mikeyb

BEAM Solo Mining Guide

• Adapted from Raskul's guide
• With help from Freshminer (sunpool.top)

Installation

• From BEAM Downloads download the following
  • beam-wallet-cli
  • beam-node
• Extract downloads into a folder called beam-mining

yozx

# Non-blocking script for shorten link via https://bit.ly Api

import asyncio
import logging
from typing import Dict, Optional

from aiohttp import ClientSession


logger = logging.getLogger('bitly_app')

thehesiod

import asyncio
from datetime import datetime, timezone
import os

def utc_now():
    # utcnow returns a naive datetime, so we have to set the timezone manually <sigh>
    return datetime.utcnow().replace(tzinfo=timezone.utc)
  
class Terminator:
  pass

fonylew

#!/bin/bash

# First sudo command
sudo whoami

# Update and upgrade
sudo apt update
sudo apt upgrade -y

# Utility

TariqAHassan

Pandas DataFrames are fantastic. However, concatenating them using standard approaches, such as pandas.concat(), can be very slow with large dataframes. This is a work around for that problem.

Note: this approach assumes that: (a) the goal is a row-wise concatenation (i.e., axis=0) and (b) all dataframes share the same column names.

If these assumptions are not met, this approach could still work…​but it will likely need to be modified.

bogdan-kulynych

# WARNING: These steps seem to not work anymore!

#!/bin/bash

# Purge existign CUDA first
sudo apt --purge remove "cublas*" "cuda*"
sudo apt --purge remove "nvidia*"

# Install CUDA Toolkit 10
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.0.130-1_amd64.deb

hest

def get_count(q):
    count_q = q.statement.with_only_columns([func.count()]).order_by(None)
    count = q.session.execute(count_q).scalar()
    return count

q = session.query(TestModel).filter(...).order_by(...)

# Slow: SELECT COUNT(*) FROM (SELECT ... FROM TestModel WHERE ...) ...
print q.count()

IanHopkinson

#!/usr/bin/env python
# encoding: utf-8

import lxml.etree
import lxml.html
import requests

xml_sample = """<?xml version="1.0" encoding="UTF-8"?>
<foo:Results xmlns:foo="http://www.foo.com" xmlns="http://www.bah.com">
<foo:Recordset setCount="2">

lars-tiede

import asyncio
import threading
import random


def thr(i):
    # we need to create a new loop for the thread, and set it as the 'default'
    # loop that will be returned by calls to asyncio.get_event_loop() from this
    # thread.
    loop = asyncio.new_event_loop()

stefansundin

# http://docs.python-requests.org/en/master/api/
import requests

class RequestsApi:
    def __init__(self, base_url, **kwargs):
        self.base_url = base_url
        self.session = requests.Session()
        for arg in kwargs:
            if isinstance(kwargs[arg], dict):
                kwargs[arg] = self.__deep_merge(getattr(self.session, arg), kwargs[arg])