Metadata-Version: 2.1
Name: pyarchappl
Version: 0.10.2
Summary: Python interface to Archiver Appliance
Home-page: https://github.com/archman/pyarchappl
Author: Tong Zhang
Author-email: zhangt@frib.msu.edu
License: GPL3+
Keywords: Archiver EPICS CA PVA
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: tzlocal
Requires-Dist: requests
Requires-Dist: simplejson
Requires-Dist: tqdm
Requires-Dist: tables
Requires-Dist: protobuf (==3.6.1)

# PyArchAppl

Python client for [Archiver Appliance](https://slacmshankar.github.io/epicsarchiver_docs/index.html).

# Installation

`pip install pyarchappl [--upgrade]`

# User Guide

Command line tool ``pyarchappl-get`` is the best tool that could be used for
data retrieval, read the usage help message by `-h` option.

# Development

## [Optional] Set up Archiver Appliance testing environment

## Data Retrieval Client
```Python
from archappl.client import ArchiverDataClient
import matplotlib.pyplot as plt


plt.style.use('ggplot')

client = ArchiverDataClient()
client.url = 'http://127.0.0.1:17665'  # default url, optional.

pv = 'TST:gaussianNoise'
data = client.get_data(pv)

data.plot()
plt.show()
```
![](tests/data_plot1.png?raw=true)

### Data (PV) Management Client
```Python
from archappl.client import ArchiverMgmtClient


client = ArchiverMgmtClient()
client.url = 'http://127.0.0.1:17665'

all_pvs = client.get_all_pvs()
print(all_pvs)
# [u'TST:fakeGaussianNoise', u'TST:gaussianNoise', u'TST:uniformNoise']
```


