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| { | |
| "meta": { | |
| "theme": "kendall" | |
| }, | |
| "basics": { | |
| "name": "Chen Du (杜琛)", | |
| "label": "Cloud Dev", | |
| "image": "https://gravatar.com/userimage/252197455/05d270125e2ee728cc21842d872b8274.jpeg?size=512", | |
| "email": "[email protected]", | |
| "phone": "18963609586", |
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| { | |
| "meta": { | |
| "theme": "kendall" | |
| }, | |
| "basics": { | |
| "name": "Chen Du (杜琛)", | |
| "label": "Cloud Ops Engineer", | |
| "image": "https://gravatar.com/userimage/252197455/05d270125e2ee728cc21842d872b8274.jpeg?size=512", | |
| "email": "[email protected]", | |
| "phone": "18963609586", |
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| import pandas as pd | |
| import pickle | |
| import numpy as np | |
| from tabulate import tabulate | |
| left_align_gen = lambda length, value: eval(r"'{:<<<length>>}'.format('''<<value>>'''[0:<<length>>])".replace('<<length>>', str(length)).replace('<<value>>', str(value))) | |
| right_align_gen = lambda length, value: eval(r"'{:><<length>>}'.format('''<<value>>'''[0:<<length>>])".replace('<<length>>', str(length)).replace('<<value>>', str(value))) | |
| # df = pd.read_pickle("dummy.pkl") |
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| def chunks(l, n): | |
| n = max(1, n) | |
| result = [l[i:i+n] for i in range(0, len(l), n)] | |
| if len(result) * n > len(l): | |
| last = result.pop(-1) | |
| result[-1] += last | |
| return result | |
| lenf = 205 | |
| div = 4 |
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| from datetime import datetime | |
| with open('test.txt') as f: | |
| date_list = f.read().split('\n') | |
| date_list = [ x.replace('"', '').strip() for x in date_list if x] | |
| for x in date_list: | |
| try: | |
| datetime.strptime(x, '%m/%d/%Y') |
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| from tqdm import tqdm | |
| import pandas as pd | |
| from sqlalchemy import create_engine, MetaData | |
| SOURCE_TABLE_NAME_LIST = ['individual_tagging_sd', ] | |
| def chunker(seq, size): | |
| return (seq[pos:pos + size] for pos in range(0, len(seq), size)) |
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| #!/bin/bash | |
| if [ $# -lt 1 ]; then | |
| echo -e "Shrink the size of raspberry pi image.\nUsage: bash $0 xxx.img " | |
| ls -l *.img | |
| exit | |
| fi | |
| IMG=$1 |
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| import os | |
| def split(filehandler, delimiter=',', row_limit=1000, | |
| output_name_template='output_%s.csv', output_path='.', keep_headers=True): | |
| import csv | |
| reader = csv.reader(filehandler, delimiter=delimiter) | |
| current_piece = 1 | |
| current_out_path = os.path.join( | |
| output_path, |
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| import json | |
| import sqlparse | |
| import xmltodict | |
| from pprint import pprint | |
| def xml2dict(xmlString): | |
| '''Return json object''' | |
| jsonString = json.dumps(xmltodict.parse(xmlString), indent=4) | |
| xml_in_dict = json.loads(jsonString) |
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| import time | |
| import pyautogui | |
| print('ready') | |
| time.sleep(3) | |
| print('start') | |
| for i in range(30): | |
| pyautogui.click(1689,444) | |
| time.sleep(.5) |
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