import sys,os
sys.path.insert(1, os.path.join(os.path.dirname(__file__), 'planet/vendor'))
from feedparser import _sanitizeHTML
assert 'strong' in _sanitizeHTML('<strong>Hello</strong>', 'utf-8', 'text/html')
assert 'mix-blend-mode' in _sanitizeHTML('<svg><path style="fill: red;mix-blend-mode:darken"></path></svg>', 'utf-8', 'text/html')

import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame(data[1:], columns=data[0])
df = df.drop('Weeks to CFP', axis=1).groupby(['Year']).sum()
fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(12,6))
fig1 = df['Count'].plot(kind="bar", ax=ax[0], title='Number of submissions')
fig2 = df['Minutes'].plot(kind="bar", ax=ax[1], title='Number of minutes')
fig.get_figure().savefig('emacsconf-by-year.png')
return df

import pandas as pd
import matplotlib.pyplot as plt
import imageio as io
df = pd.DataFrame(data[1:], columns=data[0])
fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(12,6))
count = pd.pivot_table(df, columns=['Year'], index=['Weeks to CFP'], values='Count', aggfunc='sum', fill_value=0).iloc[::-1].sort_index(ascending=True).cumsum()
minutes = pd.pivot_table(df, columns=['Year'], index=['Weeks to CFP'], values='Minutes', aggfunc='sum', fill_value=0).iloc[::-1].sort_index(ascending=True).cumsum()
ax[0].set_ylim([0, count.max().max()])
ax[1].set_ylim([0, minutes.max().max()])
with io.get_writer('emacsconf-combined.gif', mode='I', duration=[500, 500, 500, 500, 1000], loop=0) as writer:
    for year in range(2019, 2024):
        count[year].plot(ax=ax[0], title='Cumulative submissions')
        minutes[year].plot(ax=ax[1], title='Cumulative minutes')
        ax[0].legend(loc='upper left')
        ax[1].legend(loc='upper left')
        for axis in ax:
            for line in axis.get_lines():
                if line.get_label() == '2023':
                    line.set_linewidth(5)
            for line in axis.legend().get_lines():
                if line.get_label() == '2023':
                    line.set_linewidth(5)        
        filename = f'emacsconf-combined-${year}.png'
        fig.get_figure().savefig(filename)
        image = io.v3.imread(filename)
        writer.append_data(image)

(let ((years `((2023 "~/proj/emacsconf/2023/private/conf.org" "2023-09-15")
               (2022 "~/proj/emacsconf/2022/private/conf.org" "2022-09-18")
               (2021 "~/proj/emacsconf/2021/private/conf.org" "2021-09-30")
               (2020 "~/proj/emacsconf/wiki/2020/submissions.org" "2020-09-30")
               (2019 "~/proj/emacsconf/2019/private/conf.org" "2019-08-31"))))
  (append
   '(("Weeks to CFP" "Year" "Count" "Minutes"))
   (seq-mapcat
    (lambda (year-info)
      (let ((emacsconf-org-file (elt year-info 1))
            (emacsconf-cfp-deadline (elt year-info 2))
            (year (car year-info)))
        (mapcar (lambda (o) (list (car o) year (cadr o) (elt o 2)))
                (cdr (emacsconf-count-submissions-by-week (emacsconf-get-talk-info) emacsconf-cfp-deadline)))))
    years)))

import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame(data[1:], columns=data[0])
df = pd.pivot_table(df, columns=['Year'], index=['Weeks to CFP'], values='Count', aggfunc='sum', fill_value=0).iloc[::-1].sort_index(ascending=True)
fig, ax = plt.subplots()
figure = df.plot(title='Number of submissions by number of weeks to the CFP end date', ax=ax)
for line in ax.get_lines():
    if line.get_label() == '2023':
        line.set_linewidth(5)
for line in plt.legend().get_lines():
    if line.get_label() == '2023':
        line.set_linewidth(5)        
figure.get_figure().savefig('number-of-submissions.png')
return df

import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame(data[1:], columns=data[0])
df = pd.pivot_table(df, columns=['Year'], index=['Weeks to CFP'], values='Count', aggfunc='sum', fill_value=0).iloc[::-1].sort_index(ascending=True).cumsum()
fig, ax = plt.subplots()
figure = df.plot(title='Cumulative submissions by number of weeks to the CFP end date', ax=ax)
for line in ax.get_lines():
    if line.get_label() == '2023':
        line.set_linewidth(5)
for line in plt.legend().get_lines():
    if line.get_label() == '2023':
        line.set_linewidth(5)        
figure.get_figure().savefig('cumulative-submissions.png')
return df

import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame(data[1:], columns=data[0])
df = pd.pivot_table(df, columns=['Year'], index=['Weeks to CFP'], values='Minutes', aggfunc='sum', fill_value=0).iloc[::-1].sort_index(ascending=True).cumsum()
fig, ax = plt.subplots()
figure = df.plot(title='Cumulative minutes by number of weeks to the CFP end date', ax=ax)
for line in ax.get_lines():
    if line.get_label() == '2023':
        line.set_linewidth(5)
for line in plt.legend().get_lines():
    if line.get_label() == '2023':
        line.set_linewidth(5)        
figure.get_figure().savefig('cumulative-minutes.png')
return df

import logging
from llama_index import GPTSimpleVectorIndex, MockLLMPredictor, MockEmbedding, QuestionAnswerPrompt
logging.basicConfig(level=logging.DEBUG)
logging.debug('This is a test.')

logging.getLogger().setLevel(logging.DEBUG)

ffmpeg -y -f lavfi -i 'sine=frequency=1000:duration=0.1' beep.wav

(defun my-beep ()
  (interactive)
  (save-window-excursion
    (shell-command "aplay ~/recordings/beep.wav &" nil nil)))

(require 'director)
(defvar emacsconf-recording-process nil)
(shell-command "xdotool getwindowfocus windowsize 1282 720")
(progn
  (switch-to-buffer (get-buffer-create "*Questions*"))
  (erase-buffer)
  (org-mode)
  (face-remap-add-relative 'default :height 300)
  (setq-local mode-line-format "   Q&A for EmacsConf 2022: What I'd like to see in Emacs (Richard M. Stallman) - emacsconf.org/2022/talks/rms")
  (sit-for 3)
  (delete-other-windows)
  (hl-line-mode -1)
  (when (process-live-p emacsconf-recording-process) (kill-process emacsconf-recording-process))
  (setq emacsconf-recording-process (start-process "ssr" (get-buffer-create "*ssr*")
                                                   "simplescreenrecorder"
                                                   "--start-recording"
                                                   "--start-hidden"))
  (sit-for 3)
  (director-run
   :version 1
   :log-target '(file . "/tmp/director.log")
   :before-start
   (lambda ()
     (switch-to-buffer (get-buffer-create "*Questions*"))
     (delete-other-windows))
   :steps
   (let ((subtitles (subed-parse-file "~/proj/emacsconf/rms/emacsconf-2022-rms--what-id-like-to-see-in-emacs--answers--chapters.vtt")))
     (apply #'append
            (list
             (list :eval '(my-beep))
             (list :type "* Q&A for Richard Stallman's EmacsConf 2022 talk: What I'd like to see in Emacs\nhttps://emacsconf.org/2022/talks/rms\n\n"))
            (mapcar
             (lambda (sub)
               (list
                (list :log (elt sub 3))
                (list :eval '(progn (org-end-of-subtree)
                                    (unless (bolp) (insert "\n"))))
                (list :type (concat "** " (elt sub 3) "\n\n"))
                (list :eval '(org-back-to-heading))
                (list :wait 5)
                (list :eval '(my-beep))))
             subtitles)))
   :typing-style 'human
   :delay-between-steps 0
   :after-end (lambda ()
                (process-send-string emacsconf-recording-process "record-save\nwindow-show\nquit\n"))
   :on-failure (lambda ()
                 (process-send-string emacsconf-recording-process "record-save\nwindow-show\nquit\n"))
   :on-error (lambda ()
               (process-send-string emacsconf-recording-process "record-save\nwindow-show\nquit\n"))))

(let ((name "animation.webm"))
  (copy-file (my-latest-file my-recordings-dir) name t)
  (shell-command
   (format "ffmpeg -y -i %s -ar 8000 -ac 1 %s.wav"
           (shell-quote-argument name)
           (shell-quote-argument (file-name-sans-extension name)))))

filename = "animation.wav"
from scipy.io import wavfile
from scipy import signal
import numpy as np
import re
rate, source = wavfile.read(filename)
peaks = signal.find_peaks(source, height=1000, distance=1000)
base_times = (peaks[0] / rate) - 0.82
print(base_times)

import webvtt
import subprocess
chapters_filename =  "emacsconf-2022-rms--what-id-like-to-see-in-emacs--answers--chapters.vtt"
answers_filename = "answers.wav"
animation_filename = "animation.webm"
def get_length(filename):
    result = subprocess.run(["ffprobe", "-v", "error", "-show_entries",
                             "format=duration", "-of",
                             "default=noprint_wrappers=1:nokey=1", filename],
        stdout=subprocess.PIPE,
        stderr=subprocess.STDOUT)
    return float(result.stdout)

def get_frames(filename):
    result = subprocess.run(["ffprobe", "-v", "error", "-select_streams", "v:0", "-count_packets",
                             "-show_entries", "stream=nb_read_packets", "-of",
                             "csv=p=0", filename],
        stdout=subprocess.PIPE,
        stderr=subprocess.STDOUT)
    return float(result.stdout)

answers_length = get_length(answers_filename)
# override base_times
times = np.asarray([  1.515875,  13.50, 52.32125 ,  81.368625, 116.66625 , 146.023125,
       161.904875, 182.820875, 209.92125 , 226.51525 , 247.93875 ,
       260.971   , 270.87375 , 278.23325 , 303.166875, 327.44925 ,
       351.616375, 372.39525 , 394.246625, 409.36325 , 420.527875,
       431.854   , 440.608625, 473.86825 , 488.539   , 518.751875,
       544.1515  , 555.006   , 576.89225 , 598.157375, 627.795125,
       647.187125, 661.10875 , 695.87175 , 709.750125, 717.359875])
fps = 30.0
times = np.append(times, get_length(animation_filename))
anim_spans = list(zip(times[:-1], times[1:]))
chapters = webvtt.read(chapters_filename)
if chapters[0].start_in_seconds == 0:
    vtt_times = [[c.start_in_seconds, c.text] for c in chapters]
else:
    vtt_times = [[0, "Introduction"]] + [[c.start_in_seconds, c.text] for c in chapters] 
vtt_times = vtt_times + [[answers_length, "End"]]
# Add ending timestamps
vtt_times = [[x[0][0], x[1][0], x[0][1]] for x in zip(vtt_times[:-1], vtt_times[1:])]
test_rate = 1.0

i = 0
concat_list = ""
groups = list(zip(anim_spans, vtt_times))
import ffmpeg
animation = ffmpeg.input('animation.webm').video
audio = ffmpeg.input('rms.opus')

for_overlay = ffmpeg.input('color=color=black:size=1280x720:d=%f' % answers_length, f='lavfi')
params = {"b:v": "1k", "vcodec": "libvpx", "r": "30", "crf": "63"}
test_limit = 1
params = {"vcodec": "libvpx", "r": "30", "copyts": None, "b:v": "1M", "crf": 24}
test_limit = 0
anim_rate = 1
import math
cursor = 0
if test_limit > 0:
    groups = groups[0:test_limit]
clips = []

# cursor is the current time
for anim, vtt in groups:
    padding = vtt[1] - cursor - (anim[1] - anim[0]) / anim_rate
    if (padding < 0):
        print("Squeezing", math.floor((anim[1] - anim[0]) / (anim_rate * 1.0)), 'into', vtt[1] - cursor, padding)
        clips.append(animation.trim(start=anim[0], end=anim[1]).setpts('PTS-STARTPTS')) 
    elif padding == 0:
        clips.append(animation.trim(start=anim[0], end=anim[1]).setpts('PTS-STARTPTS'))
    else:
        print("%f to %f: Padding %f into %f - pad: %f" % (cursor, vtt[1], (anim[1] - anim[0]) / (anim_rate * 1.0), vtt[1] - cursor, padding))
        cursor = cursor + padding + (anim[1] - anim[0]) / anim_rate
        clips.append(animation.trim(start=anim[0], end=anim[1]).setpts('PTS-STARTPTS').filter('tpad', stop_mode="clone", stop_duration=padding))
    for_overlay = for_overlay.overlay(animation.trim(start=anim[0], end=anim[1]).setpts('PTS-STARTPTS+%f' % vtt[0]))
    clips.append(audio.filter('atrim', start=vtt[0], end=vtt[1]).filter('asetpts', 'PTS-STARTPTS'))
args = ffmpeg.concat(*clips, v=1, a=1).output('output.webm', **params).overwrite_output().compile()
print(' '.join(f'"{item}"' for item in args))

import re
s = "12/9/21 11:23"
match = re.match('([0-9]+)/([0-9]+)/([0-9]+)( [0-9]+:[0-9]+)', s)
date = '20%s-%s-%s%s:00' % (match.group(3).zfill(2), match.group(1).zfill(2), match.group(2).zfill(2), match.group(4))
print(date)

import pandas as pd
df = pd.read_csv('filename.csv', encoding='utf-8', dtype=str, na_filter=False)