self.threshold:\\n self.listening = False\\n return True \\n except (KeyboardInterrupt, SystemExit):\\n self.stream.stop_stream()\\n self.stream.close()\\n sys.exit()\\n except:\\n # if something fails then we return False\\n return False\\n\\n def detect_keyword(self, audio_stream):\\n \\\"\\\"\\\"\\n Normalizes the audio_stream argument and detects whether or not it contains the key word\\n\\n Args:\\n audio_stream (array): An audio time series\\n\\n Returns:\\n True if the key word is detected, otherwise False\\n \\\"\\\"\\\"\\n result, confidence = self._get_prediction(audio_stream)\\n\\n if result == 0 and confidence > self.threshold:\\n return True\\n return False\\n\\n def _get_audio_input_stream(self):\\n stream = pyaudio.PyAudio().open(\\n format=pyaudio.paInt16,\\n channels=1,\\n rate=self.fs,\\n input=True,\\n frames_per_buffer=self.chunk_samples,\\n input_device_index=self.device_index,\\n stream_callback=self._callback)\\n return stream\\n\\n def _get_default_config(self):\\n \\\"\\\"\\\"The default config assumes that all the default arguments for the Somnus CLI were used\\\"\\\"\\\"\\n return {\\n 'data_shape': (101, 40, 1), \\n 'sample_duration': 1.,\\n 'n_filters': 40,\\n 'win_length': 400,\\n 'win_hop': 160\\n }\\n\\n def _callback(self, in_data, frame_count, time_info, status): \\n data0 = np.frombuffer(in_data, dtype='int16')\\n \\n self.data = np.append(self.data,data0) \\n if len(self.data) > self.feed_samples:\\n self.data = self.data[-self.feed_samples:]\\n # Process data async by sending a queue.\\n if self.listening:\\n self.q.put(self.data)\\n return (in_data, pyaudio.paContinue)\\n\\n def _setup_stream(self):\\n \\\"\\\"\\\" \\n Initialize the audio stream for continuous listening\\n \\\"\\\"\\\"\\n self.stream = self._get_audio_input_stream()\\n self.listening = True\\n self.q = Queue()\\n self.data = np.zeros(self.feed_samples, dtype='int16')\\n\\n def _get_prediction(self, audio_stream):\\n \\\"\\\"\\\"\\n Predicts the class of the audio time series\\n\\n Args:\\n audio_stream (array): An audio time series\\n\\n Returns:\\n Returns the predicted class and the confidence the model has in its prediction\\n \\\"\\\"\\\"\\n data = melnormalize(audio_stream, self.n_filters, self.win_length, self.win_hop)\\n data = np.expand_dims(data, axis=0)\\n\\n preds = self.model.predict(data)\\n res = np.argmax(preds)\\n\\n return res, max(preds)\\n\"\n },\n {\n \"alpha_fraction\": 0.5801281929016113,\n \"alphanum_fraction\": 0.6023504137992859,\n \"avg_line_length\": 33.16058349609375,\n \"blob_id\": \"4e4c3ee7d65368b9c2fd8e666d1d62da713d0bc2\",\n \"content_id\": \"691c708eb6bad06b27db5ac4e99409b82574e84a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4680,\n \"license_type\": \"permissive\",\n \"max_line_length\": 125,\n \"num_lines\": 137,\n \"path\": \"/somnus/models.py\",\n \"repo_name\": \"Skuldur/somnus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nfrom tensorflow.keras.layers import Dense, GRU, Bidirectional, Input, Dropout, MaxPooling2D, Conv2D, Flatten, TimeDistributed\\nfrom tensorflow.keras.models import Model, load_model\\nfrom tensorflow.keras.optimizers import Adam\\nfrom tensorflow.keras.callbacks import ReduceLROnPlateau, ModelCheckpoint\\nfrom tensorflow.keras import losses\\n\\nclass BaseModel():\\n def __init__(self):\\n self.model = None\\n self.filepath = ''\\n\\n def compile(self, learning_rate):\\n opt = Adam(lr=learning_rate)\\n self.model.compile(loss='categorical_crossentropy', optimizer=opt, metrics=[\\\"accuracy\\\"])\\n\\n def train(self, data, labels, val_data, val_labels, epochs, save_best, batch_size):\\n callbacks = []\\n reduce_lr = ReduceLROnPlateau(monitor='val_loss', factor=0.2,\\n patience=5, min_lr=0.00001)\\n callbacks.append(reduce_lr)\\n\\n if save_best:\\n checkpoint = ModelCheckpoint(\\n self.filepath,\\n monitor='loss',\\n verbose=0,\\n save_best_only=True,\\n mode='min'\\n )\\n callbacks.append(checkpoint)\\n\\n self.model.fit(\\n x=data,\\n y=labels,\\n validation_data=(val_data, val_labels),\\n batch_size=batch_size,\\n epochs=epochs,\\n verbose=1,\\n shuffle=True,\\n callbacks=callbacks\\n )\\n\\n def predict(self, input):\\n p = self.model.predict(input)\\n\\n return p.reshape(-1)\\n\\n def save(self, name):\\n self.model.save(name)\\n\\n def load(self, weights_path):\\n self.model = load_model(weights_path)\\n\\n\\nclass CnnTradFPool(BaseModel):\\n def __init__(self, input_shape):\\n \\\"\\\"\\\"\\n Function creating the model's graph in Keras.\\n \\n Argument:\\n input_shape: shape of the model's input data (using Keras conventions)\\n \\\"\\\"\\\"\\n self.filepath = \\\"cnn-trad-f-pool-{epoch:02d}-{loss:.4f}.hdf5\\\"\\n \\n X_input = Input(shape = input_shape)\\n\\n conv1 = Conv2D(64, kernel_size=(66, 8), strides=1, padding='same', activation='relu')(X_input)\\n drop1 = Dropout(0.2)(conv1)\\n maxpool = MaxPooling2D(pool_size=[3, 3], strides=[3,3], padding='same')(drop1)\\n\\n conv2 = Conv2D(64, kernel_size=(32, 4), strides=1, padding='same', activation='relu')(maxpool)\\n drop2 = Dropout(0.2)(conv2)\\n flattened = Flatten()(drop2)\\n\\n dense = Dense(3, activation='softmax')(flattened)\\n\\n self.model = Model(inputs = X_input, outputs = dense)\\n\\n\\nclass CnnOneFStride(BaseModel):\\n def __init__(self, input_shape):\\n \\\"\\\"\\\"\\n Function creating the model's graph in Keras.\\n \\n Argument:\\n input_shape: shape of the model's input data (using Keras conventions)\\n \\\"\\\"\\\"\\n self.filepath = \\\"cnn-one-f-stride-{epoch:02d}-{loss:.4f}.hdf5\\\"\\n\\n X_input = Input(shape = input_shape)\\n\\n conv1 = Conv2D(186, kernel_size=(101, 8), strides=(1,4), padding='valid', activation='relu')(X_input)\\n drop1 = Dropout(0.2)(conv1)\\n flattened = Flatten()(drop1)\\n\\n dense = Dense(128, activation='relu')(flattened)\\n dense = Dense(128, activation='relu')(dense)\\n dense = Dense(3, activation='softmax')(dense)\\n\\n self.model = Model(inputs = X_input, outputs = dense)\\n\\n\\nclass CrnnTimeStride(BaseModel):\\n def __init__(self, input_shape):\\n \\\"\\\"\\\"\\n Function creating the model's graph in Keras.\\n \\n Argument:\\n input_shape: shape of the model's input data (using Keras conventions)\\n \\\"\\\"\\\"\\n self.filepath = \\\"crnn-time-stride-{epoch:02d}-{loss:.4f}.hdf5\\\"\\n \\n X_input = Input(shape = input_shape)\\n\\n conv1 = Conv2D(32, kernel_size=(20, 5), strides=(8,2), padding='same', activation='relu')(X_input)\\n bigru1 = TimeDistributed(Bidirectional(GRU(units=32, return_sequences=True, unroll=True)))(conv1)\\n bigru2 = TimeDistributed(Bidirectional(GRU(units=32, unroll=True)))(bigru1)\\n flatten = Flatten()(bigru2)\\n dense1 = Dense(64, activation='relu')(flatten)\\n output = Dense(3, activation='softmax')(dense1)\\n\\n self.model = Model(inputs = X_input, outputs = output)\\n\\n\\n# Model utils\\ndef get_model(model_name, shape):\\n if model_name == 'cnn-one-stride':\\n model = CnnOneFStride(input_shape=shape)\\n elif model_name == 'cnn-trad-pool':\\n model = CnnTradFPool(input_shape=shape)\\n elif model_name == 'crnn-time-stride':\\n model = CrnnTimeStride(input_shape=shape)\\n else:\\n raise ValueError(\\\"Model type %s not supported\\\" % model)\\n\\n return model\\n\"\n },\n {\n \"alpha_fraction\": 0.6593939661979675,\n \"alphanum_fraction\": 0.6840404272079468,\n \"avg_line_length\": 32,\n \"blob_id\": \"c91e1a4dd64527659f0e406f1a2db94de9360937\",\n \"content_id\": \"a852fb9285edf2d5cd23eace813d45954a816652\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2475,\n \"license_type\": \"permissive\",\n \"max_line_length\": 102,\n \"num_lines\": 75,\n \"path\": \"/somnus/utils.py\",\n \"repo_name\": \"Skuldur/somnus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport glob\\nfrom pathlib import Path\\n\\nimport numpy as np\\nfrom pydub import AudioSegment\\nfrom tqdm import tqdm\\n\\nSUPPORTED_AUDIO_EXTENSIONS = ['.wav', '.mp3', '.flac', '.ogg', '.flv', '.wma', '.aac']\\n\\n# Used to standardize volume of audio clip\\ndef match_target_amplitude(sound, target_dBFS):\\n change_in_dBFS = target_dBFS - sound.dBFS\\n return sound.apply_gain(change_in_dBFS)\\n\\n# Load raw audio files for speech synthesis\\ndef load_raw_audio(base_dir, length=1):\\n base = AudioSegment.silent(duration=length * 1000)\\n def load_directory(audio_dir, loop=False):\\n audio_segments = []\\n for path in Path(os.path.join(base_dir, audio_dir)).rglob('*.*'):\\n if path.suffix in SUPPORTED_AUDIO_EXTENSIONS:\\n audio_format = path.suffix.split('.')[-1]\\n segment = AudioSegment.from_file(path.absolute(), format=audio_format).set_channels(1)\\n\\n if loop:\\n segment = base.overlay(segment, loop=True)\\n audio_segments.append(segment)\\n\\n return audio_segments\\n\\n activates = load_directory('positives')\\n backgrounds = load_directory('backgrounds', loop=True)\\n negatives = load_directory('negatives')\\n\\n return activates, negatives, backgrounds\\n\\ndef create_positive_example(background, activate, time_shift):\\n background_var = np.random.randint(-15, 10)\\n background = background + background_var\\n\\n background = background.overlay(activate, position = time_shift)\\n\\n background = match_target_amplitude(background, -20.0)\\n\\n background = background.set_frame_rate(16000)\\n\\n return background\\n\\ndef create_negative_example(background, dummy, negative, time_shift):\\n background_var = np.random.randint(-15, 10)\\n background = background + background_var\\n background = background.overlay(dummy - 100)\\n\\n if len(negative) - 1000 <= 0:\\n random_start = np.random.randint(0, 300)\\n else:\\n random_start = np.random.randint(0, len(negative) - 1000)\\n\\n background = background.overlay(negative[random_start:], position = time_shift)\\n\\n background = match_target_amplitude(background, -20.0)\\n\\n background = background.set_frame_rate(16000)\\n\\n return background\\n\\ndef create_silent_example(background, dummy):\\n background_var = np.random.randint(-15, 10)\\n background = background + background_var\\n background = background.overlay(dummy - 100)\\n\\n background = background.set_frame_rate(16000)\\n\\n return background\\n\"\n },\n {\n \"alpha_fraction\": 0.8703703880310059,\n \"alphanum_fraction\": 0.8703703880310059,\n \"avg_line_length\": 5.875,\n \"blob_id\": \"7a2ad2305f4a5bc595e5f3d254a05da38bf3dc1c\",\n \"content_id\": \"88f3667279bd708db49897a09b68f95185eb5800\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 54,\n \"license_type\": \"permissive\",\n \"max_line_length\": 10,\n \"num_lines\": 8,\n \"path\": \"/requirements.txt\",\n \"repo_name\": \"Skuldur/somnus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"numpy\\npydub\\npyaudio\\nscipy\\nlibrosa\\ntensorflow\\nfire\\ntqdm\"\n },\n {\n \"alpha_fraction\": 0.6249088644981384,\n \"alphanum_fraction\": 0.6331486105918884,\n \"avg_line_length\": 41.3271598815918,\n \"blob_id\": \"64272666ba29a9e37456ef993177a69a4153525a\",\n \"content_id\": \"cf927d4a633b6f831d7a1f8569ac5e97bc7ef9a7\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 13714,\n \"license_type\": \"permissive\",\n \"max_line_length\": 160,\n \"num_lines\": 324,\n \"path\": \"/cli/cli.py\",\n \"repo_name\": \"Skuldur/somnus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import json\\nfrom functools import wraps\\nfrom pathlib import Path\\nfrom types import FunctionType\\nimport os\\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' \\n\\nimport fire\\nfrom pydub import AudioSegment\\nimport numpy as np\\nfrom tqdm import tqdm\\nimport pyaudio\\n\\nfrom somnus.utils import load_raw_audio, create_positive_example, create_negative_example, create_silent_example\\n\\n\\nCONFIG_ERROR_MSGS = {\\n 'raw_audio': 'Raw Audio Directory is not set. ',\\n 'augmented_audio': 'Augmented Audio Directory is not set. ',\\n 'preprocessed_data': 'Preprocessed Data Directory is not set. '\\n}\\n\\ndef config_wrapper(method, config):\\n @wraps(method)\\n def wrapped(*args, **kwargs):\\n for key in CONFIG_ERROR_MSGS.keys():\\n if not config.get(key):\\n raise ValueError(CONFIG_ERROR_MSGS[key] + 'Please run \\\\'somnus configure\\\\' to set value!')\\n \\n method(*args, **kwargs)\\n return wrapped\\n\\nclass ConfigWrapper(type):\\n def __new__(meta, classname, bases, classDict):\\n newClassDict = {}\\n config = classDict['config']\\n\\n # Wraps every public method except configure so that the user needs to run 'somnus configure'\\n # before using the other methods\\n for attributeName, attribute in classDict.items():\\n if isinstance(attribute, FunctionType) and attributeName != 'configure' and attributeName[0] != '_': \\n # replace it with a wrapped version\\n attribute = config_wrapper(attribute, config)\\n newClassDict[attributeName] = attribute\\n return type.__new__(meta, classname, bases, newClassDict)\\n\\n\\nclass SomnusCLI(metaclass=ConfigWrapper):\\n config = {}\\n\\n def __init__(self, numpy_seed=1, base_dir='.'):\\n np.random.seed(numpy_seed)\\n\\n self._load_config()\\n \\n def _load_config(self):\\n config = {}\\n config_file = os.path.join(Path.home(), '.somnus', 'config.json')\\n if os.path.isfile(config_file):\\n with open(config_file, 'r') as file:\\n config = json.load(file)\\n\\n # we copy the values over so that the config wrapper has a reference to the correct config\\n for key, val in config.items():\\n self.config[key] = val\\n\\n def configure(self):\\n config = {}\\n config['raw_audio'] = input(\\\"Raw Audio Directory [%s]: \\\" % self.config.get('raw_audio')) or self.config.get('raw_audio')\\n config['augmented_audio'] = input(\\\"Augmented Audio Directory [%s]: \\\" % self.config.get('augmented_audio')) or self.config.get('augmented_audio')\\n config['preprocessed_data'] = input(\\\"Preprocessed Data Directory [%s]: \\\" % self.config.get('preprocessed_data')) or self.config.get('preprocessed_data')\\n\\n config_file = os.path.join(Path.home(), '.somnus', 'config.json')\\n os.makedirs(os.path.dirname(config_file), exist_ok=True)\\n with open(config_file, 'w') as file:\\n file.write(json.dumps(config))\\n\\n def augment_audio(self, duration=1, positive=90000, negative=120000, background=90000):\\n \\\"\\\"\\\"\\n Method to create the audio dataset for keyword recognition.\\n\\n For each audio clip that is generated the following algorithm is executed:\\n\\n 1. Select an audio clip of background noise\\n 2. Randomly increase of decrease the DB of the background noise\\n 3. Overlay a voice clip where applicable with a random shift to the right\\n 4. Standardize the volume of the audio clip\\n 5. Set the frame rate of the resulting audio clip to 16k\\n 6. Write the audio to a file in processed_audio/\\n\\n :param duration: The duration of the audio clips in seconds\\n :param positive: The number of positive examples\\n :param negative: The number of negative examples\\n :param background: The number of examples containing only background noise\\n \\\"\\\"\\\"\\n\\n print('Please wait while we load the raw audio files...')\\n positives, negatives, backgrounds = load_raw_audio(self.config['raw_audio'], duration)\\n\\n if len(positives) == 0:\\n raise IndexError('There are no supported audio files in %s/%s' % (self.config['raw_audio'], 'positives'))\\n if len(negatives) == 0:\\n raise IndexError('There are no supported audio files in %s/%s' % (self.config['raw_audio'], 'negatives'))\\n if len(backgrounds) == 0:\\n # Add a single silent background audio segment\\n backgrounds.append(AudioSegment.silent(duration=duration * 1000))\\n\\n aug_path = self.config['augmented_audio']\\n print('Augmenting positive audio samples:')\\n for i in tqdm(range(positive)):\\n time_shift = np.random.randint(200)\\n segment = create_positive_example(backgrounds[i % len(backgrounds)], positives[i % len(positives)], time_shift)\\n\\n segment.export(os.path.join(aug_path, 'positive_%s.wav' % i), format='wav')\\n\\n print('Augmenting negative audio samples:')\\n for i in tqdm(range(negative)):\\n time_shift = np.random.randint(600)\\n segment = create_negative_example(backgrounds[i % len(backgrounds)], positives[0], negatives[i % len(negatives)], time_shift)\\n\\n segment.export(os.path.join(aug_path, 'negative_%d.wav' % i), format='wav')\\n\\n print('Augmenting background audio audio samples:')\\n for i in tqdm(range(background)):\\n segment = create_silent_example(backgrounds[i % len(backgrounds)], positives[0])\\n\\n segment.export(os.path.join(aug_path, 'background_%s.wav' % i), format='wav')\\n\\n def preprocess(self, filters=40, show_progress=True, split=(0.9, 0.05, 0.05), win_length=0.025, win_hop=0.01):\\n \\\"\\\"\\\"\\n Preprocess the augmented audio and create a dataset of numpy arrays ready for use with the keyword detection models\\n\\n :param filters: The number of filters in each frame\\n :param show_progress: Boolean option to decide whether to show a progress bar (NOTE: showing progress bar may slow down processing)\\n :param split: How much data should be in the training, validation, and test datasets. Values must add up to 1.\\n :param win_length: The length of each window in seconds\\n :param win_hop: the time between the start of each consecutive window.\\n \\\"\\\"\\\"\\n from somnus.preprocess_audio import create_dataset\\n assert sum(split) == 1\\n\\n augmented_path = self.config['augmented_audio']\\n preprocessed_path = self.config['preprocessed_data']\\n frame_rate = 16000\\n\\n win_length = int(win_length * frame_rate)\\n win_hop = int(win_hop * frame_rate)\\n\\n data, labels = create_dataset(augmented_path, filters, show_progress, win_length, win_hop)\\n\\n # randomly shuffle the data\\n p = np.random.permutation(len(data))\\n data = data[p]\\n labels = labels[p]\\n\\n train_data, val_data, test_data = np.split(data, [int(len(data)*split[0]), int(len(data)*(split[0] + split[1]))])\\n train_labels, val_labels, test_labels = np.split(labels, [int(len(labels)*split[0]), int(len(labels)*(split[0] + split[1]))])\\n\\n np.save(os.path.join(preprocessed_path, 'train_data.npy'), train_data)\\n np.save(os.path.join(preprocessed_path, 'train_labels.npy'), train_labels)\\n np.save(os.path.join(preprocessed_path, 'validation_data.npy'), val_data)\\n np.save(os.path.join(preprocessed_path, 'validation_labels.npy'), val_labels)\\n np.save(os.path.join(preprocessed_path, 'test_data.npy'), test_data)\\n np.save(os.path.join(preprocessed_path, 'test_labels.npy'), test_labels)\\n\\n audio_config = {\\n 'data_shape': train_data[0].shape, \\n 'sample_duration': (train_data[0].shape[0]-1) / (frame_rate // win_hop),\\n 'n_filters': filters,\\n 'win_length': win_length,\\n 'win_hop': win_hop\\n }\\n\\n print(\\\"\\\\nUse the following config as the audio_config parameter in Somnus when using models trained with this dataset: \\\\n\\\\n%s\\\" \\n % json.dumps(audio_config, indent=2, sort_keys=True))\\n\\n def train(self, model_name='cnn-one-stride', epochs=200, output='saved_model.h5',\\n save_best=False, batch_size=64, lr=0.0001):\\n \\\"\\\"\\\"\\n Trains a small-footprint keyword detection model using augmented WAV files\\n\\n :param model_name: The name of the model we want to train\\n :param epochs: The number of epochs\\n :param output: The name of the file the final model should be saved to\\n :param save_best: Whether or not the model should save the best model throughout the training process\\n :param batch_size: The size of each mini batch\\n :param lr: The initial learning rate\\n \\\"\\\"\\\"\\n from somnus.models import get_model\\n\\n preprocessed_path = self.config['preprocessed_data']\\n\\n train_data = np.load(os.path.join(preprocessed_path, 'train_data.npy'))\\n train_labels = np.load(os.path.join(preprocessed_path, 'train_labels.npy'))\\n val_data = np.load(os.path.join(preprocessed_path, 'validation_data.npy'))\\n val_labels = np.load(os.path.join(preprocessed_path, 'validation_labels.npy'))\\n\\n shape = train_data[0].shape\\n model = get_model(model_name, shape)\\n model.compile(lr)\\n model.train(train_data, train_labels, val_data, val_labels, epochs, save_best, batch_size)\\n model.save(output)\\n\\n def test(self, model='saved_model.h5'):\\n \\\"\\\"\\\"\\n Tests a trained model against a test dataset\\n\\n :param model: The file containing the model we want to test\\n \\\"\\\"\\\"\\n from somnus.models import BaseModel\\n\\n model_path = model\\n\\n preprocessed_path = self.config['preprocessed_data']\\n\\n data = np.load(os.path.join(preprocessed_path, 'test_data.npy'))\\n labels = np.load(os.path.join(preprocessed_path, 'test_labels.npy'))\\n\\n model = BaseModel()\\n\\n model.load(model_path)\\n\\n wrong = 0\\n for idx in tqdm(range(len(data))):\\n audio = data[idx]\\n label = labels[idx]\\n p = model.predict(np.expand_dims(audio, axis=0))\\n\\n if np.argmax(p) != np.argmax(label):\\n wrong += 1\\n\\n percentage = 100*((len(data)-wrong) / len(data))\\n print(\\\"\\\\n Test dataset accuracy is %s percent\\\" % percentage)\\n\\n def list_microphones(self):\\n \\\"\\\"\\\"\\n List all microphones connected to the device\\n \\\"\\\"\\\"\\n p = pyaudio.PyAudio()\\n for i in range(p.get_device_count()):\\n print(\\\"Input Device id \\\", i, \\\" - \\\", p.get_device_info_by_host_api_device_index(0, i).get('name'))\\n\\n def cleanup(self):\\n \\\"\\\"\\\"\\n Removes all the data files that have been generated by the CLI in the Augmented Audio Directory \\n and the Preprocessed Data Directory\\n \\\"\\\"\\\"\\n paths = [self.config['augmented_audio'], self.config['preprocessed_data']]\\n\\n for path in paths:\\n filelist = [ f for f in os.listdir(path)]\\n print(\\\"Deleting files from %s:\\\" % path)\\n for f in tqdm(filelist):\\n os.remove(os.path.join(path, f))\\n\\n def quantize_model(self, model='saved_model.h5', output='saved_model.tflite', quantization='cpu'):\\n \\\"\\\"\\\"\\n Converts the model to TFLite and quantizes it. This reduces the size of the model by a factor of 2-3, \\n while barely affecting the accuracy of the model\\n\\n :param model: The file containing the model we want to convert\\n :param output: The file that the TFLite model will be written to\\n :param quantization: The hardware that the model should be optimized for (CPU, GPU)\\n \\\"\\\"\\\"\\n import tensorflow as tf\\n from somnus.models import BaseModel\\n\\n model_path = model\\n model = BaseModel()\\n model.load(model_path)\\n\\n converter = tf.lite.TFLiteConverter.from_keras_model(model.model)\\n \\n # quantize the model. This reduces the size of the model significantly while reducing accuracy\\n # only slightly\\n quantization = quantization.lower()\\n if quantization == 'cpu':\\n converter.optimizations = [tf.lite.Optimize.DEFAULT]\\n elif quantization == 'gpu':\\n converter.optimizations = [tf.lite.Optimize.DEFAULT]\\n converter.target_spec.supported_types = [tf.float16]\\n \\n tflite_model = converter.convert()\\n\\n open(output, \\\"wb\\\").write(tflite_model)\\n\\n def test_quantized_model(self, quantized_model='saved_model.tflite'):\\n \\\"\\\"\\\"\\n Tests a trained model against a test dataset\\n\\n :param quantized_model: The file containing the quantized model we want to test\\n \\\"\\\"\\\"\\n import tensorflow as tf\\n\\n\\n interpreter = tf.lite.Interpreter(model_path=quantized_model)\\n interpreter.allocate_tensors()\\n\\n preprocessed_path = self.config['preprocessed_data']\\n\\n data = np.load(os.path.join(preprocessed_path, 'test_data.npy'))\\n labels = np.load(os.path.join(preprocessed_path, 'test_labels.npy'))\\n\\n wrong = 0\\n for idx in tqdm(range(len(data))):\\n audio = data[idx]\\n label = labels[idx]\\n\\n input_index = interpreter.get_input_details()[0][\\\"index\\\"]\\n output_index = interpreter.get_output_details()[0][\\\"index\\\"]\\n\\n interpreter.set_tensor(input_index, np.expand_dims(audio, axis=0).astype(np.float32))\\n interpreter.invoke()\\n p = interpreter.get_tensor(output_index)\\n\\n if np.argmax(p) != np.argmax(label):\\n wrong += 1\\n\\n percentage = 100*((len(data)-wrong) / len(data))\\n print(\\\"\\\\n Test dataset accuracy is %s percent\\\" % percentage)\\n\\n\\ndef main():\\n fire.Fire(SomnusCLI)\\n\"\n },\n {\n \"alpha_fraction\": 0.5371312499046326,\n \"alphanum_fraction\": 0.5707019567489624,\n \"avg_line_length\": 27.08571434020996,\n \"blob_id\": \"a34ca8c6e619c134b9a1ca8443a86686dfc8b0bb\",\n \"content_id\": \"f7f8e864972c983bff3a89442b814c36fc2b717a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 983,\n \"license_type\": \"permissive\",\n \"max_line_length\": 58,\n \"num_lines\": 35,\n \"path\": \"/setup.py\",\n \"repo_name\": \"Skuldur/somnus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import setuptools\\n\\nwith open(\\\"README.md\\\", \\\"r\\\") as fh:\\n long_description = fh.read()\\n\\nsetuptools.setup(\\n name=\\\"somnus\\\",\\n version=\\\"0.2.2\\\",\\n author=\\\"Sigurður Skúli Sigurgeirsson\\\",\\n author_email=\\\"siggiskuli@gmail.com\\\",\\n description=\\\"Somnus is keyword detection made easy.\\\",\\n long_description=long_description,\\n long_description_content_type=\\\"text/markdown\\\",\\n url=\\\"https://github.com/Skuldur/somnus\\\",\\n packages=setuptools.find_packages(exclude=(\\\"tests\\\",)),\\n install_requires=[\\n \\\"numpy>=1.16.2\\\",\\n \\\"pydub>=0.23.1\\\",\\n \\\"pyaudio>=0.2.11\\\",\\n \\\"librosa>=0.8.0\\\",\\n \\\"tensorflow>=2.2.0\\\",\\n \\\"fire>=0.3.1\\\",\\n \\\"tqdm>=4.47.0\\\"\\n ],\\n classifiers=[\\n \\\"Programming Language :: Python :: 3\\\",\\n \\\"Programming Language :: Python :: 3.6\\\",\\n \\\"License :: OSI Approved :: MIT License\\\",\\n \\\"Operating System :: OS Independent\\\",\\n ],\\n entry_points = {\\n 'console_scripts': ['somnus=cli.cli:main'],\\n },\\n python_requires='>=3.6',\\n)\\n\"\n },\n {\n \"alpha_fraction\": 0.7243683338165283,\n \"alphanum_fraction\": 0.7285445928573608,\n \"avg_line_length\": 36.13178253173828,\n \"blob_id\": \"18318da76f90dd4c2e293347022758f6a2923f02\",\n \"content_id\": \"956e84068931f1c1f359adb186c3aa25bf4af023\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 4789,\n \"license_type\": \"permissive\",\n \"max_line_length\": 292,\n \"num_lines\": 129,\n \"path\": \"/cli/README.md\",\n \"repo_name\": \"Skuldur/somnus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Somnus CLI\\n\\nSomnus comes with a CLI that allows you to generate audio data and train your own keyword detection model. The CLI is implemented using Python-Fire. For each command you can use `-h` or `--help` to get a description of the command and a list of the possible arguments/options for the command.\\n\\nTo start using the CLI run `somnus configure` to create the configuration for the Somnus CLI. Then the raw data directory must contain three sub-directories:\\n\\n* `positives/` for audio files containing utterances of the keyword. Must contain at least 1 audio file.\\n* `negatives/` for audio files containing speech that does not contain utterances of the keyword. Must contain at least 1 audio file.\\n* `backgrounds/` for audio files that contain background noise. This directory is optional but we recommend adding noise to the training data so that the keyword detector also works in noisy conditions.\\n\\nThe CLI currently supports the following audio types: **wav, mp3, flac, ogg, flv, wma, aac**\\n\\n## Configure\\n\\n```bash\\nsomnus configure\\n```\\n\\nCreate a configuration file with the absolute paths to the:\\n\\n* Raw audio data directory\\n* Directory that should contain the augmented audio files\\n* Directory that should contain the preprocessed data files\\n\\n**Note** that the augmented audio files and preprocessed data files can use a lot of space so make sure to put them on a drive with a lot of available space.\\n\\n## Augmenting audio\\n\\n```bash\\nsomnus augment_audio\\n```\\n\\nThe command to generate an audio dataset takes the raw audio in your raw audio directory as input and generates positive, negative, and silent audio files with varying amounts of background noise. These audio files are written to the augmented audio directory.\\n \\n**Arguments**\\n* **duration**: The duration of the audio clips in seconds \\n* **positive**: The number of positive examples \\n* **negative**: The number of negative examples \\n* **silent**: The number of examples containing only background noise \\n\\n## Preprocessing and creating the dataset\\n```bash\\nsomnus preprocess\\n```\\n\\nThe command to preprocess the augmented audio files. It takes the files stored in the augmented audio directory, normalizes them and stores the output array in the preprocessed data directory.\\n\\n**Arguments**\\n* **filters**: The number of filters in each frame \\n* **show_progress**: Boolean option to decide whether to show a progress bar \\n* **split**: The split between train, validation, and test data. The total should add up to 1. E.g. `(0.9, 0.05, 0.05)` \\n* **win_length**: The length of each window in seconds \\n* **win_hop**: the time between the start of each consecutive window. \\n\\n## Training\\n\\n```bash\\nsomnus train\\n```\\n\\nThe command to train a small-footprint keyword model loads the data in `./preprocessed_data/` and uses it to train the keyword model.\\n\\n**Arguments**\\n* **model_name**: The name of the model we want to train \\n* **epochs**: The number of epochs \\n* **weights_file**: The name of the file the final weights should be saved to \\n* **save_best**: Whether or not the model should save the best model throughout the training process \\n* **batch_size**: The size of each mini batch \\n* **lr**: The initial learning rate \\n\\n## Testing\\n\\n```bash\\nsomnus test\\n```\\n\\nThe command to test a trained model on a witheld test dataset.\\n\\n**Arguments**\\n* **model**: The file containing the model we want to test\\n\\n#### List microphones\\n\\n```bash\\nsomnus list_microphones\\n```\\n\\nPrints out a list of microphones connected to your device along with their device IDs.\\n\\n## Cleanup files\\n\\n```bash\\nsomnus cleanup\\n```\\n\\nRemoves all the data files that have been generated by the CLI in the Augmented Audio Directory and the Preprocessed Data Directory\\n\\n\\n## Quantize model\\n\\n```bash\\nsomnus quantize_model\\n```\\n\\nConverts the model to a format compatible with Tensorflow Lite (tflite) and quantizes it. Quantizing the model reduces the size of the model by a factor of 2-4 while barely reducing the total accuracy of the model.\\n\\nThe CLI offers two different methods for quantization:\\n\\n| Option | Quantization Method | Benefits | Hardware |\\n|--------|----------------------------|------------------------------|----------|\\n| CPU | Dynamic range quantization | 4x smaller, 2x-3x speedup | CPU |\\n| GPU | Float16 quantization | 2x smaller, GPU acceleration | CPU, GPU |\\n\\n**Arguments**\\n\\n* **model**: The file containing the model we want to convert\\n* **output**: The file that the TFLite model will be written to\\n* **quantization**: The hardware that the model should be optimized for (CPU, GPU)\\n\\n## Testing Quantized model\\n\\n```bash\\nsomnus test_quantized_model\\n```\\n\\nThe command to test a quantized model on a witheld test dataset.\\n\\n**Arguments**\\n* **model**: The file containing the model we want to test\"\n },\n {\n \"alpha_fraction\": 0.6381766200065613,\n \"alphanum_fraction\": 0.6509971618652344,\n \"avg_line_length\": 31.8125,\n \"blob_id\": \"9af0bf182018d8ac68ac67904a14f36ba805b911\",\n \"content_id\": \"d2eb6a5db8401925cbe97f118a7113dda5f4f7eb\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2106,\n \"license_type\": \"permissive\",\n \"max_line_length\": 112,\n \"num_lines\": 64,\n \"path\": \"/tests/test_utils.py\",\n \"repo_name\": \"Skuldur/somnus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport unittest\\n\\nfrom pydub import AudioSegment\\nimport numpy as np\\n\\nfrom somnus.utils import load_raw_audio, create_positive_example, create_negative_example, create_silent_example\\n\\nTEST_DIR = os.path.dirname(os.path.realpath(__file__))\\n\\n\\nclass TestUtils(unittest.TestCase):\\n\\n def setUp(self):\\n np.random.seed(1)\\n\\n def test_load_raw_audio(self):\\n base_dir = os.path.join(TEST_DIR, 'fixtures')\\n duration = 1\\n\\n pos, neg, back = load_raw_audio(base_dir, duration)\\n\\n self.assertEqual(len(pos), 1)\\n self.assertEqual(len(neg), 1)\\n self.assertEqual(len(back), 1)\\n\\n def test_create_positive_example(self):\\n base_dir = os.path.join(TEST_DIR, 'fixtures')\\n duration = 1\\n\\n pos, neg, back = load_raw_audio(base_dir, duration)\\n\\n time_shift = np.random.randint(200)\\n pos_seg = create_positive_example(back[0], pos[0], time_shift)\\n\\n true_seg = AudioSegment.from_wav(os.path.join(base_dir, 'augmented/positive_0.wav')).set_channels(1)\\n\\n self.assertSequenceEqual(pos_seg.get_array_of_samples(), true_seg.get_array_of_samples())\\n\\n def test_create_negative_example(self):\\n base_dir = os.path.join(TEST_DIR, 'fixtures')\\n duration = 1\\n\\n pos, neg, back = load_raw_audio(base_dir, duration)\\n\\n time_shift = np.random.randint(600)\\n neg_seg = create_negative_example(back[0], pos[0], neg[0], time_shift)\\n\\n true_seg = AudioSegment.from_wav(os.path.join(base_dir, 'augmented/negative_0.wav')).set_channels(1)\\n \\n\\n self.assertSequenceEqual(neg_seg.get_array_of_samples(), true_seg.get_array_of_samples())\\n\\n def test_create_silent_example(self):\\n base_dir = os.path.join(TEST_DIR, 'fixtures')\\n duration = 1\\n\\n pos, neg, back = load_raw_audio(base_dir, duration)\\n\\n back_seg = create_silent_example(back[0], pos[0])\\n\\n true_seg = AudioSegment.from_wav(os.path.join(base_dir, 'augmented/background_0.wav')).set_channels(1)\\n\\n self.assertSequenceEqual(back_seg.get_array_of_samples(), true_seg.get_array_of_samples())\\n\\n\\n\\n\\n\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":10,"string":"10"}}},{"rowIdx":2977687,"cells":{"repo_name":{"kind":"string","value":"inaccare/Beer-Type-Prediction"},"repo_url":{"kind":"string","value":"https://github.com/inaccare/Beer-Type-Prediction"},"snapshot_id":{"kind":"string","value":"ffeaba53d6b3fee223c747183d60447feb45385d"},"revision_id":{"kind":"string","value":"89327f2d721eaee74d144f01e40d53ee3d0c0eb3"},"directory_id":{"kind":"string","value":"1c7035b2099aa542887eaefc67e41ba42f951fb0"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-03-15T03:06:18.203463","string":"2020-03-15T03:06:18.203463"},"revision_date":{"kind":"timestamp","value":"2018-06-14T07:25:23","string":"2018-06-14T07:25:23"},"committer_date":{"kind":"timestamp","value":"2018-06-14T07:25:23","string":"2018-06-14T07:25:23"},"github_id":{"kind":"number","value":131934457,"string":"131,934,457"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.603411078453064,"alphanum_fraction":0.6408547163009644,"avg_line_length":34.1793098449707,"blob_id":"7cf4e9dba1f5d933034d12c4accc3a9d0002e5c6","content_id":"9be6219a2accfb1ec6f78caafaa50f845603dc36","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5101,"license_type":"no_license","max_line_length":251,"num_lines":145,"path":"/cluster.py","repo_name":"inaccare/Beer-Type-Prediction","src_encoding":"UTF-8","text":"\nimport nltk\nimport gensim\nimport pandas as pd\nimport numpy as np\nimport sys\nimport pylab as pl\nimport codecs\n\nfrom sklearn.cluster import KMeans\nfrom sklearn.decomposition import PCA\n\n\n\ndef average_vecs(w2v):\n\ttokenizer = nltk.data.load('tokenizers/punkt/english.pickle')\n\twith open('beers.csv') as f:\n\t\tdf = pd.read_csv(f)\n\t\tstyles = df['style'].unique()[:-1]\n\t\tall_styles = np.zeros((89, 100))\n\t\tfor i, s in enumerate(styles):\n\t\t\tall_beers = df.loc[df['style'] == s]\n\t\t\tsummed = np.zeros((100))\n\t\t\ttop_thousand = all_beers.head(1000)\n\t\t\tnum_rows = len(top_thousand)\n\t\t\tfor index, row in top_thousand.iterrows():\n\t\t\t\treview = row['text']\n\t\t\t\treview_tokenized = nltk.word_tokenize(review.lower())\n\t\t\t\tfor token in review_tokenized:\n\t\t\t\t\tif token in w2v.wv.vocab:\n\t\t\t\t\t\tsummed += w2v[token]\n\t\t\tsummed /= num_rows\n\t\t\tall_styles[i] = summed\n\t\treturn all_styles, styles\n\ndef cluster(all_styles):\n\tkmeans = KMeans()\n\tkmeans.fit(all_styles)\n\treturn kmeans.labels_\n\ndef add_cluster_csv(cluster):\n\ttrain = pd.read_csv('beers_train.csv')\n\tdev = pd.read_csv('beers_dev.csv')\n\ttest = pd.read_csv('beers_test.csv')\n\n\ttrain_clusters = []\n\tdev_clusters = []\n\ttest_clusters = []\n\n\tfor index, row in train.iterrows():\n\t\ts = row['style']\n\t\tif type(s) is not str:\n\t\t\ttrain_clusters.append(float('nan'))\n\t\t\tcontinue\n\t\tstring_nobackslashes = codecs.decode(s, 'unicode_escape')\n\t\tstring_nobackslashes = string_nobackslashes.encode('ISO-8859-1')\n\t\tcorrect_string = string_nobackslashes.replace(b'\\xc3\\xa9', 'e').replace(b'\\xc3\\xb6', 'o').replace(b'(IPA)', '').replace(b'(Witbier)', '').replace('\\xc3\\xa4', 'a').replace(b'\\xc3\\xa8', 'e').replace('b\\'', '').replace('\\'', '').strip()\n\t\tcorrect_string = correct_string.decode('ascii')\n\t\ttrain_clusters.append(cluster[correct_string] + 1)\n\n\ttrain['cluster'] = train_clusters\n\n\tfor index, row in dev.iterrows():\n\t\ts = row['style']\n\t\tif type(s) is not str:\n\t\t\tdev_clusters.append(float('nan'))\n\t\t\tcontinue\n\t\tstring_nobackslashes = codecs.decode(s, 'unicode_escape')\n\t\tstring_nobackslashes = string_nobackslashes.encode('ISO-8859-1')\n\t\tcorrect_string = string_nobackslashes.replace(b'\\xc3\\xa9', 'e').replace(b'\\xc3\\xb6', 'o').replace(b'(IPA)', '').replace(b'(Witbier)', '').replace('\\xc3\\xa4', 'a').replace(b'\\xc3\\xa8', 'e').replace('b\\'', '').replace('\\'', '').strip()\n\t\tcorrect_string = correct_string.decode('ascii')\n\t\tdev_clusters.append(cluster[correct_string] + 1)\n\n\tdev['cluster'] = dev_clusters\n\n\tfor index, row in test.iterrows():\n\t\ts = row['style']\n\t\tif type(s) is not str:\n\t\t\ttest_clusters.append(float('nan'))\n\t\t\tcontinue\n\t\tstring_nobackslashes = codecs.decode(s, 'unicode_escape')\n\t\tstring_nobackslashes = string_nobackslashes.encode('ISO-8859-1')\n\t\tcorrect_string = string_nobackslashes.replace(b'\\xc3\\xa9', 'e').replace(b'\\xc3\\xb6', 'o').replace(b'(IPA)', '').replace(b'(Witbier)', '').replace('\\xc3\\xa4', 'a').replace(b'\\xc3\\xa8', 'e').replace('b\\'', '').replace('\\'', '').strip()\n\t\tcorrect_string = correct_string.decode('ascii')\n\t\ttest_clusters.append(cluster[correct_string] + 1)\n\n\ttest['cluster'] = test_clusters\n\n\ttrain.to_csv('beers_train_cluster.csv')\n\tdev.to_csv('beers_dev_cluster.csv')\n\ttest.to_csv('beers_test_cluster.csv')\n\n\ndef main():\n\treplacements = {'\\xc3\\xa9': 'e', '\\xc3\\xb6': 'o', '(IPA)': ''}\n\tw2vFile = sys.argv[1]\n\tw2v = gensim.models.word2vec.Word2Vec.load(w2vFile)\n\tall_styles, styles = average_vecs(w2v)\n\tnew_styles = []\n\tfor s in styles:\n\t\tstring_nobackslashes = codecs.decode(s, 'unicode_escape')\n\t\tstring_nobackslashes = string_nobackslashes.encode('ISO-8859-1')\n\t\tcorrect_string = string_nobackslashes.replace(b'\\xc3\\xa9', 'e').replace(b'\\xc3\\xb6', 'o').replace(b'(IPA)', '').replace(b'(Witbier)', '').replace('\\xc3\\xa4', 'a').replace(b'\\xc3\\xa8', 'e').replace('b\\'', '').replace('\\'', '').strip()\n\t\tcorrect_string = correct_string.decode('ascii')\n\t\tnew_styles.append(correct_string)\n\tprint(new_styles)\n\tstyles = new_styles\n\tlabels = cluster(all_styles)\n\tcluster_key = {}\n\tclusters = {}\n\tfor i in range(8):\n\t\tclusters[i] = []\n\tfor j in range(len(labels)):\n\t\tcluster_key[styles[j]] = labels[j]\n\t\tclusters[labels[j]].append(styles[j])\n\tprint(clusters)\n\n\tadd_cluster_csv(cluster_key)\n\n\tpca = PCA(n_components=2).fit(all_styles)\n\tpca_2d = pca.transform(all_styles)\n\n\tfor i in range(pca_2d.shape[0]):\n\t\tif labels[i] == 0:\n\t\t\tc1 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='r')\n\t\telif labels[i] == 1:\n\t\t\tc2 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='g')\n\t\telif labels[i] == 2:\n\t\t\tc3 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='b')\n\t\telif labels[i] == 3:\n\t\t\tc4 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='c')\n\t\telif labels[i] == 4:\n\t\t\tc5 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='m')\n\t\telif labels[i] == 5:\n\t\t\tc6 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='y')\n\t\telif labels[i] == 6:\n\t\t\tc7 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='k')\n\t\telif labels[i] == 7:\n\t\t\tc8 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='orange')\n\t\tpl.annotate(styles[i], xy=(pca_2d[i,0], pca_2d[i,1]))\n\tpl.legend([c1, c2, c3, c4, c5, c6, c7, c8], ['1', '2', '3', '4', '5', '6', '7', '8'])\n\tpl.show()\n\n\n\nmain()"},{"alpha_fraction":0.5767731666564941,"alphanum_fraction":0.590023398399353,"avg_line_length":24.68000030517578,"blob_id":"4074595ed7e2ee35fc24458eedfbf4b067d10e8b","content_id":"59a8b4e37f42428f2d51a0b34c2152d3b5a9dd7d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1283,"license_type":"no_license","max_line_length":142,"num_lines":50,"path":"/parse_data.py","repo_name":"inaccare/Beer-Type-Prediction","src_encoding":"UTF-8","text":"import pandas as pd\nimport numpy as np\n\ndata_path = '../ratebeer.txt'\n\ndef main():\n\twith open(data_path, encoding='utf-8') as f:\n\t\treviews = f.read().split('\\n\\n')\n\t\tparsed_data = []\n\t\tcategories = set()\n\t\tnum_reviews = len(reviews)\n\t\tfor num, r in enumerate(reviews):\n\t\t\tif num % 10000 == 0:\n\t\t\t\tprint(str(num) + '/' + str(num_reviews))\n\t\t\tdatum = []\n\t\t\tfeats = r.split('\\n')\n\t\t\tfor i, feat in enumerate(feats):\n\t\t\t\tvalues = feat.split(':')\n\t\t\t\tif len(values) < 2:\n\t\t\t\t\tvalue = 'N/A'\n\t\t\t\telse:\n\t\t\t\t\tvalue = ':'.join(values[1:]).strip()\n\t\t\t\tif i == 4:\n\t\t\t\t\tcategories.add(value)\n\t\t\t\tdatum.append(value)\n\t\t\tparsed_data.append(datum)\n\n\t\tcolumns = ['name', 'beerId', 'brewerId', 'ABV', 'style', 'appearance', 'aroma', 'palate', 'taste', 'overall', 'time', 'profileName', 'text']\n\t\tdf = pd.DataFrame(parsed_data)\n\t\tdf.columns = columns\n\n\t\tarr = np.random.rand(len(df))\n\t\tmsk_train = arr < 0.9\n\t\tmsk_dev = arr > 0.95\n\t\tmsk_test = arr > 0.9\n\t\ttrain = df[msk_train]\n\t\tdev = df[msk_dev]\n\t\ttest = df[msk_test & ~msk_dev]\n\n\t\twith open('beers_train.csv', 'w') as out:\n\t\t train.to_csv(out)\n\t\tprint('Total number of categories: ' + str(len(categories)))\n\n\t\twith open('beers_dev.csv', 'w') as out:\n\t\t dev.to_csv(out)\n\n\t\twith open('beers_test.csv', 'w') as out:\n\t\t test.to_csv(out)\n\nmain()"},{"alpha_fraction":0.5919678211212158,"alphanum_fraction":0.603921115398407,"avg_line_length":41.730308532714844,"blob_id":"4cdfe43331832a21232006d410c459b9918fda45","content_id":"6b0dd807efcab573405e4bc42b1e8b9a7070cfa9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":17903,"license_type":"no_license","max_line_length":196,"num_lines":419,"path":"/LSTM_model.py","repo_name":"inaccare/Beer-Type-Prediction","src_encoding":"UTF-8","text":"import pandas as pd\nimport re\nimport sys\nimport time\nimport math\nimport numpy as np\nnp.set_printoptions(threshold=np.nan)\nimport h5py\nimport matplotlib.pyplot as plt\nimport tensorflow as tf\nfrom tensorflow.python.framework import ops\nimport json\nimport nltk\nimport multiprocessing\nimport gensim\nfrom collections import defaultdict\nimport codecs\n\n\n\"\"\"\nThis model's architecture is as follows: product descriptions go into an LSTM layer, output of LSTM goes\nthrough a 6-layer FC network. Output is a softmax vector of length 89, corresponding to 89 distinct \nBeer types.\n\"\"\"\n\nw2v = None\nw2vFile = sys.argv[3]\nw2v = gensim.models.word2vec.Word2Vec.load(w2vFile)\n\nwordToIndex = dict()\nindexToEmb = dict()\nindexToWord = dict()\ncount = 1\nwordToIndex['padding'] = 0\nindexToWord[0] = 'padding'\nindexToEmb[0] = np.random.randn(100)\nfor w in w2v.wv.vocab:\n indexToWord[count] = w\n wordToIndex[w] = count\n indexToEmb[count] = w2v.wv[w]\n count = count + 1\n\ndef main():\n # Usage is as follows: python model.py <train>.csv <dev>.csv <glove file> \n X_test = []\n Y_test = []\n testCSV = None\n trainCSV = None\n devCSV = None\n if (len(sys.argv) >=2):\n trainCSV = sys.argv[1]\n if (len(sys.argv) >= 4):\n devCSV = sys.argv[2]\n lr, ne, bs, tx = None, None, None, 400\n if (len(sys.argv) >= 5):\n lr, ne, bs, tx = getHyperparamsFromJSON(str(sys.argv[4]))\n\n styleToIndex, indexToStyle = buildStyleIndices()\n trainDF = pd.read_csv(trainCSV, header = 0, encoding='utf-8', dtype={'text': str})\n rand_arr = np.random.rand(len(trainDF))\n msk_train = rand_arr < 0.01\n trainDF = trainDF[msk_train]\n # For each entry in X_train, we have an array of length T_x with each entry\n # corresponding to an index into the word's w2v embedding\n X_train, Y_train = getReviewIndicesAndStyles(trainDF, tx, styleToIndex)\n devDF = pd.read_csv(devCSV, header = 0, encoding='utf-8')\n rand_arr = np.random.rand(len(devDF))\n msk_dev = rand_arr > .999\n devDF = devDF[msk_dev]\n X_dev, Y_dev = getReviewIndicesAndStyles(devDF, tx, styleToIndex)\n print (\"X_train shape: \" + str(X_train.shape))\n print (\"Y_train shape: \" + str(Y_train.shape))\n print (\"X_dev shape: \" + str(X_dev.shape))\n print (\"Y_dev shape: \" + str(Y_dev.shape))\n if (lr == None):\n model(X_train, Y_train, X_dev, Y_dev, styleDict=indexToStyle)\n else:\n model(X_train, Y_train, X_dev, Y_dev, learning_rate = lr, num_epochs = ne, mini_batch_size = bs, Tx = tx, styleDict=indexToStyle)\n\ndef buildStyleIndices():\n styleDict = {}\n indexToStyleDict = {}\n df = pd.read_csv(\"beers_train.csv\", header = 0, encoding='utf-8')\n styles = df['style'].unique()[:-1]\n for i, s in enumerate(styles):\n if str(s) not in styleDict:\n styleDict[str(s)] = i\n indexToStyleDict[i] = str(s)\n return styleDict, indexToStyleDict\n\ndef cleanStyles(styles):\n new_styles = []\n for s in styles:\n correct_string = s.replace('\\xc3\\xa9', 'e').replace('\\xc3\\xb6', 'o').replace('(IPA)', '').replace('(Witbier)', '').replace('\\xc3\\xa4', 'a').replace('\\xc3\\xa8', 'e').strip()\n new_styles.append(correct_string)\n return new_styles\n\ndef getReviewIndicesAndStyles(df, T_x, styleToIndex):\n X = []\n Y = []\n numBuckets = 89\n for i, row in df.iterrows():#len(df['item_description'])):\n if (pd.isnull(row['text']) == False): # Checks for Nan descriptions\n X.append(getIndexArrForSentence(row['text'], T_x))\n else:\n X.append(np.zeros(T_x))\n Y.append(OneHot(styleToIndex[str(row['style'])], 89))\n Y = np.array(Y).T\n X = np.array(X).T\n return X, Y\n\ndef getIndexArrForSentence(sentence, T_x):\n arr = np.zeros(T_x)\n words = nltk.word_tokenize(sentence.lower())\n count = 0\n for w in words:\n # Only looking at first 400 words!\n if (count == T_x):\n break\n if w in w2v.wv.vocab:\n arr[count] = wordToIndex[w]\n count = count + 1\n return arr\n\ndef getSentenceForIndexArr(arr):\n sentence = []\n for i in arr:\n sentence.append(indexToWord[int(i)])\n return sentence\n\ndef OneHot(bucket, numBuckets):\n \"\"\"\n Creates onehot vector for our Y output\n Arguments:\n bucket -- index of correct bucket for example in Y\n numBuckets -- number of buckets used to split of the prices of objects\n Returns:\n arr -- onehot array\n \"\"\"\n arr = np.zeros(numBuckets)\n arr[bucket] = 1\n return arr\n\n# ==========\n# MODEL\n# ==========\ndef model(X_train, Y_train, X_dev, Y_dev, learning_rate = 0.01, num_epochs = 3,\n mini_batch_size = 128, Tx = 400, display_step = 1, n_hidden = 64, styleDict={}):\n # Shape of X: (m, Tx, n_x)??? Emmie please check this\n # Shape of Y: (n_y, m)\n print (\"Model has following hyperparameters: learning rate: \" + str(learning_rate) + \", num_epochs: \" + str(num_epochs) + \", mini_batch_size: \" \\\n + str(mini_batch_size) + \", Tx: \"+ str(Tx) + \".\")\n\n # hidden layer num of features\n n_y = 89 # num categories\n n_x = 100 # w2v length\n\n # tf Graph input\n X = tf.placeholder(\"float\", [None, Tx, n_x])\n Y = tf.placeholder(\"float\", [n_y, None])\n # A placeholder for indicating each sequence length\n #Tx = tf.placeholder(tf.int32, [None])\n\n # Define weights\n weights = {\n # 'out': tf.Variable(tf.random_normal([n_hidden, n_y]))\n 'W_1' : tf.get_variable('W_1',[n_hidden,n_hidden], initializer = tf.contrib.layers.xavier_initializer(seed = 1)),\n 'W_2' : tf.get_variable('W_2',[n_hidden,n_hidden], initializer = tf.contrib.layers.xavier_initializer(seed = 1)),\n 'W_out' : tf.get_variable('W_out',[n_hidden, n_hidden], initializer = tf.contrib.layers.xavier_initializer(seed = 1)),\n 'W_f1' : tf.get_variable('W_f1',[n_hidden, n_hidden], initializer = tf.contrib.layers.xavier_initializer(seed = 1)),\n 'W_f2' : tf.get_variable('W_f2',[n_hidden,n_hidden], initializer = tf.contrib.layers.xavier_initializer(seed = 1)),\n 'W_fout' : tf.get_variable('W_fout',[n_hidden,n_y], initializer = tf.contrib.layers.xavier_initializer(seed = 1))\n }\n biases = {\n # 'out': tf.Variable(tf.random_normal([n_y]))\n 'b_1' : tf.get_variable('b_1',[n_hidden], initializer = tf.zeros_initializer()),\n 'b_2' : tf.get_variable('b_2',[n_hidden], initializer = tf.zeros_initializer()),\n 'b_out' : tf.get_variable('b_out',[n_hidden], initializer = tf.zeros_initializer()),\n 'b_f1' : tf.get_variable('b_f1',[n_hidden], initializer = tf.zeros_initializer()),\n 'b_f2' : tf.get_variable('b_f2',[n_hidden], initializer = tf.zeros_initializer()),\n 'b_fout' : tf.get_variable('b_fout',[n_y], initializer = tf.zeros_initializer())\n }\n\n lstm_output = dynamicRNN(X, Tx, weights, biases, n_x, n_hidden)\n tf.nn.dropout(lstm_output, 0.1)\n U = tf.get_variable(\"U\", shape=[n_hidden * 2, n_y], initializer=tf.contrib.layers.xavier_initializer())\n b_last = tf.get_variable(\"b_last\", shape=[1, n_y], initializer=tf.zeros_initializer())\n pred = tf.matmul(lstm_output, U) + b_last\n# pred = tf.Print(pred, [pred], message=\"This is pred: \", summarize=88)\n # Define loss and optimizer\n cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits = pred, labels = tf.transpose(Y)))\n\n # derivative wrt to each embedding\n dc_de = tf.gradients(cost, X)\n sc = tf.linalg.norm(dc_de[0], axis=2)\n\n\n optimizer = tf.train.AdamOptimizer(learning_rate = learning_rate).minimize(cost)\n\n # Evaluate model\n predicted_vals = tf.argmax(pred, 1)\n actual_vals = tf.argmax(tf.transpose(Y), 1)\n\n correct_pred = tf.equal(predicted_vals, actual_vals) #Argmax over columns\n num_correct = tf.reduce_sum(tf.cast(correct_pred, tf.float32), name = \"num_correct\")\n\n # Initialize the variables (i.e. assign their default value)\n init = tf.global_variables_initializer()\n\n # Initialize the saver\n saver = tf.train.Saver()\n\n m = Y_train.shape[1]\n num_minibatches = int(math.floor(m/mini_batch_size))\n # Start training\n with tf.Session() as sess:\n # Run the initializer\n sess.run(init)\n for step in range(1, num_epochs + 1):\n epoch_cost =0\n tot_num_correct = 0\n # extract each miniminibatch_X, miniBatch_Y at each\n #make minimatches here (randomly shuffling across m)\n minibatches = random_mini_batches(X_train, Y_train, mini_batch_size = mini_batch_size, seed = 0)\n for minibatch in minibatches:\n (minibatch_X, minibatch_Y) = minibatch\n # Expand mininminibatch_X \n minibatch_X = miniBatchIndicesToEmbedding(minibatch_X, Tx)# print (\"Shape of minibatch_X is \" + str(minibatch_X.shape))\n sess.run(optimizer, feed_dict={X: minibatch_X, Y: minibatch_Y})\n mini_num_correct, loss = sess.run([num_correct, cost], feed_dict={X: minibatch_X, Y: minibatch_Y})\n epoch_cost = epoch_cost + loss\n tot_num_correct = tot_num_correct + mini_num_correct\n # Tx: Tx})\n if step % display_step == 0 or step == 1:\n # Calculate batch accuracy & loss\n #Tx: Tx})\n print(\"Epoch \" + str(step) + \", Cost= \" + \\\n \"{:.6f}\".format(epoch_cost/num_minibatches) + \", Training Accuracy= \" + \\\n \"{:.5f}\".format(float(tot_num_correct/m)))\n\n print(\"Optimization Finished!\")\n train_num_correct = 0\n minibatches = random_mini_batches(X_train, Y_train, mini_batch_size = mini_batch_size, seed = 0)\n for minibatch in minibatches:\n (minibatch_X, minibatch_Y) = minibatch\n minibatch_X = miniBatchIndicesToEmbedding(minibatch_X, Tx)\n num_correct_mb, loss = sess.run([num_correct, cost], feed_dict={X: minibatch_X, Y: minibatch_Y})\n train_num_correct = train_num_correct + num_correct_mb\n print(\"Accuracy for train set: \"+ str(train_num_correct/X_train.shape[1]))\n\n dev_num_correct = 0\n minibatches = random_mini_batches(X_dev, Y_dev, mini_batch_size = mini_batch_size, seed = 0)\n\n f = open('saliency.json', 'w')\n f.write('[\\n')\n for minibatch in minibatches:\n (minibatch_X_ind, minibatch_Y) = minibatch\n minibatch_X = miniBatchIndicesToEmbedding(minibatch_X_ind, Tx)\n minibatch_sent = []\n for m in minibatch_X_ind.T:\n minibatch_sent.append(getSentenceForIndexArr(m))\n num_correct_mb, pr, ac, loss, saliency = sess.run([num_correct, predicted_vals, actual_vals, cost, sc], feed_dict={X: minibatch_X, Y: minibatch_Y})\n predicted = []\n actual = []\n for i in range(pr.shape[0]):\n predicted.append(styleDict[pr[i]])\n actual.append(styleDict[ac[i]])\n predicted = cleanStyles(predicted)\n actual = cleanStyles(actual)\n saliency_chart = list(zip(minibatch_sent, saliency))\n zipped = []\n for ex in saliency_chart:\n zipped.append(list(zip(ex[0], ex[1].tolist())))\n for i in range(len(predicted)):\n f.write('\\t{\\n')\n f.write('\\t\\t\\\"predicted\\\": \\\"' + predicted[i] + '\\\",\\n')\n f.write('\\t\\t\\\"actual\\\": \\\"' + actual[i] + '\\\",\\n')\n f.write('\\t\\t\\\"saliency\\\": ' + json.dumps(zipped[i]) + '\\n')\n f.write('\\t},\\n')\n\n dev_num_correct = dev_num_correct + num_correct_mb\n f.write(']\\n')\n f.close()\n\n\n print(\"Accuracy for dev set: \"+ str(dev_num_correct/X_dev.shape[1]))\n saver.save(sess, './LSTM_model')\n sess.close()\n # # Calculate accuracy\n # test_data = testset.data\n # test_label = testset.labels\n # test_Tx = testset.Tx\n # print(\"Testing Accuracy:\", \\\n # sess.run(accuracy, feed_dict={X: test_data, Y: test_label,\n # Tx: test_Tx}))\n\ndef dynamicRNN(X, Tx, weights, biases, n_x, n_hidden):\n\n # Prepare data shape to match `rnn` function requirements\n # Current data input shape: (m, Tx, n_x)\n # Required shape: 'n_steps' tensors list of shape (batch_size, n_input); or Tx tensors of shape (m, n_x)\n\n # Unstack to get a list of 'n_steps' tensors of shape (batch_size, n_input)\n # X = tf.unstack(X, Tx, 1) #Unstack to be (None, 100) vectors\n # Define a lstm cell with tensorflow\n lstm_cell_fw = tf.contrib.rnn.BasicLSTMCell(n_hidden)\n lstm_cell_bw = tf.contrib.rnn.BasicLSTMCell(n_hidden)\n\n # Get lstm cell output, providing 'sequence_length' will perform dynamic\n # calculation.\n # Z_out, c = tf.contrib.rnn.static_rnn(lstm_cell, X, dtype=tf.float32)\n _, output = tf.nn.bidirectional_dynamic_rnn(lstm_cell_fw, lstm_cell_bw, X, dtype=tf.float32)\n output = (output[0][1], output[1][1])\n lstm_output = tf.concat(output, 1)\n #sequence_length=Tx)\n\n # When performing dynamic calculation, we must retrieve the last\n # dynamically computed output, i.e., if a sequence length is 10, we need\n # to retrieve the 10th output.\n # However TensorFlow doesn't support advanced indexing yet, so we build\n # a custom op that for each sample in batch size, get its length and\n # get the corresponding relevant output.\n\n # 'Z_out' is a list of output at every timestep, we pack them in a Tensor\n # and change back dimension to [batch_size, n_step, n_input]\n # Z_out = tf.stack(Z_out)\n # Z_out = tf.transpose(Z_out, [1, 0, 2])\n\n # # Hack to build the indexing and retrieve the right output.\n # batch_size = tf.shape(Z_out)[0]\n # # Start indices for each sample\n # index = tf.range(0, batch_size) * Tx + (Tx - 1)\n # # Indexing\n # Z_out = tf.gather(tf.reshape(Z_out, [-1, n_hidden]), index)\n # # Deepen LSTM network with fully connected\n # Z_out = tf.matmul(Z_out, weights['W_1']) + biases['b_1']\n # Z_out = tf.nn.relu(Z_out)\n # dropout = tf.layers.dropout(inputs=Z_out, rate=0.1) # Dropout 10% of units\n # Z_out = tf.matmul(Z_out, weights['W_2']) + biases['b_2']\n # Z_out = tf.nn.relu(Z_out)\n # dropout = tf.layers.dropout(inputs=Z_out, rate=0.1)\n # Z_out = tf.matmul(dropout, weights['W_out']) + biases['b_out']\n # Z_out = tf.nn.relu(Z_out) \n\n # # Deepen Full Network\n # Z_out = tf.matmul(Z_out, weights['W_f1']) + biases['b_f1']\n # Z_out = tf.nn.relu(Z_out)\n # Z_out = tf.layers.dropout(inputs=Z_out, rate=0.1) # Dropout 10% of units\n # Z_out = tf.matmul(Z_out, weights['W_f2']) + biases['b_f2']\n # Z_out = tf.nn.relu(Z_out)\n # Z_out = tf.layers.dropout(inputs=Z_out, rate=0.1)\n # Z_out = tf.matmul(Z_out, weights['W_fout']) + biases['b_fout']\n\n # Linear activation, using Z_out computed above\n return lstm_output\n\n\n# =================================================================\n# Helper functions for reading in data/getting minibatches ready\n# =================================================================\ndef getHyperparamsFromJSON(filename):\n parameters = None\n with open(filename, 'r') as fp:\n parameters = json.load(fp)\n return float(parameters['learning_rate']), int(parameters['num_epochs']), int(parameters['batch_size']), int(parameters['Tx'])\n\ndef miniBatchIndicesToEmbedding(minibatch_X, T_x):\n m = minibatch_X.shape[1]# Maximum number of time steps (zero-padded)\n n_x = 100 # Length of words2vec vector for each word\n newArr = np.zeros((m, T_x, n_x))\n for i in range(m): # Iterating through samples\n for j in range(T_x): # Iterating through words\n indexToW2v = 0\n indexToW2v = minibatch_X[j,i]\n if indexToW2v != 0:\n newArr[i,j,:] = np.array(indexToEmb[indexToW2v])\n return newArr\n\ndef random_mini_batches(X, Y, mini_batch_size = 64, seed = 0):\n \"\"\"\n Creates a list of random minibatches from (X, Y)\n\n Arguments:\n X -- input data, of shape (number of examples, Tx)\n Y -- true \"label\" vector (containing 0 if cat, 1 if non-cat), of shape (1, number of examples)\n mini_batch_size - size of the mini-batches, integer\n seed -- this is only for the purpose of grading, so that you're \"random minibatches are the same as ours.\n\n Returns:\n mini_batches -- list of synchronous (mini_batch_X, mini_batch_Y)\n \"\"\"\n m = Y.shape[1] # number of training examples\n mini_batches = []\n np.random.seed(seed)\n # Step 1: Shuffle (X, Y) X shape: (Tx, m) Y shape: (n_y, m)\n permutation = list(np.random.permutation(m))\n print(\"shape X\", X.shape)\n shuffled_X = X[:, permutation]\n shuffled_Y = Y[:, permutation].reshape((Y.shape[0],m)) # not sure why we need to reshape here\n\n # Step 2: Partition (shuffled_X, shuffled_Y). Minus the end case.\n num_complete_minibatches = int(math.floor(m/mini_batch_size)) # number of mini batches of size mini_batch_size in your partitionning\n for k in range(0, num_complete_minibatches):\n mini_batch_X = shuffled_X[:, k * mini_batch_size : k * mini_batch_size + mini_batch_size]\n mini_batch_Y = shuffled_Y[:, k * mini_batch_size : k * mini_batch_size + mini_batch_size]\n mini_batch = (mini_batch_X, mini_batch_Y)\n mini_batches.append(mini_batch)\n\n # Handling the end case (last mini-batch < mini_batch_size)\n if m % mini_batch_size != 0:\n mini_batch_X = shuffled_X[:, num_complete_minibatches * mini_batch_size : m]\n mini_batch_Y = shuffled_Y[:, num_complete_minibatches * mini_batch_size : m]\n mini_batch = (mini_batch_X, mini_batch_Y)\n mini_batches.append(mini_batch)\n\n return mini_batches\n\nif __name__ == '__main__':\n main()"},{"alpha_fraction":0.6500765681266785,"alphanum_fraction":0.6669219136238098,"avg_line_length":21.912281036376953,"blob_id":"3da1e591ec096dc51c76af12775cafa606091d69","content_id":"ad9fa94282fa058308694e38aa6037fd7a43369c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1306,"license_type":"no_license","max_line_length":62,"num_lines":57,"path":"/baseline.py","repo_name":"inaccare/Beer-Type-Prediction","src_encoding":"UTF-8","text":"\nimport nltk\nimport gensim\nimport pandas as pd\nimport numpy as np\nimport sys\nimport codecs\nimport math\n\nfrom sklearn.linear_model import LogisticRegression\n\n\ndef average_vecs(w2v, filename):\n\ttokenizer = nltk.data.load('tokenizers/punkt/english.pickle')\n\twith open(filename) as f:\n\t\tdf = pd.read_csv(f, dtype={'text': str})\n\t\tsamples = []\n\t\tlabels = []\n\t\treviews = df['text']\n\t\tnum_rows = len(df)\n\t\tfor i, review in enumerate(reviews):\n\t\t\tif i % 1000 == 0:\n\t\t\t\tprint str(i) + '/' + str(num_rows)\n\t\t\tif type(review) is not str:\n\t\t\t\tcontinue\n\t\t\tlabels.append(df.iloc[i]['style'])\n\t\t\tsummed = np.zeros((100))\n\t\t\treview_tokenized = nltk.word_tokenize(review.lower())\n\t\t\tfor token in review_tokenized:\n\t\t\t\tif token in w2v.wv.vocab:\n\t\t\t\t\tsummed += w2v[token]\n\t\t\tsummed /= num_rows\n\t\t\tsamples.append(summed)\n\t\treturn np.array(samples), labels\n\n\ndef main():\n\tw2vFile = sys.argv[1]\n\tw2v = gensim.models.word2vec.Word2Vec.load(w2vFile)\n\ttrain_x, train_y = average_vecs(w2v, 'beers_train.csv')\n\tdev_x, dev_y = average_vecs(w2v, 'beers_dev.csv')\n\t\n\tbaseline = LogisticRegression()\n\tbaseline.fit(train_x, train_y)\n\ty_hat = baseline.predict(dev_x)\n\n\tcorrect = 0.0\n\ttotal = len(y_hat)\n\n\tfor i in range(len(y_hat)):\n\t\tif dev_y[i] == y_hat[i]:\n\t\t\tcorrect += 1\n\tacc = correct / total\n\tprint 'accuracy: ' + str(acc)\n\n\n\nmain()"},{"alpha_fraction":0.7968923449516296,"alphanum_fraction":0.8057713508605957,"avg_line_length":127.71428680419922,"blob_id":"db499fe278aaf436158a96005a61bb8621832396","content_id":"d92c474c86d4fe695ad7976c8fb3aaf31f902e5d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":901,"license_type":"no_license","max_line_length":669,"num_lines":7,"path":"/README.md","repo_name":"inaccare/Beer-Type-Prediction","src_encoding":"UTF-8","text":"# Beer-Type-Prediction\nPresentation at: https://www.youtube.com/watch?v=HazZTgU0RO8&t=26s\n\nProject Overview:\nWe built a Bi-Directional LSTM model to classify beers by type (i.e. IPA, Imperial Stout, etc.) based on reviews in the RateBeer dataset. After achieving > 44% accuracy with this model of 89 different categories of beer, we used First Derivative Saliency to make our model interpretable. By doing this, we were able to determine which words were most heavily weighted during classification through our saliency heatmaps. For example, for a fruit beer, the words \"lemons\" and \"candy\" were weighted most heavily. We believe other applications of this model could be in attempting to determine tasting notes in various wines or in a similar manner with restaurant reviews.\n\nPlease read paper \"Classifying Beer Styles Using an Interpretable NLP Model\" included for in depth discussion of project\n"},{"alpha_fraction":0.6869731545448303,"alphanum_fraction":0.7022988796234131,"avg_line_length":27.69230842590332,"blob_id":"9a6c140ff8f0c13817d6f707c06ef1ef6308ca51","content_id":"7d74d6838c76ff2e3f4c4d3a8e43d6b59aa19531","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2610,"license_type":"no_license","max_line_length":114,"num_lines":91,"path":"/build_w2v.py","repo_name":"inaccare/Beer-Type-Prediction","src_encoding":"UTF-8","text":"from collections import Counter\nimport numpy as np\nimport pandas as pd\nimport re\nimport sys\nimport nltk\nimport codecs\nimport multiprocessing\nimport gensim\n\ndef clean_and_split_str(string):\n strip_special_chars = re.compile(\"[^A-Za-z]+\")\n string = re.sub(strip_special_chars, \" \", string)\n return string.strip().split()\n\ndef main():\n\tif len(sys.argv) > 3 or len(sys.argv) < 2:\n\t\traise Exception(\"usage: python build_w2v.py ratebeer.csv <num_dim>\")\n\n\tnum_dim = 100\n\tif len(sys.argv) == 3:\n\t\tnum_dim = sys.argv[2]\n\n\tinputfile = sys.argv[1]\n\traw_df = pd.read_csv(inputfile, header = 0)\n\tprint(\"data loaded\")\n\n\traw_corpus = u\"\".join(raw_df['review/text'].astype(str) + \" \")\n\tprint(\"Raw Corpus contains {0:,} words\".format(len(raw_corpus.split())))\n\n\ttokenizer = nltk.data.load(\"tokenizers/punkt/english.pickle\")\n\tprint(\"The punkt tokenizer is loaded\")\n\traw_sentences = tokenizer.tokenize(raw_corpus)\n\tprint(\"We have {0:,} raw sentences\".format(len(raw_sentences)))\n\n\tsentences = []\n\tfor raw_sent in raw_sentences:\n\t\tif len(raw_sent) > 0:\n\t\t\tsentences.append(clean_and_split_str(raw_sent.lower()))\n\tprint(\"We have {0:,} clean sentences\".format(len(sentences)))\n\n\ttoken_count = sum([len(sentence) for sentence in sentences])\n\tprint(\"The dataset corpus contains {0:,} tokens\".format(token_count))\n\n\t#Dimensionality of the resulting word vectors\n\tnum_features = num_dim\n\t#Minimum word count threshold\n\tmin_word_count = 2\n\t#Number of threads to run in parallel\n\tnum_workers = multiprocessing.cpu_count() \n\t#Context window length\n\tcontext_size = 7\n\t#Seed for the RNG, to make the result reproducible\n\tseed = 1\n\t\n\tword2vec_model = gensim.models.word2vec.Word2Vec(\n sg=1,\n seed=seed,\n workers=num_workers, \n size=num_features, \n min_count=min_word_count, \n window=context_size)\n\t \n\tword2vec_model.build_vocab(sentences=sentences)\n\tprint(\"The vocabulary is built\")\n\tprint(\"Word2Vec vocabulary length: \", len(word2vec_model.wv.vocab))\n\t \n\t#Start training the model\n\tword2vec_model.train(sentences=sentences, total_examples=word2vec_model.corpus_count, epochs=word2vec_model.iter)\n\tprint(\"Training finished\")\n\n\tword2vec_model.save(\"Beer_reviews_trained.w2v\")\n\tprint(\"Model saved\")\n\n\tw2v_model = gensim.models.word2vec.Word2Vec.load(\"Beer_reviews_trained.w2v\")\n\tprint(\"Model loaded\")\n\n\tcounter = 0\n\tfor word in w2v_model.wv.vocab:\n\t\tprint(\"word: \", word)\n\t\tprint(w2v_model.wv[word])\n\t\tcounter += 1\n\t\tif counter > 10:\n\t\t\tbreak\n\n\t# df_des = df['item_description']\n\t# df_des.to_csv('pandas.txt', header=None, index=None, sep=' ', mode='a', escapechar=\" \")\n\treturn\n\nif __name__ == \"__main__\":\n\tmain()"},{"alpha_fraction":0.6259258985519409,"alphanum_fraction":0.6555555462837219,"avg_line_length":18.321428298950195,"blob_id":"78dc52c80b7d424fb8d93e0505164dbfa7ea6307","content_id":"cf4e8b4542805af846d17219eed2b50c37a5d822","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":540,"license_type":"no_license","max_line_length":42,"num_lines":28,"path":"/get_lengths.py","repo_name":"inaccare/Beer-Type-Prediction","src_encoding":"UTF-8","text":"import numpy as np\nimport matplotlib.pyplot as plt\nimport os\nimport json\nimport pandas as pd\n\n\nbins = 30\nbeer_file = 'beers.csv'\n\nx = []\n\nwith open(beer_file) as f:\n\tdf = pd.read_csv(f)\n\tlength = len(df['text'])\n\tfor i, row in enumerate(df['text'][:-1]):\n\t\tif i % 100000:\n\t\t\tprint str(i) + '/' + str(length)\n\t\tx.append(len(row))\n\n\tvals = np.asarray(x, dtype=np.int32)\n\n\tplt.xlabel('Tokens')\n\tplt.ylabel('Number of Reviews')\n\tplt.title('Beer Review Lengths')\n\tplt.hist(vals, bins, range=[0, 1500])\n\t#plt.show()\n\tplt.savefig('review_len.png')"}],"string":"[\n {\n \"alpha_fraction\": 0.603411078453064,\n \"alphanum_fraction\": 0.6408547163009644,\n \"avg_line_length\": 34.1793098449707,\n \"blob_id\": \"7cf4e9dba1f5d933034d12c4accc3a9d0002e5c6\",\n \"content_id\": \"9be6219a2accfb1ec6f78caafaa50f845603dc36\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5101,\n \"license_type\": \"no_license\",\n \"max_line_length\": 251,\n \"num_lines\": 145,\n \"path\": \"/cluster.py\",\n \"repo_name\": \"inaccare/Beer-Type-Prediction\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\nimport nltk\\nimport gensim\\nimport pandas as pd\\nimport numpy as np\\nimport sys\\nimport pylab as pl\\nimport codecs\\n\\nfrom sklearn.cluster import KMeans\\nfrom sklearn.decomposition import PCA\\n\\n\\n\\ndef average_vecs(w2v):\\n\\ttokenizer = nltk.data.load('tokenizers/punkt/english.pickle')\\n\\twith open('beers.csv') as f:\\n\\t\\tdf = pd.read_csv(f)\\n\\t\\tstyles = df['style'].unique()[:-1]\\n\\t\\tall_styles = np.zeros((89, 100))\\n\\t\\tfor i, s in enumerate(styles):\\n\\t\\t\\tall_beers = df.loc[df['style'] == s]\\n\\t\\t\\tsummed = np.zeros((100))\\n\\t\\t\\ttop_thousand = all_beers.head(1000)\\n\\t\\t\\tnum_rows = len(top_thousand)\\n\\t\\t\\tfor index, row in top_thousand.iterrows():\\n\\t\\t\\t\\treview = row['text']\\n\\t\\t\\t\\treview_tokenized = nltk.word_tokenize(review.lower())\\n\\t\\t\\t\\tfor token in review_tokenized:\\n\\t\\t\\t\\t\\tif token in w2v.wv.vocab:\\n\\t\\t\\t\\t\\t\\tsummed += w2v[token]\\n\\t\\t\\tsummed /= num_rows\\n\\t\\t\\tall_styles[i] = summed\\n\\t\\treturn all_styles, styles\\n\\ndef cluster(all_styles):\\n\\tkmeans = KMeans()\\n\\tkmeans.fit(all_styles)\\n\\treturn kmeans.labels_\\n\\ndef add_cluster_csv(cluster):\\n\\ttrain = pd.read_csv('beers_train.csv')\\n\\tdev = pd.read_csv('beers_dev.csv')\\n\\ttest = pd.read_csv('beers_test.csv')\\n\\n\\ttrain_clusters = []\\n\\tdev_clusters = []\\n\\ttest_clusters = []\\n\\n\\tfor index, row in train.iterrows():\\n\\t\\ts = row['style']\\n\\t\\tif type(s) is not str:\\n\\t\\t\\ttrain_clusters.append(float('nan'))\\n\\t\\t\\tcontinue\\n\\t\\tstring_nobackslashes = codecs.decode(s, 'unicode_escape')\\n\\t\\tstring_nobackslashes = string_nobackslashes.encode('ISO-8859-1')\\n\\t\\tcorrect_string = string_nobackslashes.replace(b'\\\\xc3\\\\xa9', 'e').replace(b'\\\\xc3\\\\xb6', 'o').replace(b'(IPA)', '').replace(b'(Witbier)', '').replace('\\\\xc3\\\\xa4', 'a').replace(b'\\\\xc3\\\\xa8', 'e').replace('b\\\\'', '').replace('\\\\'', '').strip()\\n\\t\\tcorrect_string = correct_string.decode('ascii')\\n\\t\\ttrain_clusters.append(cluster[correct_string] + 1)\\n\\n\\ttrain['cluster'] = train_clusters\\n\\n\\tfor index, row in dev.iterrows():\\n\\t\\ts = row['style']\\n\\t\\tif type(s) is not str:\\n\\t\\t\\tdev_clusters.append(float('nan'))\\n\\t\\t\\tcontinue\\n\\t\\tstring_nobackslashes = codecs.decode(s, 'unicode_escape')\\n\\t\\tstring_nobackslashes = string_nobackslashes.encode('ISO-8859-1')\\n\\t\\tcorrect_string = string_nobackslashes.replace(b'\\\\xc3\\\\xa9', 'e').replace(b'\\\\xc3\\\\xb6', 'o').replace(b'(IPA)', '').replace(b'(Witbier)', '').replace('\\\\xc3\\\\xa4', 'a').replace(b'\\\\xc3\\\\xa8', 'e').replace('b\\\\'', '').replace('\\\\'', '').strip()\\n\\t\\tcorrect_string = correct_string.decode('ascii')\\n\\t\\tdev_clusters.append(cluster[correct_string] + 1)\\n\\n\\tdev['cluster'] = dev_clusters\\n\\n\\tfor index, row in test.iterrows():\\n\\t\\ts = row['style']\\n\\t\\tif type(s) is not str:\\n\\t\\t\\ttest_clusters.append(float('nan'))\\n\\t\\t\\tcontinue\\n\\t\\tstring_nobackslashes = codecs.decode(s, 'unicode_escape')\\n\\t\\tstring_nobackslashes = string_nobackslashes.encode('ISO-8859-1')\\n\\t\\tcorrect_string = string_nobackslashes.replace(b'\\\\xc3\\\\xa9', 'e').replace(b'\\\\xc3\\\\xb6', 'o').replace(b'(IPA)', '').replace(b'(Witbier)', '').replace('\\\\xc3\\\\xa4', 'a').replace(b'\\\\xc3\\\\xa8', 'e').replace('b\\\\'', '').replace('\\\\'', '').strip()\\n\\t\\tcorrect_string = correct_string.decode('ascii')\\n\\t\\ttest_clusters.append(cluster[correct_string] + 1)\\n\\n\\ttest['cluster'] = test_clusters\\n\\n\\ttrain.to_csv('beers_train_cluster.csv')\\n\\tdev.to_csv('beers_dev_cluster.csv')\\n\\ttest.to_csv('beers_test_cluster.csv')\\n\\n\\ndef main():\\n\\treplacements = {'\\\\xc3\\\\xa9': 'e', '\\\\xc3\\\\xb6': 'o', '(IPA)': ''}\\n\\tw2vFile = sys.argv[1]\\n\\tw2v = gensim.models.word2vec.Word2Vec.load(w2vFile)\\n\\tall_styles, styles = average_vecs(w2v)\\n\\tnew_styles = []\\n\\tfor s in styles:\\n\\t\\tstring_nobackslashes = codecs.decode(s, 'unicode_escape')\\n\\t\\tstring_nobackslashes = string_nobackslashes.encode('ISO-8859-1')\\n\\t\\tcorrect_string = string_nobackslashes.replace(b'\\\\xc3\\\\xa9', 'e').replace(b'\\\\xc3\\\\xb6', 'o').replace(b'(IPA)', '').replace(b'(Witbier)', '').replace('\\\\xc3\\\\xa4', 'a').replace(b'\\\\xc3\\\\xa8', 'e').replace('b\\\\'', '').replace('\\\\'', '').strip()\\n\\t\\tcorrect_string = correct_string.decode('ascii')\\n\\t\\tnew_styles.append(correct_string)\\n\\tprint(new_styles)\\n\\tstyles = new_styles\\n\\tlabels = cluster(all_styles)\\n\\tcluster_key = {}\\n\\tclusters = {}\\n\\tfor i in range(8):\\n\\t\\tclusters[i] = []\\n\\tfor j in range(len(labels)):\\n\\t\\tcluster_key[styles[j]] = labels[j]\\n\\t\\tclusters[labels[j]].append(styles[j])\\n\\tprint(clusters)\\n\\n\\tadd_cluster_csv(cluster_key)\\n\\n\\tpca = PCA(n_components=2).fit(all_styles)\\n\\tpca_2d = pca.transform(all_styles)\\n\\n\\tfor i in range(pca_2d.shape[0]):\\n\\t\\tif labels[i] == 0:\\n\\t\\t\\tc1 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='r')\\n\\t\\telif labels[i] == 1:\\n\\t\\t\\tc2 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='g')\\n\\t\\telif labels[i] == 2:\\n\\t\\t\\tc3 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='b')\\n\\t\\telif labels[i] == 3:\\n\\t\\t\\tc4 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='c')\\n\\t\\telif labels[i] == 4:\\n\\t\\t\\tc5 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='m')\\n\\t\\telif labels[i] == 5:\\n\\t\\t\\tc6 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='y')\\n\\t\\telif labels[i] == 6:\\n\\t\\t\\tc7 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='k')\\n\\t\\telif labels[i] == 7:\\n\\t\\t\\tc8 = pl.scatter(pca_2d[i,0], pca_2d[i,1], c='orange')\\n\\t\\tpl.annotate(styles[i], xy=(pca_2d[i,0], pca_2d[i,1]))\\n\\tpl.legend([c1, c2, c3, c4, c5, c6, c7, c8], ['1', '2', '3', '4', '5', '6', '7', '8'])\\n\\tpl.show()\\n\\n\\n\\nmain()\"\n },\n {\n \"alpha_fraction\": 0.5767731666564941,\n \"alphanum_fraction\": 0.590023398399353,\n \"avg_line_length\": 24.68000030517578,\n \"blob_id\": \"4074595ed7e2ee35fc24458eedfbf4b067d10e8b\",\n \"content_id\": \"59a8b4e37f42428f2d51a0b34c2152d3b5a9dd7d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1283,\n \"license_type\": \"no_license\",\n \"max_line_length\": 142,\n \"num_lines\": 50,\n \"path\": \"/parse_data.py\",\n \"repo_name\": \"inaccare/Beer-Type-Prediction\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pandas as pd\\nimport numpy as np\\n\\ndata_path = '../ratebeer.txt'\\n\\ndef main():\\n\\twith open(data_path, encoding='utf-8') as f:\\n\\t\\treviews = f.read().split('\\\\n\\\\n')\\n\\t\\tparsed_data = []\\n\\t\\tcategories = set()\\n\\t\\tnum_reviews = len(reviews)\\n\\t\\tfor num, r in enumerate(reviews):\\n\\t\\t\\tif num % 10000 == 0:\\n\\t\\t\\t\\tprint(str(num) + '/' + str(num_reviews))\\n\\t\\t\\tdatum = []\\n\\t\\t\\tfeats = r.split('\\\\n')\\n\\t\\t\\tfor i, feat in enumerate(feats):\\n\\t\\t\\t\\tvalues = feat.split(':')\\n\\t\\t\\t\\tif len(values) < 2:\\n\\t\\t\\t\\t\\tvalue = 'N/A'\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tvalue = ':'.join(values[1:]).strip()\\n\\t\\t\\t\\tif i == 4:\\n\\t\\t\\t\\t\\tcategories.add(value)\\n\\t\\t\\t\\tdatum.append(value)\\n\\t\\t\\tparsed_data.append(datum)\\n\\n\\t\\tcolumns = ['name', 'beerId', 'brewerId', 'ABV', 'style', 'appearance', 'aroma', 'palate', 'taste', 'overall', 'time', 'profileName', 'text']\\n\\t\\tdf = pd.DataFrame(parsed_data)\\n\\t\\tdf.columns = columns\\n\\n\\t\\tarr = np.random.rand(len(df))\\n\\t\\tmsk_train = arr < 0.9\\n\\t\\tmsk_dev = arr > 0.95\\n\\t\\tmsk_test = arr > 0.9\\n\\t\\ttrain = df[msk_train]\\n\\t\\tdev = df[msk_dev]\\n\\t\\ttest = df[msk_test & ~msk_dev]\\n\\n\\t\\twith open('beers_train.csv', 'w') as out:\\n\\t\\t train.to_csv(out)\\n\\t\\tprint('Total number of categories: ' + str(len(categories)))\\n\\n\\t\\twith open('beers_dev.csv', 'w') as out:\\n\\t\\t dev.to_csv(out)\\n\\n\\t\\twith open('beers_test.csv', 'w') as out:\\n\\t\\t test.to_csv(out)\\n\\nmain()\"\n },\n {\n \"alpha_fraction\": 0.5919678211212158,\n \"alphanum_fraction\": 0.603921115398407,\n \"avg_line_length\": 41.730308532714844,\n \"blob_id\": \"4cdfe43331832a21232006d410c459b9918fda45\",\n \"content_id\": \"6b0dd807efcab573405e4bc42b1e8b9a7070cfa9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 17903,\n \"license_type\": \"no_license\",\n \"max_line_length\": 196,\n \"num_lines\": 419,\n \"path\": \"/LSTM_model.py\",\n \"repo_name\": \"inaccare/Beer-Type-Prediction\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pandas as pd\\nimport re\\nimport sys\\nimport time\\nimport math\\nimport numpy as np\\nnp.set_printoptions(threshold=np.nan)\\nimport h5py\\nimport matplotlib.pyplot as plt\\nimport tensorflow as tf\\nfrom tensorflow.python.framework import ops\\nimport json\\nimport nltk\\nimport multiprocessing\\nimport gensim\\nfrom collections import defaultdict\\nimport codecs\\n\\n\\n\\\"\\\"\\\"\\nThis model's architecture is as follows: product descriptions go into an LSTM layer, output of LSTM goes\\nthrough a 6-layer FC network. Output is a softmax vector of length 89, corresponding to 89 distinct \\nBeer types.\\n\\\"\\\"\\\"\\n\\nw2v = None\\nw2vFile = sys.argv[3]\\nw2v = gensim.models.word2vec.Word2Vec.load(w2vFile)\\n\\nwordToIndex = dict()\\nindexToEmb = dict()\\nindexToWord = dict()\\ncount = 1\\nwordToIndex['padding'] = 0\\nindexToWord[0] = 'padding'\\nindexToEmb[0] = np.random.randn(100)\\nfor w in w2v.wv.vocab:\\n indexToWord[count] = w\\n wordToIndex[w] = count\\n indexToEmb[count] = w2v.wv[w]\\n count = count + 1\\n\\ndef main():\\n # Usage is as follows: python model.py <train>.csv <dev>.csv <glove file> \\n X_test = []\\n Y_test = []\\n testCSV = None\\n trainCSV = None\\n devCSV = None\\n if (len(sys.argv) >=2):\\n trainCSV = sys.argv[1]\\n if (len(sys.argv) >= 4):\\n devCSV = sys.argv[2]\\n lr, ne, bs, tx = None, None, None, 400\\n if (len(sys.argv) >= 5):\\n lr, ne, bs, tx = getHyperparamsFromJSON(str(sys.argv[4]))\\n\\n styleToIndex, indexToStyle = buildStyleIndices()\\n trainDF = pd.read_csv(trainCSV, header = 0, encoding='utf-8', dtype={'text': str})\\n rand_arr = np.random.rand(len(trainDF))\\n msk_train = rand_arr < 0.01\\n trainDF = trainDF[msk_train]\\n # For each entry in X_train, we have an array of length T_x with each entry\\n # corresponding to an index into the word's w2v embedding\\n X_train, Y_train = getReviewIndicesAndStyles(trainDF, tx, styleToIndex)\\n devDF = pd.read_csv(devCSV, header = 0, encoding='utf-8')\\n rand_arr = np.random.rand(len(devDF))\\n msk_dev = rand_arr > .999\\n devDF = devDF[msk_dev]\\n X_dev, Y_dev = getReviewIndicesAndStyles(devDF, tx, styleToIndex)\\n print (\\\"X_train shape: \\\" + str(X_train.shape))\\n print (\\\"Y_train shape: \\\" + str(Y_train.shape))\\n print (\\\"X_dev shape: \\\" + str(X_dev.shape))\\n print (\\\"Y_dev shape: \\\" + str(Y_dev.shape))\\n if (lr == None):\\n model(X_train, Y_train, X_dev, Y_dev, styleDict=indexToStyle)\\n else:\\n model(X_train, Y_train, X_dev, Y_dev, learning_rate = lr, num_epochs = ne, mini_batch_size = bs, Tx = tx, styleDict=indexToStyle)\\n\\ndef buildStyleIndices():\\n styleDict = {}\\n indexToStyleDict = {}\\n df = pd.read_csv(\\\"beers_train.csv\\\", header = 0, encoding='utf-8')\\n styles = df['style'].unique()[:-1]\\n for i, s in enumerate(styles):\\n if str(s) not in styleDict:\\n styleDict[str(s)] = i\\n indexToStyleDict[i] = str(s)\\n return styleDict, indexToStyleDict\\n\\ndef cleanStyles(styles):\\n new_styles = []\\n for s in styles:\\n correct_string = s.replace('\\\\xc3\\\\xa9', 'e').replace('\\\\xc3\\\\xb6', 'o').replace('(IPA)', '').replace('(Witbier)', '').replace('\\\\xc3\\\\xa4', 'a').replace('\\\\xc3\\\\xa8', 'e').strip()\\n new_styles.append(correct_string)\\n return new_styles\\n\\ndef getReviewIndicesAndStyles(df, T_x, styleToIndex):\\n X = []\\n Y = []\\n numBuckets = 89\\n for i, row in df.iterrows():#len(df['item_description'])):\\n if (pd.isnull(row['text']) == False): # Checks for Nan descriptions\\n X.append(getIndexArrForSentence(row['text'], T_x))\\n else:\\n X.append(np.zeros(T_x))\\n Y.append(OneHot(styleToIndex[str(row['style'])], 89))\\n Y = np.array(Y).T\\n X = np.array(X).T\\n return X, Y\\n\\ndef getIndexArrForSentence(sentence, T_x):\\n arr = np.zeros(T_x)\\n words = nltk.word_tokenize(sentence.lower())\\n count = 0\\n for w in words:\\n # Only looking at first 400 words!\\n if (count == T_x):\\n break\\n if w in w2v.wv.vocab:\\n arr[count] = wordToIndex[w]\\n count = count + 1\\n return arr\\n\\ndef getSentenceForIndexArr(arr):\\n sentence = []\\n for i in arr:\\n sentence.append(indexToWord[int(i)])\\n return sentence\\n\\ndef OneHot(bucket, numBuckets):\\n \\\"\\\"\\\"\\n Creates onehot vector for our Y output\\n Arguments:\\n bucket -- index of correct bucket for example in Y\\n numBuckets -- number of buckets used to split of the prices of objects\\n Returns:\\n arr -- onehot array\\n \\\"\\\"\\\"\\n arr = np.zeros(numBuckets)\\n arr[bucket] = 1\\n return arr\\n\\n# ==========\\n# MODEL\\n# ==========\\ndef model(X_train, Y_train, X_dev, Y_dev, learning_rate = 0.01, num_epochs = 3,\\n mini_batch_size = 128, Tx = 400, display_step = 1, n_hidden = 64, styleDict={}):\\n # Shape of X: (m, Tx, n_x)??? Emmie please check this\\n # Shape of Y: (n_y, m)\\n print (\\\"Model has following hyperparameters: learning rate: \\\" + str(learning_rate) + \\\", num_epochs: \\\" + str(num_epochs) + \\\", mini_batch_size: \\\" \\\\\\n + str(mini_batch_size) + \\\", Tx: \\\"+ str(Tx) + \\\".\\\")\\n\\n # hidden layer num of features\\n n_y = 89 # num categories\\n n_x = 100 # w2v length\\n\\n # tf Graph input\\n X = tf.placeholder(\\\"float\\\", [None, Tx, n_x])\\n Y = tf.placeholder(\\\"float\\\", [n_y, None])\\n # A placeholder for indicating each sequence length\\n #Tx = tf.placeholder(tf.int32, [None])\\n\\n # Define weights\\n weights = {\\n # 'out': tf.Variable(tf.random_normal([n_hidden, n_y]))\\n 'W_1' : tf.get_variable('W_1',[n_hidden,n_hidden], initializer = tf.contrib.layers.xavier_initializer(seed = 1)),\\n 'W_2' : tf.get_variable('W_2',[n_hidden,n_hidden], initializer = tf.contrib.layers.xavier_initializer(seed = 1)),\\n 'W_out' : tf.get_variable('W_out',[n_hidden, n_hidden], initializer = tf.contrib.layers.xavier_initializer(seed = 1)),\\n 'W_f1' : tf.get_variable('W_f1',[n_hidden, n_hidden], initializer = tf.contrib.layers.xavier_initializer(seed = 1)),\\n 'W_f2' : tf.get_variable('W_f2',[n_hidden,n_hidden], initializer = tf.contrib.layers.xavier_initializer(seed = 1)),\\n 'W_fout' : tf.get_variable('W_fout',[n_hidden,n_y], initializer = tf.contrib.layers.xavier_initializer(seed = 1))\\n }\\n biases = {\\n # 'out': tf.Variable(tf.random_normal([n_y]))\\n 'b_1' : tf.get_variable('b_1',[n_hidden], initializer = tf.zeros_initializer()),\\n 'b_2' : tf.get_variable('b_2',[n_hidden], initializer = tf.zeros_initializer()),\\n 'b_out' : tf.get_variable('b_out',[n_hidden], initializer = tf.zeros_initializer()),\\n 'b_f1' : tf.get_variable('b_f1',[n_hidden], initializer = tf.zeros_initializer()),\\n 'b_f2' : tf.get_variable('b_f2',[n_hidden], initializer = tf.zeros_initializer()),\\n 'b_fout' : tf.get_variable('b_fout',[n_y], initializer = tf.zeros_initializer())\\n }\\n\\n lstm_output = dynamicRNN(X, Tx, weights, biases, n_x, n_hidden)\\n tf.nn.dropout(lstm_output, 0.1)\\n U = tf.get_variable(\\\"U\\\", shape=[n_hidden * 2, n_y], initializer=tf.contrib.layers.xavier_initializer())\\n b_last = tf.get_variable(\\\"b_last\\\", shape=[1, n_y], initializer=tf.zeros_initializer())\\n pred = tf.matmul(lstm_output, U) + b_last\\n# pred = tf.Print(pred, [pred], message=\\\"This is pred: \\\", summarize=88)\\n # Define loss and optimizer\\n cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits = pred, labels = tf.transpose(Y)))\\n\\n # derivative wrt to each embedding\\n dc_de = tf.gradients(cost, X)\\n sc = tf.linalg.norm(dc_de[0], axis=2)\\n\\n\\n optimizer = tf.train.AdamOptimizer(learning_rate = learning_rate).minimize(cost)\\n\\n # Evaluate model\\n predicted_vals = tf.argmax(pred, 1)\\n actual_vals = tf.argmax(tf.transpose(Y), 1)\\n\\n correct_pred = tf.equal(predicted_vals, actual_vals) #Argmax over columns\\n num_correct = tf.reduce_sum(tf.cast(correct_pred, tf.float32), name = \\\"num_correct\\\")\\n\\n # Initialize the variables (i.e. assign their default value)\\n init = tf.global_variables_initializer()\\n\\n # Initialize the saver\\n saver = tf.train.Saver()\\n\\n m = Y_train.shape[1]\\n num_minibatches = int(math.floor(m/mini_batch_size))\\n # Start training\\n with tf.Session() as sess:\\n # Run the initializer\\n sess.run(init)\\n for step in range(1, num_epochs + 1):\\n epoch_cost =0\\n tot_num_correct = 0\\n # extract each miniminibatch_X, miniBatch_Y at each\\n #make minimatches here (randomly shuffling across m)\\n minibatches = random_mini_batches(X_train, Y_train, mini_batch_size = mini_batch_size, seed = 0)\\n for minibatch in minibatches:\\n (minibatch_X, minibatch_Y) = minibatch\\n # Expand mininminibatch_X \\n minibatch_X = miniBatchIndicesToEmbedding(minibatch_X, Tx)# print (\\\"Shape of minibatch_X is \\\" + str(minibatch_X.shape))\\n sess.run(optimizer, feed_dict={X: minibatch_X, Y: minibatch_Y})\\n mini_num_correct, loss = sess.run([num_correct, cost], feed_dict={X: minibatch_X, Y: minibatch_Y})\\n epoch_cost = epoch_cost + loss\\n tot_num_correct = tot_num_correct + mini_num_correct\\n # Tx: Tx})\\n if step % display_step == 0 or step == 1:\\n # Calculate batch accuracy & loss\\n #Tx: Tx})\\n print(\\\"Epoch \\\" + str(step) + \\\", Cost= \\\" + \\\\\\n \\\"{:.6f}\\\".format(epoch_cost/num_minibatches) + \\\", Training Accuracy= \\\" + \\\\\\n \\\"{:.5f}\\\".format(float(tot_num_correct/m)))\\n\\n print(\\\"Optimization Finished!\\\")\\n train_num_correct = 0\\n minibatches = random_mini_batches(X_train, Y_train, mini_batch_size = mini_batch_size, seed = 0)\\n for minibatch in minibatches:\\n (minibatch_X, minibatch_Y) = minibatch\\n minibatch_X = miniBatchIndicesToEmbedding(minibatch_X, Tx)\\n num_correct_mb, loss = sess.run([num_correct, cost], feed_dict={X: minibatch_X, Y: minibatch_Y})\\n train_num_correct = train_num_correct + num_correct_mb\\n print(\\\"Accuracy for train set: \\\"+ str(train_num_correct/X_train.shape[1]))\\n\\n dev_num_correct = 0\\n minibatches = random_mini_batches(X_dev, Y_dev, mini_batch_size = mini_batch_size, seed = 0)\\n\\n f = open('saliency.json', 'w')\\n f.write('[\\\\n')\\n for minibatch in minibatches:\\n (minibatch_X_ind, minibatch_Y) = minibatch\\n minibatch_X = miniBatchIndicesToEmbedding(minibatch_X_ind, Tx)\\n minibatch_sent = []\\n for m in minibatch_X_ind.T:\\n minibatch_sent.append(getSentenceForIndexArr(m))\\n num_correct_mb, pr, ac, loss, saliency = sess.run([num_correct, predicted_vals, actual_vals, cost, sc], feed_dict={X: minibatch_X, Y: minibatch_Y})\\n predicted = []\\n actual = []\\n for i in range(pr.shape[0]):\\n predicted.append(styleDict[pr[i]])\\n actual.append(styleDict[ac[i]])\\n predicted = cleanStyles(predicted)\\n actual = cleanStyles(actual)\\n saliency_chart = list(zip(minibatch_sent, saliency))\\n zipped = []\\n for ex in saliency_chart:\\n zipped.append(list(zip(ex[0], ex[1].tolist())))\\n for i in range(len(predicted)):\\n f.write('\\\\t{\\\\n')\\n f.write('\\\\t\\\\t\\\\\\\"predicted\\\\\\\": \\\\\\\"' + predicted[i] + '\\\\\\\",\\\\n')\\n f.write('\\\\t\\\\t\\\\\\\"actual\\\\\\\": \\\\\\\"' + actual[i] + '\\\\\\\",\\\\n')\\n f.write('\\\\t\\\\t\\\\\\\"saliency\\\\\\\": ' + json.dumps(zipped[i]) + '\\\\n')\\n f.write('\\\\t},\\\\n')\\n\\n dev_num_correct = dev_num_correct + num_correct_mb\\n f.write(']\\\\n')\\n f.close()\\n\\n\\n print(\\\"Accuracy for dev set: \\\"+ str(dev_num_correct/X_dev.shape[1]))\\n saver.save(sess, './LSTM_model')\\n sess.close()\\n # # Calculate accuracy\\n # test_data = testset.data\\n # test_label = testset.labels\\n # test_Tx = testset.Tx\\n # print(\\\"Testing Accuracy:\\\", \\\\\\n # sess.run(accuracy, feed_dict={X: test_data, Y: test_label,\\n # Tx: test_Tx}))\\n\\ndef dynamicRNN(X, Tx, weights, biases, n_x, n_hidden):\\n\\n # Prepare data shape to match `rnn` function requirements\\n # Current data input shape: (m, Tx, n_x)\\n # Required shape: 'n_steps' tensors list of shape (batch_size, n_input); or Tx tensors of shape (m, n_x)\\n\\n # Unstack to get a list of 'n_steps' tensors of shape (batch_size, n_input)\\n # X = tf.unstack(X, Tx, 1) #Unstack to be (None, 100) vectors\\n # Define a lstm cell with tensorflow\\n lstm_cell_fw = tf.contrib.rnn.BasicLSTMCell(n_hidden)\\n lstm_cell_bw = tf.contrib.rnn.BasicLSTMCell(n_hidden)\\n\\n # Get lstm cell output, providing 'sequence_length' will perform dynamic\\n # calculation.\\n # Z_out, c = tf.contrib.rnn.static_rnn(lstm_cell, X, dtype=tf.float32)\\n _, output = tf.nn.bidirectional_dynamic_rnn(lstm_cell_fw, lstm_cell_bw, X, dtype=tf.float32)\\n output = (output[0][1], output[1][1])\\n lstm_output = tf.concat(output, 1)\\n #sequence_length=Tx)\\n\\n # When performing dynamic calculation, we must retrieve the last\\n # dynamically computed output, i.e., if a sequence length is 10, we need\\n # to retrieve the 10th output.\\n # However TensorFlow doesn't support advanced indexing yet, so we build\\n # a custom op that for each sample in batch size, get its length and\\n # get the corresponding relevant output.\\n\\n # 'Z_out' is a list of output at every timestep, we pack them in a Tensor\\n # and change back dimension to [batch_size, n_step, n_input]\\n # Z_out = tf.stack(Z_out)\\n # Z_out = tf.transpose(Z_out, [1, 0, 2])\\n\\n # # Hack to build the indexing and retrieve the right output.\\n # batch_size = tf.shape(Z_out)[0]\\n # # Start indices for each sample\\n # index = tf.range(0, batch_size) * Tx + (Tx - 1)\\n # # Indexing\\n # Z_out = tf.gather(tf.reshape(Z_out, [-1, n_hidden]), index)\\n # # Deepen LSTM network with fully connected\\n # Z_out = tf.matmul(Z_out, weights['W_1']) + biases['b_1']\\n # Z_out = tf.nn.relu(Z_out)\\n # dropout = tf.layers.dropout(inputs=Z_out, rate=0.1) # Dropout 10% of units\\n # Z_out = tf.matmul(Z_out, weights['W_2']) + biases['b_2']\\n # Z_out = tf.nn.relu(Z_out)\\n # dropout = tf.layers.dropout(inputs=Z_out, rate=0.1)\\n # Z_out = tf.matmul(dropout, weights['W_out']) + biases['b_out']\\n # Z_out = tf.nn.relu(Z_out) \\n\\n # # Deepen Full Network\\n # Z_out = tf.matmul(Z_out, weights['W_f1']) + biases['b_f1']\\n # Z_out = tf.nn.relu(Z_out)\\n # Z_out = tf.layers.dropout(inputs=Z_out, rate=0.1) # Dropout 10% of units\\n # Z_out = tf.matmul(Z_out, weights['W_f2']) + biases['b_f2']\\n # Z_out = tf.nn.relu(Z_out)\\n # Z_out = tf.layers.dropout(inputs=Z_out, rate=0.1)\\n # Z_out = tf.matmul(Z_out, weights['W_fout']) + biases['b_fout']\\n\\n # Linear activation, using Z_out computed above\\n return lstm_output\\n\\n\\n# =================================================================\\n# Helper functions for reading in data/getting minibatches ready\\n# =================================================================\\ndef getHyperparamsFromJSON(filename):\\n parameters = None\\n with open(filename, 'r') as fp:\\n parameters = json.load(fp)\\n return float(parameters['learning_rate']), int(parameters['num_epochs']), int(parameters['batch_size']), int(parameters['Tx'])\\n\\ndef miniBatchIndicesToEmbedding(minibatch_X, T_x):\\n m = minibatch_X.shape[1]# Maximum number of time steps (zero-padded)\\n n_x = 100 # Length of words2vec vector for each word\\n newArr = np.zeros((m, T_x, n_x))\\n for i in range(m): # Iterating through samples\\n for j in range(T_x): # Iterating through words\\n indexToW2v = 0\\n indexToW2v = minibatch_X[j,i]\\n if indexToW2v != 0:\\n newArr[i,j,:] = np.array(indexToEmb[indexToW2v])\\n return newArr\\n\\ndef random_mini_batches(X, Y, mini_batch_size = 64, seed = 0):\\n \\\"\\\"\\\"\\n Creates a list of random minibatches from (X, Y)\\n\\n Arguments:\\n X -- input data, of shape (number of examples, Tx)\\n Y -- true \\\"label\\\" vector (containing 0 if cat, 1 if non-cat), of shape (1, number of examples)\\n mini_batch_size - size of the mini-batches, integer\\n seed -- this is only for the purpose of grading, so that you're \\\"random minibatches are the same as ours.\\n\\n Returns:\\n mini_batches -- list of synchronous (mini_batch_X, mini_batch_Y)\\n \\\"\\\"\\\"\\n m = Y.shape[1] # number of training examples\\n mini_batches = []\\n np.random.seed(seed)\\n # Step 1: Shuffle (X, Y) X shape: (Tx, m) Y shape: (n_y, m)\\n permutation = list(np.random.permutation(m))\\n print(\\\"shape X\\\", X.shape)\\n shuffled_X = X[:, permutation]\\n shuffled_Y = Y[:, permutation].reshape((Y.shape[0],m)) # not sure why we need to reshape here\\n\\n # Step 2: Partition (shuffled_X, shuffled_Y). Minus the end case.\\n num_complete_minibatches = int(math.floor(m/mini_batch_size)) # number of mini batches of size mini_batch_size in your partitionning\\n for k in range(0, num_complete_minibatches):\\n mini_batch_X = shuffled_X[:, k * mini_batch_size : k * mini_batch_size + mini_batch_size]\\n mini_batch_Y = shuffled_Y[:, k * mini_batch_size : k * mini_batch_size + mini_batch_size]\\n mini_batch = (mini_batch_X, mini_batch_Y)\\n mini_batches.append(mini_batch)\\n\\n # Handling the end case (last mini-batch < mini_batch_size)\\n if m % mini_batch_size != 0:\\n mini_batch_X = shuffled_X[:, num_complete_minibatches * mini_batch_size : m]\\n mini_batch_Y = shuffled_Y[:, num_complete_minibatches * mini_batch_size : m]\\n mini_batch = (mini_batch_X, mini_batch_Y)\\n mini_batches.append(mini_batch)\\n\\n return mini_batches\\n\\nif __name__ == '__main__':\\n main()\"\n },\n {\n \"alpha_fraction\": 0.6500765681266785,\n \"alphanum_fraction\": 0.6669219136238098,\n \"avg_line_length\": 21.912281036376953,\n \"blob_id\": \"3da1e591ec096dc51c76af12775cafa606091d69\",\n \"content_id\": \"ad9fa94282fa058308694e38aa6037fd7a43369c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1306,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 57,\n \"path\": \"/baseline.py\",\n \"repo_name\": \"inaccare/Beer-Type-Prediction\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\nimport nltk\\nimport gensim\\nimport pandas as pd\\nimport numpy as np\\nimport sys\\nimport codecs\\nimport math\\n\\nfrom sklearn.linear_model import LogisticRegression\\n\\n\\ndef average_vecs(w2v, filename):\\n\\ttokenizer = nltk.data.load('tokenizers/punkt/english.pickle')\\n\\twith open(filename) as f:\\n\\t\\tdf = pd.read_csv(f, dtype={'text': str})\\n\\t\\tsamples = []\\n\\t\\tlabels = []\\n\\t\\treviews = df['text']\\n\\t\\tnum_rows = len(df)\\n\\t\\tfor i, review in enumerate(reviews):\\n\\t\\t\\tif i % 1000 == 0:\\n\\t\\t\\t\\tprint str(i) + '/' + str(num_rows)\\n\\t\\t\\tif type(review) is not str:\\n\\t\\t\\t\\tcontinue\\n\\t\\t\\tlabels.append(df.iloc[i]['style'])\\n\\t\\t\\tsummed = np.zeros((100))\\n\\t\\t\\treview_tokenized = nltk.word_tokenize(review.lower())\\n\\t\\t\\tfor token in review_tokenized:\\n\\t\\t\\t\\tif token in w2v.wv.vocab:\\n\\t\\t\\t\\t\\tsummed += w2v[token]\\n\\t\\t\\tsummed /= num_rows\\n\\t\\t\\tsamples.append(summed)\\n\\t\\treturn np.array(samples), labels\\n\\n\\ndef main():\\n\\tw2vFile = sys.argv[1]\\n\\tw2v = gensim.models.word2vec.Word2Vec.load(w2vFile)\\n\\ttrain_x, train_y = average_vecs(w2v, 'beers_train.csv')\\n\\tdev_x, dev_y = average_vecs(w2v, 'beers_dev.csv')\\n\\t\\n\\tbaseline = LogisticRegression()\\n\\tbaseline.fit(train_x, train_y)\\n\\ty_hat = baseline.predict(dev_x)\\n\\n\\tcorrect = 0.0\\n\\ttotal = len(y_hat)\\n\\n\\tfor i in range(len(y_hat)):\\n\\t\\tif dev_y[i] == y_hat[i]:\\n\\t\\t\\tcorrect += 1\\n\\tacc = correct / total\\n\\tprint 'accuracy: ' + str(acc)\\n\\n\\n\\nmain()\"\n },\n {\n \"alpha_fraction\": 0.7968923449516296,\n \"alphanum_fraction\": 0.8057713508605957,\n \"avg_line_length\": 127.71428680419922,\n \"blob_id\": \"db499fe278aaf436158a96005a61bb8621832396\",\n \"content_id\": \"d92c474c86d4fe695ad7976c8fb3aaf31f902e5d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 901,\n \"license_type\": \"no_license\",\n \"max_line_length\": 669,\n \"num_lines\": 7,\n \"path\": \"/README.md\",\n \"repo_name\": \"inaccare/Beer-Type-Prediction\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Beer-Type-Prediction\\nPresentation at: https://www.youtube.com/watch?v=HazZTgU0RO8&t=26s\\n\\nProject Overview:\\nWe built a Bi-Directional LSTM model to classify beers by type (i.e. IPA, Imperial Stout, etc.) based on reviews in the RateBeer dataset. After achieving > 44% accuracy with this model of 89 different categories of beer, we used First Derivative Saliency to make our model interpretable. By doing this, we were able to determine which words were most heavily weighted during classification through our saliency heatmaps. For example, for a fruit beer, the words \\\"lemons\\\" and \\\"candy\\\" were weighted most heavily. We believe other applications of this model could be in attempting to determine tasting notes in various wines or in a similar manner with restaurant reviews.\\n\\nPlease read paper \\\"Classifying Beer Styles Using an Interpretable NLP Model\\\" included for in depth discussion of project\\n\"\n },\n {\n \"alpha_fraction\": 0.6869731545448303,\n \"alphanum_fraction\": 0.7022988796234131,\n \"avg_line_length\": 27.69230842590332,\n \"blob_id\": \"9a6c140ff8f0c13817d6f707c06ef1ef6308ca51\",\n \"content_id\": \"7d74d6838c76ff2e3f4c4d3a8e43d6b59aa19531\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2610,\n \"license_type\": \"no_license\",\n \"max_line_length\": 114,\n \"num_lines\": 91,\n \"path\": \"/build_w2v.py\",\n \"repo_name\": \"inaccare/Beer-Type-Prediction\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import Counter\\nimport numpy as np\\nimport pandas as pd\\nimport re\\nimport sys\\nimport nltk\\nimport codecs\\nimport multiprocessing\\nimport gensim\\n\\ndef clean_and_split_str(string):\\n strip_special_chars = re.compile(\\\"[^A-Za-z]+\\\")\\n string = re.sub(strip_special_chars, \\\" \\\", string)\\n return string.strip().split()\\n\\ndef main():\\n\\tif len(sys.argv) > 3 or len(sys.argv) < 2:\\n\\t\\traise Exception(\\\"usage: python build_w2v.py ratebeer.csv <num_dim>\\\")\\n\\n\\tnum_dim = 100\\n\\tif len(sys.argv) == 3:\\n\\t\\tnum_dim = sys.argv[2]\\n\\n\\tinputfile = sys.argv[1]\\n\\traw_df = pd.read_csv(inputfile, header = 0)\\n\\tprint(\\\"data loaded\\\")\\n\\n\\traw_corpus = u\\\"\\\".join(raw_df['review/text'].astype(str) + \\\" \\\")\\n\\tprint(\\\"Raw Corpus contains {0:,} words\\\".format(len(raw_corpus.split())))\\n\\n\\ttokenizer = nltk.data.load(\\\"tokenizers/punkt/english.pickle\\\")\\n\\tprint(\\\"The punkt tokenizer is loaded\\\")\\n\\traw_sentences = tokenizer.tokenize(raw_corpus)\\n\\tprint(\\\"We have {0:,} raw sentences\\\".format(len(raw_sentences)))\\n\\n\\tsentences = []\\n\\tfor raw_sent in raw_sentences:\\n\\t\\tif len(raw_sent) > 0:\\n\\t\\t\\tsentences.append(clean_and_split_str(raw_sent.lower()))\\n\\tprint(\\\"We have {0:,} clean sentences\\\".format(len(sentences)))\\n\\n\\ttoken_count = sum([len(sentence) for sentence in sentences])\\n\\tprint(\\\"The dataset corpus contains {0:,} tokens\\\".format(token_count))\\n\\n\\t#Dimensionality of the resulting word vectors\\n\\tnum_features = num_dim\\n\\t#Minimum word count threshold\\n\\tmin_word_count = 2\\n\\t#Number of threads to run in parallel\\n\\tnum_workers = multiprocessing.cpu_count() \\n\\t#Context window length\\n\\tcontext_size = 7\\n\\t#Seed for the RNG, to make the result reproducible\\n\\tseed = 1\\n\\t\\n\\tword2vec_model = gensim.models.word2vec.Word2Vec(\\n sg=1,\\n seed=seed,\\n workers=num_workers, \\n size=num_features, \\n min_count=min_word_count, \\n window=context_size)\\n\\t \\n\\tword2vec_model.build_vocab(sentences=sentences)\\n\\tprint(\\\"The vocabulary is built\\\")\\n\\tprint(\\\"Word2Vec vocabulary length: \\\", len(word2vec_model.wv.vocab))\\n\\t \\n\\t#Start training the model\\n\\tword2vec_model.train(sentences=sentences, total_examples=word2vec_model.corpus_count, epochs=word2vec_model.iter)\\n\\tprint(\\\"Training finished\\\")\\n\\n\\tword2vec_model.save(\\\"Beer_reviews_trained.w2v\\\")\\n\\tprint(\\\"Model saved\\\")\\n\\n\\tw2v_model = gensim.models.word2vec.Word2Vec.load(\\\"Beer_reviews_trained.w2v\\\")\\n\\tprint(\\\"Model loaded\\\")\\n\\n\\tcounter = 0\\n\\tfor word in w2v_model.wv.vocab:\\n\\t\\tprint(\\\"word: \\\", word)\\n\\t\\tprint(w2v_model.wv[word])\\n\\t\\tcounter += 1\\n\\t\\tif counter > 10:\\n\\t\\t\\tbreak\\n\\n\\t# df_des = df['item_description']\\n\\t# df_des.to_csv('pandas.txt', header=None, index=None, sep=' ', mode='a', escapechar=\\\" \\\")\\n\\treturn\\n\\nif __name__ == \\\"__main__\\\":\\n\\tmain()\"\n },\n {\n \"alpha_fraction\": 0.6259258985519409,\n \"alphanum_fraction\": 0.6555555462837219,\n \"avg_line_length\": 18.321428298950195,\n \"blob_id\": \"78dc52c80b7d424fb8d93e0505164dbfa7ea6307\",\n \"content_id\": \"cf4e8b4542805af846d17219eed2b50c37a5d822\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 540,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 28,\n \"path\": \"/get_lengths.py\",\n \"repo_name\": \"inaccare/Beer-Type-Prediction\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nimport matplotlib.pyplot as plt\\nimport os\\nimport json\\nimport pandas as pd\\n\\n\\nbins = 30\\nbeer_file = 'beers.csv'\\n\\nx = []\\n\\nwith open(beer_file) as f:\\n\\tdf = pd.read_csv(f)\\n\\tlength = len(df['text'])\\n\\tfor i, row in enumerate(df['text'][:-1]):\\n\\t\\tif i % 100000:\\n\\t\\t\\tprint str(i) + '/' + str(length)\\n\\t\\tx.append(len(row))\\n\\n\\tvals = np.asarray(x, dtype=np.int32)\\n\\n\\tplt.xlabel('Tokens')\\n\\tplt.ylabel('Number of Reviews')\\n\\tplt.title('Beer Review Lengths')\\n\\tplt.hist(vals, bins, range=[0, 1500])\\n\\t#plt.show()\\n\\tplt.savefig('review_len.png')\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":7,"string":"7"}}},{"rowIdx":2977688,"cells":{"repo_name":{"kind":"string","value":"noahdesu/ucsc-transit"},"repo_url":{"kind":"string","value":"https://github.com/noahdesu/ucsc-transit"},"snapshot_id":{"kind":"string","value":"d70120e6a6b9e25c615d04d78650d68bf5ad909a"},"revision_id":{"kind":"string","value":"d5b6bc81e4af4c843dd467eb7044027078d58ffb"},"directory_id":{"kind":"string","value":"e22c8eec86a438d3caeed8ef6596ba909c4a2653"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-21T09:53:55.404844","string":"2021-01-21T09:53:55.404844"},"revision_date":{"kind":"timestamp","value":"2017-02-27T19:43:58","string":"2017-02-27T19:43:58"},"committer_date":{"kind":"timestamp","value":"2017-02-27T20:08:39","string":"2017-02-27T20:08:39"},"github_id":{"kind":"number","value":83350221,"string":"83,350,221"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5744680762290955,"alphanum_fraction":0.7446808218955994,"avg_line_length":22.5,"blob_id":"8a2c4a803106c7a263dcdd51ad58847e3f998d9f","content_id":"933374d6111794ccc5d632806e3d996ad9c73154","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":47,"license_type":"no_license","max_line_length":29,"num_lines":2,"path":"/requirements.txt","repo_name":"noahdesu/ucsc-transit","src_encoding":"UTF-8","text":"requests==2.13.0\ngoogle-cloud-bigquery==0.23.0\n"},{"alpha_fraction":0.5437997579574585,"alphanum_fraction":0.5506256818771362,"avg_line_length":26.46875,"blob_id":"35c2e83b4d1d41ddbcc26d4ea6866b7ecf338210","content_id":"8868df05c0629cb279268b3642cd8784a4114714","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":879,"license_type":"no_license","max_line_length":65,"num_lines":32,"path":"/sample.py","repo_name":"noahdesu/ucsc-transit","src_encoding":"UTF-8","text":"import time\nimport datetime\nimport requests\nfrom google.cloud import bigquery\n\nbigquery_client = bigquery.Client()\ndataset = bigquery_client.dataset('locations')\ntable = dataset.table('samples')\n\ntable.reload()\n\nwhile True:\n try:\n r = requests.get('http://bts.ucsc.edu:8081/location/get')\n timestamp = datetime.datetime.utcnow()\n rows = []\n for row in r.json():\n rows.append((timestamp, row['id'], row['lat'], \\\n row['lon'], row['type']))\n if len(rows) > 0:\n errors = table.insert_data(rows)\n if errors:\n msg = \"error {}\".format(errors)\n print msg\n else:\n print 'loaded {} rows'.format(len(rows))\n except Exception as err:\n msg = \"error {}\".format(err)\n print msg\n continue\n finally:\n time.sleep(2)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5744680762290955,\n \"alphanum_fraction\": 0.7446808218955994,\n \"avg_line_length\": 22.5,\n \"blob_id\": \"8a2c4a803106c7a263dcdd51ad58847e3f998d9f\",\n \"content_id\": \"933374d6111794ccc5d632806e3d996ad9c73154\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 47,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 2,\n \"path\": \"/requirements.txt\",\n \"repo_name\": \"noahdesu/ucsc-transit\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"requests==2.13.0\\ngoogle-cloud-bigquery==0.23.0\\n\"\n },\n {\n \"alpha_fraction\": 0.5437997579574585,\n \"alphanum_fraction\": 0.5506256818771362,\n \"avg_line_length\": 26.46875,\n \"blob_id\": \"35c2e83b4d1d41ddbcc26d4ea6866b7ecf338210\",\n \"content_id\": \"8868df05c0629cb279268b3642cd8784a4114714\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 879,\n \"license_type\": \"no_license\",\n \"max_line_length\": 65,\n \"num_lines\": 32,\n \"path\": \"/sample.py\",\n \"repo_name\": \"noahdesu/ucsc-transit\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import time\\nimport datetime\\nimport requests\\nfrom google.cloud import bigquery\\n\\nbigquery_client = bigquery.Client()\\ndataset = bigquery_client.dataset('locations')\\ntable = dataset.table('samples')\\n\\ntable.reload()\\n\\nwhile True:\\n try:\\n r = requests.get('http://bts.ucsc.edu:8081/location/get')\\n timestamp = datetime.datetime.utcnow()\\n rows = []\\n for row in r.json():\\n rows.append((timestamp, row['id'], row['lat'], \\\\\\n row['lon'], row['type']))\\n if len(rows) > 0:\\n errors = table.insert_data(rows)\\n if errors:\\n msg = \\\"error {}\\\".format(errors)\\n print msg\\n else:\\n print 'loaded {} rows'.format(len(rows))\\n except Exception as err:\\n msg = \\\"error {}\\\".format(err)\\n print msg\\n continue\\n finally:\\n time.sleep(2)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2977689,"cells":{"repo_name":{"kind":"string","value":"LikeLionSCH/github-practice-A-team"},"repo_url":{"kind":"string","value":"https://github.com/LikeLionSCH/github-practice-A-team"},"snapshot_id":{"kind":"string","value":"f9ceeb4b5d72f25372a79571fdf51e85e96aed18"},"revision_id":{"kind":"string","value":"cd37f52179aeafea96d7ec2dfcfaa062d7aa5a05"},"directory_id":{"kind":"string","value":"e9d4be9f2eb3ce42ee2d0628a6ee449303d041c4"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2022-11-18T13:49:38.681935","string":"2022-11-18T13:49:38.681935"},"revision_date":{"kind":"timestamp","value":"2020-07-22T11:50:26","string":"2020-07-22T11:50:26"},"committer_date":{"kind":"timestamp","value":"2020-07-22T11:50:26","string":"2020-07-22T11:50:26"},"github_id":{"kind":"number","value":281620668,"string":"281,620,668"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.739130437374115,"alphanum_fraction":0.782608687877655,"avg_line_length":23,"blob_id":"8cb388cc310b74c2c539161b552f9b12d8bcf882","content_id":"e5da2402e570fa9fa71e44d30aadb13933ae1378","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":23,"license_type":"no_license","max_line_length":23,"num_lines":1,"path":"/branch_tw.py","repo_name":"LikeLionSCH/github-practice-A-team","src_encoding":"UTF-8","text":"print(\"taewan branch1\")"},{"alpha_fraction":0.5555555820465088,"alphanum_fraction":0.5555555820465088,"avg_line_length":18,"blob_id":"3e3450b906929927d39e7e69c7c8031444b51cfb","content_id":"26ddfcc4eb908959d8a1250eefff73ea517e0b0f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":18,"license_type":"no_license","max_line_length":18,"num_lines":1,"path":"/yulhee.py","repo_name":"LikeLionSCH/github-practice-A-team","src_encoding":"UTF-8","text":"print(\"sorry!!!!\")"},{"alpha_fraction":0.6666666865348816,"alphanum_fraction":0.6666666865348816,"avg_line_length":12,"blob_id":"c80c94fb4a9912e3231ca7348ca716bd6a8c5e54","content_id":"46ee8fc2cce809405c1f3e348acd9f9b1c271656","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":18,"license_type":"no_license","max_line_length":12,"num_lines":1,"path":"/tw.py","repo_name":"LikeLionSCH/github-practice-A-team","src_encoding":"UTF-8","text":"print(\"화이팅\")"},{"alpha_fraction":0.7142857313156128,"alphanum_fraction":0.7142857313156128,"avg_line_length":28,"blob_id":"f128d4ce252f9000a9177516479b2514ea8c9100","content_id":"b263ead839c80db8fe120cea0180d7b91db5448c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":28,"license_type":"no_license","max_line_length":28,"num_lines":1,"path":"/newwhite.py","repo_name":"LikeLionSCH/github-practice-A-team","src_encoding":"UTF-8","text":"print(\"I made a new branch\")"},{"alpha_fraction":0.6363636255264282,"alphanum_fraction":0.6363636255264282,"avg_line_length":22,"blob_id":"c09234357086b8c0aecd866fe840b32cdfc8cbbc","content_id":"8492c2f2374f05b1f9905a355855eb42ed141e46","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":22,"license_type":"no_license","max_line_length":22,"num_lines":1,"path":"/white.py","repo_name":"LikeLionSCH/github-practice-A-team","src_encoding":"UTF-8","text":"print(\"Hi. I'm White\")"}],"string":"[\n {\n \"alpha_fraction\": 0.739130437374115,\n \"alphanum_fraction\": 0.782608687877655,\n \"avg_line_length\": 23,\n \"blob_id\": \"8cb388cc310b74c2c539161b552f9b12d8bcf882\",\n \"content_id\": \"e5da2402e570fa9fa71e44d30aadb13933ae1378\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 23,\n \"license_type\": \"no_license\",\n \"max_line_length\": 23,\n \"num_lines\": 1,\n \"path\": \"/branch_tw.py\",\n \"repo_name\": \"LikeLionSCH/github-practice-A-team\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(\\\"taewan branch1\\\")\"\n },\n {\n \"alpha_fraction\": 0.5555555820465088,\n \"alphanum_fraction\": 0.5555555820465088,\n \"avg_line_length\": 18,\n \"blob_id\": \"3e3450b906929927d39e7e69c7c8031444b51cfb\",\n \"content_id\": \"26ddfcc4eb908959d8a1250eefff73ea517e0b0f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 18,\n \"license_type\": \"no_license\",\n \"max_line_length\": 18,\n \"num_lines\": 1,\n \"path\": \"/yulhee.py\",\n \"repo_name\": \"LikeLionSCH/github-practice-A-team\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(\\\"sorry!!!!\\\")\"\n },\n {\n \"alpha_fraction\": 0.6666666865348816,\n \"alphanum_fraction\": 0.6666666865348816,\n \"avg_line_length\": 12,\n \"blob_id\": \"c80c94fb4a9912e3231ca7348ca716bd6a8c5e54\",\n \"content_id\": \"46ee8fc2cce809405c1f3e348acd9f9b1c271656\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 18,\n \"license_type\": \"no_license\",\n \"max_line_length\": 12,\n \"num_lines\": 1,\n \"path\": \"/tw.py\",\n \"repo_name\": \"LikeLionSCH/github-practice-A-team\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(\\\"화이팅\\\")\"\n },\n {\n \"alpha_fraction\": 0.7142857313156128,\n \"alphanum_fraction\": 0.7142857313156128,\n \"avg_line_length\": 28,\n \"blob_id\": \"f128d4ce252f9000a9177516479b2514ea8c9100\",\n \"content_id\": \"b263ead839c80db8fe120cea0180d7b91db5448c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 28,\n \"license_type\": \"no_license\",\n \"max_line_length\": 28,\n \"num_lines\": 1,\n \"path\": \"/newwhite.py\",\n \"repo_name\": \"LikeLionSCH/github-practice-A-team\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(\\\"I made a new branch\\\")\"\n },\n {\n \"alpha_fraction\": 0.6363636255264282,\n \"alphanum_fraction\": 0.6363636255264282,\n \"avg_line_length\": 22,\n \"blob_id\": \"c09234357086b8c0aecd866fe840b32cdfc8cbbc\",\n \"content_id\": \"8492c2f2374f05b1f9905a355855eb42ed141e46\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 22,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 1,\n \"path\": \"/white.py\",\n \"repo_name\": \"LikeLionSCH/github-practice-A-team\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(\\\"Hi. I'm White\\\")\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":5,"string":"5"}}},{"rowIdx":2977690,"cells":{"repo_name":{"kind":"string","value":"pkmollman/advent_2020"},"repo_url":{"kind":"string","value":"https://github.com/pkmollman/advent_2020"},"snapshot_id":{"kind":"string","value":"848834a968431211ad168083e7cb66bf0b0b6dd7"},"revision_id":{"kind":"string","value":"d9a84e907dc67abdb97e7dc86109068be4b8080e"},"directory_id":{"kind":"string","value":"f828734421d54b2764e7760123993b35f10a5764"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-01-30T01:41:36.570906","string":"2023-01-30T01:41:36.570906"},"revision_date":{"kind":"timestamp","value":"2020-12-11T06:38:18","string":"2020-12-11T06:38:18"},"committer_date":{"kind":"timestamp","value":"2020-12-11T06:38:18","string":"2020-12-11T06:38:18"},"github_id":{"kind":"number","value":317447825,"string":"317,447,825"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6397820115089417,"alphanum_fraction":0.6583106517791748,"avg_line_length":27.671875,"blob_id":"3b03ece4945fd921495d80e8fb8978b1dbffe631","content_id":"8150fe35ffa4e7428001a5f4003f3df13e9fc970","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1835,"license_type":"no_license","max_line_length":106,"num_lines":64,"path":"/8/5.py","repo_name":"pkmollman/advent_2020","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n\nfrom multiprocessing import Pool\n\nadapters = []\n\n# with open('input.txt', 'r') as f:\n# adapters = [int(line.strip()) for line in f.readlines()]\n\nwith open('testinput1.txt', 'r') as f:\n adapters = [int(line.strip()) for line in f.readlines()]\n\nadapters.append(0)\nadapters.sort()\nadapters.append(adapters[-1]+3)\n\nadapters_r = adapters[::-1]\n\ncount_one_gap = 1\ncount_three_gap = 1\n\nglobal g_counter\ng_counter = 0\n\nmain_list = []\n\ndef options(i, slices):\n return [ num for num in slices if (num - i) <= 3 ]\n\ndef options_r(i, adapters, adapter, sliced):\n global g_counter\n for nummy,option in enumerate([ num for num in sliced if (num - adapter) <= 3 ]):\n if option == adapters[-1]:\n g_counter += 1\n option_index = i + nummy + 1\n options_r(option_index,adapters,option,adapters[option_index+1:option_index+4])\n\ndef options_rb(i, adapters, adapter, sliced):\n global g_counter\n for nummy,option in enumerate([ num for num in sliced if (adapter - num) <= 3 ]):\n if option == adapters[-1]:\n g_counter += 1\n option_index = i + nummy + 1\n options_rb(option_index,adapters,option,adapters[option_index+1:option_index+4])\n\n\n\nadapt_len = len(adapters)\nadapt_mid = int(adapt_len//2)\n\nmid_starts = [adapt_mid-1,adapt_mid,adapt_mid+1]\nback_starts = [adapters_r.index(adapters[num-3]) for num in mid_starts]\nprint(back_starts)\nprint(mid_starts)\n# for start in mid_starts:\n# options_r(start, adapters, adapters[start],adapters[start+1:start+4])\n\nfor start in back_starts:\n options_rb(start, adapters_r, adapters_r[start],adapters_r[start+1:start+4])\n\nprint(g_counter)\n# def thread_i_guess(ind,v):\n# option_index = i + ind + 1\n# thingy += options_r3(option_index,adapters,option,adapters[option_index+1:option_index+4],g_counter)\n"},{"alpha_fraction":0.5581947565078735,"alphanum_fraction":0.5724465847015381,"avg_line_length":34.16666793823242,"blob_id":"7f4b62de6614fe4abdc3fd76344359bfc285210b","content_id":"2caf7374b8f48b112e07751e3becdd37007c7d43","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":421,"license_type":"no_license","max_line_length":79,"num_lines":12,"path":"/2/1.py","repo_name":"pkmollman/advent_2020","src_encoding":"UTF-8","text":"passwd_list = []\nwith open('input.txt','r') as f:\n for line in f.readlines():\n clean_line = line.strip().split(' ')\n min_max = clean_line[0].split('-')\n letter = clean_line[1][0]\n passwd = clean_line[2]\n passwd_count = passwd.count(letter)\n if passwd_count >= int(min_max[0]) and passwd_count <= int(min_max[1]):\n passwd_list.append(passwd)\n\nprint(len(passwd_list))"},{"alpha_fraction":0.5519630312919617,"alphanum_fraction":0.570438802242279,"avg_line_length":35.16666793823242,"blob_id":"7c5b876f932d71837df219a93946e76197063266","content_id":"3485ad4138e0b15ee3d4515ad69afbee9430cc88","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":433,"license_type":"no_license","max_line_length":93,"num_lines":12,"path":"/2/2.py","repo_name":"pkmollman/advent_2020","src_encoding":"UTF-8","text":"passwd_list = []\nwith open('input.txt','r') as f:\n for line in f.readlines():\n clean_line = line.strip().split(' ')\n poses = clean_line[0].split('-')\n letter = clean_line[1][0]\n passwd = clean_line[2]\n passwd_count = passwd.count(letter)\n if bool(passwd[int(poses[0])-1] == letter) ^ bool(passwd[int(poses[1])-1] == letter):\n passwd_list.append(passwd)\n\nprint(len(passwd_list))"},{"alpha_fraction":0.5926460027694702,"alphanum_fraction":0.615717351436615,"avg_line_length":24.703702926635742,"blob_id":"14bcb77557262b3f933f469bdfba3edd246c88cd","content_id":"b5eaffd9cbf02dbdb4f28247c4c237d0e2a52717","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1387,"license_type":"no_license","max_line_length":87,"num_lines":54,"path":"/8/2.py","repo_name":"pkmollman/advent_2020","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n\nadapters = []\n\nwith open('input.txt', 'r') as f:\n adapters = [int(line.strip()) for line in f.readlines()]\n\n\nadapters.append(0)\nadapters.sort()\nadapters.append(adapters[-1]+3)\n\ncount_one_gap = 1\ncount_three_gap = 1\n\nglobal g_counter\ng_counter = 0\n\nmain_list = []\n\ndef options(i, slices):\n return [ num for num in slices if (num - i) <= 3 ]\n\ndef options_r(i, adapters, adapter, sliced):\n global g_counter\n for option in [ num for num in sliced if (num - adapter) <= 3 ]:\n # print(option)\n if option == adapters[-1]:\n g_counter += 1\n main_list.append(option)\n # return g_counter\n option_index = adapters.index(option)\n options_r(option_index,adapters,option,adapters[option_index+1:option_index+4])\n\noption_multiplier = 1\n\nprint(options_r(0,adapters,adapters[0],adapters[1:4]))\nprint(main_list)\nprint(g_counter)\n\n# for i,adapter in enumerate(adapters):\n# if i == 0:\n# pass\n# elif adapter - adapters[i-1] == 1:\n# count_one_gap += 1\n# elif adapter - adapters[i-1] == 3:\n# count_three_gap += 1\n# print(adapter)\n# print(options(adapter, adapters[i+1:i+4]))\n# if len(options(adapter, adapters[i+1:i+4])) > 0:\n# option_multiplier *= len(options(adapter, adapters[i+1:i+4]))\n\n# print(count_one_gap * count_three_gap)\n# print(option_multiplier)"},{"alpha_fraction":0.5175023674964905,"alphanum_fraction":0.5373699069023132,"avg_line_length":22.46666717529297,"blob_id":"c610febfee4436fbf00a3b3ba613110fb2ad2fdc","content_id":"306df50ebbdf7f69930e69c37cc69d8b8b2a3079","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1057,"license_type":"no_license","max_line_length":66,"num_lines":45,"path":"/5/2.py","repo_name":"pkmollman/advent_2020","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n\ndef seat_id(seat):\n\n row_max = 128\n row_min = 0\n row_nums = list(range(row_min,row_max))\n\n for char in seat[:7]:\n if char == 'F':\n row_nums = row_nums[:(len(row_nums))//2]\n continue\n row_nums = row_nums[int((len(row_nums))//2):]\n # print(row_nums)\n\n column_max = 8\n column_min = 0\n column_nums = list(range(column_min,column_max))\n\n for char in seat[-3:]:\n if char == 'L':\n column_nums = column_nums[:int((len(column_nums))//2)]\n continue\n column_nums = column_nums[int((len(column_nums))//2):]\n # print(column_nums)\n return row_nums[0] * 8 + column_nums[0]\n\nseat_ids = []\n\nwith open('input.txt', 'r') as f:\n for line in f.readlines():\n seat_ids.append(seat_id(line.strip()))\n # print(line)\n\nseat_ids.sort()\nprint(seat_ids[-1])\n\nseat_ids.sort()\n\nfor seat in range(len(seat_ids)):\n if seat == 0:\n pass\n else:\n if seat_ids[seat-1] != seat_ids[seat]-1:\n print(seat_ids[seat]-1)\n\n"},{"alpha_fraction":0.5655339956283569,"alphanum_fraction":0.5902912616729736,"avg_line_length":23.83132553100586,"blob_id":"c295fb77a0a90370e659cac799c9b3e563960014","content_id":"068d1384ca4d42c661fe6f242bc53a96b0e1be1e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2060,"license_type":"no_license","max_line_length":100,"num_lines":83,"path":"/4/1.py","repo_name":"pkmollman/advent_2020","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n\nimport re\n\npassports_text = ''\n\nwith open('input.txt', 'r') as f:\n for line in f.readlines():\n passports_text += line\n\ndef byr(value):\n if len(value) == 4 and int(value) >= 1920 and int(value) <= 2002:\n return True\n return False\ndef iyr(value):\n if len(value) == 4 and int(value) >= 2010 and int(value) <= 2020:\n return True\n return False\ndef eyr(value):\n if len(value) == 4 and int(value) >= 2020 and int(value) <= 2030:\n return True\n return False\ndef hgt(value):\n if 'cm' in value[-2:] and 150 <= int(value[:-2]) <= 193:\n return True\n if 'in' in value[-2:] and 59 <= int(value[:-2]) <= 76:\n return True\n return False\ndef hcl(value):\n return re.match('^#[0-9a-f]{6}$',value)\ndef ecl(value):\n return value in ['amb','blu','brn','gry','grn','hzl','oth']\ndef pid(value):\n # this is trash, shoot me\n return re.match('^[0-9]{9}$',value)\n\nrequired_values = {\n 'byr': byr,\n 'iyr': iyr,\n 'eyr': eyr,\n 'hgt': hgt,\n 'hcl': hcl,\n 'ecl': ecl,\n 'pid': pid,\n}\n\nunsep_passports = passports_text.split('\\n')\npassports = []\npassport_group = []\n\nfor line in unsep_passports:\n if line == '':\n passports.append(passport_group)\n passport_group = []\n elif line == unsep_passports[-1]:\n passport_group.append(line)\n passports.append(passport_group)\n else:\n passport_group.append(line)\n\nclean_passports = []\n\nfor passport in passports:\n clean_passport = {}\n for line in passport:\n for key_value in line.split(' '):\n k,v = key_value.split(':')\n clean_passport[k] = v\n clean_passports.append(clean_passport)\n\nvalid_passports = 0\n\nfor passport in clean_passports:\n valid_passport = True\n for required_value in required_values:\n if required_value in passport and required_values[required_value](passport[required_value]):\n pass\n else:\n valid_passport = False\n if valid_passport:\n valid_passports += 1\n\nprint(valid_passports)"},{"alpha_fraction":0.6149377822875977,"alphanum_fraction":0.6390041708946228,"avg_line_length":26.409090042114258,"blob_id":"ecfcf4f64340f14bca17023d10e463e75050f4cc","content_id":"95e34e1a84a5504392cd05952b3142a9e98c5769","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1205,"license_type":"no_license","max_line_length":108,"num_lines":44,"path":"/8/3.py","repo_name":"pkmollman/advent_2020","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n\nadapters = []\n\nwith open('input.txt', 'r') as f:\n adapters = [int(line.strip()) for line in f.readlines()]\n\n\nadapters.append(0)\nadapters.sort()\nadapters.append(adapters[-1]+3)\n\ncount_one_gap = 1\ncount_three_gap = 1\n\nglobal g_counter\n# g_counter = 0\n\nmain_list = []\n\ndef options(i, slices):\n return [ num for num in slices if (num - i) <= 3 ]\n\ndef options_r(i, adapters, adapter, sliced):\n global g_counter\n for nummy,option in enumerate([ num for num in sliced if (num - adapter) <= 3 ]):\n if option == adapters[-1]:\n g_counter += 1\n option_index = i + nummy + 1\n options_r(option_index,adapters,option,adapters[option_index+1:option_index+4])\n\ndef options_r2(i, adapters, adapter, sliced, g_counter):\n thingy = g_counter\n for nummy,option in enumerate([ num for num in sliced if (num - adapter) <= 3 ]):\n if option == adapters[-1]:\n thingy += 1\n option_index = i + nummy + 1\n thingy += options_r2(option_index,adapters,option,adapters[option_index+1:option_index+4],g_counter)\n return thingy\n\noption_multiplier = 1\n\ng_counter = options_r2(0,adapters,adapters[0],adapters[1:4],0)\nprint(g_counter)"},{"alpha_fraction":0.638436496257782,"alphanum_fraction":0.6416938304901123,"avg_line_length":26.909090042114258,"blob_id":"96cef93af14cd3ea6bd0972ffd91e3c926d059d8","content_id":"751a523388b5d6feaea9c2d2a8683c516c8df5f3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1228,"license_type":"no_license","max_line_length":73,"num_lines":44,"path":"/6/2.py","repo_name":"pkmollman/advent_2020","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n\ninput_text = ''\n\nwith open('input.txt', 'r') as f:\n input_text = f.read().split('\\n')\n\ntext_groups = []\ntext_group = []\n\n# for single line of answers append to a list,\n# once a blank line is reached, append list to the main list,\n# and reset current working list to empty\nfor line in input_text:\n if line == '':\n text_groups.append(text_group)\n text_group = []\n continue\n text_group.append(line)\n\ngroup_answer_total = 0\n\n# for list of answer strings in text_groups\nfor group in text_groups:\n # track group's unique answers\n letters = []\n for answers in group:\n for letter in answers:\n if letter in letters:\n continue\n letters.append(letter)\n # track all group's answer strings in a single string\n all_answers = ''\n for answers in group:\n all_answers += answers\n # track group's valid answers\n group_total = 0\n # if unique letter count in combined answer string\n # equals number of group members the answer is counted in group_total\n for letter in letters:\n if all_answers.count(letter) == len(group): group_total += 1\n group_answer_total += group_total\n\nprint(group_answer_total)\n"},{"alpha_fraction":0.5767441987991333,"alphanum_fraction":0.6000000238418579,"avg_line_length":19.5238094329834,"blob_id":"fc89b44565edaedd570dcfceb8feb2237c18dd4d","content_id":"574c5c19b3492f7e1a90804cd8a550331bcafe66","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":430,"license_type":"no_license","max_line_length":60,"num_lines":21,"path":"/8/1.py","repo_name":"pkmollman/advent_2020","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n\nadapters = []\n\nwith open('input.txt', 'r') as f:\n adapters = [int(line.strip()) for line in f.readlines()]\n\nadapters.sort()\n\ncount_one_gap = 1\ncount_three_gap = 1\n\nfor i,adapter in enumerate(adapters):\n if i == 0:\n pass\n elif adapter - adapters[i-1] == 1:\n count_one_gap += 1\n elif adapter - adapters[i-1] == 3:\n count_three_gap += 1\n\nprint(count_one_gap * count_three_gap)"},{"alpha_fraction":0.5768194198608398,"alphanum_fraction":0.584007203578949,"avg_line_length":26.170732498168945,"blob_id":"4960e71d5b7e4ddccc1cc0b1a0efeaca40894c3d","content_id":"a676844c6de9a5134b9614c4cb4fe0061294d02c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1113,"license_type":"no_license","max_line_length":78,"num_lines":41,"path":"/7/1.py","repo_name":"pkmollman/advent_2020","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n\nimport re\n\n# REGEX = r'([\\w\\s]+)bags contain((\\s\\d+)\\s([\\w\\s]+)bags?[\\.,])+'\nmain_bag_reg = r'([\\w\\s]+)bags contain'\ninner_bag_reg = r'((\\s\\d+)\\s([\\w\\s]+) bags?)+'\ninput_text = ''\n\nwith open('input.txt', 'r') as f:\n input_text = [line for line in f.readlines()]\n\nbag_types = {}\n\nfor line in input_text:\n main_result = re.match(main_bag_reg, line)\n inner_result = re.findall(inner_bag_reg, line)\n bag_types[main_result.group(1).strip()] = {}\n for result in inner_result:\n bag_types[main_result.group(1).strip()][result[2].strip()] = result[1]\n\ncontains_shiny_golds = []\n\nfor bag in bag_types:\n # print(bag_types[bag])\n if 'shiny gold' in bag_types[bag]:\n contains_shiny_golds.append(bag)\n\n\nwhile True:\n inner_num = 0\n for bag_type in bag_types:\n for bag in contains_shiny_golds:\n if bag in bag_types[bag_type]:\n if not bag_type in contains_shiny_golds:\n contains_shiny_golds.append(bag_type)\n inner_num += 1\n if inner_num == 0:\n break\n\nprint(len(contains_shiny_golds))"},{"alpha_fraction":0.6105263233184814,"alphanum_fraction":0.6168420910835266,"avg_line_length":24,"blob_id":"0e0fbd6f149fb7c4139c21d2163da07b484a91b6","content_id":"f595d3433cd76ff9f2edc8849286c9d342458140","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":950,"license_type":"no_license","max_line_length":83,"num_lines":38,"path":"/7/2.py","repo_name":"pkmollman/advent_2020","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n\nimport re\n\nmain_bag_reg = r'([\\w\\s]+)bags contain'\ninner_bag_reg = r'((\\s\\d+)\\s([\\w\\s]+) bags?)+'\ninput_text = ''\n\nwith open('input.txt', 'r') as f:\n input_text = [line for line in f.readlines()]\n\nbag_types = {}\n\nfor line in input_text:\n main_result = re.match(main_bag_reg, line)\n inner_result = re.findall(inner_bag_reg, line)\n bag_types[main_result.group(1).strip()] = {}\n for result in inner_result:\n bag_types[main_result.group(1).strip()][result[2].strip()] = int(result[1])\n\nshiny_golds = list(bag_types['shiny gold'].keys())\n\nnumber_o_bags = 0\n\ndef num_bag(bag_type, number):\n numbag = number\n if bag_types[bag_type]:\n for bag in bag_types[bag_type]:\n numbag += num_bag(bag, bag_types[bag_type][bag]) * number\n else:\n return number\n return numbag\n\n\nfor bag in shiny_golds:\n number_o_bags += num_bag(bag, bag_types['shiny gold'][bag])\n\nprint(number_o_bags)\n"},{"alpha_fraction":0.5201109647750854,"alphanum_fraction":0.545076310634613,"avg_line_length":19.05555534362793,"blob_id":"aab43044098768b922e01a1c772fe504196f1437","content_id":"b883688bd458b788d7b487a1e66a6b83c04213b3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":721,"license_type":"no_license","max_line_length":55,"num_lines":36,"path":"/3/1.py","repo_name":"pkmollman/advent_2020","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n\nmatrix = []\nlocation = [0,0]\ntrees = 0\nbig_number = 0\nslopes = [\n [3,1],\n]\n\nwith open('input.txt', 'r') as f:\n for line in f.readlines():\n matrix.append(line.strip())\n\ndef tree_or_nah(matrix,x,y):\n r_x = (x % len(matrix[0]))\n print(r_x, y)\n print(matrix[y])\n if matrix[y][r_x] == '#':\n return True\n return False\n\nfor slope in slopes:\n while location[1] < len(matrix)-1:\n location[0] += slope[0]\n location[1] += slope[1]\n print(location)\n if tree_or_nah(matrix,location[0],location[1]):\n trees += 1\n if big_number == 0:\n big_number = trees\n else:\n big_number *= trees\n\nprint(trees)\nprint(big_number)"},{"alpha_fraction":0.5184404850006104,"alphanum_fraction":0.5447840094566345,"avg_line_length":22.75,"blob_id":"9a2c1d67a94ac879979e75194548dcde83db6b9b","content_id":"09beea555fccf92004aa9cf5d7c9e209f39ab706","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":949,"license_type":"no_license","max_line_length":69,"num_lines":40,"path":"/5/1.py","repo_name":"pkmollman/advent_2020","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n\ndef seat_id(seat):\n\n row_max = 128\n row_min = 0\n row_nums = list(range(row_min,row_max))\n\n for char in seat[:7]:\n if char == 'F':\n row_nums = row_nums[:int((len(row_nums)-1)/2)+1]\n if char == 'B':\n row_nums = row_nums[int((len(row_nums)-1)/2)+1:]\n print(row_nums)\n\n column_max = 8\n column_min = 0\n column_nums = list(range(column_min,column_max))\n\n for char in seat[-3:]:\n if char == 'L':\n column_nums = column_nums[:int((len(column_nums)-1)/2)+1]\n if char == 'R':\n column_nums = column_nums[int((len(column_nums)-1)/2)+1:]\n print(column_nums)\n return row_nums[0] * 8 + column_nums[0]\n\n\nprint(seat_id('BBFFBBFRLL'))\n\nseat_ids = []\n\nwith open('input.txt', 'r') as f:\n for line in f.readlines():\n seat_ids.append(seat_id(line.strip()))\n print(line)\n\nseat_ids.sort()\nprint(seat_ids)\nprint(seat_ids[-1])"},{"alpha_fraction":0.6631355881690979,"alphanum_fraction":0.6652542352676392,"avg_line_length":24.513513565063477,"blob_id":"d4241fb400559a1299262c675071b5db862fe4c7","content_id":"89503c3597d547e3d935891f3980a1bfe5e2fe07","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":944,"license_type":"no_license","max_line_length":73,"num_lines":37,"path":"/6/1.py","repo_name":"pkmollman/advent_2020","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n\ninput_text = ''\n\nwith open('input.txt', 'r') as f:\n input_text = f.read().split('\\n')\n\n# track each group of answers as a single string\ntext_groups = []\n\n# track current group for below iteration \ntext_group = ''\n\n# for single line of answers append to a single string,\n# once a blank line is reached, append to the main list,\n# and reset current working string to empty\nfor line in input_text:\n if line == '':\n text_groups.append(text_group)\n text_group = ''\n continue\n text_group += line\n\n# total sum of unique answers per group\ngroup_answer_total = 0\n\n# for char in group answer string, if char not in letters list, append it\n# len(letters) is group total unique answers\nfor group in text_groups:\n letters = []\n for letter in group:\n if letter in letters:\n continue\n letters.append(letter)\n group_answer_total += len(letters)\n\nprint(group_answer_total)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6397820115089417,\n \"alphanum_fraction\": 0.6583106517791748,\n \"avg_line_length\": 27.671875,\n \"blob_id\": \"3b03ece4945fd921495d80e8fb8978b1dbffe631\",\n \"content_id\": \"8150fe35ffa4e7428001a5f4003f3df13e9fc970\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1835,\n \"license_type\": \"no_license\",\n \"max_line_length\": 106,\n \"num_lines\": 64,\n \"path\": \"/8/5.py\",\n \"repo_name\": \"pkmollman/advent_2020\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\nfrom multiprocessing import Pool\\n\\nadapters = []\\n\\n# with open('input.txt', 'r') as f:\\n# adapters = [int(line.strip()) for line in f.readlines()]\\n\\nwith open('testinput1.txt', 'r') as f:\\n adapters = [int(line.strip()) for line in f.readlines()]\\n\\nadapters.append(0)\\nadapters.sort()\\nadapters.append(adapters[-1]+3)\\n\\nadapters_r = adapters[::-1]\\n\\ncount_one_gap = 1\\ncount_three_gap = 1\\n\\nglobal g_counter\\ng_counter = 0\\n\\nmain_list = []\\n\\ndef options(i, slices):\\n return [ num for num in slices if (num - i) <= 3 ]\\n\\ndef options_r(i, adapters, adapter, sliced):\\n global g_counter\\n for nummy,option in enumerate([ num for num in sliced if (num - adapter) <= 3 ]):\\n if option == adapters[-1]:\\n g_counter += 1\\n option_index = i + nummy + 1\\n options_r(option_index,adapters,option,adapters[option_index+1:option_index+4])\\n\\ndef options_rb(i, adapters, adapter, sliced):\\n global g_counter\\n for nummy,option in enumerate([ num for num in sliced if (adapter - num) <= 3 ]):\\n if option == adapters[-1]:\\n g_counter += 1\\n option_index = i + nummy + 1\\n options_rb(option_index,adapters,option,adapters[option_index+1:option_index+4])\\n\\n\\n\\nadapt_len = len(adapters)\\nadapt_mid = int(adapt_len//2)\\n\\nmid_starts = [adapt_mid-1,adapt_mid,adapt_mid+1]\\nback_starts = [adapters_r.index(adapters[num-3]) for num in mid_starts]\\nprint(back_starts)\\nprint(mid_starts)\\n# for start in mid_starts:\\n# options_r(start, adapters, adapters[start],adapters[start+1:start+4])\\n\\nfor start in back_starts:\\n options_rb(start, adapters_r, adapters_r[start],adapters_r[start+1:start+4])\\n\\nprint(g_counter)\\n# def thread_i_guess(ind,v):\\n# option_index = i + ind + 1\\n# thingy += options_r3(option_index,adapters,option,adapters[option_index+1:option_index+4],g_counter)\\n\"\n },\n {\n \"alpha_fraction\": 0.5581947565078735,\n \"alphanum_fraction\": 0.5724465847015381,\n \"avg_line_length\": 34.16666793823242,\n \"blob_id\": \"7f4b62de6614fe4abdc3fd76344359bfc285210b\",\n \"content_id\": \"2caf7374b8f48b112e07751e3becdd37007c7d43\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 421,\n \"license_type\": \"no_license\",\n \"max_line_length\": 79,\n \"num_lines\": 12,\n \"path\": \"/2/1.py\",\n \"repo_name\": \"pkmollman/advent_2020\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"passwd_list = []\\nwith open('input.txt','r') as f:\\n for line in f.readlines():\\n clean_line = line.strip().split(' ')\\n min_max = clean_line[0].split('-')\\n letter = clean_line[1][0]\\n passwd = clean_line[2]\\n passwd_count = passwd.count(letter)\\n if passwd_count >= int(min_max[0]) and passwd_count <= int(min_max[1]):\\n passwd_list.append(passwd)\\n\\nprint(len(passwd_list))\"\n },\n {\n \"alpha_fraction\": 0.5519630312919617,\n \"alphanum_fraction\": 0.570438802242279,\n \"avg_line_length\": 35.16666793823242,\n \"blob_id\": \"7c5b876f932d71837df219a93946e76197063266\",\n \"content_id\": \"3485ad4138e0b15ee3d4515ad69afbee9430cc88\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 433,\n \"license_type\": \"no_license\",\n \"max_line_length\": 93,\n \"num_lines\": 12,\n \"path\": \"/2/2.py\",\n \"repo_name\": \"pkmollman/advent_2020\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"passwd_list = []\\nwith open('input.txt','r') as f:\\n for line in f.readlines():\\n clean_line = line.strip().split(' ')\\n poses = clean_line[0].split('-')\\n letter = clean_line[1][0]\\n passwd = clean_line[2]\\n passwd_count = passwd.count(letter)\\n if bool(passwd[int(poses[0])-1] == letter) ^ bool(passwd[int(poses[1])-1] == letter):\\n passwd_list.append(passwd)\\n\\nprint(len(passwd_list))\"\n },\n {\n \"alpha_fraction\": 0.5926460027694702,\n \"alphanum_fraction\": 0.615717351436615,\n \"avg_line_length\": 24.703702926635742,\n \"blob_id\": \"14bcb77557262b3f933f469bdfba3edd246c88cd\",\n \"content_id\": \"b5eaffd9cbf02dbdb4f28247c4c237d0e2a52717\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1387,\n \"license_type\": \"no_license\",\n \"max_line_length\": 87,\n \"num_lines\": 54,\n \"path\": \"/8/2.py\",\n \"repo_name\": \"pkmollman/advent_2020\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\nadapters = []\\n\\nwith open('input.txt', 'r') as f:\\n adapters = [int(line.strip()) for line in f.readlines()]\\n\\n\\nadapters.append(0)\\nadapters.sort()\\nadapters.append(adapters[-1]+3)\\n\\ncount_one_gap = 1\\ncount_three_gap = 1\\n\\nglobal g_counter\\ng_counter = 0\\n\\nmain_list = []\\n\\ndef options(i, slices):\\n return [ num for num in slices if (num - i) <= 3 ]\\n\\ndef options_r(i, adapters, adapter, sliced):\\n global g_counter\\n for option in [ num for num in sliced if (num - adapter) <= 3 ]:\\n # print(option)\\n if option == adapters[-1]:\\n g_counter += 1\\n main_list.append(option)\\n # return g_counter\\n option_index = adapters.index(option)\\n options_r(option_index,adapters,option,adapters[option_index+1:option_index+4])\\n\\noption_multiplier = 1\\n\\nprint(options_r(0,adapters,adapters[0],adapters[1:4]))\\nprint(main_list)\\nprint(g_counter)\\n\\n# for i,adapter in enumerate(adapters):\\n# if i == 0:\\n# pass\\n# elif adapter - adapters[i-1] == 1:\\n# count_one_gap += 1\\n# elif adapter - adapters[i-1] == 3:\\n# count_three_gap += 1\\n# print(adapter)\\n# print(options(adapter, adapters[i+1:i+4]))\\n# if len(options(adapter, adapters[i+1:i+4])) > 0:\\n# option_multiplier *= len(options(adapter, adapters[i+1:i+4]))\\n\\n# print(count_one_gap * count_three_gap)\\n# print(option_multiplier)\"\n },\n {\n \"alpha_fraction\": 0.5175023674964905,\n \"alphanum_fraction\": 0.5373699069023132,\n \"avg_line_length\": 22.46666717529297,\n \"blob_id\": \"c610febfee4436fbf00a3b3ba613110fb2ad2fdc\",\n \"content_id\": \"306df50ebbdf7f69930e69c37cc69d8b8b2a3079\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1057,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 45,\n \"path\": \"/5/2.py\",\n \"repo_name\": \"pkmollman/advent_2020\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\ndef seat_id(seat):\\n\\n row_max = 128\\n row_min = 0\\n row_nums = list(range(row_min,row_max))\\n\\n for char in seat[:7]:\\n if char == 'F':\\n row_nums = row_nums[:(len(row_nums))//2]\\n continue\\n row_nums = row_nums[int((len(row_nums))//2):]\\n # print(row_nums)\\n\\n column_max = 8\\n column_min = 0\\n column_nums = list(range(column_min,column_max))\\n\\n for char in seat[-3:]:\\n if char == 'L':\\n column_nums = column_nums[:int((len(column_nums))//2)]\\n continue\\n column_nums = column_nums[int((len(column_nums))//2):]\\n # print(column_nums)\\n return row_nums[0] * 8 + column_nums[0]\\n\\nseat_ids = []\\n\\nwith open('input.txt', 'r') as f:\\n for line in f.readlines():\\n seat_ids.append(seat_id(line.strip()))\\n # print(line)\\n\\nseat_ids.sort()\\nprint(seat_ids[-1])\\n\\nseat_ids.sort()\\n\\nfor seat in range(len(seat_ids)):\\n if seat == 0:\\n pass\\n else:\\n if seat_ids[seat-1] != seat_ids[seat]-1:\\n print(seat_ids[seat]-1)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5655339956283569,\n \"alphanum_fraction\": 0.5902912616729736,\n \"avg_line_length\": 23.83132553100586,\n \"blob_id\": \"c295fb77a0a90370e659cac799c9b3e563960014\",\n \"content_id\": \"068d1384ca4d42c661fe6f242bc53a96b0e1be1e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2060,\n \"license_type\": \"no_license\",\n \"max_line_length\": 100,\n \"num_lines\": 83,\n \"path\": \"/4/1.py\",\n \"repo_name\": \"pkmollman/advent_2020\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\nimport re\\n\\npassports_text = ''\\n\\nwith open('input.txt', 'r') as f:\\n for line in f.readlines():\\n passports_text += line\\n\\ndef byr(value):\\n if len(value) == 4 and int(value) >= 1920 and int(value) <= 2002:\\n return True\\n return False\\ndef iyr(value):\\n if len(value) == 4 and int(value) >= 2010 and int(value) <= 2020:\\n return True\\n return False\\ndef eyr(value):\\n if len(value) == 4 and int(value) >= 2020 and int(value) <= 2030:\\n return True\\n return False\\ndef hgt(value):\\n if 'cm' in value[-2:] and 150 <= int(value[:-2]) <= 193:\\n return True\\n if 'in' in value[-2:] and 59 <= int(value[:-2]) <= 76:\\n return True\\n return False\\ndef hcl(value):\\n return re.match('^#[0-9a-f]{6}$',value)\\ndef ecl(value):\\n return value in ['amb','blu','brn','gry','grn','hzl','oth']\\ndef pid(value):\\n # this is trash, shoot me\\n return re.match('^[0-9]{9}$',value)\\n\\nrequired_values = {\\n 'byr': byr,\\n 'iyr': iyr,\\n 'eyr': eyr,\\n 'hgt': hgt,\\n 'hcl': hcl,\\n 'ecl': ecl,\\n 'pid': pid,\\n}\\n\\nunsep_passports = passports_text.split('\\\\n')\\npassports = []\\npassport_group = []\\n\\nfor line in unsep_passports:\\n if line == '':\\n passports.append(passport_group)\\n passport_group = []\\n elif line == unsep_passports[-1]:\\n passport_group.append(line)\\n passports.append(passport_group)\\n else:\\n passport_group.append(line)\\n\\nclean_passports = []\\n\\nfor passport in passports:\\n clean_passport = {}\\n for line in passport:\\n for key_value in line.split(' '):\\n k,v = key_value.split(':')\\n clean_passport[k] = v\\n clean_passports.append(clean_passport)\\n\\nvalid_passports = 0\\n\\nfor passport in clean_passports:\\n valid_passport = True\\n for required_value in required_values:\\n if required_value in passport and required_values[required_value](passport[required_value]):\\n pass\\n else:\\n valid_passport = False\\n if valid_passport:\\n valid_passports += 1\\n\\nprint(valid_passports)\"\n },\n {\n \"alpha_fraction\": 0.6149377822875977,\n \"alphanum_fraction\": 0.6390041708946228,\n \"avg_line_length\": 26.409090042114258,\n \"blob_id\": \"ecfcf4f64340f14bca17023d10e463e75050f4cc\",\n \"content_id\": \"95e34e1a84a5504392cd05952b3142a9e98c5769\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1205,\n \"license_type\": \"no_license\",\n \"max_line_length\": 108,\n \"num_lines\": 44,\n \"path\": \"/8/3.py\",\n \"repo_name\": \"pkmollman/advent_2020\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\nadapters = []\\n\\nwith open('input.txt', 'r') as f:\\n adapters = [int(line.strip()) for line in f.readlines()]\\n\\n\\nadapters.append(0)\\nadapters.sort()\\nadapters.append(adapters[-1]+3)\\n\\ncount_one_gap = 1\\ncount_three_gap = 1\\n\\nglobal g_counter\\n# g_counter = 0\\n\\nmain_list = []\\n\\ndef options(i, slices):\\n return [ num for num in slices if (num - i) <= 3 ]\\n\\ndef options_r(i, adapters, adapter, sliced):\\n global g_counter\\n for nummy,option in enumerate([ num for num in sliced if (num - adapter) <= 3 ]):\\n if option == adapters[-1]:\\n g_counter += 1\\n option_index = i + nummy + 1\\n options_r(option_index,adapters,option,adapters[option_index+1:option_index+4])\\n\\ndef options_r2(i, adapters, adapter, sliced, g_counter):\\n thingy = g_counter\\n for nummy,option in enumerate([ num for num in sliced if (num - adapter) <= 3 ]):\\n if option == adapters[-1]:\\n thingy += 1\\n option_index = i + nummy + 1\\n thingy += options_r2(option_index,adapters,option,adapters[option_index+1:option_index+4],g_counter)\\n return thingy\\n\\noption_multiplier = 1\\n\\ng_counter = options_r2(0,adapters,adapters[0],adapters[1:4],0)\\nprint(g_counter)\"\n },\n {\n \"alpha_fraction\": 0.638436496257782,\n \"alphanum_fraction\": 0.6416938304901123,\n \"avg_line_length\": 26.909090042114258,\n \"blob_id\": \"96cef93af14cd3ea6bd0972ffd91e3c926d059d8\",\n \"content_id\": \"751a523388b5d6feaea9c2d2a8683c516c8df5f3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1228,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 44,\n \"path\": \"/6/2.py\",\n \"repo_name\": \"pkmollman/advent_2020\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\ninput_text = ''\\n\\nwith open('input.txt', 'r') as f:\\n input_text = f.read().split('\\\\n')\\n\\ntext_groups = []\\ntext_group = []\\n\\n# for single line of answers append to a list,\\n# once a blank line is reached, append list to the main list,\\n# and reset current working list to empty\\nfor line in input_text:\\n if line == '':\\n text_groups.append(text_group)\\n text_group = []\\n continue\\n text_group.append(line)\\n\\ngroup_answer_total = 0\\n\\n# for list of answer strings in text_groups\\nfor group in text_groups:\\n # track group's unique answers\\n letters = []\\n for answers in group:\\n for letter in answers:\\n if letter in letters:\\n continue\\n letters.append(letter)\\n # track all group's answer strings in a single string\\n all_answers = ''\\n for answers in group:\\n all_answers += answers\\n # track group's valid answers\\n group_total = 0\\n # if unique letter count in combined answer string\\n # equals number of group members the answer is counted in group_total\\n for letter in letters:\\n if all_answers.count(letter) == len(group): group_total += 1\\n group_answer_total += group_total\\n\\nprint(group_answer_total)\\n\"\n },\n {\n \"alpha_fraction\": 0.5767441987991333,\n \"alphanum_fraction\": 0.6000000238418579,\n \"avg_line_length\": 19.5238094329834,\n \"blob_id\": \"fc89b44565edaedd570dcfceb8feb2237c18dd4d\",\n \"content_id\": \"574c5c19b3492f7e1a90804cd8a550331bcafe66\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 430,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 21,\n \"path\": \"/8/1.py\",\n \"repo_name\": \"pkmollman/advent_2020\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\nadapters = []\\n\\nwith open('input.txt', 'r') as f:\\n adapters = [int(line.strip()) for line in f.readlines()]\\n\\nadapters.sort()\\n\\ncount_one_gap = 1\\ncount_three_gap = 1\\n\\nfor i,adapter in enumerate(adapters):\\n if i == 0:\\n pass\\n elif adapter - adapters[i-1] == 1:\\n count_one_gap += 1\\n elif adapter - adapters[i-1] == 3:\\n count_three_gap += 1\\n\\nprint(count_one_gap * count_three_gap)\"\n },\n {\n \"alpha_fraction\": 0.5768194198608398,\n \"alphanum_fraction\": 0.584007203578949,\n \"avg_line_length\": 26.170732498168945,\n \"blob_id\": \"4960e71d5b7e4ddccc1cc0b1a0efeaca40894c3d\",\n \"content_id\": \"a676844c6de9a5134b9614c4cb4fe0061294d02c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1113,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 41,\n \"path\": \"/7/1.py\",\n \"repo_name\": \"pkmollman/advent_2020\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\nimport re\\n\\n# REGEX = r'([\\\\w\\\\s]+)bags contain((\\\\s\\\\d+)\\\\s([\\\\w\\\\s]+)bags?[\\\\.,])+'\\nmain_bag_reg = r'([\\\\w\\\\s]+)bags contain'\\ninner_bag_reg = r'((\\\\s\\\\d+)\\\\s([\\\\w\\\\s]+) bags?)+'\\ninput_text = ''\\n\\nwith open('input.txt', 'r') as f:\\n input_text = [line for line in f.readlines()]\\n\\nbag_types = {}\\n\\nfor line in input_text:\\n main_result = re.match(main_bag_reg, line)\\n inner_result = re.findall(inner_bag_reg, line)\\n bag_types[main_result.group(1).strip()] = {}\\n for result in inner_result:\\n bag_types[main_result.group(1).strip()][result[2].strip()] = result[1]\\n\\ncontains_shiny_golds = []\\n\\nfor bag in bag_types:\\n # print(bag_types[bag])\\n if 'shiny gold' in bag_types[bag]:\\n contains_shiny_golds.append(bag)\\n\\n\\nwhile True:\\n inner_num = 0\\n for bag_type in bag_types:\\n for bag in contains_shiny_golds:\\n if bag in bag_types[bag_type]:\\n if not bag_type in contains_shiny_golds:\\n contains_shiny_golds.append(bag_type)\\n inner_num += 1\\n if inner_num == 0:\\n break\\n\\nprint(len(contains_shiny_golds))\"\n },\n {\n \"alpha_fraction\": 0.6105263233184814,\n \"alphanum_fraction\": 0.6168420910835266,\n \"avg_line_length\": 24,\n \"blob_id\": \"0e0fbd6f149fb7c4139c21d2163da07b484a91b6\",\n \"content_id\": \"f595d3433cd76ff9f2edc8849286c9d342458140\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 950,\n \"license_type\": \"no_license\",\n \"max_line_length\": 83,\n \"num_lines\": 38,\n \"path\": \"/7/2.py\",\n \"repo_name\": \"pkmollman/advent_2020\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\nimport re\\n\\nmain_bag_reg = r'([\\\\w\\\\s]+)bags contain'\\ninner_bag_reg = r'((\\\\s\\\\d+)\\\\s([\\\\w\\\\s]+) bags?)+'\\ninput_text = ''\\n\\nwith open('input.txt', 'r') as f:\\n input_text = [line for line in f.readlines()]\\n\\nbag_types = {}\\n\\nfor line in input_text:\\n main_result = re.match(main_bag_reg, line)\\n inner_result = re.findall(inner_bag_reg, line)\\n bag_types[main_result.group(1).strip()] = {}\\n for result in inner_result:\\n bag_types[main_result.group(1).strip()][result[2].strip()] = int(result[1])\\n\\nshiny_golds = list(bag_types['shiny gold'].keys())\\n\\nnumber_o_bags = 0\\n\\ndef num_bag(bag_type, number):\\n numbag = number\\n if bag_types[bag_type]:\\n for bag in bag_types[bag_type]:\\n numbag += num_bag(bag, bag_types[bag_type][bag]) * number\\n else:\\n return number\\n return numbag\\n\\n\\nfor bag in shiny_golds:\\n number_o_bags += num_bag(bag, bag_types['shiny gold'][bag])\\n\\nprint(number_o_bags)\\n\"\n },\n {\n \"alpha_fraction\": 0.5201109647750854,\n \"alphanum_fraction\": 0.545076310634613,\n \"avg_line_length\": 19.05555534362793,\n \"blob_id\": \"aab43044098768b922e01a1c772fe504196f1437\",\n \"content_id\": \"b883688bd458b788d7b487a1e66a6b83c04213b3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 721,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 36,\n \"path\": \"/3/1.py\",\n \"repo_name\": \"pkmollman/advent_2020\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\nmatrix = []\\nlocation = [0,0]\\ntrees = 0\\nbig_number = 0\\nslopes = [\\n [3,1],\\n]\\n\\nwith open('input.txt', 'r') as f:\\n for line in f.readlines():\\n matrix.append(line.strip())\\n\\ndef tree_or_nah(matrix,x,y):\\n r_x = (x % len(matrix[0]))\\n print(r_x, y)\\n print(matrix[y])\\n if matrix[y][r_x] == '#':\\n return True\\n return False\\n\\nfor slope in slopes:\\n while location[1] < len(matrix)-1:\\n location[0] += slope[0]\\n location[1] += slope[1]\\n print(location)\\n if tree_or_nah(matrix,location[0],location[1]):\\n trees += 1\\n if big_number == 0:\\n big_number = trees\\n else:\\n big_number *= trees\\n\\nprint(trees)\\nprint(big_number)\"\n },\n {\n \"alpha_fraction\": 0.5184404850006104,\n \"alphanum_fraction\": 0.5447840094566345,\n \"avg_line_length\": 22.75,\n \"blob_id\": \"9a2c1d67a94ac879979e75194548dcde83db6b9b\",\n \"content_id\": \"09beea555fccf92004aa9cf5d7c9e209f39ab706\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 949,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 40,\n \"path\": \"/5/1.py\",\n \"repo_name\": \"pkmollman/advent_2020\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\ndef seat_id(seat):\\n\\n row_max = 128\\n row_min = 0\\n row_nums = list(range(row_min,row_max))\\n\\n for char in seat[:7]:\\n if char == 'F':\\n row_nums = row_nums[:int((len(row_nums)-1)/2)+1]\\n if char == 'B':\\n row_nums = row_nums[int((len(row_nums)-1)/2)+1:]\\n print(row_nums)\\n\\n column_max = 8\\n column_min = 0\\n column_nums = list(range(column_min,column_max))\\n\\n for char in seat[-3:]:\\n if char == 'L':\\n column_nums = column_nums[:int((len(column_nums)-1)/2)+1]\\n if char == 'R':\\n column_nums = column_nums[int((len(column_nums)-1)/2)+1:]\\n print(column_nums)\\n return row_nums[0] * 8 + column_nums[0]\\n\\n\\nprint(seat_id('BBFFBBFRLL'))\\n\\nseat_ids = []\\n\\nwith open('input.txt', 'r') as f:\\n for line in f.readlines():\\n seat_ids.append(seat_id(line.strip()))\\n print(line)\\n\\nseat_ids.sort()\\nprint(seat_ids)\\nprint(seat_ids[-1])\"\n },\n {\n \"alpha_fraction\": 0.6631355881690979,\n \"alphanum_fraction\": 0.6652542352676392,\n \"avg_line_length\": 24.513513565063477,\n \"blob_id\": \"d4241fb400559a1299262c675071b5db862fe4c7\",\n \"content_id\": \"89503c3597d547e3d935891f3980a1bfe5e2fe07\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 944,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 37,\n \"path\": \"/6/1.py\",\n \"repo_name\": \"pkmollman/advent_2020\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\ninput_text = ''\\n\\nwith open('input.txt', 'r') as f:\\n input_text = f.read().split('\\\\n')\\n\\n# track each group of answers as a single string\\ntext_groups = []\\n\\n# track current group for below iteration \\ntext_group = ''\\n\\n# for single line of answers append to a single string,\\n# once a blank line is reached, append to the main list,\\n# and reset current working string to empty\\nfor line in input_text:\\n if line == '':\\n text_groups.append(text_group)\\n text_group = ''\\n continue\\n text_group += line\\n\\n# total sum of unique answers per group\\ngroup_answer_total = 0\\n\\n# for char in group answer string, if char not in letters list, append it\\n# len(letters) is group total unique answers\\nfor group in text_groups:\\n letters = []\\n for letter in group:\\n if letter in letters:\\n continue\\n letters.append(letter)\\n group_answer_total += len(letters)\\n\\nprint(group_answer_total)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":14,"string":"14"}}},{"rowIdx":2977691,"cells":{"repo_name":{"kind":"string","value":"dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases"},"repo_url":{"kind":"string","value":"https://github.com/dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases"},"snapshot_id":{"kind":"string","value":"29d117ccb75b14ce73f626356062a163f0ad6546"},"revision_id":{"kind":"string","value":"72b6cb822a679705d28066e63e8d70f07a36ff29"},"directory_id":{"kind":"string","value":"3d22bb86be195e286f7337577a206c79f1332557"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-05-30T17:02:27.971317","string":"2020-05-30T17:02:27.971317"},"revision_date":{"kind":"timestamp","value":"2019-06-07T17:55:42","string":"2019-06-07T17:55:42"},"committer_date":{"kind":"timestamp","value":"2019-06-07T17:55:42","string":"2019-06-07T17:55:42"},"github_id":{"kind":"number","value":189862563,"string":"189,862,563"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"timestamp","value":"2019-06-02T15:21:50","string":"2019-06-02T15:21:50"},"gha_updated_at":{"kind":"timestamp","value":"2019-03-25T17:58:26","string":"2019-03-25T17:58:26"},"gha_pushed_at":{"kind":"timestamp","value":"2019-06-01T03:05:54","string":"2019-06-01T03:05:54"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6952314972877502,"alphanum_fraction":0.7069799304008484,"avg_line_length":67.92857360839844,"blob_id":"e65bfa78e5c3ed26b55bc265974adbd7473769bd","content_id":"1d890dbe82bb186f4bbfaf9b766db045f8ee269e","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2894,"license_type":"permissive","max_line_length":312,"num_lines":42,"path":"/sprint2/northwind.py","repo_name":"dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases","src_encoding":"UTF-8","text":"import sqlite3\n\n# Connect to northwind_small database\nconn = sqlite3.connect('northwind_small.sqlite3')\n\n# Read through its database to query later on\ncurs = conn.cursor()\n\n# Save db in result_product\nresult_10 = curs.execute('SELECT ProductName, UnitPrice FROM Product ORDER BY UnitPrice DESC LIMIT 10;').fetchall()\nprint('Top 10 expensive items:', result_10)\nprint('###################################')\n\nresult_avg_age = curs.execute('SELECT ROUND(AVG(HireDate - BirthDate), 2) FROM Employee').fetchall()\nprint('Avg age of employees at hiring date:', result_avg_age[0][0])\nprint('###################################')\n\nresult_city = curs.execute('SELECT City, HireDate, AVG(HireDate - BirthDate) FROM Employee GROUP BY City;').fetchall()\nprint('Avg age of employees at hiring date by city:', result_city)\nprint('###################################')\n\n################## PART 3 ########################\n\n# Note to self - when there's a primary key use Join on supplierid DO NOT use p.supplierid = s.supplierid\nresult_10_supplier = curs.execute('SELECT p.ProductName, s.CompanyName, p.UnitPrice FROM Supplier AS s INNER JOIN Product AS p ON SupplierID ORDER BY UnitPrice DESC LIMIT 10;').fetchall()\nprint('Top 10 expensive product and their supplier', result_10_supplier)\nprint('###################################')\n\nresult_large_category = curs.execute('SELECT CategoryID, COUNT(p.ProductName) FROM Category AS c INNER JOIN Product as p ON CategoryID GROUP BY CategoryID ORDER BY COUNT(p.ProductName) DESC LIMIT 1;').fetchall()\nprint('Largest category,', result_large_category[0][0], ', with number of unique products:', result_large_category[0][1])\nprint('###################################')\n\nresult_territory = curs.execute('SELECT EmployeeID, COUNT(TerritoryDescription) FROM EmployeeTerritory INNER JOIN Territory ON TerritoryID GROUP BY EmployeeID ORDER BY COUNT(TerritoryDescription) DESC LIMIT 1;').fetchall()\n\nprint('EmployeeID:,', result_territory[0][0], ', with the most territory:', result_territory[0][1])\n########### PART 4 ############\n\n# The type of relationship between employee and territory tables is none. However once you join the table employee territory to either emplyoee or territory then you will get a one to one relationship. You can join a second time on the primary key, EmployeeID.\n\n# Mongo DB is an object based documentation that handles and stores big data. It creates a dictionary where you're given a unique key and its value is a json dictionary(strings are keys and anything type for values) It is not good for querying data compared to sqlite or other querying languages like postgresql.\n\n# NewSQL tries to blend traditional query language to NOSQL languages. Traditional languages follow the ACID principles and NOSQL is lenient on the A,I, and D principle(the C, consistent, is kept). Basically, try to use traditional query langauages on big data."},{"alpha_fraction":0.6915380358695984,"alphanum_fraction":0.697255551815033,"avg_line_length":31.70093536376953,"blob_id":"9c563c3afce6780d82752778b8c00624f77004e0","content_id":"4a3666d1a54f4c72ba47d30476df6ea401d59bbb","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3498,"license_type":"permissive","max_line_length":85,"num_lines":107,"path":"/module2-sql-for-analysis/lecture.py","repo_name":"dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases","src_encoding":"UTF-8","text":"# Local install. Go to the desired dir and local install\n## pipenv install psycopg2-binary\n\n# Activate\n## pipenv shell\n\nimport psycopg2\n\n\n# From help(psycopg2.connect) - Enter the bottom 4.\ndbname = 'ximkxdxb'\nuser = 'ximkxdxb'\npassword = '' # Don't commit this. delete when you commit/push\nhost = 'raja.db.elephantsql.com'\n\n# Connect to Elephant Database\npg_conn = psycopg2.connect(dbname=dbname, user=user, password=password, host=host)\n\n# Set-up a cursor to read the elephant database\npg_curs = pg_conn.cursor()\n\n# Query and fetchall info in elephant database\npg_curs.execute('SELECT * FROM test_table;')\nprint(pg_curs.fetchall())\n\n# ETL - Extract, Transform, Load Pipeline\nimport sqlite3\n\n# Use sqlite3 and retrieve the RPG database\nsl_conn = sqlite3.connect('../module1-introduction-to-sql/rpg_db.sqlite3')\nprint(sl_conn) # Test to see imported library is retrieved\n\n# Setup a sqlite3 cursor to read the database\nsl_curs = sl_conn.cursor()\n\n# Query and fetchall() from rpg database\nprint(sl_curs.execute('SELECT COUNT(*) FROM charactercreator_character;').fetchall())\n\n# From the rpg database, get all the columns from the table (charcre_char)\n# Extract from sqlite3 rpg database\ncharacters = sl_curs.execute('SELECT * FROM charactercreator_character;').fetchall()\nprint(len(characters)) # Same as COUNT()\n\n# Look at the first characters and last characters\nprint('First line:', characters[0], 'Last line:', characters[-1])\n\n# CREATE TABLE to load to PostgreSQL - This will be our character schema\n# Pre- Load\n# Sets up table to be loaded to postgreSQL database\ncreate_character_table = '''\n CREATE TABLE charactercreator_character (\n character_id SERIAL PRIMARY KEY,\n name VARCHAR(30),\n level INT,\n exp INT,\n hp INT,\n strength INT,\n intelligence INT,\n dexterity INT,\n wisdom INT\n );\n'''\n############################################################\n# Read through the table we created above\n#print(pg_curs.execute(create_character_table))\n\n# Define INSERT INTO \nattempted_insert = '''\n INSERT INTO charactercreator_character\n VALUES ''' + str(characters[0])\nprint(attempted_insert)\n\n# INSERT INTO created table\n#print(pg_curs.execute(attempted_insert))\n\n# Changing Databases - CREATE or INSERT a table. You have to commit to make it work\npg_conn.commit() \n###############################################################\n# Can't create duplicate so comment out the above ####### to #########\n\n# After commit - Query the newly created and insert info\npg_curs.execute('SELECT * FROM charactercreator_character;')\npg_characters = pg_curs.fetchall()\nprint(pg_curs.fetchall())\n\n# Only INSERT INTO 1 row\nprint('Row:',pg_characters[0], 'Row Length:', len(pg_characters))\n\n# INSERT INTO the rest of the rows to postgresql database\n# for character in characters[1:]:\n# insert_character = '''\n# INSERT INTO charactercreator_character\n# VALUES ''' + str(character)\n# pg_curs.execute(insert_character)\npg_conn.commit() # Can't duplicate so comment out the for loop\n\n# Restart the cursor\npg_curs = pg_conn.cursor()\n# Query the finished table from loaded to postgresql database\npg_curs.execute('SELECT * FROM charactercreator_character')\n# Fetch all table\npg_characters = pg_curs.fetchall()\nprint('Row:', pg_characters, 'Row Length:', len(pg_characters))\n\n# Test our RPG database to our PostgreSQL database - No Error\nfor character, pg_character in zip(characters, pg_characters):\n assert character == pg_character"},{"alpha_fraction":0.7256371974945068,"alphanum_fraction":0.7466266751289368,"avg_line_length":32.400001525878906,"blob_id":"b888f040374b3a2345d2325107e77130baccc761","content_id":"9af415d603e274053b873c4255960ca1f23df2b0","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":667,"license_type":"permissive","max_line_length":194,"num_lines":20,"path":"/module1-introduction-to-sql/query_part2.py","repo_name":"dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases","src_encoding":"UTF-8","text":"import pandas as pd\nimport sqlite3\nfrom sqlalchemy import create_engine\n\n# Engine use for sql query\nengine = create_engine('sqlite://', echo=False)\n\n# DataFrame\ndf = pd.read_csv('buddymove_holidayiq.csv')\n\n# Create a new Database\nconn = sqlite3.connect('buddymove_holiday.sqlite3')\n\n# Use df as sql\ndf.to_sql('buddymove_holiday', con=engine)\n\n# Use the engine to execute query\nprint('The count is:', engine.execute('SELECT COUNT(*) FROM buddymove_holiday').fetchone()[0])\n\nprint('The number of users who reviewed at least 100 Nature and Shopping category:', engine.execute('SELECT COUNT(*) FROM buddymove_holiday WHERE Nature>=100 AND Shopping >= 100').fetchone()[0])"},{"alpha_fraction":0.6687822341918945,"alphanum_fraction":0.6751289367675781,"avg_line_length":23.25,"blob_id":"76deeef3c883d1255db0c97de36a627edf17346d","content_id":"89ea5d30114b53b5ea21b05173c258e4c276467b","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2521,"license_type":"permissive","max_line_length":82,"num_lines":104,"path":"/module2-sql-for-analysis/insert_titanic.py","repo_name":"dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases","src_encoding":"UTF-8","text":"import psycopg2\n\n# Re Enter\ndbname = 'eczastgf'\nuser = 'eczastgf'\npassword = ''\nhost = 'raja.db.elephantsql.com'\n\n# Connect to ElephantSQL\npg_conn = psycopg2.connect(dbname=dbname, user=user, password=password, host=host)\n\n# Read the ElephantSQL database\npg_curs = pg_conn.cursor()\n\n# Df to titanic database\nimport pandas as pd\nfrom sqlalchemy import create_engine\n\n# Save df\ndf = pd.read_csv('titanic.csv')\n\n# Replace ' with an empty space\ndf['Name'] = df['Name'].str.replace('\\'', ' ')\n\n# Create engine - Used to convert a dataframe to database\nengine = create_engine('sqlite://', echo=False)\n\n# Create the new table on sql db\ndf.to_sql('titanic', con=engine)\n\n# Titanic df is now a db - Is a list of tuples\ntitanic_db = engine.execute('SELECT * FROM titanic;').fetchall()\n\n# Create an empty db for ElephantSQL\ncreate_titanic_table = '''\n CREATE TABLE titanic (\n id integer NOT NULL PRIMARY KEY,\n survived INT,\n pclass INT,\n name VARCHAR(100),\n sex VARCHAR(10),\n age INT,\n siblings_spouses_aboard INT,\n parents_child_aboard INT,\n fare INT\n );\n'''\n\n# Read thourgh the table we created\npg_curs.execute(create_titanic_table)\n\n# INSERT INTO the rest of the rows to postgresql database\nfor row in titanic_db:\n insert_row = '''\n INSERT INTO titanic\n VALUES ''' + str(row)\n pg_curs.execute(insert_row)\n\n# Commit to Elephantsql and test from browser: SELECT * FROM titanic\npg_conn.commit()\n\n# Create a local titanic db then upload to elephant db\n\"\"\"\nimport sqlite3\n\n# Reset index to get an index,id\ndf = df.reset_index().rename(columns={'index':'id'})\n\n# Save a create a titanic database\nsl_conn = sqlite3.connect('titanic.sqlite3')\n\n# CREATE TYPE for titanic sex\n# CREATE TABLE for titanic database\ncreate_titanic_table = '''\n CREATE TABLE titanic (\n id integer NOT NULL PRIMARY KEY AUTOINCREMENT,\n survived INT,\n pclass INT,\n name VARCHAR(100),\n sex VARCHAR(10),\n age INT,\n siblings_spouses_aboard INT,\n parents_child_aboard INT,\n fare INT\n );\n'''\n\n# Read the database\nsl_curs = sl_conn.cursor()\n\n# Create the table for the titanic database\n#sl_curs.execute(create_titanic_table)\n## Comment out since already created\n\n# Define INSERT INTO\ninsert_titanic_db = '''\n INSERT INTO titanic\n VALUES ''' + str(tuple(df.loc[0, :].tolist()))\n\nsl_curs.execute(insert_titanic_db)\n\n# Fetch all data in titanic database\nprint(sl_curs.execute('SELECT * FROM titanic;').fetchall())\n\"\"\""},{"alpha_fraction":0.6910856366157532,"alphanum_fraction":0.7007943391799927,"avg_line_length":25.057470321655273,"blob_id":"c64d7fffdf5c223f6b7ba61d9e59ee4d32d1fbe6","content_id":"453d8717e4f6a9efeda041cc92da3be52117847e","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2266,"license_type":"permissive","max_line_length":84,"num_lines":87,"path":"/sprint_practice/sprint_practice.py","repo_name":"dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases","src_encoding":"UTF-8","text":"# From the cmd prompt set-up a virtual enviornment \n# `pipenv install ...` is the dir\n\n# Run `pipenv shell` to activate\n\nimport sqlite3\n\n# Connect to a database and if there's is none it will create one\nconn = sqlite3.connect('rpg_db.sqlite3')\n\n# Used to make queries\ncurs = conn.cursor()\n\n# Execute query and fetch all the data\nresult = curs.execute('SELECT * FROM armory_item;')\nresult.fetchall()\n# print(result.fetchall())\n\n############### Create a new table ###############\n\n# 'toy_db_sqlite3' doesn't exist so it will create one\nconn = sqlite3.connect('toy_db_sqlite3')\n\n# Create a table called toy\ncreate_toy_table = '''CREATE TABLE toy (\n toy_id integer NOT NULL PRIMARY KEY AUTOINCREMENT,\n toy_name VARCHAR(30),\n price NUMERIC,\n small_parts integer\n)\n'''\n\n# Create a cursor to make queries\ncurs = conn.cursor()\n\n# Execute `create_toy_table` to create the table\n## Is empty right now since we didn't populate it\n#curs.execute(create_toy_table)\n## Comment out above line since we can't create duplicates\n# print(curs.execute(create_toy_table).fetchall())\n\n# INSERT INTO toy VALUES to create new values of fields/col\n\ninsert = \"INSERT INTO toy VALUES (1, 'Legos', 10.5, 1), (2, 'Train', 17.6, 0);\"\n\n# Execute to insert new values to toy table\ncurs.execute(insert)\n\n# Fetch all from toy database - toy_db is a list\ntoy_db = curs.execute('SELECT * FROM toy;').fetchall()\n\n######### Try to launch it to elephantsql #####\n\nimport psycopg2\n\n# Enter/Re enter details from elephantsql\n\ndbname = 'oxwfzsio'\nuser = 'oxwfzsio'\npassword = ''\nhost = 'raja.db.elephantsql.com'\n\n# connect to elephantsql\npg_conn = psycopg2.connect(dbname=dbname, user=user, password=password, host=host)\n\n# Used to read the database on elephantsql\npg_curs = pg_conn.cursor()\n\n# Create an empty table for ElephantSQL\ncreate_toy_table_esql = '''CREATE TABLE toy (\n toy_id integer NOT NULL PRIMARY KEY,\n toy_name VARCHAR(30),\n price NUMERIC,\n small_parts integer\n)\n'''\n# Execute to create an empty table for ESQL\npg_curs.execute(create_toy_table_esql)\n\n# # Execute previous created toy database\nfor row in toy_db:\n insert_row = '''\n INSERT INTO toy VALUES ''' + str(row)\n pg_curs.execute(insert_row)\n\n# Commit to see the changes on elephantsql\npg_conn.commit()"},{"alpha_fraction":0.5940678119659424,"alphanum_fraction":0.6101694703102112,"avg_line_length":28.524999618530273,"blob_id":"3e72a53cd7649f40f0078800f2ff6ad8cd560b83","content_id":"f85a24fb589934eb83b54307513a6172640e6eb3","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1180,"license_type":"permissive","max_line_length":93,"num_lines":40,"path":"/sprint2/demo_data.py","repo_name":"dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases","src_encoding":"UTF-8","text":"import sqlite3\n\n# Connect to a database\nconn = sqlite3.connect('demo_data.sqlite3')\n\n# Make a cursor to read the database\ncurs = conn.cursor()\n\n# Create a table\ncreate_demo_data = '''\nCREATE TABLE demo (\n s CHAR(1),\n x INT,\n y INT\n)\n'''\n\n# Execute to create demo data\ncurs.execute(create_demo_data)\n\n# INSERT INTO demo VALUES to create new values of columns\ninsert = \"INSERT INTO demo VALUES ('g', 3, 9), ('v', 5, 7),('f', 8, 7);\"\n\n# Execute to insert into demo table\ncurs.execute(insert)\n\n# Query - Count how many rows\nresult_count = curs.execute('SELECT COUNT(*) FROM demo;').fetchone()\nprint('There are:', result_count[0], 'rows')\nprint('###################################')\n\n# Query - How many rows where both x and y are >= 5\nresult_count_5 = curs.execute('SELECT COUNT(*) FROM demo WHERE x >=5 AND y >= 5;').fetchone()\nprint('There are:', result_count_5[0], 'rows of x and y >= 5')\nprint('###################################')\n\n# Query - How many unique values of y are there?\nresult_unique_y = curs.execute('SELECT COUNT(DISTINCT y) FROM demo;').fetchone()\nprint('There are:', result_unique_y[0], 'unique values of y')\nprint('###################################')"},{"alpha_fraction":0.6904506683349609,"alphanum_fraction":0.707617998123169,"avg_line_length":19.955055236816406,"blob_id":"33bbe1309e1a11cd2bab107a330678bca4b75216","content_id":"03fcf221e9551222254134959bd6592c6797cd5c","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1864,"license_type":"permissive","max_line_length":79,"num_lines":89,"path":"/module1-introduction-to-sql/lecture.py","repo_name":"dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases","src_encoding":"UTF-8","text":"import sqlite3\n\n# Database\nconn = sqlite3.connect('rpg_db.sqlite3')\n\nconn\n# Goes through the database - can have multiple\ncurs = conn.cursor()\n\ncurs\n\n# Make a query\nquery = 'SELECT COUNT(*) FROM armory_item;'\n\n# Save results of query\nresult = curs.execute(query)\nresult\n\n# Fetch all results from the query\nresult.fetchall()\n\n\n# SELECT * selects all\nquery = 'SELECT * FROM armory_item;'\nresult = curs.execute(query)\nresult.fetchall()\n\n# Fetch one result from the query\nresult = curs.execute(query)\n# Once fetched then it'll won't be in there.\nresult.fetchone()\n\n############## DB Browser for SQLite ###########\n'''\n# Select all columns from the armory_item table\nSELECT * FROM armory_item\n\n# Select the table where item_id is 167, 45, 27\nWHERE item_id IN(167, 45, 27);\n\n\n'''\n\n############## Create a new table ###############\n\nimport sqlite3\nconn = sqlite3.connect('toy_db_sqlite3')\n\n# Create a table, toy_id, \ncreate_statement = '''CREATE TALBE toy (\n toy_id integer NOT NULL PRIMARY KEY AUTOINCREMENT,\n toy_name varchar(30),\n price numeric,\n small_parts integer)'''\n\n# \ncurs = conn.cursor()\n\n# Create table\ncurs.execute(create_statement)\n\n# Create new values for the table\ninsert = \"INSERT INTO toy VALUES (1, 'Legos', 10.5, 1), (2, 'Train', 17.6, 0);\"\n# Exevute query\ncurs.execute(insert)\n\n\n# Explicit Inner Join#\n'''\nSELECT \nname, mana\nFROM charactercreator_mage\nINNER JOIN charactercreator_character\nON charactercreator_mage.character_ptr_id = \ncharactercreator_character.character_id;\n'''\n# Implicit Inner Join #\n'''\nSELECT name, mana\nFROM charactercreator_mage, charactercreator_character\nWHERE charactercreator_character.character_id =\ncharactercreator_mage.character_ptr_id;\n'''\n# Alias by using AS #\n'''\nSELECT cc.name, cm.mana\nFROM charactercreator_mage AS cm, charactercreator_character AS cc\nWHERE cc.character_id = cm.character_ptr_id;\n'''"}],"string":"[\n {\n \"alpha_fraction\": 0.6952314972877502,\n \"alphanum_fraction\": 0.7069799304008484,\n \"avg_line_length\": 67.92857360839844,\n \"blob_id\": \"e65bfa78e5c3ed26b55bc265974adbd7473769bd\",\n \"content_id\": \"1d890dbe82bb186f4bbfaf9b766db045f8ee269e\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2894,\n \"license_type\": \"permissive\",\n \"max_line_length\": 312,\n \"num_lines\": 42,\n \"path\": \"/sprint2/northwind.py\",\n \"repo_name\": \"dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sqlite3\\n\\n# Connect to northwind_small database\\nconn = sqlite3.connect('northwind_small.sqlite3')\\n\\n# Read through its database to query later on\\ncurs = conn.cursor()\\n\\n# Save db in result_product\\nresult_10 = curs.execute('SELECT ProductName, UnitPrice FROM Product ORDER BY UnitPrice DESC LIMIT 10;').fetchall()\\nprint('Top 10 expensive items:', result_10)\\nprint('###################################')\\n\\nresult_avg_age = curs.execute('SELECT ROUND(AVG(HireDate - BirthDate), 2) FROM Employee').fetchall()\\nprint('Avg age of employees at hiring date:', result_avg_age[0][0])\\nprint('###################################')\\n\\nresult_city = curs.execute('SELECT City, HireDate, AVG(HireDate - BirthDate) FROM Employee GROUP BY City;').fetchall()\\nprint('Avg age of employees at hiring date by city:', result_city)\\nprint('###################################')\\n\\n################## PART 3 ########################\\n\\n# Note to self - when there's a primary key use Join on supplierid DO NOT use p.supplierid = s.supplierid\\nresult_10_supplier = curs.execute('SELECT p.ProductName, s.CompanyName, p.UnitPrice FROM Supplier AS s INNER JOIN Product AS p ON SupplierID ORDER BY UnitPrice DESC LIMIT 10;').fetchall()\\nprint('Top 10 expensive product and their supplier', result_10_supplier)\\nprint('###################################')\\n\\nresult_large_category = curs.execute('SELECT CategoryID, COUNT(p.ProductName) FROM Category AS c INNER JOIN Product as p ON CategoryID GROUP BY CategoryID ORDER BY COUNT(p.ProductName) DESC LIMIT 1;').fetchall()\\nprint('Largest category,', result_large_category[0][0], ', with number of unique products:', result_large_category[0][1])\\nprint('###################################')\\n\\nresult_territory = curs.execute('SELECT EmployeeID, COUNT(TerritoryDescription) FROM EmployeeTerritory INNER JOIN Territory ON TerritoryID GROUP BY EmployeeID ORDER BY COUNT(TerritoryDescription) DESC LIMIT 1;').fetchall()\\n\\nprint('EmployeeID:,', result_territory[0][0], ', with the most territory:', result_territory[0][1])\\n########### PART 4 ############\\n\\n# The type of relationship between employee and territory tables is none. However once you join the table employee territory to either emplyoee or territory then you will get a one to one relationship. You can join a second time on the primary key, EmployeeID.\\n\\n# Mongo DB is an object based documentation that handles and stores big data. It creates a dictionary where you're given a unique key and its value is a json dictionary(strings are keys and anything type for values) It is not good for querying data compared to sqlite or other querying languages like postgresql.\\n\\n# NewSQL tries to blend traditional query language to NOSQL languages. Traditional languages follow the ACID principles and NOSQL is lenient on the A,I, and D principle(the C, consistent, is kept). Basically, try to use traditional query langauages on big data.\"\n },\n {\n \"alpha_fraction\": 0.6915380358695984,\n \"alphanum_fraction\": 0.697255551815033,\n \"avg_line_length\": 31.70093536376953,\n \"blob_id\": \"9c563c3afce6780d82752778b8c00624f77004e0\",\n \"content_id\": \"4a3666d1a54f4c72ba47d30476df6ea401d59bbb\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3498,\n \"license_type\": \"permissive\",\n \"max_line_length\": 85,\n \"num_lines\": 107,\n \"path\": \"/module2-sql-for-analysis/lecture.py\",\n \"repo_name\": \"dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Local install. Go to the desired dir and local install\\n## pipenv install psycopg2-binary\\n\\n# Activate\\n## pipenv shell\\n\\nimport psycopg2\\n\\n\\n# From help(psycopg2.connect) - Enter the bottom 4.\\ndbname = 'ximkxdxb'\\nuser = 'ximkxdxb'\\npassword = '' # Don't commit this. delete when you commit/push\\nhost = 'raja.db.elephantsql.com'\\n\\n# Connect to Elephant Database\\npg_conn = psycopg2.connect(dbname=dbname, user=user, password=password, host=host)\\n\\n# Set-up a cursor to read the elephant database\\npg_curs = pg_conn.cursor()\\n\\n# Query and fetchall info in elephant database\\npg_curs.execute('SELECT * FROM test_table;')\\nprint(pg_curs.fetchall())\\n\\n# ETL - Extract, Transform, Load Pipeline\\nimport sqlite3\\n\\n# Use sqlite3 and retrieve the RPG database\\nsl_conn = sqlite3.connect('../module1-introduction-to-sql/rpg_db.sqlite3')\\nprint(sl_conn) # Test to see imported library is retrieved\\n\\n# Setup a sqlite3 cursor to read the database\\nsl_curs = sl_conn.cursor()\\n\\n# Query and fetchall() from rpg database\\nprint(sl_curs.execute('SELECT COUNT(*) FROM charactercreator_character;').fetchall())\\n\\n# From the rpg database, get all the columns from the table (charcre_char)\\n# Extract from sqlite3 rpg database\\ncharacters = sl_curs.execute('SELECT * FROM charactercreator_character;').fetchall()\\nprint(len(characters)) # Same as COUNT()\\n\\n# Look at the first characters and last characters\\nprint('First line:', characters[0], 'Last line:', characters[-1])\\n\\n# CREATE TABLE to load to PostgreSQL - This will be our character schema\\n# Pre- Load\\n# Sets up table to be loaded to postgreSQL database\\ncreate_character_table = '''\\n CREATE TABLE charactercreator_character (\\n character_id SERIAL PRIMARY KEY,\\n name VARCHAR(30),\\n level INT,\\n exp INT,\\n hp INT,\\n strength INT,\\n intelligence INT,\\n dexterity INT,\\n wisdom INT\\n );\\n'''\\n############################################################\\n# Read through the table we created above\\n#print(pg_curs.execute(create_character_table))\\n\\n# Define INSERT INTO \\nattempted_insert = '''\\n INSERT INTO charactercreator_character\\n VALUES ''' + str(characters[0])\\nprint(attempted_insert)\\n\\n# INSERT INTO created table\\n#print(pg_curs.execute(attempted_insert))\\n\\n# Changing Databases - CREATE or INSERT a table. You have to commit to make it work\\npg_conn.commit() \\n###############################################################\\n# Can't create duplicate so comment out the above ####### to #########\\n\\n# After commit - Query the newly created and insert info\\npg_curs.execute('SELECT * FROM charactercreator_character;')\\npg_characters = pg_curs.fetchall()\\nprint(pg_curs.fetchall())\\n\\n# Only INSERT INTO 1 row\\nprint('Row:',pg_characters[0], 'Row Length:', len(pg_characters))\\n\\n# INSERT INTO the rest of the rows to postgresql database\\n# for character in characters[1:]:\\n# insert_character = '''\\n# INSERT INTO charactercreator_character\\n# VALUES ''' + str(character)\\n# pg_curs.execute(insert_character)\\npg_conn.commit() # Can't duplicate so comment out the for loop\\n\\n# Restart the cursor\\npg_curs = pg_conn.cursor()\\n# Query the finished table from loaded to postgresql database\\npg_curs.execute('SELECT * FROM charactercreator_character')\\n# Fetch all table\\npg_characters = pg_curs.fetchall()\\nprint('Row:', pg_characters, 'Row Length:', len(pg_characters))\\n\\n# Test our RPG database to our PostgreSQL database - No Error\\nfor character, pg_character in zip(characters, pg_characters):\\n assert character == pg_character\"\n },\n {\n \"alpha_fraction\": 0.7256371974945068,\n \"alphanum_fraction\": 0.7466266751289368,\n \"avg_line_length\": 32.400001525878906,\n \"blob_id\": \"b888f040374b3a2345d2325107e77130baccc761\",\n \"content_id\": \"9af415d603e274053b873c4255960ca1f23df2b0\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 667,\n \"license_type\": \"permissive\",\n \"max_line_length\": 194,\n \"num_lines\": 20,\n \"path\": \"/module1-introduction-to-sql/query_part2.py\",\n \"repo_name\": \"dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pandas as pd\\nimport sqlite3\\nfrom sqlalchemy import create_engine\\n\\n# Engine use for sql query\\nengine = create_engine('sqlite://', echo=False)\\n\\n# DataFrame\\ndf = pd.read_csv('buddymove_holidayiq.csv')\\n\\n# Create a new Database\\nconn = sqlite3.connect('buddymove_holiday.sqlite3')\\n\\n# Use df as sql\\ndf.to_sql('buddymove_holiday', con=engine)\\n\\n# Use the engine to execute query\\nprint('The count is:', engine.execute('SELECT COUNT(*) FROM buddymove_holiday').fetchone()[0])\\n\\nprint('The number of users who reviewed at least 100 Nature and Shopping category:', engine.execute('SELECT COUNT(*) FROM buddymove_holiday WHERE Nature>=100 AND Shopping >= 100').fetchone()[0])\"\n },\n {\n \"alpha_fraction\": 0.6687822341918945,\n \"alphanum_fraction\": 0.6751289367675781,\n \"avg_line_length\": 23.25,\n \"blob_id\": \"76deeef3c883d1255db0c97de36a627edf17346d\",\n \"content_id\": \"89ea5d30114b53b5ea21b05173c258e4c276467b\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2521,\n \"license_type\": \"permissive\",\n \"max_line_length\": 82,\n \"num_lines\": 104,\n \"path\": \"/module2-sql-for-analysis/insert_titanic.py\",\n \"repo_name\": \"dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import psycopg2\\n\\n# Re Enter\\ndbname = 'eczastgf'\\nuser = 'eczastgf'\\npassword = ''\\nhost = 'raja.db.elephantsql.com'\\n\\n# Connect to ElephantSQL\\npg_conn = psycopg2.connect(dbname=dbname, user=user, password=password, host=host)\\n\\n# Read the ElephantSQL database\\npg_curs = pg_conn.cursor()\\n\\n# Df to titanic database\\nimport pandas as pd\\nfrom sqlalchemy import create_engine\\n\\n# Save df\\ndf = pd.read_csv('titanic.csv')\\n\\n# Replace ' with an empty space\\ndf['Name'] = df['Name'].str.replace('\\\\'', ' ')\\n\\n# Create engine - Used to convert a dataframe to database\\nengine = create_engine('sqlite://', echo=False)\\n\\n# Create the new table on sql db\\ndf.to_sql('titanic', con=engine)\\n\\n# Titanic df is now a db - Is a list of tuples\\ntitanic_db = engine.execute('SELECT * FROM titanic;').fetchall()\\n\\n# Create an empty db for ElephantSQL\\ncreate_titanic_table = '''\\n CREATE TABLE titanic (\\n id integer NOT NULL PRIMARY KEY,\\n survived INT,\\n pclass INT,\\n name VARCHAR(100),\\n sex VARCHAR(10),\\n age INT,\\n siblings_spouses_aboard INT,\\n parents_child_aboard INT,\\n fare INT\\n );\\n'''\\n\\n# Read thourgh the table we created\\npg_curs.execute(create_titanic_table)\\n\\n# INSERT INTO the rest of the rows to postgresql database\\nfor row in titanic_db:\\n insert_row = '''\\n INSERT INTO titanic\\n VALUES ''' + str(row)\\n pg_curs.execute(insert_row)\\n\\n# Commit to Elephantsql and test from browser: SELECT * FROM titanic\\npg_conn.commit()\\n\\n# Create a local titanic db then upload to elephant db\\n\\\"\\\"\\\"\\nimport sqlite3\\n\\n# Reset index to get an index,id\\ndf = df.reset_index().rename(columns={'index':'id'})\\n\\n# Save a create a titanic database\\nsl_conn = sqlite3.connect('titanic.sqlite3')\\n\\n# CREATE TYPE for titanic sex\\n# CREATE TABLE for titanic database\\ncreate_titanic_table = '''\\n CREATE TABLE titanic (\\n id integer NOT NULL PRIMARY KEY AUTOINCREMENT,\\n survived INT,\\n pclass INT,\\n name VARCHAR(100),\\n sex VARCHAR(10),\\n age INT,\\n siblings_spouses_aboard INT,\\n parents_child_aboard INT,\\n fare INT\\n );\\n'''\\n\\n# Read the database\\nsl_curs = sl_conn.cursor()\\n\\n# Create the table for the titanic database\\n#sl_curs.execute(create_titanic_table)\\n## Comment out since already created\\n\\n# Define INSERT INTO\\ninsert_titanic_db = '''\\n INSERT INTO titanic\\n VALUES ''' + str(tuple(df.loc[0, :].tolist()))\\n\\nsl_curs.execute(insert_titanic_db)\\n\\n# Fetch all data in titanic database\\nprint(sl_curs.execute('SELECT * FROM titanic;').fetchall())\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.6910856366157532,\n \"alphanum_fraction\": 0.7007943391799927,\n \"avg_line_length\": 25.057470321655273,\n \"blob_id\": \"c64d7fffdf5c223f6b7ba61d9e59ee4d32d1fbe6\",\n \"content_id\": \"453d8717e4f6a9efeda041cc92da3be52117847e\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2266,\n \"license_type\": \"permissive\",\n \"max_line_length\": 84,\n \"num_lines\": 87,\n \"path\": \"/sprint_practice/sprint_practice.py\",\n \"repo_name\": \"dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# From the cmd prompt set-up a virtual enviornment \\n# `pipenv install ...` is the dir\\n\\n# Run `pipenv shell` to activate\\n\\nimport sqlite3\\n\\n# Connect to a database and if there's is none it will create one\\nconn = sqlite3.connect('rpg_db.sqlite3')\\n\\n# Used to make queries\\ncurs = conn.cursor()\\n\\n# Execute query and fetch all the data\\nresult = curs.execute('SELECT * FROM armory_item;')\\nresult.fetchall()\\n# print(result.fetchall())\\n\\n############### Create a new table ###############\\n\\n# 'toy_db_sqlite3' doesn't exist so it will create one\\nconn = sqlite3.connect('toy_db_sqlite3')\\n\\n# Create a table called toy\\ncreate_toy_table = '''CREATE TABLE toy (\\n toy_id integer NOT NULL PRIMARY KEY AUTOINCREMENT,\\n toy_name VARCHAR(30),\\n price NUMERIC,\\n small_parts integer\\n)\\n'''\\n\\n# Create a cursor to make queries\\ncurs = conn.cursor()\\n\\n# Execute `create_toy_table` to create the table\\n## Is empty right now since we didn't populate it\\n#curs.execute(create_toy_table)\\n## Comment out above line since we can't create duplicates\\n# print(curs.execute(create_toy_table).fetchall())\\n\\n# INSERT INTO toy VALUES to create new values of fields/col\\n\\ninsert = \\\"INSERT INTO toy VALUES (1, 'Legos', 10.5, 1), (2, 'Train', 17.6, 0);\\\"\\n\\n# Execute to insert new values to toy table\\ncurs.execute(insert)\\n\\n# Fetch all from toy database - toy_db is a list\\ntoy_db = curs.execute('SELECT * FROM toy;').fetchall()\\n\\n######### Try to launch it to elephantsql #####\\n\\nimport psycopg2\\n\\n# Enter/Re enter details from elephantsql\\n\\ndbname = 'oxwfzsio'\\nuser = 'oxwfzsio'\\npassword = ''\\nhost = 'raja.db.elephantsql.com'\\n\\n# connect to elephantsql\\npg_conn = psycopg2.connect(dbname=dbname, user=user, password=password, host=host)\\n\\n# Used to read the database on elephantsql\\npg_curs = pg_conn.cursor()\\n\\n# Create an empty table for ElephantSQL\\ncreate_toy_table_esql = '''CREATE TABLE toy (\\n toy_id integer NOT NULL PRIMARY KEY,\\n toy_name VARCHAR(30),\\n price NUMERIC,\\n small_parts integer\\n)\\n'''\\n# Execute to create an empty table for ESQL\\npg_curs.execute(create_toy_table_esql)\\n\\n# # Execute previous created toy database\\nfor row in toy_db:\\n insert_row = '''\\n INSERT INTO toy VALUES ''' + str(row)\\n pg_curs.execute(insert_row)\\n\\n# Commit to see the changes on elephantsql\\npg_conn.commit()\"\n },\n {\n \"alpha_fraction\": 0.5940678119659424,\n \"alphanum_fraction\": 0.6101694703102112,\n \"avg_line_length\": 28.524999618530273,\n \"blob_id\": \"3e72a53cd7649f40f0078800f2ff6ad8cd560b83\",\n \"content_id\": \"f85a24fb589934eb83b54307513a6172640e6eb3\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1180,\n \"license_type\": \"permissive\",\n \"max_line_length\": 93,\n \"num_lines\": 40,\n \"path\": \"/sprint2/demo_data.py\",\n \"repo_name\": \"dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sqlite3\\n\\n# Connect to a database\\nconn = sqlite3.connect('demo_data.sqlite3')\\n\\n# Make a cursor to read the database\\ncurs = conn.cursor()\\n\\n# Create a table\\ncreate_demo_data = '''\\nCREATE TABLE demo (\\n s CHAR(1),\\n x INT,\\n y INT\\n)\\n'''\\n\\n# Execute to create demo data\\ncurs.execute(create_demo_data)\\n\\n# INSERT INTO demo VALUES to create new values of columns\\ninsert = \\\"INSERT INTO demo VALUES ('g', 3, 9), ('v', 5, 7),('f', 8, 7);\\\"\\n\\n# Execute to insert into demo table\\ncurs.execute(insert)\\n\\n# Query - Count how many rows\\nresult_count = curs.execute('SELECT COUNT(*) FROM demo;').fetchone()\\nprint('There are:', result_count[0], 'rows')\\nprint('###################################')\\n\\n# Query - How many rows where both x and y are >= 5\\nresult_count_5 = curs.execute('SELECT COUNT(*) FROM demo WHERE x >=5 AND y >= 5;').fetchone()\\nprint('There are:', result_count_5[0], 'rows of x and y >= 5')\\nprint('###################################')\\n\\n# Query - How many unique values of y are there?\\nresult_unique_y = curs.execute('SELECT COUNT(DISTINCT y) FROM demo;').fetchone()\\nprint('There are:', result_unique_y[0], 'unique values of y')\\nprint('###################################')\"\n },\n {\n \"alpha_fraction\": 0.6904506683349609,\n \"alphanum_fraction\": 0.707617998123169,\n \"avg_line_length\": 19.955055236816406,\n \"blob_id\": \"33bbe1309e1a11cd2bab107a330678bca4b75216\",\n \"content_id\": \"03fcf221e9551222254134959bd6592c6797cd5c\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1864,\n \"license_type\": \"permissive\",\n \"max_line_length\": 79,\n \"num_lines\": 89,\n \"path\": \"/module1-introduction-to-sql/lecture.py\",\n \"repo_name\": \"dustiny5/DS-Unit-3-Sprint-2-SQL-and-Databases\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sqlite3\\n\\n# Database\\nconn = sqlite3.connect('rpg_db.sqlite3')\\n\\nconn\\n# Goes through the database - can have multiple\\ncurs = conn.cursor()\\n\\ncurs\\n\\n# Make a query\\nquery = 'SELECT COUNT(*) FROM armory_item;'\\n\\n# Save results of query\\nresult = curs.execute(query)\\nresult\\n\\n# Fetch all results from the query\\nresult.fetchall()\\n\\n\\n# SELECT * selects all\\nquery = 'SELECT * FROM armory_item;'\\nresult = curs.execute(query)\\nresult.fetchall()\\n\\n# Fetch one result from the query\\nresult = curs.execute(query)\\n# Once fetched then it'll won't be in there.\\nresult.fetchone()\\n\\n############## DB Browser for SQLite ###########\\n'''\\n# Select all columns from the armory_item table\\nSELECT * FROM armory_item\\n\\n# Select the table where item_id is 167, 45, 27\\nWHERE item_id IN(167, 45, 27);\\n\\n\\n'''\\n\\n############## Create a new table ###############\\n\\nimport sqlite3\\nconn = sqlite3.connect('toy_db_sqlite3')\\n\\n# Create a table, toy_id, \\ncreate_statement = '''CREATE TALBE toy (\\n toy_id integer NOT NULL PRIMARY KEY AUTOINCREMENT,\\n toy_name varchar(30),\\n price numeric,\\n small_parts integer)'''\\n\\n# \\ncurs = conn.cursor()\\n\\n# Create table\\ncurs.execute(create_statement)\\n\\n# Create new values for the table\\ninsert = \\\"INSERT INTO toy VALUES (1, 'Legos', 10.5, 1), (2, 'Train', 17.6, 0);\\\"\\n# Exevute query\\ncurs.execute(insert)\\n\\n\\n# Explicit Inner Join#\\n'''\\nSELECT \\nname, mana\\nFROM charactercreator_mage\\nINNER JOIN charactercreator_character\\nON charactercreator_mage.character_ptr_id = \\ncharactercreator_character.character_id;\\n'''\\n# Implicit Inner Join #\\n'''\\nSELECT name, mana\\nFROM charactercreator_mage, charactercreator_character\\nWHERE charactercreator_character.character_id =\\ncharactercreator_mage.character_ptr_id;\\n'''\\n# Alias by using AS #\\n'''\\nSELECT cc.name, cm.mana\\nFROM charactercreator_mage AS cm, charactercreator_character AS cc\\nWHERE cc.character_id = cm.character_ptr_id;\\n'''\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":7,"string":"7"}}},{"rowIdx":2977692,"cells":{"repo_name":{"kind":"string","value":"nmamie/Flask-Webapplication"},"repo_url":{"kind":"string","value":"https://github.com/nmamie/Flask-Webapplication"},"snapshot_id":{"kind":"string","value":"57594701a5c8d8dfe348c1bb202694d40696ab88"},"revision_id":{"kind":"string","value":"b243d0ea1983f0768615ce9d12786d302c1eda26"},"directory_id":{"kind":"string","value":"c2df0f7aa2db749b5a3b237d1c00a47ce38a3c26"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-03-19T01:21:46.761850","string":"2023-03-19T01:21:46.761850"},"revision_date":{"kind":"timestamp","value":"2021-03-13T17:39:24","string":"2021-03-13T17:39:24"},"committer_date":{"kind":"timestamp","value":"2021-03-13T17:39:24","string":"2021-03-13T17:39:24"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5322425365447998,"alphanum_fraction":0.5466794967651367,"avg_line_length":31.484375,"blob_id":"0b028607eb009647fc6a4148b99127e681f50137","content_id":"691f468cd06bd0269af63974214e869fea532e23","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"HTML","length_bytes":2078,"license_type":"no_license","max_line_length":312,"num_lines":64,"path":"/templates/about.html","repo_name":"nmamie/Flask-Webapplication","src_encoding":"UTF-8","text":"{% extends \"layout.html\" %}\n\n{% block title %}\n About\n{% endblock %}\n\n{% block main %}\n\n<!-- dark mode -->\n{% if not dbase %}\n <h4>You have no users in database.</h4>\n{% endif %}\n{% if dbase %}\n {% for dbase_item in dbase %}\n\n {% if not dbase_item.mode %}\n <script>\n window.onload = function() {\n myFunction();\n };\n </script>\n\n {% endif %}\n\n {% endfor %}\n{% endif %}\n\n<!-- OMEGA Description -->\n <section class=\"container\" style=\"max-width:600px\">\n <h1 class=\"center\">OMEGA Rackets</h1>\n <p class=\"center\"><i>We strive for an internationally connected Racketlon community</i></p>\n <p class=\"justify\">The team behind OMEGA Rackets consists of the brothers Noah Mamié and Léon Mamié. Originating from the difficult time period during the COVID-19 pandemic in 2020, the idea behind this initiative is to promote Racketlon on an international scale and connect the members of this community.</p>\n </section>\n\n<!-- The Team Section -->\n <div class=\"row\">\n <div class=\"col-sm-6\">\n <p class=\"text-center\"><strong>Noah Mamié</strong></p><br>\n <a href=\"#demo\" data-toggle=\"collapse\">\n <img src=\"/static/Noah2.jpg\" class=\"img-circle person\" alt=\"Random Name\">\n </a>\n <div id=\"demo\" class=\"collapse\">\n <p>Co-Founder</p>\n <p>HSG Student and Racketlon enthusiast</p>\n <p>NLA player at Go For 4</p>\n <p>CH Ranking #15</p>\n <p>Member since 2020</p>\n </div>\n </div>\n <div class=\"col-sm-6\">\n <p class=\"text-center\"><strong>Léon Mamie</strong></p><br>\n <a href=\"#demo\" data-toggle=\"collapse\">\n <img src=\"/static/Leon.jpg\" class=\"img-circle person\" alt=\"Random Name\">\n </a>\n <div id=\"demo\" class=\"collapse\">\n <p>Co-Founder</p>\n <p>ETH Student and Racketlon enthusiast</p>\n <p>NLA player at Go For 4</p>\n <p>CH Ranking #29</p>\n <p>Member since 2020</p>\n </div>\n </div>\n </div>\n{% endblock %}"},{"alpha_fraction":0.5973207354545593,"alphanum_fraction":0.6051133871078491,"avg_line_length":31.448863983154297,"blob_id":"7e2c5882b474d81350962dde2b0150a44bc980c4","content_id":"f312533297a31c2aef55096f8130f2808d610834","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":11421,"license_type":"no_license","max_line_length":219,"num_lines":352,"path":"/application.py","repo_name":"nmamie/Flask-Webapplication","src_encoding":"UTF-8","text":"import os\nimport os.path\nfrom os import path\nimport camelot\nimport csv\nimport requests\n\nfrom cs50 import SQL\nfrom flask import Flask, flash, jsonify, redirect, render_template, request, session\nfrom flask_session import Session\nfrom tempfile import mkdtemp\nfrom werkzeug.exceptions import default_exceptions, HTTPException, InternalServerError\nfrom werkzeug.security import check_password_hash, generate_password_hash\n\nfrom helpers import apology, login_required\n\n# configure application\napp = Flask(__name__)\n\n# ensuring templates are auto-reloaded\napp.config[\"TEMPLATES_AUTO_RELOAD\"] = True\n\n# ensuring responses aren't cached\n@app.after_request\ndef after_request(response):\n response.headers[\"Cache-Control\"] = \"no-cache, no-store, must-revalidate\"\n response.headers[\"Expires\"] = 0\n response.headers[\"Pragma\"] = \"no-cache\"\n return response\n\n# configure session to use filesystem (instead of signed cookies)\napp.config[\"SESSION_FILE_DIR\"] = mkdtemp()\napp.config[\"SESSION_PERMANENT\"] = False\napp.config[\"SESSION_TYPE\"] = \"filesystem\"\nSession(app)\n\n# configure lib to use slqite3 database\ndb = SQL(\"sqlite:///sports.db\")\n\n# configure web application routes\n@app.route(\"/\")\n@login_required\ndef index():\n \"show sports homepage\"\n\n dbase = db.execute(\"SELECT * FROM users WHERE id = :id\", id=session[\"user_id\"])\n\n return render_template(\"index.html\", dbase=dbase)\n\n@app.route(\"/analytics\")\n@login_required\ndef analytics():\n \"show player analytics\"\n\n dbase = db.execute(\"SELECT * FROM users WHERE id = :id\", id=session[\"user_id\"])\n user = dbase[0][\"id\"]\n name = dbase[0][\"name\"]\n\n pbase = db.execute(\"SELECT * FROM players\")\n\n if len(pbase) == 0:\n # read csv into database\n with open(\"ranking.csv\", \"r\") as ranking:\n reader = csv.DictReader(ranking, delimiter=\",\")\n\n for row in reader:\n\n players = []\n\n players.append(row[\"Rackets\"])\n players.append(row[\"Rank\"])\n players.append(row[\"Name\"])\n players.append(row[\"Prev\"])\n players.append(row[\"ID\"])\n players.append(row[\"Points\"])\n\n db.execute(\"INSERT INTO players (Rackets, Rank, Name, Surname, ID, Points) VALUES(?, ?, ?, ?, ?, ?)\", players[0], players[1], players[2], players[3], players[4], players[5])\n\n db_player = db.execute(\"SELECT * FROM history WHERE user_id = :id\", id = user)\n if len(db_player) == 0:\n month = 0\n for i in range(12):\n month += 1\n if path.exists(\"ranking\" + str(month) + \".csv\") == True:\n with open(\"ranking\" + str(month) + \".csv\", \"r\") as ranking:\n reader = csv.DictReader(ranking, delimiter=\",\")\n\n for row in reader:\n\n if row[\"Name\"] == name:\n history = []\n\n history.append(row[\"Rackets\"])\n history.append(row[\"Rank\"])\n history.append(row[\"Name\"])\n history.append(row[\"ID\"])\n history.append(row[\"Points\"])\n\n db.execute(\"INSERT INTO history (user_id, month, rackets, rank, name, player_id, points) VALUES(?, ?, ?, ?, ?, ?, ?)\", user, month, history[0], history[1], history[2], history[3], history[4])\n db_player = db.execute(\"SELECT * FROM history WHERE user_id = :id\", id = user)\n else:\n print(path.exists(\"ranking\" + str(month) + \".csv\"))\n\n year = []\n month = []\n rank = []\n for i in range(len(db_player)):\n y = 2020\n m = db_player[i][\"month\"]\n year.append(y)\n month.append(m)\n rank.append(db_player[i][\"rank\"])\n m += 1\n\n return render_template(\"analytics.html\", dbase=dbase, pbase=pbase, year=year, month=month, rank=rank)\n\n@app.route(\"/tour\")\n@login_required\ndef tour():\n \"show info about tour\"\n\n dbase = db.execute(\"SELECT * FROM users WHERE id = :id\", id=session[\"user_id\"])\n\n\n return render_template(\"tour.html\", dbase=dbase)\n\n@app.route(\"/history\")\n@login_required\ndef history():\n \"show info about history\"\n\n dbase = db.execute(\"SELECT * FROM users WHERE id = :id\", id=session[\"user_id\"])\n\n return render_template(\"history.html\", dbase=dbase)\n\n@app.route(\"/about\")\n@login_required\ndef about():\n \"show info about team\"\n\n dbase = db.execute(\"SELECT * FROM users WHERE id = :id\", id=session[\"user_id\"])\n\n return render_template(\"about.html\", dbase=dbase)\n\n\n@app.route(\"/profile\")\n@login_required\ndef profile():\n \"\"\"Show user profile and options\"\"\"\n\n dbase = db.execute(\"SELECT * FROM users WHERE id = :id\", id=session[\"user_id\"])\n\n # player rating\n dbase = db.execute(\"SELECT * FROM users WHERE id = :id\", id=session[\"user_id\"])\n name = dbase[0][\"name\"]\n player = db.execute(\"SELECT * FROM players WHERE Name = :name\", name = name)\n\n return render_template(\"profile.html\", dbase=dbase, player=player)\n\n\n@app.route(\"/password\", methods=[\"GET\", \"POST\"])\n@login_required\ndef password():\n \"\"\"Change password\"\"\"\n dbase = db.execute(\"SELECT * FROM users WHERE id = :id\", id=session[\"user_id\"])\n\n # User reached route via GET\n if request.method == \"GET\":\n return render_template(\"password.html\", dbase=dbase)\n # User reached route via POST (as by submitting a form via POST)\n else:\n\n # Ensure old password was submitted\n if not request.form.get(\"old\"):\n return apology(\"must provide old password\", 403)\n\n # Ensure new password was submitted\n if not request.form.get(\"new\"):\n return apology(\"must provide new password\", 403)\n\n # Ensure confirmation was submitted\n elif not request.form.get(\"confirmation\"):\n return apology(\"must provide confirmation\", 403)\n\n # Ensure passwords match\n elif request.form.get(\"new\") != request.form.get(\"confirmation\"):\n return apology(\"passwords do not match\", 403)\n\n # Check user database for password hash\n user_db = db.execute(\"SELECT * FROM users WHERE id = :id\", id=session[\"user_id\"])\n for i in range(len(user_db)):\n pw_hash = user_db[i][\"hash\"]\n\n old = request.form.get(\"old\")\n new = request.form.get(\"new\")\n new_hash = generate_password_hash(request.form.get(\"new\"))\n\n # Ensure username exists and password is correct\n if not check_password_hash(pw_hash, old):\n return apology(\"old password is incorrect\", 403)\n\n # ensure new password is not the same as old password\n elif old == new:\n return apology(\"new password is same as old\", 403)\n\n else:\n # Update the password for this user\n db.execute(\"UPDATE users SET hash = :hash WHERE id = :id\", hash = new_hash, id = session[\"user_id\"])\n\n # Redirect user back to profile\n return redirect(\"/profile\")\n\n@app.route(\"/success\")\n@login_required\ndef success():\n \"\"\"Successful dark/light mode\"\"\"\n\n dbase = db.execute(\"SELECT * FROM users WHERE id = :id\", id=session[\"user_id\"])\n dmode = dbase[0][\"mode\"]\n\n if dmode == 1:\n # Update the mode for this user\n db.execute(\"UPDATE users SET mode = :mode WHERE id = :id\", mode = 0, id = session[\"user_id\"])\n dmode = 0\n else:\n # Update the mode for this user\n db.execute(\"UPDATE users SET mode = :mode WHERE id = :id\", mode = 1, id = session[\"user_id\"])\n dmode = 1\n\n return render_template(\"success.html\", dbase=dbase)\n\n\n\n@app.route(\"/login\", methods=[\"GET\", \"POST\"])\ndef login():\n \"\"\"Log user in\"\"\"\n\n # Forget any user_id\n session.clear()\n\n # User reached route via POST (as by submitting a form via POST)\n if request.method == \"POST\":\n\n # Ensure username was submitted\n if not request.form.get(\"username\"):\n return apology(\"must provide username\", 403)\n\n # Ensure password was submitted\n elif not request.form.get(\"password\"):\n return apology(\"must provide password\", 403)\n\n # Query database for username\n rows = db.execute(\"SELECT * FROM users WHERE username = :username\",\n username=request.form.get(\"username\"))\n\n # Ensure username exists and password is correct\n if len(rows) != 1 or not check_password_hash(rows[0][\"hash\"], request.form.get(\"password\")):\n return apology(\"invalid username and/or password\", 403)\n\n # Remember which user has logged in\n session[\"user_id\"] = rows[0][\"id\"]\n\n # Redirect user to home page\n return redirect(\"/\")\n\n # User reached route via GET (as by clicking a link or via redirect)\n else:\n return render_template(\"login.html\")\n\n\n@app.route(\"/logout\")\ndef logout():\n \"\"\"Log user out\"\"\"\n\n # Forget any user_id\n session.clear()\n\n # Redirect user to login form\n return redirect(\"/\")\n\n\n@app.route(\"/register\", methods=[\"GET\", \"POST\"])\ndef register():\n \"\"\"Register user\"\"\"\n\n # User reached route via GET\n if request.method == \"GET\":\n return render_template(\"register.html\")\n\n # User reached route via POST (as by submitting a form via POST)\n else:\n\n # Ensure username was submitted\n if not request.form.get(\"first\"):\n return apology(\"must provide first name\", 403)\n\n # Ensure username was submitted\n if not request.form.get(\"last\"):\n return apology(\"must provide last name\", 403)\n\n # Ensure username was submitted\n if not request.form.get(\"username\"):\n return apology(\"must provide username\", 403)\n\n # Ensure password was submitted\n elif not request.form.get(\"password\"):\n return apology(\"must provide password\", 403)\n\n # Ensure confirmation was submitted\n elif not request.form.get(\"confirmation\"):\n return apology(\"must provide password\", 403)\n\n # Ensure passwords match\n elif request.form.get(\"password\") != request.form.get(\"confirmation\"):\n return apology(\"passwords do not match\", 403)\n\n hash = generate_password_hash(request.form.get(\"password\"))\n\n # Check user database for username\n user_db = db.execute(\"SELECT * FROM users WHERE username = :username\", username=request.form.get(\"username\"))\n if len(user_db) == 1:\n\n username = user_db[0][\"username\"]\n\n # Ensure the username is not in the database already\n if request.form.get(\"username\") == username:\n return apology(\"username is already registered\", 403)\n\n else:\n # Add new user to database if not existing yet\n name = request.form.get(\"last\") + \"\\n\" + request.form.get(\"first\")\n mode = 1\n user = db.execute(\"INSERT INTO users (username, hash, name, mode) VALUES (:username, :hash, :name, :mode)\", username=request.form.get(\"username\"), hash=hash, name=name, mode=mode)\n\n # remember which user has logged in\n session[\"user_id\"] = user\n\n\n # Redirect user to home page\n return redirect(\"/\")\n\n\ndef errorhandler(e):\n \"\"\"Handle error\"\"\"\n if not isinstance(e, HTTPException):\n e = InternalServerError()\n return apology(e.name, e.code)\n\n\n# listen for errors\nfor code in default_exceptions:\n app.errorhandler(code)(errorhandler)"},{"alpha_fraction":0.7740113139152527,"alphanum_fraction":0.7814265489578247,"avg_line_length":42.56922912597656,"blob_id":"8ed0c276d1d77212530d900dac57014308d0d21e","content_id":"570fe632e34afc3ed67f575e0685e009f6ec980d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":2833,"license_type":"no_license","max_line_length":200,"num_lines":65,"path":"/README.md","repo_name":"nmamie/Flask-Webapplication","src_encoding":"UTF-8","text":"# CS50x: Final Project - Flask Web App #\n\n<br />\n\n<p align=\"center\">\nNoah Mamié <br />\nLéon Mamié <br />\n</p>\n\n<p align=\"center\">\n<b>CS50x: Computer Science and the Art of Programming</b> <br />\nFall 2020 <br />\nDecember 30, 2020\n</p>\n\n<p align=\"center\">\n<b>Professor:</b> David J. Malan <br />\n<b>Team:</b> OMEGA Rackets <br />\nPython, HTML/CSS/JS\n</p>\n<br />\n\n\n## Introduction\n\nThe vision of OMEGA Rackets is to promote the beautiful sport of Racketlon around the globe and connect enthusiasts to make our community even greater.\nAs racket sports enthusiasts, the brothers Léon and Noah Mamié have decided to team up and create a webpage featuring Racketlon-related content only.\nWe provide players with analytics on their athlete profile, an outlook on the FIR World Tour, the history of this sport and, ultimately, a presentation of our team.\n\n## Analytics\n\nThe analytics section features a personalized ranking history in the form of a line chart.\nThis graphic aims at providing Racketlon players with an idea of their personal development over the last months.\nFurthermore, this page contains a ranking table consisting of the top Racketlon players for demonstration.\n\n## Tour\n\nThe tour section aims at providing members of our community with an overview of the FIR Racketlon Tour, allowing them to make up their minds on which tournaments they wish to participate at.\nUltimately, we hope to spread awareness of this beautiful sport with initiatives like these, resulting in an increasing Racketlon community that is connected all around the globe.\n\n## History\n\nThe tour section walks Racketlon enthusiasts through the most important steps in the past of this still young sport.\nStarting out in the 1980s, Racketlon has seen a tremendous development over the years and has recently sparked some interest with professional athletes from its individual sports.\nThereby, names such as Alison Waters, Nick Matthew and Pongfinity member Otto Tennilä have graced this sport with their presence.\n\n## About\nThe about section introduces the team behind OMEGA rackets and provides information on the individual members' backgrounds.\n\n## More Features\nAdditionally, the the website has been equipped with some trending features to enhance the user experience even further.\nSpecifically, apart from gaining insights into their personal ranking history, registered users may switch between dark and light mode (default: dark) and change their password in the profile section.\nLast but not least, the profile section also contains specific player stats that are tailored to the individual users.\n\n\nOverall, we feel that we have learned a lot from this experience and hope to be able to transfer some of the knowledge gained to future projects.\n\n\n## Software\n\n1. Python: Flask, Camelot (for reading tables from PDFs), Requests\n\n2. HTML, CSS and JavaScript\n\n3. Leaflet (open maps)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5322425365447998,\n \"alphanum_fraction\": 0.5466794967651367,\n \"avg_line_length\": 31.484375,\n \"blob_id\": \"0b028607eb009647fc6a4148b99127e681f50137\",\n \"content_id\": \"691f468cd06bd0269af63974214e869fea532e23\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"HTML\",\n \"length_bytes\": 2078,\n \"license_type\": \"no_license\",\n \"max_line_length\": 312,\n \"num_lines\": 64,\n \"path\": \"/templates/about.html\",\n \"repo_name\": \"nmamie/Flask-Webapplication\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"{% extends \\\"layout.html\\\" %}\\n\\n{% block title %}\\n About\\n{% endblock %}\\n\\n{% block main %}\\n\\n<!-- dark mode -->\\n{% if not dbase %}\\n <h4>You have no users in database.</h4>\\n{% endif %}\\n{% if dbase %}\\n {% for dbase_item in dbase %}\\n\\n {% if not dbase_item.mode %}\\n <script>\\n window.onload = function() {\\n myFunction();\\n };\\n </script>\\n\\n {% endif %}\\n\\n {% endfor %}\\n{% endif %}\\n\\n<!-- OMEGA Description -->\\n <section class=\\\"container\\\" style=\\\"max-width:600px\\\">\\n <h1 class=\\\"center\\\">OMEGA Rackets</h1>\\n <p class=\\\"center\\\"><i>We strive for an internationally connected Racketlon community</i></p>\\n <p class=\\\"justify\\\">The team behind OMEGA Rackets consists of the brothers Noah Mamié and Léon Mamié. Originating from the difficult time period during the COVID-19 pandemic in 2020, the idea behind this initiative is to promote Racketlon on an international scale and connect the members of this community.</p>\\n </section>\\n\\n<!-- The Team Section -->\\n <div class=\\\"row\\\">\\n <div class=\\\"col-sm-6\\\">\\n <p class=\\\"text-center\\\"><strong>Noah Mamié</strong></p><br>\\n <a href=\\\"#demo\\\" data-toggle=\\\"collapse\\\">\\n <img src=\\\"/static/Noah2.jpg\\\" class=\\\"img-circle person\\\" alt=\\\"Random Name\\\">\\n </a>\\n <div id=\\\"demo\\\" class=\\\"collapse\\\">\\n <p>Co-Founder</p>\\n <p>HSG Student and Racketlon enthusiast</p>\\n <p>NLA player at Go For 4</p>\\n <p>CH Ranking #15</p>\\n <p>Member since 2020</p>\\n </div>\\n </div>\\n <div class=\\\"col-sm-6\\\">\\n <p class=\\\"text-center\\\"><strong>Léon Mamie</strong></p><br>\\n <a href=\\\"#demo\\\" data-toggle=\\\"collapse\\\">\\n <img src=\\\"/static/Leon.jpg\\\" class=\\\"img-circle person\\\" alt=\\\"Random Name\\\">\\n </a>\\n <div id=\\\"demo\\\" class=\\\"collapse\\\">\\n <p>Co-Founder</p>\\n <p>ETH Student and Racketlon enthusiast</p>\\n <p>NLA player at Go For 4</p>\\n <p>CH Ranking #29</p>\\n <p>Member since 2020</p>\\n </div>\\n </div>\\n </div>\\n{% endblock %}\"\n },\n {\n \"alpha_fraction\": 0.5973207354545593,\n \"alphanum_fraction\": 0.6051133871078491,\n \"avg_line_length\": 31.448863983154297,\n \"blob_id\": \"7e2c5882b474d81350962dde2b0150a44bc980c4\",\n \"content_id\": \"f312533297a31c2aef55096f8130f2808d610834\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 11421,\n \"license_type\": \"no_license\",\n \"max_line_length\": 219,\n \"num_lines\": 352,\n \"path\": \"/application.py\",\n \"repo_name\": \"nmamie/Flask-Webapplication\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport os.path\\nfrom os import path\\nimport camelot\\nimport csv\\nimport requests\\n\\nfrom cs50 import SQL\\nfrom flask import Flask, flash, jsonify, redirect, render_template, request, session\\nfrom flask_session import Session\\nfrom tempfile import mkdtemp\\nfrom werkzeug.exceptions import default_exceptions, HTTPException, InternalServerError\\nfrom werkzeug.security import check_password_hash, generate_password_hash\\n\\nfrom helpers import apology, login_required\\n\\n# configure application\\napp = Flask(__name__)\\n\\n# ensuring templates are auto-reloaded\\napp.config[\\\"TEMPLATES_AUTO_RELOAD\\\"] = True\\n\\n# ensuring responses aren't cached\\n@app.after_request\\ndef after_request(response):\\n response.headers[\\\"Cache-Control\\\"] = \\\"no-cache, no-store, must-revalidate\\\"\\n response.headers[\\\"Expires\\\"] = 0\\n response.headers[\\\"Pragma\\\"] = \\\"no-cache\\\"\\n return response\\n\\n# configure session to use filesystem (instead of signed cookies)\\napp.config[\\\"SESSION_FILE_DIR\\\"] = mkdtemp()\\napp.config[\\\"SESSION_PERMANENT\\\"] = False\\napp.config[\\\"SESSION_TYPE\\\"] = \\\"filesystem\\\"\\nSession(app)\\n\\n# configure lib to use slqite3 database\\ndb = SQL(\\\"sqlite:///sports.db\\\")\\n\\n# configure web application routes\\n@app.route(\\\"/\\\")\\n@login_required\\ndef index():\\n \\\"show sports homepage\\\"\\n\\n dbase = db.execute(\\\"SELECT * FROM users WHERE id = :id\\\", id=session[\\\"user_id\\\"])\\n\\n return render_template(\\\"index.html\\\", dbase=dbase)\\n\\n@app.route(\\\"/analytics\\\")\\n@login_required\\ndef analytics():\\n \\\"show player analytics\\\"\\n\\n dbase = db.execute(\\\"SELECT * FROM users WHERE id = :id\\\", id=session[\\\"user_id\\\"])\\n user = dbase[0][\\\"id\\\"]\\n name = dbase[0][\\\"name\\\"]\\n\\n pbase = db.execute(\\\"SELECT * FROM players\\\")\\n\\n if len(pbase) == 0:\\n # read csv into database\\n with open(\\\"ranking.csv\\\", \\\"r\\\") as ranking:\\n reader = csv.DictReader(ranking, delimiter=\\\",\\\")\\n\\n for row in reader:\\n\\n players = []\\n\\n players.append(row[\\\"Rackets\\\"])\\n players.append(row[\\\"Rank\\\"])\\n players.append(row[\\\"Name\\\"])\\n players.append(row[\\\"Prev\\\"])\\n players.append(row[\\\"ID\\\"])\\n players.append(row[\\\"Points\\\"])\\n\\n db.execute(\\\"INSERT INTO players (Rackets, Rank, Name, Surname, ID, Points) VALUES(?, ?, ?, ?, ?, ?)\\\", players[0], players[1], players[2], players[3], players[4], players[5])\\n\\n db_player = db.execute(\\\"SELECT * FROM history WHERE user_id = :id\\\", id = user)\\n if len(db_player) == 0:\\n month = 0\\n for i in range(12):\\n month += 1\\n if path.exists(\\\"ranking\\\" + str(month) + \\\".csv\\\") == True:\\n with open(\\\"ranking\\\" + str(month) + \\\".csv\\\", \\\"r\\\") as ranking:\\n reader = csv.DictReader(ranking, delimiter=\\\",\\\")\\n\\n for row in reader:\\n\\n if row[\\\"Name\\\"] == name:\\n history = []\\n\\n history.append(row[\\\"Rackets\\\"])\\n history.append(row[\\\"Rank\\\"])\\n history.append(row[\\\"Name\\\"])\\n history.append(row[\\\"ID\\\"])\\n history.append(row[\\\"Points\\\"])\\n\\n db.execute(\\\"INSERT INTO history (user_id, month, rackets, rank, name, player_id, points) VALUES(?, ?, ?, ?, ?, ?, ?)\\\", user, month, history[0], history[1], history[2], history[3], history[4])\\n db_player = db.execute(\\\"SELECT * FROM history WHERE user_id = :id\\\", id = user)\\n else:\\n print(path.exists(\\\"ranking\\\" + str(month) + \\\".csv\\\"))\\n\\n year = []\\n month = []\\n rank = []\\n for i in range(len(db_player)):\\n y = 2020\\n m = db_player[i][\\\"month\\\"]\\n year.append(y)\\n month.append(m)\\n rank.append(db_player[i][\\\"rank\\\"])\\n m += 1\\n\\n return render_template(\\\"analytics.html\\\", dbase=dbase, pbase=pbase, year=year, month=month, rank=rank)\\n\\n@app.route(\\\"/tour\\\")\\n@login_required\\ndef tour():\\n \\\"show info about tour\\\"\\n\\n dbase = db.execute(\\\"SELECT * FROM users WHERE id = :id\\\", id=session[\\\"user_id\\\"])\\n\\n\\n return render_template(\\\"tour.html\\\", dbase=dbase)\\n\\n@app.route(\\\"/history\\\")\\n@login_required\\ndef history():\\n \\\"show info about history\\\"\\n\\n dbase = db.execute(\\\"SELECT * FROM users WHERE id = :id\\\", id=session[\\\"user_id\\\"])\\n\\n return render_template(\\\"history.html\\\", dbase=dbase)\\n\\n@app.route(\\\"/about\\\")\\n@login_required\\ndef about():\\n \\\"show info about team\\\"\\n\\n dbase = db.execute(\\\"SELECT * FROM users WHERE id = :id\\\", id=session[\\\"user_id\\\"])\\n\\n return render_template(\\\"about.html\\\", dbase=dbase)\\n\\n\\n@app.route(\\\"/profile\\\")\\n@login_required\\ndef profile():\\n \\\"\\\"\\\"Show user profile and options\\\"\\\"\\\"\\n\\n dbase = db.execute(\\\"SELECT * FROM users WHERE id = :id\\\", id=session[\\\"user_id\\\"])\\n\\n # player rating\\n dbase = db.execute(\\\"SELECT * FROM users WHERE id = :id\\\", id=session[\\\"user_id\\\"])\\n name = dbase[0][\\\"name\\\"]\\n player = db.execute(\\\"SELECT * FROM players WHERE Name = :name\\\", name = name)\\n\\n return render_template(\\\"profile.html\\\", dbase=dbase, player=player)\\n\\n\\n@app.route(\\\"/password\\\", methods=[\\\"GET\\\", \\\"POST\\\"])\\n@login_required\\ndef password():\\n \\\"\\\"\\\"Change password\\\"\\\"\\\"\\n dbase = db.execute(\\\"SELECT * FROM users WHERE id = :id\\\", id=session[\\\"user_id\\\"])\\n\\n # User reached route via GET\\n if request.method == \\\"GET\\\":\\n return render_template(\\\"password.html\\\", dbase=dbase)\\n # User reached route via POST (as by submitting a form via POST)\\n else:\\n\\n # Ensure old password was submitted\\n if not request.form.get(\\\"old\\\"):\\n return apology(\\\"must provide old password\\\", 403)\\n\\n # Ensure new password was submitted\\n if not request.form.get(\\\"new\\\"):\\n return apology(\\\"must provide new password\\\", 403)\\n\\n # Ensure confirmation was submitted\\n elif not request.form.get(\\\"confirmation\\\"):\\n return apology(\\\"must provide confirmation\\\", 403)\\n\\n # Ensure passwords match\\n elif request.form.get(\\\"new\\\") != request.form.get(\\\"confirmation\\\"):\\n return apology(\\\"passwords do not match\\\", 403)\\n\\n # Check user database for password hash\\n user_db = db.execute(\\\"SELECT * FROM users WHERE id = :id\\\", id=session[\\\"user_id\\\"])\\n for i in range(len(user_db)):\\n pw_hash = user_db[i][\\\"hash\\\"]\\n\\n old = request.form.get(\\\"old\\\")\\n new = request.form.get(\\\"new\\\")\\n new_hash = generate_password_hash(request.form.get(\\\"new\\\"))\\n\\n # Ensure username exists and password is correct\\n if not check_password_hash(pw_hash, old):\\n return apology(\\\"old password is incorrect\\\", 403)\\n\\n # ensure new password is not the same as old password\\n elif old == new:\\n return apology(\\\"new password is same as old\\\", 403)\\n\\n else:\\n # Update the password for this user\\n db.execute(\\\"UPDATE users SET hash = :hash WHERE id = :id\\\", hash = new_hash, id = session[\\\"user_id\\\"])\\n\\n # Redirect user back to profile\\n return redirect(\\\"/profile\\\")\\n\\n@app.route(\\\"/success\\\")\\n@login_required\\ndef success():\\n \\\"\\\"\\\"Successful dark/light mode\\\"\\\"\\\"\\n\\n dbase = db.execute(\\\"SELECT * FROM users WHERE id = :id\\\", id=session[\\\"user_id\\\"])\\n dmode = dbase[0][\\\"mode\\\"]\\n\\n if dmode == 1:\\n # Update the mode for this user\\n db.execute(\\\"UPDATE users SET mode = :mode WHERE id = :id\\\", mode = 0, id = session[\\\"user_id\\\"])\\n dmode = 0\\n else:\\n # Update the mode for this user\\n db.execute(\\\"UPDATE users SET mode = :mode WHERE id = :id\\\", mode = 1, id = session[\\\"user_id\\\"])\\n dmode = 1\\n\\n return render_template(\\\"success.html\\\", dbase=dbase)\\n\\n\\n\\n@app.route(\\\"/login\\\", methods=[\\\"GET\\\", \\\"POST\\\"])\\ndef login():\\n \\\"\\\"\\\"Log user in\\\"\\\"\\\"\\n\\n # Forget any user_id\\n session.clear()\\n\\n # User reached route via POST (as by submitting a form via POST)\\n if request.method == \\\"POST\\\":\\n\\n # Ensure username was submitted\\n if not request.form.get(\\\"username\\\"):\\n return apology(\\\"must provide username\\\", 403)\\n\\n # Ensure password was submitted\\n elif not request.form.get(\\\"password\\\"):\\n return apology(\\\"must provide password\\\", 403)\\n\\n # Query database for username\\n rows = db.execute(\\\"SELECT * FROM users WHERE username = :username\\\",\\n username=request.form.get(\\\"username\\\"))\\n\\n # Ensure username exists and password is correct\\n if len(rows) != 1 or not check_password_hash(rows[0][\\\"hash\\\"], request.form.get(\\\"password\\\")):\\n return apology(\\\"invalid username and/or password\\\", 403)\\n\\n # Remember which user has logged in\\n session[\\\"user_id\\\"] = rows[0][\\\"id\\\"]\\n\\n # Redirect user to home page\\n return redirect(\\\"/\\\")\\n\\n # User reached route via GET (as by clicking a link or via redirect)\\n else:\\n return render_template(\\\"login.html\\\")\\n\\n\\n@app.route(\\\"/logout\\\")\\ndef logout():\\n \\\"\\\"\\\"Log user out\\\"\\\"\\\"\\n\\n # Forget any user_id\\n session.clear()\\n\\n # Redirect user to login form\\n return redirect(\\\"/\\\")\\n\\n\\n@app.route(\\\"/register\\\", methods=[\\\"GET\\\", \\\"POST\\\"])\\ndef register():\\n \\\"\\\"\\\"Register user\\\"\\\"\\\"\\n\\n # User reached route via GET\\n if request.method == \\\"GET\\\":\\n return render_template(\\\"register.html\\\")\\n\\n # User reached route via POST (as by submitting a form via POST)\\n else:\\n\\n # Ensure username was submitted\\n if not request.form.get(\\\"first\\\"):\\n return apology(\\\"must provide first name\\\", 403)\\n\\n # Ensure username was submitted\\n if not request.form.get(\\\"last\\\"):\\n return apology(\\\"must provide last name\\\", 403)\\n\\n # Ensure username was submitted\\n if not request.form.get(\\\"username\\\"):\\n return apology(\\\"must provide username\\\", 403)\\n\\n # Ensure password was submitted\\n elif not request.form.get(\\\"password\\\"):\\n return apology(\\\"must provide password\\\", 403)\\n\\n # Ensure confirmation was submitted\\n elif not request.form.get(\\\"confirmation\\\"):\\n return apology(\\\"must provide password\\\", 403)\\n\\n # Ensure passwords match\\n elif request.form.get(\\\"password\\\") != request.form.get(\\\"confirmation\\\"):\\n return apology(\\\"passwords do not match\\\", 403)\\n\\n hash = generate_password_hash(request.form.get(\\\"password\\\"))\\n\\n # Check user database for username\\n user_db = db.execute(\\\"SELECT * FROM users WHERE username = :username\\\", username=request.form.get(\\\"username\\\"))\\n if len(user_db) == 1:\\n\\n username = user_db[0][\\\"username\\\"]\\n\\n # Ensure the username is not in the database already\\n if request.form.get(\\\"username\\\") == username:\\n return apology(\\\"username is already registered\\\", 403)\\n\\n else:\\n # Add new user to database if not existing yet\\n name = request.form.get(\\\"last\\\") + \\\"\\\\n\\\" + request.form.get(\\\"first\\\")\\n mode = 1\\n user = db.execute(\\\"INSERT INTO users (username, hash, name, mode) VALUES (:username, :hash, :name, :mode)\\\", username=request.form.get(\\\"username\\\"), hash=hash, name=name, mode=mode)\\n\\n # remember which user has logged in\\n session[\\\"user_id\\\"] = user\\n\\n\\n # Redirect user to home page\\n return redirect(\\\"/\\\")\\n\\n\\ndef errorhandler(e):\\n \\\"\\\"\\\"Handle error\\\"\\\"\\\"\\n if not isinstance(e, HTTPException):\\n e = InternalServerError()\\n return apology(e.name, e.code)\\n\\n\\n# listen for errors\\nfor code in default_exceptions:\\n app.errorhandler(code)(errorhandler)\"\n },\n {\n \"alpha_fraction\": 0.7740113139152527,\n \"alphanum_fraction\": 0.7814265489578247,\n \"avg_line_length\": 42.56922912597656,\n \"blob_id\": \"8ed0c276d1d77212530d900dac57014308d0d21e\",\n \"content_id\": \"570fe632e34afc3ed67f575e0685e009f6ec980d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 2833,\n \"license_type\": \"no_license\",\n \"max_line_length\": 200,\n \"num_lines\": 65,\n \"path\": \"/README.md\",\n \"repo_name\": \"nmamie/Flask-Webapplication\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# CS50x: Final Project - Flask Web App #\\n\\n<br />\\n\\n<p align=\\\"center\\\">\\nNoah Mamié <br />\\nLéon Mamié <br />\\n</p>\\n\\n<p align=\\\"center\\\">\\n<b>CS50x: Computer Science and the Art of Programming</b> <br />\\nFall 2020 <br />\\nDecember 30, 2020\\n</p>\\n\\n<p align=\\\"center\\\">\\n<b>Professor:</b> David J. Malan <br />\\n<b>Team:</b> OMEGA Rackets <br />\\nPython, HTML/CSS/JS\\n</p>\\n<br />\\n\\n\\n## Introduction\\n\\nThe vision of OMEGA Rackets is to promote the beautiful sport of Racketlon around the globe and connect enthusiasts to make our community even greater.\\nAs racket sports enthusiasts, the brothers Léon and Noah Mamié have decided to team up and create a webpage featuring Racketlon-related content only.\\nWe provide players with analytics on their athlete profile, an outlook on the FIR World Tour, the history of this sport and, ultimately, a presentation of our team.\\n\\n## Analytics\\n\\nThe analytics section features a personalized ranking history in the form of a line chart.\\nThis graphic aims at providing Racketlon players with an idea of their personal development over the last months.\\nFurthermore, this page contains a ranking table consisting of the top Racketlon players for demonstration.\\n\\n## Tour\\n\\nThe tour section aims at providing members of our community with an overview of the FIR Racketlon Tour, allowing them to make up their minds on which tournaments they wish to participate at.\\nUltimately, we hope to spread awareness of this beautiful sport with initiatives like these, resulting in an increasing Racketlon community that is connected all around the globe.\\n\\n## History\\n\\nThe tour section walks Racketlon enthusiasts through the most important steps in the past of this still young sport.\\nStarting out in the 1980s, Racketlon has seen a tremendous development over the years and has recently sparked some interest with professional athletes from its individual sports.\\nThereby, names such as Alison Waters, Nick Matthew and Pongfinity member Otto Tennilä have graced this sport with their presence.\\n\\n## About\\nThe about section introduces the team behind OMEGA rackets and provides information on the individual members' backgrounds.\\n\\n## More Features\\nAdditionally, the the website has been equipped with some trending features to enhance the user experience even further.\\nSpecifically, apart from gaining insights into their personal ranking history, registered users may switch between dark and light mode (default: dark) and change their password in the profile section.\\nLast but not least, the profile section also contains specific player stats that are tailored to the individual users.\\n\\n\\nOverall, we feel that we have learned a lot from this experience and hope to be able to transfer some of the knowledge gained to future projects.\\n\\n\\n## Software\\n\\n1. Python: Flask, Camelot (for reading tables from PDFs), Requests\\n\\n2. HTML, CSS and JavaScript\\n\\n3. Leaflet (open maps)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2977693,"cells":{"repo_name":{"kind":"string","value":"cansarigol/django-daterangefilter"},"repo_url":{"kind":"string","value":"https://github.com/cansarigol/django-daterangefilter"},"snapshot_id":{"kind":"string","value":"77fd49bebaeec51100a3b0e09f95015591de9ee7"},"revision_id":{"kind":"string","value":"41f0cc606f6623716335f0d60fa18bae07282f66"},"directory_id":{"kind":"string","value":"fa6fdb16dcaf29140c4ec6d24a60481df44f1696"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2022-12-09T10:42:17.359999","string":"2022-12-09T10:42:17.359999"},"revision_date":{"kind":"timestamp","value":"2020-08-30T13:05:55","string":"2020-08-30T13:05:55"},"committer_date":{"kind":"timestamp","value":"2020-08-30T13:05:55","string":"2020-08-30T13:05:55"},"github_id":{"kind":"number","value":291471706,"string":"291,471,706"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"timestamp","value":"2020-08-30T13:04:11","string":"2020-08-30T13:04:11"},"gha_updated_at":{"kind":"timestamp","value":"2020-07-28T15:23:52","string":"2020-07-28T15:23:52"},"gha_pushed_at":{"kind":"timestamp","value":"2019-01-21T12:36:13","string":"2019-01-21T12:36:13"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.8550724387168884,"alphanum_fraction":0.8550724387168884,"avg_line_length":68,"blob_id":"5db45bff9b10124cd49e6027eddc3a7be2a87c41","content_id":"ec3c6342a08437cbb6a27d8b3a3d4dca937dec70","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":69,"license_type":"permissive","max_line_length":68,"num_lines":1,"path":"/daterangefilter/__init__.py","repo_name":"cansarigol/django-daterangefilter","src_encoding":"UTF-8","text":"default_app_config = 'daterangefilter.apps.DateRangeFilterAppConfig'\n"},{"alpha_fraction":0.7573601007461548,"alphanum_fraction":0.7715949416160583,"avg_line_length":47.296875,"blob_id":"bcff5bd088f64aca105d23abb19a1e47654f5237","content_id":"6891159a839f57e4fc0c5f202568f3480abd2af9","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":3091,"license_type":"permissive","max_line_length":443,"num_lines":64,"path":"/README.md","repo_name":"cansarigol/django-daterangefilter","src_encoding":"UTF-8","text":"# Django admin date range filter\n\n[](https://travis-ci.org/andreynovikov/django-daterangefilter)\n[](https://github.com/andreynovikov/django-daterangefilter/releases/latest)\n[](https://pypi.org/project/django-daterangefilter/)\n[](https://pypi.org/project/django-daterangefilter/)\n[](https://github.com/andreynovikov/django-daterangefilter/issues)\n[](https://www.codacy.com/app/novikov/django-daterangefilter)\n[](https://www.codacy.com/app/novikov/django-daterangefilter)\n[](LICENSE)\n\nApplication adds three Django admin list filters: ```DateRangeFilter```, ```PastDateRangeFilter``` and ```FutureDateRangeFilter```. These filters let user filter models by date range. ```PastDateRangeFilter``` and ```FutureDateRangeFilter``` add quick selection of predefined date ranges. Filters can be applied to any model date fields. Application supports default Django admin theme and [Suit theme](https://github.com/darklow/django-suit).\n\n\n\n## Requirements\n\n* Python 2.7+ or Python 3.3+\n* Django 1.9+\n\n## Installation\n\nInstall ```django-daterangefilter``` using pip:\n\n```shell\npip install django-daterangefilter\n```\n\nAdd ```daterangefilter``` to ```INSTALLED_APPS```. Example:\n\n```python\nINSTALLED_APPS = (\n ...\n 'daterangefilter',\n ...\n)\n```\n\nApplication uses static files so do not forget to issue ```collectstatic``` management command in production environment.\n\n## Example usage\n\nin admin.py:\n\n```python\nfrom django.contrib import admin\nfrom daterangefilter.filters import PastDateRangeFilter, FutureDateRangeFilter\n\n@admin.register(Post)\nclass PostAdmin(admin.ModelAdmin):\n list_filter = [\n ('created_at', PastDateRangeFilter), ('publish_at', FutureDateRangeFilter)\n ]\n```\n\n## Advanced usage\n\nPredefined ranges can be completely redefined by overriding ```_past_ranges.html``` and ```_future_ranges.html``` templates.\nTake into account that these templates are inserted in the middle of the javascript code and may contain nothing but ranges\ndefinition. For more examples on using ```moment``` library refer to [library documentation](https://momentjs.com/docs/#/manipulating/).\n\n## Credits\n\nFilter widget uses a great JavaScript date range picker component - [Date Range Picker](https://github.com/dangrossman/daterangepicker) by Dan Grossman.\n"},{"alpha_fraction":0.6400741934776306,"alphanum_fraction":0.6456400752067566,"avg_line_length":32.6875,"blob_id":"bf0afed53d60c20a2f25f3f203049d70a70f4471","content_id":"f92c985caa8378254beea18107c7528b2647badd","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1078,"license_type":"permissive","max_line_length":83,"num_lines":32,"path":"/setup.py","repo_name":"cansarigol/django-daterangefilter","src_encoding":"UTF-8","text":"import setuptools\n\nwith open('README.md', 'r') as fh:\n long_description = fh.read()\n\nsetuptools.setup(\n name='django-daterangefilter',\n version='1.0.0',\n license='MIT',\n author='Andrey Novikov',\n author_email='novikov@gmail.com',\n description='Date range filter for Django admin',\n long_description=long_description,\n long_description_content_type='text/markdown',\n url='https://github.com/andreynovikov/django-daterangefilter/tree/master',\n project_urls={\n 'Source': 'https://github.com/andreynovikov/django-daterangefilter/',\n 'Tracker': 'https://github.com/andreynovikov/django-daterangefilter/issues'\n },\n packages=setuptools.find_packages(),\n include_package_data=True,\n zip_safe=False,\n classifiers=[\n 'Development Status :: 5 - Production/Stable',\n 'Framework :: Django',\n 'Programming Language :: Python',\n 'Programming Language :: Python :: 2',\n 'Programming Language :: Python :: 3',\n 'License :: OSI Approved :: MIT License',\n 'Operating System :: OS Independent',\n ],\n)\n"},{"alpha_fraction":0.6098495721817017,"alphanum_fraction":0.6119139194488525,"avg_line_length":43.6184196472168,"blob_id":"9fda87128b6c3ca97416532c2497b745de8bf008","content_id":"4b9e6f0c03303d0565c7e6c8735d43b7f6b42dae","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3391,"license_type":"permissive","max_line_length":161,"num_lines":76,"path":"/daterangefilter/filters.py","repo_name":"cansarigol/django-daterangefilter","src_encoding":"UTF-8","text":"import datetime\n\nfrom django.db import models\nfrom django.contrib import admin, messages\nfrom django.utils import timezone\nfrom django.utils.translation import gettext_lazy as _\nfrom django.conf import settings\n\n\nclass DateRangeFilter(admin.FieldListFilter):\n def __init__(self, field, request, params, model, model_admin, field_path):\n self.field_name = field_path\n self.lookup_kwarg_gte = '{}__gte'.format(field_path)\n self.lookup_kwarg_lte = '{}__lte'.format(field_path)\n self.lookup_gte = params.get(self.lookup_kwarg_gte)\n self.lookup_lte = params.get(self.lookup_kwarg_lte)\n # todo: check if this is required in default admin\n if self.lookup_gte == '':\n params.pop(self.lookup_kwarg_gte)\n if self.lookup_lte == '':\n params.pop(self.lookup_kwarg_lte)\n if self.lookup_gte and self.lookup_lte:\n self.lookup_val = '{} - {}'.format(self.lookup_gte, self.lookup_lte)\n # if we are filtering DateTimeField we should add one day to final date\n if \"__\" in field_path:\n related_model, field = field_path.split(\"__\")\n field = model._meta.get_field(related_model).related_model._meta.get_field(field)\n else:\n field = model._meta.get_field(field_path)\n \n if isinstance(field, models.DateTimeField):\n try:\n gte_date = datetime.datetime.strptime(self.lookup_gte, '%Y-%m-%d')\n lte_date = datetime.datetime.strptime(self.lookup_lte, '%Y-%m-%d')\n lte_date = lte_date + datetime.timedelta(seconds=3600*24-1)\n if settings.USE_TZ:\n gte_date = timezone.make_aware(gte_date, timezone.get_current_timezone())\n lte_date = timezone.make_aware(lte_date, timezone.get_current_timezone())\n params[self.lookup_kwarg_gte] = gte_date.strftime('%Y-%m-%d %H:%M:%S%z')\n params[self.lookup_kwarg_lte] = lte_date.strftime('%Y-%m-%d %H:%M:%S%z')\n except ValueError:\n messages.add_message(request, messages.ERROR, _(\"Invalid date for '%(field_name)s' field range filter\") % {'field_name': field.verbose_name})\n else:\n self.lookup_val = ''\n super(DateRangeFilter, self).__init__(field, request, params, model, model_admin, field_path)\n\n def get_template(self):\n if 'suit' in settings.INSTALLED_APPS:\n return 'daterangefilter/suit_daterangefilter.html'\n else:\n return 'daterangefilter/daterangefilter.html'\n\n def choices(self, changelist):\n yield {\n 'field_name': self.field_path,\n 'ranges_template': self.ranges_template,\n 'value': self.lookup_val,\n 'query_string': changelist.get_query_string(remove=self._get_expected_fields())\n }\n\n def expected_parameters(self):\n return self._get_expected_fields()\n\n def _get_expected_fields(self):\n return [self.lookup_kwarg_gte, self.lookup_kwarg_lte]\n\n template = property(get_template)\n ranges_template = None\n\n\nclass FutureDateRangeFilter(DateRangeFilter):\n ranges_template = 'daterangefilter/_future_ranges.html'\n\n\nclass PastDateRangeFilter(DateRangeFilter):\n ranges_template = 'daterangefilter/_past_ranges.html'\n"},{"alpha_fraction":0.654275119304657,"alphanum_fraction":0.654275119304657,"avg_line_length":47.90909194946289,"blob_id":"af54435b210a6d654944fe4e4ca1f9be2a63a864","content_id":"44de1457f1b4cc2e6fd6e30c9346627b641e5475","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"HTML","length_bytes":538,"license_type":"permissive","max_line_length":97,"num_lines":11,"path":"/daterangefilter/templates/daterangefilter/_load_momentjs.html","repo_name":"cansarigol/django-daterangefilter","src_encoding":"UTF-8","text":"{% load static %}\n{% if LANGUAGE_CODE != 'en-us' %}\n {% if LANGUAGE_CODE in 'ru,' %}{# we use prefetched locale files for available translations #}\n<script src=\"{% static 'daterangefilter/moment/moment.min.js' %}\"></script>\n<script src=\"{% static 'daterangefilter/moment/locale/'|add:LANGUAGE_CODE|add:'.js' %}\"></script>\n {% else %}\n<script src=\"{% static 'daterangefilter/moment/moment-with-locales.min.js' %}\"></script>\n {% endif %}\n{% else %}\n<script src=\"{% static 'daterangefilter/moment/moment.min.js' %}\"></script>\n{% endif %}\n"},{"alpha_fraction":0.7669903039932251,"alphanum_fraction":0.7669903039932251,"avg_line_length":28.428571701049805,"blob_id":"c93c25970dc4286b51008c9b3b335bd887ebf24d","content_id":"e374891407a1a1572ec607597e3ce173fa0594ef","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":206,"license_type":"permissive","max_line_length":55,"num_lines":7,"path":"/daterangefilter/apps.py","repo_name":"cansarigol/django-daterangefilter","src_encoding":"UTF-8","text":"from django.apps import AppConfig\nfrom django.utils.translation import ugettext_lazy as _\n\n\nclass DateRangeFilterAppConfig(AppConfig):\n name = 'daterangefilter'\n verbose_name = _('Date Range Filter')\n"}],"string":"[\n {\n \"alpha_fraction\": 0.8550724387168884,\n \"alphanum_fraction\": 0.8550724387168884,\n \"avg_line_length\": 68,\n \"blob_id\": \"5db45bff9b10124cd49e6027eddc3a7be2a87c41\",\n \"content_id\": \"ec3c6342a08437cbb6a27d8b3a3d4dca937dec70\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 69,\n \"license_type\": \"permissive\",\n \"max_line_length\": 68,\n \"num_lines\": 1,\n \"path\": \"/daterangefilter/__init__.py\",\n \"repo_name\": \"cansarigol/django-daterangefilter\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"default_app_config = 'daterangefilter.apps.DateRangeFilterAppConfig'\\n\"\n },\n {\n \"alpha_fraction\": 0.7573601007461548,\n \"alphanum_fraction\": 0.7715949416160583,\n \"avg_line_length\": 47.296875,\n \"blob_id\": \"bcff5bd088f64aca105d23abb19a1e47654f5237\",\n \"content_id\": \"6891159a839f57e4fc0c5f202568f3480abd2af9\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 3091,\n \"license_type\": \"permissive\",\n \"max_line_length\": 443,\n \"num_lines\": 64,\n \"path\": \"/README.md\",\n \"repo_name\": \"cansarigol/django-daterangefilter\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Django admin date range filter\\n\\n[](https://travis-ci.org/andreynovikov/django-daterangefilter)\\n[](https://github.com/andreynovikov/django-daterangefilter/releases/latest)\\n[](https://pypi.org/project/django-daterangefilter/)\\n[](https://pypi.org/project/django-daterangefilter/)\\n[](https://github.com/andreynovikov/django-daterangefilter/issues)\\n[](https://www.codacy.com/app/novikov/django-daterangefilter)\\n[](https://www.codacy.com/app/novikov/django-daterangefilter)\\n[](LICENSE)\\n\\nApplication adds three Django admin list filters: ```DateRangeFilter```, ```PastDateRangeFilter``` and ```FutureDateRangeFilter```. These filters let user filter models by date range. ```PastDateRangeFilter``` and ```FutureDateRangeFilter``` add quick selection of predefined date ranges. Filters can be applied to any model date fields. Application supports default Django admin theme and [Suit theme](https://github.com/darklow/django-suit).\\n\\n\\n\\n## Requirements\\n\\n* Python 2.7+ or Python 3.3+\\n* Django 1.9+\\n\\n## Installation\\n\\nInstall ```django-daterangefilter``` using pip:\\n\\n```shell\\npip install django-daterangefilter\\n```\\n\\nAdd ```daterangefilter``` to ```INSTALLED_APPS```. Example:\\n\\n```python\\nINSTALLED_APPS = (\\n ...\\n 'daterangefilter',\\n ...\\n)\\n```\\n\\nApplication uses static files so do not forget to issue ```collectstatic``` management command in production environment.\\n\\n## Example usage\\n\\nin admin.py:\\n\\n```python\\nfrom django.contrib import admin\\nfrom daterangefilter.filters import PastDateRangeFilter, FutureDateRangeFilter\\n\\n@admin.register(Post)\\nclass PostAdmin(admin.ModelAdmin):\\n list_filter = [\\n ('created_at', PastDateRangeFilter), ('publish_at', FutureDateRangeFilter)\\n ]\\n```\\n\\n## Advanced usage\\n\\nPredefined ranges can be completely redefined by overriding ```_past_ranges.html``` and ```_future_ranges.html``` templates.\\nTake into account that these templates are inserted in the middle of the javascript code and may contain nothing but ranges\\ndefinition. For more examples on using ```moment``` library refer to [library documentation](https://momentjs.com/docs/#/manipulating/).\\n\\n## Credits\\n\\nFilter widget uses a great JavaScript date range picker component - [Date Range Picker](https://github.com/dangrossman/daterangepicker) by Dan Grossman.\\n\"\n },\n {\n \"alpha_fraction\": 0.6400741934776306,\n \"alphanum_fraction\": 0.6456400752067566,\n \"avg_line_length\": 32.6875,\n \"blob_id\": \"bf0afed53d60c20a2f25f3f203049d70a70f4471\",\n \"content_id\": \"f92c985caa8378254beea18107c7528b2647badd\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1078,\n \"license_type\": \"permissive\",\n \"max_line_length\": 83,\n \"num_lines\": 32,\n \"path\": \"/setup.py\",\n \"repo_name\": \"cansarigol/django-daterangefilter\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import setuptools\\n\\nwith open('README.md', 'r') as fh:\\n long_description = fh.read()\\n\\nsetuptools.setup(\\n name='django-daterangefilter',\\n version='1.0.0',\\n license='MIT',\\n author='Andrey Novikov',\\n author_email='novikov@gmail.com',\\n description='Date range filter for Django admin',\\n long_description=long_description,\\n long_description_content_type='text/markdown',\\n url='https://github.com/andreynovikov/django-daterangefilter/tree/master',\\n project_urls={\\n 'Source': 'https://github.com/andreynovikov/django-daterangefilter/',\\n 'Tracker': 'https://github.com/andreynovikov/django-daterangefilter/issues'\\n },\\n packages=setuptools.find_packages(),\\n include_package_data=True,\\n zip_safe=False,\\n classifiers=[\\n 'Development Status :: 5 - Production/Stable',\\n 'Framework :: Django',\\n 'Programming Language :: Python',\\n 'Programming Language :: Python :: 2',\\n 'Programming Language :: Python :: 3',\\n 'License :: OSI Approved :: MIT License',\\n 'Operating System :: OS Independent',\\n ],\\n)\\n\"\n },\n {\n \"alpha_fraction\": 0.6098495721817017,\n \"alphanum_fraction\": 0.6119139194488525,\n \"avg_line_length\": 43.6184196472168,\n \"blob_id\": \"9fda87128b6c3ca97416532c2497b745de8bf008\",\n \"content_id\": \"4b9e6f0c03303d0565c7e6c8735d43b7f6b42dae\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3391,\n \"license_type\": \"permissive\",\n \"max_line_length\": 161,\n \"num_lines\": 76,\n \"path\": \"/daterangefilter/filters.py\",\n \"repo_name\": \"cansarigol/django-daterangefilter\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import datetime\\n\\nfrom django.db import models\\nfrom django.contrib import admin, messages\\nfrom django.utils import timezone\\nfrom django.utils.translation import gettext_lazy as _\\nfrom django.conf import settings\\n\\n\\nclass DateRangeFilter(admin.FieldListFilter):\\n def __init__(self, field, request, params, model, model_admin, field_path):\\n self.field_name = field_path\\n self.lookup_kwarg_gte = '{}__gte'.format(field_path)\\n self.lookup_kwarg_lte = '{}__lte'.format(field_path)\\n self.lookup_gte = params.get(self.lookup_kwarg_gte)\\n self.lookup_lte = params.get(self.lookup_kwarg_lte)\\n # todo: check if this is required in default admin\\n if self.lookup_gte == '':\\n params.pop(self.lookup_kwarg_gte)\\n if self.lookup_lte == '':\\n params.pop(self.lookup_kwarg_lte)\\n if self.lookup_gte and self.lookup_lte:\\n self.lookup_val = '{} - {}'.format(self.lookup_gte, self.lookup_lte)\\n # if we are filtering DateTimeField we should add one day to final date\\n if \\\"__\\\" in field_path:\\n related_model, field = field_path.split(\\\"__\\\")\\n field = model._meta.get_field(related_model).related_model._meta.get_field(field)\\n else:\\n field = model._meta.get_field(field_path)\\n \\n if isinstance(field, models.DateTimeField):\\n try:\\n gte_date = datetime.datetime.strptime(self.lookup_gte, '%Y-%m-%d')\\n lte_date = datetime.datetime.strptime(self.lookup_lte, '%Y-%m-%d')\\n lte_date = lte_date + datetime.timedelta(seconds=3600*24-1)\\n if settings.USE_TZ:\\n gte_date = timezone.make_aware(gte_date, timezone.get_current_timezone())\\n lte_date = timezone.make_aware(lte_date, timezone.get_current_timezone())\\n params[self.lookup_kwarg_gte] = gte_date.strftime('%Y-%m-%d %H:%M:%S%z')\\n params[self.lookup_kwarg_lte] = lte_date.strftime('%Y-%m-%d %H:%M:%S%z')\\n except ValueError:\\n messages.add_message(request, messages.ERROR, _(\\\"Invalid date for '%(field_name)s' field range filter\\\") % {'field_name': field.verbose_name})\\n else:\\n self.lookup_val = ''\\n super(DateRangeFilter, self).__init__(field, request, params, model, model_admin, field_path)\\n\\n def get_template(self):\\n if 'suit' in settings.INSTALLED_APPS:\\n return 'daterangefilter/suit_daterangefilter.html'\\n else:\\n return 'daterangefilter/daterangefilter.html'\\n\\n def choices(self, changelist):\\n yield {\\n 'field_name': self.field_path,\\n 'ranges_template': self.ranges_template,\\n 'value': self.lookup_val,\\n 'query_string': changelist.get_query_string(remove=self._get_expected_fields())\\n }\\n\\n def expected_parameters(self):\\n return self._get_expected_fields()\\n\\n def _get_expected_fields(self):\\n return [self.lookup_kwarg_gte, self.lookup_kwarg_lte]\\n\\n template = property(get_template)\\n ranges_template = None\\n\\n\\nclass FutureDateRangeFilter(DateRangeFilter):\\n ranges_template = 'daterangefilter/_future_ranges.html'\\n\\n\\nclass PastDateRangeFilter(DateRangeFilter):\\n ranges_template = 'daterangefilter/_past_ranges.html'\\n\"\n },\n {\n \"alpha_fraction\": 0.654275119304657,\n \"alphanum_fraction\": 0.654275119304657,\n \"avg_line_length\": 47.90909194946289,\n \"blob_id\": \"af54435b210a6d654944fe4e4ca1f9be2a63a864\",\n \"content_id\": \"44de1457f1b4cc2e6fd6e30c9346627b641e5475\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"HTML\",\n \"length_bytes\": 538,\n \"license_type\": \"permissive\",\n \"max_line_length\": 97,\n \"num_lines\": 11,\n \"path\": \"/daterangefilter/templates/daterangefilter/_load_momentjs.html\",\n \"repo_name\": \"cansarigol/django-daterangefilter\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"{% load static %}\\n{% if LANGUAGE_CODE != 'en-us' %}\\n {% if LANGUAGE_CODE in 'ru,' %}{# we use prefetched locale files for available translations #}\\n<script src=\\\"{% static 'daterangefilter/moment/moment.min.js' %}\\\"></script>\\n<script src=\\\"{% static 'daterangefilter/moment/locale/'|add:LANGUAGE_CODE|add:'.js' %}\\\"></script>\\n {% else %}\\n<script src=\\\"{% static 'daterangefilter/moment/moment-with-locales.min.js' %}\\\"></script>\\n {% endif %}\\n{% else %}\\n<script src=\\\"{% static 'daterangefilter/moment/moment.min.js' %}\\\"></script>\\n{% endif %}\\n\"\n },\n {\n \"alpha_fraction\": 0.7669903039932251,\n \"alphanum_fraction\": 0.7669903039932251,\n \"avg_line_length\": 28.428571701049805,\n \"blob_id\": \"c93c25970dc4286b51008c9b3b335bd887ebf24d\",\n \"content_id\": \"e374891407a1a1572ec607597e3ce173fa0594ef\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 206,\n \"license_type\": \"permissive\",\n \"max_line_length\": 55,\n \"num_lines\": 7,\n \"path\": \"/daterangefilter/apps.py\",\n \"repo_name\": \"cansarigol/django-daterangefilter\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.apps import AppConfig\\nfrom django.utils.translation import ugettext_lazy as _\\n\\n\\nclass DateRangeFilterAppConfig(AppConfig):\\n name = 'daterangefilter'\\n verbose_name = _('Date Range Filter')\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":6,"string":"6"}}},{"rowIdx":2977694,"cells":{"repo_name":{"kind":"string","value":"mholwill/functions_lab_with_malcolm"},"repo_url":{"kind":"string","value":"https://github.com/mholwill/functions_lab_with_malcolm"},"snapshot_id":{"kind":"string","value":"f085037344fe4d711a1caff5c813eebb73028ba3"},"revision_id":{"kind":"string","value":"614c12219396e160a32a16bbc984187eb0dcf2e1"},"directory_id":{"kind":"string","value":"1eb2c9df52fa433941453440f86db3536472b0b0"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-03-09T17:56:55.579884","string":"2023-03-09T17:56:55.579884"},"revision_date":{"kind":"timestamp","value":"2021-02-24T16:13:31","string":"2021-02-24T16:13:31"},"committer_date":{"kind":"timestamp","value":"2021-02-24T16:13:31","string":"2021-02-24T16:13:31"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.554347813129425,"alphanum_fraction":0.6413043737411499,"avg_line_length":17.600000381469727,"blob_id":"a5eba1fddb8961b36a1fe60d9b31725066830afe","content_id":"55775ef1d3b0e25c6cb23e465008fabcca0f0473","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":92,"license_type":"no_license","max_line_length":31,"num_lines":5,"path":"/src/python_functions_practice.py","repo_name":"mholwill/functions_lab_with_malcolm","src_encoding":"UTF-8","text":"def return_10():\n return 10\n\ndef add(number_1, number_2):\n return number_1 + number_2"}],"string":"[\n {\n \"alpha_fraction\": 0.554347813129425,\n \"alphanum_fraction\": 0.6413043737411499,\n \"avg_line_length\": 17.600000381469727,\n \"blob_id\": \"a5eba1fddb8961b36a1fe60d9b31725066830afe\",\n \"content_id\": \"55775ef1d3b0e25c6cb23e465008fabcca0f0473\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 92,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 5,\n \"path\": \"/src/python_functions_practice.py\",\n \"repo_name\": \"mholwill/functions_lab_with_malcolm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def return_10():\\n return 10\\n\\ndef add(number_1, number_2):\\n return number_1 + number_2\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2977695,"cells":{"repo_name":{"kind":"string","value":"DanTulovsky/game"},"repo_url":{"kind":"string","value":"https://github.com/DanTulovsky/game"},"snapshot_id":{"kind":"string","value":"74a816d543c3aa9082c3fe37b433a5492d724574"},"revision_id":{"kind":"string","value":"6784d65bb702c0edd049afc491f88f9e68aeba70"},"directory_id":{"kind":"string","value":"b4239281a768ed1d0a9b572c51c1d1ad1e6582a1"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2019-06-16T17:41:59.040463","string":"2019-06-16T17:41:59.040463"},"revision_date":{"kind":"timestamp","value":"2013-03-13T02:11:50","string":"2013-03-13T02:11:50"},"committer_date":{"kind":"timestamp","value":"2013-03-13T02:11:50","string":"2013-03-13T02:11:50"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5727847814559937,"alphanum_fraction":0.577531635761261,"avg_line_length":16.55555534362793,"blob_id":"49a5d8fafa4cf783b894aa8d6e73987b4f585659","content_id":"2f53021f1cd8695737b40f6154737ef91f3bb710","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":632,"license_type":"no_license","max_line_length":47,"num_lines":36,"path":"/src/teams.py","repo_name":"DanTulovsky/game","src_encoding":"UTF-8","text":"# Teams.\n\nfrom colors import *\n\n\n\n\nclass Team(object):\n\n def __init__(self, color, strength=0):\n \"\"\"Init.\n\n Args:\n color: (colors.Color) Team color\n \"\"\"\n self.color = color\n self.members = set()\n # as integer; 0 is lowest\n self.strength = strength\n\n def Join(self, square):\n \"\"\"Join this team.\"\"\"\n self.members.add(square)\n\n def Leave(self, square):\n \"\"\"Leave the team.\"\"\"\n try:\n self.members.remove(square)\n except KeyError:\n # already removed\n pass\n\n\nTEAMS = {\"red\": Team(Colors.red),\n \"blue\": Team(Colors.blue, strength=1),\n \"green\": Team(Colors.green)}\n"},{"alpha_fraction":0.6191161274909973,"alphanum_fraction":0.6320657730102539,"avg_line_length":24.87765884399414,"blob_id":"4b646a4d6e5fcc6b6a5bd3230823cc69abc673c5","content_id":"39abee76541bdaed0d689fd01256f41ec73abc1b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4865,"license_type":"no_license","max_line_length":73,"num_lines":188,"path":"/src/square.py","repo_name":"DanTulovsky/game","src_encoding":"UTF-8","text":"# This is a citizen of the world.\n\nimport threading\n\nfrom colors import *\nimport random\nimport teams\n\n\nclass Error(Exception):\n \"\"\"General error.\"\"\"\n\n\nclass TeamError(Error):\n \"\"\"Raised on invalids team.\"\"\"\n\n\nclass Square(object):\n \"\"\"One square.\"\"\"\n\n @property\n def above(self):\n \"\"\"Returns coordinates of square above this one.\"\"\"\n return (self.position[0], self.position[1] - 1)\n\n @property\n def below(self):\n \"\"\"Returns coordinates of square below this one.\"\"\"\n return (self.position[0], self.position[1] + 1)\n\n @property\n def right(self):\n \"\"\"Returns coordinates of square to the right of this one.\"\"\"\n return (self.position[0] + 1, self.position[1])\n\n @property\n def left(self):\n \"\"\"Returns coordinates of square to the left of this one.\"\"\"\n return (self.position[0] - 1, self.position[1])\n\n @property\n def upperleft(self):\n \"\"\"Returns coordinates of square to the upper left of this one.\"\"\"\n return (self.position[0] - 1, self.position[1] - 1)\n\n @property\n def upperright(self):\n \"\"\"Returns coordinates of square to the upper right of this one.\"\"\"\n return (self.position[0] + 1, self.position[1] - 1)\n\n @property\n def lowerleft(self):\n \"\"\"Returns coordinates of square to the lower left of this one.\"\"\"\n return (self.position[0] - 1, self.position[1] + 1)\n\n @property\n def lowerright(self):\n \"\"\"Returns coordinates of square to the lower right of this one.\"\"\"\n return (self.position[0] + 1, self.position[1] + 1)\n\n @property\n def color(self):\n with self._data_lock:\n return self._color\n\n @color.setter\n def color(self, value):\n with self._data_lock:\n self._color = value\n\n def __init__(self, color=Colors.white, position=(0,0), team=None):\n \"\"\"Initial state of a square.\n\n The color is either Colors.black or green. The position\n is (top, left) tuple, but counting squares, not pixels.\n\n So position (1, 1) is actually (10, 10) in pixels. (1 * square_width)\n\n Args:\n color: (string) initial color of the square; b/w\n positions: ((int, int) position in the world (not px)\n team: (teams.Team) the team this square belongs to\n \"\"\"\n self._color = color\n self.tint = Colors.custom(0, 0, 0)\n self.position = position\n self.age = 0 # number of generations this has been alive.\n self._data_lock = threading.Lock()\n self.team = team\n self.tint_increase = 2 # how quickly the colors change\n\n # next generation\n self.color_new = None\n self.tint_new = None\n self.age_new = None\n self.killed = False\n\n # join team\n if self.team is None:\n raise TeamError(\"Team must be specified.\")\n self.team.Join(self)\n\n # tint_int value based on the team\n self._tint_int = self._GetTeamTint()\n\n def FlipColor(self):\n \"\"\"Flips the color of a square.\"\"\"\n if self.color in Colors.alive():\n self.color_new = Colors.white\n else:\n self.color_new = Colors.black\n\n def HappyBirthday(self):\n \"\"\"Adds one to the age of the Square.\"\"\"\n self.tint_new = self.tint\n self.age_new = self.age\n self.color_new = self.color\n self.age_new += 1\n\n # turn a deeper shade based on the team\n if self.tint_new[self._tint_int] + self.tint_increase < 256:\n self.tint_new[self._tint_int] += self.tint_increase\n else:\n tint = 255\n\n def Kill(self):\n \"\"\"Turns square white.\"\"\"\n self.tint_new = self.tint\n self.color_new = Colors.white\n self.tint_new = Colors.custom(0, 0, 0)\n self.age_new = 0\n self.killed = True\n\n if self.team:\n self.team.Leave(self)\n\n def ComeAlive(self, influence_team=None):\n \"\"\"Makes white square come alive -> black.\n\n Args:\n influence_team: (Team) team with the most influence on this square\n \"\"\"\n self.tint_new = self.tint\n self.age_new = 0\n self.color_new = Colors.black\n self.tint_new = Colors.custom(0, 0, 0)\n\n # join team based on neighbors\n if influence_team is not None:\n self.team = influence_team\n else:\n self.team = random.choice(teams.TEAMS.values())\n print \"Joining random team...\"\n self.team.Join(self)\n self._tint_int = self._GetTeamTint()\n\n def UpdateNextGenValues(self):\n \"\"\"Cycles the square to the next generation.\"\"\"\n if self.color_new:\n self.color = self.color_new\n self.color_new = None\n\n if self.age_new:\n self.age = self.age_new\n self.age_new = None\n\n if self.tint_new:\n self.tint = self.tint_new\n self.tint_new = None\n\n if self.killed:\n self.team = None\n self.killed = False\n\n def _GetTeamTint(self):\n \"\"\"Returns the correct tint index to change based on team color.\n\n Returns:\n tint: (int) 0 = r; 2 = g; 1 = b\n \"\"\"\n if self.team.color == Colors.red:\n return 0\n\n if self.team.color == Colors.blue:\n return 2\n\n if self.team.color == Colors.green:\n return 1\n"},{"alpha_fraction":0.6332256197929382,"alphanum_fraction":0.6445332169532776,"avg_line_length":29.548051834106445,"blob_id":"89149cd77fc2ea8a559e8e6e9d04b4867ed85664","content_id":"3bdfd8b1772bd3aeff25d21b0a7cfc178bb89ace","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":11762,"license_type":"no_license","max_line_length":75,"num_lines":385,"path":"/src/world_rules.py","repo_name":"DanTulovsky/game","src_encoding":"UTF-8","text":"\"\"\"\nCreated on Mar 7, 2013\n\n@author: dtulovsky\n\"\"\"\n\nfrom colors import Colors\nfrom copy import *\nimport gflags\nimport logging\nimport random\n\n\nFLAGS = gflags.FLAGS\n\n# References to neighbors\nRIGHT = \"right\"\nLEFT = \"left\"\nABOVE = \"above\"\nBELOW = \"below\"\nUPPERLEFT = \"upperleft\"\nUPPERRIGHT = \"upperright\"\nLOWERLEFT = \"lowerleft\"\nLOWERRIGHT = \"lowerright\"\n\nPOSITIONS = [RIGHT, LEFT, ABOVE, BELOW, UPPERLEFT, UPPERRIGHT, LOWERLEFT,\n LOWERRIGHT]\n\n\nclass Error(Exception):\n \"\"\"General Exception.\"\"\"\n\n\nclass WorldRules(object):\n \"\"\"Defines the rules of the world. Inherit this to extend.\"\"\"\n\n def NextGen(self, square, random_events, neighbors):\n \"\"\"Returns a copy of the square for next generation.\n\n Args:\n square: (Square) square object\n squares: (dict) Squares in the world.\n next_gen: (dict) all square objects for next generation\n index: (int) index of current square in squoares\n random_events: (bool) If True, allow random events (if any)\n\n Returns:\n square: (Square) a copy of the square object with new paramters\n \"\"\"\n raise NotImplemented(\"Don't use this class directly.\")\n\n def RandomEvents(self, squares):\n \"\"\"Introduces random events.\"\"\"\n raise NotImplemented(\"Override this function if you want to use it.\")\n\n\nclass Wolfam222(WorldRules):\n \"\"\"Wolfram222.\"\"\"\n\n color_hash = {(Colors.black, Colors.black, Colors.black): Colors.black,\n (Colors.black, Colors.black, Colors.white): Colors.black,\n (Colors.black, Colors.white, Colors.black): Colors.white,\n (Colors.black, Colors.white, Colors.white): Colors.black,\n (Colors.white, Colors.black, Colors.black): Colors.black,\n (Colors.white, Colors.black, Colors.white): Colors.black,\n (Colors.white, Colors.white, Colors.black): Colors.black,\n (Colors.white, Colors.white, Colors.white): Colors.white}\n\n def NextGen(self, square, random_events, neighbors):\n \"\"\"Given a square, sets its state for the next generation.\n\n * left neighbor self right neighbor => new self\n * b b b => b\n * b b w => b\n * b w b => w\n * b w w => b\n * w b b => b\n * w b w => b\n * w w b => b\n * w w w => w\n \"\"\"\n # copy the square so we don't mix generations\n new_square = copy(square)\n\n try:\n lnc = self._NeighborColor(square, LEFT, squares)\n except (OutsideWorld, NoNeighbor) as e:\n lnc = Colors.white\n\n try:\n rnc = self._NeighborColor(square, RIGHT, squares)\n except (OutsideWorld, NoNeighbor) as e:\n rnc = Colors.white\n\n try:\n new_square.color = Wolfam222.color_hash[(lnc, square.color, rnc)]\n except KeyError, e:\n logging.error(\"Wolfram222 Combination missing (this only works with \"\n \"black and white.\")\n\n next_gen[index] = new_square\n\nclass FlipWorld(WorldRules):\n \"\"\"Flip existing squares only.\"\"\"\n\n def NextGen(self, square, random_events, neighbors):\n \"\"\"Given a square, sets its state for the next generation.\n\n * Flip the color of each existing square.\n \"\"\"\n new_square = copy(square)\n new_square.FlipColor()\n next_gen[index] = new_square\n\n\nclass FlipWorldNeighbor(WorldRules):\n \"\"\"Flip existing squares only.\"\"\"\n\n def NextGen(self, square, random_events, neighbors):\n \"\"\"Given a square, sets its state for the next generation.\n\n * Flips if the neighbors on left and right sides are the same.\n * If there are no neighbors, don't change.\n \"\"\"\n new_square = copy(square)\n try:\n lnc = self._NeighborColor(square, LEFT, squares)\n except (OutsideWorld, NoNeighbor) as e:\n # Either no neighbor or neighbor would be out of this world\n return new_square\n\n if lnc == rnc:\n new_square.FlipColor()\n\n next_gen[index] = new_square\n\n\nclass LifeWorld(WorldRules):\n \"\"\"Life world. Game of life, original rules.\"\"\"\n\n def NextGen(self, square, random_events, neighbors):\n \"\"\"Given a square, sets its state for the next generation.\n\n Supports only black/white squares.\n\n * If black square has < 2 black neighbors, turns white.\n * If black square has 2 or 3 black neighbors, remains black.\n * If black square has > 3 neighbors, turns white.\n * If white square has 3 neighbors, turns black.\n \"\"\"\n if square.color == Colors.black:\n if neighbors[\"total_neighbors\"] < 2:\n square.color_new = Colors.white\n\n if neighbors[\"total_neighbors\"] in [2, 3]:\n square.color_new = Colors.black\n\n if neighbors[\"total_neighbors\"] > 3:\n square.color_new = Colors.white\n\n if square.color == Colors.white:\n if neighbors[\"total_neighbors\"] == 3:\n square.color_new = Colors.black\n elif neighbors[\"total_neighbors\"] == 0:\n square.color_new = Colors.white\n\nclass LifeWorldColorRandom(WorldRules):\n \"\"\"Life world. Custom.\"\"\"\n\n def RandomEvents(self, square):\n \"\"\"Random event for one square.\"\"\"\n MAX_RANDOM = 10000\n\n # % chance a square will flip colors\n if random.randrange(0, MAX_RANDOM, 1) == 1:\n logging.info(\"Random event: flipping square %s.\", square.position)\n square.FlipColor()\n return square\n\n def NextGen(self, square, random_events, neighbors):\n \"\"\"Given a square, sets its state for the next generation.\n\n * If colored square has < 2 black neighbors, turns white.\n * If colored square has 2 or 3 black neighbors, remains colored (same).\n * If colored square has > 3 neighbors, turns white.\n * If white square has 3 neighbors, turns colored (random).\n \"\"\"\n\n if square.color != Colors.white: # is alive\n if neighbors[\"total_neighbors\"] < 2:\n square.color_new = Colors.white\n\n if neighbors[\"total_neighbors\"] in [2, 3]:\n square.color_new = square.color\n\n if neighbors[\"total_neighbors\"] > 3:\n square.color_new = Colors.white\n\n if square.color == Colors.white:\n if neighbors[\"total_neighbors\"] == 3:\n square.color_new = random.choice(Colors.alive())\n elif neighbors[\"total_neighbors\"] == 0:\n square.color_new = Colors.white\n\n if random_events:\n square = self.RandomEvents(square)\n\n\nclass LifeCustomWorld(WorldRules):\n \"\"\"Life world. Custom. Includes other attributes.\"\"\"\n\n def __init__(self):\n super(LifeCustomWorld, self).__init__()\n # kill if less then this number of neighbors\n self.kill_lonely_limit = 2\n # kill if more than this number of neighbors\n self.kill_crowded_limit = 3\n # come alive if this number of neighbors\n self.come_alive_neighbors = 3\n\n def RandomEvents(self, square):\n \"\"\"Random event for one square.\"\"\"\n MAX_RANDOM = 10000\n\n # % chance a square will flip colors\n if random.randrange(0, MAX_RANDOM, 1) == 1:\n logging.info(\"Random event: flipping square %s.\", square.position)\n square.FlipColor()\n\n def NextGen(self, square, random_events, neighbors):\n \"\"\"Given a square, sets its state for the next generation.\n\n * If colored square has < 2 black neighbors, turns white.\n * If colored square has 2 or 3 black neighbors, remains colored (same).\n * If colored square has > 3 neighbors, turns white.\n * If white square has 3 neighbors, turns colored (random).\n \"\"\"\n killed = False\n kill_lonely_limit = self.kill_lonely_limit\n kill_crowded_limit = self.kill_crowded_limit\n come_alive_neighbors = self.come_alive_neighbors\n\n # with age, comes strength\n if square.age > 5:\n kill_lonely_limit = kill_lonely_limit - 1\n\n if square.age > 25:\n kill_crowded_limit = kill_crowded_limit + 1\n\n# if square.age > 60:\n# kill_lonely_limit = kill_lonely_limit - 1\n#\n# if square.age > 105:\n# kill_crowded_limit = kill_crowded_limit + 1\n\n # with deep age, comes weakness\n# if square.age > 50:\n# kill_lonely_limit = kill_lonely_limit\n# kill_crowded_limit = kill_crowded_limit\n#\n# if square.age > 80:\n# kill_lonely_limit = kill_lonely_limit + 1\n# kill_crowded_limit = kill_crowded_limit - 1\n#\n# if square.age > 120:\n# kill_lonely_limit = kill_lonely_limit + 1\n# kill_crowded_limit = kill_crowded_limit - 1\n#\n# if square.age > 150:\n# kill_lonely_limit = kill_lonely_limit + 1\n# kill_crowded_limit = kill_crowded_limit - 1\n\n\n if square.color != Colors.white: # is alive\n if neighbors[\"total_neighbors\"] < kill_lonely_limit:\n square.Kill()\n killed = True\n\n if neighbors[\"total_neighbors\"] > kill_crowded_limit:\n square.Kill()\n killed = True\n\n if not killed:\n # survived this generation!\n square.HappyBirthday()\n\n if square.color == Colors.white:\n if neighbors[\"total_neighbors\"] == come_alive_neighbors:\n square.ComeAlive()\n elif neighbors[\"total_neighbors\"] == 0:\n # Removes uninteresting squares from the list\n square.color_new = Colors.white\n\n if random_events:\n self.RandomEvents(square)\n\nclass LifeCustomWorldFight(WorldRules):\n \"\"\"Life world. Custom. Includes other attributes. Team fights.\"\"\"\n\n def __init__(self):\n super(LifeCustomWorldFight, self).__init__()\n # kill if less then this number of neighbors\n self.kill_lonely_limit = 2\n # how many friends around square kill it\n self.kill_friend_crowded_limit = 6\n # how many enemies around square kill it\n self.kill_enemy_crowded = 2\n # come alive if this number of neighbors\n self.come_alive_neighbors = 2\n\n def RandomEvents(self, square):\n \"\"\"Random event for one square.\"\"\"\n MAX_RANDOM = 10000\n\n # % chance a square will flip colors\n if random.randrange(0, MAX_RANDOM, 1) == 1:\n logging.info(\"Random event: flipping square %s.\", square.position)\n square.FlipColor()\n\n def NextGen(self, square, random_events, neighbors):\n \"\"\"Given a square, sets its state for the next generation.\"\"\"\n killed = False\n kill_lonely_limit = self.kill_lonely_limit\n kill_friend_crowded_limit = self.kill_friend_crowded_limit\n kill_enemy_crowded = self.kill_enemy_crowded\n come_alive_neighbors = self.come_alive_neighbors\n\n # with age, comes strength\n #if square.age > 5:\n # kill_lonely_limit = kill_lonely_limit - 1\n\n #if square.age > 25:\n # kill_crowded_limit = kill_crowded_limit + 1\n\n# if square.age > 60:\n# kill_lonely_limit = kill_lonely_limit - 1\n#\n# if square.age > 105:\n# kill_crowded_limit = kill_crowded_limit + 1\n\n # with deep age, comes weakness\n# if square.age > 50:\n# kill_lonely_limit = kill_lonely_limit\n# kill_crowded_limit = kill_crowded_limit\n#\n# if square.age > 80:\n# kill_lonely_limit = kill_lonely_limit + 1\n# kill_crowded_limit = kill_crowded_limit - 1\n#\n# if square.age > 120:\n# kill_lonely_limit = kill_lonely_limit + 1\n# kill_crowded_limit = kill_crowded_limit - 1\n#\n# if square.age > 150:\n# kill_lonely_limit = kill_lonely_limit + 1\n# kill_crowded_limit = kill_crowded_limit - 1\n\n\n if square.color != Colors.white: # is alive\n if neighbors[\"total_neighbors\"] < kill_lonely_limit:\n square.Kill()\n killed = True\n\n if neighbors[\"friends\"] > kill_friend_crowded_limit:\n square.Kill()\n killed = True\n\n if neighbors[\"enemies\"] > kill_enemy_crowded:\n square.Kill()\n killed = True\n\n if not killed:\n # survived this generation!\n square.HappyBirthday()\n else: # is dead\n if neighbors[\"total_neighbors\"] == come_alive_neighbors:\n if neighbors[\"influence\"] is None:\n pass\n square.ComeAlive(neighbors[\"influence\"])\n elif neighbors[\"total_neighbors\"] == 0:\n # Removes uninteresting squares from the list\n square.color_new = Colors.white\n\n if random_events:\n self.RandomEvents(square)\n\n"},{"alpha_fraction":0.5811789035797119,"alphanum_fraction":0.6866597533226013,"avg_line_length":27.47058868408203,"blob_id":"9d51e86c536d707884fd64e67f7b9a26534207c5","content_id":"c796137c1bbf4d6d49ee1cce0192027112de1430","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":967,"license_type":"no_license","max_line_length":109,"num_lines":34,"path":"/src/pygame_test.py","repo_name":"DanTulovsky/game","src_encoding":"UTF-8","text":"#! /usr/local/bin/python\n\nimport pygame\nimport sys\nimport time\n\nfrom pygame.locals import *\n\npygame.init()\n\nfpsClock = pygame.time.Clock()\nwindowSurfaceObj = pygame.display.set_mode((640, 480))\n\npygame.display.set_caption(\"Game...\")\n\nredColor = pygame.Color(255, 0, 0)\ngreenColor = pygame.Color(0, 255, 0)\nblueColor = pygame.Color(0, 0, 255)\nwhiteColor = pygame.Color(255, 255, 255)\n\nwhile True:\n windowSurfaceObj.fill(whiteColor)\n \n #pygame.draw.polygon(windowSurfaceObj, greenColor, ((146, 0), (291, 106), (236, 277), (56, 277), (0, 106)))\n #pygame.draw.circle(windowSurfaceObj, blueColor, (300, 50), 20, 0)\n #pygame.draw.ellipse(windowSurfaceObj, redColor, (300, 250, 40, 80), 1)\n pygame.draw.rect(windowSurfaceObj, \n redColor, (10, 10, 100, 100))\n \n #pygame.draw.line(windowSurfaceObj, blueColor, (60, 160), (120, 60), 4)\n \n #fpsClock.tick(30) # pause to run the loop at 30 frames per second\n pygame.display.update()\n time.sleep(300)"},{"alpha_fraction":0.6305577754974365,"alphanum_fraction":0.6426839232444763,"avg_line_length":17.477611541748047,"blob_id":"25b1f3186825d092d02da4db6b87180fecf8eae7","content_id":"13054f0082370a64bf82c806e625415f46099efd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1237,"license_type":"no_license","max_line_length":80,"num_lines":67,"path":"/src/colors.py","repo_name":"DanTulovsky/game","src_encoding":"UTF-8","text":"\"\"\"\nCreated on Mar 7, 2013\n\n@author: dtulovsky\n\"\"\"\n\nimport gflags\nimport pygame\n\nFLAGS = gflags.FLAGS\n\ngflags.DEFINE_bool(\"black_white\", False, \"Only black/white mode.\")\n\nWHITE = pygame.Color(\"white\")\nBLACK = pygame.Color(\"black\")\nGREEN = pygame.Color(\"green\")\nRED = pygame.Color(\"red\")\nBLUE = pygame.Color(\"blue\")\nPINK = pygame.Color(255, 0 , 127)\n\n\nclass Colors(object):\n \"\"\"Colors Helper.\"\"\" \n \n @classmethod\n def all(cls):\n if FLAGS.black_white:\n return [Colors.black, Colors.white]\n else:\n return [Colors.white, Colors.black, Colors.green, Colors.red, Colors.blue,\n Colors.pink]\n \n @classmethod\n def alive(cls):\n \"\"\"Returns only alive colors. No white.\"\"\"\n if FLAGS.black_white:\n return [Colors.black]\n else:\n return [Colors.black, Colors.green, Colors.red, Colors.blue, Colors.pink]\n \n @classmethod\n def white(cls):\n return WHITE\n\n @classmethod\n def black(cls):\n return BLACK\n\n @classmethod\n def green(cls):\n return GREEN \n\n @classmethod\n def red(cls):\n return RED\n\n @classmethod\n def blue(cls):\n return BLUE\n\n @classmethod\n def pink(cls):\n return PINK\n \n @classmethod\n def custom(cls, r, g, b, a=255):\n return pygame.Color(r, g, b, a)"},{"alpha_fraction":0.5833257436752319,"alphanum_fraction":0.6002179384231567,"avg_line_length":32.67278289794922,"blob_id":"00f0df2fc999dbdb5e4f97912b29fed50ec72561","content_id":"71e25677b0487b0246fc96f640be0f19db826852","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":11011,"license_type":"no_license","max_line_length":80,"num_lines":327,"path":"/src/game.py","repo_name":"DanTulovsky/game","src_encoding":"UTF-8","text":"#!/usr/local/bin/python\n# -*- coding: utf-8 -*-\n\nfrom copy import *\nimport gflags\nimport logging\nimport random\nimport sys\nimport time\n\nfrom colors import *\nimport random\nimport teams\nimport world\nfrom pygame.locals import *\nfrom square import *\nimport world_rules\n\n\nFLAGS = gflags.FLAGS\ngflags.DEFINE_integer(\"max_generations\", 2000000, \"Generations to run.\")\ngflags.DEFINE_integer(\"world_height\", 1200, \"World height in px.\")\ngflags.DEFINE_integer(\"world_width\", 1200, \"World height in px.\")\ngflags.DEFINE_integer(\"square_width\", 20, \"Citizen square width.\")\ngflags.DEFINE_integer(\"fps\", 5, \"Frame per second (wait time between gens.\")\ngflags.DEFINE_bool(\"random_events\", False, \"Allow random events.\")\ngflags.DEFINE_string(\"rules\", None, \"World rules to use.\")\ngflags.DEFINE_bool(\"random_start\", False, \"Random initial allocation.\")\ngflags.DEFINE_bool(\"manual\", False, \"Allows manual layout of initial \"\n \"position, disables random_start.\")\ngflags.DEFINE_integer(\"workers\", 100, \"Worker threads.\")\n\n\nclass Error(Exception):\n \"\"\"General Exception.\"\"\"\n\n\nclass Game(object):\n \"\"\"Models generations of squares.\n\n Squares change color based on their own color and the color\n of their neighbors. Each generation is simply a row of\n squares.\n\n Empty space on either side is considered to be a Square.Colors.black square.\n \"\"\"\n\n def __init__(self, world_rules, max_generations=None,\n world_width=None, world_height=None,\n square_width=None, random_events=None):\n \"\"\"Init.\n\n Args:\n world_rules: (WorldRules) Or derivative.\n max_generations: (int) how many iterations to run throuhg\n world_width: (int) pixel width of the world\n world_height: (int) pixel height of the world.\n \"\"\"\n # Keeps track of squares in the world\n self.squares = {}\n\n # Teams\n self.teams = teams.TEAMS\n\n self.max_generations = max_generations or FLAGS.max_generations\n self.world_width = world_width or FLAGS.world_width\n self.world_height = world_height or FLAGS.world_height\n self.square_width = square_width or FLAGS.square_width\n random_events = random_events or FLAGS.random_events\n # max squares in one line/row\n self.max_squares = self.world_width / self.square_width\n\n # drawing surface\n self.world = world.World(self.world_width, self.world_height,\n self.square_width, world_rules, self.squares,\n black_white=FLAGS.black_white,\n random_events = random_events,\n workers=FLAGS.workers)\n\n def AddSquare(self, position, color=Colors.black, overwrite=False,\n team=None):\n \"\"\"Adds a new square.\n\n Args:\n position: (tuple) (top, left)\n overwrite: (bool) If True, overwrites existing square\n team: (teams.Team) team to join.\n \"\"\"\n if position[0] < 0 or position[0] >= self.max_squares:\n return\n\n if position[1] < 0 or position[1] >= self.max_squares:\n return\n\n if team is None:\n team = random.choice(teams.TEAMS.values())\n\n if not position in self.squares or overwrite:\n self.squares[position] = Square(position=position, color=color, team=team)\n\n def AddNeighborsToList(self, square):\n \"\"\"Adds a square's neighbors to the self.squares list.\n\n Args:\n square: (Square) square object\n \"\"\"\n for pos in [square.above, square.below, square.right, square.left,\n square.upperleft, square.upperright, square.lowerleft,\n square.lowerright]:\n self.AddSquare(pos, color=Colors.white)\n\n def DisplayGeneration(self):\n \"\"\"Draws current state of the world.\"\"\"\n for top, left in sorted(self.squares.iterkeys()):\n square = self.squares[(top, left)]\n\n if square.color == square.color_new == Colors.white:\n # two generations white, remove from list\n del self.squares[square.position]\n\n if square.color == Colors.white and square.color_new == Colors.black:\n self.AddNeighborsToList(square)\n\n if square.color == Colors.black and square.color_new == Colors.black:\n self.AddNeighborsToList(square)\n\n if square.color == Colors.black and square.color_new == Colors.white:\n self.AddNeighborsToList(square)\n\n # update with next generation values\n square.UpdateNextGenValues()\n\n self.world.DrawSquare(top*self.world.square_width,\n left*self.world.square_width,\n square.color, square.tint)\n self.world.Update()\n\n def NextGeneration(self):\n \"\"\"Generates next generation.\"\"\"\n self.world.NextGeneration()\n\n def CreateWorld(self):\n \"\"\"Creates drawing surface.\"\"\"\n self.world.Initialize()\n\n def HandleNonGridClick(self, positions):\n \"\"\"Handles non-grid click.\n\n Args:\n position: (tuple) mousex, mousey pixel.\n \"\"\"\n pass\n\n def ToggleSquare(self, position):\n \"\"\"Turns a square on (black) or off (white) based on mouse click.\n\n Args:\n position: (tuple) mousex, mousey pixel.\n \"\"\"\n mousex, mousey = position\n # round down both to nearest 10. Divide by 10, take int part, * 10.\n x = round(mousex / self.world.square_width)\n y = round(mousey / self.world.square_width)\n\n if mousex > self.world_width or mousey > self.world_height:\n self.HandleNonGridClick(position)\n return\n\n if (x, y) not in self.squares:\n # create new black square\n self.AddSquare((x,y), Colors.black, overwrite=True)\n else:\n # square exists\n square = self.squares[(x, y)]\n if square.color == Colors.black:\n square.color_new = Colors.white\n square.tint = Colors.custom(0, 0, 0)\n square.tint_new = None\n else:\n square.color = Colors.black\n\n self.AddNeighborsToList(self.squares[x,y])\n\n def Run(self):\n \"\"\"Runs game.\n\n Args:\n generations: (int) run for this many generations.\n \"\"\"\n #self.DisplayGeneration()\n generations = 0\n msg = \"\"\n\n while generations < self.max_generations:\n for event in pygame.event.get():\n if event.type == QUIT:\n pygame.quit()\n sys.exit()\n elif event.type == MOUSEBUTTONUP:\n logging.info(\"Mouse clicked on: %s\", (event.pos,))\n self.ToggleSquare(event.pos)\n elif event.type == KEYDOWN:\n logging.info(\"Key '%s' pressed.\", event.unicode)\n\n # Set message\n self.world.SetMessage(\"Gen = %s\" % generations)\n # displays current generation\n self.DisplayGeneration()\n # Changes squares to next generation values\n self.NextGeneration()\n # Pause\n self.world.fps_clock.tick(FLAGS.fps)\n generations += 1\n\n # print \"Total interesting squares: %s\" % len(self.squares)\n\n def ManualPosition(self):\n \"\"\"Allows user to set manual position. <enter> when finsihed.\"\"\"\n finished = False\n while not finished:\n for event in pygame.event.get():\n if event.type == MOUSEBUTTONUP:\n logging.info(\"Mouse clicked on: %s\", (event.pos,))\n self.ToggleSquare(event.pos)\n self.DisplayGeneration()\n elif event.type == KEYDOWN:\n if event.key in [K_KP_ENTER, K_RETURN]:\n finished = True\n\n\ndef Setup(argv):\n \"\"\"Pre-game setup.\"\"\"\n if argv is None:\n argv = sys.argv\n try:\n argv = FLAGS(argv) # parse flags\n except gflags.FlagsError, e:\n print '%s\\\\nUsage: %s ARGS\\\\n%s' % (e, sys.argv[0], FLAGS)\n sys.exit(1)\n\n myformat = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'\n logging.basicConfig(level=logging.DEBUG, format=myformat)\n\n\ndef SetInitialSquares(game):\n \"\"\"Sets initial game squares.\"\"\"\n if FLAGS.manual:\n game.ManualPosition()\n elif FLAGS.random_start:\n SetRandomSquares(game)\n else:\n initial = [((9, 13), Colors.black, game.teams[\"red\"]),\n ((9, 14), Colors.black, game.teams[\"red\"]),\n ((9, 15), Colors.black, game.teams[\"red\"]),\n ((8, 15), Colors.black, game.teams[\"red\"]),\n ((7, 15), Colors.black, game.teams[\"red\"]),\n ((9, 16), Colors.black, game.teams[\"red\"]),\n ((8, 16), Colors.black, game.teams[\"red\"]),\n ((7, 13), Colors.black, game.teams[\"red\"]),\n ((6, 13), Colors.black, game.teams[\"red\"]),\n ((5, 13), Colors.black, game.teams[\"red\"]),\n ((8, 10), Colors.black, game.teams[\"red\"]),\n ((9, 10), Colors.black, game.teams[\"red\"]),\n ((10, 15), Colors.black, game.teams[\"red\"]),\n ((10, 14), Colors.black, game.teams[\"red\"]),\n ((10, 13), Colors.black, game.teams[\"red\"]),\n ((11, 10), Colors.black, game.teams[\"red\"]),\n ((8, 14), Colors.black, game.teams[\"red\"]),\n ((12, 10), Colors.black, game.teams[\"red\"]),\n ((12, 9), Colors.black, game.teams[\"red\"]),\n ((13, 9), Colors.black, game.teams[\"red\"]),\n ((50, 13), Colors.black, game.teams[\"blue\"]),\n ((50, 14), Colors.black, game.teams[\"blue\"]),\n ((50, 15), Colors.black, game.teams[\"blue\"]),\n ((49, 15), Colors.black, game.teams[\"blue\"]),\n ((48, 15), Colors.black, game.teams[\"blue\"]),\n ((50, 16), Colors.black, game.teams[\"blue\"]),\n ((49, 16), Colors.black, game.teams[\"blue\"]),\n ((48, 13), Colors.black, game.teams[\"blue\"]),\n ((47, 13), Colors.black, game.teams[\"blue\"]),\n ((46, 13), Colors.black, game.teams[\"blue\"]),\n ((49, 10), Colors.black, game.teams[\"blue\"]),\n ((50, 10), Colors.black, game.teams[\"blue\"]),\n ((51, 15), Colors.black, game.teams[\"blue\"]),\n ((51, 14), Colors.black, game.teams[\"blue\"]),\n ((51, 13), Colors.black, game.teams[\"blue\"]),\n ((52, 10), Colors.black, game.teams[\"blue\"]),\n ((49, 14), Colors.black, game.teams[\"blue\"]),\n ((53, 10), Colors.black, game.teams[\"blue\"]),\n ((53, 9), Colors.black, game.teams[\"blue\"]),\n ((54, 9), Colors.black, game.teams[\"blue\"]),\n ]\n\n for index, color, team in initial:\n game.AddSquare(index, color, overwrite=True, team=team)\n game.AddNeighborsToList(game.squares[index])\n\n\ndef SetRandomSquares(game, black_white=True):\n \"\"\"Sets random squares in the game.\"\"\"\n max_squares = FLAGS.world_width / FLAGS.square_width\n\n for x in xrange(0, max_squares):\n for y in xrange(0, max_squares):\n color = random.choice(Colors.all())\n\n if color != Colors.white:\n game.AddSquare((x, y), color, overwrite=True)\n game.AddNeighborsToList(game.squares[(x,y)])\n\n\ndef main(argv=None):\n \"\"\"Main, run me.\"\"\"\n Setup(argv)\n\n rules = getattr(world_rules, str(FLAGS.rules))\n game = Game(rules)\n game.CreateWorld()\n\n SetInitialSquares(game)\n\n game.Run()\n raw_input(\"Hit <enter> to exit...\")\n\n\nif __name__ == \"__main__\":\n main()\n"},{"alpha_fraction":0.6743420958518982,"alphanum_fraction":0.6743420958518982,"avg_line_length":18.0625,"blob_id":"3f296740f14af367283b9a70689770f737143959","content_id":"bb8c1842f2e10f93294449638c9fbcd8e5736fd8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":304,"license_type":"no_license","max_line_length":70,"num_lines":16,"path":"/src/profile/examine.py","repo_name":"DanTulovsky/game","src_encoding":"UTF-8","text":"#!/usr/local/bin/python\n\nimport gflags\nimport pstats\nimport sys\n\nFLAGS = gflags.FLAGS\n\ngflags.DEFINE_string(\"file\", None, \"File that contains profile info.\",\n short_name=\"-f\")\n\nargv = FLAGS(sys.argv)\n\np = pstats.Stats(FLAGS.file)\n\np.strip_dirs().sort_stats(\"cumulative\").print_stats()"},{"alpha_fraction":0.6099432110786438,"alphanum_fraction":0.6159090995788574,"avg_line_length":27.047809600830078,"blob_id":"5c552d9cee53ad52205efce66f8797a8f15b1e59","content_id":"0fa4a698c41cb4dee4ad3b29aea23b260da48731","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":7040,"license_type":"no_license","max_line_length":86,"num_lines":251,"path":"/src/world.py","repo_name":"DanTulovsky/game","src_encoding":"UTF-8","text":"#!/usr/local/bin/python\n# -*- coding: utf-8 -*-\n\n\"\"\"pygame helper.\"\"\"\n\nfrom colors import Colors\n\nimport gflags\nimport pygame\nimport Queue\nimport sys\nimport threading\n\nfrom pygame.locals import *\n\nfrom memoized import *\nimport world_rules\n\nFLAGS = gflags.FLAGS\n\nBACKGROUND = Colors.white()\n\n\nclass Error(Exception):\n \"\"\"General error.\"\"\"\n\n\nclass NoNeighbor(Error):\n \"\"\"Raised if square has no neighbor in the indicated direction.\"\"\"\n\n\nclass OutsideWorld(Error):\n \"\"\"Raised if neighbor would be outside the known world.\"\"\"\n\n\nclass World(object):\n \"\"\"The world (grid). (0,0) is top left. Should be square.\"\"\"\n\n def __init__(self, width, height, square_width, rules, squares,\n black_white=False, random_events=False, workers=10):\n \"\"\"Init.\n\n Args:\n width: (int) width of the world in pixels.\n height: (int) height of the world in pixels.\n square_width: (int) width/height of citizen squares\n rules: (world_rules.WorldRules) world rules, function pointer\n squares: (dict) dict of Square objects. Current state.\n \"\"\"\n pygame.init()\n self.width = width\n self.height = height\n self.square_width = square_width\n self.msg_width = 100\n self.black_white = black_white\n self.rules = rules()\n self.squares = squares\n self.random_events = random_events\n # worker queue\n #self.q = Queue.Queue()\n #self.q = multiprocessing.JoinableQueue()\n #self._StartWorkers(workers)\n\n def Initialize(self):\n self.fps_clock = pygame.time.Clock()\n self.surface = pygame.display.set_mode((self.width + self.msg_width, self.height))\n self.fontObj = pygame.font.Font('freesansbold.ttf', 14)\n\n # set background\n self.Clear()\n\n # queue worker for processing next_gen data\n def Worker(self):\n while True:\n func, args = self.q.get()\n func(*args)\n self.q.task_done()\n\n def NextGeneration(self):\n \"\"\"Moves world to next generation.\"\"\"\n# for square_index, square in self.squares.iteritems():\n# # Put each next_gen square in a worker thread\n# self.q.put((self.NextGenSquare, [square_index]))\n#\n# # wait for all threads to finish work\n# self.q.join()\n\n for square_index in self.squares.iterkeys():\n self.NextGenSquare(square_index)\n\n # reset memoized cache\n #Memoized.reset()\n\n def NextGenSquare(self, square_index):\n \"\"\"Sets the square's nextgen state.\n\n Args:\n square_index: (int) square index in world\n \"\"\"\n square = self.squares[square_index]\n neighbors = self._NeighborCount(square)\n self.rules.NextGen(square, self.random_events, neighbors)\n\n\n def SetMessage(self, msg=\"Game\"):\n self.msgSurfaceObj = self.fontObj.render(msg, False, Colors.blue())\n self.msgRectobj = self.msgSurfaceObj.get_rect()\n self.msgRectobj.topleft = (self.width + 4, 0)\n\n # Clear previous msg\n self.surface.fill(Colors.white(), self.msgRectobj)\n\n self.surface.blit(self.msgSurfaceObj, self.msgRectobj)\n\n def DrawSquare(self, top, left, color, tint=None):\n # Draw inside grid.\n square_color = color() + tint\n pygame.draw.rect(\n self.surface, square_color, (top+1, left+1, self.square_width - 1,\n self.square_width - 1))\n\n def DrawGrid(self, color=Colors.green()):\n \"\"\"Draws grid.\"\"\"\n self._DrawVerticalGrid(color=color)\n self._DrawHorizontalGrid(color=color)\n\n def Clear(self):\n \"\"\"Clears surface.\"\"\"\n self.surface.fill(BACKGROUND)\n self.DrawGrid()\n self.Update()\n\n def Update(self):\n \"\"\"Redraws surface.\"\"\"\n pygame.display.update()\n\n def InWorld(self, position):\n \"\"\"Returns True if given position is in the World.\n\n Args:\n position: (tuple) (top, left) pixel.\n \"\"\"\n top, left = position[0], position[1]\n if (top < 0 or\n left < 0 or\n top + self.square_width > self.height or\n left + self.square_width > self.width):\n return False\n else:\n return True\n\n #@Memoized\n def _NeighborColor(self, square, position):\n \"\"\"Returns the color of the neighbor in position.\n\n Args:\n square: (Square) Object\n position: (string) Valid position from Square class (RIGHT, LEFT, etc)\n\n Returns:\n color, team: (Square.COLOR, teams.Team) color and team of neighbor.\n\n Raises:\n NoNeighbor: If there is no neighbor\n OutsideWorld: If neighbor would be outside the known world.\n \"\"\"\n neighbor_position = getattr(square, position)\n\n if neighbor_position in self.squares:\n return (self.squares[neighbor_position].color,\n self.squares[neighbor_position].team)\n else:\n raise NoNeighbor(\"No neighbor at %s\" % (neighbor_position,))\n\n def _NeighborCount(self, square):\n \"\"\"Returns the count and color of a square's neighbors.\n\n Args:\n square: (Square) Object\n\n Returns:\n neighbors: (dict) {\n Color.white: N, # total\n \"friends\": H,\n \"enemies\": J,\n \"total_neighbors\": L, # non-white neighbors\n \"influence\": Team # the team with the most influence\n # simply with the most squares\n # surrounding this one\n }\n \"\"\"\n neighbors = {\"total_neighbors\": 0, \"friends\": 0, \"enemies\": 0}\n\n\n if square.position == (46, 14):\n pass\n # initialize all colors to 0\n for color in Colors.all():\n neighbors[color] = 0\n\n neighbor_team_count = {}\n\n for pos in (world_rules.POSITIONS):\n try:\n neighbor_color, neighbor_team = self._NeighborColor(square, pos)\n except (OutsideWorld, NoNeighbor):\n continue\n\n neighbors[neighbor_color] += 1\n if neighbor_color != Colors.white:\n neighbors[\"total_neighbors\"] += 1\n\n neighbor_team_count.setdefault(neighbor_team, 0)\n neighbor_team_count[neighbor_team] += 1\n\n if neighbor_team == square.team:\n neighbors[\"friends\"] += 1\n else:\n neighbors[\"enemies\"] += 1\n\n influence = None\n max = 0\n for team, count in neighbor_team_count.iteritems():\n if count > max:\n max = count\n influence = team\n\n\n neighbors[\"influence\"] = influence\n\n return neighbors\n\n def _DrawVerticalGrid(self, color):\n \"\"\"Draws vertical grid.\"\"\"\n for x in xrange(0, self.width + self.square_width, self.square_width):\n pygame.draw.line(self.surface, color, (x, 0),\n (x, self.height), 1)\n\n def _DrawHorizontalGrid(self, color):\n \"\"\"Draws horizontal grid.\"\"\"\n for y in xrange(0, self.height + self.square_width, self.square_width):\n pygame.draw.line(self.surface, color, (0, y),\n (self.width, y), 1)\n\n def _StartWorkers(self, num_worker_threads):\n \"\"\"Starts queue workers.\"\"\"\n for i in range(num_worker_threads):\n t = threading.Thread(target=self.Worker)\n #t = multiprocessing.Process(target=self.Worker)\n t.daemon = True\n t.start()\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5727847814559937,\n \"alphanum_fraction\": 0.577531635761261,\n \"avg_line_length\": 16.55555534362793,\n \"blob_id\": \"49a5d8fafa4cf783b894aa8d6e73987b4f585659\",\n \"content_id\": \"2f53021f1cd8695737b40f6154737ef91f3bb710\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 632,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 36,\n \"path\": \"/src/teams.py\",\n \"repo_name\": \"DanTulovsky/game\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Teams.\\n\\nfrom colors import *\\n\\n\\n\\n\\nclass Team(object):\\n\\n def __init__(self, color, strength=0):\\n \\\"\\\"\\\"Init.\\n\\n Args:\\n color: (colors.Color) Team color\\n \\\"\\\"\\\"\\n self.color = color\\n self.members = set()\\n # as integer; 0 is lowest\\n self.strength = strength\\n\\n def Join(self, square):\\n \\\"\\\"\\\"Join this team.\\\"\\\"\\\"\\n self.members.add(square)\\n\\n def Leave(self, square):\\n \\\"\\\"\\\"Leave the team.\\\"\\\"\\\"\\n try:\\n self.members.remove(square)\\n except KeyError:\\n # already removed\\n pass\\n\\n\\nTEAMS = {\\\"red\\\": Team(Colors.red),\\n \\\"blue\\\": Team(Colors.blue, strength=1),\\n \\\"green\\\": Team(Colors.green)}\\n\"\n },\n {\n \"alpha_fraction\": 0.6191161274909973,\n \"alphanum_fraction\": 0.6320657730102539,\n \"avg_line_length\": 24.87765884399414,\n \"blob_id\": \"4b646a4d6e5fcc6b6a5bd3230823cc69abc673c5\",\n \"content_id\": \"39abee76541bdaed0d689fd01256f41ec73abc1b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4865,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 188,\n \"path\": \"/src/square.py\",\n \"repo_name\": \"DanTulovsky/game\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# This is a citizen of the world.\\n\\nimport threading\\n\\nfrom colors import *\\nimport random\\nimport teams\\n\\n\\nclass Error(Exception):\\n \\\"\\\"\\\"General error.\\\"\\\"\\\"\\n\\n\\nclass TeamError(Error):\\n \\\"\\\"\\\"Raised on invalids team.\\\"\\\"\\\"\\n\\n\\nclass Square(object):\\n \\\"\\\"\\\"One square.\\\"\\\"\\\"\\n\\n @property\\n def above(self):\\n \\\"\\\"\\\"Returns coordinates of square above this one.\\\"\\\"\\\"\\n return (self.position[0], self.position[1] - 1)\\n\\n @property\\n def below(self):\\n \\\"\\\"\\\"Returns coordinates of square below this one.\\\"\\\"\\\"\\n return (self.position[0], self.position[1] + 1)\\n\\n @property\\n def right(self):\\n \\\"\\\"\\\"Returns coordinates of square to the right of this one.\\\"\\\"\\\"\\n return (self.position[0] + 1, self.position[1])\\n\\n @property\\n def left(self):\\n \\\"\\\"\\\"Returns coordinates of square to the left of this one.\\\"\\\"\\\"\\n return (self.position[0] - 1, self.position[1])\\n\\n @property\\n def upperleft(self):\\n \\\"\\\"\\\"Returns coordinates of square to the upper left of this one.\\\"\\\"\\\"\\n return (self.position[0] - 1, self.position[1] - 1)\\n\\n @property\\n def upperright(self):\\n \\\"\\\"\\\"Returns coordinates of square to the upper right of this one.\\\"\\\"\\\"\\n return (self.position[0] + 1, self.position[1] - 1)\\n\\n @property\\n def lowerleft(self):\\n \\\"\\\"\\\"Returns coordinates of square to the lower left of this one.\\\"\\\"\\\"\\n return (self.position[0] - 1, self.position[1] + 1)\\n\\n @property\\n def lowerright(self):\\n \\\"\\\"\\\"Returns coordinates of square to the lower right of this one.\\\"\\\"\\\"\\n return (self.position[0] + 1, self.position[1] + 1)\\n\\n @property\\n def color(self):\\n with self._data_lock:\\n return self._color\\n\\n @color.setter\\n def color(self, value):\\n with self._data_lock:\\n self._color = value\\n\\n def __init__(self, color=Colors.white, position=(0,0), team=None):\\n \\\"\\\"\\\"Initial state of a square.\\n\\n The color is either Colors.black or green. The position\\n is (top, left) tuple, but counting squares, not pixels.\\n\\n So position (1, 1) is actually (10, 10) in pixels. (1 * square_width)\\n\\n Args:\\n color: (string) initial color of the square; b/w\\n positions: ((int, int) position in the world (not px)\\n team: (teams.Team) the team this square belongs to\\n \\\"\\\"\\\"\\n self._color = color\\n self.tint = Colors.custom(0, 0, 0)\\n self.position = position\\n self.age = 0 # number of generations this has been alive.\\n self._data_lock = threading.Lock()\\n self.team = team\\n self.tint_increase = 2 # how quickly the colors change\\n\\n # next generation\\n self.color_new = None\\n self.tint_new = None\\n self.age_new = None\\n self.killed = False\\n\\n # join team\\n if self.team is None:\\n raise TeamError(\\\"Team must be specified.\\\")\\n self.team.Join(self)\\n\\n # tint_int value based on the team\\n self._tint_int = self._GetTeamTint()\\n\\n def FlipColor(self):\\n \\\"\\\"\\\"Flips the color of a square.\\\"\\\"\\\"\\n if self.color in Colors.alive():\\n self.color_new = Colors.white\\n else:\\n self.color_new = Colors.black\\n\\n def HappyBirthday(self):\\n \\\"\\\"\\\"Adds one to the age of the Square.\\\"\\\"\\\"\\n self.tint_new = self.tint\\n self.age_new = self.age\\n self.color_new = self.color\\n self.age_new += 1\\n\\n # turn a deeper shade based on the team\\n if self.tint_new[self._tint_int] + self.tint_increase < 256:\\n self.tint_new[self._tint_int] += self.tint_increase\\n else:\\n tint = 255\\n\\n def Kill(self):\\n \\\"\\\"\\\"Turns square white.\\\"\\\"\\\"\\n self.tint_new = self.tint\\n self.color_new = Colors.white\\n self.tint_new = Colors.custom(0, 0, 0)\\n self.age_new = 0\\n self.killed = True\\n\\n if self.team:\\n self.team.Leave(self)\\n\\n def ComeAlive(self, influence_team=None):\\n \\\"\\\"\\\"Makes white square come alive -> black.\\n\\n Args:\\n influence_team: (Team) team with the most influence on this square\\n \\\"\\\"\\\"\\n self.tint_new = self.tint\\n self.age_new = 0\\n self.color_new = Colors.black\\n self.tint_new = Colors.custom(0, 0, 0)\\n\\n # join team based on neighbors\\n if influence_team is not None:\\n self.team = influence_team\\n else:\\n self.team = random.choice(teams.TEAMS.values())\\n print \\\"Joining random team...\\\"\\n self.team.Join(self)\\n self._tint_int = self._GetTeamTint()\\n\\n def UpdateNextGenValues(self):\\n \\\"\\\"\\\"Cycles the square to the next generation.\\\"\\\"\\\"\\n if self.color_new:\\n self.color = self.color_new\\n self.color_new = None\\n\\n if self.age_new:\\n self.age = self.age_new\\n self.age_new = None\\n\\n if self.tint_new:\\n self.tint = self.tint_new\\n self.tint_new = None\\n\\n if self.killed:\\n self.team = None\\n self.killed = False\\n\\n def _GetTeamTint(self):\\n \\\"\\\"\\\"Returns the correct tint index to change based on team color.\\n\\n Returns:\\n tint: (int) 0 = r; 2 = g; 1 = b\\n \\\"\\\"\\\"\\n if self.team.color == Colors.red:\\n return 0\\n\\n if self.team.color == Colors.blue:\\n return 2\\n\\n if self.team.color == Colors.green:\\n return 1\\n\"\n },\n {\n \"alpha_fraction\": 0.6332256197929382,\n \"alphanum_fraction\": 0.6445332169532776,\n \"avg_line_length\": 29.548051834106445,\n \"blob_id\": \"89149cd77fc2ea8a559e8e6e9d04b4867ed85664\",\n \"content_id\": \"3bdfd8b1772bd3aeff25d21b0a7cfc178bb89ace\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 11762,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 385,\n \"path\": \"/src/world_rules.py\",\n \"repo_name\": \"DanTulovsky/game\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nCreated on Mar 7, 2013\\n\\n@author: dtulovsky\\n\\\"\\\"\\\"\\n\\nfrom colors import Colors\\nfrom copy import *\\nimport gflags\\nimport logging\\nimport random\\n\\n\\nFLAGS = gflags.FLAGS\\n\\n# References to neighbors\\nRIGHT = \\\"right\\\"\\nLEFT = \\\"left\\\"\\nABOVE = \\\"above\\\"\\nBELOW = \\\"below\\\"\\nUPPERLEFT = \\\"upperleft\\\"\\nUPPERRIGHT = \\\"upperright\\\"\\nLOWERLEFT = \\\"lowerleft\\\"\\nLOWERRIGHT = \\\"lowerright\\\"\\n\\nPOSITIONS = [RIGHT, LEFT, ABOVE, BELOW, UPPERLEFT, UPPERRIGHT, LOWERLEFT,\\n LOWERRIGHT]\\n\\n\\nclass Error(Exception):\\n \\\"\\\"\\\"General Exception.\\\"\\\"\\\"\\n\\n\\nclass WorldRules(object):\\n \\\"\\\"\\\"Defines the rules of the world. Inherit this to extend.\\\"\\\"\\\"\\n\\n def NextGen(self, square, random_events, neighbors):\\n \\\"\\\"\\\"Returns a copy of the square for next generation.\\n\\n Args:\\n square: (Square) square object\\n squares: (dict) Squares in the world.\\n next_gen: (dict) all square objects for next generation\\n index: (int) index of current square in squoares\\n random_events: (bool) If True, allow random events (if any)\\n\\n Returns:\\n square: (Square) a copy of the square object with new paramters\\n \\\"\\\"\\\"\\n raise NotImplemented(\\\"Don't use this class directly.\\\")\\n\\n def RandomEvents(self, squares):\\n \\\"\\\"\\\"Introduces random events.\\\"\\\"\\\"\\n raise NotImplemented(\\\"Override this function if you want to use it.\\\")\\n\\n\\nclass Wolfam222(WorldRules):\\n \\\"\\\"\\\"Wolfram222.\\\"\\\"\\\"\\n\\n color_hash = {(Colors.black, Colors.black, Colors.black): Colors.black,\\n (Colors.black, Colors.black, Colors.white): Colors.black,\\n (Colors.black, Colors.white, Colors.black): Colors.white,\\n (Colors.black, Colors.white, Colors.white): Colors.black,\\n (Colors.white, Colors.black, Colors.black): Colors.black,\\n (Colors.white, Colors.black, Colors.white): Colors.black,\\n (Colors.white, Colors.white, Colors.black): Colors.black,\\n (Colors.white, Colors.white, Colors.white): Colors.white}\\n\\n def NextGen(self, square, random_events, neighbors):\\n \\\"\\\"\\\"Given a square, sets its state for the next generation.\\n\\n * left neighbor self right neighbor => new self\\n * b b b => b\\n * b b w => b\\n * b w b => w\\n * b w w => b\\n * w b b => b\\n * w b w => b\\n * w w b => b\\n * w w w => w\\n \\\"\\\"\\\"\\n # copy the square so we don't mix generations\\n new_square = copy(square)\\n\\n try:\\n lnc = self._NeighborColor(square, LEFT, squares)\\n except (OutsideWorld, NoNeighbor) as e:\\n lnc = Colors.white\\n\\n try:\\n rnc = self._NeighborColor(square, RIGHT, squares)\\n except (OutsideWorld, NoNeighbor) as e:\\n rnc = Colors.white\\n\\n try:\\n new_square.color = Wolfam222.color_hash[(lnc, square.color, rnc)]\\n except KeyError, e:\\n logging.error(\\\"Wolfram222 Combination missing (this only works with \\\"\\n \\\"black and white.\\\")\\n\\n next_gen[index] = new_square\\n\\nclass FlipWorld(WorldRules):\\n \\\"\\\"\\\"Flip existing squares only.\\\"\\\"\\\"\\n\\n def NextGen(self, square, random_events, neighbors):\\n \\\"\\\"\\\"Given a square, sets its state for the next generation.\\n\\n * Flip the color of each existing square.\\n \\\"\\\"\\\"\\n new_square = copy(square)\\n new_square.FlipColor()\\n next_gen[index] = new_square\\n\\n\\nclass FlipWorldNeighbor(WorldRules):\\n \\\"\\\"\\\"Flip existing squares only.\\\"\\\"\\\"\\n\\n def NextGen(self, square, random_events, neighbors):\\n \\\"\\\"\\\"Given a square, sets its state for the next generation.\\n\\n * Flips if the neighbors on left and right sides are the same.\\n * If there are no neighbors, don't change.\\n \\\"\\\"\\\"\\n new_square = copy(square)\\n try:\\n lnc = self._NeighborColor(square, LEFT, squares)\\n except (OutsideWorld, NoNeighbor) as e:\\n # Either no neighbor or neighbor would be out of this world\\n return new_square\\n\\n if lnc == rnc:\\n new_square.FlipColor()\\n\\n next_gen[index] = new_square\\n\\n\\nclass LifeWorld(WorldRules):\\n \\\"\\\"\\\"Life world. Game of life, original rules.\\\"\\\"\\\"\\n\\n def NextGen(self, square, random_events, neighbors):\\n \\\"\\\"\\\"Given a square, sets its state for the next generation.\\n\\n Supports only black/white squares.\\n\\n * If black square has < 2 black neighbors, turns white.\\n * If black square has 2 or 3 black neighbors, remains black.\\n * If black square has > 3 neighbors, turns white.\\n * If white square has 3 neighbors, turns black.\\n \\\"\\\"\\\"\\n if square.color == Colors.black:\\n if neighbors[\\\"total_neighbors\\\"] < 2:\\n square.color_new = Colors.white\\n\\n if neighbors[\\\"total_neighbors\\\"] in [2, 3]:\\n square.color_new = Colors.black\\n\\n if neighbors[\\\"total_neighbors\\\"] > 3:\\n square.color_new = Colors.white\\n\\n if square.color == Colors.white:\\n if neighbors[\\\"total_neighbors\\\"] == 3:\\n square.color_new = Colors.black\\n elif neighbors[\\\"total_neighbors\\\"] == 0:\\n square.color_new = Colors.white\\n\\nclass LifeWorldColorRandom(WorldRules):\\n \\\"\\\"\\\"Life world. Custom.\\\"\\\"\\\"\\n\\n def RandomEvents(self, square):\\n \\\"\\\"\\\"Random event for one square.\\\"\\\"\\\"\\n MAX_RANDOM = 10000\\n\\n # % chance a square will flip colors\\n if random.randrange(0, MAX_RANDOM, 1) == 1:\\n logging.info(\\\"Random event: flipping square %s.\\\", square.position)\\n square.FlipColor()\\n return square\\n\\n def NextGen(self, square, random_events, neighbors):\\n \\\"\\\"\\\"Given a square, sets its state for the next generation.\\n\\n * If colored square has < 2 black neighbors, turns white.\\n * If colored square has 2 or 3 black neighbors, remains colored (same).\\n * If colored square has > 3 neighbors, turns white.\\n * If white square has 3 neighbors, turns colored (random).\\n \\\"\\\"\\\"\\n\\n if square.color != Colors.white: # is alive\\n if neighbors[\\\"total_neighbors\\\"] < 2:\\n square.color_new = Colors.white\\n\\n if neighbors[\\\"total_neighbors\\\"] in [2, 3]:\\n square.color_new = square.color\\n\\n if neighbors[\\\"total_neighbors\\\"] > 3:\\n square.color_new = Colors.white\\n\\n if square.color == Colors.white:\\n if neighbors[\\\"total_neighbors\\\"] == 3:\\n square.color_new = random.choice(Colors.alive())\\n elif neighbors[\\\"total_neighbors\\\"] == 0:\\n square.color_new = Colors.white\\n\\n if random_events:\\n square = self.RandomEvents(square)\\n\\n\\nclass LifeCustomWorld(WorldRules):\\n \\\"\\\"\\\"Life world. Custom. Includes other attributes.\\\"\\\"\\\"\\n\\n def __init__(self):\\n super(LifeCustomWorld, self).__init__()\\n # kill if less then this number of neighbors\\n self.kill_lonely_limit = 2\\n # kill if more than this number of neighbors\\n self.kill_crowded_limit = 3\\n # come alive if this number of neighbors\\n self.come_alive_neighbors = 3\\n\\n def RandomEvents(self, square):\\n \\\"\\\"\\\"Random event for one square.\\\"\\\"\\\"\\n MAX_RANDOM = 10000\\n\\n # % chance a square will flip colors\\n if random.randrange(0, MAX_RANDOM, 1) == 1:\\n logging.info(\\\"Random event: flipping square %s.\\\", square.position)\\n square.FlipColor()\\n\\n def NextGen(self, square, random_events, neighbors):\\n \\\"\\\"\\\"Given a square, sets its state for the next generation.\\n\\n * If colored square has < 2 black neighbors, turns white.\\n * If colored square has 2 or 3 black neighbors, remains colored (same).\\n * If colored square has > 3 neighbors, turns white.\\n * If white square has 3 neighbors, turns colored (random).\\n \\\"\\\"\\\"\\n killed = False\\n kill_lonely_limit = self.kill_lonely_limit\\n kill_crowded_limit = self.kill_crowded_limit\\n come_alive_neighbors = self.come_alive_neighbors\\n\\n # with age, comes strength\\n if square.age > 5:\\n kill_lonely_limit = kill_lonely_limit - 1\\n\\n if square.age > 25:\\n kill_crowded_limit = kill_crowded_limit + 1\\n\\n# if square.age > 60:\\n# kill_lonely_limit = kill_lonely_limit - 1\\n#\\n# if square.age > 105:\\n# kill_crowded_limit = kill_crowded_limit + 1\\n\\n # with deep age, comes weakness\\n# if square.age > 50:\\n# kill_lonely_limit = kill_lonely_limit\\n# kill_crowded_limit = kill_crowded_limit\\n#\\n# if square.age > 80:\\n# kill_lonely_limit = kill_lonely_limit + 1\\n# kill_crowded_limit = kill_crowded_limit - 1\\n#\\n# if square.age > 120:\\n# kill_lonely_limit = kill_lonely_limit + 1\\n# kill_crowded_limit = kill_crowded_limit - 1\\n#\\n# if square.age > 150:\\n# kill_lonely_limit = kill_lonely_limit + 1\\n# kill_crowded_limit = kill_crowded_limit - 1\\n\\n\\n if square.color != Colors.white: # is alive\\n if neighbors[\\\"total_neighbors\\\"] < kill_lonely_limit:\\n square.Kill()\\n killed = True\\n\\n if neighbors[\\\"total_neighbors\\\"] > kill_crowded_limit:\\n square.Kill()\\n killed = True\\n\\n if not killed:\\n # survived this generation!\\n square.HappyBirthday()\\n\\n if square.color == Colors.white:\\n if neighbors[\\\"total_neighbors\\\"] == come_alive_neighbors:\\n square.ComeAlive()\\n elif neighbors[\\\"total_neighbors\\\"] == 0:\\n # Removes uninteresting squares from the list\\n square.color_new = Colors.white\\n\\n if random_events:\\n self.RandomEvents(square)\\n\\nclass LifeCustomWorldFight(WorldRules):\\n \\\"\\\"\\\"Life world. Custom. Includes other attributes. Team fights.\\\"\\\"\\\"\\n\\n def __init__(self):\\n super(LifeCustomWorldFight, self).__init__()\\n # kill if less then this number of neighbors\\n self.kill_lonely_limit = 2\\n # how many friends around square kill it\\n self.kill_friend_crowded_limit = 6\\n # how many enemies around square kill it\\n self.kill_enemy_crowded = 2\\n # come alive if this number of neighbors\\n self.come_alive_neighbors = 2\\n\\n def RandomEvents(self, square):\\n \\\"\\\"\\\"Random event for one square.\\\"\\\"\\\"\\n MAX_RANDOM = 10000\\n\\n # % chance a square will flip colors\\n if random.randrange(0, MAX_RANDOM, 1) == 1:\\n logging.info(\\\"Random event: flipping square %s.\\\", square.position)\\n square.FlipColor()\\n\\n def NextGen(self, square, random_events, neighbors):\\n \\\"\\\"\\\"Given a square, sets its state for the next generation.\\\"\\\"\\\"\\n killed = False\\n kill_lonely_limit = self.kill_lonely_limit\\n kill_friend_crowded_limit = self.kill_friend_crowded_limit\\n kill_enemy_crowded = self.kill_enemy_crowded\\n come_alive_neighbors = self.come_alive_neighbors\\n\\n # with age, comes strength\\n #if square.age > 5:\\n # kill_lonely_limit = kill_lonely_limit - 1\\n\\n #if square.age > 25:\\n # kill_crowded_limit = kill_crowded_limit + 1\\n\\n# if square.age > 60:\\n# kill_lonely_limit = kill_lonely_limit - 1\\n#\\n# if square.age > 105:\\n# kill_crowded_limit = kill_crowded_limit + 1\\n\\n # with deep age, comes weakness\\n# if square.age > 50:\\n# kill_lonely_limit = kill_lonely_limit\\n# kill_crowded_limit = kill_crowded_limit\\n#\\n# if square.age > 80:\\n# kill_lonely_limit = kill_lonely_limit + 1\\n# kill_crowded_limit = kill_crowded_limit - 1\\n#\\n# if square.age > 120:\\n# kill_lonely_limit = kill_lonely_limit + 1\\n# kill_crowded_limit = kill_crowded_limit - 1\\n#\\n# if square.age > 150:\\n# kill_lonely_limit = kill_lonely_limit + 1\\n# kill_crowded_limit = kill_crowded_limit - 1\\n\\n\\n if square.color != Colors.white: # is alive\\n if neighbors[\\\"total_neighbors\\\"] < kill_lonely_limit:\\n square.Kill()\\n killed = True\\n\\n if neighbors[\\\"friends\\\"] > kill_friend_crowded_limit:\\n square.Kill()\\n killed = True\\n\\n if neighbors[\\\"enemies\\\"] > kill_enemy_crowded:\\n square.Kill()\\n killed = True\\n\\n if not killed:\\n # survived this generation!\\n square.HappyBirthday()\\n else: # is dead\\n if neighbors[\\\"total_neighbors\\\"] == come_alive_neighbors:\\n if neighbors[\\\"influence\\\"] is None:\\n pass\\n square.ComeAlive(neighbors[\\\"influence\\\"])\\n elif neighbors[\\\"total_neighbors\\\"] == 0:\\n # Removes uninteresting squares from the list\\n square.color_new = Colors.white\\n\\n if random_events:\\n self.RandomEvents(square)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5811789035797119,\n \"alphanum_fraction\": 0.6866597533226013,\n \"avg_line_length\": 27.47058868408203,\n \"blob_id\": \"9d51e86c536d707884fd64e67f7b9a26534207c5\",\n \"content_id\": \"c796137c1bbf4d6d49ee1cce0192027112de1430\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 967,\n \"license_type\": \"no_license\",\n \"max_line_length\": 109,\n \"num_lines\": 34,\n \"path\": \"/src/pygame_test.py\",\n \"repo_name\": \"DanTulovsky/game\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#! /usr/local/bin/python\\n\\nimport pygame\\nimport sys\\nimport time\\n\\nfrom pygame.locals import *\\n\\npygame.init()\\n\\nfpsClock = pygame.time.Clock()\\nwindowSurfaceObj = pygame.display.set_mode((640, 480))\\n\\npygame.display.set_caption(\\\"Game...\\\")\\n\\nredColor = pygame.Color(255, 0, 0)\\ngreenColor = pygame.Color(0, 255, 0)\\nblueColor = pygame.Color(0, 0, 255)\\nwhiteColor = pygame.Color(255, 255, 255)\\n\\nwhile True:\\n windowSurfaceObj.fill(whiteColor)\\n \\n #pygame.draw.polygon(windowSurfaceObj, greenColor, ((146, 0), (291, 106), (236, 277), (56, 277), (0, 106)))\\n #pygame.draw.circle(windowSurfaceObj, blueColor, (300, 50), 20, 0)\\n #pygame.draw.ellipse(windowSurfaceObj, redColor, (300, 250, 40, 80), 1)\\n pygame.draw.rect(windowSurfaceObj, \\n redColor, (10, 10, 100, 100))\\n \\n #pygame.draw.line(windowSurfaceObj, blueColor, (60, 160), (120, 60), 4)\\n \\n #fpsClock.tick(30) # pause to run the loop at 30 frames per second\\n pygame.display.update()\\n time.sleep(300)\"\n },\n {\n \"alpha_fraction\": 0.6305577754974365,\n \"alphanum_fraction\": 0.6426839232444763,\n \"avg_line_length\": 17.477611541748047,\n \"blob_id\": \"25b1f3186825d092d02da4db6b87180fecf8eae7\",\n \"content_id\": \"13054f0082370a64bf82c806e625415f46099efd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1237,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 67,\n \"path\": \"/src/colors.py\",\n \"repo_name\": \"DanTulovsky/game\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nCreated on Mar 7, 2013\\n\\n@author: dtulovsky\\n\\\"\\\"\\\"\\n\\nimport gflags\\nimport pygame\\n\\nFLAGS = gflags.FLAGS\\n\\ngflags.DEFINE_bool(\\\"black_white\\\", False, \\\"Only black/white mode.\\\")\\n\\nWHITE = pygame.Color(\\\"white\\\")\\nBLACK = pygame.Color(\\\"black\\\")\\nGREEN = pygame.Color(\\\"green\\\")\\nRED = pygame.Color(\\\"red\\\")\\nBLUE = pygame.Color(\\\"blue\\\")\\nPINK = pygame.Color(255, 0 , 127)\\n\\n\\nclass Colors(object):\\n \\\"\\\"\\\"Colors Helper.\\\"\\\"\\\" \\n \\n @classmethod\\n def all(cls):\\n if FLAGS.black_white:\\n return [Colors.black, Colors.white]\\n else:\\n return [Colors.white, Colors.black, Colors.green, Colors.red, Colors.blue,\\n Colors.pink]\\n \\n @classmethod\\n def alive(cls):\\n \\\"\\\"\\\"Returns only alive colors. No white.\\\"\\\"\\\"\\n if FLAGS.black_white:\\n return [Colors.black]\\n else:\\n return [Colors.black, Colors.green, Colors.red, Colors.blue, Colors.pink]\\n \\n @classmethod\\n def white(cls):\\n return WHITE\\n\\n @classmethod\\n def black(cls):\\n return BLACK\\n\\n @classmethod\\n def green(cls):\\n return GREEN \\n\\n @classmethod\\n def red(cls):\\n return RED\\n\\n @classmethod\\n def blue(cls):\\n return BLUE\\n\\n @classmethod\\n def pink(cls):\\n return PINK\\n \\n @classmethod\\n def custom(cls, r, g, b, a=255):\\n return pygame.Color(r, g, b, a)\"\n },\n {\n \"alpha_fraction\": 0.5833257436752319,\n \"alphanum_fraction\": 0.6002179384231567,\n \"avg_line_length\": 32.67278289794922,\n \"blob_id\": \"00f0df2fc999dbdb5e4f97912b29fed50ec72561\",\n \"content_id\": \"71e25677b0487b0246fc96f640be0f19db826852\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 11011,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 327,\n \"path\": \"/src/game.py\",\n \"repo_name\": \"DanTulovsky/game\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/local/bin/python\\n# -*- coding: utf-8 -*-\\n\\nfrom copy import *\\nimport gflags\\nimport logging\\nimport random\\nimport sys\\nimport time\\n\\nfrom colors import *\\nimport random\\nimport teams\\nimport world\\nfrom pygame.locals import *\\nfrom square import *\\nimport world_rules\\n\\n\\nFLAGS = gflags.FLAGS\\ngflags.DEFINE_integer(\\\"max_generations\\\", 2000000, \\\"Generations to run.\\\")\\ngflags.DEFINE_integer(\\\"world_height\\\", 1200, \\\"World height in px.\\\")\\ngflags.DEFINE_integer(\\\"world_width\\\", 1200, \\\"World height in px.\\\")\\ngflags.DEFINE_integer(\\\"square_width\\\", 20, \\\"Citizen square width.\\\")\\ngflags.DEFINE_integer(\\\"fps\\\", 5, \\\"Frame per second (wait time between gens.\\\")\\ngflags.DEFINE_bool(\\\"random_events\\\", False, \\\"Allow random events.\\\")\\ngflags.DEFINE_string(\\\"rules\\\", None, \\\"World rules to use.\\\")\\ngflags.DEFINE_bool(\\\"random_start\\\", False, \\\"Random initial allocation.\\\")\\ngflags.DEFINE_bool(\\\"manual\\\", False, \\\"Allows manual layout of initial \\\"\\n \\\"position, disables random_start.\\\")\\ngflags.DEFINE_integer(\\\"workers\\\", 100, \\\"Worker threads.\\\")\\n\\n\\nclass Error(Exception):\\n \\\"\\\"\\\"General Exception.\\\"\\\"\\\"\\n\\n\\nclass Game(object):\\n \\\"\\\"\\\"Models generations of squares.\\n\\n Squares change color based on their own color and the color\\n of their neighbors. Each generation is simply a row of\\n squares.\\n\\n Empty space on either side is considered to be a Square.Colors.black square.\\n \\\"\\\"\\\"\\n\\n def __init__(self, world_rules, max_generations=None,\\n world_width=None, world_height=None,\\n square_width=None, random_events=None):\\n \\\"\\\"\\\"Init.\\n\\n Args:\\n world_rules: (WorldRules) Or derivative.\\n max_generations: (int) how many iterations to run throuhg\\n world_width: (int) pixel width of the world\\n world_height: (int) pixel height of the world.\\n \\\"\\\"\\\"\\n # Keeps track of squares in the world\\n self.squares = {}\\n\\n # Teams\\n self.teams = teams.TEAMS\\n\\n self.max_generations = max_generations or FLAGS.max_generations\\n self.world_width = world_width or FLAGS.world_width\\n self.world_height = world_height or FLAGS.world_height\\n self.square_width = square_width or FLAGS.square_width\\n random_events = random_events or FLAGS.random_events\\n # max squares in one line/row\\n self.max_squares = self.world_width / self.square_width\\n\\n # drawing surface\\n self.world = world.World(self.world_width, self.world_height,\\n self.square_width, world_rules, self.squares,\\n black_white=FLAGS.black_white,\\n random_events = random_events,\\n workers=FLAGS.workers)\\n\\n def AddSquare(self, position, color=Colors.black, overwrite=False,\\n team=None):\\n \\\"\\\"\\\"Adds a new square.\\n\\n Args:\\n position: (tuple) (top, left)\\n overwrite: (bool) If True, overwrites existing square\\n team: (teams.Team) team to join.\\n \\\"\\\"\\\"\\n if position[0] < 0 or position[0] >= self.max_squares:\\n return\\n\\n if position[1] < 0 or position[1] >= self.max_squares:\\n return\\n\\n if team is None:\\n team = random.choice(teams.TEAMS.values())\\n\\n if not position in self.squares or overwrite:\\n self.squares[position] = Square(position=position, color=color, team=team)\\n\\n def AddNeighborsToList(self, square):\\n \\\"\\\"\\\"Adds a square's neighbors to the self.squares list.\\n\\n Args:\\n square: (Square) square object\\n \\\"\\\"\\\"\\n for pos in [square.above, square.below, square.right, square.left,\\n square.upperleft, square.upperright, square.lowerleft,\\n square.lowerright]:\\n self.AddSquare(pos, color=Colors.white)\\n\\n def DisplayGeneration(self):\\n \\\"\\\"\\\"Draws current state of the world.\\\"\\\"\\\"\\n for top, left in sorted(self.squares.iterkeys()):\\n square = self.squares[(top, left)]\\n\\n if square.color == square.color_new == Colors.white:\\n # two generations white, remove from list\\n del self.squares[square.position]\\n\\n if square.color == Colors.white and square.color_new == Colors.black:\\n self.AddNeighborsToList(square)\\n\\n if square.color == Colors.black and square.color_new == Colors.black:\\n self.AddNeighborsToList(square)\\n\\n if square.color == Colors.black and square.color_new == Colors.white:\\n self.AddNeighborsToList(square)\\n\\n # update with next generation values\\n square.UpdateNextGenValues()\\n\\n self.world.DrawSquare(top*self.world.square_width,\\n left*self.world.square_width,\\n square.color, square.tint)\\n self.world.Update()\\n\\n def NextGeneration(self):\\n \\\"\\\"\\\"Generates next generation.\\\"\\\"\\\"\\n self.world.NextGeneration()\\n\\n def CreateWorld(self):\\n \\\"\\\"\\\"Creates drawing surface.\\\"\\\"\\\"\\n self.world.Initialize()\\n\\n def HandleNonGridClick(self, positions):\\n \\\"\\\"\\\"Handles non-grid click.\\n\\n Args:\\n position: (tuple) mousex, mousey pixel.\\n \\\"\\\"\\\"\\n pass\\n\\n def ToggleSquare(self, position):\\n \\\"\\\"\\\"Turns a square on (black) or off (white) based on mouse click.\\n\\n Args:\\n position: (tuple) mousex, mousey pixel.\\n \\\"\\\"\\\"\\n mousex, mousey = position\\n # round down both to nearest 10. Divide by 10, take int part, * 10.\\n x = round(mousex / self.world.square_width)\\n y = round(mousey / self.world.square_width)\\n\\n if mousex > self.world_width or mousey > self.world_height:\\n self.HandleNonGridClick(position)\\n return\\n\\n if (x, y) not in self.squares:\\n # create new black square\\n self.AddSquare((x,y), Colors.black, overwrite=True)\\n else:\\n # square exists\\n square = self.squares[(x, y)]\\n if square.color == Colors.black:\\n square.color_new = Colors.white\\n square.tint = Colors.custom(0, 0, 0)\\n square.tint_new = None\\n else:\\n square.color = Colors.black\\n\\n self.AddNeighborsToList(self.squares[x,y])\\n\\n def Run(self):\\n \\\"\\\"\\\"Runs game.\\n\\n Args:\\n generations: (int) run for this many generations.\\n \\\"\\\"\\\"\\n #self.DisplayGeneration()\\n generations = 0\\n msg = \\\"\\\"\\n\\n while generations < self.max_generations:\\n for event in pygame.event.get():\\n if event.type == QUIT:\\n pygame.quit()\\n sys.exit()\\n elif event.type == MOUSEBUTTONUP:\\n logging.info(\\\"Mouse clicked on: %s\\\", (event.pos,))\\n self.ToggleSquare(event.pos)\\n elif event.type == KEYDOWN:\\n logging.info(\\\"Key '%s' pressed.\\\", event.unicode)\\n\\n # Set message\\n self.world.SetMessage(\\\"Gen = %s\\\" % generations)\\n # displays current generation\\n self.DisplayGeneration()\\n # Changes squares to next generation values\\n self.NextGeneration()\\n # Pause\\n self.world.fps_clock.tick(FLAGS.fps)\\n generations += 1\\n\\n # print \\\"Total interesting squares: %s\\\" % len(self.squares)\\n\\n def ManualPosition(self):\\n \\\"\\\"\\\"Allows user to set manual position. <enter> when finsihed.\\\"\\\"\\\"\\n finished = False\\n while not finished:\\n for event in pygame.event.get():\\n if event.type == MOUSEBUTTONUP:\\n logging.info(\\\"Mouse clicked on: %s\\\", (event.pos,))\\n self.ToggleSquare(event.pos)\\n self.DisplayGeneration()\\n elif event.type == KEYDOWN:\\n if event.key in [K_KP_ENTER, K_RETURN]:\\n finished = True\\n\\n\\ndef Setup(argv):\\n \\\"\\\"\\\"Pre-game setup.\\\"\\\"\\\"\\n if argv is None:\\n argv = sys.argv\\n try:\\n argv = FLAGS(argv) # parse flags\\n except gflags.FlagsError, e:\\n print '%s\\\\\\\\nUsage: %s ARGS\\\\\\\\n%s' % (e, sys.argv[0], FLAGS)\\n sys.exit(1)\\n\\n myformat = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'\\n logging.basicConfig(level=logging.DEBUG, format=myformat)\\n\\n\\ndef SetInitialSquares(game):\\n \\\"\\\"\\\"Sets initial game squares.\\\"\\\"\\\"\\n if FLAGS.manual:\\n game.ManualPosition()\\n elif FLAGS.random_start:\\n SetRandomSquares(game)\\n else:\\n initial = [((9, 13), Colors.black, game.teams[\\\"red\\\"]),\\n ((9, 14), Colors.black, game.teams[\\\"red\\\"]),\\n ((9, 15), Colors.black, game.teams[\\\"red\\\"]),\\n ((8, 15), Colors.black, game.teams[\\\"red\\\"]),\\n ((7, 15), Colors.black, game.teams[\\\"red\\\"]),\\n ((9, 16), Colors.black, game.teams[\\\"red\\\"]),\\n ((8, 16), Colors.black, game.teams[\\\"red\\\"]),\\n ((7, 13), Colors.black, game.teams[\\\"red\\\"]),\\n ((6, 13), Colors.black, game.teams[\\\"red\\\"]),\\n ((5, 13), Colors.black, game.teams[\\\"red\\\"]),\\n ((8, 10), Colors.black, game.teams[\\\"red\\\"]),\\n ((9, 10), Colors.black, game.teams[\\\"red\\\"]),\\n ((10, 15), Colors.black, game.teams[\\\"red\\\"]),\\n ((10, 14), Colors.black, game.teams[\\\"red\\\"]),\\n ((10, 13), Colors.black, game.teams[\\\"red\\\"]),\\n ((11, 10), Colors.black, game.teams[\\\"red\\\"]),\\n ((8, 14), Colors.black, game.teams[\\\"red\\\"]),\\n ((12, 10), Colors.black, game.teams[\\\"red\\\"]),\\n ((12, 9), Colors.black, game.teams[\\\"red\\\"]),\\n ((13, 9), Colors.black, game.teams[\\\"red\\\"]),\\n ((50, 13), Colors.black, game.teams[\\\"blue\\\"]),\\n ((50, 14), Colors.black, game.teams[\\\"blue\\\"]),\\n ((50, 15), Colors.black, game.teams[\\\"blue\\\"]),\\n ((49, 15), Colors.black, game.teams[\\\"blue\\\"]),\\n ((48, 15), Colors.black, game.teams[\\\"blue\\\"]),\\n ((50, 16), Colors.black, game.teams[\\\"blue\\\"]),\\n ((49, 16), Colors.black, game.teams[\\\"blue\\\"]),\\n ((48, 13), Colors.black, game.teams[\\\"blue\\\"]),\\n ((47, 13), Colors.black, game.teams[\\\"blue\\\"]),\\n ((46, 13), Colors.black, game.teams[\\\"blue\\\"]),\\n ((49, 10), Colors.black, game.teams[\\\"blue\\\"]),\\n ((50, 10), Colors.black, game.teams[\\\"blue\\\"]),\\n ((51, 15), Colors.black, game.teams[\\\"blue\\\"]),\\n ((51, 14), Colors.black, game.teams[\\\"blue\\\"]),\\n ((51, 13), Colors.black, game.teams[\\\"blue\\\"]),\\n ((52, 10), Colors.black, game.teams[\\\"blue\\\"]),\\n ((49, 14), Colors.black, game.teams[\\\"blue\\\"]),\\n ((53, 10), Colors.black, game.teams[\\\"blue\\\"]),\\n ((53, 9), Colors.black, game.teams[\\\"blue\\\"]),\\n ((54, 9), Colors.black, game.teams[\\\"blue\\\"]),\\n ]\\n\\n for index, color, team in initial:\\n game.AddSquare(index, color, overwrite=True, team=team)\\n game.AddNeighborsToList(game.squares[index])\\n\\n\\ndef SetRandomSquares(game, black_white=True):\\n \\\"\\\"\\\"Sets random squares in the game.\\\"\\\"\\\"\\n max_squares = FLAGS.world_width / FLAGS.square_width\\n\\n for x in xrange(0, max_squares):\\n for y in xrange(0, max_squares):\\n color = random.choice(Colors.all())\\n\\n if color != Colors.white:\\n game.AddSquare((x, y), color, overwrite=True)\\n game.AddNeighborsToList(game.squares[(x,y)])\\n\\n\\ndef main(argv=None):\\n \\\"\\\"\\\"Main, run me.\\\"\\\"\\\"\\n Setup(argv)\\n\\n rules = getattr(world_rules, str(FLAGS.rules))\\n game = Game(rules)\\n game.CreateWorld()\\n\\n SetInitialSquares(game)\\n\\n game.Run()\\n raw_input(\\\"Hit <enter> to exit...\\\")\\n\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.6743420958518982,\n \"alphanum_fraction\": 0.6743420958518982,\n \"avg_line_length\": 18.0625,\n \"blob_id\": \"3f296740f14af367283b9a70689770f737143959\",\n \"content_id\": \"bb8c1842f2e10f93294449638c9fbcd8e5736fd8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 304,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 16,\n \"path\": \"/src/profile/examine.py\",\n \"repo_name\": \"DanTulovsky/game\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/local/bin/python\\n\\nimport gflags\\nimport pstats\\nimport sys\\n\\nFLAGS = gflags.FLAGS\\n\\ngflags.DEFINE_string(\\\"file\\\", None, \\\"File that contains profile info.\\\",\\n short_name=\\\"-f\\\")\\n\\nargv = FLAGS(sys.argv)\\n\\np = pstats.Stats(FLAGS.file)\\n\\np.strip_dirs().sort_stats(\\\"cumulative\\\").print_stats()\"\n },\n {\n \"alpha_fraction\": 0.6099432110786438,\n \"alphanum_fraction\": 0.6159090995788574,\n \"avg_line_length\": 27.047809600830078,\n \"blob_id\": \"5c552d9cee53ad52205efce66f8797a8f15b1e59\",\n \"content_id\": \"0fa4a698c41cb4dee4ad3b29aea23b260da48731\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 7040,\n \"license_type\": \"no_license\",\n \"max_line_length\": 86,\n \"num_lines\": 251,\n \"path\": \"/src/world.py\",\n \"repo_name\": \"DanTulovsky/game\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/local/bin/python\\n# -*- coding: utf-8 -*-\\n\\n\\\"\\\"\\\"pygame helper.\\\"\\\"\\\"\\n\\nfrom colors import Colors\\n\\nimport gflags\\nimport pygame\\nimport Queue\\nimport sys\\nimport threading\\n\\nfrom pygame.locals import *\\n\\nfrom memoized import *\\nimport world_rules\\n\\nFLAGS = gflags.FLAGS\\n\\nBACKGROUND = Colors.white()\\n\\n\\nclass Error(Exception):\\n \\\"\\\"\\\"General error.\\\"\\\"\\\"\\n\\n\\nclass NoNeighbor(Error):\\n \\\"\\\"\\\"Raised if square has no neighbor in the indicated direction.\\\"\\\"\\\"\\n\\n\\nclass OutsideWorld(Error):\\n \\\"\\\"\\\"Raised if neighbor would be outside the known world.\\\"\\\"\\\"\\n\\n\\nclass World(object):\\n \\\"\\\"\\\"The world (grid). (0,0) is top left. Should be square.\\\"\\\"\\\"\\n\\n def __init__(self, width, height, square_width, rules, squares,\\n black_white=False, random_events=False, workers=10):\\n \\\"\\\"\\\"Init.\\n\\n Args:\\n width: (int) width of the world in pixels.\\n height: (int) height of the world in pixels.\\n square_width: (int) width/height of citizen squares\\n rules: (world_rules.WorldRules) world rules, function pointer\\n squares: (dict) dict of Square objects. Current state.\\n \\\"\\\"\\\"\\n pygame.init()\\n self.width = width\\n self.height = height\\n self.square_width = square_width\\n self.msg_width = 100\\n self.black_white = black_white\\n self.rules = rules()\\n self.squares = squares\\n self.random_events = random_events\\n # worker queue\\n #self.q = Queue.Queue()\\n #self.q = multiprocessing.JoinableQueue()\\n #self._StartWorkers(workers)\\n\\n def Initialize(self):\\n self.fps_clock = pygame.time.Clock()\\n self.surface = pygame.display.set_mode((self.width + self.msg_width, self.height))\\n self.fontObj = pygame.font.Font('freesansbold.ttf', 14)\\n\\n # set background\\n self.Clear()\\n\\n # queue worker for processing next_gen data\\n def Worker(self):\\n while True:\\n func, args = self.q.get()\\n func(*args)\\n self.q.task_done()\\n\\n def NextGeneration(self):\\n \\\"\\\"\\\"Moves world to next generation.\\\"\\\"\\\"\\n# for square_index, square in self.squares.iteritems():\\n# # Put each next_gen square in a worker thread\\n# self.q.put((self.NextGenSquare, [square_index]))\\n#\\n# # wait for all threads to finish work\\n# self.q.join()\\n\\n for square_index in self.squares.iterkeys():\\n self.NextGenSquare(square_index)\\n\\n # reset memoized cache\\n #Memoized.reset()\\n\\n def NextGenSquare(self, square_index):\\n \\\"\\\"\\\"Sets the square's nextgen state.\\n\\n Args:\\n square_index: (int) square index in world\\n \\\"\\\"\\\"\\n square = self.squares[square_index]\\n neighbors = self._NeighborCount(square)\\n self.rules.NextGen(square, self.random_events, neighbors)\\n\\n\\n def SetMessage(self, msg=\\\"Game\\\"):\\n self.msgSurfaceObj = self.fontObj.render(msg, False, Colors.blue())\\n self.msgRectobj = self.msgSurfaceObj.get_rect()\\n self.msgRectobj.topleft = (self.width + 4, 0)\\n\\n # Clear previous msg\\n self.surface.fill(Colors.white(), self.msgRectobj)\\n\\n self.surface.blit(self.msgSurfaceObj, self.msgRectobj)\\n\\n def DrawSquare(self, top, left, color, tint=None):\\n # Draw inside grid.\\n square_color = color() + tint\\n pygame.draw.rect(\\n self.surface, square_color, (top+1, left+1, self.square_width - 1,\\n self.square_width - 1))\\n\\n def DrawGrid(self, color=Colors.green()):\\n \\\"\\\"\\\"Draws grid.\\\"\\\"\\\"\\n self._DrawVerticalGrid(color=color)\\n self._DrawHorizontalGrid(color=color)\\n\\n def Clear(self):\\n \\\"\\\"\\\"Clears surface.\\\"\\\"\\\"\\n self.surface.fill(BACKGROUND)\\n self.DrawGrid()\\n self.Update()\\n\\n def Update(self):\\n \\\"\\\"\\\"Redraws surface.\\\"\\\"\\\"\\n pygame.display.update()\\n\\n def InWorld(self, position):\\n \\\"\\\"\\\"Returns True if given position is in the World.\\n\\n Args:\\n position: (tuple) (top, left) pixel.\\n \\\"\\\"\\\"\\n top, left = position[0], position[1]\\n if (top < 0 or\\n left < 0 or\\n top + self.square_width > self.height or\\n left + self.square_width > self.width):\\n return False\\n else:\\n return True\\n\\n #@Memoized\\n def _NeighborColor(self, square, position):\\n \\\"\\\"\\\"Returns the color of the neighbor in position.\\n\\n Args:\\n square: (Square) Object\\n position: (string) Valid position from Square class (RIGHT, LEFT, etc)\\n\\n Returns:\\n color, team: (Square.COLOR, teams.Team) color and team of neighbor.\\n\\n Raises:\\n NoNeighbor: If there is no neighbor\\n OutsideWorld: If neighbor would be outside the known world.\\n \\\"\\\"\\\"\\n neighbor_position = getattr(square, position)\\n\\n if neighbor_position in self.squares:\\n return (self.squares[neighbor_position].color,\\n self.squares[neighbor_position].team)\\n else:\\n raise NoNeighbor(\\\"No neighbor at %s\\\" % (neighbor_position,))\\n\\n def _NeighborCount(self, square):\\n \\\"\\\"\\\"Returns the count and color of a square's neighbors.\\n\\n Args:\\n square: (Square) Object\\n\\n Returns:\\n neighbors: (dict) {\\n Color.white: N, # total\\n \\\"friends\\\": H,\\n \\\"enemies\\\": J,\\n \\\"total_neighbors\\\": L, # non-white neighbors\\n \\\"influence\\\": Team # the team with the most influence\\n # simply with the most squares\\n # surrounding this one\\n }\\n \\\"\\\"\\\"\\n neighbors = {\\\"total_neighbors\\\": 0, \\\"friends\\\": 0, \\\"enemies\\\": 0}\\n\\n\\n if square.position == (46, 14):\\n pass\\n # initialize all colors to 0\\n for color in Colors.all():\\n neighbors[color] = 0\\n\\n neighbor_team_count = {}\\n\\n for pos in (world_rules.POSITIONS):\\n try:\\n neighbor_color, neighbor_team = self._NeighborColor(square, pos)\\n except (OutsideWorld, NoNeighbor):\\n continue\\n\\n neighbors[neighbor_color] += 1\\n if neighbor_color != Colors.white:\\n neighbors[\\\"total_neighbors\\\"] += 1\\n\\n neighbor_team_count.setdefault(neighbor_team, 0)\\n neighbor_team_count[neighbor_team] += 1\\n\\n if neighbor_team == square.team:\\n neighbors[\\\"friends\\\"] += 1\\n else:\\n neighbors[\\\"enemies\\\"] += 1\\n\\n influence = None\\n max = 0\\n for team, count in neighbor_team_count.iteritems():\\n if count > max:\\n max = count\\n influence = team\\n\\n\\n neighbors[\\\"influence\\\"] = influence\\n\\n return neighbors\\n\\n def _DrawVerticalGrid(self, color):\\n \\\"\\\"\\\"Draws vertical grid.\\\"\\\"\\\"\\n for x in xrange(0, self.width + self.square_width, self.square_width):\\n pygame.draw.line(self.surface, color, (x, 0),\\n (x, self.height), 1)\\n\\n def _DrawHorizontalGrid(self, color):\\n \\\"\\\"\\\"Draws horizontal grid.\\\"\\\"\\\"\\n for y in xrange(0, self.height + self.square_width, self.square_width):\\n pygame.draw.line(self.surface, color, (0, y),\\n (self.width, y), 1)\\n\\n def _StartWorkers(self, num_worker_threads):\\n \\\"\\\"\\\"Starts queue workers.\\\"\\\"\\\"\\n for i in range(num_worker_threads):\\n t = threading.Thread(target=self.Worker)\\n #t = multiprocessing.Process(target=self.Worker)\\n t.daemon = True\\n t.start()\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":8,"string":"8"}}},{"rowIdx":2977696,"cells":{"repo_name":{"kind":"string","value":"mek05/Task-1"},"repo_url":{"kind":"string","value":"https://github.com/mek05/Task-1"},"snapshot_id":{"kind":"string","value":"94c58e2ebc6272c11339985009c36a77885824da"},"revision_id":{"kind":"string","value":"3304951e708a3a991f25e60f8d16a1334836d08b"},"directory_id":{"kind":"string","value":"8e08027bf7d8a8b167f9d8eafbc81b1132f88d30"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-07-21T11:54:16.357028","string":"2023-07-21T11:54:16.357028"},"revision_date":{"kind":"timestamp","value":"2021-08-21T01:39:23","string":"2021-08-21T01:39:23"},"committer_date":{"kind":"timestamp","value":"2021-08-21T01:39:23","string":"2021-08-21T01:39:23"},"github_id":{"kind":"number","value":398437363,"string":"398,437,363"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6116838455200195,"alphanum_fraction":0.6288659572601318,"avg_line_length":19.714284896850586,"blob_id":"5d94d1960b1158fc8a9b7cc17c6d135d56bae7cd","content_id":"f2defb7b4b87ad8707f65f60c0e8c0110075be60","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":291,"license_type":"no_license","max_line_length":51,"num_lines":14,"path":"/Task1.py","repo_name":"mek05/Task-1","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n\"\"\"\nSpyder Editor\n\nThis is a temporary script file.\n\"\"\"\n\nr = float(input(\"input the radius of the circle:\"))\nA = r*r*3.14\nprint(\"Area of the circle with radius\",r,\"is\",A)\n\nfn = input(\"Enter filename:\")\nf = fn.split(\".\")\nprint(\"Extension of the file name is:\"+f[-1])\n "}],"string":"[\n {\n \"alpha_fraction\": 0.6116838455200195,\n \"alphanum_fraction\": 0.6288659572601318,\n \"avg_line_length\": 19.714284896850586,\n \"blob_id\": \"5d94d1960b1158fc8a9b7cc17c6d135d56bae7cd\",\n \"content_id\": \"f2defb7b4b87ad8707f65f60c0e8c0110075be60\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 291,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 14,\n \"path\": \"/Task1.py\",\n \"repo_name\": \"mek05/Task-1\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n\\\"\\\"\\\"\\nSpyder Editor\\n\\nThis is a temporary script file.\\n\\\"\\\"\\\"\\n\\nr = float(input(\\\"input the radius of the circle:\\\"))\\nA = r*r*3.14\\nprint(\\\"Area of the circle with radius\\\",r,\\\"is\\\",A)\\n\\nfn = input(\\\"Enter filename:\\\")\\nf = fn.split(\\\".\\\")\\nprint(\\\"Extension of the file name is:\\\"+f[-1])\\n \"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2977697,"cells":{"repo_name":{"kind":"string","value":"cristobaltapia/dotfiles_main"},"repo_url":{"kind":"string","value":"https://github.com/cristobaltapia/dotfiles_main"},"snapshot_id":{"kind":"string","value":"cf68264d211864a051f55cdcfaf702c0d1cf2a3c"},"revision_id":{"kind":"string","value":"cb3453193da52c5bf2cded826a4228edb3062571"},"directory_id":{"kind":"string","value":"c3c4f2e3e406822a4ba57da2186aacea643fe924"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2023-09-04T11:51:31.146429","string":"2023-09-04T11:51:31.146429"},"revision_date":{"kind":"timestamp","value":"2023-08-29T22:23:20","string":"2023-08-29T22:23:20"},"committer_date":{"kind":"timestamp","value":"2023-08-29T22:23:20","string":"2023-08-29T22:23:20"},"github_id":{"kind":"number","value":63482051,"string":"63,482,051"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.4781915545463562,"alphanum_fraction":0.4798997938632965,"avg_line_length":27.69607925415039,"blob_id":"592c41e9f564d2507a9bb6aa8505c000c659a9eb","content_id":"d9008c7d4473824e435fbc8444ffb3f085a27ca9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":8781,"license_type":"no_license","max_line_length":107,"num_lines":306,"path":"/home/.config/nvim/lua/plugins/utils.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"-- Define hints for hydra\nlocal hint_diagram = [[\n Arrow^^^^^^ Select region with <C-v>\n ^ ^ _K_ ^ ^ _f_: surround it with box\n _H_ ^ ^ _L_\n ^ ^ _J_ ^ ^ _q_\n]]\n\nlocal hint_git = [[\n _J_: next hunk _s_: stage hunk _d_: show deleted _b_: blame line\n _K_: prev hunk _u_: undo last stage _p_: preview hunk _B_: blame show full\n ^ ^ _S_: stage buffer ^ ^ _/_: show base file\n ^\n ^ ^ _<Enter>_: Fugitive _q_: exit\n]]\n\nlocal hint_ltex = [[\n ^^ Select Language for Ltex ^\n^ ^\n _e_: English (American) ^\n _d_: German (Germany) ^\n _s_: Spanish\n^ ^\n _q_: Exit\n]]\n\nreturn {\n -- Undo history\n {\n 'mbbill/undotree',\n keys = {\n { \"<F3>\", \"<cmd>UndotreeToggle<cr>\", \"n\" },\n },\n config = function()\n vim.g.undotree_WindowLayout = 2\n vim.g.undotree_SetFocusWhenToggle = true\n end\n },\n -- Web devicons\n { \"nvim-tree/nvim-web-devicons\", name = \"web-devicons\" },\n -- Better ui elements for nvim\n { 'stevearc/dressing.nvim' },\n -- Char-based diff\n {\n 'rickhowe/diffchar.vim',\n ft = { 'markdown', 'markdown.pandoc', 'tex' }\n },\n {\n 'b3nj5m1n/kommentary',\n branch = 'main',\n config = function()\n require('kommentary.config').configure_language(\"julia\", {\n single_line_comment_string = \"#\",\n prefer_single_line_comments = true,\n })\n require('kommentary.config').configure_language(\"lua\", {\n prefer_single_line_comments = true,\n })\n end\n },\n -- Better movements\n {\n 'ggandor/leap.nvim',\n keys = {\n { \"s\", \"<Plug>(leap-forward-to)\", \"n\", { silent = true } },\n { \"S\", \"<Plug>(leap-backward-to)\", \"n\", { silent = true } },\n },\n config = function()\n vim.api.nvim_set_hl(0, 'LeapBackdrop', { link = 'Comment' })\n end\n },\n -- Hydra\n {\n 'anuvyklack/hydra.nvim',\n name = \"hydra\",\n lazy = true,\n keys = {\n \"<leader>g\", \"<leader>hd\", \"<leader>hl\",\n },\n config = function(_, opts)\n local Hydra = require('hydra')\n\n Hydra({\n name = 'Draw Diagram',\n hint = hint_diagram,\n config = {\n color = 'pink',\n invoke_on_body = true,\n hint = {\n border = 'rounded'\n },\n on_enter = function()\n vim.o.virtualedit = 'all'\n end,\n },\n mode = 'n',\n body = '<leader>hd',\n heads = {\n { 'H', '<C-v>h:VBox<CR>' },\n { 'J', '<C-v>j:VBox<CR>' },\n { 'K', '<C-v>k:VBox<CR>' },\n { 'L', '<C-v>l:VBox<CR>' },\n { 'f', ':VBox<CR>', { mode = 'v' } },\n { 'q', nil, { exit = true } },\n }\n })\n\n local gitsigns = require('gitsigns')\n\n Hydra({\n name = 'Git',\n hint = hint_git,\n config = {\n buffer = bufnr,\n color = 'pink',\n invoke_on_body = true,\n hint = {\n border = 'rounded'\n },\n on_enter = function()\n vim.cmd 'mkview'\n vim.cmd 'silent! %foldopen!'\n vim.bo.modifiable = false\n gitsigns.toggle_signs(true)\n gitsigns.toggle_linehl(true)\n gitsigns.toggle_word_diff(true)\n end,\n on_exit = function()\n local cursor_pos = vim.api.nvim_win_get_cursor(0)\n vim.cmd 'loadview'\n vim.api.nvim_win_set_cursor(0, cursor_pos)\n vim.cmd 'normal zv'\n gitsigns.toggle_signs(true)\n gitsigns.toggle_linehl(false)\n gitsigns.toggle_deleted(false)\n gitsigns.toggle_word_diff(false)\n end,\n },\n mode = { 'n', 'x' },\n body = '<leader>g',\n heads = {\n { 'J',\n function()\n if vim.wo.diff then return ']c' end\n vim.schedule(function() gitsigns.next_hunk() end)\n return '<Ignore>'\n end,\n { expr = true, desc = 'next hunk' } },\n { 'K',\n function()\n if vim.wo.diff then return '[c' end\n vim.schedule(function() gitsigns.prev_hunk() end)\n return '<Ignore>'\n end,\n { expr = true, desc = 'prev hunk' } },\n { 's', ':Gitsigns stage_hunk<CR>', { silent = true, desc = 'stage hunk' } },\n { 'u', gitsigns.undo_stage_hunk, { desc = 'undo last stage' } },\n { 'S', gitsigns.stage_buffer, { desc = 'stage buffer' } },\n { 'p', gitsigns.preview_hunk, { desc = 'preview hunk' } },\n { 'd', gitsigns.toggle_deleted, {\n nowait = true,\n desc = 'toggle deleted'\n } },\n { 'b', gitsigns.blame_line, { desc = 'blame' } },\n { 'B', function() gitsigns.blame_line { full = true } end, { desc = 'blame show full' } },\n { '/', gitsigns.show, {\n exit = true,\n desc = 'show base file'\n } }, -- show the base of the file\n { '<Enter>', '<Cmd>Git<CR>', { exit = true, desc = 'Fugitive' } },\n { 'q', nil, {\n exit = true,\n nowait = true,\n desc = 'exit'\n } },\n }\n })\n\n -- Change language for ltex\n Hydra({\n name = 'Change Ltex language',\n hint = hint_ltex,\n config = {\n color = 'pink',\n invoke_on_body = true,\n hint = {\n border = 'rounded'\n },\n on_enter = function()\n vim.o.virtualedit = 'all'\n end,\n },\n mode = 'n',\n body = '<leader>hl',\n heads = {\n { 'e', function()\n require(\"lspconfig\").ltex.setup({ settings = { ltex = { language = \"en-US\" } } })\n vim.opt.spelllang = \"en_us\"\n end },\n { 'd', function()\n require(\"lspconfig\").ltex.setup({ settings = { ltex = { language = \"de-DE\" } } })\n vim.opt.spelllang = \"de_de\"\n end },\n { 's', function()\n require(\"lspconfig\").ltex.setup({ settings = { ltex = { language = \"es\" } } })\n vim.opt.spelllang = \"es\"\n end },\n { 'q', nil, { exit = true } },\n }\n })\n end\n },\n -- Docstrings generator\n {\n \"danymat/neogen\",\n keys = {\n { \"<leader>ds\", \"<cmd>Neogen func<cr>\", desc = \"Generate func docstrings\" },\n { \"<leader>dc\", \"<cmd>Neogen class<cr>\", desc = \"Generate class docstrings\" },\n },\n opts = {\n enabled = true,\n input_after_comment = true,\n languages = {\n python = {\n template = {\n annotation_convention = 'numpydoc',\n }\n }\n }\n },\n },\n -- Surround movements\n { 'tpope/vim-surround' },\n -- Close pairs of parentheses, quotes, etc\n {\n 'windwp/nvim-autopairs',\n config = true,\n },\n -- Different nice improvements for neovim\n {\n 'echasnovski/mini.nvim',\n branch = 'main',\n event = { \"BufReadPre\", \"BufNewFile\" },\n config = function()\n local animate = require('mini.animate')\n require('mini.trailspace').setup()\n require('mini.indentscope').setup()\n require('mini.animate').setup({\n cursor = { enable = false },\n resize = { enable = true },\n scroll = { enable = false, timing = animate.gen_timing.linear({ duration = 150, unit = 'total' }) }\n })\n end\n },\n -- Support for openning GNUGP excrypted files\n { 'jamessan/vim-gnupg' },\n -- Draw ascii diagrams\n {\n 'jbyuki/venn.nvim',\n dependencies = { \"hydra\" },\n },\n -- Snippets\n {\n 'SirVer/ultisnips',\n dependencies = {\n { 'honza/vim-snippets' },\n { 'cristobaltapia/MySnippets' }\n },\n config = function()\n vim.g.UltiSnipsSnippetDirectories = {\n 'UltiSnips',\n vim.env.HOME .. '/.local/share/nvim/lazy/MySnippets/Ultisnips',\n vim.env.HOME .. '/Templates/ultisnips-templates'\n }\n\n -- Set the smart function definition to use numpy style for docstrings\n vim.g.ultisnips_python_style = \"numpy\"\n vim.g.UltisnipsUsePythonVersion = 3\n end\n },\n -- Follow symlinks\n {\n 'aymericbeaumet/vim-symlink',\n -- 'Jasha10/vim-symlink',\n dependencies = { 'moll/vim-bbye' },\n },\n {\n \"jackMort/ChatGPT.nvim\",\n cmd = { \"ChatGPT\", \"ChatGPTRun\", \"ChatGPTEditWithInstructions\" },\n config = function()\n local home = vim.fn.expand(\"$HOME\")\n require(\"chatgpt\").setup(\n {\n api_key_cmd = \"cat \" .. home .. \"/.config/chatgpt/api\",\n actions_paths = { vim.env.HOME .. \"/.config/chatgpt/actions.json\" }\n }\n )\n end,\n dependencies = {\n \"MunifTanjim/nui.nvim\",\n \"nvim-lua/plenary.nvim\",\n \"nvim-telescope/telescope.nvim\"\n }\n }\n}\n-- vim: set shiftwidth=2:\n"},{"alpha_fraction":0.5131086111068726,"alphanum_fraction":0.5243445634841919,"avg_line_length":27.60714340209961,"blob_id":"ceb9137fe175750b24eb8e38e413bd356c672af2","content_id":"5058a703e4dbe83093d8df3fa8d0da9956029f19","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":801,"license_type":"no_license","max_line_length":66,"num_lines":28,"path":"/home/.local/bin/fexdox-completion.bash","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"#!/usr/bin/env bash\n\n_fexdox_completions()\n{\n # Consider account ID if given\n options=\"\"\n for IDX in ${!COMP_WORDS[@]}; do\n if [[ ${COMP_WORDS[$IDX]} = \"-i\" ]]; then\n # Get username\n options=\"-i ${COMP_WORDS[$(($IDX+1))]}\"\n fi\n done\n case ${COMP_WORDS[-2]} in\n -s )\n COMPREPLY=($(compgen -o dirnames \"${COMP_WORDS[-1]}\"));;\n -r )\n remotes=$(fexdox ${options} -l | awk '{print $5}')\n COMPREPLY=($(compgen -W \"${remotes}\" \"${COMP_WORDS[-1]}\"));;\n -D )\n remotes=$(fexdox ${options} -l | awk '{print $5}')\n COMPREPLY=($(compgen -W \"${remotes}\" \"${COMP_WORDS[-1]}\"));;\n -l )\n remotes=$(fexdox ${options} -l | awk '{print $5}')\n COMPREPLY=($(compgen -W \"${remotes}\" \"${COMP_WORDS[-1]}\"));;\n esac\n}\n\ncomplete -F _fexdox_completions fexdox\n"},{"alpha_fraction":0.6847977638244629,"alphanum_fraction":0.6908414959907532,"avg_line_length":21.882978439331055,"blob_id":"8f3cd6d221683cff0ccdb47cb41d5471285099d5","content_id":"bdf08258cc1befccc1c5f7f815c42c001e27e411","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":2154,"license_type":"no_license","max_line_length":79,"num_lines":94,"path":"/home/.config/nvim/lua/tapia/set.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"vim.g.python3_host_prog = vim.env.HOME .. '/.virtualenvs/py3neovim/bin/python3'\n\nvim.opt.title = true\nvim.opt.titlestring = \"%t %y\"\nvim.opt.autoread = true\nvim.opt.swapfile = false\nvim.opt.backup = false\nvim.opt.encoding = \"utf-8\"\nvim.opt.cursorline = true\n\n-- Line numbers\nvim.opt.nu = true\nvim.opt.relativenumber = true\n\n-- Lineabraks with indentation\nvim.opt.linebreak = true\nvim.opt.breakindent = true\nvim.opt.showbreak = \" \"\nvim.opt.wrap = true\n\n-- Change buffer without saving\nvim.opt.hidden = true\n\n-- Atomatically change current working directory to the directory\n-- containing the file in the buffer\nvim.opt.autochdir = true\n\n-- Use spaces to replace tabs\nvim.opt.expandtab = true\n\n-- Allow virtual editing in visual block\nvim.opt.virtualedit = \"block\"\n\n-- Ignore certain files\nvim.opt.wildignore = { \"*.swp\", \"*.bak\", \"*.pyc\", \"*.class\", \"*.aux\", \"*.toc\" }\n\n-- Always show status bar\nvim.opt.laststatus = 2\n\nvim.opt.hlsearch = false\nvim.opt.incsearch = true\n\nvim.opt.termguicolors = true\n\nvim.opt.scrolloff = 8\nvim.opt.signcolumn = \"yes\"\nvim.opt.isfname:append(\"@-@\")\n\nvim.opt.diffopt:append(\"vertical\")\nvim.opt.diffopt:append(\"linematch:60\")\n\nvim.opt.shada:append('r/mnt/intcdc')\n\nvim.g.mapleader = \"\\\\\"\n\n-- Visual selection copies to the clipboard\nvim.opt.clipboard:append('unnamedplus')\n\nvim.g.completion_sorting = \"none\"\nvim.g.completeopt = \"menu,menuone,noinsert\"\n\n-- Size of the completion menu\nvim.opt.pumheight = 15\n\n-- Set python syntax for Freecad macros\nvim.api.nvim_create_autocmd({ \"BufEnter\", \"BufNewFile\" }, {\n pattern = { \"*.fcmacro\" },\n callback = function()\n vim.opt.filetype = \"python\"\n end\n})\n-- Set tex syntax for pdf_tex files\nvim.api.nvim_create_autocmd({ \"BufEnter\", \"BufNewFile\" }, {\n pattern = { \"*.pdf_tex\" },\n callback = function()\n vim.opt.filetype = \"tex\"\n end\n})\n\n-- dont list quickfix buffers\nvim.api.nvim_create_autocmd(\"FileType\", {\n pattern = \"qf\",\n callback = function()\n vim.opt_local.buflisted = false\n end,\n})\n\n-- Disable editorconfig\nvim.g.editorconfig = false\n\n-- Set default tabsize\nvim.opt.softtabstop = 4\nvim.opt.shiftwidth = 4\nvim.opt.tabstop = 4\n"},{"alpha_fraction":0.5100317001342773,"alphanum_fraction":0.5129883885383606,"avg_line_length":29.54838752746582,"blob_id":"d2dc02ee35d8bbfb8fe6ca3dddc9d8c5a64ebf3d","content_id":"427158cbffcb6a0e630d5c689ac21a9bff965bed","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":9474,"license_type":"no_license","max_line_length":106,"num_lines":310,"path":"/home/.config/nvim/lua/plugins/lsp.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"return {\n -- Lsp-connfig\n {\n 'neovim/nvim-lspconfig',\n dependencies = {\n { \"folke/neodev.nvim\" },\n { \"williamboman/mason-lspconfig.nvim\" },\n { \"nvim-lua/plenary.nvim\" },\n { \"ray-x/lsp_signature.nvim\" },\n },\n event = { \"BufReadPre\", \"BufNewFile\" },\n opts = {\n -- options for vim.diagnostic.config()\n diagnostics = {\n underline = true,\n update_in_insert = false,\n virtual_text = {\n spacing = 4,\n source = \"if_many\",\n prefix = \"●\",\n -- this will set set the prefix to a function that returns\n -- the diagnostics icon based on the severity this only\n -- works on a recent 0.10.0 build. Will be set to \"●\" when\n -- not supported prefix = \"icons\",\n },\n severity_sort = true,\n },\n -- Enable this to enable the builtin LSP inlay hints on Neovim >=\n -- 0.10.0 Be aware that you also will need to properly configure\n -- your LSP server to provide the inlay hints.\n inlay_hints = {\n enabled = false,\n },\n -- add any global capabilities here\n capabilities = {},\n -- Automatically format on save\n autoformat = false,\n },\n config = function(_, opts)\n local Path = require(\"plenary.path\")\n require(\"neodev\").setup { lspconfig = true, }\n\n local lspconfig = require('lspconfig')\n local lsp_defaults = lspconfig.util.default_config\n\n lsp_defaults.capabilities = vim.tbl_deep_extend(\n 'force',\n lsp_defaults.capabilities,\n require('cmp_nvim_lsp').default_capabilities()\n )\n\n vim.api.nvim_create_autocmd('LspAttach', {\n desc = 'LSP actions',\n callback = function(event)\n -- Define current bufnr\n local bufnr = event.buf\n local map = function(m, lhs, rhs)\n local options = { buffer = bufnr, remap = false }\n vim.keymap.set(m, lhs, rhs, options)\n end\n\n -- LSP actions\n map('n', 'K', vim.lsp.buf.hover)\n map('n', 'gd', vim.lsp.buf.definition)\n map('n', 'gD', vim.lsp.buf.declaration)\n map('n', 'gi', vim.lsp.buf.implementation)\n map('n', 'go', vim.lsp.buf.type_definition)\n map('n', 'gr', vim.lsp.buf.references)\n map('n', 'gs', vim.lsp.buf.signature_help)\n map('n', '<leader>rn', vim.lsp.buf.rename)\n map({ 'n', 'x' }, 'gq', function() vim.lsp.buf.format({ async = true }) end)\n -- Format selected code only\n vim.keymap.set('v', 'gq', function()\n vim.lsp.buf.format({\n async = true,\n timeout_ms = 10000,\n range = { vim.fn.getpos('v'), vim.fn.getcurpos() },\n })\n end)\n map('n', '<leader>ca', vim.lsp.buf.code_action)\n map('x', '<leader>ca', '<cmd>lua vim.lsp.buf.range_code_action()<cr>')\n\n -- Diagnostics\n map('n', 'ge', vim.diagnostic.open_float)\n map('n', '[d', vim.diagnostic.goto_prev)\n map('n', ']d', vim.diagnostic.goto_next)\n end\n })\n\n local function lsp_settings()\n vim.diagnostic.config({\n severity_sort = true,\n float = { border = 'rounded' },\n })\n\n vim.lsp.handlers['textDocument/hover'] = vim.lsp.with(\n vim.lsp.handlers.hover,\n { border = 'rounded' }\n )\n\n vim.lsp.handlers['textDocument/signatureHelp'] = vim.lsp.with(\n vim.lsp.handlers.signature_help,\n { border = 'rounded' }\n )\n\n local command = vim.api.nvim_create_user_command\n\n command('LspWorkspaceAdd', function()\n vim.lsp.buf.add_workspace_folder()\n end, { desc = 'Add folder to workspace' })\n\n command('LspWorkspaceList', function()\n vim.notify(vim.inspect(vim.lsp.buf.list_workspace_folders()))\n end, { desc = 'List workspace folders' })\n\n command('LspWorkspaceRemove', function()\n vim.lsp.buf.remove_workspace_folder()\n end, { desc = 'Remove folder from workspace' })\n end\n\n lsp_settings()\n\n require('mason').setup({})\n\n require('mason-lspconfig').setup({\n ensure_installed = {\n 'bashls',\n 'cssls',\n 'docker_compose_language_service',\n 'dockerls',\n 'efm',\n 'eslint',\n 'fortls',\n 'jsonls',\n 'julials',\n 'ltex',\n 'lua_ls',\n 'marksman',\n 'pyright',\n 'ruff_lsp',\n 'taplo',\n 'tsserver',\n 'typst_lsp',\n }\n })\n\n -- Configure Lua-ls\n lspconfig.lua_ls.setup {\n settings = {\n Lua = {\n -- Disable telemetry\n telemetry = { enable = false },\n runtime = {\n -- Tell the language server which version of Lua you're using\n -- (most likely LuaJIT in the case of Neovim)\n version = 'LuaJIT',\n path = runtime_path,\n },\n diagnostics = {\n -- Get the language server to recognize the `vim` global\n globals = { 'vim' }\n },\n workspace = {\n checkThirdParty = false,\n library = {\n -- Make the server aware of Neovim runtime files\n vim.fn.expand('$VIMRUNTIME/lua'),\n vim.fn.stdpath('config') .. '/lua'\n }\n }\n }\n }\n }\n\n -- Python LSP\n local capabilities = vim.lsp.protocol.make_client_capabilities()\n capabilities.textDocument.publishDiagnostics.tagSupport.valueSet = { 2 }\n lspconfig.pyright.setup {\n settings = {\n python = {\n analysis = {\n autoSearchPaths = true,\n disableOrganizeImports = true,\n useLibraryCodeForTypes = true,\n diagnosticMode = 'workspace',\n autoImportCompletions = false,\n }\n }\n }\n }\n lspconfig.ruff_lsp.setup {}\n -- Typst\n lspconfig.typst_lsp.setup {\n single_file_support = true,\n }\n -- Julia\n lspconfig.julials.setup {}\n -- Latex\n -- lspconfig.texlab.setup {}\n -- Toml\n lspconfig.taplo.setup {}\n -- Docker\n lspconfig.docker_compose_language_service.setup {}\n lspconfig.dockerls.setup {\n on_attach = function(client, bufnr)\n -- Remove syntax from LSP\n client.server_capabilities.semanticTokensProvider = nil\n end,\n }\n -- CSS\n lspconfig.cssls.setup {}\n -- Grammar correctoin using ltex-ls\n local ltex_setup = {\n filetypes = { \"bib\", \"gitcommit\", \"markdown\", \"org\", \"plaintex\", \"rst\", \"rnoweb\", \"tex\", \"pandoc\",\n \"typst\" },\n settings = {\n ltex = {\n language = \"en-US\",\n },\n },\n }\n -- For ltex-ls under archlinux I have to use the system installation, but\n -- for other systems (e.g. Ubuntu) the default cmd works good.\n if Path:new(\"/usr/bin/ltex-ls\"):is_file() then\n ltex_setup[\"cmd\"] = { \"/usr/bin/ltex-ls\" }\n end\n lspconfig.ltex.setup(ltex_setup)\n lspconfig.fortls.setup {}\n -- JSON-ls\n lspconfig.jsonls.setup {}\n\n -- Define formatting for different filetypes\n local texFormatter = 'latexindent --modifylinebreaks -y=\"defaultIndent: \\' \\'\"'\n lspconfig.efm.setup {\n flags = {\n debounce_text_changes = 150,\n },\n init_options = { documentFormatting = true },\n filetypes = { \"python\", \"bib\", \"tex\", \"sty\", \"cls\", \"fortran\" },\n settings = {\n rootMarkers = { \".git/\" },\n languages = {\n python = {\n { formatCommand = \"yapf\", formatStdin = true }\n },\n bib = {\n {\n formatCommand = \"bibtex-tidy --v2 --curly --align=14 --no-escape --sort-fields --sort\",\n formatStdin = true\n }\n },\n fortran = {\n {\n formatCommand = \"findent --continuation=0 --input_format=fixed --indent_procedure=0\",\n formatStdin = true\n }\n },\n tex = { { formatCommand = texFormatter, formatStdin = true } },\n sty = { { formatCommand = texFormatter, formatStdin = true } },\n cls = { { formatCommand = texFormatter, formatStdin = true } },\n }\n }\n }\n\n\n -- Don't show diagnostics in-line\n vim.diagnostic.config({ virtual_text = false })\n\n -- Increase update frequency of the ui\n vim.opt.updatetime = 500\n end\n },\n {\n \"folke/neodev.nvim\",\n opts = {\n lspconfig = true\n }\n },\n -- Mason\n {\n 'williamboman/mason-lspconfig.nvim',\n name = \"mason\",\n dependencies = {\n {\n 'williamboman/mason.nvim',\n build = function()\n pcall(vim.cmd, 'MasonUpdate')\n end,\n },\n }\n },\n -- Function signatures\n {\n \"ray-x/lsp_signature.nvim\",\n lazy = true,\n opts = {\n bind = true, -- This is mandatory, otherwise border config won't get registered.\n hint_enable = true,\n doc_lines = 0,\n floating_window = false,\n toggle_key = \"<C-h>\",\n select_signature_key = \"<C-l>\",\n floating_window_above_cur_line = true,\n handler_opts = {\n border = \"rounded\"\n }\n }\n },\n}\n-- vim: set shiftwidth=2:\n"},{"alpha_fraction":0.7234042286872864,"alphanum_fraction":0.7446808218955994,"avg_line_length":30.33333396911621,"blob_id":"fb4ca4e1d292d756ca84e64d04d66d6043430802","content_id":"acb7a1eec3bee81c1c093996b459db545d865319","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":94,"license_type":"no_license","max_line_length":37,"num_lines":3,"path":"/home/.config/nvim/after/ftplugin/mail.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"vim.opt_local.textwidth = 80\nvim.opt_local.formatoptions = \"tcqj]\"\nvim.opt_local.spell = true\n"},{"alpha_fraction":0.6006628274917603,"alphanum_fraction":0.6043910384178162,"avg_line_length":26.12359619140625,"blob_id":"facca32930dad02906f1c7450a1cac5901dad4a5","content_id":"c0f50c59c299df4def9eb794310c110784633bec","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2414,"license_type":"no_license","max_line_length":82,"num_lines":89,"path":"/home/.config/papis/scripts/papis-bibfile","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"#! /usr/bin/env python3\n# -*- coding: utf-8 -*-\n# papis-short-help: Convert zotero library to papis library\n# Copyright 2017 Alejandro Gallo. GPLv3\nimport os\nimport sys\n\nfrom bibtexparser.bparser import BibTexParser\n\nimport papis.api\nimport papis.bibtex\nimport papis.commands\nimport papis.commands.add as papis_add\nimport papis.config\nimport papis.utils\n\nimport argparse\n\npars = argparse.ArgumentParser(description=\"Import bibfile to papis library\")\npars.add_argument(\"bibfile\", type=str)\npars.add_argument(\"--lib\", type=str)\n\nargumetns = pars.parse_args()\nbib_file = argumetns.bibfile\n\n\ndef usage():\n print(\"Usage: papis bibfile bibfile --lib\")\n\n\nif not os.path.exists(bib_file):\n print(\"ERROR: Bib file (%s) not found!\" % bib_file)\n usage()\n sys.exit(1)\n\nparser = BibTexParser()\nparser.ignore_nonstandard_types = False\n\n# entries = parser.parse(bib_file)\nwith open(bib_file) as bibtex_file:\n bib_obj = parser.parse_file(bibtex_file)\n\nentries = bib_obj.entries\n\n\ndef add(ref_data, pdf=None):\n\n if pdf_file is not None:\n papis_add.run(paths=[pdf], data=ref_data, git=True)\n else:\n papis_add.run(paths=[], data=ref_data, git=True)\n\n\ncwd = os.getcwd()\n\n# Set the library\nif argumetns.lib:\n papis.api.set_lib_from_name(argumetns.lib)\n print(f\"library {argumetns.lib}\")\n\nfor entry in entries:\n for basic_field in [\"ref\", \"author\", \"title\"]:\n if basic_field not in entry.keys():\n if basic_field == \"ref\":\n entry[basic_field] = entry[\"ID\"]\n elif basic_field == \"author\":\n entry[basic_field] = entry[\"editor\"]\n else:\n entry[basic_field] = papis.utils.input(\n \"%s Not found, please insert\" % basic_field, default=\"???????\"\n )\n\n print(\"INFO: Processing | bibkey: %s\" % entry.get(\"ref\"))\n print(\" |Author: %s\" % entry.get(\"author\"))\n print(\" | Title: %s\" % entry.get(\"title\"))\n print(\" |\")\n\n pdf_file = None\n\n if \"file\" in entry.keys():\n pdf_file = entry.get(\"file\").split(\":\")[1]\n pdf_file = os.path.join(cwd, pdf_file)\n print(\"\\tINFO: File field detected (%s)\" % pdf_file)\n if not os.path.exists(pdf_file):\n print(\"\\tWARNING: Path (%s) not found! Ignoring it\" % pdf_file)\n del entry[\"file\"]\n pdf_file = None\n\n add(entry, pdf_file)\n"},{"alpha_fraction":0.6992481350898743,"alphanum_fraction":0.7368420958518982,"avg_line_length":21.16666603088379,"blob_id":"4e4df0649408f18820f17e86bf69aa5d79d14aa6","content_id":"6afa722f5da5753c611b9fad63ecfb5c187a140f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":133,"license_type":"no_license","max_line_length":35,"num_lines":6,"path":"/home/.config/nvim/after/ftplugin/python.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"vim.opt_local.textwidth = 80\nvim.opt_local.formatoptions = \"cqj\"\n\nvim.opt.softtabstop = 4\nvim.opt.shiftwidth = 4\nvim.opt.tabstop = 4\n"},{"alpha_fraction":0.5513626933097839,"alphanum_fraction":0.552410900592804,"avg_line_length":27.058822631835938,"blob_id":"8544ffd5f42c268f26b4c230e859cb920560ea93","content_id":"974559d32a09044897b66133b4f19f3e6fa86078","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":954,"license_type":"no_license","max_line_length":80,"num_lines":34,"path":"/home/.config/nvim/lua/plugins/markdown.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"return {\n {\n 'vim-pandoc/vim-pandoc',\n ft = { 'markdown', 'markdown.pandoc', 'pandoc' },\n dependencies = {\n { 'vim-pandoc/vim-pandoc-syntax' },\n { 'godlygeek/tabular' },\n {\n \"iamcco/markdown-preview.nvim\",\n build = function() vim.fn[\"mkdp#util#install\"]() end,\n ft = { 'markdown', 'pandoc', 'markdown.pandoc' }\n }\n },\n config = function()\n vim.cmd(\n [[\n function! g:Open_browser(url)\n \"silent exe 'silent !gnome-www-browser --private-instance ' . a:url . \" &\"\n silent exe 'silent !epiphany --private-instance ' . a:url . \" &\"\n endfunction\n ]]\n )\n\n --[[ local function open_browser(url)\n io.popen(\"epiphany --private-instance \" .. url .. \" &\")\nend ]]\n vim.g.mkdp_browserfunc = 'g:Open_browser'\n\n vim.g.mkdp_filetypes = { 'pandoc', 'markdown', 'markdown.pandoc', 'wiki' }\n vim.g.mkdp_auto_close = false\n end\n },\n}\n-- vim: set shiftwidth=2:\n"},{"alpha_fraction":0.6549249887466431,"alphanum_fraction":0.6640573740005493,"avg_line_length":30.89583396911621,"blob_id":"a2ab559d1ad8a1bd5739d6cd36790f6f4152f0c8","content_id":"ca7e79b491dc60278ebbea9d2e62ed94d8c1dc23","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":1533,"license_type":"no_license","max_line_length":78,"num_lines":48,"path":"/home/.password-store/.extensions/get_pass.bash","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"#!/usr/bin/env bash\n# pass get - Password Store Extension (https://www.passwordstore.org/)\n# Copyright (C) 2020 James Patrick\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program. If not, see <http://www.gnu.org/licenses/>.\n#\n\n\nPASSWORD_STORE_DIR=\"${PASSWORD_STORE_DIR:-$HOME/.password-store}\"\n\ncmd_get_pass_usage() {\n cat <<-_EOF\nUsage:\n $PROGRAM get_pass pass_name\n Grabs the pass based on rules for Browserpass.\n 1. match \"key:value\" where key, either pass, password, or secret\n 2. if no match is present default to the first line.\n\n https://github.com/browserpass/browserpass-extension\n\n Options:\n Nada.\n_EOF\n exit 0\n}\n\n\ncmd_get_user(){\n local pass_name=\"$1\" val backup\n val=$(pass get \"(pass|password|secret)\" \"$pass_name\")\n backup=$(cmd_show \"$pass_name\" | head -1) \n echo \"${val:-$backup}\"\n}\n\n[[ \"$1\" == \"help\" || \"$1\" == \"--help\" || \"$1\" == \"-h\" ]] && cmd_get_user_usage\n[[ \"$#\" != \"1\" ]] && cmd_get_user_usage\ncmd_get_user \"$@\"\n\n\n"},{"alpha_fraction":0.7411003112792969,"alphanum_fraction":0.8155339956283569,"avg_line_length":13.714285850524902,"blob_id":"e9a9e759c0b3591e8eabed79ba308020ce779bfe","content_id":"1954d83060778a359cd5254f385168007e2d6bcb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"INI","length_bytes":309,"license_type":"no_license","max_line_length":42,"num_lines":21,"path":"/home/.config/fuzzel/fuzzel.ini","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"[main]\nfont=Inter Nerd Font:size=14:weight=medium\nicon-theme=Paper\ndpi-aware=auto\n#fields=filename,name,generic\nterminal=foot\nfuzzy=yes\ninner-pad=20\nline-height=25\n\n[colors]\nbackground=3b4252dd\ntext=d8dee9ff\nselection=5e81acff\nselection-text=eceff4ff\nmatch=ebcb8bff\nborder=5e81acff\n\n[border]\nwidth=4\nradius=4\n"},{"alpha_fraction":0.5931363105773926,"alphanum_fraction":0.6252727508544922,"avg_line_length":27.32022476196289,"blob_id":"6ae5771370cae3326ba63dc3ed2e3916d9460527","content_id":"e7dd3f1e0bce57432e1229f213a93272edf174b2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":5041,"license_type":"no_license","max_line_length":192,"num_lines":178,"path":"/home/.bashrc","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"#\n# ~/.bashrc\n#\n\n# If not running interactively, don't do anything\n[[ $- != *i* ]] && return\n\n# get current branch in git repo\nfunction parse_git_branch() {\n\tBRANCH=`git branch 2> /dev/null | sed -e '/^[^*]/d' -e 's/* \\(.*\\)/\\1/'`\n\tif [ ! \"${BRANCH}\" == \"\" ]\n\tthen\n\t\tSTAT=`parse_git_dirty`\n\t\techo \"[${BRANCH}${STAT}]\"\n\telse\n\t\techo \"\"\n\tfi\n}\n\n# get current status of git repo\nfunction parse_git_dirty {\n\tstatus=`git status 2>&1 | tee`\n\tdirty=`echo -n \"${status}\" 2> /dev/null | grep \"modified:\" &> /dev/null; echo \"$?\"`\n\tuntracked=`echo -n \"${status}\" 2> /dev/null | grep \"Untracked files\" &> /dev/null; echo \"$?\"`\n\tahead=`echo -n \"${status}\" 2> /dev/null | grep \"Your branch is ahead of\" &> /dev/null; echo \"$?\"`\n\tnewfile=`echo -n \"${status}\" 2> /dev/null | grep \"new file:\" &> /dev/null; echo \"$?\"`\n\trenamed=`echo -n \"${status}\" 2> /dev/null | grep \"renamed:\" &> /dev/null; echo \"$?\"`\n\tdeleted=`echo -n \"${status}\" 2> /dev/null | grep \"deleted:\" &> /dev/null; echo \"$?\"`\n\tbits=''\n\tif [ \"${renamed}\" == \"0\" ]; then\n\t\tbits=\">${bits}\"\n\tfi\n\tif [ \"${ahead}\" == \"0\" ]; then\n\t\tbits=\"*${bits}\"\n\tfi\n\tif [ \"${newfile}\" == \"0\" ]; then\n\t\tbits=\"+${bits}\"\n\tfi\n\tif [ \"${untracked}\" == \"0\" ]; then\n\t\tbits=\"?${bits}\"\n\tfi\n\tif [ \"${deleted}\" == \"0\" ]; then\n\t\tbits=\"x${bits}\"\n\tfi\n\tif [ \"${dirty}\" == \"0\" ]; then\n\t\tbits=\"!${bits}\"\n\tfi\n\tif [ ! \"${bits}\" == \"\" ]; then\n\t\techo \" ${bits}\"\n\telse\n\t\techo \"\"\n\tfi\n}\n\nexport PS1=\"[\\[\\e[32m\\]\\u\\[\\e[m\\]\\[\\e[32m\\]@\\[\\e[m\\]\\[\\e[32m\\]\\h\\[\\e[m\\]]:\\[\\e[36m\\]\\W\\[\\e[m\\]\\[\\e[31m\\]\\`parse_git_branch\\`\\[\\e[m\\]$ \"\n\n# Set language for the console\nexport LANG=\"en_US.UTF-8\"\n\nexport EDITORCMD=\"nvim-qt\"\nexport EDITOR=\"nvim\"\n\n# check the window size after each command and, if necessary,\n# update the values of LINES and COLUMNS\nshopt -s checkwinsize\n\n# Virtual Environment\nexport WORKON_HOME=~/.virtualenvs\nsource /usr/bin/virtualenvwrapper.sh\n\nsource \"$HOME/.homesick/repos/homeshick/homeshick.sh\"\nsource \"$HOME/.homesick/repos/homeshick/completions/homeshick-completion.bash\"\n\n# if [ $TILIX_ID ] || [ $VTE_VERSION ]; then\n# source /etc/profile.d/vte.sh\n# fi\n\n# F*EX\nexport PATH=\"$HOME/.fex/bin:$PATH\"\nsource $HOME/.local/bin/fexdox-completion.bash\n\neval $(dircolors ~/.dircolors)\n\nexport PATH=\"$HOME/bin:$PATH\"\n\n# Pyenv\nexport PYENV_ROOT=\"$HOME/.pyenv\"\nexport PATH=\"$PYENV_ROOT/bin:$PATH\"\neval \"$(pyenv init --path)\"\nif command -v pyenv 1>/dev/null 2>&1; then\n eval \"$(pyenv init -)\"\nfi\n\nexport PATH=\"$HOME/.local/bin:$PATH\"\n\n# Enable tab-completion for directories after variables\nshopt -s direxpand\n\n# br\n# source /home/tapia/.config/broot/launcher/bash/br\nalias br=broot\n\n# Generic colourizer\n[[ -s \"/etc/profile.d/grc.bashrc\" ]] && source /etc/profile.d/grc.bashrc\n\nalias ls='ls --color=auto'\nalias grep='grep --color=auto'\nalias diff='diff --color=auto'\n\nexport LESS_TERMCAP_mb=$'\\e[1;32m'\nexport LESS_TERMCAP_md=$'\\e[1;32m'\nexport LESS_TERMCAP_me=$'\\e[0m'\nexport LESS_TERMCAP_se=$'\\e[0m'\nexport LESS_TERMCAP_so=$'\\e[01;33m'\nexport LESS_TERMCAP_ue=$'\\e[0m'\nexport LESS_TERMCAP_us=$'\\e[1;4;31m'\n\n# Force xterm-color on ssh sessions\nalias ssh='TERM=xterm-256color ssh'\n\nif [ \"$TERM\" = \"xterm\" ]; then\n export TERM=xterm-256color\nfi\n\n# set PROMPT_COMMAND\nPROMPT_COMMAND=${PROMPT_COMMAND:+$PROMPT_COMMAND; }'printf \"\\033]0;%s@%s:%s\\007\" \"${USER}\" \"${HOSTNAME%%.*}\" \"${PWD/#$HOME/\\~}\"'\n\neval \"$(starship init bash)\"\n\nalias obs=\"QT_QPA_PLATFORM=xcb obs\"\n\n# Tmux with lf\n# alias mc='tmux new-session \\; send-keys lf C-m \\; split -h \\; send-keys lf C-m'\n\n\n# Install packages using yay (change to pacman/AUR helper of your choice)\nfunction yayinstall() {\n yay -Slq | fzf -q \"$1\" -m --preview 'yay -Si {1}'| xargs -ro yay -S\n}\n\n################################################\n# FZF config\n[ -f ~/.fzf.bash ] && source ~/.fzf.bash\n\nexport FZF_DEFAULT_OPTS='--color=bg+:#3B4252,bg:#2E3440,spinner:#81A1C1,hl:#616E88,fg:#D8DEE9,header:#616E88,info:#81A1C1,pointer:#d08770,marker:#d08770,fg+:#D8DEE9,prompt:#81A1C1,hl+:#81A1C1'\nexport FZF_ALT_C_OPTS='--height=40% --min-height=20'\nexport FZF_CTRL_T_OPTS='--height=40% --min-height=20'\n\n# Default commands\nexport FZF_DEFAULT_COMMAND=\"fd\"\nexport FZF_CTRL_T_COMMAND=\"$FZF_DEFAULT_COMMAND\"\nexport FZF_ALT_C_COMMAND=\"fd -t d\"\n\nsource ${HOME}/.local/share/fzf/fzf-git.bash\n\n\n# Pyhton colors\nnorm=\"$(printf '\\033[0m')\" #returns to \"normal\"\nbold=\"$(printf '\\033[0;1m')\" #set bold\nred=\"$(printf '\\033[0;31m')\" #set red\nboldyellowonblue=\"$(printf '\\033[0;1;33;44m')\"\nboldyellow=\"$(printf '\\033[0;1;33m')\"\nboldred=\"$(printf '\\033[0;1;31m')\" #set bold, and set red.\n\ncopython() {\n python $@ 2>&1 | sed -e \"s/Traceback/${boldyellowonblue}&${norm}/g\" \\\n -e \"s/File \\\".*\\.py\\\".*$/${boldyellow}&${norm}/g\" \\\n -e \"s/\\, line [[:digit:]]\\+/${boldred}&${norm}/g\"\n }\n\n\n# BEGIN_KITTY_SHELL_INTEGRATION\n# if test -n \"$KITTY_INSTALLATION_DIR\" -a -e \"$KITTY_INSTALLATION_DIR/shell-integration/bash/kitty.bash\"; then source \"$KITTY_INSTALLATION_DIR/shell-integration/bash/kitty.bash\"; fi\n# END_KITTY_SHELL_INTEGRATION\n\nsource ${HOME}/bin/fzf-beet.bash\n\nexport JULIA_NUM_THREADS=4\n"},{"alpha_fraction":0.5046461820602417,"alphanum_fraction":0.5207290649414062,"avg_line_length":23.120689392089844,"blob_id":"ca7d3fde70d6f218545b96a34676484ac938c4a5","content_id":"0fa232583cd94fc5a6f13cee59a09be6f471e805","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2799,"license_type":"no_license","max_line_length":91,"num_lines":116,"path":"/home/.config/nwg-wrapper/plan.py","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\nfrom datetime import date\nfrom textwrap import fill, wrap, shorten\nfrom os.path import expandvars\nimport ruamel.yaml as yaml\nfrom pandas import DateOffset\n\nMONTHS = {\n 1:\"Januar\",\n 2:\"Februar\",\n 3:\"März\",\n 4:\"April\",\n 5:\"Mai\",\n 6:\"Juni\",\n 7:\"Juli\",\n 8:\"August\",\n 9:\"September\",\n 10:\"Oktober\",\n 11:\"November\",\n 12:\"Dezember\"\n}\n\n\ndef main():\n # Read plan\n with open(expandvars(\"$HOME/Nextcloud/five_year_plan.yaml\"), \"r\") as stream:\n plan = yaml.safe_load(stream)\n\n out = format_output(plan)\n print(out)\n\n\ndef format_output(data):\n \"\"\"Format to correct pango markup.\n\n Parameters\n ----------\n data : TODO\n\n Returns\n -------\n TODO\n\n \"\"\"\n width = 34\n curr_year = date.today().year\n curr_month = date.today().month\n start_date = date.today() - DateOffset(months=2)\n start_year = start_date.year\n dates = [start_date + DateOffset(months=k) for k in range(36)]\n iter_dates = [(d.year, d.month) for d in dates]\n\n prev_year = dates[0].year\n list_plan = '<tt><b> ' + f\"{start_date.year}\".ljust(width) + \"</b></tt>\\n\"\n\n num_elements = 0\n max_elements = 30\n\n for year_i, month_i in iter_dates:\n if year_i > prev_year:\n list_plan += \"\\n\" + \"<tt><b> \" + f\"{year_i}\".ljust(width) + \"</b></tt>\\n\"\n prev_year += 1\n\n elements_i = data[year_i][month_i-1][MONTHS[month_i]]\n\n if month_i == curr_month and year_i == curr_year:\n color_month = \"#bf616a\"\n else:\n color_month = \"#eceff4\"\n\n if year_i == start_year:\n color_year = \"#81a1c1\"\n elif year_i == start_year + 1:\n color_year = \"#ebcb8b\"\n else:\n color_year = \"#a3be8c\"\n\n month_str = shorten(f\"{MONTHS[month_i]}\", 3, placeholder=\"\") + \" \"\n month_str = f'<span face=\"monospace\" foreground=\"{color_month}\">{month_str}</span>'\n\n list_year = []\n\n if elements_i:\n for ele_i in elements_i:\n entry_month = shorten(str(ele_i), width)\n\n list_year.append(entry_month)\n num_elements += 1\n else:\n entry_month = \"\"\n list_year.append(entry_month)\n num_elements += 1\n\n start = '<tt> </tt>'\n for l, e in enumerate(list_year):\n month_entry = f'<span foreground=\"{color_year}\">{e}</span>'\n if l > 0:\n list_plan += f\"{start}{month_entry}\\n\"\n else:\n list_plan += f\"{month_str}{month_entry}\\n\"\n\n if num_elements >= max_elements:\n break\n\n\n base = f\"\"\"<span face=\"sans\">\n<span foreground=\"#eceff4\">\n{list_plan[:-1]}\n</span>\n</span>\"\"\"\n\n return base\n\n\nif __name__ == \"__main__\":\n main()\n"},{"alpha_fraction":0.48847925662994385,"alphanum_fraction":0.5115207433700562,"avg_line_length":15.538461685180664,"blob_id":"72567ddb9b606e50930a7998adc83bac46c3bc86","content_id":"70672ea5b8337732abe607912daabffe85970684","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":217,"license_type":"no_license","max_line_length":77,"num_lines":13,"path":"/home/.local/share/fzf/fzf-fex.bash","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"#!/usr/bin/env bash\n\n# GIT heart Fex\n# -------------\n\nfzf-down() {\n fzf --height 60% --min-height 20 --border --bind ctrl-/:toggle-preview \"$@\"\n}\n\n_fl() {\n fexdox -i tapia -l |\n fzf-down -m --ansi --nth 2..,..\n}\n\n\n"},{"alpha_fraction":0.47816091775894165,"alphanum_fraction":0.48521071672439575,"avg_line_length":30.521739959716797,"blob_id":"c56672da4a5d7c9172c2af8a4b2dbeeca950499e","content_id":"7da509919ad8b4b8b9269aae06a8e29425418259","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":6525,"license_type":"no_license","max_line_length":100,"num_lines":207,"path":"/home/.config/nvim/lua/plugins/cmp.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"return {\n {\n 'hrsh7th/nvim-cmp',\n name = \"nvim-cmp\",\n event = { \"BufReadPost\", \"BufNewFile\" },\n dependencies = {\n { \"danymat/neogen\" },\n { 'hrsh7th/cmp-buffer', },\n { 'hrsh7th/cmp-omni', },\n { 'hrsh7th/cmp-path', },\n { 'hrsh7th/cmp-nvim-lsp', },\n { 'hrsh7th/cmp-nvim-lsp-signature-help', },\n { 'hrsh7th/cmp-cmdline', },\n { \"davidsierradz/cmp-conventionalcommits\", },\n { 'quangnguyen30192/cmp-nvim-ultisnips', },\n { 'rose-pine/neovim' },\n { 'windwp/nvim-autopairs' },\n },\n -- Configuration\n config = function()\n local cmp = require('cmp')\n local cmp_select_opts = { behavior = cmp.SelectBehavior.Select }\n local cmp_ultisnips_mappings = require('cmp_nvim_ultisnips.mappings')\n\n -- Define mappings for cmp\n local neogen = require('neogen')\n local cmp_mappings = {\n ['<C-p>'] = cmp.mapping.select_prev_item(cmp_select_opts),\n ['<C-n>'] = cmp.mapping.select_next_item(cmp_select_opts),\n ['<C-Space>'] = cmp.mapping(function()\n if cmp.visible() then\n print(\"here 1\")\n cmp.confirm({ select = true, behavior = 'replace' })\n else\n vim.fn[\"UltiSnips#ExpandSnippet\"]()\n end\n end,\n { \"i\", \"s\" }\n ),\n -- ['<C-Space>'] = cmp.mapping.complete(cmp_select),\n [\"<C-j>\"] = cmp.mapping(\n function(fallback)\n if neogen.jumpable() then\n neogen.jump_next()\n else\n cmp_ultisnips_mappings.jump_forwards(fallback)\n end\n end,\n { \"i\", \"s\" }\n ),\n [\"<C-z>\"] = cmp.mapping(\n function(fallback)\n if neogen.jumpable(true) then\n neogen.jump_prev()\n else\n cmp_ultisnips_mappings.jump_backwards(fallback)\n end\n end,\n { \"i\", \"s\" }\n ),\n ['<C-b>'] = cmp.mapping.scroll_docs(-4),\n ['<C-f>'] = cmp.mapping.scroll_docs(4),\n ['<C-e>'] = cmp.mapping.abort(),\n }\n\n -- Add parenthesis automatically after functions\n local cmp_autopairs = require('nvim-autopairs.completion.cmp')\n cmp.event:on(\n 'confirm_done',\n cmp_autopairs.on_confirm_done()\n )\n\n -- Define colors for the suggestion menu of nvim-cmp\n local p = require('rose-pine.palette')\n\n vim.api.nvim_set_hl(0, 'CmpItemKindVariable', { fg = p.foam })\n vim.api.nvim_set_hl(0, 'CmpItemKindClass', { fg = p.gold })\n vim.api.nvim_set_hl(0, 'CmpItemKindInterface', { fg = p.gold })\n vim.api.nvim_set_hl(0, 'CmpItemKindFunction', { fg = p.iris })\n vim.api.nvim_set_hl(0, 'CmpItemKindMethod', { fg = p.iris })\n vim.api.nvim_set_hl(0, 'CmpItemKindSnippet', { fg = p.iris })\n vim.api.nvim_set_hl(0, 'CmpItemKindKeyword', { fg = p.subtle })\n vim.api.nvim_set_hl(0, 'CmpItemKindText', { fg = p.subtle })\n\n local cmp_config = {\n -- Define sources to be used\n sources = {\n {\n name = \"nvim_lsp\",\n priority = 9,\n keyword_length = 1,\n -- Disable source for comments\n entry_filter = function(entry, ctx)\n local context = require 'cmp.config.context'\n return not context.in_treesitter_capture(\"comment\")\n and not context.in_syntax_group(\"Comment\")\n end\n },\n { name = 'omni' },\n {\n name = \"ultisnips\",\n priority = 10,\n -- Disable source for comments\n entry_filter = function(entry, ctx)\n local context = require 'cmp.config.context'\n return not context.in_treesitter_capture(\"comment\")\n and not context.in_syntax_group(\"Comment\")\n end\n },\n {\n name = \"path\",\n option = { trailin_slash = true },\n priority = 4\n },\n { name = \"latex_symbols\", priority = 2 },\n {\n name = 'buffer',\n keyword_length = 3,\n option = {\n get_bufnrs = function()\n local buf = vim.api.nvim_get_current_buf()\n local byte_size = vim.api.nvim_buf_get_offset(buf, vim.api.nvim_buf_line_count(buf))\n if byte_size > 1024 * 1024 then -- 1 Megabyte max\n return {}\n end\n return { buf }\n end\n }\n },\n },\n mapping = cmp_mappings,\n snippet = {\n expand = function(args)\n vim.fn[\"UltiSnips#Anon\"](args.body)\n end,\n },\n experimental = {\n ghost_text = { hl_group = 'DevIconCMake' },\n },\n performance = {\n max_view_entries = 40,\n fetching_timeout = 100,\n },\n formatting = {\n fields = { 'abbr', 'menu', 'kind' },\n format = function(entry, item)\n local short_name = {\n nvim_lsp = 'LSP',\n nvim_lua = 'nvim'\n }\n\n local menu_name = short_name[entry.source.name] or entry.source.name\n\n item.menu = string.format('[%s]', menu_name)\n return item\n end,\n },\n sorting = {\n comparators = {\n cmp.config.compare.sort_text,\n cmp.config.compare.offset,\n cmp.config.compare.exact,\n cmp.config.compare.score,\n cmp.config.compare.kind,\n cmp.config.compare.length,\n cmp.config.compare.order,\n }\n },\n window = {\n completion = {\n winhighlight = \"Normal:StatusLineNC,CursorLine:Substitute\",\n },\n documentation = {\n winhighlight = 'FloatBorder:WildMenu',\n border = \"rounded\",\n }\n },\n\n -- `/` cmdline setup.\n cmp.setup.cmdline('/', {\n mapping = cmp.mapping.preset.cmdline(),\n sources = {\n { name = 'buffer' }\n }\n }),\n\n -- `:` cmdline setup.\n cmp.setup.cmdline(':', {\n mapping = cmp.mapping.preset.cmdline(),\n sources = cmp.config.sources({\n { name = 'path' }\n }, {\n { name = 'cmdline', keyword_length = 2 }\n })\n }),\n }\n\n cmp.setup(cmp_config)\n end\n },\n {\n \"kdheepak/cmp-latex-symbols\",\n ft = \"julia\",\n dependencies = { \"nvim-cmp\" }\n },\n}\n-- vim: set shiftwidth=2:\n"},{"alpha_fraction":0.6866196990013123,"alphanum_fraction":0.6901408433914185,"avg_line_length":19.285715103149414,"blob_id":"5d9057e8c3450251dd530207e3f889d75129c2b8","content_id":"a7d3005c53805fdc05352bdd9d177728d5da2f8b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":284,"license_type":"no_license","max_line_length":49,"num_lines":14,"path":"/home/.bash_profile","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"#\n# ~/.bash_profile\n#\n\n[[ -f ~/.bashrc ]] && . ~/.bashrc\n\n# Autocompletion for pubs\neval \"$(register-python-argcomplete pubs)\"\n\n#export PATH=\"${PATH}:/opt/anaconda/bin\"\nexport MPA=\"$HOME/Documents/MPA\"\nexport NVIM_GTK_NO_HEADERBAR=1\n\nsource /home/tapia/.config/broot/launcher/bash/br\n"},{"alpha_fraction":0.5376344323158264,"alphanum_fraction":0.5423656105995178,"avg_line_length":30.849315643310547,"blob_id":"cb00d53da1b920e3ccf485f6994a9ae1c7f8f1af","content_id":"79bc4f1931b48114c9b409737606ada7b9ccebe0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":2325,"license_type":"no_license","max_line_length":99,"num_lines":73,"path":"/home/.config/nvim/lua/plugins/python.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"return {\n {\n \"tpope/vim-dispatch\",\n ft = { \"typst\", \"python\", \"fortran\", \"make\" },\n keys = { \"<F5>\", \"<F6>\" },\n config = function()\n -- Execute programs asyncronously\n local function save_and_run_async()\n -- Save file\n vim.cmd.write()\n -- Get filetype\n local ft = vim.bo.filetype\n -- Execute command according to filetype\n local dir = vim.fn.fnameescape(vim.fn.expand(\"%:p:h\"))\n local filename = vim.fn.fnameescape(vim.fn.expand(\"%:p\"))\n\n if ft == \"typst\" then\n vim.cmd('Dispatch -compiler=typst -dir=' .. dir .. ' typst compile ' .. filename)\n elseif ft == \"fortran\" then\n vim.cmd('Dispatch -compiler=abaqus -dir=' .. dir .. ' abq2022 make library=' .. filename)\n elseif ft == \"python\" then\n vim.cmd('Dispatch -compiler=python -dir=' .. dir .. ' python ' .. filename)\n end\n end\n\n local function debug_async()\n -- Save file\n vim.cmd.write()\n -- Get filetype\n local ft = vim.bo.filetype\n -- Execute command according to filetype\n local dir = vim.fn.fnameescape(vim.fn.expand(\"%:p:h\"))\n local filename = vim.fn.fnameescape(vim.fn.expand(\"%:p\"))\n\n if ft == \"python\" then\n vim.cmd('Start -dir=' .. dir .. ' python -m pdb ' .. filename)\n end\n end\n\n vim.keymap.set(\"n\", \"<F5>\", save_and_run_async)\n vim.keymap.set(\"n\", \"<F6>\", debug_async)\n -- Deactivate default mappings\n vim.g.dispatch_no_maps = 1\n vim.g.dispatch_no_tmux_start = 1\n end,\n },\n {\n 'untitled-ai/jupyter_ascending.vim',\n event = \"BufEnter *.sync.py\",\n dependencies = {\n { 'kana/vim-textobj-user' },\n { 'GCBallesteros/vim-textobj-hydrogen' },\n },\n keys = {\n { \"<leader><leader>x\", \"<Plug>JupyterExecute\" },\n { \"<leader><leader>X\", \"<Plug>JupyterExecuteAll\" },\n { \"<leader><leader>r\", \"<Plug>JupyterRestart\" },\n },\n config = function()\n -- Delete default key bindings\n vim.keymap.del(\"n\", \"<space><space>x\")\n vim.keymap.del(\"n\", \"<space><space>X\")\n vim.keymap.del(\"n\", \"<space><space>r\")\n end\n },\n -- {\n -- 'stevearc/overseer.nvim',\n -- opts = {\n -- templates = { \"builtin\", \"user.python_build\" }\n -- },\n -- }\n}\n-- vim: set shiftwidth=2:\n"},{"alpha_fraction":0.6427207589149475,"alphanum_fraction":0.6622911691665649,"avg_line_length":28.716312408447266,"blob_id":"4d2f725416b0f459376c2b193c1ce7b4de631ea1","content_id":"7274b8374edd74030d1547fa0339fdc5fb28f74f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":4194,"license_type":"no_license","max_line_length":192,"num_lines":141,"path":"/home/.zshrc","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"# The following lines were added by compinstall\n\nzstyle ':completion:*' completer _expand _complete _ignored _approximate\nzstyle ':completion:*' completions 1\nzstyle ':completion:*' glob 1\nzstyle ':completion:*' list-colors “${(s.:.)LS_COLORS}”\nzstyle ':completion:*' group-name ''\nzstyle ':completion:*' max-errors 2\nzstyle ':completion:*' substitute 1\nzstyle ':completion:*' file-sort modification\nzstyle ':completion:*' verbose true\nzstyle ':completion:*' menu select\nzstyle :compinstall filename '/home/tapia/.zshrc'\n\nzmodload zsh/complist\nbindkey -M menuselect 'h' vi-backward-char\nbindkey -M menuselect 'k' vi-up-line-or-history\nbindkey -M menuselect 'l' vi-forward-char\nbindkey -M menuselect 'j' vi-down-line-or-history\n\n# Surroundings\nautoload -Uz surround\nzle -N delete-surround surround\nzle -N add-surround surround\nzle -N change-surround surround\nbindkey -M vicmd cs change-surround\nbindkey -M vicmd ds delete-surround\nbindkey -M vicmd ys add-surround\nbindkey -M visual S add-surround\n\n# Completions:\n# - Homeshick\nsource \"$HOME/.homesick/repos/homeshick/homeshick.sh\"\nfpath=($HOME/.homesick/repos/homeshick/completions $fpath)\n# - Pyenv\nfpath=($HOME/.config/zsh/comp $fpath)\n\npath=($HOME/bin $path)\n\nautoload -Uz compinit\n# compinit\nif [ $(date +'%j') != $(date +\"%j\" -r $HOME/.zcompdump) ]; then\n compinit\nelse\n compinit -C\nfi\n\n# FEX\ncompdef _gnu_generic fexsend fexget fexpush \\\n fexpull fexstore fexpack fexzip fexsync \\\n autofex xx xxx sexsend sexget sexxx\n\nautoload -Uz promptinit\npromptinit\n\nautoload -Uz up-line-or-beginning-search down-line-or-beginning-search\nzle -N up-line-or-beginning-search\nzle -N down-line-or-beginning-search\n# End of lines added by compinstall\n# Lines configured by zsh-newuser-install\nHISTFILE=~/.histfile\nHISTSIZE=5000\nSAVEHIST=10000\nbindkey -v\n\nbindkey \"^?\" backward-delete-char\nbindkey \"^w\" backward-delete-word\n\n# Change cursor\n# source \"$HOME/.config/zsh/plugins/cursor_mode\"\n\n# Starship\neval \"$(starship init zsh)\"\n\n# Set language for the console\nexport LANG=\"en_US.UTF-8\"\nexport EDITORCMD=\"nvim-qt\"\nexport EDITOR=\"nvim\"\n\n#----------------------------------------------------------------------\n# Virtual Environment\nexport WORKON_HOME=~/.virtualenvs\n# source /usr/bin/virtualenvwrapper.sh\nexport VIRTUALENVWRAPPER_SCRIPT=/usr/bin/virtualenvwrapper.sh\n# Lazy-load virtualenvwrapper\nsource /usr/bin/virtualenvwrapper_lazy.sh\n\n#----------------------------------------------------------------------\n# Pyenv\nexport PYENV_ROOT=\"$HOME/.pyenv\"\ncommand -v pyenv >/dev/null || path=($PYENV_ROOT/bin $path)\neval \"$(pyenv init -)\"\n\n#----------------------------------------------------------------------\n# F*EX\npath=($HOME/.fex/bin $path)\n\n# Force xterm-color on ssh sessions\nalias ssh='TERM=xterm-256color ssh'\n\nif [ \"$TERM\" = \"xterm\" ]; then\n export TERM=xterm-256color\nfi\n\n#----------------------------------------------------------------------\n# Install packages using yay (change to pacman/AUR helper of your choice)\nfunction yayinstall() {\n yay -Slq | fzf -q \"$1\" -m --preview 'yay -Si {1}'| xargs -ro yay -S\n}\n\n#----------------------------------------------------------------------\n# FZF\nsource /usr/share/fzf/key-bindings.zsh\nsource /usr/share/fzf/completion.zsh\nsource ~/.local/share/fzf/fzf-git.bash\n\n# - Options\nexport FZF_DEFAULT_OPTS='--color=bg+:#3B4252,bg:#2E3440,spinner:#81A1C1,hl:#616E88,fg:#D8DEE9,header:#616E88,info:#81A1C1,pointer:#d08770,marker:#d08770,fg+:#D8DEE9,prompt:#81A1C1,hl+:#81A1C1'\nexport FZF_ALT_C_OPTS='--height=40% --min-height=20'\nexport FZF_CTRL_T_OPTS='--height=40% --min-height=20'\n# Default commands\nexport FZF_DEFAULT_COMMAND=\"fd\"\n# export FZF_DEFAULT_COMMAND=\"bfs\"\nexport FZF_CTRL_T_COMMAND=\"$FZF_DEFAULT_COMMAND\"\nexport FZF_ALT_C_COMMAND=\"fd -t d\"\n# export FZF_ALT_C_COMMAND=\"bfs -type d -nohidden \"\n\n#----------------------------------------------------------------------\n# Colors\nalias ls='ls --color=auto --group-directories-first'\nalias grep='grep --color=auto'\nalias diff='diff --color=auto'\n\nexport JULIA_NUM_THREADS=4\n\nexport MPA=\"$HOME/Documents/MPA\"\nexport NVIM_GTK_NO_HEADERBAR=1\n\nexport PYTHON_KEYRING_BACKEND=keyring.backends.null.Keyring\n\n[ -f ~/.fzf.zsh ] && source ~/.fzf.zsh\n"},{"alpha_fraction":0.5863853693008423,"alphanum_fraction":0.6015127301216125,"avg_line_length":26.88888931274414,"blob_id":"b920678edc1cbf64fb9d57c9816bc1c50d2e59ae","content_id":"25d2bf3d263cc73f5a77957fe6110cacfe519c89","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":2518,"license_type":"no_license","max_line_length":79,"num_lines":90,"path":"/home/.password-store/.extensions/get.bash","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"#!/usr/bin/env bash\n# pass get - Password Store Extension (https://www.passwordstore.org/)\n# Copyright (C) 2020 James Patrick\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program. If not, see <http://www.gnu.org/licenses/>.\n#\n\nR='\\033[0;31m' \nG='\\033[0;32m' \nNC='\\033[0m'\n\nPASSWORD_STORE_DIR=\"${PASSWORD_STORE_DIR:-$HOME/.password-store}\"\n\ncmd_get_usage() {\n cat <<-_EOF\nUsage:\n $PROGRAM get pattern pass_name\n Parses the pass data for lines pulling out the value of browserpass's\n format of \"key:value\". The 'pattern' arg is a case insenitive, extended\n regex using grep -iE.\n\n https://github.com/browserpass/browserpass-extension\n\n Options:\n Nada.\n_EOF\n exit 0\n}\n\n\ncmd_get_assert(){\n test=\"$1\"\n local pattern=\"$2\" expected=\"$3\"\n\n actual=\"$(cmd_get \"$pattern\")\"\n if [[ \"$actual\" == \"$expected\" ]] ; then\n echo -e \"$G ✔ '$actual' == '$expected' $NC\"\n else\n echo -e \"$R ✘ f('$test', '$pattern') → '$actual' != '$expected' $NC\"\n fi\n}\n\ncmd_get_test(){\n cmd_get_assert \"username:value\" \"(user|username|login)\" \"value\"\n cmd_get_assert \" user: whitespace\" \"(user|username|login)\" \"whitespace\"\n\n val=\"multiple:lines\nvalue:pairs\"\n cmd_get_assert \"$val\" \"value\" \"pairs\"\n cmd_get_assert \"Key:capitalization doesn't counts\" \"key\" \\\n \"capitalization doesn't counts\"\n cmd_get_assert \"missing:empty\" \"i don't exist\" \"\"\n\n\n exit 0\n}\n\ncmd_get(){\n local pattern=\"$1\" pass_name=\"$2\"\n\n # valid the regex is valid\n echo | grep -qiE \"$pattern\"\n if [[ \"$?\" == 2 ]] ; then\n >&2 echo -e \"${R}Invalid Pattern:${NC} $pattern\"\n return 1\n fi \n \n echo \"${test:-$(cmd_show \"$pass_name\")}\" \\\n | grep -iE \"$pattern\" \\\n | head -1 \\\n | cut -d ':' -f2- \\\n | sed -e 's/^[ \\t]*//'\n}\n\n\n[[ \"$1\" == \"test\" ]] && cmd_get_test\n[[ \"$1\" == \"help\" || \"$1\" == \"--help\" || \"$1\" == \"-h\" ]] && cmd_get_usage\n[[ \"$#\" != \"2\" ]] && cmd_get_usage\ncmd_get \"$@\"\n\n\n"},{"alpha_fraction":0.45193371176719666,"alphanum_fraction":0.46519336104393005,"avg_line_length":23.45945930480957,"blob_id":"a9787f2465191b0112bb41b9f948abfe57b3e7cf","content_id":"20fbedce07a07334915e1c3927382e7d1c802015","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":905,"license_type":"no_license","max_line_length":81,"num_lines":37,"path":"/home/.config/nvim/lua/plugins/git.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"return {\n -- Fugitive\n {\n 'tpope/vim-fugitive',\n cmd = \"G\",\n keys = {\n { \"<leader>gs\", vim.cmd.Git },\n { \"<leader>gc\", \"<cmd>Git commit<cr>\" },\n },\n },\n -- Gitsigns\n {\n 'lewis6991/gitsigns.nvim',\n config = function(_, opts)\n require(\"gitsigns\").setup {\n on_attach = function(bufnr)\n local gitsigns = require('gitsigns')\n vim.keymap.set(\"n\", \"<leader>gn\",\n function()\n gitsigns.next_hunk({ foldopen = true })\n end\n )\n vim.keymap.set(\"n\", \"<leader>gN\",\n function()\n gitsigns.prev_hunk({ foldopen = true })\n end\n )\n vim.keymap.set(\"n\", \"<leader>gp\",\n gitsigns.preview_hunk\n )\n end\n }\n vim.api.nvim_set_hl(0, 'GitSignsAddLn', { fg = \"#434c5e\", bg = \"#a3be8c\" })\n end\n },\n}\n-- vim: set shiftwidth=2:\n"},{"alpha_fraction":0.7136150002479553,"alphanum_fraction":0.7230046987533569,"avg_line_length":25.625,"blob_id":"63f712d2901fc5751b0fc564f13014da15ecf221","content_id":"47dc5cbc03d9a1751eff9a0c8b107852eaba8dbe","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":213,"license_type":"no_license","max_line_length":32,"num_lines":8,"path":"/home/.config/nvim/after/ftplugin/tex.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"-- Set spelling\nvim.cmd('syntax spell toplevel')\nvim.opt_local.spell = true\n-- Define tex flavor to latex\nvim.g.tex_flavor = 'latex'\n-- Set tab to two-spaces\nvim.opt_local.shiftwidth = 2\nvim.opt_local.tabstop = 2\n"},{"alpha_fraction":0.49486976861953735,"alphanum_fraction":0.5059195160865784,"avg_line_length":28.465116500854492,"blob_id":"417e236a0237f91ab6b7ff65959b21f412bb2024","content_id":"7ef3d01320dd269097d420c1a17de133c31e2e0f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":2534,"license_type":"no_license","max_line_length":94,"num_lines":86,"path":"/home/.config/nvim/lua/plugins/treesitter.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"return {\n {\n 'nvim-treesitter/nvim-treesitter',\n event = { \"BufReadPost\", \"BufNewFile\" },\n build = \":TSUpdate\",\n dependencies = { \"nvim-treesitter/nvim-treesitter-textobjects\" },\n opts = {\n -- A list of parser names, or \"all\" (the five listed parsers should always be installed)\n ensure_installed = {\n \"bash\",\n \"bibtex\",\n \"comment\",\n \"css\",\n \"dockerfile\",\n \"javascript\",\n \"json\",\n \"julia\",\n \"lua\",\n \"python\",\n \"query\",\n \"toml\",\n \"vim\",\n \"vimdoc\",\n \"yaml\",\n \"yuck\",\n },\n\n -- Install parsers synchronously (only applied to `ensure_installed`)\n sync_install = false,\n auto_install = false,\n highlight = {\n enable = true,\n additional_vim_regex_highlighting = false,\n },\n rainbow = {\n enable = true,\n colors = {\n \"#eceff4\",\n \"#88c0d0\",\n \"#ebcb8b\",\n \"#81a1c1\",\n \"#d08770\",\n },\n -- Highlight also non-parentheses delimiters, boolean or table: lang -> boolean\n extended_mode = false,\n -- Do not enable for files with more than 1000 lines, int\n max_file_lines = 1000,\n },\n textobjects = {\n select = {\n enable = true,\n -- Automatically jump forward to textobj, similar to targets.vim\n lookahead = true,\n keymaps = {\n -- You can use the capture groups defined in textobjects.scm\n [\"af\"] = \"@function.outer\",\n [\"if\"] = \"@function.inner\",\n [\"ac\"] = \"@class.outer\",\n [\"ic\"] = { query = \"@class.inner\", desc = \"Select inner part of a class region\" },\n },\n selection_modes = {\n ['@parameter.outer'] = 'v', -- charwise\n ['@function.outer'] = 'V', -- linewise\n ['@class.outer'] = 'V', -- blockwise\n },\n include_surrounding_whitespace = false,\n },\n },\n },\n config = function(_, opts)\n require(\"nvim-treesitter.configs\").setup(opts)\n -- Foldings\n vim.opt.foldmethod = \"expr\"\n vim.opt.foldexpr = \"nvim_treesitter#foldexpr()\"\n vim.opt.foldnestmax = 2\n vim.opt.foldenable = false\n\n vim.cmd('hi pythonTSParameter guifg=#b48ead')\n vim.cmd('hi TSConstant guifg=#ebcb8b')\n\n end\n },\n { \"nvim-treesitter/nvim-treesitter-textobjects\", },\n { 'nvim-treesitter/playground' },\n}\n-- vim: set shiftwidth=2:\n"},{"alpha_fraction":0.5164835453033447,"alphanum_fraction":0.5252183675765991,"avg_line_length":28.575000762939453,"blob_id":"edc4298f60815d535c736fce3333ba6ffeb71712","content_id":"54f6575b5d7b900519c5aea32514074e45a1c033","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":3549,"license_type":"no_license","max_line_length":88,"num_lines":120,"path":"/home/.config/nvim/lua/plugins/latex.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"return {\n -- Integration with latex\n {\n 'lervag/vimtex',\n ft = { \"tex\", \"cls\", \"sty\", \"tikz\" },\n dependencies = { \"hrsh7th/nvim-cmp\" },\n keys = {\n { \"<localleader>ll\", \"<Plug>(vimtex-compile-ss)\" },\n { \"<localleader>ll\", \"<Plug>(vimtex-compile-selected)\", mode = \"v\" },\n { \"<localleader>lv\", \"<Plug>(vimtex-view)\" },\n { \"<localleader>lo\", \"<Plug>(vimtex-compile-output)\" },\n { \"<localleader>rf\", \"<cmd>VimtexRefreshFolds<cr>\" },\n },\n config = function()\n vim.g.tex_flavor = 'latex'\n\n -- Set autocompletion\n require('cmp').setup.buffer {\n formatting = {\n format = function(entry, vim_item)\n vim_item.menu = ({\n omni = (vim.inspect(vim_item.menu):gsub('%\"', \"\")),\n buffer = \"[Buffer]\",\n -- formatting for other sources\n })[entry.source.name]\n return vim_item\n end,\n },\n sources = {\n { name = 'omni', priority = 9 },\n { name = 'buffer' },\n { name = \"path\", priority = 4 },\n {\n name = \"ultisnips\",\n priority = 10,\n -- Disable source for comments\n entry_filter = function(entry, ctx)\n local context = require 'cmp.config.context'\n return not context.in_treesitter_capture(\"comment\")\n and not context.in_syntax_group(\"Comment\")\n end\n },\n -- other sources\n },\n }\n\n -- Set options for vimtex\n vim.g.vimtex_compiler_latexmk = {\n out_dir = 'out',\n aux_dir = '.aux',\n callback = 1,\n continuous = 0,\n executable = 'latexmk',\n options = { '-verbose',\n '-shell-escape',\n '-file-line-error',\n '-synctex=1',\n '-interaction=nonstopmode',\n },\n }\n\n vim.g.vimtex_compiler_latexmk_engines = { _ = '-lualatex' }\n\n vim.g.vimtex_complete_enabled = 1\n vim.g.vimtex_complete_close_braces = 0\n vim.g.vimtex_complete_ignore_case = 1\n vim.g.vimtex_complete_smart_case = 1\n vim.g.vimtex_fold_enabled = 1\n\n if vim.fn.executable('bibtexparser') then\n vim.g.vimtex_parser_bib_backend = 'bibtexparser'\n end\n\n vim.g.vimtex_syntax_conceal = {\n accents = 1,\n ligatures = 0,\n cites = 1,\n fancy = 0,\n spacing = 0,\n greek = 0,\n math_bounds = 0,\n math_delimiters = 0,\n math_fracs = 0,\n math_super_sub = 0,\n math_symbols = 1,\n sections = 0,\n styles = 1,\n }\n\n -- vim.l.concealcursor = ''\n\n vim.g.vimtex_indent_enabled = true\n vim.g.vimtex_indent_on_ampersands = false\n vim.g.vimtex_indent_bib_enabled = false\n vim.g.vimtex_fold_bib_enabled = false\n\n vim.g.vimtex_imaps_leader = '#'\n vim.g.vimtex_quickfix_method = 'latexlog'\n vim.g.matchup_override_vimtex = true\n vim.g.vimtex_compiler_progname = vim.env.HOME .. '/.virtualenvs/py3neovim/bin/nvr'\n\n vim.g.vimtex_view_method = 'zathura'\n vim.g.vimtex_view_forward_search_on_start = true\n\n vim.g.vimtex_echo_verbose_input = 0\n\n vim.g.vimtex_quickfix_autoclose_after_keystrokes = 2\n vim.g.vimtex_quickfix_open_on_warning = 0\n\n -- Delimiter modifiers\n vim.g.vimtex_delim_toggle_mod_list = {\n { '\\\\left', '\\\\right' },\n { '\\\\mleft', '\\\\mright' },\n }\n end\n },\n -- Transfor latex symbols to unicode\n { 'joom/latex-unicoder.vim' },\n}\n-- vim: set shiftwidth=2:\n"},{"alpha_fraction":0.5978915691375732,"alphanum_fraction":0.6069276928901672,"avg_line_length":26.625,"blob_id":"b434a92ab11395af34a200267a8c35b7f8265731","content_id":"c36d180fc0cba7b05454e39c708fe026f3b1dbae","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":664,"license_type":"no_license","max_line_length":80,"num_lines":24,"path":"/home/.config/nvim/lua/tapia/autocmd.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"-- Define some useful autocommands\n\nvim.api.nvim_create_autocmd({ 'FileType' }, {\n pattern = { 'lua' },\n callback = function()\n vim.opt.expandtab = true\n vim.opt.softtabstop = 4\n vim.opt.shiftwidth = 4\n vim.opt.tabstop = 4\n end,\n})\n\nlocal asyncrun_group = vim.api.nvim_create_augroup('asyncrun', { clear = true })\n\nvim.api.nvim_create_autocmd({ 'User' }, {\n pattern = { 'AsyncRunStart' },\n group = asyncrun_group,\n command = 'call asyncrun#quickfix_toggle(10, 1)',\n})\nvim.api.nvim_create_autocmd({ 'User' }, {\n pattern = { 'AsyncRunStop' },\n group = asyncrun_group,\n command = \"copen | clast | wincmd k\",\n})\n\n"},{"alpha_fraction":0.33760684728622437,"alphanum_fraction":0.3390313386917114,"avg_line_length":25,"blob_id":"0c2df168a962a77ab7c1186c409bab2000306147","content_id":"87e3b1851e67cac1a2757f645f1fa7932ffa2e1e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":702,"license_type":"no_license","max_line_length":57,"num_lines":27,"path":"/home/.config/nvim/lua/overseer/template/user/python_build.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"return {\n name = \"python_build\",\n builder = function()\n -- Full path to current file (see :help expand())\n local file = vim.fn.expand(\"%:p\")\n return {\n cmd = { \"python\" },\n args = { file },\n components = {\n { \"on_exit_set_status\" },\n {\n \"display_duration\",\n detail_level = 2,\n },\n {\n \"on_output_quickfix\",\n open = true,\n items_only = false,\n tail = true,\n },\n },\n }\n end,\n condition = {\n filetype = { \"python\" },\n },\n}\n"},{"alpha_fraction":0.774193525314331,"alphanum_fraction":0.774193525314331,"avg_line_length":30,"blob_id":"2d7633a2450ccc33850d82636fdfc4823583d915","content_id":"844318b10e71f619b6632be2c1b7027dbc0677b0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":31,"license_type":"no_license","max_line_length":30,"num_lines":1,"path":"/home/.config/nvim/after/ftplugin/pandoc.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"vim.opt_local.formatexpr = nil\n"},{"alpha_fraction":0.5241379141807556,"alphanum_fraction":0.5413793325424194,"avg_line_length":23.16666603088379,"blob_id":"8439b25e5e91c9225c5b6c46dee912d874da73c3","content_id":"97a47de4944d7c718a9dcc9767831b3acf6b2cb7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":290,"license_type":"no_license","max_line_length":89,"num_lines":12,"path":"/home/.config/nvim/lua/plugins/typst.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"return {\n {\n 'kaarmu/typst.vim',\n ft = { \"typst\" },\n branch = 'main',\n dependencies = { { 'skywind3000/asyncrun.vim' } },\n config = function()\n vim.keymap.set(\"n\", \"<leader>lv\", \"<cmd>AsyncRun -mode=hide zathura '%<'.pdf <cr>\")\n end\n },\n}\n-- vim: set shiftwidth=2:\n"},{"alpha_fraction":0.5249999761581421,"alphanum_fraction":0.5249999761581421,"avg_line_length":25.66666603088379,"blob_id":"467ff0002559e0b6595720df20cb96e999349d1a","content_id":"a412b42c24fb5e212783e89467a5aabc3dddc584","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":160,"license_type":"no_license","max_line_length":45,"num_lines":6,"path":"/home/.config/nvim/after/ftplugin/gitcommit.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"require 'cmp'.setup.buffer {\n sources = require 'cmp'.config.sources(\n { { name = 'conventionalcommits' } },\n { { name = 'buffer' } }\n ),\n}\n"},{"alpha_fraction":0.7816091775894165,"alphanum_fraction":0.7816091775894165,"avg_line_length":23.85714340209961,"blob_id":"ac890e13d25f46c20061366c4474a86ece556ddf","content_id":"002568a7a7729a945cf639bd56cfa6f82165d9d5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"INI","length_bytes":174,"license_type":"no_license","max_line_length":54,"num_lines":7,"path":"/home/.pylintrc","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"[MESSAGES CONTROL]\n\ndisable=too-many-locals,missing-docstring,invalid-name\n\n[VARIABLES]\n# Good variable names,which should always be accepted\ngood-names=i,j,k,ix,ij,ik,x,y,z\n"},{"alpha_fraction":0.6275992393493652,"alphanum_fraction":0.6389414072036743,"avg_line_length":22.46666717529297,"blob_id":"bf7750d5ca94cd60214a7ea05d27f3336fe7afcc","content_id":"c55502739b69ea67f7f3e660d37e13d8fc75c096","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":1058,"license_type":"no_license","max_line_length":73,"num_lines":45,"path":"/home/bin/yalafi-grammarous","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"#!/bin/bash\n\n#\n# interface between vim-grammarous or vim-LanguageTool and yalafi.shell\n# - collect all options passed by editor, except --api\n# - languagetool-commandline.jar is a bit picky with repeated options\n#\n\n# LT's base directory\n#\nltdir=~/.vim/plugged/vim-grammarous/misc/LanguageTool-4.8\n\n# comment out to use languagetool-commandline\n#\nuse_server=\"--server my\"\n\n# vim-grammarous needs byte offsets in XML report\n# --> set to xml-b\n#\noutput=xml-b\noutput=xml\n\nopts=x\nlang=en-GB\nwhile [ $# -gt 1 ]\ndo\n if [ X$1 == X-l ]\n then\n # languagetool-commandline does not like multiple language specs\n shift\n lang=$1\n elif [ X$1 == X-c ]\n then\n # languagetool-commandline does not like multiple encoding specs\n # (yalafi.shell already includes --encoding utf-8)\n shift\n elif [ X$1 != X--api ]\n then\n opts+=\"$1 \"\n fi\n shift\ndone\n\npython3 -m yalafi.shell $use_server --output $output --language $lang \\\n --lt-directory $ltdir --lt-options \"$opts\" $1 2>/dev/null\n\n\n"},{"alpha_fraction":0.4814264476299286,"alphanum_fraction":0.5061911940574646,"avg_line_length":35.05356979370117,"blob_id":"b63b820a720a8521008908c2501befa3522435ee","content_id":"5be70bd494683b5e033330e651189918d80eac66","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":2025,"license_type":"no_license","max_line_length":144,"num_lines":56,"path":"/home/.config/nvim/lua/tapia/init.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"require(\"tapia.remap\")\nrequire(\"tapia.set\")\nrequire(\"tapia.autocmd\")\n\nvim.opt.guicursor =\n\"n-v-c:block,i-ci-ve:ver25,r-cr:hor20,o:hor50,a:blinkwait700-blinkoff400-blinkon250-Cursor/lCursor,sm:block-blinkwait175-blinkoff150-blinkon175\"\n\n-- Define format for quickfix window\nfunction _G.qftf(info)\n local items\n local ret = {}\n if info.quickfix == 1 then\n items = vim.fn.getqflist({ id = info.id, items = 0 }).items\n else\n items = vim.fn.getloclist(info.winid, { id = info.id, items = 0 }).items\n end\n local limit = 31\n local fname_fmt1, fname_fmt2 = '%-' .. limit .. 's', '…%.' .. (limit - 1) .. 's'\n local valid_fmt = '%s │%5d:%2d│%s %s'\n for i = info.start_idx, info.end_idx do\n local e = items[i]\n local fname = ''\n local str\n if e.valid == 1 then\n if e.bufnr > 0 then\n fname = vim.fn.bufname(e.bufnr)\n if fname == '' then\n fname = '[No Name]'\n else\n fname = fname:gsub('^' .. vim.env.HOME, '~')\n end\n -- char in fname may occur more than 1 width, ignore this issue in order to keep performance\n if #fname <= limit then\n fname = fname_fmt1:format(fname)\n else\n fname = fname_fmt2:format(fname:sub(1 - limit))\n end\n end\n local lnum = e.lnum > 99999 and -1 or e.lnum\n local cnum = e.col\n local qtype = e.type == '' and '' or ' ' .. e.type:sub(1, 1):upper()\n local module\n if string.len(e.module) > 1 and string.len(e.text) > 1 then\n module = e.module .. \": \"\n else\n module = e.module\n end\n local textm = e.text:gsub(\"\\n\", ' ')\n str = valid_fmt:format(fname, lnum, cnum, qtype, module .. textm)\n else\n str = e.text\n end\n table.insert(ret, str)\n end\n return ret\nend\n"},{"alpha_fraction":0.5099928379058838,"alphanum_fraction":0.5171306133270264,"avg_line_length":26.20388412475586,"blob_id":"d72f69a80924a79d2c049996b87339136e75e6f3","content_id":"01a79f0d7a90c89e9079f79840b21e1581e41847","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":2802,"license_type":"no_license","max_line_length":87,"num_lines":103,"path":"/home/.config/nvim/lua/plugins/ui.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"return {\n -- Colorschemes\n {\n 'shaunsingh/nord.nvim',\n name = 'nord',\n config = function()\n vim.cmd('colorscheme nord')\n vim.api.nvim_set_hl(0, \"FloatBorder\", { fg = \"#ebcb8b\", bold = true })\n vim.api.nvim_set_hl(0, \"NormalFloat\", { bg = \"#434c5e\" })\n end\n },\n -- Tmux\n {\n 'jpalardy/vim-slime',\n keys = {\n { \"<C-c><C-c>\", mode = \"n\" },\n { \"<C-c><C-c>\", mode = \"v\" },\n },\n config = function()\n vim.g.slime_target = \"tmux\"\n vim.g.slime_default_config = { socket_name = \"default\", target_pane = \"0.1\" }\n vim.g.slime_bracketed_paste = 1\n end\n },\n -- Status line\n {\n 'nvim-lualine/lualine.nvim',\n event = { \"BufReadPost\", \"BufNewFile\" },\n dependencies = {\n 'nvim-tree/nvim-web-devicons',\n },\n opts = {\n extensions = { 'quickfix', 'fugitive' },\n tabline = {\n lualine_a = { 'buffers' },\n lualine_z = { function()\n return [[buffers]]\n end },\n },\n },\n },\n -- FZF support\n {\n 'junegunn/fzf.vim',\n dependencies = {\n { 'junegunn/fzf', build = './install --all' },\n },\n },\n -- Integration with tmux\n {\n 'christoomey/vim-tmux-navigator',\n lazy = true,\n keys = {\n { \"<A-h>\", \"<cmd>TmuxNavigateLeft<cr>\", \"n\", { silent = true } },\n { \"<A-j>\", \"<cmd>TmuxNavigateDown<cr>\", \"n\", { silent = true } },\n { \"<A-k>\", \"<cmd>TmuxNavigateUp<cr>\", \"n\", { silent = true } },\n { \"<A-l>\", \"<cmd>TmuxNavigateRight<cr>\", \"n\", { silent = true } },\n },\n init = function()\n vim.g.tmux_navigator_no_mappings = true\n end\n },\n -- Nice visualization of quickfix errors\n {\n 'kevinhwang91/nvim-bqf',\n config = function()\n vim.o.qftf = '{info -> v:lua._G.qftf(info)}'\n\n require('bqf').setup()\n vim.api.nvim_set_hl(0, 'BqfPreviewTitle', { bg = '#ebcb8b', fg = '#3b4252' })\n end\n },\n -- Overview of code\n {\n 'stevearc/aerial.nvim',\n ft = { \"python\", \"julia\", \"tex\", \"markdown\", \"typst\" },\n dependencies = {\n -- \"nvim-treesitter/nvim-treesitter\",\n \"nvim-tree/nvim-web-devicons\"\n },\n keys = { { \"<leader>a\", \"<cmd>AerialToggle<cr>\" } },\n config = function()\n local aerial = require('aerial')\n require('aerial').setup({\n -- optionally use on_attach to set keymaps when aerial has attached to a buffer\n on_attach = function(bufnr)\n -- Jump forwards/backwards with '{' and '}'\n vim.keymap.set('n', '}', aerial.next, { buffer = bufnr })\n vim.keymap.set('n', '{', aerial.prev, { buffer = bufnr })\n end\n })\n end\n },\n -- Better display of errors\n {\n \"folke/trouble.nvim\",\n dependencies = \"web-devicons\",\n keys = {\n { \"<leader>tt\", \"<cmd>TroubleToggle<cr>\", \"n\" },\n }\n },\n}\n-- vim: set shiftwidth=2:\n"},{"alpha_fraction":0.5759046673774719,"alphanum_fraction":0.5781112313270569,"avg_line_length":30.041095733642578,"blob_id":"e28bfd847d06b293b6668f2cfb3635b35d472a67","content_id":"62267b87736a5543b1f91b9f780a0d13904f79a7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":2266,"license_type":"no_license","max_line_length":88,"num_lines":73,"path":"/home/.config/nvim/lua/tapia/remap.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"vim.keymap.set(\"n\", \"<leader>pv\", vim.cmd.Ex)\n\n-- Allow to move lines in visual mode\nvim.keymap.set(\"v\", \"J\", \":m '>+1<CR>gv=gv\")\nvim.keymap.set(\"v\", \"K\", \":m '<-2<CR>gv=gv\")\n-- Keep search items in the middle of the screen\nvim.keymap.set(\"n\", \"n\", \"nzzzv\")\nvim.keymap.set(\"n\", \"N\", \"Nzzzv\")\n\n-- Paste without deleting the previous selection\nvim.keymap.set(\"x\", \"<leader>p\", [[\"_dP]])\n-- Yank to system clipboard\n-- vim.keymap.set({\"n\", \"v\"}, \"<leader>y\", [[\"+y]])\n-- vim.keymap.set(\"n\", \"<leader>Y\", [[\"+Y]])\n\nvim.keymap.set(\"n\", \"Q\", \"<nop>\")\n\n-- Replace word below the cursor\nvim.keymap.set(\"n\", \"<leader>s\", [[:%s/\\<<C-r><C-w>\\>/<C-r><C-w>/gI<Left><Left><Left>]])\n\n-- Correct spelling in insert mode\nvim.keymap.set(\"i\", \"<C-s>\", \"<c-g>u<Esc>[s1z=`]a<c-g>u\")\n\n-- Faster folding\nvim.keymap.set({ \"n\", \"v\" }, \"<space>\", \"za\")\n\n-- Map <Esc> to shift-space\nvim.keymap.set({ \"i\", \"v\", \"s\" }, \"<S-Space>\", \"<Esc>\")\nvim.keymap.set({ \"i\", \"v\", \"s\" }, \"<M-Space>\", \"<Esc>\")\n\n-- Redefine movements\nvim.keymap.set(\"n\", \"j\", \"gj\")\nvim.keymap.set(\"n\", \"k\", \"gk\")\nvim.keymap.set(\"n\", \"gj\", \"j\")\nvim.keymap.set(\"n\", \"gk\", \"k\")\n\n-- Escape to normal mode when in terminal\nvim.keymap.set(\"t\", \"<Esc>\", \"<C-\\\\><C-n>\")\n\n-- For the quickfix window it is better to undo the previous remapping\nlocal qf_group = vim.api.nvim_create_augroup('quickfix', { clear = true })\nvim.api.nvim_create_autocmd({ 'FileType' }, {\n pattern = { 'qf' },\n group = qf_group,\n callback = function()\n vim.keymap.set('n', 'j', 'j', { buffer = true })\n vim.keymap.set('n', 'k', 'k', { buffer = true })\n end,\n})\n\n-- Move to next buffer\nvim.keymap.set(\"n\", \"tn\", \"<cmd>bnext<cr>\")\nvim.keymap.set(\"n\", \"tp\", \"<cmd>bprevious<cr>\")\n\n-- Close current buffer\nvim.keymap.set(\"n\", \"<leader>bq\", \"<cmd>bp <BAR> bd #<cr>\")\n\n-- Close quickfix window\nvim.keymap.set(\"n\", \"<leader>cq\", vim.cmd.cclose)\n\n-- Run files with overseer\n-- local overseer = require(\"overseer\")\n-- local function compile_and_run()\n-- local file_path = vim.api.nvim_buf_get_name(0)\n-- local file_cwd = vim.loop.cwd()\n\n-- if vim.bo.filetype == 'python' then\n-- vim.cmd(\"write\")\n-- overseer.run_template({ name = \"python_build\" })\n-- end\n-- end\n\n-- vim.keymap.set('n', '<F5>', compile_and_run)\n"},{"alpha_fraction":0.4417218565940857,"alphanum_fraction":0.4562913775444031,"avg_line_length":25.964284896850586,"blob_id":"972588f8474f1be552ed4704c95c32c03be68730","content_id":"77c513644314249cf764242b60dfd231259e7a9e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":1510,"license_type":"no_license","max_line_length":106,"num_lines":56,"path":"/home/.config/nvim/lua/plugins/telescope.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"return {\n {\n 'nvim-telescope/telescope.nvim',\n tag = '0.1.1',\n dependencies = { { 'nvim-lua/plenary.nvim' } },\n cmd = \"Telescope\",\n keys = {\n { \"<leader>ff\", function() require(\"telescope.builtin\").find_files() end, desc = \"find files\" },\n { \"<leader>fg\", function() require(\"telescope.builtin\").live_grep() end, desc = \"live grep\" },\n { \"<leader>fb\", function() require(\"telescope.builtin\").buffers() end, desc = \"find buffers\" },\n { \"<C-p>\", function() require(\"telescope.builtin\").git_files() end, desc = \"find git files\" },\n {\n \"<leader>ps\",\n function()\n require(\"telescope.builtin\").grep_string({ search = vim.fn.input(\"Grep > \") });\n end,\n desc = \"Grep\"\n },\n },\n opts = {\n defaults = {\n scroll_strategy = \"limit\",\n winblend = 30,\n sorting_strategy = 'ascending',\n layout_strategy = 'vertical',\n layout_config = {\n vertical = {\n width = 0.85,\n height = 0.95,\n preview_cutoff = 10,\n mirror = false,\n },\n center = {\n width = 0.85,\n height = 0.95,\n preview_cutoff = 10,\n prompt_position = 'top',\n },\n },\n file_ignore_patterns = {\n \"%.pyc\",\n \"%.rpy\",\n \"%.fil\",\n }\n },\n pickers = {\n find_files = {\n follow = true,\n }\n }\n\n }\n\n },\n}\n-- vim: set shiftwidth=2:\n"},{"alpha_fraction":0.4535752534866333,"alphanum_fraction":0.45464247465133667,"avg_line_length":22.424999237060547,"blob_id":"851dc906113c1e27ba6f87905a044f710e8a3e11","content_id":"fbda229fc891982490748f20acc2d4e316672314","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":937,"license_type":"no_license","max_line_length":55,"num_lines":40,"path":"/home/.config/nvim/lua/plugins/coding.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"return {\n {\n \"ThePrimeagen/refactoring.nvim\",\n dependencies = {\n { \"nvim-lua/plenary.nvim\" },\n -- { \"nvim-treesitter/nvim-treesitter\" }\n },\n ft = { \"python\", \"lua\" },\n keys = {\n {\n \"<leader>re\",\n \"<cmd>Refactor extract<cr>\",\n mode = \"v\",\n { noremap = true, silent = true, expr = false }\n },\n {\n \"<leader>rf\",\n \"<cmd>Refactor extract_to_file<cr>\",\n mode = \"v\",\n { noremap = true, silent = true, expr = false }\n },\n {\n \"<leader>rv\",\n \"<cmd>Refactor extract_var<cr>\",\n mode = \"v\",\n { noremap = true, silent = true, expr = false }\n },\n {\n \"<leader>ri\",\n \"<cmd>Refactor inline_var<cr>\",\n mode = \"v\",\n { noremap = true, silent = true, expr = false }\n },\n },\n config = function()\n require(\"refactoring\").setup({})\n end\n },\n}\n-- vim: set shiftwidth=2:\n"},{"alpha_fraction":0.699999988079071,"alphanum_fraction":0.699999988079071,"avg_line_length":19,"blob_id":"f19b80d7e2dd7689172193a70de80610849d5b25","content_id":"98f1b5a5bebcd286bfd2219885a5ac5e93c32db5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":20,"license_type":"no_license","max_line_length":19,"num_lines":1,"path":"/home/.config/nvim/after/ftplugin/wiki.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"vim.opt.wrap = true\n"},{"alpha_fraction":0.7272727489471436,"alphanum_fraction":0.8281444311141968,"avg_line_length":16.45652198791504,"blob_id":"621c7d47430e6d5d02d697aca4c0820c0966fcef","content_id":"e03b6a055d64f6d372c8eef2a284b3f452cd00d6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"INI","length_bytes":803,"license_type":"no_license","max_line_length":47,"num_lines":46,"path":"/home/.config/foot/foot.ini","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"font=FuraCode Nerd Font:size=12:style=medium\nfont-bold=FuraCode Nerd Font:size=12:style=bold\ndpi-aware=no\nbold-text-in-bright=false\nbox-drawings-uses-font-glyphs=true\n\n[tweak]\ngrapheme-shaping=yes\n\n[scrollback]\nlines=2000\n\n[cursor]\nblink=true\n\n[colors]\n# Nord color palette\nalpha=0.8\nforeground=d8dee9\nbackground=2e3440\nregular0=3b4252\nregular1=bf616a\nregular2=a3be8c\nregular3=ebcb8b\nregular4=81a1c1\nregular5=b48ead\nregular6=88c0d0\nregular7=e5e9f0\nbright0=4c566a\nbright1=bf616a\nbright2=a3be8c\nbright3=ebcb8b\nbright4=81a1c1\nbright5=b48ead\nbright6=8fbcbb\nbright7=eceff4\nselection-foreground=d8dee9\nselection-background=4c566a\n\n[key-bindings]\nscrollback-up-page=Control+Shift+k\nscrollback-down-page=Control+Shift+j\nscrollback-up-line=Control+Shift+b\nscrollback-down-line=Control+Shift+f\n\n[search-bindings]\n"},{"alpha_fraction":0.45782145857810974,"alphanum_fraction":0.4602784514427185,"avg_line_length":20.421052932739258,"blob_id":"68890b2ee7f9c6302b1323a3f33de3c9a8160296","content_id":"070077238e5d2d5016e93dbac3f81249de31262e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Lua","length_bytes":1221,"license_type":"no_license","max_line_length":60,"num_lines":57,"path":"/home/.config/nvim/lua/plugins/wiki.lua","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"return {\n -- Note-taking utilities\n {\n 'lervag/wiki.vim',\n -- ft = { \"wiki\" },\n dependencies = {\n { 'lervag/wiki-ft.vim' },\n },\n tag = \"v0.8\",\n cmd = \"WikiIndex\",\n init = function()\n vim.g.vimwiki_pubs_config = {\n vim.env.HOME .. \"/.config/pubs/main_library.conf\",\n vim.env.HOME .. \"/.config/pubs/misc_library.conf\",\n }\n\n vim.g.wiki_root = '~/Nextcloud/Notes'\n vim.g.wiki_link_creation = {\n wiki = {\n link_type = \"wiki\",\n url_extension = \".wiki\",\n url_transform = function(x)\n local name\n name, _ = string.gsub(string.lower(x), \" \", \"-\")\n return name\n end\n }\n }\n vim.g.wiki_filetypes = { 'wiki' }\n vim.g.wiki_select_method = 'fzf'\n end\n },\n {\n 'dkarter/bullets.vim',\n ft = {\n \"gitcommit\",\n \"mail\",\n \"markdown\",\n \"markdown.pandoc\",\n \"pandoc\",\n \"text\",\n \"wiki\",\n },\n init = function()\n vim.g.bullets_enabled_file_types = {\n 'gitcommit',\n 'mail',\n 'markdown',\n 'markdown.pandoc',\n 'pandoc',\n 'text',\n 'wiki',\n }\n end\n },\n}\n-- vim: set shiftwidth=2:\n"},{"alpha_fraction":0.6533742547035217,"alphanum_fraction":0.6533742547035217,"avg_line_length":9.1875,"blob_id":"f3e19f77c3946a0720bf681e0fc08180d6e41b93","content_id":"74d1fbfa8148f3e0ce8c0ecdd61c1a53695505da","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"TOML","length_bytes":326,"license_type":"no_license","max_line_length":22,"num_lines":32,"path":"/home/.config/starship.toml","repo_name":"cristobaltapia/dotfiles_main","src_encoding":"UTF-8","text":"add_newline = true\nformat=\"\"\"\n$username\\\n$hostname\\\n$directory\\\n$package\\\n$python\\\n$julia\\\n$time\\\n$fill\\\n$git_branch\\\n$git_status\\\n$shell\\n\\\n$character\"\"\"\nright_format = \"\"\"\n$battery\n\"\"\"\n\n[username]\nshow_always = true\n\n[fill]\nsymbol = \" \"\n\n[hostname]\nssh_only = true\n\n[python]\ndetect_extensions = []\n\n[nodejs]\ndisabled = true\n"}],"string":"[\n {\n \"alpha_fraction\": 0.4781915545463562,\n \"alphanum_fraction\": 0.4798997938632965,\n \"avg_line_length\": 27.69607925415039,\n \"blob_id\": \"592c41e9f564d2507a9bb6aa8505c000c659a9eb\",\n \"content_id\": \"d9008c7d4473824e435fbc8444ffb3f085a27ca9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 8781,\n \"license_type\": \"no_license\",\n \"max_line_length\": 107,\n \"num_lines\": 306,\n \"path\": \"/home/.config/nvim/lua/plugins/utils.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"-- Define hints for hydra\\nlocal hint_diagram = [[\\n Arrow^^^^^^ Select region with <C-v>\\n ^ ^ _K_ ^ ^ _f_: surround it with box\\n _H_ ^ ^ _L_\\n ^ ^ _J_ ^ ^ _q_\\n]]\\n\\nlocal hint_git = [[\\n _J_: next hunk _s_: stage hunk _d_: show deleted _b_: blame line\\n _K_: prev hunk _u_: undo last stage _p_: preview hunk _B_: blame show full\\n ^ ^ _S_: stage buffer ^ ^ _/_: show base file\\n ^\\n ^ ^ _<Enter>_: Fugitive _q_: exit\\n]]\\n\\nlocal hint_ltex = [[\\n ^^ Select Language for Ltex ^\\n^ ^\\n _e_: English (American) ^\\n _d_: German (Germany) ^\\n _s_: Spanish\\n^ ^\\n _q_: Exit\\n]]\\n\\nreturn {\\n -- Undo history\\n {\\n 'mbbill/undotree',\\n keys = {\\n { \\\"<F3>\\\", \\\"<cmd>UndotreeToggle<cr>\\\", \\\"n\\\" },\\n },\\n config = function()\\n vim.g.undotree_WindowLayout = 2\\n vim.g.undotree_SetFocusWhenToggle = true\\n end\\n },\\n -- Web devicons\\n { \\\"nvim-tree/nvim-web-devicons\\\", name = \\\"web-devicons\\\" },\\n -- Better ui elements for nvim\\n { 'stevearc/dressing.nvim' },\\n -- Char-based diff\\n {\\n 'rickhowe/diffchar.vim',\\n ft = { 'markdown', 'markdown.pandoc', 'tex' }\\n },\\n {\\n 'b3nj5m1n/kommentary',\\n branch = 'main',\\n config = function()\\n require('kommentary.config').configure_language(\\\"julia\\\", {\\n single_line_comment_string = \\\"#\\\",\\n prefer_single_line_comments = true,\\n })\\n require('kommentary.config').configure_language(\\\"lua\\\", {\\n prefer_single_line_comments = true,\\n })\\n end\\n },\\n -- Better movements\\n {\\n 'ggandor/leap.nvim',\\n keys = {\\n { \\\"s\\\", \\\"<Plug>(leap-forward-to)\\\", \\\"n\\\", { silent = true } },\\n { \\\"S\\\", \\\"<Plug>(leap-backward-to)\\\", \\\"n\\\", { silent = true } },\\n },\\n config = function()\\n vim.api.nvim_set_hl(0, 'LeapBackdrop', { link = 'Comment' })\\n end\\n },\\n -- Hydra\\n {\\n 'anuvyklack/hydra.nvim',\\n name = \\\"hydra\\\",\\n lazy = true,\\n keys = {\\n \\\"<leader>g\\\", \\\"<leader>hd\\\", \\\"<leader>hl\\\",\\n },\\n config = function(_, opts)\\n local Hydra = require('hydra')\\n\\n Hydra({\\n name = 'Draw Diagram',\\n hint = hint_diagram,\\n config = {\\n color = 'pink',\\n invoke_on_body = true,\\n hint = {\\n border = 'rounded'\\n },\\n on_enter = function()\\n vim.o.virtualedit = 'all'\\n end,\\n },\\n mode = 'n',\\n body = '<leader>hd',\\n heads = {\\n { 'H', '<C-v>h:VBox<CR>' },\\n { 'J', '<C-v>j:VBox<CR>' },\\n { 'K', '<C-v>k:VBox<CR>' },\\n { 'L', '<C-v>l:VBox<CR>' },\\n { 'f', ':VBox<CR>', { mode = 'v' } },\\n { 'q', nil, { exit = true } },\\n }\\n })\\n\\n local gitsigns = require('gitsigns')\\n\\n Hydra({\\n name = 'Git',\\n hint = hint_git,\\n config = {\\n buffer = bufnr,\\n color = 'pink',\\n invoke_on_body = true,\\n hint = {\\n border = 'rounded'\\n },\\n on_enter = function()\\n vim.cmd 'mkview'\\n vim.cmd 'silent! %foldopen!'\\n vim.bo.modifiable = false\\n gitsigns.toggle_signs(true)\\n gitsigns.toggle_linehl(true)\\n gitsigns.toggle_word_diff(true)\\n end,\\n on_exit = function()\\n local cursor_pos = vim.api.nvim_win_get_cursor(0)\\n vim.cmd 'loadview'\\n vim.api.nvim_win_set_cursor(0, cursor_pos)\\n vim.cmd 'normal zv'\\n gitsigns.toggle_signs(true)\\n gitsigns.toggle_linehl(false)\\n gitsigns.toggle_deleted(false)\\n gitsigns.toggle_word_diff(false)\\n end,\\n },\\n mode = { 'n', 'x' },\\n body = '<leader>g',\\n heads = {\\n { 'J',\\n function()\\n if vim.wo.diff then return ']c' end\\n vim.schedule(function() gitsigns.next_hunk() end)\\n return '<Ignore>'\\n end,\\n { expr = true, desc = 'next hunk' } },\\n { 'K',\\n function()\\n if vim.wo.diff then return '[c' end\\n vim.schedule(function() gitsigns.prev_hunk() end)\\n return '<Ignore>'\\n end,\\n { expr = true, desc = 'prev hunk' } },\\n { 's', ':Gitsigns stage_hunk<CR>', { silent = true, desc = 'stage hunk' } },\\n { 'u', gitsigns.undo_stage_hunk, { desc = 'undo last stage' } },\\n { 'S', gitsigns.stage_buffer, { desc = 'stage buffer' } },\\n { 'p', gitsigns.preview_hunk, { desc = 'preview hunk' } },\\n { 'd', gitsigns.toggle_deleted, {\\n nowait = true,\\n desc = 'toggle deleted'\\n } },\\n { 'b', gitsigns.blame_line, { desc = 'blame' } },\\n { 'B', function() gitsigns.blame_line { full = true } end, { desc = 'blame show full' } },\\n { '/', gitsigns.show, {\\n exit = true,\\n desc = 'show base file'\\n } }, -- show the base of the file\\n { '<Enter>', '<Cmd>Git<CR>', { exit = true, desc = 'Fugitive' } },\\n { 'q', nil, {\\n exit = true,\\n nowait = true,\\n desc = 'exit'\\n } },\\n }\\n })\\n\\n -- Change language for ltex\\n Hydra({\\n name = 'Change Ltex language',\\n hint = hint_ltex,\\n config = {\\n color = 'pink',\\n invoke_on_body = true,\\n hint = {\\n border = 'rounded'\\n },\\n on_enter = function()\\n vim.o.virtualedit = 'all'\\n end,\\n },\\n mode = 'n',\\n body = '<leader>hl',\\n heads = {\\n { 'e', function()\\n require(\\\"lspconfig\\\").ltex.setup({ settings = { ltex = { language = \\\"en-US\\\" } } })\\n vim.opt.spelllang = \\\"en_us\\\"\\n end },\\n { 'd', function()\\n require(\\\"lspconfig\\\").ltex.setup({ settings = { ltex = { language = \\\"de-DE\\\" } } })\\n vim.opt.spelllang = \\\"de_de\\\"\\n end },\\n { 's', function()\\n require(\\\"lspconfig\\\").ltex.setup({ settings = { ltex = { language = \\\"es\\\" } } })\\n vim.opt.spelllang = \\\"es\\\"\\n end },\\n { 'q', nil, { exit = true } },\\n }\\n })\\n end\\n },\\n -- Docstrings generator\\n {\\n \\\"danymat/neogen\\\",\\n keys = {\\n { \\\"<leader>ds\\\", \\\"<cmd>Neogen func<cr>\\\", desc = \\\"Generate func docstrings\\\" },\\n { \\\"<leader>dc\\\", \\\"<cmd>Neogen class<cr>\\\", desc = \\\"Generate class docstrings\\\" },\\n },\\n opts = {\\n enabled = true,\\n input_after_comment = true,\\n languages = {\\n python = {\\n template = {\\n annotation_convention = 'numpydoc',\\n }\\n }\\n }\\n },\\n },\\n -- Surround movements\\n { 'tpope/vim-surround' },\\n -- Close pairs of parentheses, quotes, etc\\n {\\n 'windwp/nvim-autopairs',\\n config = true,\\n },\\n -- Different nice improvements for neovim\\n {\\n 'echasnovski/mini.nvim',\\n branch = 'main',\\n event = { \\\"BufReadPre\\\", \\\"BufNewFile\\\" },\\n config = function()\\n local animate = require('mini.animate')\\n require('mini.trailspace').setup()\\n require('mini.indentscope').setup()\\n require('mini.animate').setup({\\n cursor = { enable = false },\\n resize = { enable = true },\\n scroll = { enable = false, timing = animate.gen_timing.linear({ duration = 150, unit = 'total' }) }\\n })\\n end\\n },\\n -- Support for openning GNUGP excrypted files\\n { 'jamessan/vim-gnupg' },\\n -- Draw ascii diagrams\\n {\\n 'jbyuki/venn.nvim',\\n dependencies = { \\\"hydra\\\" },\\n },\\n -- Snippets\\n {\\n 'SirVer/ultisnips',\\n dependencies = {\\n { 'honza/vim-snippets' },\\n { 'cristobaltapia/MySnippets' }\\n },\\n config = function()\\n vim.g.UltiSnipsSnippetDirectories = {\\n 'UltiSnips',\\n vim.env.HOME .. '/.local/share/nvim/lazy/MySnippets/Ultisnips',\\n vim.env.HOME .. '/Templates/ultisnips-templates'\\n }\\n\\n -- Set the smart function definition to use numpy style for docstrings\\n vim.g.ultisnips_python_style = \\\"numpy\\\"\\n vim.g.UltisnipsUsePythonVersion = 3\\n end\\n },\\n -- Follow symlinks\\n {\\n 'aymericbeaumet/vim-symlink',\\n -- 'Jasha10/vim-symlink',\\n dependencies = { 'moll/vim-bbye' },\\n },\\n {\\n \\\"jackMort/ChatGPT.nvim\\\",\\n cmd = { \\\"ChatGPT\\\", \\\"ChatGPTRun\\\", \\\"ChatGPTEditWithInstructions\\\" },\\n config = function()\\n local home = vim.fn.expand(\\\"$HOME\\\")\\n require(\\\"chatgpt\\\").setup(\\n {\\n api_key_cmd = \\\"cat \\\" .. home .. \\\"/.config/chatgpt/api\\\",\\n actions_paths = { vim.env.HOME .. \\\"/.config/chatgpt/actions.json\\\" }\\n }\\n )\\n end,\\n dependencies = {\\n \\\"MunifTanjim/nui.nvim\\\",\\n \\\"nvim-lua/plenary.nvim\\\",\\n \\\"nvim-telescope/telescope.nvim\\\"\\n }\\n }\\n}\\n-- vim: set shiftwidth=2:\\n\"\n },\n {\n \"alpha_fraction\": 0.5131086111068726,\n \"alphanum_fraction\": 0.5243445634841919,\n \"avg_line_length\": 27.60714340209961,\n \"blob_id\": \"ceb9137fe175750b24eb8e38e413bd356c672af2\",\n \"content_id\": \"5058a703e4dbe83093d8df3fa8d0da9956029f19\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 801,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 28,\n \"path\": \"/home/.local/bin/fexdox-completion.bash\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env bash\\n\\n_fexdox_completions()\\n{\\n # Consider account ID if given\\n options=\\\"\\\"\\n for IDX in ${!COMP_WORDS[@]}; do\\n if [[ ${COMP_WORDS[$IDX]} = \\\"-i\\\" ]]; then\\n # Get username\\n options=\\\"-i ${COMP_WORDS[$(($IDX+1))]}\\\"\\n fi\\n done\\n case ${COMP_WORDS[-2]} in\\n -s )\\n COMPREPLY=($(compgen -o dirnames \\\"${COMP_WORDS[-1]}\\\"));;\\n -r )\\n remotes=$(fexdox ${options} -l | awk '{print $5}')\\n COMPREPLY=($(compgen -W \\\"${remotes}\\\" \\\"${COMP_WORDS[-1]}\\\"));;\\n -D )\\n remotes=$(fexdox ${options} -l | awk '{print $5}')\\n COMPREPLY=($(compgen -W \\\"${remotes}\\\" \\\"${COMP_WORDS[-1]}\\\"));;\\n -l )\\n remotes=$(fexdox ${options} -l | awk '{print $5}')\\n COMPREPLY=($(compgen -W \\\"${remotes}\\\" \\\"${COMP_WORDS[-1]}\\\"));;\\n esac\\n}\\n\\ncomplete -F _fexdox_completions fexdox\\n\"\n },\n {\n \"alpha_fraction\": 0.6847977638244629,\n \"alphanum_fraction\": 0.6908414959907532,\n \"avg_line_length\": 21.882978439331055,\n \"blob_id\": \"8f3cd6d221683cff0ccdb47cb41d5471285099d5\",\n \"content_id\": \"bdf08258cc1befccc1c5f7f815c42c001e27e411\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 2154,\n \"license_type\": \"no_license\",\n \"max_line_length\": 79,\n \"num_lines\": 94,\n \"path\": \"/home/.config/nvim/lua/tapia/set.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"vim.g.python3_host_prog = vim.env.HOME .. '/.virtualenvs/py3neovim/bin/python3'\\n\\nvim.opt.title = true\\nvim.opt.titlestring = \\\"%t %y\\\"\\nvim.opt.autoread = true\\nvim.opt.swapfile = false\\nvim.opt.backup = false\\nvim.opt.encoding = \\\"utf-8\\\"\\nvim.opt.cursorline = true\\n\\n-- Line numbers\\nvim.opt.nu = true\\nvim.opt.relativenumber = true\\n\\n-- Lineabraks with indentation\\nvim.opt.linebreak = true\\nvim.opt.breakindent = true\\nvim.opt.showbreak = \\\" \\\"\\nvim.opt.wrap = true\\n\\n-- Change buffer without saving\\nvim.opt.hidden = true\\n\\n-- Atomatically change current working directory to the directory\\n-- containing the file in the buffer\\nvim.opt.autochdir = true\\n\\n-- Use spaces to replace tabs\\nvim.opt.expandtab = true\\n\\n-- Allow virtual editing in visual block\\nvim.opt.virtualedit = \\\"block\\\"\\n\\n-- Ignore certain files\\nvim.opt.wildignore = { \\\"*.swp\\\", \\\"*.bak\\\", \\\"*.pyc\\\", \\\"*.class\\\", \\\"*.aux\\\", \\\"*.toc\\\" }\\n\\n-- Always show status bar\\nvim.opt.laststatus = 2\\n\\nvim.opt.hlsearch = false\\nvim.opt.incsearch = true\\n\\nvim.opt.termguicolors = true\\n\\nvim.opt.scrolloff = 8\\nvim.opt.signcolumn = \\\"yes\\\"\\nvim.opt.isfname:append(\\\"@-@\\\")\\n\\nvim.opt.diffopt:append(\\\"vertical\\\")\\nvim.opt.diffopt:append(\\\"linematch:60\\\")\\n\\nvim.opt.shada:append('r/mnt/intcdc')\\n\\nvim.g.mapleader = \\\"\\\\\\\\\\\"\\n\\n-- Visual selection copies to the clipboard\\nvim.opt.clipboard:append('unnamedplus')\\n\\nvim.g.completion_sorting = \\\"none\\\"\\nvim.g.completeopt = \\\"menu,menuone,noinsert\\\"\\n\\n-- Size of the completion menu\\nvim.opt.pumheight = 15\\n\\n-- Set python syntax for Freecad macros\\nvim.api.nvim_create_autocmd({ \\\"BufEnter\\\", \\\"BufNewFile\\\" }, {\\n pattern = { \\\"*.fcmacro\\\" },\\n callback = function()\\n vim.opt.filetype = \\\"python\\\"\\n end\\n})\\n-- Set tex syntax for pdf_tex files\\nvim.api.nvim_create_autocmd({ \\\"BufEnter\\\", \\\"BufNewFile\\\" }, {\\n pattern = { \\\"*.pdf_tex\\\" },\\n callback = function()\\n vim.opt.filetype = \\\"tex\\\"\\n end\\n})\\n\\n-- dont list quickfix buffers\\nvim.api.nvim_create_autocmd(\\\"FileType\\\", {\\n pattern = \\\"qf\\\",\\n callback = function()\\n vim.opt_local.buflisted = false\\n end,\\n})\\n\\n-- Disable editorconfig\\nvim.g.editorconfig = false\\n\\n-- Set default tabsize\\nvim.opt.softtabstop = 4\\nvim.opt.shiftwidth = 4\\nvim.opt.tabstop = 4\\n\"\n },\n {\n \"alpha_fraction\": 0.5100317001342773,\n \"alphanum_fraction\": 0.5129883885383606,\n \"avg_line_length\": 29.54838752746582,\n \"blob_id\": \"d2dc02ee35d8bbfb8fe6ca3dddc9d8c5a64ebf3d\",\n \"content_id\": \"427158cbffcb6a0e630d5c689ac21a9bff965bed\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 9474,\n \"license_type\": \"no_license\",\n \"max_line_length\": 106,\n \"num_lines\": 310,\n \"path\": \"/home/.config/nvim/lua/plugins/lsp.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"return {\\n -- Lsp-connfig\\n {\\n 'neovim/nvim-lspconfig',\\n dependencies = {\\n { \\\"folke/neodev.nvim\\\" },\\n { \\\"williamboman/mason-lspconfig.nvim\\\" },\\n { \\\"nvim-lua/plenary.nvim\\\" },\\n { \\\"ray-x/lsp_signature.nvim\\\" },\\n },\\n event = { \\\"BufReadPre\\\", \\\"BufNewFile\\\" },\\n opts = {\\n -- options for vim.diagnostic.config()\\n diagnostics = {\\n underline = true,\\n update_in_insert = false,\\n virtual_text = {\\n spacing = 4,\\n source = \\\"if_many\\\",\\n prefix = \\\"●\\\",\\n -- this will set set the prefix to a function that returns\\n -- the diagnostics icon based on the severity this only\\n -- works on a recent 0.10.0 build. Will be set to \\\"●\\\" when\\n -- not supported prefix = \\\"icons\\\",\\n },\\n severity_sort = true,\\n },\\n -- Enable this to enable the builtin LSP inlay hints on Neovim >=\\n -- 0.10.0 Be aware that you also will need to properly configure\\n -- your LSP server to provide the inlay hints.\\n inlay_hints = {\\n enabled = false,\\n },\\n -- add any global capabilities here\\n capabilities = {},\\n -- Automatically format on save\\n autoformat = false,\\n },\\n config = function(_, opts)\\n local Path = require(\\\"plenary.path\\\")\\n require(\\\"neodev\\\").setup { lspconfig = true, }\\n\\n local lspconfig = require('lspconfig')\\n local lsp_defaults = lspconfig.util.default_config\\n\\n lsp_defaults.capabilities = vim.tbl_deep_extend(\\n 'force',\\n lsp_defaults.capabilities,\\n require('cmp_nvim_lsp').default_capabilities()\\n )\\n\\n vim.api.nvim_create_autocmd('LspAttach', {\\n desc = 'LSP actions',\\n callback = function(event)\\n -- Define current bufnr\\n local bufnr = event.buf\\n local map = function(m, lhs, rhs)\\n local options = { buffer = bufnr, remap = false }\\n vim.keymap.set(m, lhs, rhs, options)\\n end\\n\\n -- LSP actions\\n map('n', 'K', vim.lsp.buf.hover)\\n map('n', 'gd', vim.lsp.buf.definition)\\n map('n', 'gD', vim.lsp.buf.declaration)\\n map('n', 'gi', vim.lsp.buf.implementation)\\n map('n', 'go', vim.lsp.buf.type_definition)\\n map('n', 'gr', vim.lsp.buf.references)\\n map('n', 'gs', vim.lsp.buf.signature_help)\\n map('n', '<leader>rn', vim.lsp.buf.rename)\\n map({ 'n', 'x' }, 'gq', function() vim.lsp.buf.format({ async = true }) end)\\n -- Format selected code only\\n vim.keymap.set('v', 'gq', function()\\n vim.lsp.buf.format({\\n async = true,\\n timeout_ms = 10000,\\n range = { vim.fn.getpos('v'), vim.fn.getcurpos() },\\n })\\n end)\\n map('n', '<leader>ca', vim.lsp.buf.code_action)\\n map('x', '<leader>ca', '<cmd>lua vim.lsp.buf.range_code_action()<cr>')\\n\\n -- Diagnostics\\n map('n', 'ge', vim.diagnostic.open_float)\\n map('n', '[d', vim.diagnostic.goto_prev)\\n map('n', ']d', vim.diagnostic.goto_next)\\n end\\n })\\n\\n local function lsp_settings()\\n vim.diagnostic.config({\\n severity_sort = true,\\n float = { border = 'rounded' },\\n })\\n\\n vim.lsp.handlers['textDocument/hover'] = vim.lsp.with(\\n vim.lsp.handlers.hover,\\n { border = 'rounded' }\\n )\\n\\n vim.lsp.handlers['textDocument/signatureHelp'] = vim.lsp.with(\\n vim.lsp.handlers.signature_help,\\n { border = 'rounded' }\\n )\\n\\n local command = vim.api.nvim_create_user_command\\n\\n command('LspWorkspaceAdd', function()\\n vim.lsp.buf.add_workspace_folder()\\n end, { desc = 'Add folder to workspace' })\\n\\n command('LspWorkspaceList', function()\\n vim.notify(vim.inspect(vim.lsp.buf.list_workspace_folders()))\\n end, { desc = 'List workspace folders' })\\n\\n command('LspWorkspaceRemove', function()\\n vim.lsp.buf.remove_workspace_folder()\\n end, { desc = 'Remove folder from workspace' })\\n end\\n\\n lsp_settings()\\n\\n require('mason').setup({})\\n\\n require('mason-lspconfig').setup({\\n ensure_installed = {\\n 'bashls',\\n 'cssls',\\n 'docker_compose_language_service',\\n 'dockerls',\\n 'efm',\\n 'eslint',\\n 'fortls',\\n 'jsonls',\\n 'julials',\\n 'ltex',\\n 'lua_ls',\\n 'marksman',\\n 'pyright',\\n 'ruff_lsp',\\n 'taplo',\\n 'tsserver',\\n 'typst_lsp',\\n }\\n })\\n\\n -- Configure Lua-ls\\n lspconfig.lua_ls.setup {\\n settings = {\\n Lua = {\\n -- Disable telemetry\\n telemetry = { enable = false },\\n runtime = {\\n -- Tell the language server which version of Lua you're using\\n -- (most likely LuaJIT in the case of Neovim)\\n version = 'LuaJIT',\\n path = runtime_path,\\n },\\n diagnostics = {\\n -- Get the language server to recognize the `vim` global\\n globals = { 'vim' }\\n },\\n workspace = {\\n checkThirdParty = false,\\n library = {\\n -- Make the server aware of Neovim runtime files\\n vim.fn.expand('$VIMRUNTIME/lua'),\\n vim.fn.stdpath('config') .. '/lua'\\n }\\n }\\n }\\n }\\n }\\n\\n -- Python LSP\\n local capabilities = vim.lsp.protocol.make_client_capabilities()\\n capabilities.textDocument.publishDiagnostics.tagSupport.valueSet = { 2 }\\n lspconfig.pyright.setup {\\n settings = {\\n python = {\\n analysis = {\\n autoSearchPaths = true,\\n disableOrganizeImports = true,\\n useLibraryCodeForTypes = true,\\n diagnosticMode = 'workspace',\\n autoImportCompletions = false,\\n }\\n }\\n }\\n }\\n lspconfig.ruff_lsp.setup {}\\n -- Typst\\n lspconfig.typst_lsp.setup {\\n single_file_support = true,\\n }\\n -- Julia\\n lspconfig.julials.setup {}\\n -- Latex\\n -- lspconfig.texlab.setup {}\\n -- Toml\\n lspconfig.taplo.setup {}\\n -- Docker\\n lspconfig.docker_compose_language_service.setup {}\\n lspconfig.dockerls.setup {\\n on_attach = function(client, bufnr)\\n -- Remove syntax from LSP\\n client.server_capabilities.semanticTokensProvider = nil\\n end,\\n }\\n -- CSS\\n lspconfig.cssls.setup {}\\n -- Grammar correctoin using ltex-ls\\n local ltex_setup = {\\n filetypes = { \\\"bib\\\", \\\"gitcommit\\\", \\\"markdown\\\", \\\"org\\\", \\\"plaintex\\\", \\\"rst\\\", \\\"rnoweb\\\", \\\"tex\\\", \\\"pandoc\\\",\\n \\\"typst\\\" },\\n settings = {\\n ltex = {\\n language = \\\"en-US\\\",\\n },\\n },\\n }\\n -- For ltex-ls under archlinux I have to use the system installation, but\\n -- for other systems (e.g. Ubuntu) the default cmd works good.\\n if Path:new(\\\"/usr/bin/ltex-ls\\\"):is_file() then\\n ltex_setup[\\\"cmd\\\"] = { \\\"/usr/bin/ltex-ls\\\" }\\n end\\n lspconfig.ltex.setup(ltex_setup)\\n lspconfig.fortls.setup {}\\n -- JSON-ls\\n lspconfig.jsonls.setup {}\\n\\n -- Define formatting for different filetypes\\n local texFormatter = 'latexindent --modifylinebreaks -y=\\\"defaultIndent: \\\\' \\\\'\\\"'\\n lspconfig.efm.setup {\\n flags = {\\n debounce_text_changes = 150,\\n },\\n init_options = { documentFormatting = true },\\n filetypes = { \\\"python\\\", \\\"bib\\\", \\\"tex\\\", \\\"sty\\\", \\\"cls\\\", \\\"fortran\\\" },\\n settings = {\\n rootMarkers = { \\\".git/\\\" },\\n languages = {\\n python = {\\n { formatCommand = \\\"yapf\\\", formatStdin = true }\\n },\\n bib = {\\n {\\n formatCommand = \\\"bibtex-tidy --v2 --curly --align=14 --no-escape --sort-fields --sort\\\",\\n formatStdin = true\\n }\\n },\\n fortran = {\\n {\\n formatCommand = \\\"findent --continuation=0 --input_format=fixed --indent_procedure=0\\\",\\n formatStdin = true\\n }\\n },\\n tex = { { formatCommand = texFormatter, formatStdin = true } },\\n sty = { { formatCommand = texFormatter, formatStdin = true } },\\n cls = { { formatCommand = texFormatter, formatStdin = true } },\\n }\\n }\\n }\\n\\n\\n -- Don't show diagnostics in-line\\n vim.diagnostic.config({ virtual_text = false })\\n\\n -- Increase update frequency of the ui\\n vim.opt.updatetime = 500\\n end\\n },\\n {\\n \\\"folke/neodev.nvim\\\",\\n opts = {\\n lspconfig = true\\n }\\n },\\n -- Mason\\n {\\n 'williamboman/mason-lspconfig.nvim',\\n name = \\\"mason\\\",\\n dependencies = {\\n {\\n 'williamboman/mason.nvim',\\n build = function()\\n pcall(vim.cmd, 'MasonUpdate')\\n end,\\n },\\n }\\n },\\n -- Function signatures\\n {\\n \\\"ray-x/lsp_signature.nvim\\\",\\n lazy = true,\\n opts = {\\n bind = true, -- This is mandatory, otherwise border config won't get registered.\\n hint_enable = true,\\n doc_lines = 0,\\n floating_window = false,\\n toggle_key = \\\"<C-h>\\\",\\n select_signature_key = \\\"<C-l>\\\",\\n floating_window_above_cur_line = true,\\n handler_opts = {\\n border = \\\"rounded\\\"\\n }\\n }\\n },\\n}\\n-- vim: set shiftwidth=2:\\n\"\n },\n {\n \"alpha_fraction\": 0.7234042286872864,\n \"alphanum_fraction\": 0.7446808218955994,\n \"avg_line_length\": 30.33333396911621,\n \"blob_id\": \"fb4ca4e1d292d756ca84e64d04d66d6043430802\",\n \"content_id\": \"acb7a1eec3bee81c1c093996b459db545d865319\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 94,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 3,\n \"path\": \"/home/.config/nvim/after/ftplugin/mail.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"vim.opt_local.textwidth = 80\\nvim.opt_local.formatoptions = \\\"tcqj]\\\"\\nvim.opt_local.spell = true\\n\"\n },\n {\n \"alpha_fraction\": 0.6006628274917603,\n \"alphanum_fraction\": 0.6043910384178162,\n \"avg_line_length\": 26.12359619140625,\n \"blob_id\": \"facca32930dad02906f1c7450a1cac5901dad4a5\",\n \"content_id\": \"c0f50c59c299df4def9eb794310c110784633bec\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2414,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 89,\n \"path\": \"/home/.config/papis/scripts/papis-bibfile\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#! /usr/bin/env python3\\n# -*- coding: utf-8 -*-\\n# papis-short-help: Convert zotero library to papis library\\n# Copyright 2017 Alejandro Gallo. GPLv3\\nimport os\\nimport sys\\n\\nfrom bibtexparser.bparser import BibTexParser\\n\\nimport papis.api\\nimport papis.bibtex\\nimport papis.commands\\nimport papis.commands.add as papis_add\\nimport papis.config\\nimport papis.utils\\n\\nimport argparse\\n\\npars = argparse.ArgumentParser(description=\\\"Import bibfile to papis library\\\")\\npars.add_argument(\\\"bibfile\\\", type=str)\\npars.add_argument(\\\"--lib\\\", type=str)\\n\\nargumetns = pars.parse_args()\\nbib_file = argumetns.bibfile\\n\\n\\ndef usage():\\n print(\\\"Usage: papis bibfile bibfile --lib\\\")\\n\\n\\nif not os.path.exists(bib_file):\\n print(\\\"ERROR: Bib file (%s) not found!\\\" % bib_file)\\n usage()\\n sys.exit(1)\\n\\nparser = BibTexParser()\\nparser.ignore_nonstandard_types = False\\n\\n# entries = parser.parse(bib_file)\\nwith open(bib_file) as bibtex_file:\\n bib_obj = parser.parse_file(bibtex_file)\\n\\nentries = bib_obj.entries\\n\\n\\ndef add(ref_data, pdf=None):\\n\\n if pdf_file is not None:\\n papis_add.run(paths=[pdf], data=ref_data, git=True)\\n else:\\n papis_add.run(paths=[], data=ref_data, git=True)\\n\\n\\ncwd = os.getcwd()\\n\\n# Set the library\\nif argumetns.lib:\\n papis.api.set_lib_from_name(argumetns.lib)\\n print(f\\\"library {argumetns.lib}\\\")\\n\\nfor entry in entries:\\n for basic_field in [\\\"ref\\\", \\\"author\\\", \\\"title\\\"]:\\n if basic_field not in entry.keys():\\n if basic_field == \\\"ref\\\":\\n entry[basic_field] = entry[\\\"ID\\\"]\\n elif basic_field == \\\"author\\\":\\n entry[basic_field] = entry[\\\"editor\\\"]\\n else:\\n entry[basic_field] = papis.utils.input(\\n \\\"%s Not found, please insert\\\" % basic_field, default=\\\"???????\\\"\\n )\\n\\n print(\\\"INFO: Processing | bibkey: %s\\\" % entry.get(\\\"ref\\\"))\\n print(\\\" |Author: %s\\\" % entry.get(\\\"author\\\"))\\n print(\\\" | Title: %s\\\" % entry.get(\\\"title\\\"))\\n print(\\\" |\\\")\\n\\n pdf_file = None\\n\\n if \\\"file\\\" in entry.keys():\\n pdf_file = entry.get(\\\"file\\\").split(\\\":\\\")[1]\\n pdf_file = os.path.join(cwd, pdf_file)\\n print(\\\"\\\\tINFO: File field detected (%s)\\\" % pdf_file)\\n if not os.path.exists(pdf_file):\\n print(\\\"\\\\tWARNING: Path (%s) not found! Ignoring it\\\" % pdf_file)\\n del entry[\\\"file\\\"]\\n pdf_file = None\\n\\n add(entry, pdf_file)\\n\"\n },\n {\n \"alpha_fraction\": 0.6992481350898743,\n \"alphanum_fraction\": 0.7368420958518982,\n \"avg_line_length\": 21.16666603088379,\n \"blob_id\": \"4e4df0649408f18820f17e86bf69aa5d79d14aa6\",\n \"content_id\": \"6afa722f5da5753c611b9fad63ecfb5c187a140f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 133,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 6,\n \"path\": \"/home/.config/nvim/after/ftplugin/python.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"vim.opt_local.textwidth = 80\\nvim.opt_local.formatoptions = \\\"cqj\\\"\\n\\nvim.opt.softtabstop = 4\\nvim.opt.shiftwidth = 4\\nvim.opt.tabstop = 4\\n\"\n },\n {\n \"alpha_fraction\": 0.5513626933097839,\n \"alphanum_fraction\": 0.552410900592804,\n \"avg_line_length\": 27.058822631835938,\n \"blob_id\": \"8544ffd5f42c268f26b4c230e859cb920560ea93\",\n \"content_id\": \"974559d32a09044897b66133b4f19f3e6fa86078\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 954,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 34,\n \"path\": \"/home/.config/nvim/lua/plugins/markdown.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"return {\\n {\\n 'vim-pandoc/vim-pandoc',\\n ft = { 'markdown', 'markdown.pandoc', 'pandoc' },\\n dependencies = {\\n { 'vim-pandoc/vim-pandoc-syntax' },\\n { 'godlygeek/tabular' },\\n {\\n \\\"iamcco/markdown-preview.nvim\\\",\\n build = function() vim.fn[\\\"mkdp#util#install\\\"]() end,\\n ft = { 'markdown', 'pandoc', 'markdown.pandoc' }\\n }\\n },\\n config = function()\\n vim.cmd(\\n [[\\n function! g:Open_browser(url)\\n \\\"silent exe 'silent !gnome-www-browser --private-instance ' . a:url . \\\" &\\\"\\n silent exe 'silent !epiphany --private-instance ' . a:url . \\\" &\\\"\\n endfunction\\n ]]\\n )\\n\\n --[[ local function open_browser(url)\\n io.popen(\\\"epiphany --private-instance \\\" .. url .. \\\" &\\\")\\nend ]]\\n vim.g.mkdp_browserfunc = 'g:Open_browser'\\n\\n vim.g.mkdp_filetypes = { 'pandoc', 'markdown', 'markdown.pandoc', 'wiki' }\\n vim.g.mkdp_auto_close = false\\n end\\n },\\n}\\n-- vim: set shiftwidth=2:\\n\"\n },\n {\n \"alpha_fraction\": 0.6549249887466431,\n \"alphanum_fraction\": 0.6640573740005493,\n \"avg_line_length\": 30.89583396911621,\n \"blob_id\": \"a2ab559d1ad8a1bd5739d6cd36790f6f4152f0c8\",\n \"content_id\": \"ca7e79b491dc60278ebbea9d2e62ed94d8c1dc23\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 1533,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 48,\n \"path\": \"/home/.password-store/.extensions/get_pass.bash\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env bash\\n# pass get - Password Store Extension (https://www.passwordstore.org/)\\n# Copyright (C) 2020 James Patrick\\n#\\n# This program is free software: you can redistribute it and/or modify\\n# it under the terms of the GNU General Public License as published by\\n# the Free Software Foundation, either version 3 of the License, or\\n# (at your option) any later version.\\n#\\n# This program is distributed in the hope that it will be useful,\\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\\n# GNU General Public License for more details.\\n#\\n# You should have received a copy of the GNU General Public License\\n# along with this program. If not, see <http://www.gnu.org/licenses/>.\\n#\\n\\n\\nPASSWORD_STORE_DIR=\\\"${PASSWORD_STORE_DIR:-$HOME/.password-store}\\\"\\n\\ncmd_get_pass_usage() {\\n cat <<-_EOF\\nUsage:\\n $PROGRAM get_pass pass_name\\n Grabs the pass based on rules for Browserpass.\\n 1. match \\\"key:value\\\" where key, either pass, password, or secret\\n 2. if no match is present default to the first line.\\n\\n https://github.com/browserpass/browserpass-extension\\n\\n Options:\\n Nada.\\n_EOF\\n exit 0\\n}\\n\\n\\ncmd_get_user(){\\n local pass_name=\\\"$1\\\" val backup\\n val=$(pass get \\\"(pass|password|secret)\\\" \\\"$pass_name\\\")\\n backup=$(cmd_show \\\"$pass_name\\\" | head -1) \\n echo \\\"${val:-$backup}\\\"\\n}\\n\\n[[ \\\"$1\\\" == \\\"help\\\" || \\\"$1\\\" == \\\"--help\\\" || \\\"$1\\\" == \\\"-h\\\" ]] && cmd_get_user_usage\\n[[ \\\"$#\\\" != \\\"1\\\" ]] && cmd_get_user_usage\\ncmd_get_user \\\"$@\\\"\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7411003112792969,\n \"alphanum_fraction\": 0.8155339956283569,\n \"avg_line_length\": 13.714285850524902,\n \"blob_id\": \"e9a9e759c0b3591e8eabed79ba308020ce779bfe\",\n \"content_id\": \"1954d83060778a359cd5254f385168007e2d6bcb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"INI\",\n \"length_bytes\": 309,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 21,\n \"path\": \"/home/.config/fuzzel/fuzzel.ini\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"[main]\\nfont=Inter Nerd Font:size=14:weight=medium\\nicon-theme=Paper\\ndpi-aware=auto\\n#fields=filename,name,generic\\nterminal=foot\\nfuzzy=yes\\ninner-pad=20\\nline-height=25\\n\\n[colors]\\nbackground=3b4252dd\\ntext=d8dee9ff\\nselection=5e81acff\\nselection-text=eceff4ff\\nmatch=ebcb8bff\\nborder=5e81acff\\n\\n[border]\\nwidth=4\\nradius=4\\n\"\n },\n {\n \"alpha_fraction\": 0.5931363105773926,\n \"alphanum_fraction\": 0.6252727508544922,\n \"avg_line_length\": 27.32022476196289,\n \"blob_id\": \"6ae5771370cae3326ba63dc3ed2e3916d9460527\",\n \"content_id\": \"e7dd3f1e0bce57432e1229f213a93272edf174b2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 5041,\n \"license_type\": \"no_license\",\n \"max_line_length\": 192,\n \"num_lines\": 178,\n \"path\": \"/home/.bashrc\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#\\n# ~/.bashrc\\n#\\n\\n# If not running interactively, don't do anything\\n[[ $- != *i* ]] && return\\n\\n# get current branch in git repo\\nfunction parse_git_branch() {\\n\\tBRANCH=`git branch 2> /dev/null | sed -e '/^[^*]/d' -e 's/* \\\\(.*\\\\)/\\\\1/'`\\n\\tif [ ! \\\"${BRANCH}\\\" == \\\"\\\" ]\\n\\tthen\\n\\t\\tSTAT=`parse_git_dirty`\\n\\t\\techo \\\"[${BRANCH}${STAT}]\\\"\\n\\telse\\n\\t\\techo \\\"\\\"\\n\\tfi\\n}\\n\\n# get current status of git repo\\nfunction parse_git_dirty {\\n\\tstatus=`git status 2>&1 | tee`\\n\\tdirty=`echo -n \\\"${status}\\\" 2> /dev/null | grep \\\"modified:\\\" &> /dev/null; echo \\\"$?\\\"`\\n\\tuntracked=`echo -n \\\"${status}\\\" 2> /dev/null | grep \\\"Untracked files\\\" &> /dev/null; echo \\\"$?\\\"`\\n\\tahead=`echo -n \\\"${status}\\\" 2> /dev/null | grep \\\"Your branch is ahead of\\\" &> /dev/null; echo \\\"$?\\\"`\\n\\tnewfile=`echo -n \\\"${status}\\\" 2> /dev/null | grep \\\"new file:\\\" &> /dev/null; echo \\\"$?\\\"`\\n\\trenamed=`echo -n \\\"${status}\\\" 2> /dev/null | grep \\\"renamed:\\\" &> /dev/null; echo \\\"$?\\\"`\\n\\tdeleted=`echo -n \\\"${status}\\\" 2> /dev/null | grep \\\"deleted:\\\" &> /dev/null; echo \\\"$?\\\"`\\n\\tbits=''\\n\\tif [ \\\"${renamed}\\\" == \\\"0\\\" ]; then\\n\\t\\tbits=\\\">${bits}\\\"\\n\\tfi\\n\\tif [ \\\"${ahead}\\\" == \\\"0\\\" ]; then\\n\\t\\tbits=\\\"*${bits}\\\"\\n\\tfi\\n\\tif [ \\\"${newfile}\\\" == \\\"0\\\" ]; then\\n\\t\\tbits=\\\"+${bits}\\\"\\n\\tfi\\n\\tif [ \\\"${untracked}\\\" == \\\"0\\\" ]; then\\n\\t\\tbits=\\\"?${bits}\\\"\\n\\tfi\\n\\tif [ \\\"${deleted}\\\" == \\\"0\\\" ]; then\\n\\t\\tbits=\\\"x${bits}\\\"\\n\\tfi\\n\\tif [ \\\"${dirty}\\\" == \\\"0\\\" ]; then\\n\\t\\tbits=\\\"!${bits}\\\"\\n\\tfi\\n\\tif [ ! \\\"${bits}\\\" == \\\"\\\" ]; then\\n\\t\\techo \\\" ${bits}\\\"\\n\\telse\\n\\t\\techo \\\"\\\"\\n\\tfi\\n}\\n\\nexport PS1=\\\"[\\\\[\\\\e[32m\\\\]\\\\u\\\\[\\\\e[m\\\\]\\\\[\\\\e[32m\\\\]@\\\\[\\\\e[m\\\\]\\\\[\\\\e[32m\\\\]\\\\h\\\\[\\\\e[m\\\\]]:\\\\[\\\\e[36m\\\\]\\\\W\\\\[\\\\e[m\\\\]\\\\[\\\\e[31m\\\\]\\\\`parse_git_branch\\\\`\\\\[\\\\e[m\\\\]$ \\\"\\n\\n# Set language for the console\\nexport LANG=\\\"en_US.UTF-8\\\"\\n\\nexport EDITORCMD=\\\"nvim-qt\\\"\\nexport EDITOR=\\\"nvim\\\"\\n\\n# check the window size after each command and, if necessary,\\n# update the values of LINES and COLUMNS\\nshopt -s checkwinsize\\n\\n# Virtual Environment\\nexport WORKON_HOME=~/.virtualenvs\\nsource /usr/bin/virtualenvwrapper.sh\\n\\nsource \\\"$HOME/.homesick/repos/homeshick/homeshick.sh\\\"\\nsource \\\"$HOME/.homesick/repos/homeshick/completions/homeshick-completion.bash\\\"\\n\\n# if [ $TILIX_ID ] || [ $VTE_VERSION ]; then\\n# source /etc/profile.d/vte.sh\\n# fi\\n\\n# F*EX\\nexport PATH=\\\"$HOME/.fex/bin:$PATH\\\"\\nsource $HOME/.local/bin/fexdox-completion.bash\\n\\neval $(dircolors ~/.dircolors)\\n\\nexport PATH=\\\"$HOME/bin:$PATH\\\"\\n\\n# Pyenv\\nexport PYENV_ROOT=\\\"$HOME/.pyenv\\\"\\nexport PATH=\\\"$PYENV_ROOT/bin:$PATH\\\"\\neval \\\"$(pyenv init --path)\\\"\\nif command -v pyenv 1>/dev/null 2>&1; then\\n eval \\\"$(pyenv init -)\\\"\\nfi\\n\\nexport PATH=\\\"$HOME/.local/bin:$PATH\\\"\\n\\n# Enable tab-completion for directories after variables\\nshopt -s direxpand\\n\\n# br\\n# source /home/tapia/.config/broot/launcher/bash/br\\nalias br=broot\\n\\n# Generic colourizer\\n[[ -s \\\"/etc/profile.d/grc.bashrc\\\" ]] && source /etc/profile.d/grc.bashrc\\n\\nalias ls='ls --color=auto'\\nalias grep='grep --color=auto'\\nalias diff='diff --color=auto'\\n\\nexport LESS_TERMCAP_mb=$'\\\\e[1;32m'\\nexport LESS_TERMCAP_md=$'\\\\e[1;32m'\\nexport LESS_TERMCAP_me=$'\\\\e[0m'\\nexport LESS_TERMCAP_se=$'\\\\e[0m'\\nexport LESS_TERMCAP_so=$'\\\\e[01;33m'\\nexport LESS_TERMCAP_ue=$'\\\\e[0m'\\nexport LESS_TERMCAP_us=$'\\\\e[1;4;31m'\\n\\n# Force xterm-color on ssh sessions\\nalias ssh='TERM=xterm-256color ssh'\\n\\nif [ \\\"$TERM\\\" = \\\"xterm\\\" ]; then\\n export TERM=xterm-256color\\nfi\\n\\n# set PROMPT_COMMAND\\nPROMPT_COMMAND=${PROMPT_COMMAND:+$PROMPT_COMMAND; }'printf \\\"\\\\033]0;%s@%s:%s\\\\007\\\" \\\"${USER}\\\" \\\"${HOSTNAME%%.*}\\\" \\\"${PWD/#$HOME/\\\\~}\\\"'\\n\\neval \\\"$(starship init bash)\\\"\\n\\nalias obs=\\\"QT_QPA_PLATFORM=xcb obs\\\"\\n\\n# Tmux with lf\\n# alias mc='tmux new-session \\\\; send-keys lf C-m \\\\; split -h \\\\; send-keys lf C-m'\\n\\n\\n# Install packages using yay (change to pacman/AUR helper of your choice)\\nfunction yayinstall() {\\n yay -Slq | fzf -q \\\"$1\\\" -m --preview 'yay -Si {1}'| xargs -ro yay -S\\n}\\n\\n################################################\\n# FZF config\\n[ -f ~/.fzf.bash ] && source ~/.fzf.bash\\n\\nexport FZF_DEFAULT_OPTS='--color=bg+:#3B4252,bg:#2E3440,spinner:#81A1C1,hl:#616E88,fg:#D8DEE9,header:#616E88,info:#81A1C1,pointer:#d08770,marker:#d08770,fg+:#D8DEE9,prompt:#81A1C1,hl+:#81A1C1'\\nexport FZF_ALT_C_OPTS='--height=40% --min-height=20'\\nexport FZF_CTRL_T_OPTS='--height=40% --min-height=20'\\n\\n# Default commands\\nexport FZF_DEFAULT_COMMAND=\\\"fd\\\"\\nexport FZF_CTRL_T_COMMAND=\\\"$FZF_DEFAULT_COMMAND\\\"\\nexport FZF_ALT_C_COMMAND=\\\"fd -t d\\\"\\n\\nsource ${HOME}/.local/share/fzf/fzf-git.bash\\n\\n\\n# Pyhton colors\\nnorm=\\\"$(printf '\\\\033[0m')\\\" #returns to \\\"normal\\\"\\nbold=\\\"$(printf '\\\\033[0;1m')\\\" #set bold\\nred=\\\"$(printf '\\\\033[0;31m')\\\" #set red\\nboldyellowonblue=\\\"$(printf '\\\\033[0;1;33;44m')\\\"\\nboldyellow=\\\"$(printf '\\\\033[0;1;33m')\\\"\\nboldred=\\\"$(printf '\\\\033[0;1;31m')\\\" #set bold, and set red.\\n\\ncopython() {\\n python $@ 2>&1 | sed -e \\\"s/Traceback/${boldyellowonblue}&${norm}/g\\\" \\\\\\n -e \\\"s/File \\\\\\\".*\\\\.py\\\\\\\".*$/${boldyellow}&${norm}/g\\\" \\\\\\n -e \\\"s/\\\\, line [[:digit:]]\\\\+/${boldred}&${norm}/g\\\"\\n }\\n\\n\\n# BEGIN_KITTY_SHELL_INTEGRATION\\n# if test -n \\\"$KITTY_INSTALLATION_DIR\\\" -a -e \\\"$KITTY_INSTALLATION_DIR/shell-integration/bash/kitty.bash\\\"; then source \\\"$KITTY_INSTALLATION_DIR/shell-integration/bash/kitty.bash\\\"; fi\\n# END_KITTY_SHELL_INTEGRATION\\n\\nsource ${HOME}/bin/fzf-beet.bash\\n\\nexport JULIA_NUM_THREADS=4\\n\"\n },\n {\n \"alpha_fraction\": 0.5046461820602417,\n \"alphanum_fraction\": 0.5207290649414062,\n \"avg_line_length\": 23.120689392089844,\n \"blob_id\": \"ca7d3fde70d6f218545b96a34676484ac938c4a5\",\n \"content_id\": \"0fa232583cd94fc5a6f13cee59a09be6f471e805\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2799,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 116,\n \"path\": \"/home/.config/nwg-wrapper/plan.py\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\nfrom datetime import date\\nfrom textwrap import fill, wrap, shorten\\nfrom os.path import expandvars\\nimport ruamel.yaml as yaml\\nfrom pandas import DateOffset\\n\\nMONTHS = {\\n 1:\\\"Januar\\\",\\n 2:\\\"Februar\\\",\\n 3:\\\"März\\\",\\n 4:\\\"April\\\",\\n 5:\\\"Mai\\\",\\n 6:\\\"Juni\\\",\\n 7:\\\"Juli\\\",\\n 8:\\\"August\\\",\\n 9:\\\"September\\\",\\n 10:\\\"Oktober\\\",\\n 11:\\\"November\\\",\\n 12:\\\"Dezember\\\"\\n}\\n\\n\\ndef main():\\n # Read plan\\n with open(expandvars(\\\"$HOME/Nextcloud/five_year_plan.yaml\\\"), \\\"r\\\") as stream:\\n plan = yaml.safe_load(stream)\\n\\n out = format_output(plan)\\n print(out)\\n\\n\\ndef format_output(data):\\n \\\"\\\"\\\"Format to correct pango markup.\\n\\n Parameters\\n ----------\\n data : TODO\\n\\n Returns\\n -------\\n TODO\\n\\n \\\"\\\"\\\"\\n width = 34\\n curr_year = date.today().year\\n curr_month = date.today().month\\n start_date = date.today() - DateOffset(months=2)\\n start_year = start_date.year\\n dates = [start_date + DateOffset(months=k) for k in range(36)]\\n iter_dates = [(d.year, d.month) for d in dates]\\n\\n prev_year = dates[0].year\\n list_plan = '<tt><b> ' + f\\\"{start_date.year}\\\".ljust(width) + \\\"</b></tt>\\\\n\\\"\\n\\n num_elements = 0\\n max_elements = 30\\n\\n for year_i, month_i in iter_dates:\\n if year_i > prev_year:\\n list_plan += \\\"\\\\n\\\" + \\\"<tt><b> \\\" + f\\\"{year_i}\\\".ljust(width) + \\\"</b></tt>\\\\n\\\"\\n prev_year += 1\\n\\n elements_i = data[year_i][month_i-1][MONTHS[month_i]]\\n\\n if month_i == curr_month and year_i == curr_year:\\n color_month = \\\"#bf616a\\\"\\n else:\\n color_month = \\\"#eceff4\\\"\\n\\n if year_i == start_year:\\n color_year = \\\"#81a1c1\\\"\\n elif year_i == start_year + 1:\\n color_year = \\\"#ebcb8b\\\"\\n else:\\n color_year = \\\"#a3be8c\\\"\\n\\n month_str = shorten(f\\\"{MONTHS[month_i]}\\\", 3, placeholder=\\\"\\\") + \\\" \\\"\\n month_str = f'<span face=\\\"monospace\\\" foreground=\\\"{color_month}\\\">{month_str}</span>'\\n\\n list_year = []\\n\\n if elements_i:\\n for ele_i in elements_i:\\n entry_month = shorten(str(ele_i), width)\\n\\n list_year.append(entry_month)\\n num_elements += 1\\n else:\\n entry_month = \\\"\\\"\\n list_year.append(entry_month)\\n num_elements += 1\\n\\n start = '<tt> </tt>'\\n for l, e in enumerate(list_year):\\n month_entry = f'<span foreground=\\\"{color_year}\\\">{e}</span>'\\n if l > 0:\\n list_plan += f\\\"{start}{month_entry}\\\\n\\\"\\n else:\\n list_plan += f\\\"{month_str}{month_entry}\\\\n\\\"\\n\\n if num_elements >= max_elements:\\n break\\n\\n\\n base = f\\\"\\\"\\\"<span face=\\\"sans\\\">\\n<span foreground=\\\"#eceff4\\\">\\n{list_plan[:-1]}\\n</span>\\n</span>\\\"\\\"\\\"\\n\\n return base\\n\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.48847925662994385,\n \"alphanum_fraction\": 0.5115207433700562,\n \"avg_line_length\": 15.538461685180664,\n \"blob_id\": \"72567ddb9b606e50930a7998adc83bac46c3bc86\",\n \"content_id\": \"70672ea5b8337732abe607912daabffe85970684\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 217,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 13,\n \"path\": \"/home/.local/share/fzf/fzf-fex.bash\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env bash\\n\\n# GIT heart Fex\\n# -------------\\n\\nfzf-down() {\\n fzf --height 60% --min-height 20 --border --bind ctrl-/:toggle-preview \\\"$@\\\"\\n}\\n\\n_fl() {\\n fexdox -i tapia -l |\\n fzf-down -m --ansi --nth 2..,..\\n}\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.47816091775894165,\n \"alphanum_fraction\": 0.48521071672439575,\n \"avg_line_length\": 30.521739959716797,\n \"blob_id\": \"c56672da4a5d7c9172c2af8a4b2dbeeca950499e\",\n \"content_id\": \"7da509919ad8b4b8b9269aae06a8e29425418259\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 6525,\n \"license_type\": \"no_license\",\n \"max_line_length\": 100,\n \"num_lines\": 207,\n \"path\": \"/home/.config/nvim/lua/plugins/cmp.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"return {\\n {\\n 'hrsh7th/nvim-cmp',\\n name = \\\"nvim-cmp\\\",\\n event = { \\\"BufReadPost\\\", \\\"BufNewFile\\\" },\\n dependencies = {\\n { \\\"danymat/neogen\\\" },\\n { 'hrsh7th/cmp-buffer', },\\n { 'hrsh7th/cmp-omni', },\\n { 'hrsh7th/cmp-path', },\\n { 'hrsh7th/cmp-nvim-lsp', },\\n { 'hrsh7th/cmp-nvim-lsp-signature-help', },\\n { 'hrsh7th/cmp-cmdline', },\\n { \\\"davidsierradz/cmp-conventionalcommits\\\", },\\n { 'quangnguyen30192/cmp-nvim-ultisnips', },\\n { 'rose-pine/neovim' },\\n { 'windwp/nvim-autopairs' },\\n },\\n -- Configuration\\n config = function()\\n local cmp = require('cmp')\\n local cmp_select_opts = { behavior = cmp.SelectBehavior.Select }\\n local cmp_ultisnips_mappings = require('cmp_nvim_ultisnips.mappings')\\n\\n -- Define mappings for cmp\\n local neogen = require('neogen')\\n local cmp_mappings = {\\n ['<C-p>'] = cmp.mapping.select_prev_item(cmp_select_opts),\\n ['<C-n>'] = cmp.mapping.select_next_item(cmp_select_opts),\\n ['<C-Space>'] = cmp.mapping(function()\\n if cmp.visible() then\\n print(\\\"here 1\\\")\\n cmp.confirm({ select = true, behavior = 'replace' })\\n else\\n vim.fn[\\\"UltiSnips#ExpandSnippet\\\"]()\\n end\\n end,\\n { \\\"i\\\", \\\"s\\\" }\\n ),\\n -- ['<C-Space>'] = cmp.mapping.complete(cmp_select),\\n [\\\"<C-j>\\\"] = cmp.mapping(\\n function(fallback)\\n if neogen.jumpable() then\\n neogen.jump_next()\\n else\\n cmp_ultisnips_mappings.jump_forwards(fallback)\\n end\\n end,\\n { \\\"i\\\", \\\"s\\\" }\\n ),\\n [\\\"<C-z>\\\"] = cmp.mapping(\\n function(fallback)\\n if neogen.jumpable(true) then\\n neogen.jump_prev()\\n else\\n cmp_ultisnips_mappings.jump_backwards(fallback)\\n end\\n end,\\n { \\\"i\\\", \\\"s\\\" }\\n ),\\n ['<C-b>'] = cmp.mapping.scroll_docs(-4),\\n ['<C-f>'] = cmp.mapping.scroll_docs(4),\\n ['<C-e>'] = cmp.mapping.abort(),\\n }\\n\\n -- Add parenthesis automatically after functions\\n local cmp_autopairs = require('nvim-autopairs.completion.cmp')\\n cmp.event:on(\\n 'confirm_done',\\n cmp_autopairs.on_confirm_done()\\n )\\n\\n -- Define colors for the suggestion menu of nvim-cmp\\n local p = require('rose-pine.palette')\\n\\n vim.api.nvim_set_hl(0, 'CmpItemKindVariable', { fg = p.foam })\\n vim.api.nvim_set_hl(0, 'CmpItemKindClass', { fg = p.gold })\\n vim.api.nvim_set_hl(0, 'CmpItemKindInterface', { fg = p.gold })\\n vim.api.nvim_set_hl(0, 'CmpItemKindFunction', { fg = p.iris })\\n vim.api.nvim_set_hl(0, 'CmpItemKindMethod', { fg = p.iris })\\n vim.api.nvim_set_hl(0, 'CmpItemKindSnippet', { fg = p.iris })\\n vim.api.nvim_set_hl(0, 'CmpItemKindKeyword', { fg = p.subtle })\\n vim.api.nvim_set_hl(0, 'CmpItemKindText', { fg = p.subtle })\\n\\n local cmp_config = {\\n -- Define sources to be used\\n sources = {\\n {\\n name = \\\"nvim_lsp\\\",\\n priority = 9,\\n keyword_length = 1,\\n -- Disable source for comments\\n entry_filter = function(entry, ctx)\\n local context = require 'cmp.config.context'\\n return not context.in_treesitter_capture(\\\"comment\\\")\\n and not context.in_syntax_group(\\\"Comment\\\")\\n end\\n },\\n { name = 'omni' },\\n {\\n name = \\\"ultisnips\\\",\\n priority = 10,\\n -- Disable source for comments\\n entry_filter = function(entry, ctx)\\n local context = require 'cmp.config.context'\\n return not context.in_treesitter_capture(\\\"comment\\\")\\n and not context.in_syntax_group(\\\"Comment\\\")\\n end\\n },\\n {\\n name = \\\"path\\\",\\n option = { trailin_slash = true },\\n priority = 4\\n },\\n { name = \\\"latex_symbols\\\", priority = 2 },\\n {\\n name = 'buffer',\\n keyword_length = 3,\\n option = {\\n get_bufnrs = function()\\n local buf = vim.api.nvim_get_current_buf()\\n local byte_size = vim.api.nvim_buf_get_offset(buf, vim.api.nvim_buf_line_count(buf))\\n if byte_size > 1024 * 1024 then -- 1 Megabyte max\\n return {}\\n end\\n return { buf }\\n end\\n }\\n },\\n },\\n mapping = cmp_mappings,\\n snippet = {\\n expand = function(args)\\n vim.fn[\\\"UltiSnips#Anon\\\"](args.body)\\n end,\\n },\\n experimental = {\\n ghost_text = { hl_group = 'DevIconCMake' },\\n },\\n performance = {\\n max_view_entries = 40,\\n fetching_timeout = 100,\\n },\\n formatting = {\\n fields = { 'abbr', 'menu', 'kind' },\\n format = function(entry, item)\\n local short_name = {\\n nvim_lsp = 'LSP',\\n nvim_lua = 'nvim'\\n }\\n\\n local menu_name = short_name[entry.source.name] or entry.source.name\\n\\n item.menu = string.format('[%s]', menu_name)\\n return item\\n end,\\n },\\n sorting = {\\n comparators = {\\n cmp.config.compare.sort_text,\\n cmp.config.compare.offset,\\n cmp.config.compare.exact,\\n cmp.config.compare.score,\\n cmp.config.compare.kind,\\n cmp.config.compare.length,\\n cmp.config.compare.order,\\n }\\n },\\n window = {\\n completion = {\\n winhighlight = \\\"Normal:StatusLineNC,CursorLine:Substitute\\\",\\n },\\n documentation = {\\n winhighlight = 'FloatBorder:WildMenu',\\n border = \\\"rounded\\\",\\n }\\n },\\n\\n -- `/` cmdline setup.\\n cmp.setup.cmdline('/', {\\n mapping = cmp.mapping.preset.cmdline(),\\n sources = {\\n { name = 'buffer' }\\n }\\n }),\\n\\n -- `:` cmdline setup.\\n cmp.setup.cmdline(':', {\\n mapping = cmp.mapping.preset.cmdline(),\\n sources = cmp.config.sources({\\n { name = 'path' }\\n }, {\\n { name = 'cmdline', keyword_length = 2 }\\n })\\n }),\\n }\\n\\n cmp.setup(cmp_config)\\n end\\n },\\n {\\n \\\"kdheepak/cmp-latex-symbols\\\",\\n ft = \\\"julia\\\",\\n dependencies = { \\\"nvim-cmp\\\" }\\n },\\n}\\n-- vim: set shiftwidth=2:\\n\"\n },\n {\n \"alpha_fraction\": 0.6866196990013123,\n \"alphanum_fraction\": 0.6901408433914185,\n \"avg_line_length\": 19.285715103149414,\n \"blob_id\": \"5d9057e8c3450251dd530207e3f889d75129c2b8\",\n \"content_id\": \"a7d3005c53805fdc05352bdd9d177728d5da2f8b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 284,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 14,\n \"path\": \"/home/.bash_profile\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#\\n# ~/.bash_profile\\n#\\n\\n[[ -f ~/.bashrc ]] && . ~/.bashrc\\n\\n# Autocompletion for pubs\\neval \\\"$(register-python-argcomplete pubs)\\\"\\n\\n#export PATH=\\\"${PATH}:/opt/anaconda/bin\\\"\\nexport MPA=\\\"$HOME/Documents/MPA\\\"\\nexport NVIM_GTK_NO_HEADERBAR=1\\n\\nsource /home/tapia/.config/broot/launcher/bash/br\\n\"\n },\n {\n \"alpha_fraction\": 0.5376344323158264,\n \"alphanum_fraction\": 0.5423656105995178,\n \"avg_line_length\": 30.849315643310547,\n \"blob_id\": \"cb00d53da1b920e3ccf485f6994a9ae1c7f8f1af\",\n \"content_id\": \"79bc4f1931b48114c9b409737606ada7b9ccebe0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 2325,\n \"license_type\": \"no_license\",\n \"max_line_length\": 99,\n \"num_lines\": 73,\n \"path\": \"/home/.config/nvim/lua/plugins/python.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"return {\\n {\\n \\\"tpope/vim-dispatch\\\",\\n ft = { \\\"typst\\\", \\\"python\\\", \\\"fortran\\\", \\\"make\\\" },\\n keys = { \\\"<F5>\\\", \\\"<F6>\\\" },\\n config = function()\\n -- Execute programs asyncronously\\n local function save_and_run_async()\\n -- Save file\\n vim.cmd.write()\\n -- Get filetype\\n local ft = vim.bo.filetype\\n -- Execute command according to filetype\\n local dir = vim.fn.fnameescape(vim.fn.expand(\\\"%:p:h\\\"))\\n local filename = vim.fn.fnameescape(vim.fn.expand(\\\"%:p\\\"))\\n\\n if ft == \\\"typst\\\" then\\n vim.cmd('Dispatch -compiler=typst -dir=' .. dir .. ' typst compile ' .. filename)\\n elseif ft == \\\"fortran\\\" then\\n vim.cmd('Dispatch -compiler=abaqus -dir=' .. dir .. ' abq2022 make library=' .. filename)\\n elseif ft == \\\"python\\\" then\\n vim.cmd('Dispatch -compiler=python -dir=' .. dir .. ' python ' .. filename)\\n end\\n end\\n\\n local function debug_async()\\n -- Save file\\n vim.cmd.write()\\n -- Get filetype\\n local ft = vim.bo.filetype\\n -- Execute command according to filetype\\n local dir = vim.fn.fnameescape(vim.fn.expand(\\\"%:p:h\\\"))\\n local filename = vim.fn.fnameescape(vim.fn.expand(\\\"%:p\\\"))\\n\\n if ft == \\\"python\\\" then\\n vim.cmd('Start -dir=' .. dir .. ' python -m pdb ' .. filename)\\n end\\n end\\n\\n vim.keymap.set(\\\"n\\\", \\\"<F5>\\\", save_and_run_async)\\n vim.keymap.set(\\\"n\\\", \\\"<F6>\\\", debug_async)\\n -- Deactivate default mappings\\n vim.g.dispatch_no_maps = 1\\n vim.g.dispatch_no_tmux_start = 1\\n end,\\n },\\n {\\n 'untitled-ai/jupyter_ascending.vim',\\n event = \\\"BufEnter *.sync.py\\\",\\n dependencies = {\\n { 'kana/vim-textobj-user' },\\n { 'GCBallesteros/vim-textobj-hydrogen' },\\n },\\n keys = {\\n { \\\"<leader><leader>x\\\", \\\"<Plug>JupyterExecute\\\" },\\n { \\\"<leader><leader>X\\\", \\\"<Plug>JupyterExecuteAll\\\" },\\n { \\\"<leader><leader>r\\\", \\\"<Plug>JupyterRestart\\\" },\\n },\\n config = function()\\n -- Delete default key bindings\\n vim.keymap.del(\\\"n\\\", \\\"<space><space>x\\\")\\n vim.keymap.del(\\\"n\\\", \\\"<space><space>X\\\")\\n vim.keymap.del(\\\"n\\\", \\\"<space><space>r\\\")\\n end\\n },\\n -- {\\n -- 'stevearc/overseer.nvim',\\n -- opts = {\\n -- templates = { \\\"builtin\\\", \\\"user.python_build\\\" }\\n -- },\\n -- }\\n}\\n-- vim: set shiftwidth=2:\\n\"\n },\n {\n \"alpha_fraction\": 0.6427207589149475,\n \"alphanum_fraction\": 0.6622911691665649,\n \"avg_line_length\": 28.716312408447266,\n \"blob_id\": \"4d2f725416b0f459376c2b193c1ce7b4de631ea1\",\n \"content_id\": \"7274b8374edd74030d1547fa0339fdc5fb28f74f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 4194,\n \"license_type\": \"no_license\",\n \"max_line_length\": 192,\n \"num_lines\": 141,\n \"path\": \"/home/.zshrc\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# The following lines were added by compinstall\\n\\nzstyle ':completion:*' completer _expand _complete _ignored _approximate\\nzstyle ':completion:*' completions 1\\nzstyle ':completion:*' glob 1\\nzstyle ':completion:*' list-colors “${(s.:.)LS_COLORS}”\\nzstyle ':completion:*' group-name ''\\nzstyle ':completion:*' max-errors 2\\nzstyle ':completion:*' substitute 1\\nzstyle ':completion:*' file-sort modification\\nzstyle ':completion:*' verbose true\\nzstyle ':completion:*' menu select\\nzstyle :compinstall filename '/home/tapia/.zshrc'\\n\\nzmodload zsh/complist\\nbindkey -M menuselect 'h' vi-backward-char\\nbindkey -M menuselect 'k' vi-up-line-or-history\\nbindkey -M menuselect 'l' vi-forward-char\\nbindkey -M menuselect 'j' vi-down-line-or-history\\n\\n# Surroundings\\nautoload -Uz surround\\nzle -N delete-surround surround\\nzle -N add-surround surround\\nzle -N change-surround surround\\nbindkey -M vicmd cs change-surround\\nbindkey -M vicmd ds delete-surround\\nbindkey -M vicmd ys add-surround\\nbindkey -M visual S add-surround\\n\\n# Completions:\\n# - Homeshick\\nsource \\\"$HOME/.homesick/repos/homeshick/homeshick.sh\\\"\\nfpath=($HOME/.homesick/repos/homeshick/completions $fpath)\\n# - Pyenv\\nfpath=($HOME/.config/zsh/comp $fpath)\\n\\npath=($HOME/bin $path)\\n\\nautoload -Uz compinit\\n# compinit\\nif [ $(date +'%j') != $(date +\\\"%j\\\" -r $HOME/.zcompdump) ]; then\\n compinit\\nelse\\n compinit -C\\nfi\\n\\n# FEX\\ncompdef _gnu_generic fexsend fexget fexpush \\\\\\n fexpull fexstore fexpack fexzip fexsync \\\\\\n autofex xx xxx sexsend sexget sexxx\\n\\nautoload -Uz promptinit\\npromptinit\\n\\nautoload -Uz up-line-or-beginning-search down-line-or-beginning-search\\nzle -N up-line-or-beginning-search\\nzle -N down-line-or-beginning-search\\n# End of lines added by compinstall\\n# Lines configured by zsh-newuser-install\\nHISTFILE=~/.histfile\\nHISTSIZE=5000\\nSAVEHIST=10000\\nbindkey -v\\n\\nbindkey \\\"^?\\\" backward-delete-char\\nbindkey \\\"^w\\\" backward-delete-word\\n\\n# Change cursor\\n# source \\\"$HOME/.config/zsh/plugins/cursor_mode\\\"\\n\\n# Starship\\neval \\\"$(starship init zsh)\\\"\\n\\n# Set language for the console\\nexport LANG=\\\"en_US.UTF-8\\\"\\nexport EDITORCMD=\\\"nvim-qt\\\"\\nexport EDITOR=\\\"nvim\\\"\\n\\n#----------------------------------------------------------------------\\n# Virtual Environment\\nexport WORKON_HOME=~/.virtualenvs\\n# source /usr/bin/virtualenvwrapper.sh\\nexport VIRTUALENVWRAPPER_SCRIPT=/usr/bin/virtualenvwrapper.sh\\n# Lazy-load virtualenvwrapper\\nsource /usr/bin/virtualenvwrapper_lazy.sh\\n\\n#----------------------------------------------------------------------\\n# Pyenv\\nexport PYENV_ROOT=\\\"$HOME/.pyenv\\\"\\ncommand -v pyenv >/dev/null || path=($PYENV_ROOT/bin $path)\\neval \\\"$(pyenv init -)\\\"\\n\\n#----------------------------------------------------------------------\\n# F*EX\\npath=($HOME/.fex/bin $path)\\n\\n# Force xterm-color on ssh sessions\\nalias ssh='TERM=xterm-256color ssh'\\n\\nif [ \\\"$TERM\\\" = \\\"xterm\\\" ]; then\\n export TERM=xterm-256color\\nfi\\n\\n#----------------------------------------------------------------------\\n# Install packages using yay (change to pacman/AUR helper of your choice)\\nfunction yayinstall() {\\n yay -Slq | fzf -q \\\"$1\\\" -m --preview 'yay -Si {1}'| xargs -ro yay -S\\n}\\n\\n#----------------------------------------------------------------------\\n# FZF\\nsource /usr/share/fzf/key-bindings.zsh\\nsource /usr/share/fzf/completion.zsh\\nsource ~/.local/share/fzf/fzf-git.bash\\n\\n# - Options\\nexport FZF_DEFAULT_OPTS='--color=bg+:#3B4252,bg:#2E3440,spinner:#81A1C1,hl:#616E88,fg:#D8DEE9,header:#616E88,info:#81A1C1,pointer:#d08770,marker:#d08770,fg+:#D8DEE9,prompt:#81A1C1,hl+:#81A1C1'\\nexport FZF_ALT_C_OPTS='--height=40% --min-height=20'\\nexport FZF_CTRL_T_OPTS='--height=40% --min-height=20'\\n# Default commands\\nexport FZF_DEFAULT_COMMAND=\\\"fd\\\"\\n# export FZF_DEFAULT_COMMAND=\\\"bfs\\\"\\nexport FZF_CTRL_T_COMMAND=\\\"$FZF_DEFAULT_COMMAND\\\"\\nexport FZF_ALT_C_COMMAND=\\\"fd -t d\\\"\\n# export FZF_ALT_C_COMMAND=\\\"bfs -type d -nohidden \\\"\\n\\n#----------------------------------------------------------------------\\n# Colors\\nalias ls='ls --color=auto --group-directories-first'\\nalias grep='grep --color=auto'\\nalias diff='diff --color=auto'\\n\\nexport JULIA_NUM_THREADS=4\\n\\nexport MPA=\\\"$HOME/Documents/MPA\\\"\\nexport NVIM_GTK_NO_HEADERBAR=1\\n\\nexport PYTHON_KEYRING_BACKEND=keyring.backends.null.Keyring\\n\\n[ -f ~/.fzf.zsh ] && source ~/.fzf.zsh\\n\"\n },\n {\n \"alpha_fraction\": 0.5863853693008423,\n \"alphanum_fraction\": 0.6015127301216125,\n \"avg_line_length\": 26.88888931274414,\n \"blob_id\": \"b920678edc1cbf64fb9d57c9816bc1c50d2e59ae\",\n \"content_id\": \"25d2bf3d263cc73f5a77957fe6110cacfe519c89\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 2518,\n \"license_type\": \"no_license\",\n \"max_line_length\": 79,\n \"num_lines\": 90,\n \"path\": \"/home/.password-store/.extensions/get.bash\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env bash\\n# pass get - Password Store Extension (https://www.passwordstore.org/)\\n# Copyright (C) 2020 James Patrick\\n#\\n# This program is free software: you can redistribute it and/or modify\\n# it under the terms of the GNU General Public License as published by\\n# the Free Software Foundation, either version 3 of the License, or\\n# (at your option) any later version.\\n#\\n# This program is distributed in the hope that it will be useful,\\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\\n# GNU General Public License for more details.\\n#\\n# You should have received a copy of the GNU General Public License\\n# along with this program. If not, see <http://www.gnu.org/licenses/>.\\n#\\n\\nR='\\\\033[0;31m' \\nG='\\\\033[0;32m' \\nNC='\\\\033[0m'\\n\\nPASSWORD_STORE_DIR=\\\"${PASSWORD_STORE_DIR:-$HOME/.password-store}\\\"\\n\\ncmd_get_usage() {\\n cat <<-_EOF\\nUsage:\\n $PROGRAM get pattern pass_name\\n Parses the pass data for lines pulling out the value of browserpass's\\n format of \\\"key:value\\\". The 'pattern' arg is a case insenitive, extended\\n regex using grep -iE.\\n\\n https://github.com/browserpass/browserpass-extension\\n\\n Options:\\n Nada.\\n_EOF\\n exit 0\\n}\\n\\n\\ncmd_get_assert(){\\n test=\\\"$1\\\"\\n local pattern=\\\"$2\\\" expected=\\\"$3\\\"\\n\\n actual=\\\"$(cmd_get \\\"$pattern\\\")\\\"\\n if [[ \\\"$actual\\\" == \\\"$expected\\\" ]] ; then\\n echo -e \\\"$G ✔ '$actual' == '$expected' $NC\\\"\\n else\\n echo -e \\\"$R ✘ f('$test', '$pattern') → '$actual' != '$expected' $NC\\\"\\n fi\\n}\\n\\ncmd_get_test(){\\n cmd_get_assert \\\"username:value\\\" \\\"(user|username|login)\\\" \\\"value\\\"\\n cmd_get_assert \\\" user: whitespace\\\" \\\"(user|username|login)\\\" \\\"whitespace\\\"\\n\\n val=\\\"multiple:lines\\nvalue:pairs\\\"\\n cmd_get_assert \\\"$val\\\" \\\"value\\\" \\\"pairs\\\"\\n cmd_get_assert \\\"Key:capitalization doesn't counts\\\" \\\"key\\\" \\\\\\n \\\"capitalization doesn't counts\\\"\\n cmd_get_assert \\\"missing:empty\\\" \\\"i don't exist\\\" \\\"\\\"\\n\\n\\n exit 0\\n}\\n\\ncmd_get(){\\n local pattern=\\\"$1\\\" pass_name=\\\"$2\\\"\\n\\n # valid the regex is valid\\n echo | grep -qiE \\\"$pattern\\\"\\n if [[ \\\"$?\\\" == 2 ]] ; then\\n >&2 echo -e \\\"${R}Invalid Pattern:${NC} $pattern\\\"\\n return 1\\n fi \\n \\n echo \\\"${test:-$(cmd_show \\\"$pass_name\\\")}\\\" \\\\\\n | grep -iE \\\"$pattern\\\" \\\\\\n | head -1 \\\\\\n | cut -d ':' -f2- \\\\\\n | sed -e 's/^[ \\\\t]*//'\\n}\\n\\n\\n[[ \\\"$1\\\" == \\\"test\\\" ]] && cmd_get_test\\n[[ \\\"$1\\\" == \\\"help\\\" || \\\"$1\\\" == \\\"--help\\\" || \\\"$1\\\" == \\\"-h\\\" ]] && cmd_get_usage\\n[[ \\\"$#\\\" != \\\"2\\\" ]] && cmd_get_usage\\ncmd_get \\\"$@\\\"\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.45193371176719666,\n \"alphanum_fraction\": 0.46519336104393005,\n \"avg_line_length\": 23.45945930480957,\n \"blob_id\": \"a9787f2465191b0112bb41b9f948abfe57b3e7cf\",\n \"content_id\": \"20fbedce07a07334915e1c3927382e7d1c802015\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 905,\n \"license_type\": \"no_license\",\n \"max_line_length\": 81,\n \"num_lines\": 37,\n \"path\": \"/home/.config/nvim/lua/plugins/git.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"return {\\n -- Fugitive\\n {\\n 'tpope/vim-fugitive',\\n cmd = \\\"G\\\",\\n keys = {\\n { \\\"<leader>gs\\\", vim.cmd.Git },\\n { \\\"<leader>gc\\\", \\\"<cmd>Git commit<cr>\\\" },\\n },\\n },\\n -- Gitsigns\\n {\\n 'lewis6991/gitsigns.nvim',\\n config = function(_, opts)\\n require(\\\"gitsigns\\\").setup {\\n on_attach = function(bufnr)\\n local gitsigns = require('gitsigns')\\n vim.keymap.set(\\\"n\\\", \\\"<leader>gn\\\",\\n function()\\n gitsigns.next_hunk({ foldopen = true })\\n end\\n )\\n vim.keymap.set(\\\"n\\\", \\\"<leader>gN\\\",\\n function()\\n gitsigns.prev_hunk({ foldopen = true })\\n end\\n )\\n vim.keymap.set(\\\"n\\\", \\\"<leader>gp\\\",\\n gitsigns.preview_hunk\\n )\\n end\\n }\\n vim.api.nvim_set_hl(0, 'GitSignsAddLn', { fg = \\\"#434c5e\\\", bg = \\\"#a3be8c\\\" })\\n end\\n },\\n}\\n-- vim: set shiftwidth=2:\\n\"\n },\n {\n \"alpha_fraction\": 0.7136150002479553,\n \"alphanum_fraction\": 0.7230046987533569,\n \"avg_line_length\": 25.625,\n \"blob_id\": \"63f712d2901fc5751b0fc564f13014da15ecf221\",\n \"content_id\": \"47dc5cbc03d9a1751eff9a0c8b107852eaba8dbe\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 213,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 8,\n \"path\": \"/home/.config/nvim/after/ftplugin/tex.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"-- Set spelling\\nvim.cmd('syntax spell toplevel')\\nvim.opt_local.spell = true\\n-- Define tex flavor to latex\\nvim.g.tex_flavor = 'latex'\\n-- Set tab to two-spaces\\nvim.opt_local.shiftwidth = 2\\nvim.opt_local.tabstop = 2\\n\"\n },\n {\n \"alpha_fraction\": 0.49486976861953735,\n \"alphanum_fraction\": 0.5059195160865784,\n \"avg_line_length\": 28.465116500854492,\n \"blob_id\": \"417e236a0237f91ab6b7ff65959b21f412bb2024\",\n \"content_id\": \"7ef3d01320dd269097d420c1a17de133c31e2e0f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 2534,\n \"license_type\": \"no_license\",\n \"max_line_length\": 94,\n \"num_lines\": 86,\n \"path\": \"/home/.config/nvim/lua/plugins/treesitter.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"return {\\n {\\n 'nvim-treesitter/nvim-treesitter',\\n event = { \\\"BufReadPost\\\", \\\"BufNewFile\\\" },\\n build = \\\":TSUpdate\\\",\\n dependencies = { \\\"nvim-treesitter/nvim-treesitter-textobjects\\\" },\\n opts = {\\n -- A list of parser names, or \\\"all\\\" (the five listed parsers should always be installed)\\n ensure_installed = {\\n \\\"bash\\\",\\n \\\"bibtex\\\",\\n \\\"comment\\\",\\n \\\"css\\\",\\n \\\"dockerfile\\\",\\n \\\"javascript\\\",\\n \\\"json\\\",\\n \\\"julia\\\",\\n \\\"lua\\\",\\n \\\"python\\\",\\n \\\"query\\\",\\n \\\"toml\\\",\\n \\\"vim\\\",\\n \\\"vimdoc\\\",\\n \\\"yaml\\\",\\n \\\"yuck\\\",\\n },\\n\\n -- Install parsers synchronously (only applied to `ensure_installed`)\\n sync_install = false,\\n auto_install = false,\\n highlight = {\\n enable = true,\\n additional_vim_regex_highlighting = false,\\n },\\n rainbow = {\\n enable = true,\\n colors = {\\n \\\"#eceff4\\\",\\n \\\"#88c0d0\\\",\\n \\\"#ebcb8b\\\",\\n \\\"#81a1c1\\\",\\n \\\"#d08770\\\",\\n },\\n -- Highlight also non-parentheses delimiters, boolean or table: lang -> boolean\\n extended_mode = false,\\n -- Do not enable for files with more than 1000 lines, int\\n max_file_lines = 1000,\\n },\\n textobjects = {\\n select = {\\n enable = true,\\n -- Automatically jump forward to textobj, similar to targets.vim\\n lookahead = true,\\n keymaps = {\\n -- You can use the capture groups defined in textobjects.scm\\n [\\\"af\\\"] = \\\"@function.outer\\\",\\n [\\\"if\\\"] = \\\"@function.inner\\\",\\n [\\\"ac\\\"] = \\\"@class.outer\\\",\\n [\\\"ic\\\"] = { query = \\\"@class.inner\\\", desc = \\\"Select inner part of a class region\\\" },\\n },\\n selection_modes = {\\n ['@parameter.outer'] = 'v', -- charwise\\n ['@function.outer'] = 'V', -- linewise\\n ['@class.outer'] = 'V', -- blockwise\\n },\\n include_surrounding_whitespace = false,\\n },\\n },\\n },\\n config = function(_, opts)\\n require(\\\"nvim-treesitter.configs\\\").setup(opts)\\n -- Foldings\\n vim.opt.foldmethod = \\\"expr\\\"\\n vim.opt.foldexpr = \\\"nvim_treesitter#foldexpr()\\\"\\n vim.opt.foldnestmax = 2\\n vim.opt.foldenable = false\\n\\n vim.cmd('hi pythonTSParameter guifg=#b48ead')\\n vim.cmd('hi TSConstant guifg=#ebcb8b')\\n\\n end\\n },\\n { \\\"nvim-treesitter/nvim-treesitter-textobjects\\\", },\\n { 'nvim-treesitter/playground' },\\n}\\n-- vim: set shiftwidth=2:\\n\"\n },\n {\n \"alpha_fraction\": 0.5164835453033447,\n \"alphanum_fraction\": 0.5252183675765991,\n \"avg_line_length\": 28.575000762939453,\n \"blob_id\": \"edc4298f60815d535c736fce3333ba6ffeb71712\",\n \"content_id\": \"54f6575b5d7b900519c5aea32514074e45a1c033\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 3549,\n \"license_type\": \"no_license\",\n \"max_line_length\": 88,\n \"num_lines\": 120,\n \"path\": \"/home/.config/nvim/lua/plugins/latex.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"return {\\n -- Integration with latex\\n {\\n 'lervag/vimtex',\\n ft = { \\\"tex\\\", \\\"cls\\\", \\\"sty\\\", \\\"tikz\\\" },\\n dependencies = { \\\"hrsh7th/nvim-cmp\\\" },\\n keys = {\\n { \\\"<localleader>ll\\\", \\\"<Plug>(vimtex-compile-ss)\\\" },\\n { \\\"<localleader>ll\\\", \\\"<Plug>(vimtex-compile-selected)\\\", mode = \\\"v\\\" },\\n { \\\"<localleader>lv\\\", \\\"<Plug>(vimtex-view)\\\" },\\n { \\\"<localleader>lo\\\", \\\"<Plug>(vimtex-compile-output)\\\" },\\n { \\\"<localleader>rf\\\", \\\"<cmd>VimtexRefreshFolds<cr>\\\" },\\n },\\n config = function()\\n vim.g.tex_flavor = 'latex'\\n\\n -- Set autocompletion\\n require('cmp').setup.buffer {\\n formatting = {\\n format = function(entry, vim_item)\\n vim_item.menu = ({\\n omni = (vim.inspect(vim_item.menu):gsub('%\\\"', \\\"\\\")),\\n buffer = \\\"[Buffer]\\\",\\n -- formatting for other sources\\n })[entry.source.name]\\n return vim_item\\n end,\\n },\\n sources = {\\n { name = 'omni', priority = 9 },\\n { name = 'buffer' },\\n { name = \\\"path\\\", priority = 4 },\\n {\\n name = \\\"ultisnips\\\",\\n priority = 10,\\n -- Disable source for comments\\n entry_filter = function(entry, ctx)\\n local context = require 'cmp.config.context'\\n return not context.in_treesitter_capture(\\\"comment\\\")\\n and not context.in_syntax_group(\\\"Comment\\\")\\n end\\n },\\n -- other sources\\n },\\n }\\n\\n -- Set options for vimtex\\n vim.g.vimtex_compiler_latexmk = {\\n out_dir = 'out',\\n aux_dir = '.aux',\\n callback = 1,\\n continuous = 0,\\n executable = 'latexmk',\\n options = { '-verbose',\\n '-shell-escape',\\n '-file-line-error',\\n '-synctex=1',\\n '-interaction=nonstopmode',\\n },\\n }\\n\\n vim.g.vimtex_compiler_latexmk_engines = { _ = '-lualatex' }\\n\\n vim.g.vimtex_complete_enabled = 1\\n vim.g.vimtex_complete_close_braces = 0\\n vim.g.vimtex_complete_ignore_case = 1\\n vim.g.vimtex_complete_smart_case = 1\\n vim.g.vimtex_fold_enabled = 1\\n\\n if vim.fn.executable('bibtexparser') then\\n vim.g.vimtex_parser_bib_backend = 'bibtexparser'\\n end\\n\\n vim.g.vimtex_syntax_conceal = {\\n accents = 1,\\n ligatures = 0,\\n cites = 1,\\n fancy = 0,\\n spacing = 0,\\n greek = 0,\\n math_bounds = 0,\\n math_delimiters = 0,\\n math_fracs = 0,\\n math_super_sub = 0,\\n math_symbols = 1,\\n sections = 0,\\n styles = 1,\\n }\\n\\n -- vim.l.concealcursor = ''\\n\\n vim.g.vimtex_indent_enabled = true\\n vim.g.vimtex_indent_on_ampersands = false\\n vim.g.vimtex_indent_bib_enabled = false\\n vim.g.vimtex_fold_bib_enabled = false\\n\\n vim.g.vimtex_imaps_leader = '#'\\n vim.g.vimtex_quickfix_method = 'latexlog'\\n vim.g.matchup_override_vimtex = true\\n vim.g.vimtex_compiler_progname = vim.env.HOME .. '/.virtualenvs/py3neovim/bin/nvr'\\n\\n vim.g.vimtex_view_method = 'zathura'\\n vim.g.vimtex_view_forward_search_on_start = true\\n\\n vim.g.vimtex_echo_verbose_input = 0\\n\\n vim.g.vimtex_quickfix_autoclose_after_keystrokes = 2\\n vim.g.vimtex_quickfix_open_on_warning = 0\\n\\n -- Delimiter modifiers\\n vim.g.vimtex_delim_toggle_mod_list = {\\n { '\\\\\\\\left', '\\\\\\\\right' },\\n { '\\\\\\\\mleft', '\\\\\\\\mright' },\\n }\\n end\\n },\\n -- Transfor latex symbols to unicode\\n { 'joom/latex-unicoder.vim' },\\n}\\n-- vim: set shiftwidth=2:\\n\"\n },\n {\n \"alpha_fraction\": 0.5978915691375732,\n \"alphanum_fraction\": 0.6069276928901672,\n \"avg_line_length\": 26.625,\n \"blob_id\": \"b434a92ab11395af34a200267a8c35b7f8265731\",\n \"content_id\": \"c36d180fc0cba7b05454e39c708fe026f3b1dbae\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 664,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 24,\n \"path\": \"/home/.config/nvim/lua/tapia/autocmd.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"-- Define some useful autocommands\\n\\nvim.api.nvim_create_autocmd({ 'FileType' }, {\\n pattern = { 'lua' },\\n callback = function()\\n vim.opt.expandtab = true\\n vim.opt.softtabstop = 4\\n vim.opt.shiftwidth = 4\\n vim.opt.tabstop = 4\\n end,\\n})\\n\\nlocal asyncrun_group = vim.api.nvim_create_augroup('asyncrun', { clear = true })\\n\\nvim.api.nvim_create_autocmd({ 'User' }, {\\n pattern = { 'AsyncRunStart' },\\n group = asyncrun_group,\\n command = 'call asyncrun#quickfix_toggle(10, 1)',\\n})\\nvim.api.nvim_create_autocmd({ 'User' }, {\\n pattern = { 'AsyncRunStop' },\\n group = asyncrun_group,\\n command = \\\"copen | clast | wincmd k\\\",\\n})\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.33760684728622437,\n \"alphanum_fraction\": 0.3390313386917114,\n \"avg_line_length\": 25,\n \"blob_id\": \"0c2df168a962a77ab7c1186c409bab2000306147\",\n \"content_id\": \"87e3b1851e67cac1a2757f645f1fa7932ffa2e1e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 702,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 27,\n \"path\": \"/home/.config/nvim/lua/overseer/template/user/python_build.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"return {\\n name = \\\"python_build\\\",\\n builder = function()\\n -- Full path to current file (see :help expand())\\n local file = vim.fn.expand(\\\"%:p\\\")\\n return {\\n cmd = { \\\"python\\\" },\\n args = { file },\\n components = {\\n { \\\"on_exit_set_status\\\" },\\n {\\n \\\"display_duration\\\",\\n detail_level = 2,\\n },\\n {\\n \\\"on_output_quickfix\\\",\\n open = true,\\n items_only = false,\\n tail = true,\\n },\\n },\\n }\\n end,\\n condition = {\\n filetype = { \\\"python\\\" },\\n },\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.774193525314331,\n \"alphanum_fraction\": 0.774193525314331,\n \"avg_line_length\": 30,\n \"blob_id\": \"2d7633a2450ccc33850d82636fdfc4823583d915\",\n \"content_id\": \"844318b10e71f619b6632be2c1b7027dbc0677b0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 31,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 1,\n \"path\": \"/home/.config/nvim/after/ftplugin/pandoc.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"vim.opt_local.formatexpr = nil\\n\"\n },\n {\n \"alpha_fraction\": 0.5241379141807556,\n \"alphanum_fraction\": 0.5413793325424194,\n \"avg_line_length\": 23.16666603088379,\n \"blob_id\": \"8439b25e5e91c9225c5b6c46dee912d874da73c3\",\n \"content_id\": \"97a47de4944d7c718a9dcc9767831b3acf6b2cb7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 290,\n \"license_type\": \"no_license\",\n \"max_line_length\": 89,\n \"num_lines\": 12,\n \"path\": \"/home/.config/nvim/lua/plugins/typst.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"return {\\n {\\n 'kaarmu/typst.vim',\\n ft = { \\\"typst\\\" },\\n branch = 'main',\\n dependencies = { { 'skywind3000/asyncrun.vim' } },\\n config = function()\\n vim.keymap.set(\\\"n\\\", \\\"<leader>lv\\\", \\\"<cmd>AsyncRun -mode=hide zathura '%<'.pdf <cr>\\\")\\n end\\n },\\n}\\n-- vim: set shiftwidth=2:\\n\"\n },\n {\n \"alpha_fraction\": 0.5249999761581421,\n \"alphanum_fraction\": 0.5249999761581421,\n \"avg_line_length\": 25.66666603088379,\n \"blob_id\": \"467ff0002559e0b6595720df20cb96e999349d1a\",\n \"content_id\": \"a412b42c24fb5e212783e89467a5aabc3dddc584\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 160,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 6,\n \"path\": \"/home/.config/nvim/after/ftplugin/gitcommit.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"require 'cmp'.setup.buffer {\\n sources = require 'cmp'.config.sources(\\n { { name = 'conventionalcommits' } },\\n { { name = 'buffer' } }\\n ),\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.7816091775894165,\n \"alphanum_fraction\": 0.7816091775894165,\n \"avg_line_length\": 23.85714340209961,\n \"blob_id\": \"ac890e13d25f46c20061366c4474a86ece556ddf\",\n \"content_id\": \"002568a7a7729a945cf639bd56cfa6f82165d9d5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"INI\",\n \"length_bytes\": 174,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 7,\n \"path\": \"/home/.pylintrc\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"[MESSAGES CONTROL]\\n\\ndisable=too-many-locals,missing-docstring,invalid-name\\n\\n[VARIABLES]\\n# Good variable names,which should always be accepted\\ngood-names=i,j,k,ix,ij,ik,x,y,z\\n\"\n },\n {\n \"alpha_fraction\": 0.6275992393493652,\n \"alphanum_fraction\": 0.6389414072036743,\n \"avg_line_length\": 22.46666717529297,\n \"blob_id\": \"bf7750d5ca94cd60214a7ea05d27f3336fe7afcc\",\n \"content_id\": \"c55502739b69ea67f7f3e660d37e13d8fc75c096\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 1058,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 45,\n \"path\": \"/home/bin/yalafi-grammarous\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/bash\\n\\n#\\n# interface between vim-grammarous or vim-LanguageTool and yalafi.shell\\n# - collect all options passed by editor, except --api\\n# - languagetool-commandline.jar is a bit picky with repeated options\\n#\\n\\n# LT's base directory\\n#\\nltdir=~/.vim/plugged/vim-grammarous/misc/LanguageTool-4.8\\n\\n# comment out to use languagetool-commandline\\n#\\nuse_server=\\\"--server my\\\"\\n\\n# vim-grammarous needs byte offsets in XML report\\n# --> set to xml-b\\n#\\noutput=xml-b\\noutput=xml\\n\\nopts=x\\nlang=en-GB\\nwhile [ $# -gt 1 ]\\ndo\\n if [ X$1 == X-l ]\\n then\\n # languagetool-commandline does not like multiple language specs\\n shift\\n lang=$1\\n elif [ X$1 == X-c ]\\n then\\n # languagetool-commandline does not like multiple encoding specs\\n # (yalafi.shell already includes --encoding utf-8)\\n shift\\n elif [ X$1 != X--api ]\\n then\\n opts+=\\\"$1 \\\"\\n fi\\n shift\\ndone\\n\\npython3 -m yalafi.shell $use_server --output $output --language $lang \\\\\\n --lt-directory $ltdir --lt-options \\\"$opts\\\" $1 2>/dev/null\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4814264476299286,\n \"alphanum_fraction\": 0.5061911940574646,\n \"avg_line_length\": 35.05356979370117,\n \"blob_id\": \"b63b820a720a8521008908c2501befa3522435ee\",\n \"content_id\": \"5be70bd494683b5e033330e651189918d80eac66\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 2025,\n \"license_type\": \"no_license\",\n \"max_line_length\": 144,\n \"num_lines\": 56,\n \"path\": \"/home/.config/nvim/lua/tapia/init.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"require(\\\"tapia.remap\\\")\\nrequire(\\\"tapia.set\\\")\\nrequire(\\\"tapia.autocmd\\\")\\n\\nvim.opt.guicursor =\\n\\\"n-v-c:block,i-ci-ve:ver25,r-cr:hor20,o:hor50,a:blinkwait700-blinkoff400-blinkon250-Cursor/lCursor,sm:block-blinkwait175-blinkoff150-blinkon175\\\"\\n\\n-- Define format for quickfix window\\nfunction _G.qftf(info)\\n local items\\n local ret = {}\\n if info.quickfix == 1 then\\n items = vim.fn.getqflist({ id = info.id, items = 0 }).items\\n else\\n items = vim.fn.getloclist(info.winid, { id = info.id, items = 0 }).items\\n end\\n local limit = 31\\n local fname_fmt1, fname_fmt2 = '%-' .. limit .. 's', '…%.' .. (limit - 1) .. 's'\\n local valid_fmt = '%s │%5d:%2d│%s %s'\\n for i = info.start_idx, info.end_idx do\\n local e = items[i]\\n local fname = ''\\n local str\\n if e.valid == 1 then\\n if e.bufnr > 0 then\\n fname = vim.fn.bufname(e.bufnr)\\n if fname == '' then\\n fname = '[No Name]'\\n else\\n fname = fname:gsub('^' .. vim.env.HOME, '~')\\n end\\n -- char in fname may occur more than 1 width, ignore this issue in order to keep performance\\n if #fname <= limit then\\n fname = fname_fmt1:format(fname)\\n else\\n fname = fname_fmt2:format(fname:sub(1 - limit))\\n end\\n end\\n local lnum = e.lnum > 99999 and -1 or e.lnum\\n local cnum = e.col\\n local qtype = e.type == '' and '' or ' ' .. e.type:sub(1, 1):upper()\\n local module\\n if string.len(e.module) > 1 and string.len(e.text) > 1 then\\n module = e.module .. \\\": \\\"\\n else\\n module = e.module\\n end\\n local textm = e.text:gsub(\\\"\\\\n\\\", ' ')\\n str = valid_fmt:format(fname, lnum, cnum, qtype, module .. textm)\\n else\\n str = e.text\\n end\\n table.insert(ret, str)\\n end\\n return ret\\nend\\n\"\n },\n {\n \"alpha_fraction\": 0.5099928379058838,\n \"alphanum_fraction\": 0.5171306133270264,\n \"avg_line_length\": 26.20388412475586,\n \"blob_id\": \"d72f69a80924a79d2c049996b87339136e75e6f3\",\n \"content_id\": \"01a79f0d7a90c89e9079f79840b21e1581e41847\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 2802,\n \"license_type\": \"no_license\",\n \"max_line_length\": 87,\n \"num_lines\": 103,\n \"path\": \"/home/.config/nvim/lua/plugins/ui.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"return {\\n -- Colorschemes\\n {\\n 'shaunsingh/nord.nvim',\\n name = 'nord',\\n config = function()\\n vim.cmd('colorscheme nord')\\n vim.api.nvim_set_hl(0, \\\"FloatBorder\\\", { fg = \\\"#ebcb8b\\\", bold = true })\\n vim.api.nvim_set_hl(0, \\\"NormalFloat\\\", { bg = \\\"#434c5e\\\" })\\n end\\n },\\n -- Tmux\\n {\\n 'jpalardy/vim-slime',\\n keys = {\\n { \\\"<C-c><C-c>\\\", mode = \\\"n\\\" },\\n { \\\"<C-c><C-c>\\\", mode = \\\"v\\\" },\\n },\\n config = function()\\n vim.g.slime_target = \\\"tmux\\\"\\n vim.g.slime_default_config = { socket_name = \\\"default\\\", target_pane = \\\"0.1\\\" }\\n vim.g.slime_bracketed_paste = 1\\n end\\n },\\n -- Status line\\n {\\n 'nvim-lualine/lualine.nvim',\\n event = { \\\"BufReadPost\\\", \\\"BufNewFile\\\" },\\n dependencies = {\\n 'nvim-tree/nvim-web-devicons',\\n },\\n opts = {\\n extensions = { 'quickfix', 'fugitive' },\\n tabline = {\\n lualine_a = { 'buffers' },\\n lualine_z = { function()\\n return [[buffers]]\\n end },\\n },\\n },\\n },\\n -- FZF support\\n {\\n 'junegunn/fzf.vim',\\n dependencies = {\\n { 'junegunn/fzf', build = './install --all' },\\n },\\n },\\n -- Integration with tmux\\n {\\n 'christoomey/vim-tmux-navigator',\\n lazy = true,\\n keys = {\\n { \\\"<A-h>\\\", \\\"<cmd>TmuxNavigateLeft<cr>\\\", \\\"n\\\", { silent = true } },\\n { \\\"<A-j>\\\", \\\"<cmd>TmuxNavigateDown<cr>\\\", \\\"n\\\", { silent = true } },\\n { \\\"<A-k>\\\", \\\"<cmd>TmuxNavigateUp<cr>\\\", \\\"n\\\", { silent = true } },\\n { \\\"<A-l>\\\", \\\"<cmd>TmuxNavigateRight<cr>\\\", \\\"n\\\", { silent = true } },\\n },\\n init = function()\\n vim.g.tmux_navigator_no_mappings = true\\n end\\n },\\n -- Nice visualization of quickfix errors\\n {\\n 'kevinhwang91/nvim-bqf',\\n config = function()\\n vim.o.qftf = '{info -> v:lua._G.qftf(info)}'\\n\\n require('bqf').setup()\\n vim.api.nvim_set_hl(0, 'BqfPreviewTitle', { bg = '#ebcb8b', fg = '#3b4252' })\\n end\\n },\\n -- Overview of code\\n {\\n 'stevearc/aerial.nvim',\\n ft = { \\\"python\\\", \\\"julia\\\", \\\"tex\\\", \\\"markdown\\\", \\\"typst\\\" },\\n dependencies = {\\n -- \\\"nvim-treesitter/nvim-treesitter\\\",\\n \\\"nvim-tree/nvim-web-devicons\\\"\\n },\\n keys = { { \\\"<leader>a\\\", \\\"<cmd>AerialToggle<cr>\\\" } },\\n config = function()\\n local aerial = require('aerial')\\n require('aerial').setup({\\n -- optionally use on_attach to set keymaps when aerial has attached to a buffer\\n on_attach = function(bufnr)\\n -- Jump forwards/backwards with '{' and '}'\\n vim.keymap.set('n', '}', aerial.next, { buffer = bufnr })\\n vim.keymap.set('n', '{', aerial.prev, { buffer = bufnr })\\n end\\n })\\n end\\n },\\n -- Better display of errors\\n {\\n \\\"folke/trouble.nvim\\\",\\n dependencies = \\\"web-devicons\\\",\\n keys = {\\n { \\\"<leader>tt\\\", \\\"<cmd>TroubleToggle<cr>\\\", \\\"n\\\" },\\n }\\n },\\n}\\n-- vim: set shiftwidth=2:\\n\"\n },\n {\n \"alpha_fraction\": 0.5759046673774719,\n \"alphanum_fraction\": 0.5781112313270569,\n \"avg_line_length\": 30.041095733642578,\n \"blob_id\": \"e28bfd847d06b293b6668f2cfb3635b35d472a67\",\n \"content_id\": \"62267b87736a5543b1f91b9f780a0d13904f79a7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 2266,\n \"license_type\": \"no_license\",\n \"max_line_length\": 88,\n \"num_lines\": 73,\n \"path\": \"/home/.config/nvim/lua/tapia/remap.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"vim.keymap.set(\\\"n\\\", \\\"<leader>pv\\\", vim.cmd.Ex)\\n\\n-- Allow to move lines in visual mode\\nvim.keymap.set(\\\"v\\\", \\\"J\\\", \\\":m '>+1<CR>gv=gv\\\")\\nvim.keymap.set(\\\"v\\\", \\\"K\\\", \\\":m '<-2<CR>gv=gv\\\")\\n-- Keep search items in the middle of the screen\\nvim.keymap.set(\\\"n\\\", \\\"n\\\", \\\"nzzzv\\\")\\nvim.keymap.set(\\\"n\\\", \\\"N\\\", \\\"Nzzzv\\\")\\n\\n-- Paste without deleting the previous selection\\nvim.keymap.set(\\\"x\\\", \\\"<leader>p\\\", [[\\\"_dP]])\\n-- Yank to system clipboard\\n-- vim.keymap.set({\\\"n\\\", \\\"v\\\"}, \\\"<leader>y\\\", [[\\\"+y]])\\n-- vim.keymap.set(\\\"n\\\", \\\"<leader>Y\\\", [[\\\"+Y]])\\n\\nvim.keymap.set(\\\"n\\\", \\\"Q\\\", \\\"<nop>\\\")\\n\\n-- Replace word below the cursor\\nvim.keymap.set(\\\"n\\\", \\\"<leader>s\\\", [[:%s/\\\\<<C-r><C-w>\\\\>/<C-r><C-w>/gI<Left><Left><Left>]])\\n\\n-- Correct spelling in insert mode\\nvim.keymap.set(\\\"i\\\", \\\"<C-s>\\\", \\\"<c-g>u<Esc>[s1z=`]a<c-g>u\\\")\\n\\n-- Faster folding\\nvim.keymap.set({ \\\"n\\\", \\\"v\\\" }, \\\"<space>\\\", \\\"za\\\")\\n\\n-- Map <Esc> to shift-space\\nvim.keymap.set({ \\\"i\\\", \\\"v\\\", \\\"s\\\" }, \\\"<S-Space>\\\", \\\"<Esc>\\\")\\nvim.keymap.set({ \\\"i\\\", \\\"v\\\", \\\"s\\\" }, \\\"<M-Space>\\\", \\\"<Esc>\\\")\\n\\n-- Redefine movements\\nvim.keymap.set(\\\"n\\\", \\\"j\\\", \\\"gj\\\")\\nvim.keymap.set(\\\"n\\\", \\\"k\\\", \\\"gk\\\")\\nvim.keymap.set(\\\"n\\\", \\\"gj\\\", \\\"j\\\")\\nvim.keymap.set(\\\"n\\\", \\\"gk\\\", \\\"k\\\")\\n\\n-- Escape to normal mode when in terminal\\nvim.keymap.set(\\\"t\\\", \\\"<Esc>\\\", \\\"<C-\\\\\\\\><C-n>\\\")\\n\\n-- For the quickfix window it is better to undo the previous remapping\\nlocal qf_group = vim.api.nvim_create_augroup('quickfix', { clear = true })\\nvim.api.nvim_create_autocmd({ 'FileType' }, {\\n pattern = { 'qf' },\\n group = qf_group,\\n callback = function()\\n vim.keymap.set('n', 'j', 'j', { buffer = true })\\n vim.keymap.set('n', 'k', 'k', { buffer = true })\\n end,\\n})\\n\\n-- Move to next buffer\\nvim.keymap.set(\\\"n\\\", \\\"tn\\\", \\\"<cmd>bnext<cr>\\\")\\nvim.keymap.set(\\\"n\\\", \\\"tp\\\", \\\"<cmd>bprevious<cr>\\\")\\n\\n-- Close current buffer\\nvim.keymap.set(\\\"n\\\", \\\"<leader>bq\\\", \\\"<cmd>bp <BAR> bd #<cr>\\\")\\n\\n-- Close quickfix window\\nvim.keymap.set(\\\"n\\\", \\\"<leader>cq\\\", vim.cmd.cclose)\\n\\n-- Run files with overseer\\n-- local overseer = require(\\\"overseer\\\")\\n-- local function compile_and_run()\\n-- local file_path = vim.api.nvim_buf_get_name(0)\\n-- local file_cwd = vim.loop.cwd()\\n\\n-- if vim.bo.filetype == 'python' then\\n-- vim.cmd(\\\"write\\\")\\n-- overseer.run_template({ name = \\\"python_build\\\" })\\n-- end\\n-- end\\n\\n-- vim.keymap.set('n', '<F5>', compile_and_run)\\n\"\n },\n {\n \"alpha_fraction\": 0.4417218565940857,\n \"alphanum_fraction\": 0.4562913775444031,\n \"avg_line_length\": 25.964284896850586,\n \"blob_id\": \"972588f8474f1be552ed4704c95c32c03be68730\",\n \"content_id\": \"77c513644314249cf764242b60dfd231259e7a9e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 1510,\n \"license_type\": \"no_license\",\n \"max_line_length\": 106,\n \"num_lines\": 56,\n \"path\": \"/home/.config/nvim/lua/plugins/telescope.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"return {\\n {\\n 'nvim-telescope/telescope.nvim',\\n tag = '0.1.1',\\n dependencies = { { 'nvim-lua/plenary.nvim' } },\\n cmd = \\\"Telescope\\\",\\n keys = {\\n { \\\"<leader>ff\\\", function() require(\\\"telescope.builtin\\\").find_files() end, desc = \\\"find files\\\" },\\n { \\\"<leader>fg\\\", function() require(\\\"telescope.builtin\\\").live_grep() end, desc = \\\"live grep\\\" },\\n { \\\"<leader>fb\\\", function() require(\\\"telescope.builtin\\\").buffers() end, desc = \\\"find buffers\\\" },\\n { \\\"<C-p>\\\", function() require(\\\"telescope.builtin\\\").git_files() end, desc = \\\"find git files\\\" },\\n {\\n \\\"<leader>ps\\\",\\n function()\\n require(\\\"telescope.builtin\\\").grep_string({ search = vim.fn.input(\\\"Grep > \\\") });\\n end,\\n desc = \\\"Grep\\\"\\n },\\n },\\n opts = {\\n defaults = {\\n scroll_strategy = \\\"limit\\\",\\n winblend = 30,\\n sorting_strategy = 'ascending',\\n layout_strategy = 'vertical',\\n layout_config = {\\n vertical = {\\n width = 0.85,\\n height = 0.95,\\n preview_cutoff = 10,\\n mirror = false,\\n },\\n center = {\\n width = 0.85,\\n height = 0.95,\\n preview_cutoff = 10,\\n prompt_position = 'top',\\n },\\n },\\n file_ignore_patterns = {\\n \\\"%.pyc\\\",\\n \\\"%.rpy\\\",\\n \\\"%.fil\\\",\\n }\\n },\\n pickers = {\\n find_files = {\\n follow = true,\\n }\\n }\\n\\n }\\n\\n },\\n}\\n-- vim: set shiftwidth=2:\\n\"\n },\n {\n \"alpha_fraction\": 0.4535752534866333,\n \"alphanum_fraction\": 0.45464247465133667,\n \"avg_line_length\": 22.424999237060547,\n \"blob_id\": \"851dc906113c1e27ba6f87905a044f710e8a3e11\",\n \"content_id\": \"fbda229fc891982490748f20acc2d4e316672314\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 937,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 40,\n \"path\": \"/home/.config/nvim/lua/plugins/coding.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"return {\\n {\\n \\\"ThePrimeagen/refactoring.nvim\\\",\\n dependencies = {\\n { \\\"nvim-lua/plenary.nvim\\\" },\\n -- { \\\"nvim-treesitter/nvim-treesitter\\\" }\\n },\\n ft = { \\\"python\\\", \\\"lua\\\" },\\n keys = {\\n {\\n \\\"<leader>re\\\",\\n \\\"<cmd>Refactor extract<cr>\\\",\\n mode = \\\"v\\\",\\n { noremap = true, silent = true, expr = false }\\n },\\n {\\n \\\"<leader>rf\\\",\\n \\\"<cmd>Refactor extract_to_file<cr>\\\",\\n mode = \\\"v\\\",\\n { noremap = true, silent = true, expr = false }\\n },\\n {\\n \\\"<leader>rv\\\",\\n \\\"<cmd>Refactor extract_var<cr>\\\",\\n mode = \\\"v\\\",\\n { noremap = true, silent = true, expr = false }\\n },\\n {\\n \\\"<leader>ri\\\",\\n \\\"<cmd>Refactor inline_var<cr>\\\",\\n mode = \\\"v\\\",\\n { noremap = true, silent = true, expr = false }\\n },\\n },\\n config = function()\\n require(\\\"refactoring\\\").setup({})\\n end\\n },\\n}\\n-- vim: set shiftwidth=2:\\n\"\n },\n {\n \"alpha_fraction\": 0.699999988079071,\n \"alphanum_fraction\": 0.699999988079071,\n \"avg_line_length\": 19,\n \"blob_id\": \"f19b80d7e2dd7689172193a70de80610849d5b25\",\n \"content_id\": \"98f1b5a5bebcd286bfd2219885a5ac5e93c32db5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 20,\n \"license_type\": \"no_license\",\n \"max_line_length\": 19,\n \"num_lines\": 1,\n \"path\": \"/home/.config/nvim/after/ftplugin/wiki.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"vim.opt.wrap = true\\n\"\n },\n {\n \"alpha_fraction\": 0.7272727489471436,\n \"alphanum_fraction\": 0.8281444311141968,\n \"avg_line_length\": 16.45652198791504,\n \"blob_id\": \"621c7d47430e6d5d02d697aca4c0820c0966fcef\",\n \"content_id\": \"e03b6a055d64f6d372c8eef2a284b3f452cd00d6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"INI\",\n \"length_bytes\": 803,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 46,\n \"path\": \"/home/.config/foot/foot.ini\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"font=FuraCode Nerd Font:size=12:style=medium\\nfont-bold=FuraCode Nerd Font:size=12:style=bold\\ndpi-aware=no\\nbold-text-in-bright=false\\nbox-drawings-uses-font-glyphs=true\\n\\n[tweak]\\ngrapheme-shaping=yes\\n\\n[scrollback]\\nlines=2000\\n\\n[cursor]\\nblink=true\\n\\n[colors]\\n# Nord color palette\\nalpha=0.8\\nforeground=d8dee9\\nbackground=2e3440\\nregular0=3b4252\\nregular1=bf616a\\nregular2=a3be8c\\nregular3=ebcb8b\\nregular4=81a1c1\\nregular5=b48ead\\nregular6=88c0d0\\nregular7=e5e9f0\\nbright0=4c566a\\nbright1=bf616a\\nbright2=a3be8c\\nbright3=ebcb8b\\nbright4=81a1c1\\nbright5=b48ead\\nbright6=8fbcbb\\nbright7=eceff4\\nselection-foreground=d8dee9\\nselection-background=4c566a\\n\\n[key-bindings]\\nscrollback-up-page=Control+Shift+k\\nscrollback-down-page=Control+Shift+j\\nscrollback-up-line=Control+Shift+b\\nscrollback-down-line=Control+Shift+f\\n\\n[search-bindings]\\n\"\n },\n {\n \"alpha_fraction\": 0.45782145857810974,\n \"alphanum_fraction\": 0.4602784514427185,\n \"avg_line_length\": 20.421052932739258,\n \"blob_id\": \"68890b2ee7f9c6302b1323a3f33de3c9a8160296\",\n \"content_id\": \"070077238e5d2d5016e93dbac3f81249de31262e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Lua\",\n \"length_bytes\": 1221,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 57,\n \"path\": \"/home/.config/nvim/lua/plugins/wiki.lua\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"return {\\n -- Note-taking utilities\\n {\\n 'lervag/wiki.vim',\\n -- ft = { \\\"wiki\\\" },\\n dependencies = {\\n { 'lervag/wiki-ft.vim' },\\n },\\n tag = \\\"v0.8\\\",\\n cmd = \\\"WikiIndex\\\",\\n init = function()\\n vim.g.vimwiki_pubs_config = {\\n vim.env.HOME .. \\\"/.config/pubs/main_library.conf\\\",\\n vim.env.HOME .. \\\"/.config/pubs/misc_library.conf\\\",\\n }\\n\\n vim.g.wiki_root = '~/Nextcloud/Notes'\\n vim.g.wiki_link_creation = {\\n wiki = {\\n link_type = \\\"wiki\\\",\\n url_extension = \\\".wiki\\\",\\n url_transform = function(x)\\n local name\\n name, _ = string.gsub(string.lower(x), \\\" \\\", \\\"-\\\")\\n return name\\n end\\n }\\n }\\n vim.g.wiki_filetypes = { 'wiki' }\\n vim.g.wiki_select_method = 'fzf'\\n end\\n },\\n {\\n 'dkarter/bullets.vim',\\n ft = {\\n \\\"gitcommit\\\",\\n \\\"mail\\\",\\n \\\"markdown\\\",\\n \\\"markdown.pandoc\\\",\\n \\\"pandoc\\\",\\n \\\"text\\\",\\n \\\"wiki\\\",\\n },\\n init = function()\\n vim.g.bullets_enabled_file_types = {\\n 'gitcommit',\\n 'mail',\\n 'markdown',\\n 'markdown.pandoc',\\n 'pandoc',\\n 'text',\\n 'wiki',\\n }\\n end\\n },\\n}\\n-- vim: set shiftwidth=2:\\n\"\n },\n {\n \"alpha_fraction\": 0.6533742547035217,\n \"alphanum_fraction\": 0.6533742547035217,\n \"avg_line_length\": 9.1875,\n \"blob_id\": \"f3e19f77c3946a0720bf681e0fc08180d6e41b93\",\n \"content_id\": \"74d1fbfa8148f3e0ce8c0ecdd61c1a53695505da\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"TOML\",\n \"length_bytes\": 326,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 32,\n \"path\": \"/home/.config/starship.toml\",\n \"repo_name\": \"cristobaltapia/dotfiles_main\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"add_newline = true\\nformat=\\\"\\\"\\\"\\n$username\\\\\\n$hostname\\\\\\n$directory\\\\\\n$package\\\\\\n$python\\\\\\n$julia\\\\\\n$time\\\\\\n$fill\\\\\\n$git_branch\\\\\\n$git_status\\\\\\n$shell\\\\n\\\\\\n$character\\\"\\\"\\\"\\nright_format = \\\"\\\"\\\"\\n$battery\\n\\\"\\\"\\\"\\n\\n[username]\\nshow_always = true\\n\\n[fill]\\nsymbol = \\\" \\\"\\n\\n[hostname]\\nssh_only = true\\n\\n[python]\\ndetect_extensions = []\\n\\n[nodejs]\\ndisabled = true\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":38,"string":"38"}}},{"rowIdx":2977698,"cells":{"repo_name":{"kind":"string","value":"LcNdinda/Flask_Business"},"repo_url":{"kind":"string","value":"https://github.com/LcNdinda/Flask_Business"},"snapshot_id":{"kind":"string","value":"d68cb0b7ae4d16c6ed05b054db8721bff9a27589"},"revision_id":{"kind":"string","value":"56099d1ca1be433260b84de18d6c132edba2fecc"},"directory_id":{"kind":"string","value":"dd88b6bb1455e607ab1a950596b40b3950a0f4da"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-04-10T06:30:53.515014","string":"2020-04-10T06:30:53.515014"},"revision_date":{"kind":"timestamp","value":"2018-12-07T17:48:14","string":"2018-12-07T17:48:14"},"committer_date":{"kind":"timestamp","value":"2018-12-07T17:48:14","string":"2018-12-07T17:48:14"},"github_id":{"kind":"number","value":160856780,"string":"160,856,780"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5600000023841858,"alphanum_fraction":0.5600000023841858,"avg_line_length":19,"blob_id":"b0cd6bee2b5f30beb3541d70b8e8afe7ea8336bf","content_id":"4ca1ace289a83bd9217b9deae7303ddaf373a05c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":100,"license_type":"no_license","max_line_length":27,"num_lines":5,"path":"/run.py","repo_name":"LcNdinda/Flask_Business","src_encoding":"UTF-8","text":"from app import app\n\nif __name__ == '__main__':\n app.secret_key='/QCS8Z5*pSzuZwI'\n app.run(debug=True)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5600000023841858,\n \"alphanum_fraction\": 0.5600000023841858,\n \"avg_line_length\": 19,\n \"blob_id\": \"b0cd6bee2b5f30beb3541d70b8e8afe7ea8336bf\",\n \"content_id\": \"4ca1ace289a83bd9217b9deae7303ddaf373a05c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 100,\n \"license_type\": \"no_license\",\n \"max_line_length\": 27,\n \"num_lines\": 5,\n \"path\": \"/run.py\",\n \"repo_name\": \"LcNdinda/Flask_Business\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from app import app\\n\\nif __name__ == '__main__':\\n app.secret_key='/QCS8Z5*pSzuZwI'\\n app.run(debug=True)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2977699,"cells":{"repo_name":{"kind":"string","value":"arw180/websocket-examples"},"repo_url":{"kind":"string","value":"https://github.com/arw180/websocket-examples"},"snapshot_id":{"kind":"string","value":"1d3860bacd54663460645545cbcef7c203c13977"},"revision_id":{"kind":"string","value":"e8890503ebd342d19228d767db5432e3db94bbd0"},"directory_id":{"kind":"string","value":"66c0e819339f4808f047a0722093ff6e4764c754"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2016-09-05T21:43:18.987707","string":"2016-09-05T21:43:18.987707"},"revision_date":{"kind":"timestamp","value":"2014-01-16T03:13:55","string":"2014-01-16T03:13:55"},"committer_date":{"kind":"timestamp","value":"2014-01-16T03:13:55","string":"2014-01-16T03:13:55"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6483180522918701,"alphanum_fraction":0.6544342637062073,"avg_line_length":28.727272033691406,"blob_id":"c2beb1c0ac36116a4aca30b0a76fff764200df23","content_id":"f9215c6407eafd06967c895c2f4df19a53229c4f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":327,"license_type":"no_license","max_line_length":61,"num_lines":11,"path":"/README.md","repo_name":"arw180/websocket-examples","src_encoding":"UTF-8","text":"websocket-examples\n==================\n\nJust some examples using WebSockets\n\nUse `pip install -r requirements.txt` to install dependencies\n\nSimple Synchronous (Blocking) Example\n----------------------------------------\n1. run `python simple_server.py` in a terminal\n2. run `python simple_blocking_client.py` in another terminal\n"},{"alpha_fraction":0.6507936716079712,"alphanum_fraction":0.6556776762008667,"avg_line_length":23.08823585510254,"blob_id":"2fe5f49d09ed0821260fd378d1ea4f0611d35371","content_id":"ae37c41139660c897a3953284879e9c1a2f7e5ac","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":819,"license_type":"no_license","max_line_length":60,"num_lines":34,"path":"/simple_server.py","repo_name":"arw180/websocket-examples","src_encoding":"UTF-8","text":"\"\"\"\nserver.py\n\nWebsocket server\n\"\"\"\nimport json\n\nimport tornado.httpserver\nimport tornado.ioloop\nimport tornado.web\nimport tornado.websocket\n\nclass WSHandler(tornado.websocket.WebSocketHandler):\n def open(self):\n print (\"new connection\")\n\n def on_message(self, message):\n message = json.loads(message)\n if message['command'] == 'get_colors':\n self.write_message(\"Red, Blue, Green\")\n if message['command'] == 'get_shapes':\n self.write_message(\"Circle, Square, Triangle\")\n\n def on_close(self):\n print (\"connection closed\")\n\napplication = tornado.web.Application([\n (r'/ws', WSHandler),\n])\n\nif __name__ == \"__main__\":\n http_server = tornado.httpserver.HTTPServer(application)\n http_server.listen(8888)\n tornado.ioloop.IOLoop.instance().start()\n"},{"alpha_fraction":0.7003968358039856,"alphanum_fraction":0.7083333134651184,"avg_line_length":21.909090042114258,"blob_id":"c369ba6b3d39f440b4e82825af7f02a9a4b59070","content_id":"35c8217dfd7d1d22da51042c4d89bcf538f778de","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":504,"license_type":"no_license","max_line_length":73,"num_lines":22,"path":"/simple_blocking_client.py","repo_name":"arw180/websocket-examples","src_encoding":"UTF-8","text":"\"\"\"\nclient.py\n\nThis example shows how easy it is to create a client WebSocket connection\nin Python using a synchronous (i.e. blocking) architecture\n\"\"\"\nimport json\nfrom websocket import create_connection\n\nws = create_connection(\"ws://localhost:8888/ws\")\n\ndata = {'command': 'get_colors'}\nws.send(json.dumps(data))\nresult = ws.recv()\nprint (\"Received colors: %s\" % result)\n\ndata = {'command': 'get_shapes'}\nws.send(json.dumps(data))\nresult = ws.recv()\nprint (\"Received shapes: %s\" % result)\n\nws.close()\n"},{"alpha_fraction":0.593406617641449,"alphanum_fraction":0.7362637519836426,"avg_line_length":21.75,"blob_id":"2472c04753ef6832fe9ab1458a293fd58cb83bee","content_id":"cc405392d2f71c53b28f175d2a91db34e8d75ad1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":91,"license_type":"no_license","max_line_length":37,"num_lines":4,"path":"/requirements.txt","repo_name":"arw180/websocket-examples","src_encoding":"UTF-8","text":"backports.ssl-match-hostname==3.4.0.2\ntornado==3.2\nwebsocket-client==0.12.0\nwsgiref==0.1.2\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6483180522918701,\n \"alphanum_fraction\": 0.6544342637062073,\n \"avg_line_length\": 28.727272033691406,\n \"blob_id\": \"c2beb1c0ac36116a4aca30b0a76fff764200df23\",\n \"content_id\": \"f9215c6407eafd06967c895c2f4df19a53229c4f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 327,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 11,\n \"path\": \"/README.md\",\n \"repo_name\": \"arw180/websocket-examples\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"websocket-examples\\n==================\\n\\nJust some examples using WebSockets\\n\\nUse `pip install -r requirements.txt` to install dependencies\\n\\nSimple Synchronous (Blocking) Example\\n----------------------------------------\\n1. run `python simple_server.py` in a terminal\\n2. run `python simple_blocking_client.py` in another terminal\\n\"\n },\n {\n \"alpha_fraction\": 0.6507936716079712,\n \"alphanum_fraction\": 0.6556776762008667,\n \"avg_line_length\": 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500swapnil/tictactoe-bot | https://github.com/500swapnil/tictactoe-bot | 018ffb82966ef2d85d9a9b88a2553df3bcf40a20 | 1a31e423eb11f03c9a87f5c1fa6c9d4444d5b0ce | 99df6415eb275af37623d935e517ec0b2a36dd54 | refs/heads/master | 2021-08-31T17:36:31.032804 | 2017-12-22T08:13:05 | 2017-12-22T08:13:05 | 115,091,533 | 0 | 0 | null | null | null | null | null | [
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emeraldant/robo-survival | https://github.com/emeraldant/robo-survival | 43d6e21ac1c2164e22e95effcae7c17759e55f1d | af7d5091f2db1220b9d79e3b286102d527705cd1 | 6ba41b0f92e1e44cdda40814834671f8ab11b7e3 | refs/heads/master | 2020-04-04T16:48:14.487076 | 2018-11-04T15:06:03 | 2018-11-04T15:06:03 | 156,093,378 | 0 | 0 | null | null | null | null | null | [
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topistalamaro/Variance | https://github.com/topistalamaro/Variance | e5c716299c5b2d5a31fc948f9a444fce89e2f612 | 320b50244d6a8a8ae2239f96fff379eb2225633e | be31a9639f4e304ca115faac8109bf0a9e61bba2 | refs/heads/main | 2023-07-04T14:04:59.219795 | 2021-08-12T17:39:47 | 2021-08-12T17:39:47 | 393,435,294 | 0 | 0 | null | null | null | null | null | [
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dylanwach/guitars_test_real | https://github.com/dylanwach/guitars_test_real | 7e8703ad3e720186348363fc458d5403906ee204 | 94dfed1300c13e688ecb04b0ae933aa55a428c39 | 62ebaef7ae1781be12bb4c7eb74f28eba344dcc0 | refs/heads/master | 2023-04-27T00:27:44.759722 | 2021-06-08T01:19:22 | 2021-06-08T01:19:22 | 374,842,650 | 0 | 0 | null | null | null | null | null | [
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newbiejasper/newbie_programming | https://github.com/newbiejasper/newbie_programming | 88c4a432f878b518c3c705d7fc2d09735f0ea8b2 | d6cd9d622f7df10603b3cd8d6ea177fbe9914947 | b2aa6a2bf658fc5890900ba64ce9cb237a279bbc | refs/heads/master | 2021-01-22T19:09:14.961720 | 2019-03-30T03:36:43 | 2019-03-30T03:36:43 | 85,171,155 | 0 | 0 | null | null | null | null | null | [
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samy19980109/KasaSafe | https://github.com/samy19980109/KasaSafe | e2c54360ea1b2442c84d5ca4bc176a2211c70f53 | 2b00528548423e10da7e5a70c79140247ad01269 | a1b0ee51e75920d7a5036f5dbc867b1a8ffdd21c | refs/heads/master | 2020-06-26T05:07:21.552344 | 2019-07-30T00:29:12 | 2019-07-30T00:29:12 | 199,541,904 | 0 | 0 | null | null | null | null | null | [
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mfkiwl/BPSK-Transceiver | https://github.com/mfkiwl/BPSK-Transceiver | ff7cc7f35c04c888eaf5198a5cbf33f319a9a787 | 440ffb01ead58c278a1b327246718d5a35c68afd | 0ed5a1a1715f5223c877cfdea2085b8ce54ea5dd | refs/heads/master | 2023-05-14T07:43:52.080215 | 2021-06-03T23:06:25 | 2021-06-03T23:06:25 | null | 0 | 0 | null | null | null | null | null | [
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alexminnaar/Joint_Image_Text_Classifier | https://github.com/alexminnaar/Joint_Image_Text_Classifier | 1c93593c5202b555d08155a355a0cfede8b75873 | c11bbd5413ef50653c68d68d9ba78c8cdc5ae54d | c8db4d0b97eff7ee577b114fb5c17dd1d1d46d0f | refs/heads/master | 2021-01-20T06:51:48.670641 | 2017-05-04T02:23:01 | 2017-05-04T02:23:01 | 89,937,545 | 0 | 0 | null | null | null | null | null | [
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juniorjrml/desafioFinalPyDevIGTI | https://github.com/juniorjrml/desafioFinalPyDevIGTI | 55b7c501ba79aa10dd1d4cb53a7b3b1fca41ac92 | 61e52396f6d036f081ecc66f0f74c502b45a367f | 08781da9611d44a2088882da2b53b175f2a6b9f9 | refs/heads/master | 2023-01-12T08:12:59.038898 | 2020-11-17T18:56:59 | 2020-11-17T18:56:59 | 313,358,988 | 0 | 0 | null | null | null | null | null | [
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tobiasrausch/bamStats | https://github.com/tobiasrausch/bamStats | e620f6beff71d654ed35b4cd89810e08bafaa40d | 2bec03143aebfcefedda4a86602b04754d6cd5b8 | f98ca807b65aba7ccaf8703bcee1e47f119dbe87 | refs/heads/master | 2021-05-23T23:09:58.752345 | 2021-05-08T12:31:48 | 2021-05-08T12:31:48 | 52,509,133 | 1 | 0 | null | null | null | null | null | [
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isando3/B2GEfficiencyPlots | https://github.com/isando3/B2GEfficiencyPlots | b7e071c41943ccf60fb94db5a3de790b1a867ab7 | 8f8e32bdebd3efc7ffba2328fb9d34001ced4035 | 3d8bbe501d2640da0daf03f2829b0692a4ddf657 | refs/heads/master | 2021-01-19T00:47:32.764001 | 2016-01-20T20:44:43 | 2016-01-20T20:44:43 | 30,425,889 | 0 | 0 | null | null | null | null | null | [
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devmapal/gitolite-manager | https://github.com/devmapal/gitolite-manager | 1aaeec73a6653388d2f5b54da8143d597363fac3 | 4a185f3101a176cdc6b350cb9e0944fb58f6321b | 3b4c70de18d4f3d9994025cce5486d70caf14a1f | refs/heads/master | 2021-01-14T12:57:26.351698 | 2015-04-09T12:52:51 | 2015-04-09T12:52:51 | 28,190,728 | 1 | 1 | null | null | null | null | null | [
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HiredMark/OneCleverHorse | https://github.com/HiredMark/OneCleverHorse | 0d56630024b3b87eea5e56f8ed732c313539453f | 923ac3e27a0835ca56a3d8a0b62ed15ec4331671 | 2c3a83799b0febd243220f44fde4c767548d4a32 | refs/heads/main | 2023-04-04T17:33:22.899230 | 2021-04-12T14:48:36 | 2021-04-12T14:48:36 | null | 0 | 0 | null | null | null | null | null | [
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gedamia/clinic-income | https://github.com/gedamia/clinic-income | 6698def3033a92b2fe10ee6641151edddf645704 | abc3b3b6c10c1f1bea7f8917624f83f43b9ae963 | 3fec54c877e07c2c7335d1476c02e3588d3ca8ac | refs/heads/master | 2021-04-27T08:12:40.256131 | 2018-04-03T22:22:00 | 2018-04-03T22:22:00 | 122,650,889 | 0 | 0 | null | null | null | null | null | [
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songhao8080/demo_git | https://github.com/songhao8080/demo_git | 50adb59e872f76ca9851f55a807f31c7650308ab | f373421f13d8b5e82e5176479a8df464e2293547 | 8043bb84c3db1f7c8ed6e8bed7f92938c35849f7 | refs/heads/master | 2021-06-15T19:18:13.546388 | 2017-03-07T11:52:08 | 2017-03-07T11:52:08 | null | 0 | 0 | null | null | null | null | null | [
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shreyanvaidya/Python | https://github.com/shreyanvaidya/Python | 5339df6660237f0156fa8d4fcca87e10a61ced1c | 43674acdc6779a809c4999f759a06d30619ce0e0 | 1c47d9e3c025d76aa2a921300fc93482ea68ff8a | refs/heads/main | 2023-03-23T20:49:01.153866 | 2021-03-20T17:43:38 | 2021-03-20T17:43:38 | 349,794,791 | 0 | 0 | null | null | null | null | null | [
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mehrad/solid_presentation | https://github.com/mehrad/solid_presentation | c05c95cfa312e3e2c190d6a7953a78b6c0be7c44 | aec4548d02e630e338965224bee70a0f331bbf70 | 3643ac58060556df1ec41b39688c5517d915748e | refs/heads/master | 2022-12-30T07:24:38.633177 | 2020-09-27T04:27:01 | 2020-09-27T04:37:04 | 298,982,963 | 0 | 0 | null | null | null | null | null | [
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LuigiChiricosta/Development-of-next-generation-sequencing-tools-for-the-diagnosis-of-neurodevelopmental-disorders | https://github.com/LuigiChiricosta/Development-of-next-generation-sequencing-tools-for-the-diagnosis-of-neurodevelopmental-disorders | 717130442bcb6479effe0f26f038ad7ca46b3ec2 | 4dbafd807f9a9a083f6d29e703292eb3df1cad18 | 472dab863cbd86469efa28a4e8f2966aa3eeb54c | refs/heads/master | 2020-03-09T18:58:00.353593 | 2018-05-07T13:28:40 | 2018-05-07T13:28:40 | 128,945,803 | 0 | 0 | null | null | null | null | null | [
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chenhongbiao/My_Web_Spider | https://github.com/chenhongbiao/My_Web_Spider | 7c366ff9e8b58351ef01675da8d7d594e5f5a302 | ecf5360678e09da599160e504cd7ac2f23b080db | 9dd069fc7f31ca1a506f41317a78dcf5ccbebace | refs/heads/master | 2021-01-19T04:07:40.785679 | 2016-08-04T14:47:32 | 2016-08-04T14:47:32 | 64,398,626 | 0 | 0 | null | null | null | null | null | [
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rjfarmer/multimesa | https://github.com/rjfarmer/multimesa | 953f4098978a279d80fe8e217b1970dd2a4fa5f1 | e9c9739acdb2200ff729d4ebea3405da2a564de0 | 308434746a6b49b6735cdaea02fc7cdccfa0ea68 | refs/heads/master | 2021-03-12T22:42:31.107445 | 2018-11-04T18:10:53 | 2018-11-04T18:10:53 | 30,721,088 | 0 | 0 | null | null | null | null | null | [
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nairobi222/indy-catalyst | https://github.com/nairobi222/indy-catalyst | b867355a48a817c4759fc627ee093633c45b5e45 | dcbd80524ace7747ecfecd716ff932e9b571d69a | 00a96c2f10efab746bebc818dbcc50e7a4819d4c | refs/heads/master | 2020-06-09T19:41:33.598166 | 2019-06-13T23:59:40 | 2019-06-13T23:59:40 | 193,495,135 | 0 | 0 | Apache-2.0 | 2019-06-24T11:47:47 | 2019-06-24T11:47:43 | 2019-06-22T23:37:59 | null | [
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philpot/stanford-extraction-prep | https://github.com/philpot/stanford-extraction-prep | 261eee865238380a04e93bfa3145da1ffd085480 | c29d523c9c36403628535864f85d35c7b434b0f1 | a84b934ae01933ac338102246615826989020c92 | refs/heads/master | 2021-01-10T06:17:09.948956 | 2015-11-10T20:03:43 | 2015-11-10T20:03:43 | 45,663,204 | 0 | 0 | null | null | null | null | null | [
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WesleyW-code/First-Capstone-Project-Level-1-Python | https://github.com/WesleyW-code/First-Capstone-Project-Level-1-Python | 8645e852f4a3b2cea796395c2f0de967ebad7b2b | b05881f1fd2f8738aa1e46164be79f6ad3e63704 | 7f8cce027fa06fe1b0a3df4bf13f1f468be9192e | refs/heads/main | 2023-04-14T04:26:27.542665 | 2021-05-05T11:17:33 | 2021-05-05T11:17:33 | 364,540,431 | 0 | 0 | null | null | null | null | null | [
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libraryhackers/library-callnumber-lc | https://github.com/libraryhackers/library-callnumber-lc | 295a2195df415131546650fc396bd6c143f882f6 | 5ce1d7ab5cca7533bad406f37cc3e718ac37c0fb | eed3f0cffd7f9bd1dfe3771d92b89262e22f7343 | refs/heads/master | 2021-05-16T03:13:31.315091 | 2014-12-12T17:46:05 | 2014-12-12T18:04:16 | 32,171,460 | 35 | 4 | null | 2015-03-13T17:48:03 | 2016-09-21T17:23:03 | 2015-03-13T17:51:42 | Perl | [
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BartekCITSystems/Test | https://github.com/BartekCITSystems/Test | 1c7bf8a4dda9851fa410566a684977ab8a95d145 | 5bba69fc412827b1a8e6136864aa8f32485c6ba9 | 30780d9079aba0ff434b7af49e11b4555d145e79 | refs/heads/master | 2018-04-13T11:06:47.346264 | 2017-02-05T18:26:25 | 2017-02-05T18:26:25 | 81,009,946 | 0 | 0 | null | null | null | null | null | [
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ojarva/hsl-poikkeusinfo | https://github.com/ojarva/hsl-poikkeusinfo | 5800a32cc30318309343bbdbb96958ba125b2a90 | 63b2cf9a81c2f864d75e13b2c02a6f4cfa4741a6 | 880ba1a51b493a5d4531428fdc35bd71c65758cf | refs/heads/master | 2023-05-24T20:44:53.629547 | 2023-03-28T06:19:47 | 2023-03-28T06:19:47 | 52,455,469 | 0 | 0 | MIT | 2016-02-24T16:08:00 | 2023-03-28T06:19:53 | 2023-05-23T00:51:20 | Python | [
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steffenheyne/UCSC_trackHub_generator | https://github.com/steffenheyne/UCSC_trackHub_generator | 81d6fda75dc24067a3ebc0f65d054e14b6f872cd | e275d5d6966c61eb73795db94b3f200683c4780f | 7704f547d9608fb94da5df4f539b99d6b3f7cd10 | refs/heads/master | 2021-06-14T06:29:18.941698 | 2021-05-25T20:03:04 | 2021-05-25T20:03:04 | 197,746,206 | 0 | 2 | null | null | null | null | null | [
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Learsim/LearsimControlPanel | https://github.com/Learsim/LearsimControlPanel | ea718611f1eb0cabe745d3dcafe384e81384f49b | 80ae68d7e21caf768582fabcb81862720b1a63ba | 1dc81c1e6287dd9f0ed3741ec98d60544debb782 | refs/heads/main | 2023-06-18T04:38:21.907080 | 2021-07-16T12:23:57 | 2021-07-16T12:23:57 | 352,812,556 | 0 | 0 | null | null | null | null | null | [
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alvsgithub/erp5 | https://github.com/alvsgithub/erp5 | f254903679e7d16076671dce66759f6c74ff3566 | 22887cde63f9099258ebf910f3662aa5680d5cdf | 50bba4746d7d34b116b729486f3ad876e0b16e51 | refs/heads/master | 2020-12-28T23:46:45.850199 | 2014-10-23T13:16:01 | 2014-10-23T13:37:39 | null | 0 | 0 | null | null | null | null | null | [
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Tkocz/pysteam | https://github.com/Tkocz/pysteam | 8d1f1f9ff9a3c9932462cb2cd231d02af4c45079 | df9d929ea4e8d43762add346fae3d557cfecff74 | 7b5c41ff35def855c804ebbb7fab3af61290ea85 | refs/heads/master | 2021-03-16T09:07:38.577565 | 2017-08-30T12:32:01 | 2017-08-30T12:32:01 | 76,860,176 | 1 | 2 | null | null | null | null | null | [
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Harmionee/TeamProjects | https://github.com/Harmionee/TeamProjects | c6ac70861c6e5abc581d070d108ad15df8cc6d58 | 272743efa8db0e51fdb8ab33858b1ec7b6e0e310 | 2ca67e0af383048a58f2ef8f347848c6aeccc440 | refs/heads/main | 2023-01-28T13:26:05.363451 | 2020-12-07T22:48:22 | 2020-12-07T22:48:22 | null | 0 | 0 | null | null | null | null | null | [
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cindylyl/djpractice | https://github.com/cindylyl/djpractice | aedc11919bebce15ec04c53441112431b12a0cc6 | c1c6efc37b3762fbf131aabf495406b9801e4164 | 60e625f1a656480a915d6ea53d5ba9d68fb92a6d | refs/heads/master | 2021-08-10T21:58:50.599548 | 2020-05-30T21:13:34 | 2020-05-30T21:13:34 | 84,659,675 | 0 | 0 | null | null | null | null | null | [
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madan554/madhan1 | https://github.com/madan554/madhan1 | a79c1c7e77ac3be3071ff9db7c3a91444ba4c61f | 520f2df427932912e1d82ce0805f50e0d97bbb3d | e7fcee8283f7f51eec1c94c4fd993c094aae7ed7 | refs/heads/master | 2023-04-07T12:19:34.659080 | 2021-04-04T11:03:11 | 2021-04-04T11:03:11 | 353,239,064 | 0 | 0 | null | null | null | null | null | [
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sadeghieh/PersianNLP | https://github.com/sadeghieh/PersianNLP | 0d4e14ec9e66299c3fa44a02a7a45d07e5c423d6 | 8479a11f848b3e9cff55e5feff8ee5346e1eb36e | 15bda869b70a17723cad2b16dd9dfbe8876cf5ac | refs/heads/master | 2020-04-04T20:39:22.323766 | 2018-12-02T04:29:41 | 2018-12-02T04:29:41 | 156,255,023 | 0 | 0 | null | null | null | null | null | [
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mloumeau/Discrete-Mathematics | https://github.com/mloumeau/Discrete-Mathematics | 9781e2b31c53fad91a805e2f9c99c5f57a95b544 | edc1c68da5569d719d07be1af02873fe83da3e06 | e19cbc5a577a36558ffc362680506b0a1bd1cc69 | refs/heads/main | 2023-02-10T16:08:19.153121 | 2020-12-31T18:46:36 | 2020-12-31T18:46:36 | null | 0 | 0 | null | null | null | null | null | [
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nithin9296/awitha | https://github.com/nithin9296/awitha | 3f764c4df97301fee76c7d513d1ef12e6efed18f | dea5003297c03154d9a7a93f3f9352ab0d59bc4e | 69d661f33481d0b1f2544da847bb2cb71c942130 | refs/heads/master | 2020-03-10T22:55:53.135309 | 2018-04-15T16:52:56 | 2018-04-15T16:52:56 | 124,306,317 | 0 | 0 | null | null | null | null | null | [
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AashishMehtoliya/titanic | https://github.com/AashishMehtoliya/titanic | 2bcf9f038f211270621006b7280b887539686466 | 1b1f95490ba85aff21034471df357f06e688da6b | 908967fbd79694bb24a446552e85686d1e36848c | refs/heads/master | 2020-04-20T02:24:24.709210 | 2019-05-30T06:05:52 | 2019-05-30T06:05:52 | 168,570,772 | 0 | 0 | null | null | null | null | null | [
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denrsch/home_terminal | https://github.com/denrsch/home_terminal | 639fbf251358a8225f4d6c1a5d9bfb366fa26e2e | af1a6ba0475c2a101647ae10545f867a32cd9f76 | 77e02d9154dd929f7c931729bf37749955274633 | refs/heads/master | 2020-12-24T14:45:40.471972 | 2015-04-03T00:09:23 | 2015-04-03T00:09:23 | 33,276,082 | 0 | 0 | null | null | null | null | null | [
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Skuldur/somnus | https://github.com/Skuldur/somnus | bd759794fbeb8b562a0863aafcc31a8ce47ad246 | 45cec3e2ed3f27e2a024ea214651af30a0e6fe60 | d9082b1c64096f3d39b0d037a5c23386d510f235 | refs/heads/master | 2022-12-01T21:18:40.765549 | 2020-08-18T21:22:57 | 2020-08-18T21:22:57 | 279,154,687 | 5 | 1 | MIT | 2020-07-12T21:57:01 | 2020-08-15T08:26:00 | 2020-08-17T21:14:39 | Python | [
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inaccare/Beer-Type-Prediction | https://github.com/inaccare/Beer-Type-Prediction | ffeaba53d6b3fee223c747183d60447feb45385d | 89327f2d721eaee74d144f01e40d53ee3d0c0eb3 | 1c7035b2099aa542887eaefc67e41ba42f951fb0 | refs/heads/master | 2020-03-15T03:06:18.203463 | 2018-06-14T07:25:23 | 2018-06-14T07:25:23 | 131,934,457 | 0 | 0 | null | null | null | null | null | [
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noahdesu/ucsc-transit | https://github.com/noahdesu/ucsc-transit | d70120e6a6b9e25c615d04d78650d68bf5ad909a | d5b6bc81e4af4c843dd467eb7044027078d58ffb | e22c8eec86a438d3caeed8ef6596ba909c4a2653 | refs/heads/master | 2021-01-21T09:53:55.404844 | 2017-02-27T19:43:58 | 2017-02-27T20:08:39 | 83,350,221 | 0 | 0 | null | null | null | null | null | [
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LikeLionSCH/github-practice-A-team | https://github.com/LikeLionSCH/github-practice-A-team | f9ceeb4b5d72f25372a79571fdf51e85e96aed18 | cd37f52179aeafea96d7ec2dfcfaa062d7aa5a05 | e9d4be9f2eb3ce42ee2d0628a6ee449303d041c4 | refs/heads/master | 2022-11-18T13:49:38.681935 | 2020-07-22T11:50:26 | 2020-07-22T11:50:26 | 281,620,668 | 0 | 0 | null | null | null | null | null | [
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pkmollman/advent_2020 | https://github.com/pkmollman/advent_2020 | 848834a968431211ad168083e7cb66bf0b0b6dd7 | d9a84e907dc67abdb97e7dc86109068be4b8080e | f828734421d54b2764e7760123993b35f10a5764 | refs/heads/main | 2023-01-30T01:41:36.570906 | 2020-12-11T06:38:18 | 2020-12-11T06:38:18 | 317,447,825 | 0 | 0 | null | null | null | null | null | [
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