---
id: import-external-libraries-using-runpy
title: Import external libraries using RunPy
---
ToolJet allows you to utilize python packages in your app by importing them using the [RunPy query](/docs/data-sources/run-py).
In this how-to guide, we will import a few packages and use it in the application.
:::caution Unsupported modules
The modules that are not currently supported in Pyodide are those that have C or C++ extensions that rely on system libraries. These modules cannot be used in Pyodide because it runs in a web browser, which does not have access to the underlying system libraries that the C or C++ extensions rely on. Additionally, Pyodide uses a version of Python that has been compiled to WebAssembly, which does not support the same system calls as a regular version of Python. Therefore, any module that requires access to system libraries or system calls will not work in Pyodide.
:::
- Create a new application and then create a new RunPy query from the query panel.
- Let's write some code for importing packages. We will first import the micropip which is a package installer for Python and then we will install the `Pandas` and `NumPy` using micropip. **Run** the query to install the packages.
```python
import micropip
await micropip.install('pandas')
await micropip.install('numpy')
```
:::tip
Enable the **Run this query on application load?** option to make the packages available throughout the application.
:::
## Examples
### Array of random numbers of using NumPy
- Let's create a **RunPy** query that will use **random** module from the **NumPy** package and the query will generate array of random numbers.
```python
from numpy import random
x = random.binomial(n=10, p=0.5, size=10)
print(x)
```
:::info
You can check the output on the browser's console.
:::
### Parse CSV data
- Let's create a RunPy query that will parse the data from the csv file. In this query we will use `StringIO`, `csv`, and `Pandas` module.
```python
from io import StringIO
import csv
import pandas as pd
scsv = components.filepicker1.file[0].content
f = StringIO(scsv)
reader = csv.reader(f, delimiter=',')
df = pd.DataFrame(reader)
print(df.info())
print(df)
```
- Add a file picker component on the canvas and set a event handler for **On file loaded** event to **Run Query** that we created for parsing the data.
- Finally, let's load a csv file on the file picker and check the output by the RunPy query on the browser console.