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ImageLoader: spawn one thread per image. fix #93
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In the process of fixing #93, I realized that we were spawning new
threads to fetch images for each update (we only need one).
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@math2001
math2001 committed Nov 16, 2019
1 parent cf68b2c commit e462e8b
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Showing 6 changed files with 23 additions and 22 deletions.
2 changes: 1 addition & 1 deletion .gitattributes
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docs/ export-ignore
resources/
!resources/*.base64
!resources/*.base64
2 changes: 1 addition & 1 deletion live-testing/test.md
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# Why?
Why do you want to use fancy symbols in your standard monospace font? Obviously to have a fancy prompt like mine :-)

![prompt](https://github.com/gabrielelana/awesome-terminal-fonts/raw/master/why.png)
<!-- ![prompt](https://github.com/gabrielelana/awesome-terminal-fonts/raw/master/why.png) -->

And because when you live in a terminal a symbol can convey more informations in less space creating a dense and beautiful (for those who have a certain aesthetic taste) informative workspace

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36 changes: 18 additions & 18 deletions markdown2html.py
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Expand Up @@ -25,13 +25,6 @@
# does it stupidly throw them out? (we could implement something of our own)
executor = concurrent.futures.ThreadPoolExecutor(max_workers=5)

images_cache = {}


class LoadingError(Exception):
pass


def markdown2html(markdown, basepath, re_render, resources, viewport_width):
""" converts the markdown to html, loads the images and puts in base64 for sublime
to understand them correctly. That means that we are responsible for loading the
Expand Down Expand Up @@ -59,12 +52,7 @@ def markdown2html(markdown, basepath, re_render, resources, viewport_width):
# realpath: simplify that paths so that we don't have duplicated caches
path = os.path.realpath(os.path.expanduser(os.path.join(basepath, src)))

try:
base64, (width, height) = get_base64_image(path, re_render)
except FileNotFoundError as e:
base64, (width, height) = resources["base64_404_image"]
except LoadingError:
base64, (width, height) = resources["base64_loading_image"]
base64, (width, height) = get_base64_image(path, re_render, resources)

img_element["src"] = base64
if width > viewport_width:
Expand Down Expand Up @@ -100,22 +88,31 @@ def markdown2html(markdown, basepath, re_render, resources, viewport_width):
"<br/>", "<br />"
)

images_cache = {}
images_loading = []

def get_base64_image(path, re_render):
def get_base64_image(path, re_render, resources):
""" Gets the base64 for the image (local and remote images). re_render is a
callback which is called when we finish loading an image from the internet
to trigger an update of the preview (the image will then be loaded from the cache)
return base64_data, (width, height)
"""

def callback(path, future):
def callback(path, resources, future):
# altering images_cache is "safe" to do because callback is called in the same
# thread as add_done_callback:
# > Added callables are called in the order that they were added and are always
# > called in a thread belonging to the process that added them
# > --- Python docs
images_cache[path] = future.result()
try:
images_cache[path] = future.result()
except urllib.error.HTTPError as e:
images_cache[path] = resources['base64_404_image']
print("Error loading {!r}: {!r}".format(path, e))

images_loading.remove(path)

# we render, which means this function will be called again, but this time, we
# will read from the cache
re_render()
Expand All @@ -124,8 +121,11 @@ def callback(path, future):
return images_cache[path]

if path.startswith("http://") or path.startswith("https://"):
executor.submit(load_image, path).add_done_callback(partial(callback, path))
raise LoadingError()
# FIXME: submiting a load of loaders, we should only have one
if path not in images_loading:
executor.submit(load_image, path).add_done_callback(partial(callback, path, resources))
images_loading.append(path)
return resources['base64_loading_image']

with open(path, "rb") as fhandle:
image_content = fhandle.read()
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2 changes: 1 addition & 1 deletion resources/404.base64
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iVBORw0KGgoAAAANSUhEUgAAAGQAAAArCAYAAACO7C3tAAAABGdBTUEAALGOfPtRkwAAACBjSFJNAACHDgAAjBIAAPxoAACFkgAAeeQAAO3tAAA7IgAAIN+/WeXLAAAKqGlDQ1BJQ0MgUHJvZmlsZQAASMetl2dQFOkWhk/35EQaGAEJQ06C5Cg5DqAgGUwMM4QhjOPAkEyoLCq4oqiIgAldJCi4BkDWgIhiWhQT5gVZVNTrYkBUVG4Dl+Huj/1xq+6pOtVPnf76/U73nK/qHQD6Za5IlIrKAaQJM8Qhvh7sqOgYNukpEEEDlMAO9Lm8dJF7cHAg/GN8ugfI+PW26bgW/G8hz49P5wEgwRjH8dN5aRifwLKBJxJnAOD4WF0nK0M0zhswVhRjDWJcOc6Jk3x0nOMmuWNiTViIJ8b3Ach0LlecCED7E6uzM3mJmA4dj7G5kC8QYmyNsQsviYvtQ8fuway0tKXjvA9jw7j/0kn8m2acVJPLTZTy5LtMBNlLkC5K5ebA/zvSUiVTe2hhSU8S+4VgVwXsm1WmLA2QsjBuXtAUC/gT6yc4SeIXPsW8dM+YKeZzvQKmWJIS7j7FXPH0s4IMTtgUi5eGSPWFqfMCpfrxHCnHp3uHTnGCwIczxblJYZFTnCmImDfF6SmhAdNrPKV1sSRE2nOC2Ef6jmnp073xuNN7ZSSF+UnfK97LW9qPMFy6RpThIdURpQZP95zqK62nZ4ZKn83AhmqKk7n+wdM6wdJvAp4gACHEQxpwgQ1+4AWQEZ89PlfguVSUIxYkJmWw3bFTEs/mCHlms9iW5hbYBI6fucmf9MP9ibOEsMjTtdwUALfLAKj3dC0Sm926WgCW2nRN9xs2+sUArdd4EnHmZG181IEAVJAFRVDBzrQOGIIpWIItOIEbeIM/BEEYRMNi4EES1rcYsmAFrIECKIItsAPKYS8cgBo4AsegGU7DebgE1+Am3IVH0AsD8BqG4BOMIghCQhgIE1FBNBE9xASxROwRF8QbCURCkGgkFklEhIgEWYGsQ4qQEqQc2Y/UIr8ip5DzyBWkG3mA9CGDyHvkK4pD6agiqo7qo7NRe9QdDUDD0EVoIroMzUXz0c1oGVqFHkab0PPoNfQu2ou+RodxgKPhWDgtnCnOHueJC8LF4BJwYtwqXCGuFFeFa8C14jpxt3G9uDe4L3ginoln403xTng/fDieh1+GX4XfhC/H1+Cb8B342/g+/BD+B4FBUCOYEBwJHEIUIZGQRSgglBKqCScJFwl3CQOET0QikUU0INoR/YjRxGTicuIm4m5iI7GN2E3sJw6TSCQVkgnJmRRE4pIySAWkXaTDpHOkW6QB0mcyjaxJtiT7kGPIQvJacim5jnyWfIv8gjxKkaPoURwpQRQ+JYdSTDlIaaXcoAxQRqnyVAOqMzWMmkxdQy2jNlAvUh9TP9BoNG2aA20+TUDLo5XRjtIu0/poX+gKdGO6J30hXULfTD9Eb6M/oH9gMBj6DDdGDCODsZlRy7jAeMr4LMOUMZPhyPBlVstUyDTJ3JJ5K0uR1ZN1l10smytbKntc9obsGzmKnL6cpxxXbpVchdwpuR65YXmmvIV8kHya/Cb5Ovkr8i8VSAr6Ct4KfIV8hQMKFxT6mTimDtOTyWOuYx5kXmQOKBIVDRQ5ismKRYpHFLsUh5QUlKyVIpSylSqUzij1snAsfRaHlcoqZh1j3WN9naE+w31G/IyNMxpm3JoxojxT2U05XrlQuVH5rvJXFbaKt0qKylaVZpUnqnhVY9X5qlmqe1Qvqr6ZqTjTaSZvZuHMYzMfqqFqxmohasvVDqhdVxtW11D3VRep71K/oP5Gg6XhppGssV3jrMagJlPTRVOguV3znOYrthLbnZ3KLmN3sIe01LT8tCRa+7W6tEa1DbTDtddqN2o/0aHq2Osk6GzXadcZ0tXUnau7Qrde96EeRc9eL0lvp16n3oi+gX6k/nr9Zv2XBsoGHINcg3qDx4YMQ1fDZYZVhneMiEb2RilGu41uGqPGNsZJxhXGN0xQE1sTgcluk+5ZhFkOs4Szqmb1mNJN3U0zTetN+8xYZoFma82azd7O1p0dM3vr7M7ZP8xtzFPND5o/slCw8LdYa9Fq8d7S2JJnWWF5x4ph5WO12qrF6p21iXW89R7r+zZMm7k2623abb7b2tmKbRtsB+107WLtKu167BXtg+032V92IDh4OKx2OO3wxdHWMcPxmONfTqZOKU51Ti/nGMyJn3NwTr+ztjPXeb9zrwvbJdZln0uvq5Yr17XK9ZmbjhvfrdrthbuRe7L7Yfe3HuYeYo+THiOejp4rPdu8cF6+XoVeXd4K3uHe5d5PfbR9En3qfYZ8bXyX+7b5EfwC/Lb69XDUOTxOLWfI385/pX9HAD0gNKA84FmgcaA4sHUuOtd/7ra5j+fpzRPOaw6CIE7QtqAnwQbBy4J/m0+cHzy/Yv7zEIuQFSGdoczQJaF1oZ/CPMKKwx6FG4ZLwtsjZCMWRtRGjER6RZZE9kbNjloZdS1aNVoQ3RJDiomIqY4ZXuC9YMeCgYU2CwsW3ltksCh70ZXFqotTF59ZIruEu+R4LCE2MrYu9hs3iFvFHY7jxFXGDfE8eTt5r/lu/O38wXjn+JL4FwnOCSUJLxOdE7clDia5JpUmvRF4CsoF75L9kvcmj6QEpRxKGUuNTG1MI6fFpp0SKghThB1LNZZmL+0WmYgKRL3LHJftWDYkDhBXpyPpi9JbMhQxc3NdYij5SdKX6ZJZkfk5KyLreLZ8tjD7eo5xzsacF7k+ub8sxy/nLW9fobVizYq+le4r969CVsWtal+tszp/9UCeb17NGuqalDW/rzVfW7L247rIda356vl5+f0/+f5UXyBTIC7oWe+0fu8G/AbBhq6NVht3bfxRyC+8WmReVFr0bRNv09WfLX4u+3lsc8LmrmLb4j1biFuEW+5tdd1aUyJfklvSv23utqbt7O2F2z/uWLLjSql16d6d1J2Snb1lgWUtu3R3bdn1rTyp/G6FR0VjpVrlxsqR3fzdt/a47WnYq763aO/XfYJ99/f77m+q0q8qPUA8kHng+cGIg52/2P9SW61aXVT9/ZDwUG9NSE1HrV1tbZ1aXXE9Wi+pHzy88PDNI15HWhpMG/Y3shqLjsJRydFXv8b+eu9YwLH24/bHG07onag8yTxZ2IQ05TQNNSc197ZEt3Sf8j/V3urUevI3s98OndY6XXFG6UzxWerZ/LNj53LPDbeJ2t6cTzzf376k/dGFqAt3OuZ3dF0MuHj5ks+lC53unecuO18+fcXxyqmr9lebr9lea7puc/3k7za/n+yy7Wq6YXej5abDzdbuOd1nb7neOn/b6/alO5w71+7Ou9t9L/ze/Z6FPb33+fdfPkh98O5h5sPRR3mPCY8Ln8g9KX2q9rTqD6M/Gntte8/0efVdfxb67FE/r//1n+l/fhvIf854XvpC80XtS8uXpwd9Bm++WvBq4LXo9eibgn/J/6vyreHbE3+5/XV9KGpo4J343dj7TR9UPhz6aP2xfTh4+OmntE+jI4WfVT7XfLH/0vk18uuL0axvpG9l342+t/4I+PF4LG1sTMQVcyesAA5LNCEB4P0hAEY0APMmAFVm0hNPBDLp4ycI/oknffNE2AIcaMO8CJb+WFbmAehhycRuBbsBhLkBamUlzf9EeoKV5aQWrRmzJqVjYx8wL0gyAvjeMzY22jw29r0aa/YhQNunSS8+HkTsH0qJFoqYMS9kj+T93RED/BtQMACLL7YRYgAAAAlwSFlzAAAOxAAADsQBlSsOGwAAC/RJREFUeF7Vm3WoVU8Qx/c9u7sQC8VCBcUGUexEQUVFRRED7MbuVkxsBfUPG1swUcQCu7u7u+v3+6xn32/v3nPvO/X0/b6w+s6ePTu7M7Mzs7N7Y379C/E/w9u3b8W7d+/Ely9f5N/Pnz+X9VmyZBEZM2YUyZMnF+nSpRPp06eX9f8n+BLIqVOnZEmSJIlV8xt0SV2TJk0kY4LAt2/fxJEjR8SxY8fE2bNnxYMHD6QwoBUbGyvb/Pz5U8TExEiauXPnFiVLlhTlypUTlSpVEilSpJBt/gS2bt0qlUSNS+H79+9yXHXr1rVqwuFZIK9fvxY9evQQ165dE0mTJrVqf+P9+/eiUaNGYuzYsVaNP5w4cUJMmDBB0vz8+bNIliyZFDjMp+hgOpQfP35IIaZMmVKulEGDBokKFSpYrRIOhw4dEkOGDJG0dYEwJlb0lClTRPXq1a3acHgWyKRJk8SGDRvCzAJagMnYtWuXVeMdaNnMmTPFzp07RerUqaXg7YQQCbpwPnz4IGrWrCl69eolcubMabUIFtDo2LGjXL3wQAfvatSoIcaNG2fV2CN0TTkEBDdu3ChNg2KQYhJa0L17d/m3X/Ts2VPs3btXZMiQQU4QjTOFoZiuig7a8g0rij72798vevfuHdYuKKxcuVLcvHlTjlXnCwqB4jrhiyeBjBo1Ko5BCkwSYVSpUkU0aNDAqvUGzFKXLl3E7du3RZo0aWyFwCRp9+nTJ/H161dZ+Js63tkJh77u3r0rOnXqJDU2SDDWFStWiLRp04aMl3FgNaDpZGW6NlmrV68W8+bNi9MCBZiAgBYuXCgKFixo1XoDAsfkYaZMYeC4P378KDJnzizKli0rsmbNKjJlyiTbvXz5UhYcP+YOAehKA5gu32PH8XFm/17AmPr37y/pEjyoPqGFopQqVUqaXtPX2sGVQN68eSPatWsnnStmQAfvWrZsKfr27WvVeMOZM2dE165dpTM2VyCaBjM7d+4sateuLfLmzWu9DcX9+/elqZs7d26I71GAgaykWbNmSaH6xZ49e8SYMWMkT8wxP3v2TKxZs0YULVrUqo0OVwLBIaIFpuaiBSxHCPtFvXr1pOnRBc4QiVrwAzNmzHC8AjEj+CGUhf70MdMfgoKZfkBESXiPhVCRH2DMmMVmzZqJfv36yToncOxDTp48KUM6Uxgq9sfm+8WWLVvEixcvwpY2NFgxw4cPd2UO8+fPL7/hW/rQAQ2YuXbtWqvGG+bMmSMZrwsDIPA8efKIDh06WDXO4EggmAn8BjZZB1qAI69YsWLU2Nop8BswTwc0WIHNmzeXmzy34JumTZvKPkxjgB/ct2+f9eQep0+flivMTklB69atpX9zA0cCWb58ubhw4ULYsleay6bLL/AdhIymvVchI/G9V+BzUCZ9lUADWrdu3ZIbT7dASWfPni0FbQYOKCmK0LhxY6vGOeIVCA5y/fr1IlWqVCGMQtuwzW3atJH5I79A2wgWzMnhT9Bwv2jYsKF05DqgRfqF9I9bYF6vXLkSlpJB6AhrwIABVo07xCsQQlAkbkYPaEaZMmWkQPyC6AmmmKuDyUEXp+kXCBU6utlSqwTazMcpSGwSxuohLqBvhIE/zZEjh1XrDlEFQpLs4sWL0iyZjGIwmAIm5BdoLubKTFLCwNKlSweStSUTXLx4cdmnDsYPbTcCGT16tByrPl6lpIS3fpQ0okDYYK1atUo6Ph0QhoGVK1f25GTtgFY9evQoTCBEKiVKlAjb83gBCkRf9KmDFcheAfPrBKRfjh8/bht8oLStWrUKC37cIKJA5s+fH9HJMjm0JCjg0KFhLn+e8+XLZ9X4B32ZaRVoIBQnfoSQHL6osenA15E2YsPqB7YCIaLatm2blLTJJAiz2QoS9+7dC1sd0CIvhKkJCqRZ0GxdIAClYwzxYdmyZeLOnTth0aZSUjcbwEiw3am3bdtWEoaIAs0wVdj06dOnh5gRbOfixYvl2Yhej71mcxRfOoXwkRyZvtSZJDvzyZMni8KFC1u1/sAqGDZsmFQqXQEwmYSoAwcOtGrC8eTJExmp4c/MAAcnz9mQ6TvIFMAX+KZ/Az3acnBmImyFLFmyRMbmpu/AkZNuJ4Vs2nTenT9/Xp7oHT16NK7wzOlefLALd5kodAi3gwKrwxw7gDbhbyQwPw6dGIspDJSRg68WLVpYtf8BQZFq0nlCIeOBgO0QwgX2HMTXDNq0kaQH6tSpI4oUKWLV/Afa8g0rikmrwrMdA0yQwjDpMVlMiZPvnQIlY2XQtw5oM4ZI2Lx5s7h+/XrYWOgHYbVv3952nAgPHtjxxTTRCiECIbYmurKLdliqHO4kBOwEAhCIuVL9QAnEBLTRZjuQxl+6dKlso48RYWB6OB9nPxYU4gRy8OBBsXv3bilBnTAaoJZsQgFTYGotwAeZ+wY/oC/mYgLazNsOU6dOjUt46nyhr2zZsgXiyHVIgeB0SB6qgx4FBsq78uXLi2rVqlm1wQPfZAqEceDY3WzY4gMZB/rU5wigbXc7hnD8wIEDtslDBMLZUJA+DkiBIAyiKrRAB4PPnj27jD7MSejAJppOWSFSvQ7MYaQVAhODAqbX3BgCGGzm49gosjowc6aS0kfVqlXjzbFF838mrxViL1++LLZv3y6ZajKdgRYqVEi8evVKRgt2hUzp4cOHpQ02mc8zdvbSpUtx7Ykybty4YbX4DcJduxXC6owW/bgFTKZPc57QZhXoWLdunYw2YarZnmfufJ07dy6EF3ohxCbChIfm9wgDHvBetYeHjC/m3wjiF1dTiPlN0BmCYsB2GgwUMbSZNjpx9Q1aRl8Ajec6ztChQ+Uz2LRpk5g4cWJIzopvaTtixAhRq1Ytq9YfiCChY254UaY+ffrEha5YBgIYMtCmb1G8wFTRTs3RBP3zDr6oZwV4gVBQWPU9Y2B/F0tFNHMDU7DjarmbhXcU+tGJAvVMH6o9f6tBKrDZVAJV4Fvac+UoKHDjhH71cUITOnqkpN7r7RTU92wu4+ML/6tvdMBX5qt/D1/kOzuiOvjYSYnUD/XxteUGCUWtIgXMBSbVrPcCGHD16tUw241AcOhmujwaX+zmFKlE6seurayX//5lYNI4K8cE6EAgZFaDuEOFSeBegOloEVSBAgUC3e/4gTRZFLTQT9HNjQ6zb7t2+CnOKli6+ns2cTg6Ug1+wdk5JkJpIoAWNEnLR/IV+tjdFtWHHcy+VbtYBkTkgU30WrB/eqcKPKP1Zv8wxgR+hEjH7AMHTJbVL7jmaUZS0EIZzJ02c2GM+pi9lGh8seM7q9XzZWsddEFGF5OgL30mVaxYMbFgwQKrJjIYXLdu3WTOSO+Dvnk3cuRIz9HWjh075CVnMwvB+DBXXKjTM81BAZ/FjUZSQ3rKBvPJfLiDZiIQH4K0I4WAaIgTwCxuEcIkvR8YiCNetGiRePjwoVXrHJxEksGmD10Y0GDcrMyEEAYwI0cF6kx/qRCIQOyIKkR7Z4ILyQzUFCLMfPz4sRg/frxV4xx8Q6rbLrpC+EFc8IsEL3xJFFGWAkzjpiH2VB8wmo2tZ6PGMsc0qrjdDjCaPBS38GlrZiHomwzC4MGDIyYV/xYSlUAAZ9JEPQhFBwzFKVNPhhXbjKMmeiIFQeECAhczuBOFTyNcNhODgD4416lfv75Vk3gQiFNHW2ECGow2KqCpHL9yjOkG5HlgOmczen8KmDTsP2BfocwRNluvRxCmMBgraaJp06bZHrYFCe4mcKtT3f1VID/HUTI/+zOR6FYIYJPIOTvRFgw0dYa9BIJS0RiCoADqeEcb00zRF8LjIC6hheEViVIggN9+8ENPzmgIE+2iOBiu0g6qmCuCb/iW0JPkJeGv3x8UJSQSrUAAB2OcZ3MLBmD7MYNOQmna0Fb5In5MRLaXC36JGYEIhMmjgZybqJ+VUXhGu/2Cmy6YMK73s9HET3BTBZpES2wcKfxNHe8QBtc6uUnIj3xIp7OC/iTUOO34EilKDGynzqYNbdQnjaCw59zNCgrQYLPHxbanT5/K824KY+AiHBfrOOvG5OXKlSvwI1Y3gOkcHzA23ZTi7/jFmX7+8xtC/AOF/82HDx1fAgAAAABJRU5ErkJggg==
data:image/png;base64,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
1 change: 1 addition & 0 deletions resources/convertresources.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,7 @@ def make_cache(image_name):
width, height = get_image_size(png)
png.seek(0)
base64.write(bytes("{}\n{}\n".format(width, height), encoding="utf-8"))
base64.write(b'data:image/png;base64,')
base64.write(b64encode(png.read()))


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