| Name | nemwriter JSON |
| Version |
0.4.6
JSON |
| download |
| home_page | None |
| Summary | nemwriter |
| upload_time | 2023-12-14 23:37:34 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | None |
| keywords |
energy
nem12
nem13
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
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|
# nem-writer
[](https://badge.fury.io/py/nemwriter) [](https://travis-ci.org/aguinane/nem-writer) [](https://coveralls.io/github/aguinane/nem-writer?branch=master)
Write meter readings to AEMO NEM12 (interval metering data) and NEM13 (accumulated metering data) data files
## Accumulated Data (NEM13)
```python
from datetime import datetime
from nemwriter import NEM13
m = NEM13(to_participant='123')
ch = m.add_reading(nmi='123',
nmi_configuration='E1B1B2',
register_id='1',
nmi_suffix='E1',
previous_read=412,
previous_read_date=datetime(2017,1,1),
previous_quality_method='A',
current_read=512,
current_read_date=datetime(2017,2,1),
current_quality_method='A',
quantity=100,
uom='kWh'
)
output = m.output_csv(file_path='output.csv')
```
Will output:
```
100,NEM13,201701010101,,123
250,123,E1B1B2,1,E1,,,E,412,201701010000,A,,,512,201702010000,A,,,100,kWh,,,
900
```
## Interval Data (NEM12)
```python
from datetime import datetime
from nemwriter import NEM12
m = NEM12(to_participant='123')
readings = [
# read end, read value, quality method, event code, event desc
[datetime(2004, 4, 18, 0, 30), 10.1, 'A', 79, 'Power Outage Alarm'],
[datetime(2004, 4, 18, 1, 0), 11.2, 'A'],
[datetime(2004, 4, 18, 1, 30), 12.3, 'A'],
[datetime(2004, 4, 18, 2, 0), 13.4, 'A'],
]
ch = m.add_readings(nmi='123',
nmi_configuration='E1B1B2',
nmi_suffix='E1', uom='kWh',
readings=readings)
output = m.output_csv(file_path='output.csv')
```
Will output:
```
100,NEM12,201701010101,,123
200,123,E1B1B2,,E1,,,kWh,30,
300,20040418,10.1,11.2,12.3,13.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,V,,,,
400,1,1,A,79,Power Outage Alarm
400,2,48,A,,
900
```
Alternatively, save as a compressed csv in a zip file.
```python
output = m.output_zip(file_path='output.zip')
```
### From Pandas DataFrame
If you create a pandas DataFrame, for example:
```python
num_intervals = 288
index = [datetime(2004, 4, 1) + timedelta(minutes=5*x) for x in range(1,num_intervals+1)]
e1 = [randrange(1,10) for x in range(1,num_intervals+1)]
e2 = [randrange(1,5) for x in range(1,num_intervals+1)]
s1 = pd.Series(data=e1, index=index, name="E1")
s2 = pd.Series(data=e2, index=index, name="E2")
df=pd.concat([s1,s2],axis=1)
print(df)
```
```
E1 E2
2004-04-01 00:05:00 2 3
2004-04-01 00:10:00 8 3
2004-04-01 00:15:00 7 2
2004-04-01 00:20:00 4 3
2004-04-01 00:25:00 3 4
... .. ..
2004-04-01 23:40:00 9 2
2004-04-01 23:45:00 1 1
2004-04-01 23:50:00 6 2
2004-04-01 23:55:00 7 1
2004-04-01 00:00:00 4 2
```
You can easily output the dataframe to a NEM12 file:
```python
m = NEM12(to_participant='123')
m.add_dataframe(nmi='123', interval=5, df=df, uoms={'E1': 'kWh', 'E2': 'kWh'})
output = m.output_csv(file_path='output.csv')
```
If your DataFrame has a `Quality` and `EventDesc` column, they will also be handled appropriately.
Raw data
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"description": "# nem-writer\n\n[](https://badge.fury.io/py/nemwriter) [](https://travis-ci.org/aguinane/nem-writer) [](https://coveralls.io/github/aguinane/nem-writer?branch=master)\n\nWrite meter readings to AEMO NEM12 (interval metering data) and NEM13 (accumulated metering data) data files\n\n## Accumulated Data (NEM13)\n\n```python\nfrom datetime import datetime\nfrom nemwriter import NEM13\n\nm = NEM13(to_participant='123')\nch = m.add_reading(nmi='123',\n nmi_configuration='E1B1B2',\n register_id='1',\n nmi_suffix='E1',\n previous_read=412,\n previous_read_date=datetime(2017,1,1),\n previous_quality_method='A',\n current_read=512,\n current_read_date=datetime(2017,2,1),\n current_quality_method='A',\n quantity=100,\n uom='kWh'\n )\noutput = m.output_csv(file_path='output.csv')\n```\n\nWill output:\n```\n100,NEM13,201701010101,,123\n250,123,E1B1B2,1,E1,,,E,412,201701010000,A,,,512,201702010000,A,,,100,kWh,,,\n900\n```\n\n## Interval Data (NEM12)\n\n```python\nfrom datetime import datetime\nfrom nemwriter import NEM12\n\nm = NEM12(to_participant='123')\nreadings = [\n # read end, read value, quality method, event code, event desc\n [datetime(2004, 4, 18, 0, 30), 10.1, 'A', 79, 'Power Outage Alarm'],\n [datetime(2004, 4, 18, 1, 0), 11.2, 'A'],\n [datetime(2004, 4, 18, 1, 30), 12.3, 'A'],\n [datetime(2004, 4, 18, 2, 0), 13.4, 'A'],\n]\n\nch = m.add_readings(nmi='123',\n nmi_configuration='E1B1B2',\n nmi_suffix='E1', uom='kWh',\n readings=readings)\noutput = m.output_csv(file_path='output.csv')\n```\n\nWill output:\n```\n100,NEM12,201701010101,,123\n200,123,E1B1B2,,E1,,,kWh,30,\n300,20040418,10.1,11.2,12.3,13.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,V,,,,\n400,1,1,A,79,Power Outage Alarm\n400,2,48,A,,\n900\n\n```\n\nAlternatively, save as a compressed csv in a zip file.\n```python\noutput = m.output_zip(file_path='output.zip')\n```\n\n### From Pandas DataFrame\n\nIf you create a pandas DataFrame, for example:\n\n```python\nnum_intervals = 288\nindex = [datetime(2004, 4, 1) + timedelta(minutes=5*x) for x in range(1,num_intervals+1)]\ne1 = [randrange(1,10) for x in range(1,num_intervals+1)]\ne2 = [randrange(1,5) for x in range(1,num_intervals+1)]\ns1 = pd.Series(data=e1, index=index, name=\"E1\")\ns2 = pd.Series(data=e2, index=index, name=\"E2\")\ndf=pd.concat([s1,s2],axis=1)\nprint(df)\n```\n\n```\n E1 E2\n2004-04-01 00:05:00 2 3\n2004-04-01 00:10:00 8 3\n2004-04-01 00:15:00 7 2\n2004-04-01 00:20:00 4 3\n2004-04-01 00:25:00 3 4\n... .. ..\n2004-04-01 23:40:00 9 2\n2004-04-01 23:45:00 1 1\n2004-04-01 23:50:00 6 2\n2004-04-01 23:55:00 7 1\n2004-04-01 00:00:00 4 2\n```\n\nYou can easily output the dataframe to a NEM12 file:\n```python\nm = NEM12(to_participant='123')\nm.add_dataframe(nmi='123', interval=5, df=df, uoms={'E1': 'kWh', 'E2': 'kWh'})\noutput = m.output_csv(file_path='output.csv')\n```\n\nIf your DataFrame has a `Quality` and `EventDesc` column, they will also be handled appropriately.\n",
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