Description:
recordkit 0.1.10
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.
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
Files:
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