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Sampling process 44517 for 3 seconds with 1 millisecond of run time between samples
Sampling completed, processing symbols...
Analysis of sampling csgo_osx64 (pid 44517) every 1 millisecond
Process:         csgo_osx64 [44517]
Path:            /Users/USER/Library/Application Support/Steam/*/csgo_osx64
Load Address:    0x10f2e9000
Identifier:      csgo_osx64
Version:         ???
Code Type:       X86-64
Parent Process:  bash [44514]

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2021-02-03T05:26:14.6653679Z ##[section]Starting: PyTest Python36
2021-02-03T05:26:14.9395796Z ##[section]Starting: Initialize job
2021-02-03T05:26:14.9397123Z Agent name: 'Azure Pipelines 4'
2021-02-03T05:26:14.9397517Z Agent machine name: 'fv-az315-103'
2021-02-03T05:26:14.9397757Z Current agent version: '2.181.1'
2021-02-03T05:26:14.9441788Z ##[group]Operating System
2021-02-03T05:26:14.9442012Z Ubuntu
2021-02-03T05:26:14.9442183Z 18.04.5
2021-02-03T05:26:14.9442318Z LTS
2021-02-03T05:26:14.9442484Z ##[endgroup]

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import scanpy as sc, numpy as np
from matplotlib import pyplot as plt
from sklearn.utils import sparsefuncs

def norm_frac(adata):
    sparsefuncs.inplace_row_scale(adata.X, 1 / adata.X.sum(axis=1).A1)
    return adata

def norm_cpm(adata):
    sparsefuncs.inplace_row_scale(adata.X, 1_000_000 / adata.X.sum(axis=1).A1)

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import requests
import pandas as pd


def fetch_state_results(state: str) -> dict:
    r = requests.get(f"https://static01.nyt.com/elections-assets/2020/data/api/2020-11-03/race-page/{state}/president.json")
    return r.json()["data"]


def _process_records(input: "list[dict]") -> pd.DataFrame:

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Computer Information:
    Manufacturer:  Apple
    Model:  MacBookPro16,1
    Form Factor: Laptop
    No Touch Input Detected

Processor Information:
    CPU Vendor:  GenuineIntel
    CPU Brand:  Intel(R) Core(TM) i9-9880H CPU @ 2.30GHz
    CPU Family:  0x6

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===================================================== test session starts =====================================================
platform darwin -- Python 3.8.5, pytest-5.4.3, py-1.9.0, pluggy-0.13.1
rootdir: /Users/isaac/github/diffxpy
plugins: cov-2.10.0
collected 68 items                                                                                                            

diffxpy/unit_test/test_acc_glm_all_numpy_temp.py F                                                                      [  1%]
diffxpy/unit_test/test_backends.py .FF                                                                                  [  5%]
diffxpy/unit_test/test_constrained.py FFF                                                                               [ 10%]
diffxpy/unit_test/test_continuous_de.py .F                                                                                         [ 13%]

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from PIL import image
import pandas as pd
import numpy as np

empty_pixel = np.array([255, 255, 255, 0]).reshape(1, 1, -1)

# !wget https://github.com/theislab/scanpy/raw/master/docs/_static/img/Scanpy_Logo_RGB.png
im = Image.open("./Scanpy_Logo_RGB.png")
a = np.array(im)

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"""Simple OrderedSet implementation."""

from collections import OrderedDict
from collections.abc import MutableSet
from functools import reduce
from itertools import repeat
from operator import or_, sub


class OrderedSet(MutableSet):

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All benchmarks:

       before           after         ratio
     [4440b90f]       [a80db25c]
     <doc-fix2>       <obsp-update>
- 2.1052631578947367  1.4814814814814814     0.70  views.SubsetMemorySuite.track_repeated_subset_memratio(100, 100, 'X-csr', 'obs', 'boolarray')
- 1.8181818181818181  1.2758620689655173     0.70  views.SubsetMemorySuite.track_repeated_subset_memratio(100, 100, 'X-csr', 'obs', 'intarray')
- 0.6666666666666666              0.5     0.75  views.SubsetMemorySuite.track_repeated_subset_memratio(100, 100, 'X-csr', 'obs', 'slice')
- 1.9473684210526316            1.375     0.71  views.SubsetMemorySuite.track_repeated_subset_memratio(100, 100, 'X-csr', 'var', 'boolarray')

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"""
TODO:

* Get dates for each state
"""

from requests_html import HTMLSession
import pandas as pd
import string