python爬虫接单的方式有两种
一、接定制需求的单子
爬虫定制的需求其实很多，比如 “爬取某某电商网站的评论”，这类需求一般是按照爬取数据量的大小来收费，价格不会太高，正常500的样子。
常见的接单渠道有以下几种：
a） QQ群接单
QQ群接单因为没有中介抽成价格相对高一些，但是也容易出现客户跑路不给尾款的情况。以我多年的接单经验，建议大家写完程序之后留一个小BUG，防止客户不给尾款。
b） 猪八戒、程序员客栈等第三方平台
第三方担保平台，你需要入驻成为他们的技术员，优点是有平台担保，缺点是内卷严重，根本接不到单子。
c） 淘宝店铺
淘宝搜索“python爬虫代做”，联系店铺客服，申请成为他们的技术员。店铺老板会把你拉到技术员群里面，通过群里抢单的方式来接单。优点是单子多，价格也还ok，缺点是一旦出了纠纷，淘宝店铺只会维护客户的利益，有时候甚至出现了单子做完了，不给技术员钱的情况。
二、出售源码
不知道大家有没有发现，近两年IT行业内卷非常的严重，python代做这块也超级内卷，培训机构每年都向社会输出了大量的python工程师，python爬虫这块因为接单门槛很低受到了极大的冲击。
与其低价格去接爬虫的定制需求，还不如直接出售源码，实现薄利多销。比如“基于requests的电商爬虫程序”
这里给大家介绍一个比较靠谱的平台，大家可以百度搜索 “知行编程网”，入驻成为创作者之后，就可以在上面寄售源码
也可以直接访问知行编程网的官方网站
COMP6714 ASSIGNMENT 1DUE ON 20:59 29 NOV, 2019 (FRI)Q1. (25 marks)Consider the following pseudo code which performs list intersection based on the divideand-conquerparadigm. Note that the input lists are not necessarily sorted.Algorithm 1: Intersect(A, B)1 if ... then/* Deal with the boundary case */2 ...3 return ...4 else/* Recursively break down each list into two parts and recurse */5 ...6 return ...(1) Complete the above pseudo code. You can assume that you can invoke the followingmember methods on a List object L:• L.len returns the length of the list L.You can also use the usually indexing and slicing operation on the list (as inpython).(2) Think of a method to divide each input list into k sub-lists (k2) without changingthe main logic of the algorithm you implemented in the first part. You should beable to describe the only change succinctly.Q2. (25 marks)Consider the scenario of dynamic inverted index construction. Assume that t sub-indexes(each of M pages) will be created if one chooses the no-merge strategy.(1) Show that if the logarithmic merge strategy is used, it will result in at most dlog2 tesub-indexes.(2) Prove that the total I/O cost of the logarithmic merge is O(t · M · log2 t).12 DUE ON 20:59 29 NOV, 2019 (FRI)Q3. (25 marks)The following list of Rs and Ns represents relevant (R) and nonrelevant (N) returneddocuments in a ranked list of 20 documents retrieved in response to a query from a collectionof 10, 000 documents. The top of the ranked list is on the left of the list. This list shows 6relevant documents. Assume that there are 8 relevant documents in total in the collection.RRNNN NNNRN RNNNR NNNNR(Note that spaces above are just added to make the list easier to read)(1) What is the precision of the system on the top-20?(2) What is the F1 on the top-20?(3) What is/are the uninterpolated precision(s) of the system at 25% recall?(4) What is the interpolated precision at 33% recall?(5) Assume that these 20 documents are the complete result set of the system. Whatis the MAP for the query?Assume, now, instead, that the system returned the entire 10, 000 documents in a rankedlist, and these arCOMP6714代做、python程序语言代写、代做pythe the first 20 results returned.(6) What is the largest possible MAP that this system could have?(7) What is the smallest possible MAP that this system could have?(8) In a set of experiments, only the top-20 results are evaluated by hand. The resultin (5) is used to approximate the range (6) to (7). For this example, how large (inabsolute terms) can the error for the MAP be by calculating (5) instead of (6) and(7) for this query?Q4. (25 marks)Suppose we have a document collection with an extremely small vocabulary with only6 words w1, w2,...,w6. The following table shows the estimated background languagemodel p(w|C) using the whole collection of documents (2nd column) and the word countsfor document d1 (3rd column) and d2 (4th column), where c(w, di) is the count of word win document di. Let Q = {w1, w2, w3, w4, w5, w6} be a query.Word p(w|C) c(w, d1) c(w, d2)w1 0.800 2 7w2 0.100 3 1w3 0.025 1 1w4 0.025 2 1w5 0.025 2 0w6 0.025 0 0(1) Suppose we do not smooth the language model for d1 and d2. Compute the likelihoodof the query for both d1 and d2, i.e., p(Q|d1) and p(Q|d2) (Do not computethe log-likelihood. You should use the scientific notation (e.g., 0.0061 should be6.1 ⇥ 103)Which document would be ranked higher?COMP6714 ASSIGNMENT 1 3(2) Suppose we now smooth the language model for d1 and d2 using the Jelinek-Mercersmoothing method with= 0.8 (i.e., p(w|d) = ·pmle(w|Md)+(1)·pmle(w|Mc)).Recompute the likelihood of the query for both d1 and d2, i.e., p(Q|d1) and p(Q|d2)(Do not compute the log-likelihood. You should use the scientific notation) Whichdocument would be ranked higher?Submission InstructionsYou need to write your solutions to the questions in a pdf file named ass1.pdf. Youmust• include your name and student ID in the file, and• the file can be opened correctly on CSE machines.You need to show the key steps to get the full mark.Note: Collaboration is allowed. However, each person must independently write uphis/her own solution.You can then submit the file by give cs6714 ass1 ass1.pdf. The file size is limitedto 5MB.Late Penalty: -10% per day for the first two days, and -20% per day for the followingdays.转自：http://www.daixie0.com/contents/3/4354.htmlPython的应用方向1. 常规软件开发
Python支持函数式编程和OOP面向对象编程，能够承担任何种类软件的开发工作，因此常规的软件开发、脚本编写、网络编程等都属于标配能力。
2. 科学计算
随着NumPy，SciPy，Matplotlib，Enthoughtlibrarys等众多程序库的开发，Python越来越适合于做科学计算、绘制高质量的2D和3D图像。和科学计算领域最流行的商业软件Matlab相比，Python是一门通用的程序设计语言，比Matlab所采用的脚本语言的应用范围更广泛，有更多的程序库的支持。虽然Matlab中的许多高级功能和toolbox目前还是无法替代的，不过在日常的科研开发之中仍然有很多的工作是可以用Python代劳的。
3. 自动化运维
这几乎是Python应用的自留地，作为运维工程师首选的编程语言，Python在自动化运维方面已经深入人心，比如Saltstack和Ansible都是大名鼎鼎的自动化平台。
4. 云计算
开源云计算解决方案OpenStack就是基于Python开发的，搞云计算的同学都懂的。
5. WEB开发
基于Python的Web开发框架不要太多，比如耳熟能详的Django，还有Tornado，Flask。其中的Python+Django架构，应用范围非常广，开发速度非常快，学习门槛也很低，能够帮助你快速的搭建起可用的WEB服务。
6. 网络爬虫
也称网络蜘蛛，是大数据行业获取数据的核心工具。没有网络爬虫自动地、不分昼夜地、高智能地在互联网上爬取免费的数据，那些大数据相关的公司恐怕要少四分之三。能够编写网络爬虫的编程语言有不少，但Python绝对是其中的主流之一，其Scripy爬虫框架应用非常广泛。
7. 数据分析
在大量数据的基础上，结合科学计算、机器学习等技术，对数据进行清洗、去重、规格化和针对性的分析是大数据行业的基石。Python是数据分析的主流语言之一。
8. 人工智能
Python在人工智能大范畴领域内的机器学习、神经网络、深度学习等方面都是主流的编程语言，得到广泛的支持和应用。
参考：网页链接
