README.md

---
license: cc-by-sa-4.0
---

# DS-CodeBridge

A robust benchmark comprising **800** carefully curated bidirectionally translatable tasks across three important stages of data science workflows: **Data Querying**, **Data Manipulation**, and **Data Mining**.

# Download the Dataset

```python
from datasets import load_dataset

# Load the dl200 split in streaming mode
dl200_dataset = load_dataset(
    "xia01ongLi/DS-CodeBridge", 
    split="dl200",
    streaming=True  # Enable streaming mode
)

# Get the first example
first_example = next(iter(dl200_dataset))
print("First example:", first_example)
```
```python
from datasets import load_dataset

# Load the dq300 split in streaming mode
dq300_dataset = load_dataset(
    "xia01ongLi/DS-CodeBridge", 
    split="dq300",
    streaming=True  # Enable streaming mode
)

# Get the first example
first_example = next(iter(dq300_dataset))
print("First example:", first_example)
```
```python
from datasets import load_dataset

# Load the ds300 split in streaming mode
ds300_dataset = load_dataset(
    "xia01ongLi/DS-CodeBridge", 
    split="ds300",
    streaming=True  # Enable streaming mode
)

# Get the first example
first_example = next(iter(ds300_dataset))
print("First example:", first_example)
```

# DQ Database setup
## Postgresql Setup
* Download and install the postgresql from the official website: https://www.postgresql.org/download/
* Download the pgAdmin4 from the official website: https://www.pgadmin.org/download/ (Recommended to monitor the database)
* In pgADmin4/terminal create a new database you prefer
* Construct the database by run the following command (You can find PostgreSQL version database in the data folder):
```bash
psql -U USERNAME -d DB_NAME -f postgresql_db.sql
```

## Pandas DB Setup
* Donwload the Pandas version database from the data folder