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Source channel @devilsbelow · Post #494 · Feb 2

🌐Weekly News Digest [ January 26 – February 1 ] That was a week of bribery charges and expansion of extraction activities across the whole continent. 💡Here are the key highlights: 🇩🇿 Algeria — Algeria’s minister for hydrocarbons visits Chad and Niger 🇨🇬 Congo — Two Norwegians and an oil company charged with bribing Congo’s president 🇨🇩 DR Congo — The leader of the AFC/M23 critisizes the US-DRC strategic agreement on access to minerals — More than 200 killed in a collapse at the AFC/M23-controlled Rubaya coltan mines in eastern DRC 🇱🇷 Liberia — Liberia ratified an agreement with the Luxembourg-based ArcelorMittal, extending the company’s rights to the Tokadeh iron deposit until 2075 🇲🇱 Mali — China’s largest mining company, Zijin buys Canadian company Allied Gold 🇲🇬 Madagascar — Madagascar has lifted its 2010 moratorium on new mining permits, except for gold 🇲🇿 Mozambique — TotalEnergies officially resume the Mozambique LNG project 🇳🇬 Nigeria — Nigeria’s President Bola Tinubu grants tax incentives to speed up Shell’s Bonga South West oil project — TotalEnergies sells its 10% stake in a Nigerian oil asset to a brand new local firm — A bribery trial of a former Nigerian minister of petroleum opens in London 🇸🇩 Sudan — Sudan seeks closer alignment with Saudi Arabia, including gold refinement 🇿🇲 Zambia — Zambia’s army carries out a full-fledged military operation around a gold deposit in the northwest of the country 🇿🇼 Zimbabwe — Illegal miners blamed for water supply disruptions in Zimbabwe's second largest city — Zimbabwe starts early implementation of increased royalties on gold mining #NewsDigest ➡️ Follow to stay informed - @devilsbelow

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djangoproject

@djangoproject · Post #118 · 08/08/2016, 11:44 AM

https://docs.python.org/3/library/multiprocessing.html multiprocessing is a package that supports spawning processes using an API similar to the threading module. The multiprocessing package offers both local and remote concurrency, effectively side-stepping the Global Interpreter Lock by using subprocesses instead of threads. Due to this, the multiprocessing module allows the programmer to fully leverage multiple processors on a given machine. It runs on both Unix and Windows. The #multiprocessing module also introduces #APIs which do not have analogs in the #threading#module. A prime example of this is the Pool object which offers a convenient means of parallelizing the execution of a function across multiple input values, distributing the input data across processes (data #parallelism). The following example demonstrates the common practice of defining such functions in a module so that child processes can successfully import that module. This basic example of data parallelism using Pool,