pip / easy_install

pip install speedtest_reader

or

easy_install speedtest_reader

Github

pip install git+https://github.com/shuntingyard/speedtest_reader.git

or

git clone https://github.com/shuntingyard/speedtest_reader.git
cd speedtest_reader
python setup.py install

plotly

import plotly
import plotly.graph_objs as go
from speedtest_reader import format_timestamps, Reader, util

sensor1 = Reader("~/speedtest.csv")


@util.append_tslocal()
def slice_s1(**kwargs):
    start, end = format_timestamps(**kwargs)
    return sensor1.copy_df(start, end)


# minimal line- and scatterplot example
df = slice_s1()
graph = dict(
    data=[
        go.Scatter(
            x=df["tslocal"], y=df["Download"], mode="lines", connectgaps=False
        ),
        go.Scatter(x=df["tslocal"], y=df["Upload"], mode="markers"),
    ]
)
plotly.offline.plot(graph)

seaborn

import matplotlib.pyplot as plt
import seaborn as sns
from speedtest_reader import format_timestamps, Reader, util

sensor1 = Reader("~/speedtest.csv")


@util.to_Mbit
@util.append_mpldate(colname="date2num")
def slice_s1(**kwargs):
    start, end = format_timestamps(**kwargs)
    return sensor1.copy_df(start, end)


# minimal scatterplot example
ts = slice_s1()["date2num"]
dl = slice_s1()["Download"]
_, ax = plt.subplots()
sns.scatterplot(ts, dl)
ax.xaxis_date()
plt.show()

timezone config

from speedtest_reader import format_timestamps, Reader, util

sensor1 = Reader("~/speedtest.csv")


@util.append_tslocal(tz="EST")  # zone for local timestamp to append
def slice_EST(**kwargs):
    kwargs["tz"] = "EST"  # zone to use for slicing
    start, end = format_timestamps(**kwargs)
    return sensor1.copy_df(start, end)


# use local timezone (selected by module 'tzlocal')
@util.append_tslocal()
def slice_local(**kwargs):
    start, end = format_timestamps(**kwargs)
    return sensor1.copy_df(start, end)


# test configured- and local timezone setup
print(slice_EST(start="yesterday"))
print(slice_local(start="yesterday"))

Version 0.0.4

• Complete API redesign