.datetime(2015, 3, 2, 13, 13), 0)
- c.set(datetime.datetime(2015, 3, 4, 18), 1)
- c.set(datetime.datetime(2015, 3, 5, 4), 0)
-
- # output the three time series
- for i, ts in enumerate([a, b, c]):
-
- for (t0, v0), (t1, v1) in ts.iterintervals(1):
- print(t0.isoformat(), i)
- print(t1.isoformat(), i)
-
- print('')
-
- for (t0, v0), (t1, v1) in ts.iterintervals(0):
- print(t0.isoformat(), i)
- print(t1.isoformat(), i)
-
- print('')
-
- # output the sum
- # for dt, i in sum([a, b, c]):
- # print dt.isoformat(), i
- # print ''
- for dt, i in TimeSeries.merge([a, b, c], operation=sum):
- print(dt.isoformat(), i)
-
-
def test_interpolation():
-
ts = TimeSeries(data=[(0, 0), (1, 2)])
- assert ts.get(0, interpolate='linear') == 0
- assert ts.get(0.25, interpolate='linear') == 0.5
- assert ts.get(0.5, interpolate='linear') == 1.0
- assert ts.get(0.75, interpolate='linear') == 1.5
- assert ts.get(1, interpolate='linear') == 2
+ assert ts.get(0, interpolate="linear") == 0
+ assert ts.get(0.25, interpolate="linear") == 0.5
+ assert ts.get(0.5, interpolate="linear") == 1.0
+ assert ts.get(0.75, interpolate="linear") == 1.5
+ assert ts.get(1, interpolate="linear") == 2
- assert ts.get(-1, interpolate='linear') is None
- assert ts.get(2, interpolate='linear') == 2
+ assert ts.get(-1, interpolate="linear") is None
+ assert ts.get(2, interpolate="linear") == 2
- nose.tools.assert_raises(ValueError, ts.get, 0.5, 'spline')
+ pytest.raises(ValueError, ts.get, 0.5, "spline")
def test_default():
@@ -263,9 +112,8 @@ def test_default():
def test_difference():
-
a = TimeSeries(data=[(0, 0), (2, 2)], default=0)
b = TimeSeries(data=[(1, 1), (3, 2)], default=0)
c = a - b
- nose.tools.eq_(list(c.items()), [(0, 0), (1, -1), (2, 1), (3, 0)])
+ assert list(c.items()) == [(0, 0), (1, -1), (2, 1), (3, 0)]
diff --git a/tests/test_plot.py b/tests/test_plot.py
index 735de6d..b2e6697 100644
--- a/tests/test_plot.py
+++ b/tests/test_plot.py
@@ -1,20 +1,21 @@
-import traces
import pytest
+import traces
+
+
@pytest.mark.mpl_image_compare(
- savefig_kwargs={'bbox_inches': 'tight', 'dpi': 300},
+ savefig_kwargs={"bbox_inches": "tight", "dpi": 300},
remove_text=True,
- style='ggplot',
+ style="ggplot",
tolerance=20,
)
def test_plot():
-
ts = traces.TimeSeries()
ts[0] = 0
ts[1] = 2
ts[3] = 1
ts[5] = 0
-
+
figure, axes = ts.plot()
return figure
@@ -25,21 +26,18 @@ def test_optional_import():
def test_invalid_call():
-
ts = traces.TimeSeries()
ts[0] = 0
ts[1] = 1
-
- ts.plot(interpolate='previous')
- ts.plot(interpolate='linear')
+
+ ts.plot(interpolate="previous")
+ ts.plot(interpolate="linear")
with pytest.raises(ValueError):
- ts.plot(interpolate='yomama')
+ ts.plot(interpolate="yomama")
def test_empty():
-
ts = traces.TimeSeries()
-
+
ts.plot()
-
diff --git a/tests/test_something.py b/tests/test_something.py
index 0ae74c1..53a5295 100644
--- a/tests/test_something.py
+++ b/tests/test_something.py
@@ -1,8 +1,9 @@
+import contextlib
+
import traces
def test_compact():
-
# make a v. simple time series
ts = traces.TimeSeries()
ts[0] = 42
@@ -24,7 +25,6 @@ def test_compact():
def test_remove():
-
# v. simple time series
ts = traces.TimeSeries()
ts[0] = 42
@@ -32,10 +32,8 @@ def test_remove():
# asser that trying to delete a non-existent entry raises a
# KeyError
- try:
+ with contextlib.suppress(KeyError):
del ts[2]
- except KeyError:
- pass
# now delete the measurement at t=1
del ts[1]
@@ -47,7 +45,6 @@ def test_remove():
def test_last_item():
-
# v. simple time series
ts = traces.TimeSeries()
ts[0] = 42
diff --git a/tests/test_traces.py b/tests/test_traces.py
index 3372819..64c33ff 100644
--- a/tests/test_traces.py
+++ b/tests/test_traces.py
@@ -1,10 +1,11 @@
-from datetime import datetime
+import csv
+import os
import pickle
-import nose
+from datetime import datetime
+
+import pytest
from traces import TimeSeries
-import csv
-import os
def test_init_data():
@@ -41,7 +42,6 @@ def test_init_data():
def test_get():
ts = TimeSeries()
- # nose.tools.assert_raises(KeyError, ts.get, 0)
assert ts[0] is None
ts[1.2] = 1
@@ -54,9 +54,7 @@ def test_get():
def test_exists():
- ts = TimeSeries([
- (-5, 0), (0, 23), (5, None)
- ])
+ ts = TimeSeries([(-5, 0), (0, 23), (5, None)])
ts_exists = ts.exists()
assert ts_exists[-10] is False
@@ -110,25 +108,33 @@ def test_set_interval():
tsc = TimeSeries(ts)
ts.set_interval(3, 4, 4)
- assert list(ts.items()) == [(1.2, 1), (2, 5),
- (3, 4), (4, 4), (5, 0), (6, 2)]
+ assert list(ts.items()) == [
+ (1.2, 1),
+ (2, 5),
+ (3, 4),
+ (4, 4),
+ (5, 0),
+ (6, 2),
+ ]
tsc.set_interval(3, 4, 4, compact=True)
assert list(tsc.items()) == [(1.2, 1), (2, 5), (3, 4), (5, 0), (6, 2)]
tsd = TimeSeries()
- nose.tools.assert_raises(ValueError, tsd.set_interval, 4, 4, 4)
+ pytest.raises(ValueError, tsd.set_interval, 4, 4, 4)
def test_set_interval_datetime():
ts = TimeSeries(default=400)
ts[datetime(2012, 1, 4, 12)] = 5
ts[datetime(2012, 1, 9, 18)] = 10
- ts[datetime(2012, 1, 8):datetime(2012, 1, 10)] = 100
+ ts[datetime(2012, 1, 8) : datetime(2012, 1, 10)] = 100
- assert list(ts.items()) == [(datetime(2012, 1, 4, 12, 0), 5),
- (datetime(2012, 1, 8, 0, 0), 100),
- (datetime(2012, 1, 10, 0, 0), 10)]
+ assert list(ts.items()) == [
+ (datetime(2012, 1, 4, 12, 0), 5),
+ (datetime(2012, 1, 8, 0, 0), 100),
+ (datetime(2012, 1, 10, 0, 0), 10),
+ ]
def test_remove_points_from_interval():
@@ -163,7 +169,7 @@ def test_pickle():
ts[1] = True
ts[2] = False
dump_string = pickle.dumps(ts)
- unpickled = pickle.loads(dump_string)
+ unpickled = pickle.loads(dump_string) # noqa: S301
assert unpickled == ts
unpickled[3] = unpickled[1]
@@ -180,16 +186,16 @@ def value_parse(value):
except ValueError:
return None
- filename = 'sample.csv'
- with open(filename, 'w') as csvfile:
+ filename = "sample.csv"
+ with open(filename, "w") as csvfile:
writer = csv.writer(csvfile)
- writer.writerow(['hour', 'value'])
- writer.writerow(['10', '15'])
- writer.writerow(['11', '34'])
- writer.writerow(['12', '19'])
- writer.writerow(['13', 'nan'])
- writer.writerow(['14', '18'])
- writer.writerow(['15', 'nan'])
+ writer.writerow(["hour", "value"])
+ writer.writerow(["10", "15"])
+ writer.writerow(["11", "34"])
+ writer.writerow(["12", "19"])
+ writer.writerow(["13", "nan"])
+ writer.writerow(["14", "18"])
+ writer.writerow(["15", "nan"])
ts = TimeSeries.from_csv(
filename,
@@ -197,7 +203,7 @@ def value_parse(value):
time_transform=time_parse,
value_column=1,
value_transform=value_parse,
- default=None
+ default=None,
)
os.remove(filename)
@@ -206,22 +212,22 @@ def value_parse(value):
assert ts[13.5] is None
histogram = ts.distribution()
- nose.tools.assert_almost_equal(histogram.mean(), (15 + 34 + 19 + 18) / 4.0)
+ assert histogram.mean() == pytest.approx((15 + 34 + 19 + 18) / 4.0)
- filename = 'sample.csv'
- with open(filename, 'w') as csvfile:
+ filename = "sample.csv"
+ with open(filename, "w") as csvfile:
writer = csv.writer(csvfile)
- writer.writerow(['hour', 'value'])
- writer.writerow(['2000-01-01 10:00:00', '15'])
- writer.writerow(['2000-01-01 11:00:00', '34'])
- writer.writerow(['2000-01-01 12:00:00', '19'])
- writer.writerow(['2000-01-01 13:00:00', 'nan'])
- writer.writerow(['2000-01-01 14:00:00', '18'])
- writer.writerow(['2000-01-01 15:00:00', 'nan'])
+ writer.writerow(["hour", "value"])
+ writer.writerow(["2000-01-01 10:00:00", "15"])
+ writer.writerow(["2000-01-01 11:00:00", "34"])
+ writer.writerow(["2000-01-01 12:00:00", "19"])
+ writer.writerow(["2000-01-01 13:00:00", "nan"])
+ writer.writerow(["2000-01-01 14:00:00", "18"])
+ writer.writerow(["2000-01-01 15:00:00", "nan"])
ts = TimeSeries.from_csv(filename)
os.remove(filename)
assert ts[datetime(2000, 1, 1, 9)] is None
- assert ts[datetime(2000, 1, 1, 10, 30)] == '15'
- assert ts[datetime(2000, 1, 1, 20)] == 'nan'
+ assert ts[datetime(2000, 1, 1, 10, 30)] == "15"
+ assert ts[datetime(2000, 1, 1, 20)] == "nan"
diff --git a/tests/test_utils.py b/tests/test_utils.py
index 358e52c..57d107d 100644
--- a/tests/test_utils.py
+++ b/tests/test_utils.py
@@ -1,39 +1,35 @@
-from datetime import timedelta, datetime, date
-import nose
+from datetime import date, datetime, timedelta
+
+import pytest
from infinity import inf
import traces.utils as utils
-
timedelta_list = [
timedelta(hours=1),
timedelta(minutes=2),
timedelta(seconds=5),
- timedelta(milliseconds=5)
+ timedelta(milliseconds=5),
]
-numeric_types = {
- int: [1, 2, 3, 0],
- float: [1.0, 2.0, 3.0, 0.0]
-}
+numeric_types = {int: [1, 2, 3, 0], float: [1.0, 2.0, 3.0, 0.0]}
-non_numeric_types = [
- [2], {'a': 4}, (2, 4), 'df', 'a'
-]
+non_numeric_types = [[2], {"a": 4}, (2, 4), "df", "a"]
def test_duration_to_number():
for tdelta in timedelta_list:
assert utils.duration_to_number(tdelta) == tdelta.total_seconds()
- nose.tools.assert_raises(
- NotImplementedError, utils.duration_to_number, tdelta, 'hours')
+ pytest.raises(
+ NotImplementedError, utils.duration_to_number, tdelta, "hours"
+ )
for _type, item in numeric_types.items():
for num in item:
assert utils.duration_to_number(num) == num
for item in non_numeric_types:
- nose.tools.assert_raises(TypeError, utils.duration_to_number, item)
+ pytest.raises(TypeError, utils.duration_to_number, item)
def test_convert_args_to_list():
@@ -51,7 +47,7 @@ def test_convert_args_to_list():
[[[1, 2], [4, 5], [6, 7]]],
[[(1, 2), (4, 5), (6, 7)]],
[([1, 2], [4, 5], [6, 7])],
- [((1, 2), (4, 5), (6, 7))]
+ [((1, 2), (4, 5), (6, 7))],
]
iterable_inputs_answers = [
@@ -68,94 +64,102 @@ def test_convert_args_to_list():
[[1, 2], [4, 5], [6, 7]],
[[1, 2], [4, 5], [6, 7]],
[[1, 2], [4, 5], [6, 7]],
- [[1, 2], [4, 5], [6, 7]]
+ [[1, 2], [4, 5], [6, 7]],
]
for inputs, answers in zip(iterable_inputs, iterable_inputs_answers):
assert utils.convert_args_to_list(inputs) == answers
- nose.tools.assert_raises(TypeError, utils.convert_args_to_list, [2, 3, 4])
- nose.tools.assert_raises(TypeError, utils.convert_args_to_list, [2])
+ pytest.raises(TypeError, utils.convert_args_to_list, [2, 3, 4])
+ pytest.raises(TypeError, utils.convert_args_to_list, [2])
def test_datetime_range():
# test default options
- dt_range = list(utils.datetime_range(
- datetime(2016, 1, 1), datetime(2016, 2, 1), 'days'))
+ dt_range = list(
+ utils.datetime_range(datetime(2016, 1, 1), datetime(2016, 2, 1), "days")
+ )
assert dt_range[0] == datetime(2016, 1, 1)
assert dt_range[-1] == datetime(2016, 1, 31)
assert dt_range[10] == datetime(2016, 1, 11)
# test non-default options
- dt_range = list(utils.datetime_range(
- datetime(2016, 1, 2),
- datetime(2016, 2, 1),
- 'days', n_units=2, inclusive_end=True))
+ dt_range = list(
+ utils.datetime_range(
+ datetime(2016, 1, 2),
+ datetime(2016, 2, 1),
+ "days",
+ n_units=2,
+ inclusive_end=True,
+ )
+ )
assert dt_range[0] == datetime(2016, 1, 2)
assert dt_range[-1] == datetime(2016, 2, 1)
assert dt_range[10] == datetime(2016, 1, 22)
# test units
- dt_range = list(utils.datetime_range(
- datetime(2016, 1, 1), datetime(2016, 2, 1), 'hours'))
+ dt_range = list(
+ utils.datetime_range(
+ datetime(2016, 1, 1), datetime(2016, 2, 1), "hours"
+ )
+ )
assert dt_range[1] - dt_range[0] == timedelta(hours=1)
- dt_range = list(utils.datetime_range(
- datetime(2016, 1, 1),
- datetime(2016, 2, 1),
- 'minutes',
- n_units=10,
- ))
+ dt_range = list(
+ utils.datetime_range(
+ datetime(2016, 1, 1),
+ datetime(2016, 2, 1),
+ "minutes",
+ n_units=10,
+ )
+ )
assert dt_range[1] - dt_range[0] == timedelta(minutes=10)
# test end < start
- dt_range = list(utils.datetime_range(
- datetime(2016, 2, 1), datetime(2016, 1, 1), 'days'
- ))
+ dt_range = list(
+ utils.datetime_range(datetime(2016, 2, 1), datetime(2016, 1, 1), "days")
+ )
assert dt_range == []
def test_datetime_floor():
# the date here is May 6th, 2016 (week 18)
- nose.tools.eq_(
- utils.datetime_floor(date(2016, 5, 6), 'years'),
- datetime(2016, 1, 1)
+ assert utils.datetime_floor(date(2016, 5, 6), "years") == datetime(
+ 2016, 1, 1
)
- nose.tools.eq_(utils.datetime_floor(inf), inf)
+
+ assert utils.datetime_floor(inf) == inf
test_dt = datetime(2016, 5, 6, 11, 45, 6)
- nose.tools.eq_(
- utils.datetime_floor(test_dt, 'months', n_units=3),
- datetime(2016, 4, 1)
+ assert utils.datetime_floor(test_dt, "months", n_units=3) == datetime(
+ 2016, 4, 1
)
- nose.tools.eq_(
- utils.datetime_floor(test_dt, 'weeks', n_units=3),
- datetime(2016, 4, 18)
- )
- nose.tools.eq_(
- utils.datetime_floor(test_dt, 'hours', n_units=10),
- datetime(2016, 5, 6, 10)
+
+ assert utils.datetime_floor(test_dt, "weeks", n_units=3) == datetime(
+ 2016, 4, 18
)
- nose.tools.eq_(
- utils.datetime_floor(test_dt, 'minutes', n_units=15),
- datetime(2016, 5, 6, 11, 45)
+
+ assert utils.datetime_floor(test_dt, "hours", n_units=10) == datetime(
+ 2016, 5, 6, 10
)
- nose.tools.eq_(
- utils.datetime_floor(test_dt, 'seconds', n_units=30),
- datetime(2016, 5, 6, 11, 45)
+
+ assert utils.datetime_floor(test_dt, "minutes", n_units=15) == datetime(
+ 2016, 5, 6, 11, 45
)
- nose.tools.assert_raises(
- ValueError, utils.datetime_floor, "2016-6-7"
+
+ assert utils.datetime_floor(test_dt, "seconds", n_units=30) == datetime(
+ 2016, 5, 6, 11, 45
)
- nose.tools.assert_raises(
- ValueError, utils.datetime_floor,
- test_dt, 'sleconds', n_units=3
+
+ pytest.raises(ValueError, utils.datetime_floor, "2016-6-7")
+ pytest.raises(
+ ValueError, utils.datetime_floor, test_dt, "sleconds", n_units=3
)
def test_weekday_number():
assert utils.weekday_number(5) == 5
- nose.tools.assert_raises(ValueError, utils.weekday_number, 7)
+ pytest.raises(ValueError, utils.weekday_number, 7)
print(utils.weekday_number("Tuesday"))
assert utils.weekday_number("Tuesday") == 1
- nose.tools.assert_raises(ValueError, utils.weekday_number, 'Mooday')
+ pytest.raises(ValueError, utils.weekday_number, "Mooday")
diff --git a/traces/__init__.py b/traces/__init__.py
index ade756d..86823e3 100644
--- a/traces/__init__.py
+++ b/traces/__init__.py
@@ -1,13 +1,12 @@
-# -*- coding: utf-8 -*-
-
from infinity import inf
+
from traces import decorators, operations
+from .eventseries import EventSeries
from .histogram import Histogram
from .timeseries import TimeSeries
from .utils import datetime_range
-from .eventseries import EventSeries
-__author__ = 'Mike Stringer'
-__email__ = 'mike.stringer@datascopeanalytics.com'
-__version__ = '0.6.0'
+__author__ = "Mike Stringer"
+__email__ = "mike.stringer@datascopeanalytics.com"
+__version__ = "0.6.0"
diff --git a/traces/eventseries.py b/traces/eventseries.py
index 8919f12..9efaaeb 100644
--- a/traces/eventseries.py
+++ b/traces/eventseries.py
@@ -1,8 +1,7 @@
-import sortedcontainers
-import numpy as np
import collections
-from . import TimeSeries
+import numpy as np
+import sortedcontainers
class EventSeries(sortedcontainers.SortedList):
@@ -10,11 +9,13 @@ def __init__(self, data=None):
super().__init__(data)
def cumsum(self):
- '''
+ """
Returns a TimeSeries with each unique time in the EventSeries as an
index point and with the cumulative number of events that have occured
since the earliest time in the EventSeries as the value
- '''
+ """
+ from traces import TimeSeries
+
# Multiple events can happen at the same time so we need to hash them
# as counts
c = collections.Counter(self)
@@ -26,30 +27,30 @@ def cumsum(self):
return TimeSeries(zip(keys, values), default=0)
def events_between(self, start, end):
- '''
+ """
Returns the number of events that occured between `start and `end.
Calculates on a closed interval, so start and end are included in the
range
- '''
+ """
start_idx = self.bisect_left(start)
end_idx = self.bisect_right(end)
return end_idx - start_idx
def time_lag(self):
- '''
+ """
Returns a `np.array` of inter event arrival times. This will only work
for EventSeries of a type that have a minus operation implemented.
- '''
- return (np.array(self[1:]) - np.array(self[0:-1]))
+ """
+ return np.array(self[1:]) - np.array(self[0:-1])
@staticmethod
def count_active(es_open, es_closed):
- '''
+ """
Calculates the running difference from two event series
`es_open` is an EventSeries that adds to the cumulative sum and
`es_closed` is an EventSeries of subtracts from it
Returns a TimeSeries of the number of open cases at any given time,
assuming 0 open cases at the earliest time in either EventSeries
- '''
+ """
return es_open.cumsum() - es_closed.cumsum()
diff --git a/traces/histogram.py b/traces/histogram.py
index 1fedfc2..42bce05 100644
--- a/traces/histogram.py
+++ b/traces/histogram.py
@@ -21,50 +21,44 @@ def from_dict(cls, in_dict, *args, **kwargs):
def __init__(self, data=(), **kwargs):
if "key" in kwargs:
- super(Histogram, self).__init__(kwargs["key"])
+ super().__init__(kwargs["key"])
else:
- super(Histogram, self).__init__()
+ super().__init__()
for datum in data:
self[datum] += 1
def __getitem__(self, key):
try:
- result = super(Histogram, self).__getitem__(key)
+ result = super().__getitem__(key)
except KeyError:
result = 0
except TypeError as error:
-
if "unorderable" in str(error):
- raise UnorderableElements(error)
+ raise UnorderableElements(error) from error
if "unhashable" in str(error):
- msg = "Can't make histogram of unhashable type ({})".format(
- type(key)
- )
- raise UnhashableType(msg)
+ msg = f"Can't make histogram of unhashable type ({type(key)})"
+ raise UnhashableType(msg) from error
- raise error
+ raise
return result
def __setitem__(self, key, value):
try:
- result = super(Histogram, self).__setitem__(key, value)
+ result = super().__setitem__(key, value)
except TypeError as error:
-
if "unorderable" in str(error):
- raise UnorderableElements(error)
+ raise UnorderableElements(error) from error
if "not supported between instances of" in str(error):
- raise UnorderableElements(error)
+ raise UnorderableElements(error) from error
if "unhashable" in str(error):
- msg = "Can't make histogram of unhashable type ({})".format(
- type(key)
- )
- raise UnhashableType(msg)
+ msg = f"Can't make histogram of unhashable type ({type(key)})"
+ raise UnhashableType(msg) from error
- raise error
+ raise
return result
def total(self):
@@ -141,7 +135,7 @@ def min(self, include_zero=False):
if value > 0 or include_zero:
return key
- def _quantile_function(self, alpha=0.5, smallest_count=None):
+ def _quantile_function(self, alpha=0.5, smallest_count=None): # noqa: C901
"""Return a function that returns the quantile values for this
histogram.
@@ -181,9 +175,8 @@ def _quantile_function(self, alpha=0.5, smallest_count=None):
# print ''
def function(q):
-
if q < 0.0 or q > 1.0:
- msg = "invalid quantile {}, need `0 <= q <= 1`".format(q)
+ msg = f"invalid quantile {q}, need `0 <= q <= 1`"
raise ValueError(msg)
elif q < q_min:
q = q_min
@@ -228,7 +221,9 @@ def quantiles(self, q_list, alpha=0.5, smallest_count=None):
def quantile(self, q, alpha=0.5, smallest_count=None):
return self.quantiles(
- [q], alpha=alpha, smallest_count=smallest_count,
+ [q],
+ alpha=alpha,
+ smallest_count=smallest_count,
)[0]
def add(self, other):
diff --git a/traces/plot.py b/traces/plot.py
index 62ffb76..7a1a939 100644
--- a/traces/plot.py
+++ b/traces/plot.py
@@ -58,16 +58,15 @@ def plot(
aspect_ratio=None,
font=None,
):
-
try:
import matplotlib.pyplot as plt
from matplotlib import font_manager
- except ImportError:
+ except ImportError as error:
msg = "need to install matplotlib for `plot` function"
- raise ImportError(msg)
+ raise ImportError(msg) from error
if font is None:
- available_fonts = set(f.name for f in font_manager.fontManager.ttflist)
+ available_fonts = {f.name for f in font_manager.fontManager.ttflist}
for font in FONTS:
if font in available_fonts:
break
@@ -84,14 +83,14 @@ def plot(
try:
drawstyle = INTERPOLATE_DRAWSTYLE[interpolate]
- except KeyError:
- raise ValueError((
- "invalid value for interpolate='{}', "
- "must be in {}"
- ).format(interpolate, set(INTERPOLATE_DRAWSTYLE.keys())))
+ except KeyError as error:
+ msg = (
+ f"invalid value for interpolate='{interpolate}', "
+ f"must be in {set(INTERPOLATE_DRAWSTYLE.keys())}"
+ )
+ raise ValueError(msg) from error
with plt.style.context(PLOT_STYLE):
-
figure, axes = plt.subplots(
figsize=(figure_width, aspect_ratio * figure_width),
)
@@ -102,7 +101,7 @@ def plot(
else:
x, y = [], []
- plot = axes.plot(
+ axes.plot(
x,
y,
linewidth=linewidth,
diff --git a/traces/timeseries.py b/traces/timeseries.py
index ad099fa..2b66883 100644
--- a/traces/timeseries.py
+++ b/traces/timeseries.py
@@ -4,20 +4,21 @@
http://en.wikipedia.org/wiki/Unevenly_spaced_time_series
"""
+
+import contextlib
import csv
import datetime
import itertools
-import pprint
from queue import PriorityQueue
import sortedcontainers
from dateutil.parser import parse as date_parse
from infinity import inf
-from . import histogram, operations, utils, plot
+from . import histogram, operations, plot, utils
-class TimeSeries(object):
+class TimeSeries:
"""A class to help manipulate and analyze time series that are the
result of taking measurements at irregular points in time. For
example, here would be a simple time series that starts at 8am and
@@ -112,24 +113,22 @@ def _get_previous(self, time):
return self.default
else:
msg = (
- "self._d.bisect_right({}) returned a negative value. "
+ f"self._d.bisect_right({time}) returned a negative value. "
"""This "can't" happen: please file an issue at """
"https://github.com/datascopeanalytics/traces/issues"
- ).format(time)
+ )
raise ValueError(msg)
def get(self, time, interpolate="previous"):
- """Get the value of the time series, even in-between measured values.
-
- """
+ """Get the value of the time series, even in-between measured values."""
try:
getter = self.getter_functions[interpolate]
- except KeyError:
+ except KeyError as error:
msg = (
- "unknown value '{}' for interpolate, "
- "valid values are in [{}]"
- ).format(interpolate, ", ".join(self.getter_functions))
- raise ValueError(msg)
+ f"unknown value '{interpolate}' for interpolate, "
+ f"valid values are in [{", ".join(self.getter_functions)}]"
+ )
+ raise ValueError(msg) from error
else:
return getter(time)
@@ -180,7 +179,7 @@ def set_interval(self, start, end, value, compact=False):
"""
# for each interval to render
- for i, (s, e, v) in enumerate(self.iterperiods(start, end)):
+ for i, (s, _e, v) in enumerate(self.iterperiods(start, end)): # noqa: B007
# look at all intervals included in the current interval
# (always at least 1)
if i == 0:
@@ -216,9 +215,9 @@ def exists(self):
otherwise
"""
- result = TimeSeries(default=False if self.default is None else True)
+ result = TimeSeries(default=self.default is not None)
for t, v in self:
- result[t] = False if v is None else True
+ result[t] = v is not None
return result
def remove(self, time):
@@ -228,19 +227,18 @@ def remove(self, time):
"""
try:
del self._d[time]
- except KeyError:
- raise KeyError("no measurement at {}".format(time))
+ except KeyError as error:
+ error.add_note(f"no measurement at {time}")
+ raise
def remove_points_from_interval(self, start, end):
"""Allow removal of all points from the time series within a interval
[start:end].
"""
- for s, e, v in self.iterperiods(start, end):
- try:
+ for s, _e, _v in self.iterperiods(start, end):
+ with contextlib.suppress(KeyError):
del self._d[s]
- except KeyError:
- pass
def n_measurements(self):
"""Return the number of measurements in the time series."""
@@ -274,20 +272,16 @@ def format_item(item):
half = MAX_LENGTH // 2
if len(self) > MAX_LENGTH:
one = ", ".join(format_item(_) for _ in self._d.items()[:half])
- two = ", ".join(
- format_item(_) for _ in self._d.items()[half:-half]
- )
+ two = ", ".join(format_item(_) for _ in self._d.items()[half:-half])
three = ", ".join(format_item(_) for _ in self._d.items()[-half:])
- truncate_string = "<...{} items...>".format(len(self) - MAX_LENGTH)
+ truncate_string = f"<...{len(self) - MAX_LENGTH} items...>"
if len(truncate_string) < len(two):
two = truncate_string
items = ", ".join([one, two, three])
else:
items = ", ".join(format_item(_) for _ in self._d.items())
- return "{name}({{{items}}})".format(
- name=type(self).__name__, items=items,
- )
+ return f"{type(self).__name__}({{{items}}})"
def iterintervals(self, n=2):
"""Iterate over groups of `n` consecutive measurement points in the
@@ -311,12 +305,10 @@ def iterintervals(self, n=2):
# now, zip the offset streams back together to yield tuples,
# in the n=3 example it would yield:
# (a, b, c), (b, c, d), ..., (w, x, y), (x, y, z)
- for intervals in zip(*streams):
- yield intervals
+ yield from zip(*streams)
@staticmethod
def _value_function(value):
-
# if value is None, don't filter
if value is None:
@@ -363,7 +355,6 @@ def iterperiods(self, start=None, end=None, value=None):
interval_t0, interval_value = start, start_value
for interval_t1 in self._d.islice(start_index, end_index):
-
if value_function(interval_t0, interval_t1, interval_value):
yield interval_t0, interval_t1, interval_value
@@ -373,9 +364,10 @@ def iterperiods(self, start=None, end=None, value=None):
interval_value = self[interval_t0]
# yield the time, duration, and value of the final period
- if interval_t0 < end:
- if value_function(interval_t0, end, interval_value):
- yield interval_t0, end, interval_value
+ if interval_t0 < end and value_function(
+ interval_t0, end, interval_value
+ ):
+ yield interval_t0, end, interval_value
def slice(self, start, end):
"""Return an equivalent TimeSeries that only has points between
@@ -387,7 +379,7 @@ def slice(self, start, end):
)
result = TimeSeries(default=self.default)
- for t0, t1, value in self.iterperiods(start, end):
+ for t0, t1, value in self.iterperiods(start, end): # noqa: B007
result[t0] = value
result[t1] = self[t1]
@@ -395,10 +387,8 @@ def slice(self, start, end):
return result
def _check_regularization(self, start, end, sampling_period=None):
-
# only do these checks if sampling period is given
if sampling_period is not None:
-
# cast to both seconds and timedelta for error checking
if isinstance(sampling_period, datetime.timedelta):
sampling_period_seconds = sampling_period.total_seconds()
@@ -421,19 +411,18 @@ def _check_regularization(self, start, end, sampling_period=None):
)
raise ValueError(msg)
- if isinstance(start, datetime.date):
- sampling_period = sampling_period_timedelta
- else:
- sampling_period = sampling_period_seconds
+ sampling_period = (
+ sampling_period_timedelta
+ if isinstance(start, datetime.date)
+ else sampling_period_seconds
+ )
return sampling_period
def sample(
self, sampling_period, start=None, end=None, interpolate="previous"
):
- """Sampling at regular time periods.
-
- """
+ """Sampling at regular time periods."""
start, end, mask = self._check_boundaries(start, end)
sampling_period = self._check_regularization(
@@ -448,7 +437,7 @@ def sample(
current_time += sampling_period
return result
- def moving_average(
+ def moving_average( # noqa: C901
self,
sampling_period,
window_size=None,
@@ -457,8 +446,7 @@ def moving_average(
placement="center",
pandas=False,
):
- """Averaging over regular intervals
- """
+ """Averaging over regular intervals"""
start, end, mask = self._check_boundaries(start, end)
# default to sampling_period if not given
@@ -481,7 +469,6 @@ def moving_average(
result = []
current_time = start
while current_time <= end:
-
if placement == "center":
window_start = current_time - half_window
window_end = current_time + half_window
@@ -492,7 +479,7 @@ def moving_average(
window_start = current_time - full_window
window_end = current_time
else:
- msg = 'unknown placement "{}"'.format(placement)
+ msg = f'unknown placement "{placement}"'
raise ValueError(msg)
# calculate mean over window and add (t, v) tuple to list
@@ -502,29 +489,30 @@ def moving_average(
if "NoneType" in str(e):
mean = None
else:
- raise e
+ raise
result.append((current_time, mean))
current_time += sampling_period
# convert to pandas Series if pandas=True
if pandas:
-
try:
import pandas as pd
- except ImportError:
- msg = "can't have pandas=True if pandas is not installed"
- raise ImportError(msg)
+ except ImportError as error:
+ error.add_note(
+ "can't have pandas=True if pandas is not installed"
+ )
+ raise
result = pd.Series(
- [v for t, v in result], index=[t for t, v in result],
+ [v for t, v in result],
+ index=[t for t, v in result],
)
return result
@staticmethod
def rebin(binned, key_function):
-
result = sortedcontainers.SortedDict()
for bin_start, value in binned.items():
new_bin_start = key_function(bin_start)
@@ -545,17 +533,17 @@ def bin(
smaller=None,
transform="distribution",
):
-
- # return an empty sorted dictionary if there is no time span
if mask is not None and mask.is_empty():
return sortedcontainers.SortedDict()
- elif start is not None and start == end:
+
+ if start is not None and start == end:
return sortedcontainers.SortedDict()
# use smaller if available
if smaller:
return self.rebin(
- smaller, lambda x: utils.datetime_floor(x, unit, n_units),
+ smaller,
+ lambda x: utils.datetime_floor(x, unit, n_units),
)
start, end, mask = self._check_boundaries(start, end, mask=mask)
@@ -629,13 +617,15 @@ def distribution(
counter = histogram.Histogram()
for i_start, i_end, _ in mask.iterperiods(value=True):
for t0, t1, _ in self.iterperiods(i_start, i_end):
- duration = utils.duration_to_number(t1 - t0, units="seconds",)
+ duration = utils.duration_to_number(
+ t1 - t0,
+ units="seconds",
+ )
midpoint = utils.time_midpoint(t0, t1)
value = self.get(midpoint, interpolate=interpolate)
try:
counter[value] += duration
except histogram.UnorderableElements:
-
counter = histogram.Histogram.from_dict(
dict(counter), key=hash
)
@@ -686,16 +676,17 @@ def n_points(
count = 0
for i_start, i_end, _ in mask.iterperiods(value=True):
+ end_count = (
+ self._d.bisect_right(i_end)
+ if include_end
+ else self._d.bisect_left(i_end)
+ )
- if include_end:
- end_count = self._d.bisect_right(i_end)
- else:
- end_count = self._d.bisect_left(i_end)
-
- if include_start:
- start_count = self._d.bisect_left(i_start)
- else:
- start_count = self._d.bisect_right(i_start)
+ start_count = (
+ self._d.bisect_left(i_start)
+ if include_start
+ else self._d.bisect_right(i_start)
+ )
count += end_count - start_count
@@ -710,10 +701,7 @@ def _check_time_series(self, other):
"""
if not isinstance(other, TimeSeries):
- msg = "unsupported operand types(s) for +: %s and %s" % (
- type(self),
- type(other),
- )
+ msg = f"unsupported operand types(s) for +: {type(self)} and {type(other)}"
raise TypeError(msg)
@staticmethod
@@ -745,7 +733,6 @@ def _iter_merge(timeseries_list):
# of the default value for each individual TimeSeries.
state = [ts.default for ts in timeseries_list]
while not queue.empty():
-
# get the next time with a measurement from queue
t, index, next_value, iterator = queue.get()
@@ -815,10 +802,7 @@ def merge(cls, ts_list, compact=True, operation=None):
result = cls(default=default)
for t, merged in cls.iter_merge(ts_list):
- if operation is None:
- value = merged
- else:
- value = operation(merged)
+ value = merged if operation is None else operation(merged)
result.set(t, value, compact=compact)
return result
@@ -841,7 +825,6 @@ def from_csv(
skip_header=True,
default=None,
):
-
# use default on class if not given
if time_transform is None:
time_transform = cls.csv_time_transform
@@ -953,7 +936,8 @@ def __setitem__(self, time, value):
def __getitem__(self, time):
"""Allow a[time] syntax."""
if isinstance(time, slice):
- raise ValueError("Syntax a[start:end] not allowed")
+ msg = "Syntax a[start:end] not allowed"
+ raise ValueError(msg) # noqa: TRY004
else:
return self.get(time)
@@ -974,7 +958,7 @@ def __radd__(self, other):
"""
# skip type check if other is the integer 0
- if not other == 0:
+ if other != 0:
self._check_time_series(other)
# 0 + self = self
@@ -1007,7 +991,6 @@ def __ne__(self, other):
return not (self == other)
def _check_boundary(self, value, allow_infinite, lower_or_upper):
-
if lower_or_upper == "lower":
infinity_value = -inf
method_name = "first_key"
@@ -1015,8 +998,9 @@ def _check_boundary(self, value, allow_infinite, lower_or_upper):
infinity_value = inf
method_name = "last_key"
else:
- msg = '`lower_or_upper` must be "lower" or "upper", got {}'.format(
- lower_or_upper,
+ msg = (
+ f'`lower_or_upper` must be "lower" or "upper", '
+ f"got {lower_or_upper}"
)
raise ValueError(msg)
@@ -1026,19 +1010,19 @@ def _check_boundary(self, value, allow_infinite, lower_or_upper):
else:
try:
return getattr(self, method_name)()
- except IndexError:
+ except IndexError as error:
msg = (
- "can't use '{}' for default {} boundary "
- "of empty TimeSeries"
- ).format(method_name, lower_or_upper)
- raise KeyError(msg)
+ f"can't use '{method_name}' for default "
+ f"{lower_or_upper} boundary of empty TimeSeries"
+ )
+ raise KeyError(msg) from error
else:
return value
def _check_boundaries(self, start, end, mask=None, allow_infinite=False):
-
if mask is not None and mask.is_empty():
- raise ValueError("mask can not be empty")
+ msg = "mask can not be empty"
+ raise ValueError(msg)
# if only a mask is passed in, return mask boundaries and mask
if start is None and end is None and mask is not None:
@@ -1049,24 +1033,20 @@ def _check_boundaries(self, start, end, mask=None, allow_infinite=False):
end = self._check_boundary(end, allow_infinite, "upper")
if start >= end:
- msg = "start can't be >= end ({} >= {})".format(start, end)
+ msg = f"start can't be >= end ({start} >= {end})"
raise ValueError(msg)
start_end_mask = TimeSeries(default=False)
start_end_mask[start] = True
start_end_mask[end] = False
- if mask is None:
- mask = start_end_mask
- else:
- mask = mask & start_end_mask
+ mask = start_end_mask if mask is None else mask & start_end_mask
return start, end, mask
def distribution_by_hour_of_day(
self, first=0, last=23, start=None, end=None
):
-
start, end, mask = self._check_boundaries(start, end)
result = []
@@ -1079,7 +1059,6 @@ def distribution_by_hour_of_day(
def distribution_by_day_of_week(
self, first=0, last=6, start=None, end=None
):
-
start, end, mask = self._check_boundaries(start, end)
result = []
@@ -1110,7 +1089,6 @@ def plot(
def hour_of_day(start, end, hour):
-
# start should be date, or if datetime, will use date of datetime
floored = utils.datetime_floor(start)
@@ -1129,7 +1107,6 @@ def hour_of_day(start, end, hour):
def day_of_week(start, end, weekday):
-
# allow weekday name or number
number = utils.weekday_number(weekday)
diff --git a/traces/utils.py b/traces/utils.py
index 00bd166..225d59e 100644
--- a/traces/utils.py
+++ b/traces/utils.py
@@ -1,3 +1,4 @@
+import contextlib
import datetime
from infinity import inf
@@ -65,7 +66,7 @@ def convert_args_to_list(args):
if len(args) == 2:
list_of_pairs.append(list(args))
else:
- msg = "The argument type is invalid. {}".format(args)
+ msg = f"The argument type is invalid. {args}"
raise TypeError(msg)
return list_of_pairs
@@ -122,12 +123,11 @@ def floor_datetime(dt, unit, n_units=1):
dt.year, dt.month, dt.day, dt.hour, dt.minute, new_second
)
else:
- msg = "Unknown unit type {}".format(unit)
+ msg = f"Unknown unit type {unit}"
raise ValueError(msg)
def datetime_floor(value, unit="days", n_units=1):
-
# if it's a date, convert to datetime at start of day
if type(value) is datetime.date:
value = datetime.datetime.combine(value, datetime.time())
@@ -139,7 +139,7 @@ def datetime_floor(value, unit="days", n_units=1):
elif value == inf:
return inf
else:
- msg = "must be date, datetime, or inf; got {}".format(value)
+ msg = f"must be date, datetime, or inf; got {value}"
raise ValueError(msg)
@@ -155,7 +155,6 @@ def datetime_floor(value, unit="days", n_units=1):
def weekday_number(value):
-
if isinstance(value, int):
if 0 <= value < 7:
return value
@@ -168,18 +167,16 @@ def weekday_number(value):
if result:
return result
else:
- try:
+ with contextlib.suppress(TypeError):
result = WEEKDAY_LOOKUP.get(value.lower())
- except TypeError:
- pass
if result:
return result
- msg = "must be a valid weekday, got {}".format(value)
+ msg = f"must be a valid weekday, got {value}"
raise ValueError(msg)
def pairwise(iterable):
- """ given an interable `p1, p2, p3, ...`
+ """given an interable `p1, p2, p3, ...`
it iterates through pairwise tuples `(p0, p1), (p1, p2), ...`"""
it = iter(iterable)
a = next(it, None)