Add timedelta2string

LICENSE

@@ -1,21 +1,21 @@
-MIT License
-
-Copyright (c) 2020 The Penut Python Package
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
+MIT License
+
+Copyright (c) 2020 The Penut Python Package
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,44 +1,35 @@
-# Penut
-
-## Introduction
-+ [GitHub](https://github.com/penut85420/penut)  
-[![GitHub release](https://img.shields.io/github/v/release/penut85420/penut.svg)](https://github.com/penut85420/penut/releases)
-[![GitHub release date](https://img.shields.io/github/release-date/penut85420/penut.svg)](https://github.com/penut85420/penut/releases)
-[![GitHub issues](https://img.shields.io/github/issues/penut85420/penut.svg)](https://github.com/penut85420/penut/issues)
-+ PyPI  
-[![PyPI version](https://img.shields.io/pypi/v/penut.svg?maxAge=3600)](https://pypi.org/project/penut)
-[![PyPI license](https://img.shields.io/pypi/l/penut.svg?maxAge=3600)](https://github.com/ckiplab/penut/blob/master/LICENSE)
-[![PyPI python](https://img.shields.io/pypi/pyversions/penut.svg?maxAge=3600)](https://pypi.org/project/penut)
-+ This package is a collection of my useful functions.
-+ Including useful IO operation and NLP utils.
-
-## Installation
-+ You can install this package through pip:
-  ```
-  pip install penut
-  ```
-
-## Usage
-+ You can easily load or dump and json/pkl/csv/npy file:
-  ```python
-  import penut.io as pio
-
-  data = pio.load('./data.json')
-  data = pio.load('./data.pkl')
-  data = pio.load('./data.csv')
-  data = pio.load('./data.npy')
-
-  pio.dump(data, './data.json')
-  pio.dump(data, './data.pkl')
-  pio.dump(data, './data.csv')
-  pio.dump(data, './data.npy')
-  ```
-+ You can easily measure the execute time of code:
-  ```python
-  from penut.uitls import TimeCost
-
-  with TimeCost('Sleep Time'):
-    import time
-    time.sleep(1)
-  # Output: Sleep Time: 1.000262s
+# Penut
+
+## Introduction
++ This package is a collection of my useful functions, including some useful IO operations.
+
+## Installation
++ You can install this package through pip:
+  ```
+  pip install penut
+  ```
+
+## Usage
++ You can easily load or dump and json/pkl/csv/npy file:
+  ```python
+  import penut.io as pio
+
+  data = pio.load('./data.json')
+  data = pio.load('./data.pkl')
+  data = pio.load('./data.csv')
+  data = pio.load('./data.npy')
+
+  pio.dump(data, './data.json')
+  pio.dump(data, './data.pkl')
+  pio.dump(data, './data.csv')
+  pio.dump(data, './data.npy')
+  ```
++ You can easily measure the execution time of code:
+  ```python
+  from penut.uitls import TimeCost
+
+  with TimeCost('Sleep Time'):
+    import time
+    time.sleep(1)
+  # Output: Sleep Time: 1.000262s
   ```

mk_build.sh

@@ -0,0 +1,13 @@
+#!/bin/bash
+
+# Upload to PyPI
+# 1. Delete all the file in dist if exists.
+# 2. Build dist by `python setup.py sdist bdist_wheel`.
+# 3. Upload by `twine upload dist/*`.
+
+python -m pip install -U setuptools wheel twine
+rm -rf build dist penut_utils.egg-info
+python setup.py sdist bdist_wheel
+python -m twine upload --repository testpypi dist/*
+# python -m twine upload dist/*
+# python -m pip install -i https://test.pypi.org/simple/ penut_utils==0.0.1

penut/__init__.py

@@ -0,0 +1 @@
+from .utils import TimeCost, walk_dir, td2s, timedelta2string

penut/io.py

@@ -1,81 +1,66 @@
-import os
-import json
-import numpy as np
-import pandas as pd
-import pickle as pk
-
-def dump_json(obj, fpath, encoding='UTF-8', is_ascii=False, indent=4):
-    with open(fpath, 'w', encoding=encoding) as f:
-        json.dump(obj, f, ensure_ascii=is_ascii, indent=indent)
-
-def load_json(fpath, encoding='UTF-8'):
-    with open(fpath, 'r', encoding=encoding) as f:
-        return json.load(f)
-
-def dump_pkl(obj, fpath):
-    with open(fpath, 'wb') as f:
-        pk.dump(obj, f)
-
-def load_pkl(fpath):
-    with open(fpath, 'rb') as f:
-        return pk.load(f)
-
-def dump_npy(obj, fpath):
-    np.save(fpath, obj)
-
-def load_npy(fpath):
-    return np.load(fpath)
-
-def dump_csv(obj, fpath, header=False, index=False):
-    pd.DataFrame(obj).to_csv(fpath, header=header, index=index)
-
-def load_csv(fpath, header=None):
-    pd.read_csv(fpath, header=header)
-
-def load(fpath, **kwargs):
-    load_dict = {
-        '.json': load_json,
-        '.pkl': load_pkl,
-        '.npy': load_npy,
-        '.csv': load_csv
-    }
-    _, ext = os.path.splitext(fpath)
-    return load_dict[ext](fpath)
-
-def dump(obj, fpath, **kwargs):
-    dump_dict = {
-        '.json': dump_json,
-        '.pkl': dump_pkl,
-        '.npy': dump_npy,
-        '.csv': dump_csv
-    }
-    _, ext = os.path.splitext(fpath)
-    return dump_dict[ext](obj, fpath, **kwargs)
-
-def mkdir(dir_path):
-    os.makedirs(dir_path, exist_ok=True)
-
-if __name__ == "__main__":
-    d = {'Name': 'Testing', 'Arr': [1, 2, 3], '測試': '項目'}
-    dump(d, 'a.json', is_ascii=True)
-    # dump_json(d, './a.json')
-    # dd = load_json('./a.json')
-    # assert d == dd
-
-    # dump_pkl(d, './a.pkl')
-    # dd = load_pkl('./a.pkl')
-    # assert d == dd
-
-    # dump(d, 'a.json')
-    # dump(d, 'a.pkl')
-    # dump(d, 'a.csv')
-    # a = load('a.json')
-    # b = load('a.pkl')
-    # c = load('a.csv')
-    # assert a == b
-
-    # print('Success!')
-
-    os.remove('a.json')
-    # os.remove('a.pkl')
-    # os.remove('a.csv')
+import os
+import json
+
+def dump_json(obj, fpath, encoding='UTF-8', is_ascii=False, indent=4):
+    with open(fpath, 'w', encoding=encoding) as f:
+        json.dump(obj, f, ensure_ascii=is_ascii, indent=indent)
+
+def load_json(fpath, encoding='UTF-8'):
+    with open(fpath, 'r', encoding=encoding) as f:
+        return json.load(f)
+
+def dump_pkl(obj, fpath):
+    import pickle as pk
+    with open(fpath, 'wb') as f:
+        pk.dump(obj, f)
+
+def load_pkl(fpath):
+    import pickle as pk
+    with open(fpath, 'rb') as f:
+        return pk.load(f)
+
+def dump_npy(obj, fpath):
+    import numpy as np
+    np.save(fpath, obj)
+
+def load_npy(fpath):
+    import numpy as np
+    return np.load(fpath)
+
+def dump_csv(obj, fpath, header=False, index=False):
+    pd = load_pandas()
+    pd.DataFrame(obj).to_csv(fpath, header=header, index=index)
+
+def load_csv(fpath, header=None):
+    pd = load_pandas()
+    return pd.read_csv(fpath, header=header)
+
+def load_pandas():
+    try:
+        import pandas as pd
+        return pd
+    except ModuleNotFoundError:
+        raise RuntimeError('Pandas is not installed!')
+
+def load(fpath, **kwargs):
+    load_dict = {
+        '.json': load_json,
+        '.pkl': load_pkl,
+        '.npy': load_npy,
+        '.csv': load_csv
+    }
+    _, ext = os.path.splitext(fpath)
+    return load_dict[ext](fpath, **kwargs)
+
+def dump(obj, fpath, **kwargs):
+    dump_dict = {
+        '.json': dump_json,
+        '.pkl': dump_pkl,
+        '.npy': dump_npy,
+        '.csv': dump_csv
+    }
+    _, ext = os.path.splitext(fpath)
+    return dump_dict[ext](obj, fpath, **kwargs)
+
+def mkdir(dir_path):
+    os.makedirs(dir_path, exist_ok=True)