Save your files with current date time appended; load the newest back without specifying file name everytime
Project description
This is a simple script that has only two functions for one purpose. It allows you to save files with date time appended behind the filename but in front of the extension, like sldt.s(variable, 'filename.csv')
will save variable to a file "filename_1912181212.csv". Everytime you want to load it back, use sldt.l('filename.csv')
, it will automatically find the newest file.
This is useful when you want to save some intermediate result during running your code. But be aware the saved files will keep growing everytime you run.
Feel free to download/edit this script, and maybe share your version with me!
Installation
pip install sldt
Supported File Types
It supports only 4 common file types now showed below. Basically it just calls like pd.DataFrame.to_csv()
as you already familiar.
import sldt
sldt.__version__
'1.0.2'
sldt.SUPPORTED_EXT
['.pkl', '.csv', '.png', '.txt']
Demo
# launch logger to see info when saving and loading files
import logging
logging.getLogger().setLevel(logging.INFO)
anything -> pkl
a_list = ['a', 0.1, False]
# save
sldt.s(a_list, 'output/a_list.pkl')
# save the second file for demo
import time
time.sleep(60)
a_list = ['b', 0.2, True]
sldt.s(a_list, 'output/a_list.pkl')
# load the newest (which is the later one) back
a_list = sldt.l('output/a_list.pkl')
a_list
INFO:root:output/a_list_1912240334.pkl saved
INFO:root:output/a_list_1912240335.pkl saved
INFO:root:output/a_list_1912240335.pkl loaded
['b', 0.2, True]
pandas dataframe -> csv
import pandas as pd
df = pd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})
sldt.s(df, 'output/df.csv')
df = sldt.l('output/df.csv')
df
INFO:root:output/df_1912240335.csv saved
INFO:root:output/df_1912240335.csv loaded
col1 | col2 | |
---|---|---|
0 | 1 | 3 |
1 | 2 | 4 |
For example, save_dt(df, 'output/df.csv', sep=';')
figure -> png
import seaborn as sns
exercise = sns.load_dataset("exercise")
g = sns.catplot(x="time", y="pulse", hue="kind", data=exercise)
sldt.s(g, 'output/g.png')
INFO:root:output/g_1912240335.png saved
Display it using ![](output/g_1912240037.png)
in markdown.
the default arguments will be dpi=600, bbox_inches='tight'
. And it will try to close the fig after saving the file.
string -> txt
text = '''some random sentences
here
and there'''
sldt.s(text, 'output/text.txt')
text = sldt.l('output/text.txt')
text
INFO:root:output/text_1912240335.txt saved
INFO:root:output/text_1912240335.txt loaded
'some random sentences\nhere\nand there'
helper functions
you can save your own file type and load it back using append_dt
and find_newest
import pickle
output_filename = sldt.append_dt('output/sth.pkl', datetime_format="%y%m%d%H%M")[0]
with open(output_filename, 'wb') as f:
pickle.dump('some strings', f)
newest_file = sldt.find_newest('output/sth.pkl')[0]
with open(newest_file, 'rb') as f:
sth = pickle.load(f)
sth
'some strings'
find_newest
returns a tuplet (filename, extension)
sldt.find_newest('output/text.txt')
('output/text_1912240335.txt', '.txt')
It can be served as checking whether file is exist
try:
sldt.find_newest('output/text.txt')
print('file exist')
except:
print('no file exist')
file exist
Similarly, load only if you haven't save the needed file
try:
sldt.l('output/result.csv')
except:
# do some calculation
result = pd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})
# save calculation result
sldt.s(result, 'output/result.csv')
INFO:root:output/result_1912240335.csv saved
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.