- How to Make Manual Predictions for ARIMA Models with Python
- How to Make Out-of-Sample Forecasts with ARIMA in Python
- How to Model Residual Errors to Correct Time Series Forecasts with Python
- How to Tune ARIMA Parameters in Python
- Sensitivity Analysis of History Size to Forecast Skill with ARIMA in Python
from nbformat.v4 import new_notebook, new_code_cell, new_markdown_cell
import nbformat
nb = new_notebook()
nb.cells = [
new_code_cell('print("hello")'),
new_markdown_cell('# Cool')
In your tests/init.py file, add the following
from model_mommy import mommy
def generator_function():
return {}
mommy.generators.add('django_mysql.models.JSONField', generator_function)
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import os | |
import re | |
output = os.popen('arp -a').read().splitlines() | |
ips = [re.search(r'\d+\.\d+\d+.\d+.\d+', b).group(0) for b in output] | |
for ip in ips: | |
print(os.popen('nmblookup -A {}'.format(ip)).read()) |
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from pdfminer.pdfparser import PDFParser | |
from pdfminer.pdfdocument import PDFDocument | |
import sys | |
# python tldr.py filename.pdf | |
fp = open(sys.argv[1], 'rb') | |
parser = PDFParser(fp) | |
doc = PDFDocument(parser) |
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import csv | |
import boto3 | |
def get_available_methods(service): | |
client = boto3.client(service) | |
all_attributes = dir(client) | |
available_methods = [attribute for attribute in all_attributes if callable(getattr(client, attribute))] | |
available_methods = [i for i in available_methods if not i.startswith('_')] |
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import requests | |
from bs4 import BeautifulSoup | |
payload = { | |
'keyword': '20403105', | |
'slug': 'SearchResult' | |
} | |
response = requests.post('http://www.neb.gov.np/result/search', data=payload) |