Metadata-Version: 2.1
Name: energy-trading-api
Version: 0.0.30
Summary: API Wrappers for the Energy Markets
Home-page: https://github.com/jericmac/energy-trading-api-wrappers
Author: jericmac
Author-email: 
License: UNKNOWN
Description: # Energy Trading API Wrappers
        This package aims to build Pandas-based API wrappers for Energy Markets Data coming from publicly available sources.
        The results are returned in the Pandas dataFrame format unless specified otherwise.
        
        > **disclaimer** While readily useable, this API library is under constant in development. The reliability of the data from  the API list depends on the sources.
         Enjoy!
        
        Supported APIs:
        > **Australia**
        - [Western Australia Gas Bulletin Board](https://gbbwa.aemo.com.au/)
        - [ACCC LNG Netback Price Index](https://www.accc.gov.au/regulated-infrastructure/energy/gas-inquiry-2017-2020/lng-netback-price-series)
        - [Australian REC Register](https://www.rec-registry.gov.au/)
        - [AEMC Gas Scheme Register (developing)](https://www.aemc.gov.au/energy-system/gas/gas-scheme-register)
        - [Western Australia Wholesale Electricity Market (WEM)](http://data.wa.aemo.com.au/#)
        - [Bureau of Meteorology](http://www.bom.gov.au/)
        
        > **Singapore**
        - [Singapore National Electricity Market (NEMS)](https://www.emcsg.com/)
        
        
        > **Japan**
        - [Japan Electric Power Exchange](http://www.jepx.org/)
        - [Kyushu Electric Power Company - H/5M Demand and Forecasted Demand](http://www.kyuden.co.jp)
        - [Chubu Electric Power Company - Hourly Historical and Current Demand](http://denki-yoho.chuden.jp)
        - [Tokyo Electric Power Company - Hourly Historical and Current Demand](http://tepco.co.jp)
        > **Global**
        - [U.S. Energy Information Administration Open Data](https://www.eia.gov/opendata/)
        
        ## Installation
        * Python 3.6 or 3.7
        
        To install,  use `pip` :
        ```bash
        $ pip install energy-trading-api
        ```
        
        ### Requirements
        * Python 3.7
        
        
        ## Usage
        ### AUSTRALIA
        ##### Western Australian Wholesale Electricity Market (WEM)
        ```python
        from energy_trading_api import australiaWEM 
        df = australiaWEM.loadForecast()
        df1 = australiaWEM.demandSideProgrammePrices(year="2019")
        
        ```   
        [WEM Data API Documentation](http://data.wa.aemo.com.au/#)
        
        ##### ACCC LNG Netback Price Series
        ```python
        from energy_trading_api import australiaLNG
        netback,netforward,merged = australiaLNG.acccNetbackPrice()
        print(netback.head())
        ```   
        
        [ACCC LNG Netback Price Series Documentation](https://www.accc.gov.au/system/files/Guide%20to%20the%20LNG%20netback%20price%20series%20-%20October%202018.pdf)
        
        
        ##### Australian REC Register
        ```python
        from energy_trading_api import australiaREC 
        df = australiaREC.recDay("2019-01-01")
        
        ```   
        [REC Registry API Documentation](http://www.cleanenergyregulator.gov.au/DocumentAssets/Pages/REC-Registry-API-specifications.aspx)
        
        
        ##### AEMC Gas Scheme Register
        ```python
        from energy_trading_api import australiaNG 
        df = australiaNG.pipelineRegister()
        df1 = australiaNG.pipelineRegisterSearch(state="NSW",operator="APA Group")
        
        ```   
        [AEMC Gas Scheme Register Website](https://www.aemc.gov.au/energy-system/gas/gas-scheme-register)
        
        ##### Western Australia Gas Bulletin Board
        ```python
        from energy_trading_api import wagbb 
        wagbb.capacityOutlook()
        ```    
        [WAGBB API Documentation](https://gbbwa.aemo.com.au/api/v1/document/1f2bc41e-3e42-41eb-86f7-4a10d2d6e4bc/content)
        
        ##### Australian Bureau of Meteorology
        Retrieves BOM records into a pandas dataframe, given Product and location.
        
        For instance, Bankstown time series data has a product code of IDN60901.94765.
        
        To return Air Temp, Apparent Temp Rel Humidity, Cloud data in a pandas df, simply do:
        
        ```python
        from energy_trading_api import australiaBOM 
        df1 = australiaBOM.airTemp('IDN60901.94765')
        df2 = australiaBOM.apparentTemp('IDN60901.94765')
        df2 = australiaBOM.relativeHumidity('IDN60901.94765')
        df3 = australiaBOM.cloud('IDN60901.94765')
        
        ```    
        
        You can also access the entire dataset by doing:
        
        ```python
        from energy_trading_api import australiaBOM 
        df, df_header = australiaBOM.__call_api_BOM('IDN60901.94765')
        # e.g. dew point:
        print(df['dewpt'].to_string())
        ```    
        
        
        [Bankstown BOM Data Example](http://www.bom.gov.au/products/IDN60901/IDN60901.94765.shtml)
        
        
        
         ### SINGAPORE
        ##### Singapore National Electricity Market (NEMS)
        
        ```python
        from energy_trading_api import singaporeNEMS 
        df = singaporeNEMS.singaporeUSEP(date="2019-01-01")
        ```    
        
        ### JAPAN
        ##### Japan Electric Power Exchange
        ```python
        from energy_trading_api import jepx 
        df = jepx.spotLatest()
        df = jepx.spotLatest("20190101")
        ```  
        
        ##### Kyushu Electric Power Company (Kyuden)
        ```python
        from energy_trading_api import japanElectricity as je 
        df = je.kyushuElectricdemandJapanese()
        df1 = je.kyushuElectricdemandJapanese(day="20190101")
        ```  
         ##### Chubu Electric Power Company (Chuden)
        ```python
        from energy_trading_api import japanElectricity as je 
        df = je.chubuElectricdemandJapanese()
        df1 = je.chubuElectricDemandJapaneseRange(begtime="20190101",endtime="20190101")
        ```  
        
         ##### Tokyo Electric Power Company (TEPCO)
        ```python
        from energy_trading_api import japanElectricity as je 
        df = je.tepcoElectricDemandHistoricalJapanese("2018")
        df1 = je.tepcoElectricDemandCurrentJapanese()
        ```  
        
        
        ### GLOBAL
        ##### U.S. Energy Information Administration
        ```python
        from energy_trading_api import eia_api 
        df = eia_api.ngAustraliaProduction("<YOUR-API-KEY-HERE>")
        ```    
        [EIA-Python Documentation](https://github.com/mra1385/EIA-python)
        [EIA API Documentation](https://www.eia.gov/opendata/commands.php)
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
