semvec/pypi-packages huggingface dataset:
pycodeobject 1.0.5
用于解析、编辑和处理Python字节码(bytecode)的工具。A tool for parsing and processing Python bytecode object.
Keywords: python, bytecode, 字节码, assembly, pyc, decompiling, 反编译

pycodeobject库是一个用于解析、编辑和处理Python字节码(bytecode)的工具。

PyCodeObject is a tool for parsing and processing Python bytecode object.

详细介绍
========

字节码的结构
"""""""""""""""""""""""

众所周知, Python中的字节码(bytecode) 是一种数据类型, Python代码的编译结果就是bytecode对象。

bytecode对象可以由虚拟机加载后直接运行，而pyc文件就是bytecode在硬盘上的保存形式。
先通过一个示例, 分析什么是字节码::

.. code-block:: python

    >>> import dis
    >>> def f(x):print('hello',x)
    
    >>> f.__code__
    <code object f at 0x02B27498, file "<pyshell#2>", line 1>
    >>> f.__code__.co_code
    b't\x00d\x01|\x00\x83\x02\x01\x00d\x00S\x00'
    >>> dis.dis(f)
      1           0 LOAD_GLOBAL              0 (print)
                  2 LOAD_CONST               1 ('hello')
                  4 LOAD_FAST                0 (x)
                  6 CALL_FUNCTION            2
                  8 POP_TOP
                 10 LOAD_CONST               0 (None)
                 12 RETURN_VALUE
    >>> 

上述示例中f.__code__就是bytecode对象, f.__code__.co_code就是二进制的字节码, 通过dis模块可以反编译、分析这些二进制代码。

Python解释执行代码时, 会首先将原始的源代码翻译成bytecode形式, 再直接执行bytecode, 以提高性能。

.. image:: https://img-blog.csdnimg.cn/20210719105023666.png
    :alt: 字节码结构图

(在 Python 3.8中, 增加了一个属性 `co_posonlyargcount`, 而Python 3.11的字节码有较大的改动)

详尽的说明参见Python官方文档 https://docs.python.org/zh-cn/3.7/library/dis.html 。

包装字节码
""""""""""""""""""""

在python中, bytecode对象的属性是不可修改的。如::

.. code-block:: python

    >>> def f():pass
    >>> f.__code__.co_code = b''
    Traceback (most recent call last): ... ...
    AttributeError: readonly attribute

为了使bytecode对象更易用, 本项目中的Code类, 用于包装 (wrap)字节码对象。

下面的示例是从doctest中摘取的::

.. code-block:: python

    >>> def f():print("Hello")
    >>> c=Code.fromfunc(f) # 或 c=Code(f.__code__)
    >>> c.co_consts
    (None, 'Hello')
    >>> c.co_consts=(None, 'Hello World!')
    >>> c.exec()
    Hello World!
    >>>
    >>> import os,pickle
    >>> temp=os.getenv('temp')
    >>> with open(os.path.join(temp,"temp.pkl"),'wb') as f:
    ...     pickle.dump(c,f)
    ... 
    >>> f=open(os.path.join(temp,"temp.pkl"),'rb')
    >>> pickle.load(f).to_func()()
    Hello World!
    >>> 
    >>> c.to_pycfile(os.path.join(temp,"temppyc.pyc"))
    >>> sys.path.append(temp)
    >>> import temppyc
    Hello World!
    >>> Code.from_pycfile(os.path.join(temp,"temppyc.pyc")).exec()
    Hello World!

版本 VERSION
============
    1.0.5 (更新: 增加了对3.10及以上版本的支持。)

	**本模块与pyobject库的关系**

	pycodeobject库最初是作者单独开发的项目。后来因pyobject库的开发，pycodeobject库被整合到了pyobject.code_模块中。现今的pyobject的Code类和本模块的Code类完全相同。

作者 AUTHOR
===========
    qfcy qq:3076711200 贴吧账号:qfcy\_

    作者CSDN主页: https://blog.csdn.net/qfcy\_
hidrotest 0.0.4
API to easily access Demeter REST API provided by Hidroconta S.A.U.

# Integrations-PythonAPI
API Python para facilitar el acceso a los endpoints de la interfaz REST de Demeter

La API permite la gestiÃ³n de grandes cantidades de datos mediante la librerÃ­a Pandas, siempre y cuando se utilice la siguiente directiva en las llamadas a los mÃ©todos:
```
# Pandas = True returns a pandas dataframe instead a json
```

La forma de usar la API es la siguiente:

- Importar los modulos deseados:
```
import demeterpy as demeter
import demeterapitypes as tp
import pandas as pd
import datetime
import endpoints
```
- Seleccionar el servidor con el cual se quiere comunicar (se puede modificar en todo momento):
```
# Set server
demeter.set_server(endpoints.Server.MAIN)
```

- Realizar el login en dicho servidor
```
# Login
demeter.login('USERNAME', 'PASSWORD')
```

Una vez seguidos los anteriores pasos, se puede realizar cualquier consulta sobre el sistema.
Algunas de ellas son:

- BÃºsqueda
```
# Search
df = demeter.search(text='SAT', element_types=[tp.Element.COUNTER, tp.Element.ANALOG_INPUT, tp.Element.RTU], status=tp.Status.ENABLED, pandas=True)
print(df)
```

- ObtenciÃ³n de historicos
```
# Get historics
df = demeter.get_historics(start_date=datetime.datetime.now(), end_date=datetime.datetime.now(), element_ids=[1000], subtype=tp.AnalogInputHist.subtype, subcode=[tp.AnalogInputHist.subcode], pandas=True)
print(df)
```

- ObtenciÃ³n de elementos
```
# Get
df = demeter.get_rtus(element_id=17512, pandas=True)
print(df)
```
La API define tambiÃ©n una excepciÃ³n especial cuando la llamada al endpoint de Demeter no devuelve el resultado esperado.
La excepciÃ³n de denomina "DemeterStatusCodeException" y contiene el cÃ³digo de error HTTP.
```
# Exception treatment
try:
    df = demeter.get_rtus(element_id=17512, pandas=True)
except demeter.DemeterStatusCodeException as status_code:
    print('Error {}'.format(status_code))
```
- Por Ãºltimo, se deberÃ­a hacer un logout en el servidor
```
demeter.logout()
```
py-timer 1.2.4
A Python timer module, containing class Timer() and decorator function timer(), as well as some useful functions that can be used for performance analysis.一个Python计时器模块, 其中包含Timer()类和timer()装饰器, 以及一些相关的有用函数, 可用于程序性能分析。
Keywords: timer, performance, analysis, 计时器, 性能

**警告: 由于本模块的名称timer和pywin32库中的timer模块名称冲突，本模块已弃用和停止更新，请安装作者最新版本的timer-tool模块（https://pypi.org/project/timer-tool/）。**

**Warning: Due to a naming conflict with the timer module in the pywin32 library, this module has been deprecated and will no longer be maintained. Please install the author's latest version of module timer-tool (https://pypi.org/project/timer-tool/).**

模块名称 MODULE NAME
====================

::

    timer

简介 DESCRIPTION
================

::

    A Python timer module, containing class Timer() and decorator function timer(), 
    as well as some useful functions that can be used for performance analysis.
    一个Python计时器模块, 其中包含Timer()类和timer()装饰器, 以及一些相关的有用函数, 可用于程序性能分析。

包含的函数和类 Functions & Classes:
===================================

类:

class Timer
"""""""""""
    一个计时器类
    
    start()
        开始计时。此方法在Timer类初始化时会被自动调用。
    
    gettime()
        获取从计时开始到现在的时间。
    
    printtime(fmt_str="用时:{:.8f}秒")
        打印出从计时开始到现在的时间, 也就是获取的值。

函数: 

timer(msg=None, file=sys.stdout, flush=False)::

    一个装饰器, 为某个函数计时 (比使用Timer类更快、更简单)。
    用法:@timer(msg="用时:{time}秒")
    def func(args):
        print("Hello World!")
    
    #或:
    @timer
    def func(args):
        print("Hello World!")

示例代码 EXAMPLES
=================

示例1:

.. code-block:: python

    import timer
    t=timer.Timer() #初始化Timer对象
    do_something()
    t.printtime() #输出执行do_something()所用时间 (也可使用t.gettime()获取所用时间)

示例2:

.. code-block:: python

    #退出with语句时自动打印出所用时间。
    import timer
    with timer.Timer(): #在这里开始计时
        do_something()

示例3:

.. code-block:: python

    # 为某个函数计时
    from timer import timer
    @timer
    def func():
        print("Hello World!")

示例4:

.. code-block:: python

    # 程序精确地延迟一段时间
    from time import sleep
    from timer import sleep as sleep2
    sleep(0.0001)
    sleep2(0.0001)
    # 经测试表明, time模块的sleep()函数与本模块的函数相比, 有明显的延迟

版本 VERSION
============

    1.2.4

    **警告: 由于本模块的名称timer和pywin32库中的timer模块名称冲突，本模块已弃用和停止更新，请安装作者最新版本的timer-tool模块（https://pypi.org/project/timer-tool/）。**

作者 AUTHOR
===========

    七分诚意 qq:3076711200

    作者CSDN主页: https://blog.csdn.net/qfcy\_
pypeakify 1.0.1
General purpose peak deconvolution package for Python.
Requires Python: >=3.6

# PyPeakify

PyPeakify is a [Python](https://python.org) package that provides a simple way to perform peak deconvolutions of various spectra.

## Installation

PyPeakify can be installed using [pip](https://pip.pypa.io/en/stable/):

```bash
pip install pypeakify
```

Alternatively, PyPeakify is available on [GitHub](TODO) and can be installed by cloning the repository and running the following command:

```bash
python setup.py sdist
pip install dist/pypeakify-{VERSION}.tar.gz
```

where `{VERSION}` is the version number of the package.

## Usage

See the [usage guide](usage.md) for more information on how to use PyPeakify.

## License

PyPeakify is licensed under the [GPL-3.0](https://github.com/mscloudlab/pypeakify?tab=GPL-3.0-1-ov-file) license.

## Usage in Literature

PyPeakify (or its predecessor, ylftir), has been used in the following publications:

- [Skin repair and infection control in diabetic, obese mice using bioactive laser-activated sealants](https://doi.org/10.1016/j.biomaterials.2024.122668)
hidroconta-demeter 13
API to easily access Demeter REST API provided by Hidroconta S.A.U.

# Integrations-PythonAPI
API Python para facilitar el acceso a los endpoints de la interfaz REST de Demeter

La API permite la gestiÃ³n de grandes cantidades de datos mediante la librerÃ­a Pandas, siempre y cuando se utilice la siguiente directiva en las llamadas a los mÃ©todos:
```
# Pandas = True returns a pandas dataframe instead a json
```

La forma de usar la API es la siguiente:

- Importar los modulos deseados:
```
import demeterpy as demeter
import demeterapitypes as tp
import pandas as pd
import datetime
import endpoints
```
- Seleccionar el servidor con el cual se quiere comunicar (se puede modificar en todo momento):
```
# Set server
demeter.set_server(endpoints.Server.MAIN)
```

- Realizar el login en dicho servidor
```
# Login
demeter.login('USERNAME', 'PASSWORD')
```

Una vez seguidos los anteriores pasos, se puede realizar cualquier consulta sobre el sistema.
Algunas de ellas son:

- BÃºsqueda
```
# Search
df = demeter.search(text='SAT', element_types=[tp.Element.COUNTER, tp.Element.ANALOG_INPUT, tp.Element.RTU], status=tp.Status.ENABLED, pandas=True)
print(df)
```

- ObtenciÃ³n de historicos
```
# Get historics
df = demeter.get_historics(start_date=datetime.datetime.now(), end_date=datetime.datetime.now(), element_ids=[1000], subtype=tp.AnalogInputHist.subtype, subcode=[tp.AnalogInputHist.subcode], pandas=True)
print(df)
```

- ObtenciÃ³n de elementos
```
# Get
df = demeter.get_rtus(element_id=17512, pandas=True)
print(df)
```
La API define tambiÃ©n una excepciÃ³n especial cuando la llamada al endpoint de Demeter no devuelve el resultado esperado.
La excepciÃ³n de denomina "DemeterStatusCodeException" y contiene el cÃ³digo de error HTTP.
```
# Exception treatment
try:
    df = demeter.get_rtus(element_id=17512, pandas=True)
except demeter.DemeterStatusCodeException as status_code:
    print('Error {}'.format(status_code))
```
- Por Ãºltimo, se deberÃ­a hacer un logout en el servidor
```
demeter.logout()
```
modi-helper 0.0.1a4
A set of scripts and tools to help configure a MODI environment.

===================
modi-helper-scripts
===================

.. image:: https://readthedocs.org/projects/modi-helper-scripts/badge/?version=latest
    :target: https://modi-helper-scripts.readthedocs.io/en/latest/?badge=latest
    :alt: Documentation Status

A set of helper scripts that can be used on MODI to setup environemnts and execute jobs.
maestro2charmmgui 0.1.6
PDB Format transformation from Maestro to CHARMM-GUI. This can make the CHARMM-GUI recognise the original orientation of the hydrogen atoms generated by Maestro.
Requires Python: <4.0,>=3.8

# Maestro2CharmmGUI
PDB Format transformation from Maestro to CHARMM-GUI. This can make the CHARMM-GUI recognise the original orientation of the hydrogen atoms generated by Maestro.

## Get started
``` bash
# install by pypi
pip install maestro2charmmgui

# install by poetry
poetry add maestro2charmmgui
```

```python
from maestro2charmmgui.rename import transform_with_resname

# rename the atoms by using a residue-based corresponding dictionary with a single function
input = "path/to/pdbfile.pdb"
output = "path/to/pdbfile_charmm.pdb"

transform_with_resname(input, output)

```
For further usage, see the [jupyter notebook](https://github.com/fornililab/Maestro2CharmmGUI/rename_Hs.ipynb) for renaming the hydrogens defined in Maestro into CHARMM's definition. 

## Change log
### 0.1.6
* fix bugs in `rename.py`: `transform_self_defined_dict`. Use resname to find the key for self defined dictionary.

### 0.1.5
* addional hydrogen at terminal nitrogen renaming (H -> HT3)
* change the order of the conditions of universal modifications of the hydrogen and the termini atoms' modification

## Developer note
Check whether it works:

```bash
poetry run pytest

# 2 passed, 1 warnining
```
mypypisearch 1.3.6
Replacement of temporarily deprecated pip search command
Requires Python: >=3.8

# PyPiSearch
[![Latest Release](https://img.shields.io/github/v/release/shidenko97/pypisearch)](https://github.com/shidenko97/pypisearch/releases/latest)
[![Downloads](https://pepy.tech/badge/pypisearch)](https://pepy.tech/project/pypisearch)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![License](https://img.shields.io/github/license/shidenko97/pypisearch)](https://github.com/shidenko97/pypisearch/blob/master/LICENSE)
A fork of https://github.com/shidenko97/pypisearch

One more replacement of temporarily deprecated pip search command implemented on regular expressions and uses [pypi site](https://pypi.org/) search line.
You are able to query multiple pages providing range to page argument (e.g. 1-5).

## Install and run
- Clone this repo and run `python pypisearch <query>`
- Install it by pip `pip install pypisearch` and run `python -m pypisearch <query>`

### This fork provides `pypisearch` as a shell command

- Clone this repo, cd inside and run `pip install .`
- Run from anywhere `pypisearch <query>`.