mldev-reporting 0.1.1

Description:

mldevreporting 0.1.1

MLDev Reporting
Welcome to MLDev reporting - library for creating html reports for your experiment. The library provides functionaity for creating reports using Markdown templates and data from your experiment.
Start creating insightful reports today and unlock a clearer understanding of your ML experiments with MLDev reporting.
User Guide
First Step
Install MLDev Reporting using pip with comand
pip install mldev_reporting


Don't forget to add MLDev Reorting to your .mldev/stages/__init__.py file

import mldev_reporting

Second Step
Create an experement using experiment.yml
pipeline: !GenericPipeline
runs:
- !BasicStage
name: report

env:
PYTHONPATH: '${env.PYTHONPATH}:./.mldev'

script:
- mldev run -f ./report.yml

Third Step
Create a report.yml to configire your report
report: &report !Report
name: "index"
output_dir: "light_report"
template: "./template.md"
theme: "light"
lang: "ru"
report_model:


pipeline: !GenericPipeline
runs:
- *report

name is the name of your html file. output_dir is a folder where your report will be located. template is a link to your tamplate file. theme is a theme of your report. It can be light | dark | cards. lang is the report language. It can be ru or en. report_model is where your report data will go.
Fourth Step
Create a template for the report. repo is an object wrom with you can access your report data
# Me cool report

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nulla sem elit, tincidunt {{repo.data.result}} consectetur aliquam eget, ornare eget nunc. Aliquam erat purus, rutrum in erat nec, sodales commodo augue. Nullam ante nibh, accumsan sit amet eleifend nec, porttitor vel tellus. Sed dapibus at sapien vel mattis. Ut commodo quam tortor, quis porta erat convallis quis.

## Subtitle 1
{{repo.table}}

## Subtitle 2
{{repo.graphic}}

Fifth Step
Specify your report data. You can do it ather by hand or by loading data from file using !LoadFile
loadfile: &load_json_file !LoadFile
url: "index.json"

loadfile: &load_cvs_file !LoadFile
url: "index.csv"

Now you can add your data to report_model
report: &report !Report
name: "index"
output_dir: "light_report"
template: "./template.md"
theme: "light"
lang: "ru"
report_model:
data: *load_json_file

To create table use this comands
report: &report !Report
name: "index"
output_dir: "light_report"
template: "./template.md"
theme: "light"
lang: "ru"
report_model:
data: *load_json_file
table: !Table
title: "Example Table"
data: *load_cvs_file

To create graphic use this comands
report: &report !Report
name: "index"
output_dir: "light_report"
template: "./template.md"
theme: "light"
lang: "ru"
report_model:
data: *load_json_file
graphic: !Graphic
datasets:
- dataset: *load_cvs_file
x: "x_axis"
y: "y_axis"
name: "Example Graphic"
graphic_type: "line"

Sixth Step
Run the following comand to generate your report
mldev run -f experiment.yml

Documentation
Report Class











Field name
Type
Values
Default Value


name
string
Report file name
Required


output_dir
string
Path to the folder where the report will be stored
Required


template
string
Layout file path
Required


report_model
object
Report data
Required


theme
string
Topic
light


lang
string
Language
en



Table class











Field name
Type
Values
Default Value


title
string
Table name
Required


headers
string / array of strings
Object key if json file is used / Table column headers
Optional


rows
string / array of arrays of strings
Object key if json file is used / Table rows
Optional


data
link to data from file
Data from a file in json or csv format
Optional


widths
string
Column width as a percentage
Optional


header_rows
Integer
Line number to be used as header
Optional



Class Graphic











Field name
Type
Values
Default Value


datasets
array
Graph Datasets
Required


config
object
Graph Configuration
Empty object



More detailed information about the datasets can be found on the library page.
LoadFile class











Field name
Type
Values
Default Value


url
string
File path
Required


filter_fields
string array
A set of keys whose values ​​will be filtered (for json)
Optional


filter_columns
string array
A set of columns whose values ​​will be filtered (for csv)
Optional



Contributing
Please check the CONTRIBUTING.md guide if you'd like to participate in the project, ask a question or give a suggestion.
License
The software is licensed under Apache 2.0 license.