oldmonkABA

#######################################################################
# Author : Arun B
# 
# Purpose : Automate the process of generating access token for kiteconnect in python
############################################################################
# For this code to run you have to download geckodriver and put it in /usr/local/bin
from kiteconnect import KiteConnect,KiteTicker
import requests
from selenium import webdriver
from selenium.webdriver.common.by import By

AlokGaira

class Session:
    __init__(api_key)
    set_api_secret(api_secret)
    set_redirect_uri(redirect_uri)
    set_code(code)
    get_login_url(self)
    retrieve_access_token(self)


class Upstox:

rochacbruno

UNDER DEVELOPMENT HERE: https://github.com/rochacbruno/markdocs

---

Python documentation

I still think that the problem of lack of good documentation in the Python ecosystem is also related to .rst format and the use of complicated tools like Sphinx.

I'm enjoying writing functional documentation using Markdown in Rustlang, so I'll do experiments to have the same functionality in Python. Take a look at rustdoc and here an example of documentation site generated for a Rust crate using markdown comments.

adippel

import time
import socket
import threading
import logging

from ws4py.client import WebSocketBaseClient
from ws4py.streaming import Stream

logger = logging.getLogger(__name__)

bdarnell

"""Demo of streaming requests with Tornado.

This script features a client using AsyncHTTPClient's body_producer
feature to slowly produce a large request body, and two server
handlers to receive this body (one is a proxy that forwards to the
other, also using body_producer).

It also demonstrates flow control: if --client_delay is smaller than
--server_delay, the client will eventually be suspended to allow the
server to catch up. You can see this in the logs, as the "client

dedunumax

##############################
## Java
##############################
.mtj.tmp/
*.class
*.jar
*.war
*.ear
*.nar
hs_err_pid*

terrywang

# User and group used by worker processes
# ubuntu
# user www-data;
# fedora
user nginx;

# Ideally # of worker processes = # of CPUs or cores
# Set to auto to autodetect
# max_clients = worker_processes * worker_connections
worker_processes auto;

igniteflow

from contextlib import contextmanager

"""
Usage:

with env_var('MY_VAR', 'foo'):
    # is set here
    
# does not exist here
"""

sebclaeys

# Autodict class
# Create new autodict if accessing undefined key
# support dot access syntax (mydict.test == mydict['test'])
class autodict(dict):
    def __getitem__(self, name):
        if not name in self:
            dict.__setitem__(self, name, autodict())
        return dict.__getitem__(self, name)

    def __getattr__(self, name):

joninvski

import pdb
"""
The Bellman-Ford algorithm

Graph API:

    iter(graph) gives all nodes
    iter(graph[u]) gives neighbours of u
    graph[u][v] gives weight of edge (u, v)
"""