208 lines
9.4 KiB
Plaintext
208 lines
9.4 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 239,
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"source": [
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"import json\r\n",
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"\r\n",
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"# create a new scene graph\r\n",
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"def new_scene(name):\r\n",
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" # create empty neutrino data\r\n",
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" data = {\r\n",
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" \"graph\": {\r\n",
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" \"scene\": {\r\n",
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" \"meta\": {\r\n",
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" \"name\": name\r\n",
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" },\r\n",
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" \"objects\": {}\r\n",
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" },\r\n",
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" \"assets\": {}\r\n",
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" },\r\n",
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" \"meta\": {\r\n",
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" \"max_key\": 0\r\n",
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" }\r\n",
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" }\r\n",
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"\r\n",
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" # return that empty data\r\n",
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" return data\r\n",
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"\r\n",
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"# write the data to a JSON file\r\n",
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"def save_scene(data):\r\n",
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" clean_data = {\r\n",
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" \"graph\": data[\"graph\"]\r\n",
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" }\r\n",
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"\r\n",
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" # include cache if relevant\r\n",
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" if \"cache\" in data:\r\n",
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" clean_data[\"cache\"] = data[\"cache\"]\r\n",
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"\r\n",
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" filename = data[\"graph\"][\"scene\"][\"meta\"][\"name\"].replace(\" \", \"\") + \".json\"\r\n",
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" with open(filename, \"w\") as outfile:\r\n",
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" json.dump(clean_data, outfile, indent = 4)\r\n",
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"\r\n",
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"# get a new indexed object key and increment the scene's max key\r\n",
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"def add_key(data):\r\n",
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" # get the indexed key\r\n",
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" key = hex(data[\"meta\"][\"max_key\"] + 1)\r\n",
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"\r\n",
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" # index the max key\r\n",
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" data[\"meta\"][\"max_key\"] += 1\r\n",
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"\r\n",
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" return key\r\n",
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"\r\n",
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"# add an asset to the graph\r\n",
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"def add_asset(data, name):\r\n",
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" asset_data = {\r\n",
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" \"name\": {\"t\": \"name\", \"v\": name}\r\n",
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" }\r\n",
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" \r\n",
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" # add the asset to the graph\r\n",
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" data[\"graph\"][\"assets\"][add_key(data)] = asset_data\r\n",
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"\r\n",
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"# add an object to the scene\r\n",
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"def spawn_object(data, name, asset):\r\n",
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" object_data = {\r\n",
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" \"name\": {\"t\": \"name\", \"v\": name},\r\n",
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" \"asset\": {\"t\": \"asset\", \"v\": asset},\r\n",
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" \"trans\": {\"t\": \"trans\", \"v\": [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [1.0, 1.0, 1.0]]}\r\n",
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" }\r\n",
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"\r\n",
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" # get an asset key by the provided name\r\n",
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" for key, value in data[\"graph\"][\"assets\"].items():\r\n",
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" if value[\"name\"][\"v\"] == asset:\r\n",
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" object_data[\"asset\"][\"v\"] = f\"*{key}\"\r\n",
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"\r\n",
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" # add the object to the scene\r\n",
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" data[\"graph\"][\"scene\"][\"objects\"][add_key(data)] = object_data"
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],
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"outputs": [],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": 240,
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"source": [
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"# cache the scene\r\n",
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"def cache_scene(data):\r\n",
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" # add the cache object to the scene data\r\n",
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" data[\"cache\"] = {}\r\n",
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"\r\n",
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" containers = [\r\n",
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" data[\"graph\"][\"scene\"][\"objects\"],\r\n",
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" data[\"graph\"][\"assets\"]\r\n",
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" ]\r\n",
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"\r\n",
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" for objects in containers:\r\n",
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" # temp cache\r\n",
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" hash_cache = {}\r\n",
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"\r\n",
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" # hash all values\r\n",
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" for key, value in objects.items():\r\n",
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" for key, value in value.items():\r\n",
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" # ignore pointers\r\n",
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" if type(value) == str:\r\n",
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" is_pointer = value[0] == \"*\"\r\n",
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" else:\r\n",
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" is_pointer = False\r\n",
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" if not is_pointer:\r\n",
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" # convert into string and hash that\r\n",
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" value_hash = hash(str(value))\r\n",
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"\r\n",
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" # track in temp cache\r\n",
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" if value_hash not in hash_cache:\r\n",
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" hash_cache[value_hash] = {\"value\": value, \"count\": 1}\r\n",
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" else:\r\n",
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" hash_cache[value_hash][\"count\"] += 1\r\n",
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"\r\n",
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" # throw out all non-repeated values\r\n",
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" bad_keys = []\r\n",
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" for key, value in hash_cache.items():\r\n",
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" if value[\"count\"] < 2:\r\n",
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" bad_keys.append(key)\r\n",
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" for key in bad_keys:\r\n",
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" del hash_cache[key]\r\n",
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"\r\n",
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" # create hash objects for each repeated value\r\n",
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" for key, value in hash_cache.items():\r\n",
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" cache_pointer = f\"#{add_key(data)}\"\r\n",
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" data[\"cache\"][cache_pointer] = value[\"value\"]\r\n",
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" hash_cache[key][\"pointer\"] = cache_pointer\r\n",
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"\r\n",
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" # replace all instances of cached values in the graph with corresponding cache pointers\r\n",
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" for object_key, object_value in objects.items():\r\n",
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" for value_key, value_value in object_value.items():\r\n",
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" # ignore pointers\r\n",
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" if type(value_value) == str:\r\n",
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" is_pointer = value_value[0] == \"*\"\r\n",
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" else:\r\n",
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" is_pointer = False\r\n",
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" if not is_pointer:\r\n",
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" # convert into string and hash that\r\n",
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" value_hash = hash(str(value_value))\r\n",
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"\r\n",
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" # if this value is cached, replace it with its cache pointer\r\n",
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" if value_hash in hash_cache:\r\n",
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" objects[object_key][value_key] = hash_cache[value_hash][\"pointer\"]"
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],
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"outputs": [],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": 241,
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"source": [
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"# just returns a random string\r\n",
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"import random\r\n",
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"import string\r\n",
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"def random_string(length):\r\n",
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" return ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(length))\r\n",
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"\r\n",
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"# create test scene\r\n",
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"test_scene = new_scene(\"Neutrino Test Scene\")\r\n",
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"\r\n",
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"# populate assets\r\n",
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"asset_names = []\r\n",
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"for i in range(3):\r\n",
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" name = random_string(8)\r\n",
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" add_asset(test_scene, name)\r\n",
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" asset_names.append(name)\r\n",
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"\r\n",
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"# populate objects in scene\r\n",
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"for i in range(5):\r\n",
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" spawn_object(test_scene, random_string(8), random.choice(asset_names))\r\n",
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"\r\n",
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"# cache the scene\r\n",
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"cache_scene(test_scene)\r\n",
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"\r\n",
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"save_scene(test_scene)"
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],
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"outputs": [],
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"metadata": {}
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}
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],
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"metadata": {
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"orig_nbformat": 4,
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"language_info": {
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"name": "python",
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"version": "3.7.8",
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"mimetype": "text/x-python",
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"pygments_lexer": "ipython3",
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"nbconvert_exporter": "python",
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"file_extension": ".py"
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3.7.8 64-bit"
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},
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"interpreter": {
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"hash": "57baa5815c940fdaff4d14510622de9616cae602444507ba5d0b6727c008cbd6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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} |