├── .gitignore ├── LICENSE ├── README.md ├── main.py └── 行政区划乡镇清单201910.xlsx /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; otherwise, check them in: 88 | # .python-version 89 | 90 | # pipenv 91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 94 | # install all needed dependencies. 95 | #Pipfile.lock 96 | 97 | # poetry 98 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. 99 | # This is especially recommended for binary packages to ensure reproducibility, and is more 100 | # commonly ignored for libraries. 101 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control 102 | #poetry.lock 103 | 104 | # pdm 105 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. 106 | #pdm.lock 107 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it 108 | # in version control. 109 | # https://pdm.fming.dev/#use-with-ide 110 | .pdm.toml 111 | 112 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm 113 | __pypackages__/ 114 | 115 | # Celery stuff 116 | celerybeat-schedule 117 | celerybeat.pid 118 | 119 | # SageMath parsed files 120 | *.sage.py 121 | 122 | # Environments 123 | .env 124 | .venv 125 | env/ 126 | venv/ 127 | ENV/ 128 | env.bak/ 129 | venv.bak/ 130 | 131 | # Spyder project settings 132 | .spyderproject 133 | .spyproject 134 | 135 | # Rope project settings 136 | .ropeproject 137 | 138 | # mkdocs documentation 139 | /site 140 | 141 | # mypy 142 | .mypy_cache/ 143 | .dmypy.json 144 | dmypy.json 145 | 146 | # Pyre type checker 147 | .pyre/ 148 | 149 | # pytype static type analyzer 150 | .pytype/ 151 | 152 | # Cython debug symbols 153 | cython_debug/ 154 | 155 | # PyCharm 156 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can 157 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore 158 | # and can be added to the global gitignore or merged into this file. 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It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # 百度迁徙平台数据获取 2 | 3 | [百度迁徙平台](http://qianxi.baidu.com/#/)（百度慧眼）几乎是日前最具有参考价值的中国人口迁徙数据，许多论文以此为数据基础。但在其官网上既没有展示**所有的**数据，也没有提他们有公开的接口，只有一句“获取详情数据请点击[联系我们](https://huiyan.baidu.com/contact?article=qianxi)”。实际上除了没有给出公开的文档以外，百度迁徙平台不仅留了免费的接口，还能获取**几乎所有的**数据。~~感觉百度的意思就是：你有能力爬，我们愿意把数据给你；你没能力爬，那就花钱找我们要。~~ 2024 年初 GitHub 上没有仍然在更新的、满足相同需求的代码，我们尝试抛砖引玉补齐这些，并整理好信息为后来人提供帮助。 4 | 5 | 2024.12.6 对代码进行了测试，似乎仍有效。 6 | 7 | **注：似乎部分日期的部分数据缺失。如果不幸通过本仓库的方法获取到的数据中，您需要的日期刚好没有数据，也许可以尝试直接联系百度迁徙获得……** 8 | 9 | ## 接口 10 | 11 | 以下面的接口为例。 12 | 13 | http://huiyan.baidu.com/migration/cityrank.jsonp?dt=province&id=330000&type=move_in&callback=jsonp_1581412681419_9173670 14 | 15 | 其中 `cityrank`（`/migration/` 后、`.jsonp` 前） 处的可选项一共有四个：`cityrank`、`provincerank`、`lastdate`、`historycurve`。其中 `historycurve` 比较特殊，直接返回历史上所有日期的数据。 16 | 17 | ## 参数 18 | 19 | 请参考 `main.py` 中的注释。以下给出简要说明： 20 | 21 | `dt`：级别。可选的值有：`country`、`province`、`city`。 22 | 23 | `id`：六位数，代表区域（可以是省，也可以是市），如：360100。如果是 dt 是 country，不需要给这个参数。 24 | 25 | `type`: `move_in`, `move_out` 分别代表迁入迁出数据。 26 | 27 | `date`: 长度为8、格式为年月日的日期，如：`20240130`。如果接口是 `historycurve`，不需要给这个参数。 28 | 29 | `callback`: 时间戳，他调取的时候格式为：`jsonp_X_Y`，其中 X 经实验为 13 位的毫秒级时间戳，Y是7位数字，估计是更精确的时间。爬取的时候甚至不需要填写这个。它只是代表“我给你返回的数据确实是你这次获取的数据”。 30 | 31 | ## 代码 32 | 33 | 运行`main.py`，查找“请修改这里”，并修改这些地方为你所需要的数据即可。所有爬到的 json 数据会保存在`./data/`下面。如果需要改为其他的格式（如 `csv`），可以在代码中操作 `json_data`。 34 | 35 | ## 已知问题 36 | 37 | 1. 经反馈，由于当前版本的保存的目标路径是写死的（`./data/`），如果使用 Pytorch 等特殊环境可能会很难找到最后生成的文件到底在哪里。之后有时间可能会将这些改成一个变量方便修改。 38 | 39 | ## 遇到了问题…… 40 | 41 | 可以提 [Issue](https://github.com/baisebaoma/baiduqianxi/issues) 或 [发送邮件](mailto:baisebaoma@foxmail.com) 联系我。我更建议您提 Issue，这样其他人也可以看到并参与讨论您的问题！ 42 | 43 | ## Star History 44 | 45 | 如果您觉得有用，请点一个 Star！ 46 | 47 | [![Star History Chart](https://api.star-history.com/svg?repos=baisebaoma/baiduqianxi&type=Date)](https://star-history.com/#baisebaoma/baiduqianxi&Date) 48 | -------------------------------------------------------------------------------- /main.py: -------------------------------------------------------------------------------- 1 | import requests 2 | import json 3 | import re 4 | import time 5 | import os 6 | from datetime import datetime, timedelta 7 | import pandas as pd 8 | # import pyarrow 9 | 10 | 11 | # 用来把英文和数字翻译成中文存到文件名里。也许还有别的用途。 12 | translation_table = { 13 | 'lastdate': '最后日期', 14 | 'historycurve': '迁徙规模指数', 15 | 'cityrank': '市百分比', 16 | 'provincerank': '省百分比', 17 | 'country': '国家', 18 | 'province': '省', 19 | 'city': '市', 20 | 'move_in': '迁入', 21 | 'move_out': '迁出', 22 | 23 | # 如果你有其他省市数据需要获取，请修改这里 24 | '360000': '江西省', 25 | '360100': '南昌市', 26 | '360700': '赣州市', 27 | '360900': '宜春市', 28 | '360800': '吉安市', 29 | '361100': '上饶市', 30 | '361000': '抚州市', 31 | '360400': '九江市', 32 | '360200': '景德镇市', 33 | '360300': '萍乡市', 34 | '360500': '新余市', 35 | '360600': '鹰潭市', 36 | } 37 | 38 | 39 | class Types: 40 | """ 41 | 存储我们已知和要请求的一些数据。 42 | """ 43 | # 请不要修改data_type 44 | data_type = { # 'lastdate', # 虽然 lastdate 确实是一个接口，但是我们在每次爬取时 45 | # 只需在最开始调用一次就可以了。所以我们在设计时排除之。 46 | # 'historycurve', # 虽然 historycurve 确实是一个接口，但是这个接口会返回 47 | # 所有日期的这个数据。所以只用调用一次就可以了 48 | 'cityrank', 49 | 'provincerank'} 50 | # 请不要修改dt 51 | dt = {'country', 52 | 'province', 53 | 'city'} 54 | # 如果你有其他省市数据需要获取，请修改这里 55 | region = { 56 | # 使用Types.region.keys()来找到有哪些省份；使用Types.region["360000"]来查询它是省还是市。 57 | "360000": "province", 58 | '360100': 'city', 59 | '360700': 'city', 60 | '360900': 'city', 61 | '360800': 'city', 62 | '361100': 'city', 63 | '361000': 'city', 64 | '360400': 'city', 65 | '360200': 'city', 66 | '360300': 'city', 67 | '360500': 'city', 68 | '360600': 'city', 69 | } 70 | # 请不要修改move_type 71 | move_type = {'move_in', 72 | 'move_out'} 73 | 74 | 75 | def generate_date_range(start_date_str:str, end_date_str:str): 76 | """ 77 | 输入两端的日期，输出包括这两天在内的所有日期。 78 | 79 | :param start_date_str: 起始日期，长度为8、格式为年月日的字符串，如"20201231"。 80 | :param end_date_str: 结束日期，格式同上。 81 | :return: 一个list，包含从起始日期开始到结束日期为止的所有日期，格式同上。 82 | """ 83 | # 将输入的日期字符串转换为datetime对象 84 | start_date = datetime.strptime(start_date_str, '%Y%m%d') 85 | end_date = datetime.strptime(end_date_str, '%Y%m%d') 86 | 87 | # 初始化日期列表，包含起始日期 88 | date_list = [start_date.strftime('%Y%m%d')] 89 | 90 | # 生成日期范围 91 | current_date = start_date 92 | while current_date < end_date: 93 | current_date += timedelta(days=1) 94 | date_list.append(current_date.strftime('%Y%m%d')) 95 | 96 | return date_list 97 | 98 | 99 | def get_timestamp(): 100 | """ 101 | 获得当前时间戳。 102 | 103 | :return: 长度为13的时间戳 104 | """ 105 | return str(int(time.time() * 1000)) # * 1000获取毫秒级时间戳 106 | 107 | 108 | def get_lastdate(): 109 | """ 110 | 从API获得目前API有的最晚的日期。 111 | 112 | :return: 长度为8、格式为年月日的字符串，如"20201231"。 113 | """ 114 | url = f'http://huiyan.baidu.com/migration/lastdate.jsonp' 115 | response = requests.get(url) 116 | json_data_match = re.search(r'{.*}', response.text) 117 | if json_data_match: 118 | json_data_str = json_data_match.group() 119 | 120 | # Decode JSON string, automatically handling Unicode characters 121 | json_data = json.loads(json_data_str) 122 | return_value = json_data['data']['lastdate'] 123 | print(f"成功获取到API最晚日期：{return_value}") 124 | return return_value 125 | else: 126 | print('获取API最晚日期时失败') 127 | 128 | 129 | def get_historycurve(region: str, move_type: str): 130 | """ 131 | 从API获得一个区域（省或市）的迁入或迁出的迁徙规模指数。historycurve API会直接返回所有日期。存储文件到文件名。 132 | 133 | :param region: 行政区域编码，如300001。 134 | :param move_type: 'move_in' 或 'move_out' 135 | :return: 成功返回 True，失败返回 False 136 | """ 137 | # 注意：这个文件要覆写，因为每次抓到的可能不一样。不需要判断是否已存在文件。 138 | output_file = f'./data/{translation_table[region]}_{translation_table[move_type]}_{translation_table["historycurve"]}.json' 139 | 140 | print(f"正在获取" 141 | f' {translation_table[region]}' 142 | f' {translation_table[move_type]} 的' 143 | f' {translation_table["historycurve"]}') 144 | 145 | url = f"http://huiyan.baidu.com/migration/historycurve.jsonp?dt={Types.region[region]}&id={region}&type={move_type}" 146 | response = requests.get(url) 147 | json_data_match = re.search(r'{.*}', response.text) 148 | if json_data_match: 149 | json_data_str = json_data_match.group() 150 | 151 | # Decode JSON string, automatically handling Unicode characters 152 | json_data = json.loads(json_data_str) 153 | 154 | with open(output_file, 'w', encoding='utf-8') as f: 155 | json.dump(json_data, f, ensure_ascii=False, indent=2) 156 | print('成功') 157 | return True 158 | else: 159 | print('失败') 160 | return False 161 | 162 | 163 | # http://huiyan.baidu.com/migration/cityrank.jsonp? 164 | # dt=country&id=0&type=move_in&date=20240130&callback=jsonp_1706674779082_8488633 165 | def download_and_convert_jsonp(data_type: str, dt: str, id: str, move_type: str, date: str, callback: str): 166 | """ 167 | 从百度慧眼的API上获得数据并存到本地。 168 | 169 | :param data_type: 就是你要获取的信息类型，有且仅有下列几个值： 170 | lastdate，返回最后有数据的日期（昨天）； 171 | historycurve，返回从20190112到lastdate为止的迁徙规模指数； 172 | cityrank，返回迁入xx来源地（城市级别）； 173 | provincerank，返回xx来源地（省份级别）。 174 | :param dt: 级别。可选的值有：country，province，city。 175 | :param id: 哪里的数据（若dt为国家则不需要id）。参照"行政区划乡镇清单201910"表。级别要和上面的id对应。 176 | :param move_type: 迁入还是迁出。可选的值有：move_in, move_out。 177 | :param date: 要的日期，格式：八位数的年月日，如20240131。data_type为lastdate或historycurve时不需要这个参数。 178 | :param callback: 没什么用，只是为了确认返回值是我这次要的数据罢了。给个时间戳就行。 179 | :param output_file: 该文件要存到的文件名。 180 | :return: boolean 成功返回True，失败返回False 181 | """ 182 | # TODO: 如果要爬大量数据，搞多线程 183 | output_file = f'./data/{translation_table[id]}_' \ 184 | f'{translation_table[move_type]}_' \ 185 | f'{translation_table[data_type]}_' \ 186 | f'{date}.json' 187 | 188 | if os.path.exists(output_file): 189 | print("文件已存在") 190 | return False 191 | 192 | # Construct the full URL with query parameters 193 | url = f'http://huiyan.baidu.com/migration/{data_type}.jsonp?dt={dt}&id={id}&type={move_type}&date={date}&callback={callback}' 194 | 195 | response = requests.get(url) 196 | 197 | # Extract JSON data part using regular expression 198 | json_data_match = re.search(r'{.*}', response.text) 199 | if json_data_match: 200 | json_data_str = json_data_match.group() 201 | 202 | # Decode JSON string, automatically handling Unicode characters 203 | json_data = json.loads(json_data_str) 204 | 205 | # 如果要导出 CSV 文件，可以在这里操作json_data。可以修改下面的代码： 206 | # if json_data['errmsg'] == 'SUCCESS': 207 | # data = json_data['data']['list'] 208 | # file = pd.DataFrame({id: data}).T 209 | # csv_filename = f'./data/{translation_table[id]}_' \ 210 | # f'{translation_table[move_type]}_' \ 211 | # f'{translation_table[data_type]}_' \ 212 | # f'{date}.csv' 213 | # file.to_csv(csv_filename, encoding='utf-8') 214 | 215 | with open(output_file, 'w', encoding='utf-8') as f: 216 | json.dump(json_data, f, ensure_ascii=False, indent=2) 217 | 218 | print('成功') 219 | else: 220 | print('失败') 221 | 222 | 223 | def get_data(region: str, data_type: str, move_type: str, date: str): 224 | timestamp = get_timestamp() 225 | print(f"正在获取" 226 | f' {translation_table[region]}' 227 | f' {translation_table[move_type]} 的' 228 | f' {translation_table[data_type]}，日期为{date}') 229 | download_and_convert_jsonp( 230 | data_type=data_type, 231 | dt=Types.region[region], 232 | id=region, 233 | move_type=move_type, 234 | date=date, 235 | callback=timestamp 236 | ) 237 | 238 | 239 | def get_by_date(from_date, to_date, lastdate): 240 | # 将日期字符串转换为datetime对象 241 | from_date_dt = datetime.strptime(from_date, '%Y%m%d') 242 | to_date_dt = datetime.strptime(to_date, '%Y%m%d') 243 | lastdate_dt = datetime.strptime(lastdate, '%Y%m%d') 244 | 245 | print("正在检查日期输入合法性") 246 | 247 | # 检查from_date是否小于'20190112' 248 | earlydate = datetime(2019, 1, 12) 249 | if from_date_dt < earlydate: 250 | print("你的起始日期比API目前有的最早日期还早。已经将起始日期设置成API的最早日期，并尝试继续运行。") 251 | from_date_dt = earlydate 252 | 253 | # 检查to_date是否大于lastdate 254 | if to_date_dt > lastdate_dt: 255 | print("你的结束日期比API目前有的最晚日期还晚。已经将结束日期设置成API的最晚日期，并尝试继续运行。") 256 | to_date_dt = lastdate_dt 257 | 258 | # 检查输入合法性 259 | if from_date_dt > to_date_dt: 260 | print("你的起始日期需要比结束日期早。") 261 | return 262 | 263 | print("成功") 264 | 265 | # 转换为字符串，以便生成日期范围 266 | from_date = from_date_dt.strftime('%Y%m%d') 267 | to_date = to_date_dt.strftime('%Y%m%d') 268 | 269 | for region in Types.region.keys(): 270 | for move_type in Types.move_type: 271 | get_historycurve(region, move_type) # 获取他的迁徙规模指数 272 | 273 | for date in generate_date_range(from_date, to_date): # 日期 274 | for region in Types.region.keys(): 275 | for move_type in Types.move_type: 276 | for data_type in Types.data_type: 277 | get_data(region, data_type, move_type, date) 278 | print("完成") 279 | 280 | 281 | if __name__ == "__main__": 282 | # 检查文件夹是否存在 283 | if not os.path.exists('data'): 284 | # 如果不存在，创建文件夹 285 | os.makedirs('data') 286 | lastdate = get_lastdate() # 接口给到的最晚日期 287 | # 如果你需要修改起始和结束日期，请修改这里 288 | get_by_date('20240131', '20240131', lastdate) 289 | -------------------------------------------------------------------------------- /行政区划乡镇清单201910.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/baisebaoma/baiduqianxi/7e1a3e5f7b8d709fcc4348c2385e4b545b5f4e6a/行政区划乡镇清单201910.xlsx --------------------------------------------------------------------------------