Python API for searching AFLOW database.
Project description
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# `AFLOW` Python API
Python API wrapping the AFLUX API language for AFLOW library. _Note:_ This is not an official repo of the AFLOW consortium and is not maintained by them. [API Documentation](https://rosenbrockc.github.io/aflow/).
If you use this package, please cite it:
```
@ARTICLE{2017arXiv171000813R,
author = {{Rosenbrock}, C.~W.},
title = "{A Practical Python API for Querying AFLOWLIB}",
journal = {ArXiv e-prints},
archivePrefix = "arXiv",
eprint = {1710.00813},
primaryClass = "cs.DB",
keywords = {Computer Science - Databases},
year = 2017,
month = sep,
adsurl = {http://adsabs.harvard.edu/abs/2017arXiv171000813R},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
```
## Quickstart
Install `aflow` from the python package index:
```
pip install aflow
```
Open an ipython notebook or terminal and execute the query from the paper:
```python
from aflow import *
result = search(batch_size=20
).select(K.agl_thermal_conductivity_300K
).filter(K.Egap > 6).orderby(K.agl_thermal_conductivity_300K, True)
# Now, you can just iterate over the results.
for entry in result:
print(entry.Egap)
```
`aflow` supports lazy evaluation. This means that if you didn't ask for a particular property during the initial query, you can just ask for it later and the request will happen transparently in the background.
# `AFLOW` Python API
Python API wrapping the AFLUX API language for AFLOW library. _Note:_ This is not an official repo of the AFLOW consortium and is not maintained by them. [API Documentation](https://rosenbrockc.github.io/aflow/).
If you use this package, please cite it:
```
@ARTICLE{2017arXiv171000813R,
author = {{Rosenbrock}, C.~W.},
title = "{A Practical Python API for Querying AFLOWLIB}",
journal = {ArXiv e-prints},
archivePrefix = "arXiv",
eprint = {1710.00813},
primaryClass = "cs.DB",
keywords = {Computer Science - Databases},
year = 2017,
month = sep,
adsurl = {http://adsabs.harvard.edu/abs/2017arXiv171000813R},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
```
## Quickstart
Install `aflow` from the python package index:
```
pip install aflow
```
Open an ipython notebook or terminal and execute the query from the paper:
```python
from aflow import *
result = search(batch_size=20
).select(K.agl_thermal_conductivity_300K
).filter(K.Egap > 6).orderby(K.agl_thermal_conductivity_300K, True)
# Now, you can just iterate over the results.
for entry in result:
print(entry.Egap)
```
`aflow` supports lazy evaluation. This means that if you didn't ask for a particular property during the initial query, you can just ask for it later and the request will happen transparently in the background.
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