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Project description
# openergy
Client api to interact with openergy platform
## Suggested conda env
<pre>
openpyxl>=2.4.7,<3.0.0
requests>=2.14.2,<3.0.0
nose>=1.3.7,<2.0.0
pandas>=0.20.1,<0.21.0
pytables>=3.2.0,<4.0
</pre>
## Url endpoints philosophy
Mainly inspired by [rest_framework simple router actions](http://www.django-rest-framework.org/api-guide/routers/#simplerouter).
## Examples
<pre>
from openergy import set_client, select_series
client = set_client("login", "password", "host")
</pre>
### select series
<pre>
# returns a pandas Series object
se = select_series("993e2f73-20ef-4f60-8e06-d81d6cefbc9a")
</pre>
### create local database
<pre>
from openergy import LocalDatabase
db = LocalDatabase(db_dir_path)
# download one series
# (local_se is not a pandas series but a local database series object)
local_se = db.get_local_series(
"my_project",
"analysis", # importer, cleaner or analysis
"my_analysis",
"se1")
local_se.download()
# se1 is a pandas series
se1 = local_se.data
# download multiple series
db.download_all_series(
my_project,
generator_model=analysis, # importer, cleaner or analysis
generator_name=my_analysis)
# 1. local se1 will be deleted and downloaded again
# 2. all project will be downloaded if no generator has been specified
# work with series
se1 = db.get_local_series(
"my_project",
"analysis",
"my_analysis",
"se1").data
</pre>
Client api to interact with openergy platform
## Suggested conda env
<pre>
openpyxl>=2.4.7,<3.0.0
requests>=2.14.2,<3.0.0
nose>=1.3.7,<2.0.0
pandas>=0.20.1,<0.21.0
pytables>=3.2.0,<4.0
</pre>
## Url endpoints philosophy
Mainly inspired by [rest_framework simple router actions](http://www.django-rest-framework.org/api-guide/routers/#simplerouter).
## Examples
<pre>
from openergy import set_client, select_series
client = set_client("login", "password", "host")
</pre>
### select series
<pre>
# returns a pandas Series object
se = select_series("993e2f73-20ef-4f60-8e06-d81d6cefbc9a")
</pre>
### create local database
<pre>
from openergy import LocalDatabase
db = LocalDatabase(db_dir_path)
# download one series
# (local_se is not a pandas series but a local database series object)
local_se = db.get_local_series(
"my_project",
"analysis", # importer, cleaner or analysis
"my_analysis",
"se1")
local_se.download()
# se1 is a pandas series
se1 = local_se.data
# download multiple series
db.download_all_series(
my_project,
generator_model=analysis, # importer, cleaner or analysis
generator_name=my_analysis)
# 1. local se1 will be deleted and downloaded again
# 2. all project will be downloaded if no generator has been specified
# work with series
se1 = db.get_local_series(
"my_project",
"analysis",
"my_analysis",
"se1").data
</pre>
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