record-kit

A simple record toolkit generating human-readable data record in experiments.

Installation

pip install record-kit

Usage

Suppose you have an experiment script like this:

import argparse

parser = argparse.ArgumentParser()
parser.add_argument('--lr', type=float)
args = parser.parse_args()

def train_ml_model():
    for i in range(2):
        epoch, loss, acc = i, 0.1, 0.5

Using record-kit to track these generated data is quite easy:

from record_kit import Recorder, Record             # use Recorder to track experiment data
import argparse

parser = argparse.ArgumentParser()
parser.add_argument('--lr', type=float, default=0.1)
args = parser.parse_args()


def train_ml_model():
    for i in range(2):
        epoch, loss, acc = i, 0.1, 0.5
        recorder.add_data(epoch, loss, acc)   # save data


# init Recorder
recorder = Recorder()                              # init Recorder
recorder.set_meta(args)                            # save arguments like hyperparameters
recorder.set_header('epoch', 'loss', 'acc')        # specify table header

# parse record
record = Record(recorder) # or record = Record('path/to/record')
print(record.meta)
print(record.data)

output

{'lr': 0.1}
   epoch  loss  acc
0    0.0  0.10  0.5
1    1.0  0.08  0.9

generated record in ./records/record-timestamp.md

Record Format

A typical record includes two sections Meta and Data.

# record-20201020-154912
## Meta
| key | value | type |
| :---: | :---: | :---: |
| lr | 0.1 | float |
## Data
| epoch | loss | acc |
| :---: | :---: | :---: |
| 0 | 0.1 | 0.5 |
| 1 | 0.08 | 0.9 |

API

Recorder

Recorder(file_name='record', records_dir='./records', with_timestamp=True)

Initialize a Recorder instance

Recorder.set_meta(dict_like_object)

Add meta info to the record. Note meta info can only be added once. You may use dict or argparse.Namespace(return type of parser.parse_args()) as its parameter.

Recorder.set_header(*args)

Specify header of data table in Data section. The header can only be added once.

Recorder.add(*args)

Add a data line to the table in Data section. The number of parameters in should be consistent with Recorder.set_header(*args)

Record

Record(Recorder_or_path_str)

Load & parse record

Record.meta -> dict

Get meta info of record.

Record.data -> pandas.DataFrame

Get data table of record.