import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter

import requests


def get_job_links(workflow_run_id, token=None):
    """Extract job names and their job links in a GitHub Actions workflow run"""

    headers = None
    if token is not None:
        headers = {"Accept": "application/vnd.github+json", "Authorization": f"Bearer {token}"}

    url = f"https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100"
    result = requests.get(url, headers=headers).json()
    job_links = {}

    try:
        job_links.update({job["name"]: job["html_url"] for job in result["jobs"]})
        pages_to_iterate_over = math.ceil((result["total_count"] - 100) / 100)

        for i in range(pages_to_iterate_over):
            result = requests.get(url + f"&page={i + 2}", headers=headers).json()
            job_links.update({job["name"]: job["html_url"] for job in result["jobs"]})

        return job_links
    except Exception:
        print(f"Unknown error, could not fetch links:\n{traceback.format_exc()}")

    return {}


def get_artifacts_links(worflow_run_id, token=None):
    """Get all artifact links from a workflow run"""

    headers = None
    if token is not None:
        headers = {"Accept": "application/vnd.github+json", "Authorization": f"Bearer {token}"}

    url = f"https://api.github.com/repos/huggingface/transformers/actions/runs/{worflow_run_id}/artifacts?per_page=100"
    result = requests.get(url, headers=headers).json()
    artifacts = {}

    try:
        artifacts.update({artifact["name"]: artifact["archive_download_url"] for artifact in result["artifacts"]})
        pages_to_iterate_over = math.ceil((result["total_count"] - 100) / 100)

        for i in range(pages_to_iterate_over):
            result = requests.get(url + f"&page={i + 2}", headers=headers).json()
            artifacts.update({artifact["name"]: artifact["archive_download_url"] for artifact in result["artifacts"]})

        return artifacts
    except Exception:
        print(f"Unknown error, could not fetch links:\n{traceback.format_exc()}")

    return {}


def download_artifact(artifact_name, artifact_url, output_dir, token):
    """Download a GitHub Action artifact from a URL.

    The URL is of the form `https://api.github.com/repos/huggingface/transformers/actions/artifacts/{ARTIFACT_ID}/zip`,
    but it can't be used to download directly. We need to get a redirect URL first.
    See https://docs.github.com/en/rest/actions/artifacts#download-an-artifact
    """
    headers = None
    if token is not None:
        headers = {"Accept": "application/vnd.github+json", "Authorization": f"Bearer {token}"}

    result = requests.get(artifact_url, headers=headers, allow_redirects=False)
    download_url = result.headers["Location"]
    response = requests.get(download_url, allow_redirects=True)
    file_path = os.path.join(output_dir, f"{artifact_name}.zip")
    with open(file_path, "wb") as fp:
        fp.write(response.content)


def get_errors_from_single_artifact(artifact_zip_path, job_links=None):
    """Extract errors from a downloaded artifact (in .zip format)"""
    errors = []
    failed_tests = []
    job_name = None

    with zipfile.ZipFile(artifact_zip_path) as z:
        for filename in z.namelist():
            if not os.path.isdir(filename):
                # read the file
                if filename in ["failures_line.txt", "summary_short.txt", "job_name.txt"]:
                    with z.open(filename) as f:
                        for line in f:
                            line = line.decode("UTF-8").strip()
                            if filename == "failures_line.txt":
                                try:
                                    # `error_line` is the place where `error` occurs
                                    error_line = line[: line.index(": ")]
                                    error = line[line.index(": ") + len(": ") :]
                                    errors.append([error_line, error])
                                except Exception:
                                    # skip un-related lines
                                    pass
                            elif filename == "summary_short.txt" and line.startswith("FAILED "):
                                # `test` is the test method that failed
                                test = line[len("FAILED ") :]
                                failed_tests.append(test)
                            elif filename == "job_name.txt":
                                job_name = line

    if len(errors) != len(failed_tests):
        raise ValueError(
            f"`errors` and `failed_tests` should have the same number of elements. Got {len(errors)} for `errors` "
            f"and {len(failed_tests)} for `failed_tests` instead. The test reports in {artifact_zip_path} have some"
            " problem."
        )

    job_link = None
    if job_name and job_links:
        job_link = job_links.get(job_name, None)

    # A list with elements of the form (line of error, error, failed test)
    result = [x + [y] + [job_link] for x, y in zip(errors, failed_tests)]

    return result


def get_all_errors(artifact_dir, job_links=None):
    """Extract errors from all artifact files"""

    errors = []

    paths = [os.path.join(artifact_dir, p) for p in os.listdir(artifact_dir) if p.endswith(".zip")]
    for p in paths:
        errors.extend(get_errors_from_single_artifact(p, job_links=job_links))

    return errors


def reduce_by_error(logs, error_filter=None):
    """count each error"""

    counter = Counter()
    counter.update([x[1] for x in logs])
    counts = counter.most_common()
    r = {}
    for error, count in counts:
        if error_filter is None or error not in error_filter:
            r[error] = {"count": count, "failed_tests": [(x[2], x[0]) for x in logs if x[1] == error]}

    r = dict(sorted(r.items(), key=lambda item: item[1]["count"], reverse=True))
    return r


def get_model(test):
    """Get the model name from a test method"""
    test = test.split("::")[0]
    if test.startswith("tests/models/"):
        test = test.split("/")[2]
    else:
        test = None

    return test


def reduce_by_model(logs, error_filter=None):
    """count each error per model"""

    logs = [(x[0], x[1], get_model(x[2])) for x in logs]
    logs = [x for x in logs if x[2] is not None]
    tests = {x[2] for x in logs}

    r = {}
    for test in tests:
        counter = Counter()
        # count by errors in `test`
        counter.update([x[1] for x in logs if x[2] == test])
        counts = counter.most_common()
        error_counts = {error: count for error, count in counts if (error_filter is None or error not in error_filter)}
        n_errors = sum(error_counts.values())
        if n_errors > 0:
            r[test] = {"count": n_errors, "errors": error_counts}

    r = dict(sorted(r.items(), key=lambda item: item[1]["count"], reverse=True))
    return r


def make_github_table(reduced_by_error):
    header = "| no. | error | status |"
    sep = "|-:|:-|:-|"
    lines = [header, sep]
    for error in reduced_by_error:
        count = reduced_by_error[error]["count"]
        line = f"| {count} | {error[:100]} |  |"
        lines.append(line)

    return "\n".join(lines)


def make_github_table_per_model(reduced_by_model):
    header = "| model | no. of errors | major error | count |"
    sep = "|-:|-:|-:|-:|"
    lines = [header, sep]
    for model in reduced_by_model:
        count = reduced_by_model[model]["count"]
        error, _count = list(reduced_by_model[model]["errors"].items())[0]
        line = f"| {model} | {count} | {error[:60]} | {_count} |"
        lines.append(line)

    return "\n".join(lines)


if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    # Required parameters
    parser.add_argument("--workflow_run_id", type=str, required=True, help="A GitHub Actions workflow run id.")
    parser.add_argument(
        "--output_dir",
        type=str,
        required=True,
        help="Where to store the downloaded artifacts and other result files.",
    )
    parser.add_argument("--token", default=None, type=str, help="A token that has actions:read permission.")
    args = parser.parse_args()

    os.makedirs(args.output_dir, exist_ok=True)

    _job_links = get_job_links(args.workflow_run_id, token=args.token)
    job_links = {}
    # To deal with `workflow_call` event, where a job name is the combination of the job names in the caller and callee.
    # For example, `PyTorch 1.11 / Model tests (models/albert, single-gpu)`.
    if _job_links:
        for k, v in _job_links.items():
            # This is how GitHub actions combine job names.
            if " / " in k:
                index = k.find(" / ")
                k = k[index + len(" / ") :]
            job_links[k] = v
    with open(os.path.join(args.output_dir, "job_links.json"), "w", encoding="UTF-8") as fp:
        json.dump(job_links, fp, ensure_ascii=False, indent=4)

    artifacts = get_artifacts_links(args.workflow_run_id, token=args.token)
    with open(os.path.join(args.output_dir, "artifacts.json"), "w", encoding="UTF-8") as fp:
        json.dump(artifacts, fp, ensure_ascii=False, indent=4)

    for idx, (name, url) in enumerate(artifacts.items()):
        download_artifact(name, url, args.output_dir, args.token)
        # Be gentle to GitHub
        time.sleep(1)

    errors = get_all_errors(args.output_dir, job_links=job_links)

    # `e[1]` is the error
    counter = Counter()
    counter.update([e[1] for e in errors])

    # print the top 30 most common test errors
    most_common = counter.most_common(30)
    for item in most_common:
        print(item)

    with open(os.path.join(args.output_dir, "errors.json"), "w", encoding="UTF-8") as fp:
        json.dump(errors, fp, ensure_ascii=False, indent=4)

    reduced_by_error = reduce_by_error(errors)
    reduced_by_model = reduce_by_model(errors)

    s1 = make_github_table(reduced_by_error)
    s2 = make_github_table_per_model(reduced_by_model)

    with open(os.path.join(args.output_dir, "reduced_by_error.txt"), "w", encoding="UTF-8") as fp:
        fp.write(s1)
    with open(os.path.join(args.output_dir, "reduced_by_model.txt"), "w", encoding="UTF-8") as fp:
        fp.write(s2)
