AllenDang

Use pre-built gccemacs

Fortunatly we could use pre-built gccemacs right now.

Those two repos did the greate job for us.

https://github.com/twlz0ne/nix-gccemacs-darwin

https://github.com/twlz0ne/nix-gccemacs-sierra

Here is the tutorial:

rcugut

GUIDE to install yarn, nvm (node) on macOS

last update: Dec 4, 2020

Assumptions:

• macOS >= 10.14 (Mojave); tested with 10.15 (Catalina)
• homebrew properly installed

chssch

# This small script shows how to use AllenNLP Semantic Role Labeling (http://allennlp.org/) with SpaCy 2.0 (http://spacy.io) components and extensions
# Script installs allennlp default model
# Important: Install allennlp form source and replace the spacy requirement with spacy-nightly in the requirements.txt
# Developed for SpaCy 2.0.0a18

from allennlp.commands import DEFAULT_MODELS
from allennlp.common.file_utils import cached_path
from allennlp.service.predictors import SemanticRoleLabelerPredictor
from allennlp.models.archival import load_archive

nruth

# load into test setup after `require 'capybara/rails'`

# some sources for below flags and profile settings
# https://stackoverflow.com/questions/43143014/chrome-is-being-controlled-by-automated-test-software/43145088
# https://sqa.stackexchange.com/questions/26051/chrome-driver-2-28-chrome-is-being-controlled-by-automated-test-software-notif
# http://stackoverflow.com/questions/12211781/how-to-maximize-window-in-chrome-using-webdriver-python
# update sources for new Options object
# https://github.com/SeleniumHQ/selenium/wiki/Ruby-Bindings
# https://github.com/teamcapybara/capybara/blob/master/lib/capybara/selenium/driver.rb
begin

pervognsen

enum { BMAX = 32, BCUT = BMAX / 2, BHEIGHT = 6 };

typedef uint8_t BIndex;

struct BNode {
    BIndex length;
    Key keys[BMAX];
    union {
        BNode *children[BMAX];
        Value values[BMAX];

kaushiks

all:
	flex flex-scanner.l
	g++ -o d flex-scanner.c scanner.cc main.cc

test: all
	./d

clean:
	rm ./d
	rm ./flex-scanner.c

m00nlight

class KMP:
    def partial(self, pattern):
        """ Calculate partial match table: String -> [Int]"""
        ret = [0]
        
        for i in range(1, len(pattern)):
            j = ret[i - 1]
            while j > 0 and pattern[j] != pattern[i]:
                j = ret[j - 1]
            ret.append(j + 1 if pattern[j] == pattern[i] else j)

lastlegion

#Import library essentials
from sumy.parsers.plaintext import PlaintextParser #We're choosing a plaintext parser here, other parsers available for HTML etc.
from sumy.nlp.tokenizers import Tokenizer 
from sumy.summarizers.lex_rank import LexRankSummarizer #We're choosing Lexrank, other algorithms are also built in

file = "plain_text.txt" #name of the plain-text file
parser = PlaintextParser.from_file(file, Tokenizer("english"))
summarizer = LexRankSummarizer()

summary = summarizer(parser.document, 5) #Summarize the document with 5 sentences

farleyknight

# Includes Operating System name from `uname`

export PS1="\[\033[36m\]\u\[\033[m\]@\[\033[32m\]\h\[\033[35m\][$(uname)]\[\033[33;1m\]\w\[\033[m\]\n$ "

chrisdone

Basic unit type:

λ> replTy "()"
() :: ()

Basic functions: