scx

SCx

MIT's Supply Chain Micromaster (SCx) Python Package

Documentation

Technical documentation can be found here.

Examples

Setup

Cloud Setup (Google Colab)

You can access google colab here
Create a new notebook
Install the scx package by adding the following to a new code cell at the top of your notebook and running it:
- pip install scx

Local Setup

Make sure you have Python 3.11.x (or higher) installed on your system. You can download it here.

Recommended (but Optional) -> Expand this section to setup and activate a virtual environment.

Install (or upgrade) virtualenv:

python3 -m pip install --upgrade virtualenv

Create your virtualenv named venv:
```
python3 -m virtualenv venv
```
Activate your virtual environment
- On Unix (Mac or Linux):
```
source venv/bin/activate
```
- On Windows:
```
venv\scripts\activate
```

pip install scx

Optimization Getting Started

See all of the optimization examples here.

Basic Usage

from scx.optimize import Model

Simple Optimization

from scx.optimize import Model

# Create variables
product_1_amt = Model.variable(name="product_1", lowBound=0)
product_2_amt = Model.variable(name="product_2", lowBound=0)

# Initialize the model
my_model = Model(name="Generic_Problem", sense='maximize')

# Add the Objective Fn
my_model.add_objective(
    fn = (product_1_amt*1)+(product_2_amt*1)
)

# Add Constraints
my_model.add_constraint(
    name = 'input_1_constraint',
    fn = product_1_amt*1+product_2_amt*2 <= 100
)
my_model.add_constraint(
    name = 'input_2_constraint',
    fn = product_1_amt*3+product_2_amt*1 <= 200
)

# Solve the model
my_model.solve(get_duals=True, get_slacks=True)

# Show the outputs
# NOTE: outputs can be fetched directly as a dictionary with `my_model.get_outputs()`
my_model.show_outputs()

Outputs:

{'duals': {'input_1_constraint': 0.4, 'input_2_constraint': 0.2},
 'objective': 80.0,
 'slacks': {'input_1_constraint': -0.0, 'input_2_constraint': -0.0},
 'status': 'Optimal',
 'variables': {'product_1': 60.0, 'product_2': 20.0}}

Database Getting Started

See all of the database examples here

Basic Usage

from scx.database import Database
# Specify the S3 path to the data
data_folder = 's3://scx-dev/databases/supermarket/'
# Create the database
db = Database(f'''
    CREATE TABLE Customers AS SELECT * FROM read_parquet('{data_folder}customers.parquet');
''')
# Show the database Schema
db.show_info()

# Query the database
db.query("SELECT * FROM Customers LIMIT 5")

View Source

  1"""
  2# SCx
  3[![PyPI version](https://badge.fury.io/py/scx.svg)](https://badge.fury.io/py/scx)
  4[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
  5
  6MIT's [Supply Chain Micromaster](https://micromasters.mit.edu/scm/) (SCx) Python Package
  7
  8## Documentation
  9[Technical documentation](https://connor-makowski.github.io/scx/scx.html) can be found [here](https://connor-makowski.github.io/scx/scx.html).
 10
 11## Examples
 12- [All Optimization Examples](https://github.com/connor-makowski/scx/tree/main/notebooks/optimization/)
 13  - [Basic Examples](https://github.com/connor-makowski/scx/tree/main/notebooks/optimization/basic_examples)
 14  - [Blinky Examples (with video walkthroughs)](https://github.com/connor-makowski/scx/tree/main/notebooks/optimization/blinky_examples)
 15  - [Food On Wheels Examples (with video walkthroughs)](https://github.com/connor-makowski/scx/tree/main/notebooks/optimization/fow_examples)
 16  - [Eco Pants Examples (with video walkthroughs)](https://github.com/connor-makowski/scx/tree/main/notebooks/optimization/eco_pants_examples)
 17  - [Miscellaneous Examples](https://github.com/connor-makowski/scx/tree/main/notebooks/optimization/misc_examples)
 18- [All Database Examples](https://github.com/connor-makowski/scx/tree/main/notebooks/database/)
 19  - [Transaction Database Example](https://github.com/connor-makowski/scx/tree/main/notebooks/database/Transaction.ipynb)
 20
 21## Setup
 22
 23### Cloud Setup (Google Colab)
 24- You can access google colab [here](https://colab.research.google.com/)
 25- Create a new notebook
 26- Install the `scx` package by adding the following to a new code cell at the **top** of your notebook and running it:
 27  - `pip install scx`
 28
 29
 30### Local Setup
 31Make sure you have Python 3.11.x (or higher) installed on your system. You can download it [here](https://www.python.org/downloads/).
 32<details>
 33<summary>
 34Recommended (but Optional) -> Expand this section to setup and activate a virtual environment.
 35</summary>
 36
 37  - Install (or upgrade) virtualenv:
 38  ```
 39  python3 -m pip install --upgrade virtualenv
 40  ```
 41  - Create your virtualenv named `venv`:
 42  ```
 43  python3 -m virtualenv venv
 44  ```
 45  - Activate your virtual environment
 46    - On Unix (Mac or Linux):
 47    ```
 48    source venv/bin/activate
 49    ```
 50    - On Windows:
 51    ```
 52    venv\\scripts\\activate
 53    ```
 54</details>
 55
 56```
 57pip install scx
 58```
 59
 60## Optimization Getting Started
 61See all of the optimization examples [here](https://github.com/connor-makowski/scx/tree/main/notebooks/optimization/).
 62
 63### Basic Usage
 64```py
 65from scx.optimize import Model
 66```
 67
 68#### Simple Optimization
 69```py
 70from scx.optimize import Model
 71
 72# Create variables
 73product_1_amt = Model.variable(name="product_1", lowBound=0)
 74product_2_amt = Model.variable(name="product_2", lowBound=0)
 75
 76# Initialize the model
 77my_model = Model(name="Generic_Problem", sense='maximize')
 78
 79# Add the Objective Fn
 80my_model.add_objective(
 81    fn = (product_1_amt*1)+(product_2_amt*1)
 82)
 83
 84# Add Constraints
 85my_model.add_constraint(
 86    name = 'input_1_constraint',
 87    fn = product_1_amt*1+product_2_amt*2 <= 100
 88)
 89my_model.add_constraint(
 90    name = 'input_2_constraint',
 91    fn = product_1_amt*3+product_2_amt*1 <= 200
 92)
 93
 94# Solve the model
 95my_model.solve(get_duals=True, get_slacks=True)
 96
 97# Show the outputs
 98# NOTE: outputs can be fetched directly as a dictionary with `my_model.get_outputs()`
 99my_model.show_outputs()
100```
101Outputs:
102```py
103{'duals': {'input_1_constraint': 0.4, 'input_2_constraint': 0.2},
104 'objective': 80.0,
105 'slacks': {'input_1_constraint': -0.0, 'input_2_constraint': -0.0},
106 'status': 'Optimal',
107 'variables': {'product_1': 60.0, 'product_2': 20.0}}
108
109```
110
111## Database Getting Started
112See all of the database examples [here](https://github.com/connor-makowski/scx/tree/main/notebooks/database/)
113
114### Basic Usage
115```py
116from scx.database import Database
117# Specify the S3 path to the data
118data_folder = 's3://scx-dev/databases/supermarket/'
119# Create the database
120db = Database(f'''
121    CREATE TABLE Customers AS SELECT * FROM read_parquet('{data_folder}customers.parquet');
122''')
123# Show the database Schema
124db.show_info()
125
126# Query the database
127db.query("SELECT * FROM Customers LIMIT 5")
128```"""