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BibMartin
/ unstack_dict.py
Last active
May 9, 2017 07:37
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| def unstack(x, prefix=""): | |
| if isinstance(x, dict): | |
| out = {} | |
| for key, val in x.items(): | |
| z = unstack(val, prefix=key+'.') | |
| if isinstance(z, dict): | |
| for subkey, subval in z.items(): | |
| out[prefix+subkey] = subval | |
| else: | |
| out[prefix+key] = val |
BibMartin
/ gist:eb08cf972c33d5d2552274eaf2e3887f
Created
January 21, 2017 14:13
A tornado web service that self-calls itself periodically
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| import tornado.ioloop | |
| import tornado.web | |
| import pandas as pd | |
| import requests | |
| import os | |
| class MainHandler(tornado.web.RequestHandler): | |
| def get(self): | |
| print('handler', pd.Timestamp.utcnow()) | |
| self.write(str(self.request.headers.get('Authorization'))) |
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| <!DOCTYPE html> | |
| <head> | |
| <!-- FOLIUM (simplified) HEADER --> | |
| <meta http-equiv="content-type" content="text/html; charset=UTF-8" /> | |
| <script src="https://cdnjs.cloudflare.com/ajax/libs/leaflet/0.7.3/leaflet.js"></script> | |
| <script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.1/jquery.min.js"></script> | |
| <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script> | |
| <script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.min.js"></script> | |
| <script src="https://cdnjs.cloudflare.com/ajax/libs/leaflet.markercluster/0.4.0/leaflet.markercluster-src.js"></script> | |
| <script src="https://cdnjs.cloudflare.com/ajax/libs/leaflet.markercluster/0.4.0/leaflet.markercluster.js"></script> |
BibMartin
/ TimestampedGeoJson example.ipynb
Created
June 21, 2016 19:30
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BibMartin
/ BindColormap.ipynb
Created
June 15, 2016 19:09
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BibMartin
/ Asynchronous service with tornado.ipynb
Created
April 1, 2016 21:06
Asynchronous service with tornado
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| https://docs.mongodb.org/manual/tutorial/install-mongodb-on-ubuntu/ |
BibMartin
/ Le Compte Foyer Fiscal.ipynb
Created
March 20, 2016 09:55
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BibMartin
/ halton-sequence
Created
March 17, 2016 20:40
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| ```python | |
| import numpy as np | |
| import scipy.stats as st | |
| import matplotlib.pyplot as plt | |
| import openturns as ot | |
| import pandas as pd | |
| sequence = ot.LowDiscrepancySequence(ot.HaltonSequence(1000)) |