Improve application workflow and control flow
This commit is contained in:
yagudin
parent
192c2c6037
commit
b86157e592
106
strmlt.py
106
strmlt.py
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@ -65,58 +65,68 @@ if __name__ == "__main__":
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curl_value = """curl 'https://www.gjopen.com/' \\
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-H 'authority: www.gjopen.com' \\
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-H 'cache-control: max-age=0' \\
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-H 'sec-ch-ua: " Not A;Brand";v="99", "Chromium";v="90", "Google Chrome";v="90"' \\
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-H 'sec-ch-ua: "something-something-about-your-browser"' \\
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-H 'sec-ch-ua-mobile: ?0' \\
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-H 'dnt: 1' \\
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-H 'upgrade-insecure-requests: 1' \
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-H 'user-agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.212 Safari/537.36' \
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-H 'accept: text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9' \
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-H 'user-agent: Mozilla/5.0 something-something-about-your-PC' \
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-H 'accept: text/html...' \
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-H 'sec-fetch-site: none' \\
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-H 'sec-fetch-mode: navigate' \\
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-H 'sec-fetch-user: ?1' \\
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-H 'sec-fetch-dest: document' \
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-H 'sec-fetch-dest: document' \\
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-H 'accept-language: en-US,en;q=0.9,ru;q=0.8' \\
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-H 'cookie: a-very-long-mysterious-string' \\
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--compressed"""
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curl_command = st.text_area(
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"Ugh... Gimme your cURL info...", value=curl_value
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"Om Nom Nom Nom... Paste cURL here, if confued see the sidebar for the instrucitons.", value=curl_value
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)
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curl_command = "".join(curl_command.split("\\\n"))
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if curl_command != curl_value:
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if curl_command == curl_value:
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st.warning('Please input your cURL (see the sidebar for instrucitons :-) ')
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st.stop()
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try:
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curl_command = curl_command.replace("\\", "")
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curl_content = uncurl.parse_context(curl_command)
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headers, cookies = curl_content.headers, curl_content.cookies
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except SystemExit:
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st.warning("It seems like something is wrong with the cURL you provided: see the sidebar for the instrucitons.")
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st.stop()
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# ---
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# ---
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with st.spinner('Loading resolved questions...'):
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questions = get_resolved_questions(uid, platform_url, headers, cookies)
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st.write(f"{len(questions)} questions you forecasted on have resolved.")
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st.write(f"- {len(questions)} questions you forecasted on have resolved.")
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# ---
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# TODO: Make a progress bar..?
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# ---
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# TODO: Make a progress bar..?
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with st.spinner('Loading your forecasts...'):
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forecasts = get_forecasts(uid, questions, platform_url, headers, cookies)
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with st.spinner("Loading questions's resolutions..."):
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resolutions = get_resolutions(questions, platform_url, headers, cookies)
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# ---
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# ---
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num_forecasts = sum(len(f) for f in forecasts.values())
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st.write(
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f"On these {len(questions)} questions you've made {num_forecasts} forecasts."
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)
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num_forecasts = sum(len(f) for f in forecasts.values())
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st.write(
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f"- You've made {num_forecasts} forecasts on these {len(questions)} questions."
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)
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flatten = lambda t: [item for sublist in t for item in sublist]
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y_true = flatten(resolutions[q]["y_true"] for q in questions for _ in forecasts[q])
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y_pred = flatten(f["y_pred"] for q in questions for f in forecasts[q])
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flatten = lambda t: [item for sublist in t for item in sublist]
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# y_true = flatten(resolutions[q]["y_true"] for q in questions for _ in forecasts[q])
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# y_pred = flatten(f["y_pred"] for q in questions for f in forecasts[q])
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# Note that I am "double counting" each prediction.
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if st.checkbox("Drop last"):
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y_true = flatten(
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resolutions[q]["y_true"][:-1] for q in questions for _ in forecasts[q]
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)
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y_pred = flatten(f["y_pred"][:-1] for q in questions for f in forecasts[q])
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# Note that I am "double counting" each prediction.
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# if st.checkbox("Drop last"):
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y_true = flatten(
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resolutions[q]["y_true"][:-1] for q in questions for _ in forecasts[q]
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)
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y_pred = flatten(f["y_pred"][:-1] for q in questions for f in forecasts[q])
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y_true, y_pred = np.array(y_true), np.array(y_pred)
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@ -124,27 +134,37 @@ if __name__ == "__main__":
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np.random.default_rng(0).shuffle(order)
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y_true, y_pred = y_true[order], y_pred[order]
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# ---
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strategy = st.selectbox(
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"Which binning stranegy do you prefer?",
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["uniform", "quantile"],
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)
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st.write(f"- Which gives us {len(y_pred)} datapoints to work with.")
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recommended_n_bins = int(np.sqrt(len(y_pred))) if strategy == "quantile" else 20 + 1
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n_bins = st.number_input(
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"How many bins do you want me to display?",
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min_value=1,
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value=recommended_n_bins,
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)
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# ---
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fig = plotly_calibration(y_true, y_pred, n_bins=n_bins, strategy=strategy)
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st.plotly_chart(fig, use_container_width=True)
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strategy_select = st.selectbox(
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"Which binning stranegy do you prefer?",
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[
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"I want bins to have identical widths",
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"I want bins to have the same number of samples",
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],
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)
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strategy = {
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"I want bins to have identical widths": "uniform",
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"I want bins to have the same number of samples": "quantile",
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}[strategy_select]
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overconf = overconfidence(y_true, y_pred)
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st.write(f"Your over/under- confidence score is {overconf:.2f}.")
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recommended_n_bins = int(np.sqrt(len(y_pred))) if strategy == "quantile" else 20 + 1
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n_bins = st.number_input(
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"How many bins do you want me to display?",
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min_value=1,
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value=recommended_n_bins,
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)
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# ---
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# ---
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fig = plotly_calibration_odds(y_true, y_pred, n_bins=n_bins, strategy=strategy)
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st.plotly_chart(fig, use_container_width=True)
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fig = plotly_calibration(y_true, y_pred, n_bins=n_bins, strategy=strategy)
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st.plotly_chart(fig, use_container_width=True)
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fig = plotly_calibration_odds(y_true, y_pred, n_bins=n_bins, strategy=strategy)
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st.plotly_chart(fig, use_container_width=True)
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# overconf = overconfidence(y_true, y_pred)
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# st.write(f"Your over/under- confidence score is {overconf:.2f}.")
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