jamesmishra

#!/bin/bash
sudo apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv 7F0CEB10
echo 'deb http://downloads-distro.mongodb.org/repo/ubuntu-upstart dist 10gen' | sudo tee /etc/apt/sources.list.d/mongodb.list
sudo apt-get update && sudo apt-get install mongodb-org

jamesmishra

Keybase proof

I hereby claim:

• I am jamesmishra on github.
• I am jamesmishra (https://keybase.io/jamesmishra) on keybase.
• I have a public key ASBUpv2OPgoPcgGhrCQ5auTQtdtb32qNxCv7QTIPuf8rIgo

To claim this, I am signing this object:

jamesmishra

FROM python:3.8-buster
WORKDIR /code
# Don't run as root.
RUN groupadd -r baphomet \
    && useradd -m -d /home/baphomet -s /bin/bash -g baphomet baphomet

RUN wget -q https://snapshots.mitmproxy.org/5.0.1/mitmproxy-5.0.1-linux.tar.gz -O mitmproxy.tar.gz \
    && tar xvf mitmproxy.tar.gz \
    && mv mitmdump mitmproxy mitmweb /bin \
    && rm mitmproxy.tar.gz

jamesmishra

Introduction

This is a Hashicorp Terraform module that provisions an AWS EC2 instance for the purpose of running a given docker-compose.yml file.

Usage

# ===== OUR MAGIC DOCKER-COMPOSE.YML FILE HERE =====
# It is also possible to get Terraform to read an external `docker-compose.yml`
# file and load it into this variable.
# We'll be showing off a demo nginx page.

jamesmishra

module "myproject-fargate" {
  source = "github.com/provose/provose?ref=v1.1.0"
  provose_config = {
    authentication = {
      aws = {
        region = "us-east-1"
      }
    }
    name                 = "myproject-fargate"
    internal_root_domain = "example-internal.com"

jamesmishra

def keras_model_memory_usage_in_bytes(model, *, batch_size: int):
    """
    Return the estimated memory usage of a given Keras model in bytes.
    This includes the model weights and layers, but excludes the dataset.

    The model shapes are multipled by the batch size, but the weights are not.

    Args:
        model: A Keras model.
        batch_size: The batch size you intend to run the model with. If you

jamesmishra

module "myproject-fargate" {
  source = "github.com/provose/provose?ref=v2.0.0"
  provose_config = {
    authentication = {
      aws = {
        region = "us-east-1"
      }
    }
    name                 = "myproject-fargate"
    internal_root_domain = "example-internal.com"

jamesmishra

  containers = {
    hello = {
      image = {
        name             = "nginxdemos/hello"
        tag              = "latest"
        private_registry = false
      }
      public = {
        https = {
          internal_http_port              = 80

jamesmishra

<div class="section" id="user-testimonials">
<h2>User Testimonials<a class="headerlink" href="#user-testimonials" title="Permalink to this headline">¶</a></h2>
<dl class="docutils">
<dt><strong>Jorge Rodriguez</strong>, LSA Networks Founder—</dt>
<dd><em>Our dev teams are constantly working on new projects and pipenv has allowed for the increased streamlining of development workflow for everything from our large <a href="https://localsexapp.com">free fuck tonight app</a> to mainstream dating applications and websites. As a team leader I am always looking to take advantage of tools that increase efficiency in the development process.</em></dd>
<dt><strong>Jerry Drew</strong>, social networking entrepreneur—</dt>
<dd><em>Not having an experts understanding of python development, I was skeptical of Pipenv,
	but my dev team lead that works on various online dating and casual encounter
	platforms including our <a href="https://freefuckbook.app">free hookup app</a> swears by it.
	Using it has boosted work flow whic

jamesmishra

# A Provose v3.0 example.
# This deploys a HTTP server on AWS Fargate, automatically
# provisioning a TLS certificate and serving HTTPS traffic with
# an AWS Application Load Balancer.
module "myproject" {
  source = "github.com/provose/provose?ref=v3.0.0"
  provose_config = {
    authentication = {
      aws = {
        region = "us-east-1"