automatic import of python-open-backtest

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diff --git a/.gitignore b/.gitignore
index e69de29..7ee1b36 100644
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1 @@
+/open-backtest-7.0.0.tar.gz
diff --git a/python-open-backtest.spec b/python-open-backtest.spec
new file mode 100644
index 0000000..567bbce
--- /dev/null
+++ b/python-open-backtest.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-open-backtest
+Version:	7.0.0
+Release:	1
+Summary:	Open Backtest is a beginner friendly & powerful backtesting engine for crypto trading
+License:	MIT License
+URL:		https://github.com/Shaft-3796/OpenBacktest
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/5e/cb/a663a59c3d9548bffd2fb07947a03e7dd810a8c6514a8170a6d0ec6c80b9/open-backtest-7.0.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-binance
+Requires:	python3-pandas
+Requires:	python3-numpy
+Requires:	python3-plotly
+Requires:	python3-ta
+
+%description
+# Open Backtest
+
+<img src="https://cdn.discordapp.com/attachments/901790872033714216/901790945127841862/IMG_2895.JPG" alt="drawing" width="300"/>
+
+### Open source & beginner friendly crypto trading backtest library
+- [French page](https://github.com/Shaft-3796/OpenBacktest/blob/master/README-FRA.md)
+
+<br>
+
+<img src="https://static.pepy.tech/personalized-badge/open-backtest?period=total&units=international_system&left_color=black&right_color=blue&left_text=Downloads" width=150></img>
+```
+pip install open-backtest
+```
+### Wanna contact me ? 👋
+
+https://discord.gg/wfpGXvjj9t
+
+### Wanna support my work ? 💰
+
+- paypal: *sh4ft.me@gmail.com*
+- usdt (ERC20): *0x17B516E9cA55C330B6b2bd2830042cAf5C7ecD7a*
+- btc: *34vo6zxSFYS5QJM6dpr4JLHVEo5vZ5owZH*
+- eth: *0xF7f87bc828707354AAfae235dE584F27bDCc9569*
+
+*thanks if you do it 💖*
+
+## What is it ? 📈
+
+**Passionate about the world of crypto and about development I decided to create a python library because I found very
+ annoying for beginners to just run a simple backtest. Open Backtest got created to give apprentice but also confirmed 
+ programmers a powerful and easy to use backtesting tool**
+
+## How does it work ? 🔧
+
+**Open Backtest is currently made with a core engine that use different classes, it can run a backtest with binance data
+ and it can handle different timeframes. The library can also download and save data as a csv file to be able to load 
+ it to save a considerable amount of time. The wallet class will handle orders and the data handler will summarize and 
+ calculate all required data to analyze the backtest but also to plot graphs.**
+ 
+ ##### Requirements :
+ 
+ - Pandas
+ - Numpy
+ - Plotly
+ - Python-binance
+ 
+ *All requirements will be downloaded and installed with Open Backtest installation*
+ 
+ ## Doc 📝
+
+### How to run a backtest ?
+We will see here a simple example
+
+```python
+# ------------------------------------------------------------------
+# Let's show you how to run a very simple strategy !
+# First of all, let's see all our imports
+# ------------------------------------------------------------------
+
+# The library Technical Analyse is already included when installing open backtest
+# it allow to add a lot of indicators very useful for trading strategy
+from ta import trend, momentum
+
+# Let's import here 4 classes of Open Backtest we will later see how to use it
+from OpenBacktest.ObtEngine import Engine, Container, Pair, Report
+
+# Python Binance is also included with Open Backtest it allow us to get the market data
+from binance.client import Client
+
+# ------------------------------------------------------------------
+# The let's initialise our classes
+# ------------------------------------------------------------------
+
+# First of all we are here creating our container, it will contain all of our market pairs
+container = Container()
+
+# Let's add our market pair with the container.add_main_pair() method
+
+# The parameter of the method is a Pair class with 5
+# parameters, the parameters are quite self-explanatory but just to clarify, name is just a recognizable name for you
+# that will be used later to get the data of a pair if you have multiple dataframes but we will see it later !
+# At the moment just don't take care about the name it's not important,
+# the path is the location of files that already exist or
+# the location of futures files that will be saved, this parameter is optional.
+
+# We register here our main pair ! The data will be get for the pair Ethereum - Usdt from the 01 january 2021 to now
+# with candles of 1 hour
+container.add_main_pair(
+    Pair(market_pair="ETHUSDT", start="01 january 2021", timeframe=Client.KLINE_INTERVAL_1HOUR, name="ETHUSDT",
+         path=""))
+
+# Let's now initialise our engine with our container
+engine = Engine(container)
+
+# This line is not required ! it's used to save our data as csv files to be able to just have to load it
+# for the next backtest
+container.save_all(default_path="")
+
+# We are here enriching our dataframe with technical indicators using TA lib more information here
+# https://technical-analysis-library-in-python.readthedocs.io/en/latest/
+
+# Let's add to our dataframe 2 EMA
+engine.main_dataframe()["EMA3"] = trend.ema_indicator(engine.main_dataframe()['close'], 3)
+engine.main_dataframe()["EMA100"] = trend.ema_indicator(engine.main_dataframe()['close'], 100)
+
+
+# We will now set a strategy that will return a report class. The engine
+# will call this function with the main dataframe and each index
+def strategy(dataframe, index):
+    # first, there's our buy condition
+    if dataframe["EMA3"][index] >= dataframe["EMA100"][index]:
+        # we return a report with the order_type and the amount in percent of our coin wallet we want to buy
+        return Report("buy", percent_amount=100)
+    # then, there's our sell condition
+    if dataframe["EMA3"][index] <= dataframe["EMA100"][index]:
+        # we return a report with the order_type and the amount in percent of our token wallet we want to sell
+        return Report("sell", percent_amount=100)
+
+
+# ------------------------------------------------------------------
+# The let's run our backtest !
+# ------------------------------------------------------------------
+
+# This function is used to register our strategy
+engine.register_strategy(strategy)
+
+# This function is used to run the backtest, first parameter is the coin name, second is the token name, third
+# is your initial coin balance 4th is your initial token balance 5th is your taker fees in percent
+engine.run_strategy(coin_name="USDT", token_name="ETH", coin_balance=1000, token_balance=0, taker=0.075)
+
+# We use this function to summarize and display the result of our backtest
+engine.wallet.get_data_handler().display_wallet()
+
+# And we finally use it to plot graphs of price and balance evolution, you can use the parameter size=... to set the
+# points size and the parameter tradeline=False to disable trade lines
+engine.wallet.get_data_handler().plot_wallet()
+
+# -----------------------------------------------------------------------------------------------------------------
+# And that's finish ! Hope you like and that it wasn't hard ! If you have any question dm me on discord: Shaft#3796
+# -----------------------------------------------------------------------------------------------------------------
+```
+
+<img src="https://cdn.discordapp.com/attachments/901790872033714216/908336432760889404/unknown.png" alt="drawing" width="800"/>
+<img src="https://cdn.discordapp.com/attachments/901790872033714216/908336484149510165/unknown.png" alt="drawing" width="800"/>
+<img src="https://cdn.discordapp.com/attachments/901790872033714216/908336590319943740/unknown.png" alt="drawing" width="1000"/>
+
+*Next part is coming soon*
+
+
+
+
+%package -n python3-open-backtest
+Summary:	Open Backtest is a beginner friendly & powerful backtesting engine for crypto trading
+Provides:	python-open-backtest
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-open-backtest
+# Open Backtest
+
+<img src="https://cdn.discordapp.com/attachments/901790872033714216/901790945127841862/IMG_2895.JPG" alt="drawing" width="300"/>
+
+### Open source & beginner friendly crypto trading backtest library
+- [French page](https://github.com/Shaft-3796/OpenBacktest/blob/master/README-FRA.md)
+
+<br>
+
+<img src="https://static.pepy.tech/personalized-badge/open-backtest?period=total&units=international_system&left_color=black&right_color=blue&left_text=Downloads" width=150></img>
+```
+pip install open-backtest
+```
+### Wanna contact me ? 👋
+
+https://discord.gg/wfpGXvjj9t
+
+### Wanna support my work ? 💰
+
+- paypal: *sh4ft.me@gmail.com*
+- usdt (ERC20): *0x17B516E9cA55C330B6b2bd2830042cAf5C7ecD7a*
+- btc: *34vo6zxSFYS5QJM6dpr4JLHVEo5vZ5owZH*
+- eth: *0xF7f87bc828707354AAfae235dE584F27bDCc9569*
+
+*thanks if you do it 💖*
+
+## What is it ? 📈
+
+**Passionate about the world of crypto and about development I decided to create a python library because I found very
+ annoying for beginners to just run a simple backtest. Open Backtest got created to give apprentice but also confirmed 
+ programmers a powerful and easy to use backtesting tool**
+
+## How does it work ? 🔧
+
+**Open Backtest is currently made with a core engine that use different classes, it can run a backtest with binance data
+ and it can handle different timeframes. The library can also download and save data as a csv file to be able to load 
+ it to save a considerable amount of time. The wallet class will handle orders and the data handler will summarize and 
+ calculate all required data to analyze the backtest but also to plot graphs.**
+ 
+ ##### Requirements :
+ 
+ - Pandas
+ - Numpy
+ - Plotly
+ - Python-binance
+ 
+ *All requirements will be downloaded and installed with Open Backtest installation*
+ 
+ ## Doc 📝
+
+### How to run a backtest ?
+We will see here a simple example
+
+```python
+# ------------------------------------------------------------------
+# Let's show you how to run a very simple strategy !
+# First of all, let's see all our imports
+# ------------------------------------------------------------------
+
+# The library Technical Analyse is already included when installing open backtest
+# it allow to add a lot of indicators very useful for trading strategy
+from ta import trend, momentum
+
+# Let's import here 4 classes of Open Backtest we will later see how to use it
+from OpenBacktest.ObtEngine import Engine, Container, Pair, Report
+
+# Python Binance is also included with Open Backtest it allow us to get the market data
+from binance.client import Client
+
+# ------------------------------------------------------------------
+# The let's initialise our classes
+# ------------------------------------------------------------------
+
+# First of all we are here creating our container, it will contain all of our market pairs
+container = Container()
+
+# Let's add our market pair with the container.add_main_pair() method
+
+# The parameter of the method is a Pair class with 5
+# parameters, the parameters are quite self-explanatory but just to clarify, name is just a recognizable name for you
+# that will be used later to get the data of a pair if you have multiple dataframes but we will see it later !
+# At the moment just don't take care about the name it's not important,
+# the path is the location of files that already exist or
+# the location of futures files that will be saved, this parameter is optional.
+
+# We register here our main pair ! The data will be get for the pair Ethereum - Usdt from the 01 january 2021 to now
+# with candles of 1 hour
+container.add_main_pair(
+    Pair(market_pair="ETHUSDT", start="01 january 2021", timeframe=Client.KLINE_INTERVAL_1HOUR, name="ETHUSDT",
+         path=""))
+
+# Let's now initialise our engine with our container
+engine = Engine(container)
+
+# This line is not required ! it's used to save our data as csv files to be able to just have to load it
+# for the next backtest
+container.save_all(default_path="")
+
+# We are here enriching our dataframe with technical indicators using TA lib more information here
+# https://technical-analysis-library-in-python.readthedocs.io/en/latest/
+
+# Let's add to our dataframe 2 EMA
+engine.main_dataframe()["EMA3"] = trend.ema_indicator(engine.main_dataframe()['close'], 3)
+engine.main_dataframe()["EMA100"] = trend.ema_indicator(engine.main_dataframe()['close'], 100)
+
+
+# We will now set a strategy that will return a report class. The engine
+# will call this function with the main dataframe and each index
+def strategy(dataframe, index):
+    # first, there's our buy condition
+    if dataframe["EMA3"][index] >= dataframe["EMA100"][index]:
+        # we return a report with the order_type and the amount in percent of our coin wallet we want to buy
+        return Report("buy", percent_amount=100)
+    # then, there's our sell condition
+    if dataframe["EMA3"][index] <= dataframe["EMA100"][index]:
+        # we return a report with the order_type and the amount in percent of our token wallet we want to sell
+        return Report("sell", percent_amount=100)
+
+
+# ------------------------------------------------------------------
+# The let's run our backtest !
+# ------------------------------------------------------------------
+
+# This function is used to register our strategy
+engine.register_strategy(strategy)
+
+# This function is used to run the backtest, first parameter is the coin name, second is the token name, third
+# is your initial coin balance 4th is your initial token balance 5th is your taker fees in percent
+engine.run_strategy(coin_name="USDT", token_name="ETH", coin_balance=1000, token_balance=0, taker=0.075)
+
+# We use this function to summarize and display the result of our backtest
+engine.wallet.get_data_handler().display_wallet()
+
+# And we finally use it to plot graphs of price and balance evolution, you can use the parameter size=... to set the
+# points size and the parameter tradeline=False to disable trade lines
+engine.wallet.get_data_handler().plot_wallet()
+
+# -----------------------------------------------------------------------------------------------------------------
+# And that's finish ! Hope you like and that it wasn't hard ! If you have any question dm me on discord: Shaft#3796
+# -----------------------------------------------------------------------------------------------------------------
+```
+
+<img src="https://cdn.discordapp.com/attachments/901790872033714216/908336432760889404/unknown.png" alt="drawing" width="800"/>
+<img src="https://cdn.discordapp.com/attachments/901790872033714216/908336484149510165/unknown.png" alt="drawing" width="800"/>
+<img src="https://cdn.discordapp.com/attachments/901790872033714216/908336590319943740/unknown.png" alt="drawing" width="1000"/>
+
+*Next part is coming soon*
+
+
+
+
+%package help
+Summary:	Development documents and examples for open-backtest
+Provides:	python3-open-backtest-doc
+%description help
+# Open Backtest
+
+<img src="https://cdn.discordapp.com/attachments/901790872033714216/901790945127841862/IMG_2895.JPG" alt="drawing" width="300"/>
+
+### Open source & beginner friendly crypto trading backtest library
+- [French page](https://github.com/Shaft-3796/OpenBacktest/blob/master/README-FRA.md)
+
+<br>
+
+<img src="https://static.pepy.tech/personalized-badge/open-backtest?period=total&units=international_system&left_color=black&right_color=blue&left_text=Downloads" width=150></img>
+```
+pip install open-backtest
+```
+### Wanna contact me ? 👋
+
+https://discord.gg/wfpGXvjj9t
+
+### Wanna support my work ? 💰
+
+- paypal: *sh4ft.me@gmail.com*
+- usdt (ERC20): *0x17B516E9cA55C330B6b2bd2830042cAf5C7ecD7a*
+- btc: *34vo6zxSFYS5QJM6dpr4JLHVEo5vZ5owZH*
+- eth: *0xF7f87bc828707354AAfae235dE584F27bDCc9569*
+
+*thanks if you do it 💖*
+
+## What is it ? 📈
+
+**Passionate about the world of crypto and about development I decided to create a python library because I found very
+ annoying for beginners to just run a simple backtest. Open Backtest got created to give apprentice but also confirmed 
+ programmers a powerful and easy to use backtesting tool**
+
+## How does it work ? 🔧
+
+**Open Backtest is currently made with a core engine that use different classes, it can run a backtest with binance data
+ and it can handle different timeframes. The library can also download and save data as a csv file to be able to load 
+ it to save a considerable amount of time. The wallet class will handle orders and the data handler will summarize and 
+ calculate all required data to analyze the backtest but also to plot graphs.**
+ 
+ ##### Requirements :
+ 
+ - Pandas
+ - Numpy
+ - Plotly
+ - Python-binance
+ 
+ *All requirements will be downloaded and installed with Open Backtest installation*
+ 
+ ## Doc 📝
+
+### How to run a backtest ?
+We will see here a simple example
+
+```python
+# ------------------------------------------------------------------
+# Let's show you how to run a very simple strategy !
+# First of all, let's see all our imports
+# ------------------------------------------------------------------
+
+# The library Technical Analyse is already included when installing open backtest
+# it allow to add a lot of indicators very useful for trading strategy
+from ta import trend, momentum
+
+# Let's import here 4 classes of Open Backtest we will later see how to use it
+from OpenBacktest.ObtEngine import Engine, Container, Pair, Report
+
+# Python Binance is also included with Open Backtest it allow us to get the market data
+from binance.client import Client
+
+# ------------------------------------------------------------------
+# The let's initialise our classes
+# ------------------------------------------------------------------
+
+# First of all we are here creating our container, it will contain all of our market pairs
+container = Container()
+
+# Let's add our market pair with the container.add_main_pair() method
+
+# The parameter of the method is a Pair class with 5
+# parameters, the parameters are quite self-explanatory but just to clarify, name is just a recognizable name for you
+# that will be used later to get the data of a pair if you have multiple dataframes but we will see it later !
+# At the moment just don't take care about the name it's not important,
+# the path is the location of files that already exist or
+# the location of futures files that will be saved, this parameter is optional.
+
+# We register here our main pair ! The data will be get for the pair Ethereum - Usdt from the 01 january 2021 to now
+# with candles of 1 hour
+container.add_main_pair(
+    Pair(market_pair="ETHUSDT", start="01 january 2021", timeframe=Client.KLINE_INTERVAL_1HOUR, name="ETHUSDT",
+         path=""))
+
+# Let's now initialise our engine with our container
+engine = Engine(container)
+
+# This line is not required ! it's used to save our data as csv files to be able to just have to load it
+# for the next backtest
+container.save_all(default_path="")
+
+# We are here enriching our dataframe with technical indicators using TA lib more information here
+# https://technical-analysis-library-in-python.readthedocs.io/en/latest/
+
+# Let's add to our dataframe 2 EMA
+engine.main_dataframe()["EMA3"] = trend.ema_indicator(engine.main_dataframe()['close'], 3)
+engine.main_dataframe()["EMA100"] = trend.ema_indicator(engine.main_dataframe()['close'], 100)
+
+
+# We will now set a strategy that will return a report class. The engine
+# will call this function with the main dataframe and each index
+def strategy(dataframe, index):
+    # first, there's our buy condition
+    if dataframe["EMA3"][index] >= dataframe["EMA100"][index]:
+        # we return a report with the order_type and the amount in percent of our coin wallet we want to buy
+        return Report("buy", percent_amount=100)
+    # then, there's our sell condition
+    if dataframe["EMA3"][index] <= dataframe["EMA100"][index]:
+        # we return a report with the order_type and the amount in percent of our token wallet we want to sell
+        return Report("sell", percent_amount=100)
+
+
+# ------------------------------------------------------------------
+# The let's run our backtest !
+# ------------------------------------------------------------------
+
+# This function is used to register our strategy
+engine.register_strategy(strategy)
+
+# This function is used to run the backtest, first parameter is the coin name, second is the token name, third
+# is your initial coin balance 4th is your initial token balance 5th is your taker fees in percent
+engine.run_strategy(coin_name="USDT", token_name="ETH", coin_balance=1000, token_balance=0, taker=0.075)
+
+# We use this function to summarize and display the result of our backtest
+engine.wallet.get_data_handler().display_wallet()
+
+# And we finally use it to plot graphs of price and balance evolution, you can use the parameter size=... to set the
+# points size and the parameter tradeline=False to disable trade lines
+engine.wallet.get_data_handler().plot_wallet()
+
+# -----------------------------------------------------------------------------------------------------------------
+# And that's finish ! Hope you like and that it wasn't hard ! If you have any question dm me on discord: Shaft#3796
+# -----------------------------------------------------------------------------------------------------------------
+```
+
+<img src="https://cdn.discordapp.com/attachments/901790872033714216/908336432760889404/unknown.png" alt="drawing" width="800"/>
+<img src="https://cdn.discordapp.com/attachments/901790872033714216/908336484149510165/unknown.png" alt="drawing" width="800"/>
+<img src="https://cdn.discordapp.com/attachments/901790872033714216/908336590319943740/unknown.png" alt="drawing" width="1000"/>
+
+*Next part is coming soon*
+
+
+
+
+%prep
+%autosetup -n open-backtest-7.0.0
+
+%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-open-backtest -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 7.0.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..30c71ee
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+3a0f8f4763390e7eba10760c4fc1bd53  open-backtest-7.0.0.tar.gz