prologic

Learn Go in ~5mins

This is inspired by A half-hour to learn Rust and Zig in 30 minutes.

Basics

Your first Go program as a classical "Hello World" is pretty simple:

First we create a workspace for our project:

ameerkat

ThilinaRajapakse

# Google Data
train_df = pd.read_csv("data/train.tsv", sep="\t").astype(str)
eval_df = pd.read_csv("data/dev.tsv", sep="\t").astype(str)

train_df = train_df.loc[train_df["label"] == "1"]
eval_df = eval_df.loc[eval_df["label"] == "1"]

train_df = train_df.rename(
    columns={"sentence1": "input_text", "sentence2": "target_text"}
)

nahidalam

def EmbeddingRec(EMBEDDING_SIZE, NUM_MOVIES, NUM_USERS, ROW_COUNT):
    movie_input = keras.Input(shape=(1,), name='movie_id')

    movie_emb = layers.Embedding(output_dim=EMBEDDING_SIZE, input_dim=NUM_MOVIES, input_length=ROW_COUNT, name='movie_emb')(movie_input)
    movie_vec = layers.Flatten(name='FlattenMovie')(movie_emb)

    movie_model = keras.Model(inputs=movie_input, outputs=movie_vec)
    
    user_input = keras.Input(shape=(1,), name='user_id')

Felflare

mf1024

htorrence

Getting Started With Pytest by Jacob Kaplan-Moss

Surrender Python Mocking! I Have You Now by Matt Pease

Python Mocking 101: Fake It Before You Make It by Mike Lin

Python Mock Gotchas by Alex Marandon

melgor

kristopolous

// Usage:
//   Copy and paste all of this into a debug console window of the "Who is Hiring?" comment thread 
//   then use as follows:
//
//   query(term | [term, term, ...], term | [term, term, ...], ...)
// 
// When arguments are in an array then that means an "or" and when they are seperate that means "and"
//
// Term is of the format:
//    ((-)text/RegExp)  ( '-' means negation )

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)