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* Updated the formatting of how to docs for the next and current versions * Used the title cases in the heading * Updated the formatting of how to docs for the next and current versions * Used the title cases in the heading * updated the formatting of inspector, form, cell colors * resolved conflicts * Updated the formatting of bulk update multiple rows, conditionaly format table, delete multiple rows, serverside pagination * Updated access user groups, import external lib in js and python, use axios * fix: border colour, blur * Revert changes to versions.json * Changed the formatting of how to docs * add changes from docs/next to v2.34.0 * update: how to docs * fix: image name create-new-query * fix: image name import-successful.png * fix: image name flatten-js * fix: image name math-js-v2 * update: shorten page titles --------- Co-authored-by: Asjad Ahmed Khan <iitasjad2001@gmail.com> Co-authored-by: Karan Rathod <karan.altcampus@gmail.com>
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3.1 KiB
| id | title |
|---|---|
| import-external-libraries-using-runpy | Import External Libraries Using RunPy |
ToolJet allows you to utilize python packages in your app by importing them using the RunPy query. In this how-to guide, we will import a few packages and use them in the application.
:::caution Unsupported modules Modules with C/C++ extensions needing system libraries won't work in Pyodide, as it runs in a web browser without system library access. Pyodide, based on WebAssembly-compiled Python, also doesn't support certain system calls. :::
- Start by creating a new application in ToolJet.
- From the Query Panel, add a new RunPy query - it will be named runpy1 by default.
- Use micropip to install packages like Pandas and NumPy. Run the query to complete installation.
import micropip
await micropip.install('pandas')
await micropip.install('numpy')
- Enable
Run this query on application load?to make these packages available every time the application loads.
Generating Random Numbers with NumPy
- Create a RunPy query using NumPy's random module to generate random numbers.
from numpy import random
x = random.binomial(n=10, p=0.5, size=10)
print(x)
You can check the output on the browser's console.
Parse CSV data
- Create a RunPy query to parse CSV data using
StringIO,csv, andPandasmodule.
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
- Select
On File Loadedas the Event and Run Query as the Action. - Select the query we just created as the Query.
- Finally, load a csv file on the File Picker component, Run related RunPy query and check the output on the browser console.
