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{
  "customModes": [
    {
      "slug": "sparc",
      "name": "⚡️ SPARC Orchestrator",
      "roleDefinition": "You are SPARC, the orchestrator of complex workflows. You break down large objectives into delegated subtasks aligned to the SPARC methodology. You ensure secure, modular, testable, and maintainable delivery using the appropriate specialist modes.",
      "customInstructions": "Follow SPARC:\n\n1. Specification: Clarify objectives and scope. Never allow hard-coded env vars.\n2. Pseudocode: Request high-level logic with TDD anchors.\n3. Architecture: Ensure extensible system diagrams and service boundaries.\n4. Refinement: Use TDD, debugging, security, and optimization flows.\n5. Completion: Integrate, document, and monitor for continuous improvement.\n\nUse `new_task` to assign:\n- spec-pseudocode\n- architect\n- code\n- tdd\n- debug\n- security-review\n- docs-writer\n- integration\n- post-deployment-monitoring-mode\n- refinement-optimization-mode\n\nValidate:\n✅ Files < 500 lines\n✅ No hard-coded

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layout	author	title	revision	version	description
default	mattmc3	Modern SQL Style Guide	2019-01-17	1.0.1	A guide to writing clean, clear, and consistent SQL.

Modern SQL Style Guide

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// http://ccrma.stanford.edu/planetccrma/



dnf install snd
dnf install snd-gtk
dnf install snd-motif
dnf install liblscp
dnf install liblscp-devel
dnf install liblscp-devel

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def rolling_window(self, ts, window, stride):
    shape = ts.shape[:-1] + (int((ts.shape[-1] - window)/stride + 1), window)
    strides = (stride*ts.strides[-1],) + (ts.strides[-1],)
    return np.lib.stride_tricks.as_strided(ts,
                                           shape=shape,
                                           strides=strides)

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syntax on

set nocompatible
set smartindent
set shiftwidth=4
set backspace=indent,eol,start
set ruler
set number
set showcmd
set incsearch

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# A virtualenv running Python3.6 on Amazon Linux/EC2 (approximately) simulates the Python 3.6 Docker container used by Lambda
# and can be used for developing/testing Python 3.6 Lambda functions
# This script installs Python 3.6 on an EC2 instance running Amazon Linux and creates a virtualenv running this version of Python
# This is required because Amazon Linux does not come with Python 3.6 pre-installed 
# and several packages available in Amazon Linux are not available in the Lambda Python 3.6 runtime

# The script has been tested successfully on a EC2 instance
# running 4.9.75-1.56.amzn2.x86_64 
# and was developed with the help of AWS Support

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# to setup on a fresh ec2 amazon linux box
sudo yum install git
sudo yum install -y gcc-c++ make
curl -sL https://rpm.nodesource.com/setup_6.x | sudo -E bash -
sudo yum install nodejs
git clone https://github.com/awslabs/aws-ai-qna-bot.git
cd aws-ai-qna-bot/
# setup aws credentials

PabTorre

def clean_json(x):
    """
    Cleans JSON object to make it DynamoDB friendly.
    It removes any keys that have an empty value.
    It moves all float values to string.
    """
    out = dict()
    if type(x) is dict:
        for k in x:
            if x[k] not in ["", {}, []]: