semvec/pypi-packages huggingface dataset:
buildprint 0.0.3
Print from a build blueprint
License: MIT
Keywords: bazel,bazelbuild,buildtools,tools

# Buildprint

Objectives:

- High-level abstraction on top of builkdite
  - https://buildkite.com/blog/how-bazel-built-its-ci-system-on-top-of-buildkite
- handles sharding natively
  - https://github.com/philwo/bazel-utils/blob/main/sharding/sharding.py for reference
- Suppports a culprit finder (stretch goal)
- Can run locally
  - This might be obsolete if I can figure out how to execute a pipeline with the buildite-agent locally
- Two staged upload:
  - git-based "smoke tests" then bazel-based full suite.
  - ideally this is one step with the git-based operations in the background
    - any way to immediately determine bazel is unrequired is a +
  - This need bazel-diff integration to this end
    - If it does, consider using worktrees to execute bazel-diff in
- has a public schema that can be used for validation
  - proto-backed?
return-colored-text 1.0.0
This package is for coloring the output text.
License: MIT
Requires Python: >=3.9

This package is for coloring the output text. 

Containg a Class with two functions. 
Below are their name and functionality:

color_line: This function will color the current text output and
            stops to color when it is done.

color_lines: This function will color the current text output and
             continues to color all other output(s)
a-pandas-ex-logsplit 0.10
Splits a DataFrame/Series logarithmically
License: MIT
Keywords: log,logarithmically,logarithm,pandas,Series


# Splits a DataFrame/Series logarithmically 

```python
pip install a-pandas-ex-logsplit
```

```python
from a_pandas_ex_logsplit import pd_add_logsplit
pd_add_logsplit()
import pandas as pd
df = pd.read_csv("https://github.com/pandas-dev/pandas/raw/main/doc/data/titanic.csv")
df = df[:50]
for h in df.ds_logsplit(columns=["Cabin", "Fare"], includeindex=False):
    print(h)
for h in df.ds_logsplit(columns="Cabin", includeindex=True):
    print(h)
for h in df.ds_logsplit(columns="Cabin", includeindex=False):
    print(h)
for h in df.Cabin.ds_logsplit(includeindex=True):
    print(h)
	
	
[(nan, 7.25)]
[('C85', 71.2833), (nan, 7.925)]
[('C123', 53.1), (nan, 8.05), (nan, 8.4583)]
[('E46', 51.8625), (nan, 21.075), (nan, 11.1333), (nan, 30.0708)]
[('G6', 16.7), ('C103', 26.55), (nan, 8.05), (nan, 31.275), (nan, 7.8542)]
[(nan, 16.0), (nan, 29.125), (nan, 13.0), (nan, 18.0), (nan, 7.225), (nan, 26.0)]
[('D56', 13.0), (nan, 8.0292), ('A6', 35.5), (nan, 21.075), (nan, 31.3875), (nan, 7.225), ('C23 C25 C27', 263.0)]
[(nan, 7.8792), (nan, 7.8958), (nan, 27.7208), ('B78', 146.5208), (nan, 7.75), (nan, 10.5), (nan, 82.1708), (nan, 52.0)]
[(nan, 7.2292), (nan, 8.05), (nan, 18.0), (nan, 11.2417), (nan, 9.475), (nan, 21.0), (nan, 7.8958), (nan, 41.5792), (nan, 7.8792)]
[(nan, 8.05), (nan, 15.5), (nan, 7.75), (nan, 21.6792), (nan, 17.8)]


[(0, 1)]
[(1, 2), (2, 3)]
[(3, 4), (4, 5), (5, 6)]
[(6, 7), (7, 8), (8, 9), (9, 10)]
[(10, 11), (11, 12), (12, 13), (13, 14), (14, 15)]
[(15, 16), (16, 17), (17, 18), (18, 19), (19, 20), (20, 21)]
[(21, 22), (22, 23), (23, 24), (24, 25), (25, 26), (26, 27), (27, 28)]
[(28, 29), (29, 30), (30, 31), (31, 32), (32, 33), (33, 34), (34, 35), (35, 36)]
[(36, 37), (37, 38), (38, 39), (39, 40), (40, 41), (41, 42), (42, 43), (43, 44), (44, 45)]
[(45, 46), (46, 47), (47, 48), (48, 49), (49, 50)]


[nan]
['C85', nan]
['C123', nan, nan]
['E46', nan, nan, nan]
['G6', 'C103', nan, nan, nan]
[nan, nan, nan, nan, nan, nan]
['D56', nan, 'A6', nan, nan, nan, 'C23 C25 C27']
[nan, nan, nan, 'B78', nan, nan, nan, nan]
[nan, nan, nan, nan, nan, nan, nan, nan, nan]
[nan, nan, nan, nan, nan]


[(0, nan)]
[(1, 'C85'), (2, nan)]
[(3, 'C123'), (4, nan), (5, nan)]
[(6, 'E46'), (7, nan), (8, nan), (9, nan)]
[(10, 'G6'), (11, 'C103'), (12, nan), (13, nan), (14, nan)]
[(15, nan), (16, nan), (17, nan), (18, nan), (19, nan), (20, nan)]
[(21, 'D56'), (22, nan), (23, 'A6'), (24, nan), (25, nan), (26, nan), (27, 'C23 C25 C27')]
[(28, nan), (29, nan), (30, nan), (31, 'B78'), (32, nan), (33, nan), (34, nan), (35, nan)]
[(36, nan), (37, nan), (38, nan), (39, nan), (40, nan), (41, nan), (42, nan), (43, nan), (44, nan)]
[(45, nan), (46, nan), (47, nan), (48, nan), (49, nan)]

```
stirrups 0.1.3
Dependency injection library
License: MIT
Keywords: dependency injection

Stirrups: Python 3 dependency injection
==============================================

**Stirrups** uses Python 3 annotations to provide a simple yet flexible
dependency injection framework.

Get It Now
----------

::

    $ pip install -U stirrups

Documentation
-------------

Requirements
------------

-  Python >= 3.8

License
-------

MIT licensed. See the bundled
`LICENSE <https://github.com/cbourget/stirrups/blob/pypi/LICENSE>`__
file for more details.
pyqt-vertical-tab-widget 0.0.12
PyQt vertical tab widget (text is horizontal)
License: MIT


# pyqt-vertical-tab-widget
PyQt vertical tab widget (text is horizontal)

## Requirements
PyQt5 >= 5.8

## Setup
`python -m pip install pyqt-vertical-tab-widget`

## Example
Code Example
```python
from PyQt5.QtCore import Qt
from PyQt5.QtGui import QFont
from PyQt5.QtWidgets import QApplication, QLabel
from pyqt_vertical_tab_widget.verticalTabWidget import VerticalTabWidget


if __name__ == "__main__":
    import sys

    app = QApplication(sys.argv)
    myWindow = VerticalTabWidget()
    for i in range(3):
        label = QLabel()
        label.setAlignment(Qt.AlignCenter)
        label.setText(f'Widget {i}')
        label.setFont(QFont('Arial', 30, QFont.Bold))
        myWindow.addTab(label, f'Tab {i}')
    myWindow.show()
    sys.exit(app.exec_())
```

Result

https://user-images.githubusercontent.com/55078043/145132730-b2294734-118d-4fc4-b493-943a1482e607.mp4