过去的二三年中，我一直关注的是机器翻译API在自动化翻译过程中的应用，包括采用CAT工具和Python编程语言来调用机器翻译API，然后再进行译后编辑，从而达到快速翻译的目的。

然而，我发现随着人工智能的发展，很多机器翻译也做了相应的调整，调用机器翻译api的样例也发生了变化，今天我特意把主流机器翻译api调用的Python代码汇聚于此，总共有七种方法，供大家学习参考。

一、Python调用Google机器翻译API

目前官方网站的调用代码没有之前的好用，所以我们依然采用以前的代码，只用安装requests, 而不用安装额外的Python包，前提是只要知道Google翻译的API密匙和翻译的语对方向即可，代码如下：

import requestsdef google_api(content):    url = "https://translation.googleapis.com/language/translate/v2"    data = {        'key': "YOUR_API_KEY", #你自己的api密钥        'source': "zh",        'target': "en",        'q': content,        'format': 'text'    }    headers = {'X-HTTP-Method-Override': 'GET'}    response = requests.post(url, data=data, headers=headers)    res = response.json()    text = res["data"]["translations"][0]["translatedText"]    return textprint("谷歌翻译:"+google_api("好好学习，天天向上！"))

二、Python调用百度机器翻译API

Python调用百度机器翻译API的代码有些变化，但前提是需要申请百度的api id和key，放到以下代码中：

import requestsimport randomimport jsonfrom hashlib import md5# Set your own appid/appkey.appid = 'YOUR APP ID'appkey = 'YOU APP KEY'# For list of language codes, please refer to `https://api.fanyi.baidu.com/doc/21`from_lang = 'en'to_lang =  'zh'endpoint = 'http://api.fanyi.baidu.com'path = '/api/trans/vip/translate'url = endpoint + pathquery = 'Hello World!'# Generate salt and signdef make_md5(s, encoding='utf-8'):    return md5(s.encode(encoding)).hexdigest()def baidu_api(query,from_lang,to_lang):    salt = random.randint(32768, 65536)    sign = make_md5(appid + query + str(salt) + appkey)    # Build request    headers = {'Content-Type': 'application/x-www-form-urlencoded'}    payload = {'appid': appid, 'q': query, 'from': from_lang, 'to': to_lang, 'salt': salt, 'sign': sign}    # Send request    r = requests.post(url, params=payload, headers=headers)    result = r.json()    # Show response    #print(json.dumps(result, indent=4, ensure_ascii=False))    return result["trans_result"][0]['dst']print(baidu_api(query,from_lang, to_lang))

三、Python调用小牛机器翻译API代码

以下代码是经过我改进后的代码，效率更高一些，供大家参考。小牛现在提供100万字符/月的额度，大家可以申请试用。

import jsonimport requestsapikey="YOUR_API_KEY"def translate(sentence, src_lan, tgt_lan):    url = 'http://api.niutrans.com/NiuTransServer/translation?'    data = {"from": src_lan, "to": tgt_lan, "apikey": apikey, "src_text": sentence}    res = requests.post(url, data = data)    res_dict = json.loads(res.text)    if "tgt_text" in res_dict:        result = res_dict['tgt_text']    else:        result = res    return resultif __name__ == "__main__":    while True:        line = input("请输入要翻译的文本：")        try:            trans = translate(line, 'auto', 'en')            print(trans+"\n---------")        except Exception as exc:            print(exc)

四、Python调用同花顺机器翻译api

之前我已经写出采用Python调用同花顺机器翻译api来翻译字幕的代码，详情如下：

import json,os,sysimport requestsimport easygui as g# appid = '你申请的id'# appkey = '你申请的key'# 解说打包报错问题os.environ['REQUESTS_CA_BUNDLE'] =  os.path.join(os.path.dirname(sys.argv[0]), 'cacert.pem')def get_key():"""读取本地appid.txt，获取id和key并生成字典"""    dic={}    with open("appid.txt","r",encoding="utf-8") as f:        lines=[line.strip() for line in f.readlines()]        for line in lines:            ls=line.split("=")            dic[ls[0].strip()]=ls[1].strip()    return dicdef getToken():"因为用同花顺的API时要校验token，由于token只有24小时的有效期，因此每次都要调用一下，以防过期。本函数获取最新的token"    tokenUrl = 'https://b2b-api.10jqka.com.cn/gateway/service-mana/app/login-appkey'    param = {}    param['appId'] = appid    param['appSecret'] = appkey    authResult = requests.post(tokenUrl, data=param)    authResult = authResult.content    res = json.loads(authResult)    access_token = ''    if 0 == res['flag']:        access_token = res['data']['access_token']    return access_tokendef translate(texts, token):"调用同花顺机器翻译API函数，注意这里是英文翻译成中文，如果要中文翻译成英文要修改【param['from']】为zh，【param['to'] 】为en"    ls=[]    if '' == token:        return    param = {}    param['app_id'] = appid    param['from'] = "en"    param['to'] = 'zh'    param['domain'] = 'default'    param['text'] = json.dumps(texts)    headers = {"Content-Type": "application/x-www-form-urlencoded; charset=UTF-8", "open-authorization": "Bearer" + token}    url = 'https://b2b-api.10jqka.com.cn/gateway/arsenal/machineTranslation/batch/get/result'    response = requests.post(url, headers=headers, data=param)    Ret = response.content    res = json.loads(Ret)    if 0 == res['status_code']:        res = res['data']    for rst in res['trans_result']:        ls.append(rst['dst'])    return lsdef read_srt(file):"读取字幕文件，生成字幕序号、时间和字幕内容的列表"    with open(file, "r", encoding = "utf-8-sig") as f:        lines=[line.strip() for line in f.readlines()]    max_line=len(lines)    if max_line<=600:        texts=lines[2:max_line:4]        times=lines[1:max_line:4]        nums=lines[:max_line:4]    else:        g.msgbox("字幕文件超过150行！请更换文件。")    return nums,times,textsdef add_to_srt(nums,times,texts,trans):"生成新的字幕文件，把译文也添加上。"    final_list=[]    for (num,time,text,tran) in zip(nums,times,texts,trans):        new_line = num + "\n"+ time + "\n" + text + "\n" + tran +"\n\n"        final_list.append(new_line)    with open(srt.replace(".srt", "_new.srt"), "wt", encoding= "utf-8-sig") as f:        f.write("".join(final_list))        print("done!")        if __name__ == '__main__':    d=get_key()    appid=d["id"]    appkey=d["key"]    title='请打开字幕文件'    srt=g.fileopenbox(default='*.srt')    nums,times,texts=read_srt(srt)    token = getToken() #token有效期为24小时，请在应用程序中做好定时获取操作，避免token失效    trans=translate(texts, token)    add_to_srt(nums,times,texts,trans)    g.msgbox("字幕文件已经翻译成功，请在字幕所在目录查看。")

五、Python调用彩云 小译机器翻译api

彩云这个小而美的机器翻译一直很低调，翻译的速度和质量都还不错。以下是相关的样例代码：

import requestsimport json url = "http://api.interpreter.caiyunai.com/v1/translator"token = "你的令牌" #这里填写你自己的令牌 payload = {        #"source" : ["Where there is a will, there is a way.",                      #"ColorfulClouds Weather is the best weather service."],        "source" : "Where there is a will, there is a way.",        "trans_type" : "en2zh",        "request_id" : "demo",        } headers = {        'content-type': "application/txt",        'x-authorization': "token " + token,} response = requests.request("POST", url, data=json.dumps(payload), headers=headers) #print(response.text)resp = json.loads(response.text)['target']print(resp)

六、Python调用阿里云机器翻译api

阿里云机器翻译api的调用比较繁琐，申请过程也较复杂，其翻译质量倒时一般，大家可以有选择地使用以下代码：

from alibabacloud_alimt20181012.client import Client as alimt20181012Clientfrom alibabacloud_tea_openapi import models as open_api_modelsfrom alibabacloud_alimt20181012 import models as alimt_20181012_modelsfrom alibabacloud_tea_util import models as util_modelsACCESS_KEY_ID = 【Access_key_id>】#这里把尖括号里的 Acess_key_id和Acess_key_secret分别修改为自己申请的通用翻译apiACCESS_KEY_SECRET = 【Access_key_secret】def create_client(    access_key_id: str,    access_key_secret: str,) -> alimt20181012Client:    config = open_api_models.Config(        access_key_id=access_key_id,        access_key_secret=access_key_secret    )    config.endpoint = f'mt.cn-hangzhou.aliyuncs.com'    return alimt20181012Client(config)def translate(text):    client = create_client(ACCESS_KEY_ID, ACCESS_KEY_SECRET)    translate_general_request = alimt_20181012_models.TranslateGeneralRequest(        format_type='text',        source_language='en',        target_language='zh',        source_text=text,        scene='general'    )    runtime = util_models.RuntimeOptions()    resp = client.translate_general_with_options(translate_general_request, runtime)    return resp.body.data.__dict__['translated']print(translate("Rome is not built in a day."))

七、利用ChatGPT来翻译

ChatGPT也可以用于翻译，只要我们给它发出指令即可。代码如下：

import openaiopenai.api_base = "https://api.openai.com/v1"openai.api_key = "YOUR_API_KEY"model_engine_id = "text-davinci-003"while True:    prompt = input("Q：")    completions = openai.Completion.create(        engine=model_engine_id,        prompt="Translate the following sentences into Chinese:"+prompt,        max_tokens=800,    )    message = completions.choices[0].text.strip()    print("A:",message,end="\n")

八、学后反思

本文总结了六大机器翻译api的调用方法，供大家参考。英译汉，个人推荐的是Google翻译。汉译英推荐百度翻译、小牛翻译等。译文润色可以调用ChatGPT帮忙。

下一步，我将努力整合一下更多的机器翻译api的调用方法，添加在一起，也可以写一个调用包，以方便大家使用。

来源地址：https://blog.csdn.net/henanlion/article/details/131967430