Metadata-Version: 2.1
Name: cimiss-python
Version: 0.1.3
Summary: A CIMISS client for python
Home-page: https://github.com/So0ni/cimiss-python
Author: Sonic Young
Author-email: 173976914@qq.com
License: GPL Licence
Description: # cimiss-python
         CIMISS client for Python 3
        
        ## Installation
        
        > Python >= 3.6
        
        ### Ubuntu
        
        ```bash
        sudo apt install -y build-essential libssl-dev libbz2-dev
        pip install cimiss-python
        ```
        
        
        ### Windows
        
        ```bash
        pip install cimiss-python
        ```
        
        
        ### CentOS
        
        > 未经验证
        
        ```bash
        yum groupinstall "Development Tools"
        yum -y install zlib-devel bzip2-devel openssl-devel
        pip install cimiss-python
        ```
        
        ## Usage
        
        > CIMISS-MUSIC仅为内网用户提供服务，且需要拥有相应数据访问权限的账号。
        
        ```python
        import cimiss
        
        # host 不带http前缀，通常为纯ip地址
        client = cimiss.Query(user_id='myuserid', password='mypasswd', host='myhost')
        
        
        # callAPI_to_array2D
        # array_2d(interface_id: str, params: Dict[str, str]) -> pd.DataFrame
        resp_array_2d = client.array_2d(interface_id="getSurfEleByTime",
                                        params={'dataCode': "SURF_CHN_MUL_HOR",
                                                'elements': "Station_ID_C,PRE_1h,PRS,RHU,VIS,WIN_S_Avg_2mi,WIN_D_Avg_2mi,Q_PRS",
                                                'times': "20181224000000",
                                                'orderby': "Station_ID_C:ASC",
                                                'limitCnt': "10"}
                                        )
        # pandas
        # https://pandas.pydata.org/pandas-docs/stable/
        
        
        # callAPI_to_gridArray2D
        # grid_array_2d(interface_id: str, params: Dict[str, str]) -> xr.DataArray
        resp_grid = client.grid_array_2d(interface_id="	getNafpEleGridByTimeAndLevelAndValidtime",
                                         params={'dataCode': 'NAFP_FOR_FTM_HIGH_EC_ANEA',
                                                 'fcstEle': 'TEM',
                                                 'time': '20191206000000',
                                                 'fcstLevel': '1000',
                                                 'validTime': '0'
                                                 }
                                         )
        # xarray
        # http://xarray.pydata.org/en/stable/
        
        
        # callAPI_to_fileList
        # def file_list(interface_id: str, params: Dict[str, str]) -> pd.DataFrame
        
        
        # callAPI_to_saveAsFile
        # save_file(interface_id: str, params: Dict[str, str], data_format: str, file_name: str) -> str
        
        
        # callAPI_to_downFile
        # down_file(interface_id: str, params: Dict[str, str], file_dir: str) -> List[str]#
        
        ```
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: License :: OSI Approved :: GNU General Public License (GPL)
Classifier: Development Status :: 4 - Beta
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
