On 11/01/2018 12:20 PM, Tom Tanner wrote:
Hey everyone,
I have a bunch of text files that each have a bunch of columns in
common. I plan to import these files into PostgreSQL tables. The
website user will be able to send a GET request to query a table and
get back data from it. Since most of the tables will have a bunch of
columns in common, how should I structure them in my `models.py`?
I think you want a core model with most of the common fields and meta
abstract = True ...
class CoreFields(models.Model):
...
class Meta:
abstract = True
Then a bunch of other tables set up with fields which are not in
CoreFields ...
class DataSetX(CoreFields):
...
You can also move any methods in common into CoreFields
hth
Mike
Here's a couple examples of tab-delimited text files I'll import.
|
NAME S1903_C02_001E state county tract State-County-Tract-ID
CensusTract201,AutaugaCounty,Alabama660000100102010001001020100
CensusTract202,AutaugaCounty,Alabama411070100102020001001020200
CensusTract203,AutaugaCounty,Alabama512500100102030001001020300
|
and
|
NAME S1903_C02_001F S1903_C02_001G state county tract
State-County-Tract-ID
CensusTract201,AutaugaCounty,Alabama6600040400100102010001001020100
CensusTract202,AutaugaCounty,Alabama411071928370100102020001001020200
CensusTract203,AutaugaCounty,Alabama51250394820100102030001001020300
|
As you can see, they have several columns in common. I wouldn't want
to repeat myself in `models.py` by listing the same columns over and over.
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