pydata-london-2022-sqlalchemy-tutorial

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pydata-london-2022-sqlalchemy-tutorial

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My tutorial on SQLAlchemy for Pydata London 2022 Conference

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# SQLAlchemy and you – making SQL the best thing since sliced bread

Are you writing SQL strings in your code? Have you only used ORMs and want to start getting more 
control over your SQL?

SQLAlchemy is the gold-standard for working with SQL in Python and this tutorial will get you 
comfortable working in it, so you can take advantage of its power.

We will go through Core and ORM abstractions, so you'll be comfortable navigating through the 
different layers and be able to fully use the power of Python when writing your SQL

# Project setup

If you have your own, preferred setup for installing packages - go right ahead and use that. 
There's a requirements.txt and an environment.yml file you can use. 
Alternatively, if you have `docker` and `docker compose` installed, you can use the provided 
`docker-compose` setup

## Docker compose
```bash
docker compose up -d
docker compose logs jupyter
```

In the logs you should see a URL that looks similar to

`http://127.0.0.1:8888/lab?token=39ec5120ee84b090487a822b991269732a264629c894803e`

Copy-paste that into your browser, you should be able to login to the Jupyter instance

## Conda-based

If you have Anaconda distribution installed, you can run the following

```bash
conda env create
```

This will install all the packages defined in the `environment.yml` file into an environment named
`sqlalchemy-tutorial`.

To activate this environment, run
```bash
conda activate sqlalchemy-tutorial
```

## Virtualenv-based
This tutorial was written in 3.9.13 - ensure that you have at least 3.9.X installed on your machine

To create a new virtualenv run
```bash
python -m venv venv
```

To activate the virtualenv - run one of the following:

### Windows

```cmd
./venv/Scripts/activate
```

### MacOS/Linux

```bash
source venv/bin/activate
```

You'll then need to install the packages

```bash
python -m pip install -r requirements.txt
```

After you've installed the packages run `jupyter lab` to start the Jupyter lab server

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