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|
%global _empty_manifest_terminate_build 0
Name: python-MonsterLab
Version: 1.2.7
Release: 1
Summary: Monster Generator
License: Free for non-commercial use
URL: https://github.com/BrokenShell/MonsterLab
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/1c/f0/d251b7300022e5fb1941f786d473211bf0c5d8e4758629515fbc7052f89e/MonsterLab-1.2.7.tar.gz
BuildArch: noarch
Requires: python3-pytz
%description
# MonsterLab
by Robert Sharp
## Monster Class
### Optional Inputs
It is recommended to pass all the optional arguments or none of them. For example,
a custom type requires a custom name.
- Name: Compound Gaussian Distribution -> String
- Derived from Type
- Multidimensional distribution of types and subtypes
- Type: Wide Flat Distribution -> String
- Demonic
- Devilkin
- Dragon
- Undead
- Elemental
- Fey
- Undead
- Level: Poisson Distribution -> Integer
- Range: [1..20]
- Most Common: [4..7] ~64%
- Mean: 6.001
- Median: 6
- Rarity: Linear Distribution [Rank 0..Rank 5] -> String
- Rank 0: 30.5% Very Common
- Rank 1: 25.0% Common
- Rank 2: 19.4% Uncommon
- Rank 3: 13.8% Rare
- Rank 4: 8.3% Epic
- Rank 5: 2.7% Legendary
### Derived Fields
- Damage: Compound Geometric Distribution with Linear Noise -> String
- Derived from Level and Rarity
- Health: Geometric Distribution with Gaussian Noise -> Float
- Derived from Level and Rarity
- Energy: Geometric Distribution with Gaussian Noise -> Float
- Derived from Level and Rarity
- Sanity: Geometric Distribution with Gaussian Noise -> Float
- Derived from Level and Rarity
- Time Stamp: The Monster's Birthday -> String
### Example Monster
- Name: Revenant
- Type: Undead
- Level: 3
- Rarity: Rank 0
- Damage: 3d2+1
- Health: 6.35
- Energy: 5.78
- Sanity: 6.0
- Time Stamp: 2021-08-09 14:23:23
### Code Example
```
$ pip install MonsterLab
$ python3
>>> from MonsterLab import Monster
>>> Monster()
Name: Imp
Type: Demonic
Level: 10
Rarity: Rank 0
Damage: 10d2+1
Health: 20.89
Energy: 20.55
Sanity: 20.79
Time Stamp: 2021-08-09 14:23:23
```
%package -n python3-MonsterLab
Summary: Monster Generator
Provides: python-MonsterLab
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-MonsterLab
# MonsterLab
by Robert Sharp
## Monster Class
### Optional Inputs
It is recommended to pass all the optional arguments or none of them. For example,
a custom type requires a custom name.
- Name: Compound Gaussian Distribution -> String
- Derived from Type
- Multidimensional distribution of types and subtypes
- Type: Wide Flat Distribution -> String
- Demonic
- Devilkin
- Dragon
- Undead
- Elemental
- Fey
- Undead
- Level: Poisson Distribution -> Integer
- Range: [1..20]
- Most Common: [4..7] ~64%
- Mean: 6.001
- Median: 6
- Rarity: Linear Distribution [Rank 0..Rank 5] -> String
- Rank 0: 30.5% Very Common
- Rank 1: 25.0% Common
- Rank 2: 19.4% Uncommon
- Rank 3: 13.8% Rare
- Rank 4: 8.3% Epic
- Rank 5: 2.7% Legendary
### Derived Fields
- Damage: Compound Geometric Distribution with Linear Noise -> String
- Derived from Level and Rarity
- Health: Geometric Distribution with Gaussian Noise -> Float
- Derived from Level and Rarity
- Energy: Geometric Distribution with Gaussian Noise -> Float
- Derived from Level and Rarity
- Sanity: Geometric Distribution with Gaussian Noise -> Float
- Derived from Level and Rarity
- Time Stamp: The Monster's Birthday -> String
### Example Monster
- Name: Revenant
- Type: Undead
- Level: 3
- Rarity: Rank 0
- Damage: 3d2+1
- Health: 6.35
- Energy: 5.78
- Sanity: 6.0
- Time Stamp: 2021-08-09 14:23:23
### Code Example
```
$ pip install MonsterLab
$ python3
>>> from MonsterLab import Monster
>>> Monster()
Name: Imp
Type: Demonic
Level: 10
Rarity: Rank 0
Damage: 10d2+1
Health: 20.89
Energy: 20.55
Sanity: 20.79
Time Stamp: 2021-08-09 14:23:23
```
%package help
Summary: Development documents and examples for MonsterLab
Provides: python3-MonsterLab-doc
%description help
# MonsterLab
by Robert Sharp
## Monster Class
### Optional Inputs
It is recommended to pass all the optional arguments or none of them. For example,
a custom type requires a custom name.
- Name: Compound Gaussian Distribution -> String
- Derived from Type
- Multidimensional distribution of types and subtypes
- Type: Wide Flat Distribution -> String
- Demonic
- Devilkin
- Dragon
- Undead
- Elemental
- Fey
- Undead
- Level: Poisson Distribution -> Integer
- Range: [1..20]
- Most Common: [4..7] ~64%
- Mean: 6.001
- Median: 6
- Rarity: Linear Distribution [Rank 0..Rank 5] -> String
- Rank 0: 30.5% Very Common
- Rank 1: 25.0% Common
- Rank 2: 19.4% Uncommon
- Rank 3: 13.8% Rare
- Rank 4: 8.3% Epic
- Rank 5: 2.7% Legendary
### Derived Fields
- Damage: Compound Geometric Distribution with Linear Noise -> String
- Derived from Level and Rarity
- Health: Geometric Distribution with Gaussian Noise -> Float
- Derived from Level and Rarity
- Energy: Geometric Distribution with Gaussian Noise -> Float
- Derived from Level and Rarity
- Sanity: Geometric Distribution with Gaussian Noise -> Float
- Derived from Level and Rarity
- Time Stamp: The Monster's Birthday -> String
### Example Monster
- Name: Revenant
- Type: Undead
- Level: 3
- Rarity: Rank 0
- Damage: 3d2+1
- Health: 6.35
- Energy: 5.78
- Sanity: 6.0
- Time Stamp: 2021-08-09 14:23:23
### Code Example
```
$ pip install MonsterLab
$ python3
>>> from MonsterLab import Monster
>>> Monster()
Name: Imp
Type: Demonic
Level: 10
Rarity: Rank 0
Damage: 10d2+1
Health: 20.89
Energy: 20.55
Sanity: 20.79
Time Stamp: 2021-08-09 14:23:23
```
%prep
%autosetup -n MonsterLab-1.2.7
%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-MonsterLab -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue May 30 2023 Python_Bot <Python_Bot@openeuler.org> - 1.2.7-1
- Package Spec generated
|
