update

AppZoo.py

@@ -0,0 +1,20 @@
+import streamlit as st
+
+
+def run():
+    st.set_page_config(
+        page_title="Hello",
+        page_icon="👋",
+    )
+
+    st.write("# Welcome to AppZoo! 👋")
+
+    st.markdown(
+        """
+        > 应用集合
+        """
+    )
+
+
+if __name__ == "__main__":
+    run()

README.md

@@ -5,7 +5,7 @@ colorFrom: green
 colorTo: gray
 sdk: streamlit
 sdk_version: 1.10.0
-app_file: app.py
+app_file: AppZoo.py
 pinned: true
 license: mit
 ---

app.py

@@ -1,51 +0,0 @@
-# Copyright 2018-2022 Streamlit Inc.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#    http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import streamlit as st
-from streamlit.logger import get_logger
-
-LOGGER = get_logger(__name__)
-
-
-def run():
-    st.set_page_config(
-        page_title="Hello",
-        page_icon="👋",
-    )
-
-    st.write("# Welcome to Streamlit! 👋")
-
-    st.sidebar.success("Select a demo above.")
-
-    st.markdown(
-        """
-        Streamlit is an open-source app framework built specifically for
-        Machine Learning and Data Science projects.
-        **👈 Select a demo from the sidebar** to see some examples
-        of what Streamlit can do!
-        ### Want to learn more?
-        - Check out [streamlit.io](https://streamlit.io)
-        - Jump into our [documentation](https://docs.streamlit.io)
-        - Ask a question in our [community
-          forums](https://discuss.streamlit.io)
-        ### See more complex demos
-        - Use a neural net to [analyze the Udacity Self-driving Car Image
-          Dataset](https://github.com/streamlit/demo-self-driving)
-        - Explore a [New York City rideshare dataset](https://github.com/streamlit/demo-uber-nyc-pickups)
-    """
-    )
-
-
-if __name__ == "__main__":
-    run()

data/lr.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5a25d13f7011117e75f4cdb5f50181519adb93f248f759aa6c79bb7354c340d9
+size 771

git_init.sh

@@ -1,5 +1,7 @@
 #!/usr/bin/env bash
 
+#git config --global credential.helper store
+
 git add *
 git commit -m "update"
 

pages/1_🔥_模型生成代码.py

@@ -0,0 +1,55 @@
+from meutils.pipe import *
+from appzoo.streamlit_app import Page
+
+import m2cgen as m2c
+import streamlit as st
+
+
+class MyPage(Page):
+
+    def main(self):
+        file = st.file_uploader('上传默模型文件')
+        if file:
+            estimator = joblib.load(file)
+        else:
+            estimator = joblib.load(get_resolve_path('../data/lr.pkl', __file__))
+
+        languages = [
+            'python',
+            'java',
+            'go',
+            'c',
+            'c_sharp',
+            'r',
+            'dart',
+            'elixir',
+            'f_sharp',
+            'haskell',
+            'javascript',
+            'php',
+            'powershell',
+            'ruby',
+            'rust',
+            'visual_basi'
+        ]
+
+        _ = st.selectbox('选择输出语言', languages)
+
+        if st.button('开始转换'):
+            code = m2c.__getattribute__(f'export_to_{_}')(estimator)
+
+            st.markdown("##### code:")
+            st.text(code)
+
+
+
+if __name__ == '__main__':
+    app_title = "ModelToCode"
+    app_info = """
+    将训练过的统计模型转化为本地代码(`Python, C, Java, Go, JavaScript, Visual Basic, c#， PowerShell, R, PHP, Dart, Haskell, Ruby, f#， Rust, Elixir`)。
+    """
+    MyPage(
+        app_title=f"# {app_title}",
+        app_info=f"> {app_info}",
+        sidebar_title=None,
+    ).main()

pages/1_🔥_食品安全比赛提交.py

@@ -1,24 +0,0 @@
-import paramiko
-from meutils.pipe import *
-import streamlit as st
-
-host = 'sftp.ai.xm.gov.cn'  # 主机
-port = 57891  # 端口
-sf = paramiko.Transport((host, port))
-
-username = st.text_input('username', 'comp_5154')  # 用户名
-password = st.text_input('password')  # 密码
-
-
-uploaded_file = st.file_uploader("上传文件")
-if uploaded_file is not None and password:
-    df = pd.read_csv(uploaded_file, '|', header=0)
-    df.to_csv('result.txt', '|',index=False)
-
-    sf.connect(username=username, password=password)
-    sftp = paramiko.SFTPClient.from_transport(sf)
-
-    _ = sftp.put('result.txt', '/result/result.txt')
-    st.write(_)
-
-    st.write(df)

requirements.txt

@@ -1,2 +1,3 @@
 meutils
-paramiko
+
+m2cgen

run.sh

@@ -6,7 +6,5 @@
 # @Software     : PyCharm
 # @Description  : ${DESCRIPTION}
 
-#streamlit run mapps.py
-#streamlit-launchpad ./examples
-streamlit run app.py
+streamlit run AppZoo.py