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トップに関する質問【Python・streamlit】Herokuに公開したいけど、アプリが表示されない。

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3

質問を編集しました。

2021/12/30 07:48

投稿

Shuri31
Shuri31

スコア1

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  ![イメージ説明](9ba15e0e5b96ea8f8d87fa6cd225b642.png)
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- ### 該当のソースコード
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-
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- ```python
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- import streamlit as st
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- import numpy as np
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- import pandas as pd
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- import sklearn
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- from sklearn.ensemble import RandomForestRegressor
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- from sklearn.metrics import mean_squared_error
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-
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-
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- st.title("応募用紙に対する応募数を予測する")
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-
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- #回帰モデルの作成
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-
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- #データの読み込み
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- train_y = pd.read_csv("train_y.csv", encoding="utf-8")
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- train_X = pd.read_csv("train_x.csv", encoding="utf-8")
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-
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- #train_y["No."]をdropする
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- train_y = train_y.drop(["No."], axis=1)
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-
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- #train_xのデータ整形（空白だけ・不要？なカラムの削除）
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- train_X = train_X.dropna(axis=1, how='all')
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- train_X = train_X.fillna(0)
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- train_X = train_X.drop(["掲載期間　開始日", "掲載期間　終了日"], axis=1)
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-
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- #train_yとtrain_Xを連結して学習データとして利用する
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- train = pd.concat([train_y.reset_index(drop=True), train_X.reset_index(drop=True)], axis=1)
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-
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- #データ変換と分割
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- y = train["応募数 合計"]
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- X = train.drop(["No.", "応募数 合計"], axis=1)
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-
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- y_array = np.array(y)
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- X_array = np.array(X)
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-
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- #文章のデータ整形が難しかったので、文章のカラムを一括に学習データから外します。
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- X_array = X.select_dtypes(exclude="object")
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-
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- from sklearn.model_selection import train_test_split
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- X_train, X_test, y_train, y_test = train_test_split(X_array, y_array, test_size=0.4, random_state=0)
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-
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- #回帰モデル作成
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- rfr = RandomForestRegressor(random_state=0)
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- rfr.fit(X_train, y_train)
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-
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- y_pred = rfr.predict(X_test)
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- # print(y_pred.shape)
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-
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- mse = np.sqrt(mean_squared_error(y_pred, y_test))
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- st.write(f"Mean Squared Error:{mse:.3}")
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-
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- #ファイルがアップロードされるまでの処理を書く
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- uploaded_file = st.file_uploader("Choose a file", type=["csv"])
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-
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- if uploaded_file is not None:
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- test_X = pd.read_csv(uploaded_file).dropna(axis=1, how="all").fillna(0)
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-
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- #応募数合計の予測をするためのデータ成形
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- test_X = test_X.drop(["掲載期間　開始日", "掲載期間　終了日"], axis=1)
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-
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- #文章のデータ整形が難しかったので、文章のカラムを一括に学習データから外します。
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- test_X2 = test_X.drop(["No."], axis=1)
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- test_X2 = test_X2.select_dtypes(exclude="object")
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-
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- #応募数合計の予測・データの予測
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- test_pred = rfr.predict(test_X2)
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- print(test_pred.shape)
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-
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- test_pred = pd.DataFrame(test_pred, columns=["応募数 合計"])
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- result = pd.concat([test_X["No."], test_pred], axis=1)
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- result = result.reset_index(drop=True)
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-
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- st.dataframe(result)
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- st.download_button(label = '予測結果をダウンロード', data=result.to_csv(index=False).encode('utf-8'), file_name="result.csv")
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- ```
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-
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- ```.gitignore
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- *.csv
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- ```
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-
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- ```Herokuのログ
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- 2021-12-29T08:58:33.633044+00:00 app[worker.1]: streamlit run main.py [ARGUMENTS]
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- 2021-12-29T08:58:33.633698+00:00 app[worker.1]: Traceback (most recent call last):
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- 2021-12-29T08:58:33.633702+00:00 app[worker.1]: File "/app/main.py", line 19, in <module>
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- 2021-12-29T08:58:33.633849+00:00 app[worker.1]: train_y = pd.read_csv("train_y.csv", encoding="utf-8")
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- 2021-12-29T08:58:33.633854+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/util/_decorators.py", line 311, in wrapper
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- 2021-12-29T08:58:33.633979+00:00 app[worker.1]: return func(*args, **kwargs)
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- 2021-12-29T08:58:33.633989+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 586, in read_csv
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- 2021-12-29T08:58:33.634151+00:00 app[worker.1]: return _read(filepath_or_buffer, kwds)
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- 2021-12-29T08:58:33.634161+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 482, in _read
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- 2021-12-29T08:58:33.634299+00:00 app[worker.1]: parser = TextFileReader(filepath_or_buffer, **kwds)
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- 2021-12-29T08:58:33.634309+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 811, in __init__
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- 2021-12-29T08:58:33.634517+00:00 app[worker.1]: self._engine = self._make_engine(self.engine)
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- 2021-12-29T08:58:33.634533+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1040, in _make_engine
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- 2021-12-29T08:58:33.634756+00:00 app[worker.1]: return mapping[engine](self.f, **self.options) # type: ignore[call-arg]
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- 2021-12-29T08:58:33.634758+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 51, in __init__
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- 2021-12-29T08:58:33.634832+00:00 app[worker.1]: self._open_handles(src, kwds)
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- 2021-12-29T08:58:33.634841+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/io/parsers/base_parser.py", line 222, in _open_handles
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- 2021-12-29T08:58:33.634933+00:00 app[worker.1]: self.handles = get_handle(
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- 2021-12-29T08:58:33.634943+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/io/common.py", line 702, in get_handle
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- 2021-12-29T08:58:33.635111+00:00 app[worker.1]: handle = open(
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- 2021-12-29T08:58:33.635145+00:00 app[worker.1]: FileNotFoundError: [Errno 2] No such file or directory: 'train_y.csv'
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- 2021-12-29T09:11:36.477338+00:00 heroku[worker.1]: State changed from crashed to starting
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- 2021-12-29T09:11:54.701484+00:00 heroku[worker.1]: Starting process with command `python main.py`
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- 2021-12-29T09:11:55.332453+00:00 heroku[worker.1]: State changed from starting to up
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- 2021-12-29T09:12:02.838739+00:00 heroku[worker.1]: Process exited with status 1
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- 2021-12-29T09:12:02.460135+00:00 app[worker.1]: 2021-12-29 09:12:02.459
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- 2021-12-29T09:12:02.460162+00:00 app[worker.1]: Warning: to view this Streamlit app on a browser, run it with the following
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- 2021-12-29T09:12:02.460163+00:00 app[worker.1]: command:
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- 2021-12-29T09:12:02.460163+00:00 app[worker.1]:
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- 2021-12-29T09:12:02.460163+00:00 app[worker.1]: streamlit run main.py [ARGUMENTS]
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- 2021-12-29T09:12:02.460876+00:00 app[worker.1]: Traceback (most recent call last):
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- 2021-12-29T09:12:02.460880+00:00 app[worker.1]: File "/app/main.py", line 19, in <module>
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- 2021-12-29T09:12:02.461008+00:00 app[worker.1]: train_y = pd.read_csv("train_y.csv", encoding="utf-8")
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- 2021-12-29T09:12:02.461021+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/util/_decorators.py", line 311, in wrapper
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- 2021-12-29T09:12:02.461149+00:00 app[worker.1]: return func(*args, **kwargs)
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- 2021-12-29T09:12:02.461157+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 586, in read_csv
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- 2021-12-29T09:12:02.461313+00:00 app[worker.1]: return _read(filepath_or_buffer, kwds)
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- 2021-12-29T09:12:02.461322+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 482, in _read
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- 2021-12-29T09:12:02.461506+00:00 app[worker.1]: parser = TextFileReader(filepath_or_buffer, **kwds)
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- 2021-12-29T09:12:02.461508+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 811, in __init__
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- 2021-12-29T09:12:02.463039+00:00 app[worker.1]: self._engine = self._make_engine(self.engine)
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- 2021-12-29T09:12:02.463051+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1040, in _make_engine
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- 2021-12-29T09:12:02.463055+00:00 app[worker.1]: return mapping[engine](self.f, **self.options) # type: ignore[call-arg]
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- 2021-12-29T09:12:02.463056+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 51, in __init__
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- 2021-12-29T09:12:02.463056+00:00 app[worker.1]: self._open_handles(src, kwds)
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- 2021-12-29T09:12:02.463056+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/io/parsers/base_parser.py", line 222, in _open_handles
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- 2021-12-29T09:12:02.463057+00:00 app[worker.1]: self.handles = get_handle(
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- 2021-12-29T09:12:02.463057+00:00 app[worker.1]: File "/app/.heroku/python/lib/python3.9/site-packages/pandas/io/common.py", line 702, in get_handle
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- 2021-12-29T09:12:02.463058+00:00 app[worker.1]: handle = open(
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- 2021-12-29T09:12:02.463058+00:00 app[worker.1]: FileNotFoundError: [Errno 2] No such file or directory: 'train_y.csv'
144
- 2021-12-29T09:12:02.901159+00:00 heroku[worker.1]: State changed from up to crashed
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- 2021-12-29T09:16:50.750172+00:00 heroku[router]: at=error code=H14 desc="No web processes running" method=GET path="/" host=dip-intern-asaitodev.herokuapp.com request_id=1d035980-620b-4c62-aaaf-b16be9ce2c11 fwd="92.202.111.147" dyno= connect= service= status=503 bytes= protocol=https
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- 2021-12-29T09:16:51.189584+00:00 heroku[router]: at=error code=H14 desc="No web processes running" method=GET path="/favicon.ico" host=dip-intern-asaitodev.herokuapp.com request_id=3e6e253c-7beb-4d7a-a00d-819c15311d4f fwd="92.202.111.147" dyno= connect= service= status=503 bytes= protocol=https
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- ```
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-
149
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  ### 試したこと
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151
13
  ①code=14ということなので↓を記述

2

.gitignoreを追加しました！

2021/12/30 07:48

投稿

Shuri31
Shuri31

スコア1

title CHANGED
File without changes
body CHANGED
@@ -86,6 +86,10 @@
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86
  st.download_button(label = '予測結果をダウンロード', data=result.to_csv(index=False).encode('utf-8'), file_name="result.csv")
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87
  ```
88
88
 
89
+ ```.gitignore
90
+ *.csv
91
+ ```
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+
89
93
  ```Herokuのログ
90
94
  2021-12-29T08:58:33.633044+00:00 app[worker.1]: streamlit run main.py [ARGUMENTS]
91
95
  2021-12-29T08:58:33.633698+00:00 app[worker.1]: Traceback (most recent call last):

1

動かしたいアプリのコードを掲載しました。

2021/12/29 13:58

投稿

Shuri31
Shuri31

スコア1

title CHANGED
File without changes
body CHANGED
@@ -10,7 +10,83 @@
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10
 
11
11
  ### 該当のソースコード
12
12
 
13
- ```bash
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+ ```python
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+ import streamlit as st
15
+ import numpy as np
16
+ import pandas as pd
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+ import sklearn
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+ from sklearn.ensemble import RandomForestRegressor
19
+ from sklearn.metrics import mean_squared_error
20
+
21
+
22
+ st.title("応募用紙に対する応募数を予測する")
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+
24
+ #回帰モデルの作成
25
+
26
+ #データの読み込み
27
+ train_y = pd.read_csv("train_y.csv", encoding="utf-8")
28
+ train_X = pd.read_csv("train_x.csv", encoding="utf-8")
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+
30
+ #train_y["No."]をdropする
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+ train_y = train_y.drop(["No."], axis=1)
32
+
33
+ #train_xのデータ整形（空白だけ・不要？なカラムの削除）
34
+ train_X = train_X.dropna(axis=1, how='all')
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+ train_X = train_X.fillna(0)
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+ train_X = train_X.drop(["掲載期間　開始日", "掲載期間　終了日"], axis=1)
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+
38
+ #train_yとtrain_Xを連結して学習データとして利用する
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+ train = pd.concat([train_y.reset_index(drop=True), train_X.reset_index(drop=True)], axis=1)
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+
41
+ #データ変換と分割
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+ y = train["応募数 合計"]
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+ X = train.drop(["No.", "応募数 合計"], axis=1)
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+
45
+ y_array = np.array(y)
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+ X_array = np.array(X)
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+
48
+ #文章のデータ整形が難しかったので、文章のカラムを一括に学習データから外します。
49
+ X_array = X.select_dtypes(exclude="object")
50
+
51
+ from sklearn.model_selection import train_test_split
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+ X_train, X_test, y_train, y_test = train_test_split(X_array, y_array, test_size=0.4, random_state=0)
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+
54
+ #回帰モデル作成
55
+ rfr = RandomForestRegressor(random_state=0)
56
+ rfr.fit(X_train, y_train)
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+
58
+ y_pred = rfr.predict(X_test)
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+ # print(y_pred.shape)
60
+
61
+ mse = np.sqrt(mean_squared_error(y_pred, y_test))
62
+ st.write(f"Mean Squared Error:{mse:.3}")
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+
64
+ #ファイルがアップロードされるまでの処理を書く
65
+ uploaded_file = st.file_uploader("Choose a file", type=["csv"])
66
+
67
+ if uploaded_file is not None:
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+ test_X = pd.read_csv(uploaded_file).dropna(axis=1, how="all").fillna(0)
69
+
70
+ #応募数合計の予測をするためのデータ成形
71
+ test_X = test_X.drop(["掲載期間　開始日", "掲載期間　終了日"], axis=1)
72
+
73
+ #文章のデータ整形が難しかったので、文章のカラムを一括に学習データから外します。
74
+ test_X2 = test_X.drop(["No."], axis=1)
75
+ test_X2 = test_X2.select_dtypes(exclude="object")
76
+
77
+ #応募数合計の予測・データの予測
78
+ test_pred = rfr.predict(test_X2)
79
+ print(test_pred.shape)
80
+
81
+ test_pred = pd.DataFrame(test_pred, columns=["応募数 合計"])
82
+ result = pd.concat([test_X["No."], test_pred], axis=1)
83
+ result = result.reset_index(drop=True)
84
+
85
+ st.dataframe(result)
86
+ st.download_button(label = '予測結果をダウンロード', data=result.to_csv(index=False).encode('utf-8'), file_name="result.csv")
87
+ ```
88
+
89
+ ```Herokuのログ
14
90
  2021-12-29T08:58:33.633044+00:00 app[worker.1]: streamlit run main.py [ARGUMENTS]
15
91
  2021-12-29T08:58:33.633698+00:00 app[worker.1]: Traceback (most recent call last):
16
92
  2021-12-29T08:58:33.633702+00:00 app[worker.1]: File "/app/main.py", line 19, in <module>