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+/uniplot-0.10.0.tar.gz
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+%global _empty_manifest_terminate_build 0
+Name:		python-uniplot
+Version:	0.10.0
+Release:	1
+Summary:	Lightweight plotting to the terminal. 4x resolution via Unicode.
+License:	MIT
+URL:		https://pypi.org/project/uniplot/
+Source0:	https://mirrors.aliyun.com/pypi/web/packages/84/3c/e12798b1789fbba1185db59c902733e87adfe33a38c43bfc72d9cd826feb/uniplot-0.10.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-numpy
+
+%description
+# Uniplot
+[![Build Status](https://github.com/olavolav/uniplot/workflows/Unit%20Tests/badge.svg)](https://github.com/olavolav/uniplot/actions?query=workflow%3A"Unit+Tests")
+[![PyPI Version](https://badge.fury.io/py/uniplot.svg)](https://pypi.org/project/uniplot/)
+[![PyPI Downloads](https://pepy.tech/badge/uniplot)](https://pepy.tech/project/uniplot)
+
+Lightweight plotting to the terminal. 4x resolution via Unicode.
+
+![uniplot demo GIF](https://github.com/olavolav/uniplot/raw/master/resource/uniplot-demo.gif)
+
+When working with production data science code it can be handy to have plotting
+tool that does not rely on graphics dependencies or works only in a Jupyter notebook.
+
+The **use case** that this was built for is to have plots as part of your data science /
+machine learning CI pipeline - that way whenever something goes wrong, you get not only
+the error and backtrace but also plots that show what the problem was.
+
+
+## Features
+
+* Unicode drawing, so 4x the resolution (pixels) of usual ASCII plots
+* Super simple API
+* Interactive mode (pass `interactive=True`)
+* Color mode (pass `color=True`) useful in particular when plotting multiple series
+* It's fast: Plotting 1M data points takes 100ms thanks to NumPy magic
+* Only one dependency: NumPy (but you have that anyway don't you)
+
+Please note that Unicode drawing will work correctly only when using a font that
+fully supports the [Box-drawing character set](https://en.wikipedia.org/wiki/Box-drawing_character).
+Please refer to [this page for a (incomplete) list of supported fonts](https://www.fileformat.info/info/unicode/block/block_elements/fontsupport.htm).
+
+
+## Examples
+
+Note that all the examples are without color and plotting only a single series od data. For using color see the GIF example above.
+
+### Plot sine wave
+
+```python
+import math
+x = [math.sin(i/20)+i/300 for i in range(600)]
+from uniplot import plot
+plot(x, title="Sine wave")
+```
+
+Result:
+```
+                          Sine wave
+┌────────────────────────────────────────────────────────────┐
+│                                                    ▟▀▚     │
+│                                                   ▗▘ ▝▌    │
+│                                       ▗▛▜▖        ▞   ▐    │
+│                                       ▞  ▜       ▗▌    ▌   │ 2
+│                           ▟▀▙        ▗▘  ▝▌      ▐     ▜   │
+│                          ▐▘ ▝▖       ▞    ▜      ▌     ▝▌  │
+│              ▗▛▜▖        ▛   ▜      ▗▌    ▝▌    ▐▘      ▜  │
+│              ▛  ▙       ▗▘   ▝▖     ▐      ▚    ▞       ▝▌ │
+│  ▟▀▖        ▐▘  ▝▖      ▟     ▚     ▌      ▝▖  ▗▌        ▜▄│ 1
+│ ▐▘ ▐▖       ▛    ▙      ▌     ▐▖   ▗▘       ▚  ▞           │
+│ ▛   ▙      ▗▘    ▐▖    ▐       ▙   ▞        ▝▙▟▘           │
+│▐▘   ▐▖     ▐      ▌    ▛       ▐▖ ▗▘                       │
+│▞     ▌     ▌      ▐   ▗▘        ▜▄▛                        │
+│▌─────▐────▐▘───────▙──▞────────────────────────────────────│ 0
+│       ▌   ▛        ▝▙▟▘                                    │
+│       ▜  ▐▘                                                │
+│        ▙▄▛                                                 │
+└────────────────────────────────────────────────────────────┘
+         100       200       300       400       500       600
+```
+
+### Plot global temperature data
+
+Here we're using Pandas to load and prepare global temperature data from the [Our World in Data GitHub repository](https://github.com/owid/owid-datasets).
+
+First we load the data, rename a column and and filter the data:
+
+```python
+import pandas as pd
+uri = "https://github.com/owid/owid-datasets/raw/master/datasets/Global%20average%20temperature%20anomaly%20-%20Hadley%20Centre/Global%20average%20temperature%20anomaly%20-%20Hadley%20Centre.csv"
+data = pd.read_csv(uri)
+data = data.rename(columns={"Global average temperature anomaly (Hadley Centre)": "Global"})
+data = data[data.Entity == "median"]
+```
+
+Then we can plot it:
+
+```python
+from uniplot import plot
+plot(xs=data.Year, ys=data.Global, lines=True, title="Global normalized land-sea temperature anomaly", y_unit=" °C")
+```
+
+Result:
+```
+        Global normalized land-sea temperature anomaly
+┌────────────────────────────────────────────────────────────┐
+│                                                          ▞▀│
+│                                                         ▐  │
+│                                                         ▐  │
+│                                                     ▗   ▌  │ 0.6 °C
+│                                           ▙  ▗▄ ▛▄▖▗▘▌ ▞   │
+│                                          ▗▜  ▌ ▜  ▚▞ ▚▞    │
+│                                          ▐▝▖▐      ▘       │
+│                                    ▗   ▗ ▌ ▙▌              │ 0.3 °C
+│                                    ▛▖  ▞▙▘  ▘              │
+│                              ▖  ▗▄▗▘▐ ▐▘▜                  │
+│                            ▟ █  ▞ ▜ ▝▄▘                    │
+│   ▗▚   ▗    ▖       ▗   ▖▗▞ █▐  ▌    ▘                     │
+│▁▁▁▞▐▁▁▗▘▜▗▀▀▌▁▁▁▁▙▁▁▟▁▁▁▙▐▁▁▜▁▌▞▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁│ 0 °C
+│▚ ▐ ▝▖ ▐  ▛  ▌ ▗▄▐ ▌▗▘▌ ▐▝▌    ▝▘                           │
+│ ▌▌  ▌ ▞     ▐▗▘ ▛ ▐▞ ▌ ▐                                   │
+│ ▝   ▝▖▌     ▐▞    ▝▌ ▚▜▐                                   │
+│      ▗▌     ▝        ▝ ▌                                   │
+└────────────────────────────────────────────────────────────┘
+1,950    1,960    1,970   1,980    1,990    2,000   2,010
+```
+
+
+## Parameters
+
+The `plot` function accepts a number of parameters, all listed below. Note that only
+`ys` is required, all others are optional.
+
+There is also a `plot_to_string` function with the same signature, if you want the result as a list of strings, to include the output elsewhere.
+
+### Data
+
+* `xs` - The x coordinates of the points to plot. Can either be `None`, or a list or NumPy array for plotting a single series, or a list of those for plotting multiple series. Defaults to `None`, meaning that the x axis will be just the sample index of
+`ys`.
+* `ys` - The y coordinates of the points to plot. Can either be a list or NumPy array for plotting a single series, or a list of those for plotting multiple series.
+
+In both cases, NaN values are ignored.
+
+### Options
+
+In alphabetical order:
+
+* `color` - Draw series in color. Defaults to `False` when plotting a single series, and to `True` when plotting multiple.
+* `force_ascii` - Force ASCII characters for plotting only. This can be useful for compatibility, for example when using uniplot inside of CI/CD systems that do not support Unicode. Defaults to `False`.
+* `height` - The height of the plotting region, in characters. Default is `17`.
+* `interactive` - Enable interactive mode. Defaults to `False`.
+* `legend_labels` - Labels for the series. Can be `None` or a list of strings. Defaults to `None`.
+* `lines` - Enable lines between points. Can either be `True` or `False`, or a list of those values for plotting multiple series. Defaults to `False`.
+* `line_length_hard_cap` - Enforce a hard limit on the number of characters per line of the plot area. This may override the `width` option if there is not enough space. Defaults to `None`.
+* `title` - The title of the plot. Defaults to `None`.
+* `width` - The width of the plotting region, in characters. Default is `60`. Note that if the `line_length_hard_cap` option is used and there is not enough space, the actual width may be smaller.
+* `x_as_log` - Plot the x axis as logarithmic scale. Defaults to `False`.
+* `x_gridlines` - A list of x values that have a vertical line for better orientation. Defaults to `[0]`, or to `[]` if `x_as_log` is enabled.
+* `x_max` - Maximum x value of the view. Defaults to a value that shows all data points.
+* `x_min` - Minimum x value of the view. Defaults to a value that shows all data points.
+* `x_unit` - Unit of the x axis. This is a string that is appended to the axis labels. Defaults to `""`.
+* `y_as_log` - Plot the y axis as logarithmic scale. Defaults to `False`.
+* `y_gridlines` - A list of y values that have a horizontal line for better orientation. Defaults to `[0]`, or to `[]` if `y_as_log` is enabled.
+* `y_max` - Maximum y value of the view. Defaults to a value that shows all data points.
+* `y_min` - Minimum y value of the view. Defaults to a value that shows all data points.
+* `y_unit` - Unit of the y axis. This is a string that is appended to the axis labels. Defaults to `""`.
+
+
+## Experimental features
+
+For convenience there is also a `histogram` function that accepts one or more series and
+plots bar-chart like histograms. It will automatically discretize the series into a
+number of bins given by the `bins` option and display the result.
+
+When calling the `histogram` function, the `lines` option is `True` by default.
+
+Example:
+
+```python
+import numpy as np
+x = np.sin(np.linspace(1, 1000))
+from uniplot import histogram
+histogram(x)
+```
+
+Result:
+```
+┌────────────────────────────────────────────────────────────┐
+│   ▛▀▀▌                       │                   ▐▀▀▜      │ 5
+│   ▌  ▌                       │                   ▐  ▐      │
+│   ▌  ▌                       │                   ▐  ▐      │
+│   ▌  ▀▀▀▌                    │                ▐▀▀▀  ▝▀▀▜   │ 4
+│   ▌     ▌                    │                ▐        ▐   │
+│   ▌     ▌                    │                ▐        ▐   │
+│   ▌     ▙▄▄▄▄▄▖              │          ▗▄▄▄  ▐        ▐   │ 3
+│   ▌           ▌              │          ▐  ▐  ▐        ▐   │
+│   ▌           ▌              │          ▐  ▐  ▐        ▐   │
+│   ▌           ▌              │          ▐  ▐  ▐        ▐   │
+│   ▌           ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▜  ▐▀▀▀  ▝▀▀▀        ▐   │ 2
+│   ▌                          │    ▐  ▐                 ▐   │
+│   ▌                          │    ▐  ▐                 ▐   │
+│   ▌                          │    ▐▄▄▟                 ▐   │ 1
+│   ▌                          │                         ▐   │
+│   ▌                          │                         ▐   │
+│▄▄▄▌▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁│▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▐▄▄▄│ 0
+└────────────────────────────────────────────────────────────┘
+     -1                        0                       1
+```
+
+
+## Installation
+
+Install via pip using:
+
+```
+pip install uniplot
+```
+
+
+## Contributing
+
+Clone this repository, and install dependecies via `poetry install`.
+
+You can run the tests vie `poetry run ./run_tests` to make sure your setup is good. Then proceed with issues, PRs etc. the usual way.
+
+
+%package -n python3-uniplot
+Summary:	Lightweight plotting to the terminal. 4x resolution via Unicode.
+Provides:	python-uniplot
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-uniplot
+# Uniplot
+[![Build Status](https://github.com/olavolav/uniplot/workflows/Unit%20Tests/badge.svg)](https://github.com/olavolav/uniplot/actions?query=workflow%3A"Unit+Tests")
+[![PyPI Version](https://badge.fury.io/py/uniplot.svg)](https://pypi.org/project/uniplot/)
+[![PyPI Downloads](https://pepy.tech/badge/uniplot)](https://pepy.tech/project/uniplot)
+
+Lightweight plotting to the terminal. 4x resolution via Unicode.
+
+![uniplot demo GIF](https://github.com/olavolav/uniplot/raw/master/resource/uniplot-demo.gif)
+
+When working with production data science code it can be handy to have plotting
+tool that does not rely on graphics dependencies or works only in a Jupyter notebook.
+
+The **use case** that this was built for is to have plots as part of your data science /
+machine learning CI pipeline - that way whenever something goes wrong, you get not only
+the error and backtrace but also plots that show what the problem was.
+
+
+## Features
+
+* Unicode drawing, so 4x the resolution (pixels) of usual ASCII plots
+* Super simple API
+* Interactive mode (pass `interactive=True`)
+* Color mode (pass `color=True`) useful in particular when plotting multiple series
+* It's fast: Plotting 1M data points takes 100ms thanks to NumPy magic
+* Only one dependency: NumPy (but you have that anyway don't you)
+
+Please note that Unicode drawing will work correctly only when using a font that
+fully supports the [Box-drawing character set](https://en.wikipedia.org/wiki/Box-drawing_character).
+Please refer to [this page for a (incomplete) list of supported fonts](https://www.fileformat.info/info/unicode/block/block_elements/fontsupport.htm).
+
+
+## Examples
+
+Note that all the examples are without color and plotting only a single series od data. For using color see the GIF example above.
+
+### Plot sine wave
+
+```python
+import math
+x = [math.sin(i/20)+i/300 for i in range(600)]
+from uniplot import plot
+plot(x, title="Sine wave")
+```
+
+Result:
+```
+                          Sine wave
+┌────────────────────────────────────────────────────────────┐
+│                                                    ▟▀▚     │
+│                                                   ▗▘ ▝▌    │
+│                                       ▗▛▜▖        ▞   ▐    │
+│                                       ▞  ▜       ▗▌    ▌   │ 2
+│                           ▟▀▙        ▗▘  ▝▌      ▐     ▜   │
+│                          ▐▘ ▝▖       ▞    ▜      ▌     ▝▌  │
+│              ▗▛▜▖        ▛   ▜      ▗▌    ▝▌    ▐▘      ▜  │
+│              ▛  ▙       ▗▘   ▝▖     ▐      ▚    ▞       ▝▌ │
+│  ▟▀▖        ▐▘  ▝▖      ▟     ▚     ▌      ▝▖  ▗▌        ▜▄│ 1
+│ ▐▘ ▐▖       ▛    ▙      ▌     ▐▖   ▗▘       ▚  ▞           │
+│ ▛   ▙      ▗▘    ▐▖    ▐       ▙   ▞        ▝▙▟▘           │
+│▐▘   ▐▖     ▐      ▌    ▛       ▐▖ ▗▘                       │
+│▞     ▌     ▌      ▐   ▗▘        ▜▄▛                        │
+│▌─────▐────▐▘───────▙──▞────────────────────────────────────│ 0
+│       ▌   ▛        ▝▙▟▘                                    │
+│       ▜  ▐▘                                                │
+│        ▙▄▛                                                 │
+└────────────────────────────────────────────────────────────┘
+         100       200       300       400       500       600
+```
+
+### Plot global temperature data
+
+Here we're using Pandas to load and prepare global temperature data from the [Our World in Data GitHub repository](https://github.com/owid/owid-datasets).
+
+First we load the data, rename a column and and filter the data:
+
+```python
+import pandas as pd
+uri = "https://github.com/owid/owid-datasets/raw/master/datasets/Global%20average%20temperature%20anomaly%20-%20Hadley%20Centre/Global%20average%20temperature%20anomaly%20-%20Hadley%20Centre.csv"
+data = pd.read_csv(uri)
+data = data.rename(columns={"Global average temperature anomaly (Hadley Centre)": "Global"})
+data = data[data.Entity == "median"]
+```
+
+Then we can plot it:
+
+```python
+from uniplot import plot
+plot(xs=data.Year, ys=data.Global, lines=True, title="Global normalized land-sea temperature anomaly", y_unit=" °C")
+```
+
+Result:
+```
+        Global normalized land-sea temperature anomaly
+┌────────────────────────────────────────────────────────────┐
+│                                                          ▞▀│
+│                                                         ▐  │
+│                                                         ▐  │
+│                                                     ▗   ▌  │ 0.6 °C
+│                                           ▙  ▗▄ ▛▄▖▗▘▌ ▞   │
+│                                          ▗▜  ▌ ▜  ▚▞ ▚▞    │
+│                                          ▐▝▖▐      ▘       │
+│                                    ▗   ▗ ▌ ▙▌              │ 0.3 °C
+│                                    ▛▖  ▞▙▘  ▘              │
+│                              ▖  ▗▄▗▘▐ ▐▘▜                  │
+│                            ▟ █  ▞ ▜ ▝▄▘                    │
+│   ▗▚   ▗    ▖       ▗   ▖▗▞ █▐  ▌    ▘                     │
+│▁▁▁▞▐▁▁▗▘▜▗▀▀▌▁▁▁▁▙▁▁▟▁▁▁▙▐▁▁▜▁▌▞▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁│ 0 °C
+│▚ ▐ ▝▖ ▐  ▛  ▌ ▗▄▐ ▌▗▘▌ ▐▝▌    ▝▘                           │
+│ ▌▌  ▌ ▞     ▐▗▘ ▛ ▐▞ ▌ ▐                                   │
+│ ▝   ▝▖▌     ▐▞    ▝▌ ▚▜▐                                   │
+│      ▗▌     ▝        ▝ ▌                                   │
+└────────────────────────────────────────────────────────────┘
+1,950    1,960    1,970   1,980    1,990    2,000   2,010
+```
+
+
+## Parameters
+
+The `plot` function accepts a number of parameters, all listed below. Note that only
+`ys` is required, all others are optional.
+
+There is also a `plot_to_string` function with the same signature, if you want the result as a list of strings, to include the output elsewhere.
+
+### Data
+
+* `xs` - The x coordinates of the points to plot. Can either be `None`, or a list or NumPy array for plotting a single series, or a list of those for plotting multiple series. Defaults to `None`, meaning that the x axis will be just the sample index of
+`ys`.
+* `ys` - The y coordinates of the points to plot. Can either be a list or NumPy array for plotting a single series, or a list of those for plotting multiple series.
+
+In both cases, NaN values are ignored.
+
+### Options
+
+In alphabetical order:
+
+* `color` - Draw series in color. Defaults to `False` when plotting a single series, and to `True` when plotting multiple.
+* `force_ascii` - Force ASCII characters for plotting only. This can be useful for compatibility, for example when using uniplot inside of CI/CD systems that do not support Unicode. Defaults to `False`.
+* `height` - The height of the plotting region, in characters. Default is `17`.
+* `interactive` - Enable interactive mode. Defaults to `False`.
+* `legend_labels` - Labels for the series. Can be `None` or a list of strings. Defaults to `None`.
+* `lines` - Enable lines between points. Can either be `True` or `False`, or a list of those values for plotting multiple series. Defaults to `False`.
+* `line_length_hard_cap` - Enforce a hard limit on the number of characters per line of the plot area. This may override the `width` option if there is not enough space. Defaults to `None`.
+* `title` - The title of the plot. Defaults to `None`.
+* `width` - The width of the plotting region, in characters. Default is `60`. Note that if the `line_length_hard_cap` option is used and there is not enough space, the actual width may be smaller.
+* `x_as_log` - Plot the x axis as logarithmic scale. Defaults to `False`.
+* `x_gridlines` - A list of x values that have a vertical line for better orientation. Defaults to `[0]`, or to `[]` if `x_as_log` is enabled.
+* `x_max` - Maximum x value of the view. Defaults to a value that shows all data points.
+* `x_min` - Minimum x value of the view. Defaults to a value that shows all data points.
+* `x_unit` - Unit of the x axis. This is a string that is appended to the axis labels. Defaults to `""`.
+* `y_as_log` - Plot the y axis as logarithmic scale. Defaults to `False`.
+* `y_gridlines` - A list of y values that have a horizontal line for better orientation. Defaults to `[0]`, or to `[]` if `y_as_log` is enabled.
+* `y_max` - Maximum y value of the view. Defaults to a value that shows all data points.
+* `y_min` - Minimum y value of the view. Defaults to a value that shows all data points.
+* `y_unit` - Unit of the y axis. This is a string that is appended to the axis labels. Defaults to `""`.
+
+
+## Experimental features
+
+For convenience there is also a `histogram` function that accepts one or more series and
+plots bar-chart like histograms. It will automatically discretize the series into a
+number of bins given by the `bins` option and display the result.
+
+When calling the `histogram` function, the `lines` option is `True` by default.
+
+Example:
+
+```python
+import numpy as np
+x = np.sin(np.linspace(1, 1000))
+from uniplot import histogram
+histogram(x)
+```
+
+Result:
+```
+┌────────────────────────────────────────────────────────────┐
+│   ▛▀▀▌                       │                   ▐▀▀▜      │ 5
+│   ▌  ▌                       │                   ▐  ▐      │
+│   ▌  ▌                       │                   ▐  ▐      │
+│   ▌  ▀▀▀▌                    │                ▐▀▀▀  ▝▀▀▜   │ 4
+│   ▌     ▌                    │                ▐        ▐   │
+│   ▌     ▌                    │                ▐        ▐   │
+│   ▌     ▙▄▄▄▄▄▖              │          ▗▄▄▄  ▐        ▐   │ 3
+│   ▌           ▌              │          ▐  ▐  ▐        ▐   │
+│   ▌           ▌              │          ▐  ▐  ▐        ▐   │
+│   ▌           ▌              │          ▐  ▐  ▐        ▐   │
+│   ▌           ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▜  ▐▀▀▀  ▝▀▀▀        ▐   │ 2
+│   ▌                          │    ▐  ▐                 ▐   │
+│   ▌                          │    ▐  ▐                 ▐   │
+│   ▌                          │    ▐▄▄▟                 ▐   │ 1
+│   ▌                          │                         ▐   │
+│   ▌                          │                         ▐   │
+│▄▄▄▌▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁│▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▐▄▄▄│ 0
+└────────────────────────────────────────────────────────────┘
+     -1                        0                       1
+```
+
+
+## Installation
+
+Install via pip using:
+
+```
+pip install uniplot
+```
+
+
+## Contributing
+
+Clone this repository, and install dependecies via `poetry install`.
+
+You can run the tests vie `poetry run ./run_tests` to make sure your setup is good. Then proceed with issues, PRs etc. the usual way.
+
+
+%package help
+Summary:	Development documents and examples for uniplot
+Provides:	python3-uniplot-doc
+%description help
+# Uniplot
+[![Build Status](https://github.com/olavolav/uniplot/workflows/Unit%20Tests/badge.svg)](https://github.com/olavolav/uniplot/actions?query=workflow%3A"Unit+Tests")
+[![PyPI Version](https://badge.fury.io/py/uniplot.svg)](https://pypi.org/project/uniplot/)
+[![PyPI Downloads](https://pepy.tech/badge/uniplot)](https://pepy.tech/project/uniplot)
+
+Lightweight plotting to the terminal. 4x resolution via Unicode.
+
+![uniplot demo GIF](https://github.com/olavolav/uniplot/raw/master/resource/uniplot-demo.gif)
+
+When working with production data science code it can be handy to have plotting
+tool that does not rely on graphics dependencies or works only in a Jupyter notebook.
+
+The **use case** that this was built for is to have plots as part of your data science /
+machine learning CI pipeline - that way whenever something goes wrong, you get not only
+the error and backtrace but also plots that show what the problem was.
+
+
+## Features
+
+* Unicode drawing, so 4x the resolution (pixels) of usual ASCII plots
+* Super simple API
+* Interactive mode (pass `interactive=True`)
+* Color mode (pass `color=True`) useful in particular when plotting multiple series
+* It's fast: Plotting 1M data points takes 100ms thanks to NumPy magic
+* Only one dependency: NumPy (but you have that anyway don't you)
+
+Please note that Unicode drawing will work correctly only when using a font that
+fully supports the [Box-drawing character set](https://en.wikipedia.org/wiki/Box-drawing_character).
+Please refer to [this page for a (incomplete) list of supported fonts](https://www.fileformat.info/info/unicode/block/block_elements/fontsupport.htm).
+
+
+## Examples
+
+Note that all the examples are without color and plotting only a single series od data. For using color see the GIF example above.
+
+### Plot sine wave
+
+```python
+import math
+x = [math.sin(i/20)+i/300 for i in range(600)]
+from uniplot import plot
+plot(x, title="Sine wave")
+```
+
+Result:
+```
+                          Sine wave
+┌────────────────────────────────────────────────────────────┐
+│                                                    ▟▀▚     │
+│                                                   ▗▘ ▝▌    │
+│                                       ▗▛▜▖        ▞   ▐    │
+│                                       ▞  ▜       ▗▌    ▌   │ 2
+│                           ▟▀▙        ▗▘  ▝▌      ▐     ▜   │
+│                          ▐▘ ▝▖       ▞    ▜      ▌     ▝▌  │
+│              ▗▛▜▖        ▛   ▜      ▗▌    ▝▌    ▐▘      ▜  │
+│              ▛  ▙       ▗▘   ▝▖     ▐      ▚    ▞       ▝▌ │
+│  ▟▀▖        ▐▘  ▝▖      ▟     ▚     ▌      ▝▖  ▗▌        ▜▄│ 1
+│ ▐▘ ▐▖       ▛    ▙      ▌     ▐▖   ▗▘       ▚  ▞           │
+│ ▛   ▙      ▗▘    ▐▖    ▐       ▙   ▞        ▝▙▟▘           │
+│▐▘   ▐▖     ▐      ▌    ▛       ▐▖ ▗▘                       │
+│▞     ▌     ▌      ▐   ▗▘        ▜▄▛                        │
+│▌─────▐────▐▘───────▙──▞────────────────────────────────────│ 0
+│       ▌   ▛        ▝▙▟▘                                    │
+│       ▜  ▐▘                                                │
+│        ▙▄▛                                                 │
+└────────────────────────────────────────────────────────────┘
+         100       200       300       400       500       600
+```
+
+### Plot global temperature data
+
+Here we're using Pandas to load and prepare global temperature data from the [Our World in Data GitHub repository](https://github.com/owid/owid-datasets).
+
+First we load the data, rename a column and and filter the data:
+
+```python
+import pandas as pd
+uri = "https://github.com/owid/owid-datasets/raw/master/datasets/Global%20average%20temperature%20anomaly%20-%20Hadley%20Centre/Global%20average%20temperature%20anomaly%20-%20Hadley%20Centre.csv"
+data = pd.read_csv(uri)
+data = data.rename(columns={"Global average temperature anomaly (Hadley Centre)": "Global"})
+data = data[data.Entity == "median"]
+```
+
+Then we can plot it:
+
+```python
+from uniplot import plot
+plot(xs=data.Year, ys=data.Global, lines=True, title="Global normalized land-sea temperature anomaly", y_unit=" °C")
+```
+
+Result:
+```
+        Global normalized land-sea temperature anomaly
+┌────────────────────────────────────────────────────────────┐
+│                                                          ▞▀│
+│                                                         ▐  │
+│                                                         ▐  │
+│                                                     ▗   ▌  │ 0.6 °C
+│                                           ▙  ▗▄ ▛▄▖▗▘▌ ▞   │
+│                                          ▗▜  ▌ ▜  ▚▞ ▚▞    │
+│                                          ▐▝▖▐      ▘       │
+│                                    ▗   ▗ ▌ ▙▌              │ 0.3 °C
+│                                    ▛▖  ▞▙▘  ▘              │
+│                              ▖  ▗▄▗▘▐ ▐▘▜                  │
+│                            ▟ █  ▞ ▜ ▝▄▘                    │
+│   ▗▚   ▗    ▖       ▗   ▖▗▞ █▐  ▌    ▘                     │
+│▁▁▁▞▐▁▁▗▘▜▗▀▀▌▁▁▁▁▙▁▁▟▁▁▁▙▐▁▁▜▁▌▞▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁│ 0 °C
+│▚ ▐ ▝▖ ▐  ▛  ▌ ▗▄▐ ▌▗▘▌ ▐▝▌    ▝▘                           │
+│ ▌▌  ▌ ▞     ▐▗▘ ▛ ▐▞ ▌ ▐                                   │
+│ ▝   ▝▖▌     ▐▞    ▝▌ ▚▜▐                                   │
+│      ▗▌     ▝        ▝ ▌                                   │
+└────────────────────────────────────────────────────────────┘
+1,950    1,960    1,970   1,980    1,990    2,000   2,010
+```
+
+
+## Parameters
+
+The `plot` function accepts a number of parameters, all listed below. Note that only
+`ys` is required, all others are optional.
+
+There is also a `plot_to_string` function with the same signature, if you want the result as a list of strings, to include the output elsewhere.
+
+### Data
+
+* `xs` - The x coordinates of the points to plot. Can either be `None`, or a list or NumPy array for plotting a single series, or a list of those for plotting multiple series. Defaults to `None`, meaning that the x axis will be just the sample index of
+`ys`.
+* `ys` - The y coordinates of the points to plot. Can either be a list or NumPy array for plotting a single series, or a list of those for plotting multiple series.
+
+In both cases, NaN values are ignored.
+
+### Options
+
+In alphabetical order:
+
+* `color` - Draw series in color. Defaults to `False` when plotting a single series, and to `True` when plotting multiple.
+* `force_ascii` - Force ASCII characters for plotting only. This can be useful for compatibility, for example when using uniplot inside of CI/CD systems that do not support Unicode. Defaults to `False`.
+* `height` - The height of the plotting region, in characters. Default is `17`.
+* `interactive` - Enable interactive mode. Defaults to `False`.
+* `legend_labels` - Labels for the series. Can be `None` or a list of strings. Defaults to `None`.
+* `lines` - Enable lines between points. Can either be `True` or `False`, or a list of those values for plotting multiple series. Defaults to `False`.
+* `line_length_hard_cap` - Enforce a hard limit on the number of characters per line of the plot area. This may override the `width` option if there is not enough space. Defaults to `None`.
+* `title` - The title of the plot. Defaults to `None`.
+* `width` - The width of the plotting region, in characters. Default is `60`. Note that if the `line_length_hard_cap` option is used and there is not enough space, the actual width may be smaller.
+* `x_as_log` - Plot the x axis as logarithmic scale. Defaults to `False`.
+* `x_gridlines` - A list of x values that have a vertical line for better orientation. Defaults to `[0]`, or to `[]` if `x_as_log` is enabled.
+* `x_max` - Maximum x value of the view. Defaults to a value that shows all data points.
+* `x_min` - Minimum x value of the view. Defaults to a value that shows all data points.
+* `x_unit` - Unit of the x axis. This is a string that is appended to the axis labels. Defaults to `""`.
+* `y_as_log` - Plot the y axis as logarithmic scale. Defaults to `False`.
+* `y_gridlines` - A list of y values that have a horizontal line for better orientation. Defaults to `[0]`, or to `[]` if `y_as_log` is enabled.
+* `y_max` - Maximum y value of the view. Defaults to a value that shows all data points.
+* `y_min` - Minimum y value of the view. Defaults to a value that shows all data points.
+* `y_unit` - Unit of the y axis. This is a string that is appended to the axis labels. Defaults to `""`.
+
+
+## Experimental features
+
+For convenience there is also a `histogram` function that accepts one or more series and
+plots bar-chart like histograms. It will automatically discretize the series into a
+number of bins given by the `bins` option and display the result.
+
+When calling the `histogram` function, the `lines` option is `True` by default.
+
+Example:
+
+```python
+import numpy as np
+x = np.sin(np.linspace(1, 1000))
+from uniplot import histogram
+histogram(x)
+```
+
+Result:
+```
+┌────────────────────────────────────────────────────────────┐
+│   ▛▀▀▌                       │                   ▐▀▀▜      │ 5
+│   ▌  ▌                       │                   ▐  ▐      │
+│   ▌  ▌                       │                   ▐  ▐      │
+│   ▌  ▀▀▀▌                    │                ▐▀▀▀  ▝▀▀▜   │ 4
+│   ▌     ▌                    │                ▐        ▐   │
+│   ▌     ▌                    │                ▐        ▐   │
+│   ▌     ▙▄▄▄▄▄▖              │          ▗▄▄▄  ▐        ▐   │ 3
+│   ▌           ▌              │          ▐  ▐  ▐        ▐   │
+│   ▌           ▌              │          ▐  ▐  ▐        ▐   │
+│   ▌           ▌              │          ▐  ▐  ▐        ▐   │
+│   ▌           ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▜  ▐▀▀▀  ▝▀▀▀        ▐   │ 2
+│   ▌                          │    ▐  ▐                 ▐   │
+│   ▌                          │    ▐  ▐                 ▐   │
+│   ▌                          │    ▐▄▄▟                 ▐   │ 1
+│   ▌                          │                         ▐   │
+│   ▌                          │                         ▐   │
+│▄▄▄▌▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁│▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▐▄▄▄│ 0
+└────────────────────────────────────────────────────────────┘
+     -1                        0                       1
+```
+
+
+## Installation
+
+Install via pip using:
+
+```
+pip install uniplot
+```
+
+
+## Contributing
+
+Clone this repository, and install dependecies via `poetry install`.
+
+You can run the tests vie `poetry run ./run_tests` to make sure your setup is good. Then proceed with issues, PRs etc. the usual way.
+
+
+%prep
+%autosetup -n uniplot-0.10.0
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+	find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+	find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+	find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+	find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+	find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-uniplot -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 0.10.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..b632278
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+3cee09eea0112cef098f557e96760e9e  uniplot-0.10.0.tar.gz