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View mirror-mouse.py
# inspired by:
# https://www.halfbakery.com/idea/Mirrored_20Mouse
import pyautogui
width, height = pyautogui.size()
def mirror(duration=0.0):
current = pyautogui.position()
new_x = width - current.x
View schematize.py
### For finding schema
def schematize(obj):
'''
Get schema of nested JSON, assuming first item in lists.
'''
if isinstance(obj, dict):
return {k: schematize(v) for k, v in obj.items()}
elif isinstance(obj, list):
return [schematize(elem) for elem in obj][:1]
View schematize.py
### For finding schema
def schematize(obj):
'''
Get schema of nested JSON, assuming first item in lists.
'''
if isinstance(obj, dict):
return {k: schematize(v) for k, v in obj.items()}
elif isinstance(obj, list):
return [schematize(elem) for elem in obj][:1]
View md_language_splitter_autodetect.py
import os
import collections
import langdetect
LANGUAGE_CODES = os.listdir(langdetect.PROFILES_DIRECTORY)
def detect_language(text, max_length=2):
""" Make sure we return N-letter keys for languages"""
shorter = {'zh-cn': 'cn', 'zh-tw': 'zh'}
code = langdetect.detect(text)
View xarray_fundamentals.py
import pandas
import xarray
ds = xarray.Dataset(
{'x': ([None], [1,2,3] ),
'y': ([None], [4,5,6] )},
)
# *is equivalent to*
View parallelize_df.py
import pandas
from dask import dataframe
from dask.diagnostics import ProgressBar
def parallel_apply(df, func, progress=True, chunkrows=100, scheduler_address=None, *args, **kwargs):
if scheduler_address:
from dask.distributed import Client
client = Client(scheduler_address)
View complex_frames.py
# Practically, it's useful if we have complex observations (rows) and variables (columns):
df = pandas.DataFrame(
data=pandas.np.array(
[[1,2,3,4,5],
[6,7,8,9,10],
[11,12,13,14,15]]).T,
index=pandas.MultiIndex.from_arrays(
[['x','x','x','y','z'],
['a','a','b','b','c'],
View grouped_apply.py
import pandas
import multiprocessing
def apply_parallel(grouped_df, func):
with multiprocessing.Pool(multiprocessing.cpu_count()) as p:
ret_list = p.map(func, [group for name, group in grouped_df])
return pandas.concat(ret_list)
View keybase.md

Keybase proof

I hereby claim:

  • I am mindey on github.
  • I am mindey (https://keybase.io/mindey) on keybase.
  • I have a public key whose fingerprint is 5AFD B16B 8980 5133 F450 688B DA58 0D1D 5F5C C7AD

To claim this, I am signing this object:

View keybase.md

Keybase proof

I hereby claim:

  • I am mindey on github.
  • I am mindey (https://keybase.io/mindey) on keybase.
  • I have a public key whose fingerprint is 5AFD B16B 8980 5133 F450 688B DA58 0D1D 5F5C C7AD

To claim this, I am signing this object:

You can’t perform that action at this time.