jdkato

jdkato

jdkato

package main

import (
	"gopkg.in/jdkato/prose.v2"
)

func main() {
    doc, _ := prose.NewDocument("This is a sentence.")
    for _, token := range doc.Tokens() {
        fmt.Println(token.Text)

jdkato

package main

import (
	"gopkg.in/jdkato/prose.v2"
)

func main() {
    // You can pass "functional options" to control the document-creation
    // pipeline -- e.g., `prose.WithExtraction(false)` disables named-entity
    // extraction.

jdkato

Spelling

Observed	Expected	File
softwares	software	big-data-in-the-linode-cloud-streaming-data-processing-with-apache-storm.md
strucure	structure	[how-to-scrape-a-website-with-beautiful-soup.md](https://github.com/linode/docs/blame/master/docs/applications/big-data/how-to-scrape-a-website-with-beautiful-soup.

jdkato

#include "HMyClass.h"
#include <stdio.h>

void my_eh( const char * error_message, void * unused)
{
  printf("my_eh: %s\n", error_message);
}

int main()
{

jdkato

#!/bin/sed -f

# Sed script to produce Penn Treebank tokenization on arbitrary raw text.
# Yeah, sure.

# expected input: raw text with ONE SENTENCE TOKEN PER LINE

# by Robert MacIntyre, University of Pennsylvania, late 1995.

# If this wasn't such a trivial program, I'd include all that stuff about

jdkato

How to recover lost Python source code if it's still resident in-memory

I screwed up using git ("git checkout --" on the wrong file) and managed to delete the code I had just written... but it was still running in a process in a docker container. Here's how I got it back, using https://pypi.python.org/pypi/pyrasite/ and https://pypi.python.org/pypi/uncompyle6

Attach a shell to the docker container

Install GDB (needed by pyrasite)

apt-get update && apt-get install gdb

jdkato

Keybase proof

I hereby claim:

• I am jdkato on github.
• I am jdkato (https://keybase.io/jdkato) on keybase.
• I have a public key whose fingerprint is E374 305F 11CF 8879 591C 8083 72B6 1C8B C681 C52E

To claim this, I am signing this object:

jdkato

This is intended as a quick reference and showcase. For more complete info, see [John Gruber's original spec](http://daringfireball.net/projects/markdown/) and the [Github-flavored Markdown info page](http://github.github.com/github-flavored-markdown/).
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This cheatsheet is specifically *Markdown Here's* version of Github-flavored Markdown. This differs slightly in styling and syntax from what Github uses, so what you see below might vary a little from what you get in a *Markdown Here* email, but it should be pretty close.
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