# -*- coding: utf-8 -*-

import setuptools

# with open("README.md", "r") as fh:
#     long_description = fh.read()

long_desc = """
# pyhkconnect

香港交易所 沪港通 深港通 数据接口

## Demo

```python
>>> import pyhkconnect as hkc
>>> dp = hkc.northbound_shareholding_sh() # dataframe from pandas
>>> dp
      code                                               name   shareholding shareholding_percent
0    90000  SHANGHAI PUDONG DEVELOPMENT BANK CO., LTD. (A ...    379,430,135                1.35%
1    90004  GUANGZHOU BAIYUN INTERNATIONAL AIRPORT CO.,LTD...    282,353,856               13.64%
2    90006            DONGFENG AUTOMOBILE CO.,LTD (A #600006)      7,461,913                0.37%
3    90007  CHINA WORLD TRADE CENTER COMPANY LTD. (A #600007)     13,202,103                1.31%
4    90008                BEIJING CAPITAL CO.,LTD (A #600008)     63,689,287                1.32%
5    90009  SHANGHAI INTERNATIONAL AIRPORT CO., LTD. (A #6...    316,733,029               28.96%
6    90010  INNER MONGOLIA BAOTOU STEEL UNION CO.,LTD. (A ...    215,362,295                0.67%
7    90011      HUANENG POWER INTERNATIONAL, INC. (A #600011)     42,917,773                0.40%
8    90012       ANHUI EXPRESSWAY COMPANY LIMITED (A #600012)      6,149,168                0.52%
9    90015              HUA XIA BANK CO., LIMITED (A #600015)     83,923,960                0.65%
10   90016     CHINA MINSHENG BANKING CORP., LTD. (A #600016)    594,264,189                1.67%
..     ...                                                ...            ...                  ...
840  93979        JCHX MINING MANAGEMENT CO.,LTD. (A #603979)        191,590                0.03%
841  93986  GIGADEVICE SEMICONDUCTOR(BEIJING) INC (A #603986)        358,240                0.17%
842  93989             HUNAN AIHUA GROUP C0.,LTD. (A #603989)      5,537,526                1.41%
843  93993             CHINA MOLYBDENUM CO., LTD. (A #603993)    133,230,718                0.75%
844  93997       NINGBO JIFENG AUTO PARTS CO.,LTD (A #603997)        100,463                0.01%

[845 rows x 4 columns]
>>>
>>>json_obj=dp.to_json(orient='index') # return json data
```
"""


def read_install_requires():
    reqs = [
        'pandas >= 0.18.0',
        'requests >= 2.0.0',
        'lxml >= 3.8.0',
        'simplejson >= 3.16.0',
        'beautifulsoup4 >= 4.6.3'
    ]
    return reqs


setuptools.setup(
    name="pyhkconnect",
    version="0.0.1",
    author="<NAME>",
    author_email="<EMAIL>",
    description="香港交易所 沪港通 深港通 数据接口 HKC",
    long_description=long_desc,
    long_description_content_type="text/markdown",
    url="https://github.com/uname-yang/pyhkconnect",
    packages=setuptools.find_packages(),
    classifiers=[
        "Programming Language :: Python :: 3",
        "License :: OSI Approved :: MIT License",
        "Operating System :: OS Independent",
    ],
    keywords=('Financial Data', 'HKEX', 'HKC', '沪港通', '深港通', 'Python Api'),
    install_requires=read_install_requires(),
)

# -*- coding: utf-8 -*-

import setuptools

# with open("README.md", "r") as fh:
#     long_description = fh.read()

long_desc = """
# pyhkconnect

香港交易所 沪港通 深港通 数据接口

## Demo

```python
>>> import pyhkconnect as hkc
>>> dp = hkc.northbound_shareholding_sh() # dataframe from pandas
>>> dp
      code                                               name   shareholding shareholding_percent
0    90000  SHANGHAI PUDONG DEVELOPMENT BANK CO., LTD. (A ...    379,430,135                1.35%
1    90004  GUANGZHOU BAIYUN INTERNATIONAL AIRPORT CO.,LTD...    282,353,856               13.64%
2    90006            DONGFENG AUTOMOBILE CO.,LTD (A #600006)      7,461,913                0.37%
3    90007  CHINA WORLD TRADE CENTER COMPANY LTD. (A #600007)     13,202,103                1.31%
4    90008                BEIJING CAPITAL CO.,LTD (A #600008)     63,689,287                1.32%
5    90009  SHANGHAI INTERNATIONAL AIRPORT CO., LTD. (A #6...    316,733,029               28.96%
6    90010  INNER MONGOLIA BAOTOU STEEL UNION CO.,LTD. (A ...    215,362,295                0.67%
7    90011      HUANENG POWER INTERNATIONAL, INC. (A #600011)     42,917,773                0.40%
8    90012       ANHUI EXPRESSWAY COMPANY LIMITED (A #600012)      6,149,168                0.52%
9    90015              HUA XIA BANK CO., LIMITED (A #600015)     83,923,960                0.65%
10   90016     CHINA MINSHENG BANKING CORP., LTD. (A #600016)    594,264,189                1.67%
..     ...                                                ...            ...                  ...
840  93979        JCHX MINING MANAGEMENT CO.,LTD. (A #603979)        191,590                0.03%
841  93986  GIGADEVICE SEMICONDUCTOR(BEIJING) INC (A #603986)        358,240                0.17%
842  93989             HUNAN AIHUA GROUP C0.,LTD. (A #603989)      5,537,526                1.41%
843  93993             CHINA MOLYBDENUM CO., LTD. (A #603993)    133,230,718                0.75%
844  93997       NINGBO JIFENG AUTO PARTS CO.,LTD (A #603997)        100,463                0.01%

[845 rows x 4 columns]
>>>
>>>json_obj=dp.to_json(orient='index') # return json data
```
"""


def read_install_requires():
    reqs = [
        'pandas >= 0.18.0',
        'requests >= 2.0.0',
        'lxml >= 3.8.0',
        'simplejson >= 3.16.0',
        'beautifulsoup4 >= 4.6.3'
    ]
    return reqs


setuptools.setup(
    name="pyhkconnect",
    version="0.0.1",
    author="<NAME>",
    author_email="<EMAIL>",
    description="香港交易所 沪港通 深港通 数据接口 HKC",
    long_description=long_desc,
    long_description_content_type="text/markdown",
    url="https://github.com/uname-yang/pyhkconnect",
    packages=setuptools.find_packages(),
    classifiers=[
        "Programming Language :: Python :: 3",
        "License :: OSI Approved :: MIT License",
        "Operating System :: OS Independent",
    ],
    keywords=('Financial Data', 'HKEX', 'HKC', '沪港通', '深港通', 'Python Api'),
    install_requires=read_install_requires(),
)

# -*- coding: utf-8 -*- # with open("README.md", "r") as fh: #     long_description = fh.read() # pyhkconnect  香港交易所 沪港通 深港通 数据接口  ## Demo  ```python >>> import pyhkconnect as hkc >>> dp = hkc.northbound_shareholding_sh() # dataframe from pandas >>> dp       code                                               name   shareholding shareholding_percent 0    90000  SHANGHAI PUDONG DEVELOPMENT BANK CO., LTD. (A ...    379,430,135                1.35% 1    90004  GUANGZHOU BAIYUN INTERNATIONAL AIRPORT CO.,LTD...    282,353,856               13.64% 2    90006            DONGFENG AUTOMOBILE CO.,LTD (A #600006)      7,461,913                0.37% 3    90007  CHINA WORLD TRADE CENTER COMPANY LTD. (A #600007)     13,202,103                1.31% 4    90008                BEIJING CAPITAL CO.,LTD (A #600008)     63,689,287                1.32% 5    90009  SHANGHAI INTERNATIONAL AIRPORT CO., LTD. (A #6...    316,733,029               28.96% 6    90010  INNER MONGOLIA BAOTOU STEEL UNION CO.,LTD. (A ...    215,362,295                0.67% 7    90011      HUANENG POWER INTERNATIONAL, INC. (A #600011)     42,917,773                0.40% 8    90012       ANHUI EXPRESSWAY COMPANY LIMITED (A #600012)      6,149,168                0.52% 9    90015              HUA XIA BANK CO., LIMITED (A #600015)     83,923,960                0.65% 10   90016     CHINA MINSHENG BANKING CORP., LTD. (A #600016)    594,264,189                1.67% ..     ...                                                ...            ...                  ... 840  93979        JCHX MINING MANAGEMENT CO.,LTD. (A #603979)        191,590                0.03% 841  93986  GIGADEVICE SEMICONDUCTOR(BEIJING) INC (A #603986)        358,240                0.17% 842  93989             HUNAN AIHUA GROUP C0.,LTD. (A #603989)      5,537,526                1.41% 843  93993             CHINA MOLYBDENUM CO., LTD. (A #603993)    133,230,718                0.75% 844  93997       NINGBO JIFENG AUTO PARTS CO.,LTD (A #603997)        100,463                0.01%  [845 rows x 4 columns] >>> >>>json_obj=dp.to_json(orient='index') # return json data ```