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Research documentation

Getting Started

Developer guide

Release

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Technical Documentation

Resources

Tasks

Conda env agent

Create a sugar type of food

Create folder from files

Create json dict

Create lab note

Create note resource

Decompress file

Download an scenario

Download resource from a S3 bucket

Download resource from external source

Extract column tags to new row

Extract column values to row tags

Extract row tags to new column

Extract row values to column tags

Folder exporter

Fs node extractor

Generate lab note from note resource

Histogram Plotly

JSON Dict exporter

JSON Dict importer

Mamba env agent

Merge note resources

R conda env agent

R mamba env agent

Resource exporter

Resource importer

Resource picker

Resource set exporter

Resource stacker

Scatterplot Plotly

Select note template

Smart interactive plot generator

Smart json transformer

Smart multi tables transformer

Smart plot generator

Smart table transformer

Streamlit agent

Table column aggregator

Table column aggregator filter

Table column annotator

Table column concat

Table column data numeric filter

Table column data text filter

Table column operation mass

Table column operations

Table column scaler

Table column tag aggregator

Table column tag unfolder

Table column tags deleter

Table column tags selector

Table columns deleter

Table columns selector

Table row aggregator

Table row aggregator filter

Table row annotator

Table row concat

Table row data numeric filter

Table row data text filter

Table row scaler

Table row tag aggregator

Table row tag unfolder

Table row tags deleter

Table row tags selector

Table rows deleter

Table rows selector

Table transposer

The travel of `Astro`

Unzip and load resource

Update note resource

Upload resource to S3

Violinplot Plotly

[Support] Update process typing name

[Support] Update resource typing name

Protocols

Other Classes

Conda env agent

TASK

Typing name : TASK.gws_core.PyCondaAgent

Brick : gws_core

Agent to run Python snippets in a conda shell environment.

Conda-based Python agents allow to execute Python snippets on the fly in isolated conda environments.

Agents are fast and efficient tools to develop, test, use and share code snippets.

Warning: It is recommended to use code snippets comming from trusted sources.

Here is the general documentation for agent (including how to use the parameters): https://constellab.community/bricks/gws_core/latest/doc/developer-guide/agent/getting-started/69820653-52e0-41ba-a5f3-4d9d54561779

Here is the documentation of the agent: https://constellab.community/bricks/gws_core/latest/doc/developer-guide/agent/env-agent/c6acb3c3-2a7c-44cd-8fb2-ea1beccdbdcc

Input

File or folder

Optional

Output

File or folder

Configuration

params

Optional

Please give one parameter definition per line (https://constellab.community/bricks/gws_core/latest/doc/developer-guide/agent/getting-started/69820653-52e0-41ba-a5f3-4d9d54561779#parameters)

Type : list

Default value :

env

Optional

YAML configuration of the conda environment

Type : yaml_code_param

Default value :

name: .venv
channels:
  - conda-forge
dependencies:
  - python=3.10
  - pandas==2.2.2
  - numpy==1.26.4

code

Optional

The Python code snippet to execute using shell command

Type : python_code_param

Default value :

# This is a snippet template for a Python agent.
import pandas

# Do the job here ...
data = pandas.read_csv(source_paths[0], header=0, index_col=0, sep=',')

# transform the data
result = data.transpose()

# Write the output file in the target folder
result_path = "result.csv"
result.to_csv(result_path, index=True)
target_paths = [result_path]