Steven Smith revised this gist . Go to revision
1 file changed, 14 insertions
elstate.py(file created)
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| 1 | + | import urllib,json | |
| 2 | + | d=json.loads(urllib.urlopen("https://intf.nyt.com/newsgraphics/2016/11-08-election-forecast/president.json").read())["president"] | |
| 3 | + | print("""As of {timestamp}: | |
| 4 | + | Clinton: | |
| 5 | + | Votes: {electoral_votes_counted[clintonh]}/270 | |
| 6 | + | Counted: {vote_share_counted[clintonh]:.3%} | |
| 7 | + | Win prob: {win_prob[clintonh]:.3%} | |
| 8 | + | Trump: | |
| 9 | + | Votes: {electoral_votes_counted[trumpd]}/270 | |
| 10 | + | Counted: {vote_share_counted[trumpd]:.3%} | |
| 11 | + | Win prob: {win_prob[trumpd]:.3%}""".format(**d["timeseries"][-1])) | |
| 12 | + | print("\n".join( "{state}: {current[winner][name_display]}".format(**s) if s["current"]["winner"] else | |
| 13 | + | "{state}: Undecided, {current[percent_counted]:.1%} counted - Clinton: {current[win_prob][clintonh]:.1%}, Trump: {current[win_prob][trumpd]:.1%}".format(**s) | |
| 14 | + | for s in d["races"] )) | |
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